DOI： 10.26434/chemrxiv-2023-3mwbd

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Language：Japanese   Publisher：(公社)日本生物工学会  

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Publishing type：Research paper (scientific journal)   Publisher：MDPI AG  

Bayesian optimization (BO)-assisted screening was applied to identify improved reaction conditions toward a hundred-gram scale-up synthesis of 2,3,7,8-tetrathiaspiro[4.4]nonane (1), a key synthetic intermediate of 2,2-bis(mercaptomethyl)propane-1,3-dithiol [tetramercaptan pentaerythritol]. Starting from the initial training set (ITS) consisting of six trials sampled by random screening for BO, suitable parameters were predicted (78% conversion yield of spiro-dithiolane 1) within seven experiments. Moreover, BO-assisted screening with the ITS selected by Latin hypercube sampling (LHS) further improved the yield of 1 to 89% within the eight trials. The established conditions were confirmed to be satisfactory for a hundred grams scale-up synthesis of 1.

DOI： 10.3390/molecules28135180

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Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

Abstract

We aimed to identify combinations of clinical factors that predict heart failure (HF) onset using a novel limitless-arity multiple-testing procedure (LAMP). We also determined if increases in numbers of predictive combinations of factors increases the probability of developing HF. We recruited people without HF who received health check-ups in 2010, who were followed annually for 4 years. Using 32,547 people, LAMP was performed to identify combinations of factors of fewer than four factors that could predict the onset of HF. The ability of the method to predict the probability of HF onset based on the number of matching predictive combinations of factors was determined in 275,658 people. We identified 549 combinations of factors for the onset of HF. Then we classified 275,658 people into six groups who had 0, 1–50, 51–100, 101–150, 151–200 or 201–250 predictive combinations of factors for the onset of HF. We found that the probability of HF progressively increased as the number of predictive combinations of factors increased. We identified combinations of variables that predict HF onset. An increased number of matching predictive combinations for the onset of HF increased the probability of HF onset.

DOI： 10.1038/s41598-023-31600-0

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Other Link： https://www.nature.com/articles/s41598-023-31600-0

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1021/acs.oprd.2c00267

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Publishing type：Research paper (scientific journal)  

DOI： 10.1038/s42004-022-00764-7

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Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

DOI： 10.1007/s10115-022-01765-7

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Other Link： https://link.springer.com/article/10.1007/s10115-022-01765-7/fulltext.html

Publishing type：Research paper (scientific journal)   Publisher：Frontiers Media SA  

The emergence of bacteria that are resistant to antibiotics is common in areas where antibiotics are used widely. The current standard procedure for detecting bacterial drug resistance is based on bacterial growth under antibiotic treatments. Here we describe the morphological changes in enoxacin-resistant Escherichia coli cells and the computational method used to identify these resistant cells in transmission electron microscopy (TEM) images without using antibiotics. Our approach was to create patches from TEM images of enoxacin-sensitive and enoxacin-resistant E. coli strains, use a convolutional neural network for patch classification, and identify the strains on the basis of the classification results. The proposed method was highly accurate in classifying cells, achieving an accuracy rate of 0.94. Using a gradient-weighted class activation mapping to visualize the region of interest, enoxacin-resistant and enoxacin-sensitive cells were characterized by comparing differences in the envelope. Moreover, Pearson’s correlation coefficients suggested that four genes, including lpp, the gene encoding the major outer membrane lipoprotein, were strongly associated with the image features of enoxacin-resistant cells.

DOI： 10.3389/fmicb.2022.839718

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Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.commatsci.2022.111207

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1039/d2cc00124a

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Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

<title>Abstract</title>High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SARS-CoV-2. However, RT-PCR requires the extraction of viral RNA from clinical specimens to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity by using nanopores together with artificial intelligence, a relatively simple procedure that does not require RNA extraction. Our final platform, which we call the artificially intelligent nanopore, consists of machine learning software on a server, a portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. We show that artificially intelligent nanopores are successful in accurately identifying four types of coronaviruses similar in size, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2. Detection of SARS-CoV-2 in saliva specimen is achieved with a sensitivity of 90% and specificity of 96% with a 5-minute measurement.

DOI： 10.1038/s41467-021-24001-2

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Other Link： http://www.nature.com/articles/s41467-021-24001-2

Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

<title>Abstract</title>Controlling the fast electrophoresis of nano-objects in solid-state nanopores is a critical issue for achieving electrical analysis of single-particles by ionic current. In particular, it is crucial to slow-down the translocation dynamics of nanoparticles. We herein report that a focused electric field and associated water flow in a surround-gate nanopore can be used to trap and manipulate a nanoscale object. We fine-control the electroosmosis-induced water flow by modulating the wall surface potential via gate voltage. We find that a nanoparticle can be captured in the vicinity of the conduit by balancing the counteracting electrophoretic and hydrodynamic drag forces. By creating a subtle force imbalance, in addition, we also demonstrate a gate-controllable motion of single-particles moving at an extremely slow speed of several tens of nanometers per second. The present method may be useful in single-molecule detection by solid-state nanopores and nanochannels.

DOI： 10.1038/s43246-021-00132-3

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Other Link： http://www.nature.com/articles/s43246-021-00132-3

Publishing type：Research paper (scientific journal)   Publisher：American Chemical Society (ACS)  

DOI： 10.1021/acs.joc.1c01242

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Publishing type：Research paper (scientific journal)   Publisher：Wiley  

DOI： 10.1002/smtd.202100542

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Other Link： https://onlinelibrary.wiley.com/doi/full-xml/10.1002/smtd.202100542

Publishing type：Research paper (scientific journal)   Publisher：MDPI AG  

A better understanding of the microstructure–property relationship can be achieved by sampling and analyzing a microstructure leading to a desired material property. During the simulation of filled rubber, this approach includes extracting common aggregates from a complex filler morphology consisting of hundreds of filler particles. However, a method for extracting a core structure that determines the rubber mechanical properties has not been established yet. In this study, we analyzed complex filler morphologies that generated extremely high stress using two machine learning techniques. First, filler morphology was quantified by persistent homology and then vectorized using persistence image as the input data. After that, a binary classification model involving logistic regression analysis was developed by training a dataset consisting of the vectorized morphology and stress-based class. The filler aggregates contributing to the desired mechanical properties were extracted based on the trained regression coefficients. Second, a convolutional neural network was employed to establish a classification model by training a dataset containing the imaged filler morphology and class. The aggregates strongly contributing to stress generation were extracted by a kernel. The aggregates extracted by both models were compared, and their shapes and distributions producing high stress levels were discussed. Finally, we confirmed the effects of the extracted aggregates on the mechanical property, namely the validity of the proposed method for extracting stress-contributing fillers, by performing coarse-grained molecular dynamics simulations.

DOI： 10.3390/polym13162683

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Publishing type：Research paper (scientific journal)   Publisher：Wiley  

DOI： 10.1002/smtd.202100191

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Other Link： https://onlinelibrary.wiley.com/doi/full-xml/10.1002/smtd.202100191

Publishing type：Research paper (scientific journal)   Publisher：IOS Press  

We propose novel approaches for classification from positive and unlabeled data (PUC) based on maximum likelihood principle. These are particularly suited to measurement tasks in which the class prior of the target object in each measurement is unknown and significantly different from the class prior used for training, while the likelihood function representing the observation process is invariant over the training and measurement stages. Our PUCs effectively work without estimating the class priors of the unlabeled objects. First, we present a PUC approach called Naive Likelihood PUC (NL-PUC) using the maximum likelihood principle in a nontrivial but rather straightforward manner. The extended version called Enhanced Likelihood PUC (EL-PUC) employs an algorithm iteratively improving the likelihood estimation of the positive class. This is advantageous when the availability of the labeled positive data is limited. These characteristics are demonstrated both theoretically and experimentally. Moreover, the practicality of our PUCs is demonstrated in a real application to single molecule measurement.

DOI： 10.3233/ida-194980

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Language：English   Publishing type：Research paper (scientific journal)  

Reversibly photoswitchable fluorescent proteins (RSFPs) are a class of fluorescent proteins whose fluorescence can be turned on and off by light irradiation. RSFPs have become essential tools for super-resolution (SR) imaging. Because most SR imaging techniques require high power density illumination, mitigating phototoxicity in cells due to intense light irradiation has been a challenge. Although we previously developed a RSFP named Kohinoor to achieve SR imaging with low phototoxicity, the photoproperties were insufficient to move a step further to explore the cellular dynamics by SR imaging. Here, we show an improved version of RSFP, Kohinoor2.0, which is suitable for SR imaging of cellular processes. Kohinoor2.0 shows a 2.6-fold higher fluorescence intensity, 2.5-fold faster chromophore maturation, and 1.5-fold faster off-switching than Kohinoor. The analysis of the pH-dependence of the visible absorption band revealed that Kohinoor2.0 and Kohinoor were in equilibria among multiple fluorescently-bright and dark states, with the mutations introduced into Kohinoor2.0 bringing about a higher stabilization of the fluorescently-bright states compared to Kohinoor. Using Kohinoor2.0 with our SR imaging technique, SPoD-OnSPAN, we conducted 4-h time-lapse SR imaging of an actin filament network in mammalian cells with a total acquisition time of 480 s without a noticeable indication of phototoxicity. Furthermore, we demonstrated the SR imaging of mitochondria dynamics at a time resolution of 0.5 s, in which the fusion and fission processes were clearly visualized. Thus, Kohinoor2.0 is shown to be an invaluable RSFP for the SR imaging of cellular dynamics.

DOI： 10.1093/jmicro/dfab001

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1109/JSEN.2020.3016678

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1021/acs.analchem.0c04353

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Authorship：Last author   Publishing type：Part of collection (book)   Publisher：Springer International Publishing  

DOI： 10.1007/978-3-030-75015-2_5

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Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr2109.html#abs-2109-14198

Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

DOI： 10.1109/ICDM51629.2021.00073

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2021.html#TingWWZ21

Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s10618-021-00785-1

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Publishing type：Research paper (scientific journal)   Publisher：Royal Society of Chemistry (RSC)  

A highly efficient synthesis of α-ketiminophosphonates has been established for the electrochemical oxidation of α-amino phosphonates with the utilization of machine-learning-assisted simultaneous multiparameter screening.

DOI： 10.1039/d1gc01583d

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Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

<title>Abstract</title>
A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a polymer-integrated low thickness-to-diameter aspect ratio pore and machine learning-driven resistive pulse analyses. A high-spatiotemporal resolution of this electrical sensor enabled to observe galvanotactic response intrinsic to the microbes during their translocation. We demonstrated discrimination of the cellular motility via signal pattern classifications in a high-dimensional feature space. As the detection-to-decision can be completed within milliseconds, the present technique may be used for real-time screening of pathogenic bacteria for environmental and medical applications.

DOI： 10.1038/s41598-020-72508-3

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Other Link： http://www.nature.com/articles/s41598-020-72508-3

Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

<title>Abstract</title>Molecular dynamics (MD) simulation is used to analyze the mechanical properties of polymerized and nanoscale filled rubber. Unfortunately, the computation time for a simulation can require several months’ computing power, because the interactions of thousands of filler particles must be calculated. To alleviate this problem, we introduce a surrogate convolutional neural network model to achieve faster and more accurate predictions. The major difficulty when employing machine-learning-based surrogate models is the shortage of training data, contributing to the huge simulation costs. To derive a highly accurate surrogate model using only a small amount of training data, we increase the number of training instances by dividing the large-scale simulation results into 3D images of middle-scale filler morphologies and corresponding regional stresses. The images include fringe regions to reflect the influence of the filler constituents outside the core regions. The resultant surrogate model provides higher prediction accuracy than that trained only by images of the entire region. Afterwards, we extract the fillers that dominate the mechanical properties using the surrogate model and we confirm their validity using MD.

DOI： 10.1038/s41598-020-75038-0

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Other Link： https://www.nature.com/articles/s41598-020-75038-0

Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

DOI： 10.1038/s41598-020-68236-3

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Other Link： http://www.nature.com/articles/s41598-020-68236-3

Language：English   Publishing type：Research paper (scientific journal)  

The variability of bioparticles remains a key barrier to realizing the competent potential of nanoscale detection into a digital diagnosis of an extraneous object that causes an infectious disease. Here, we report label-free virus identification based on machine-learning classification. Single virus particles were detected using nanopores, and resistive-pulse waveforms were analyzed multilaterally using artificial intelligence. In the discrimination, over 99% accuracy for five different virus species was demonstrated. This advance is accessed through the classification of virus-derived ionic current signal patterns reflecting their intrinsic physical properties in a high-dimensional feature space. Moreover, consideration of viral similarity based on the accuracies indicates the contributing factors in the recognitions. The present findings offer the prospect of a novel surveillance system applicable to detection of multiple viruses including new strains.

DOI： 10.1021/acssensors.0c01564

PubMed

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Publisher：Research Square  

<title>Abstract</title>
High-throughput, high-accuracy detection of emerging viruses allows for pandemic prevention and control. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is used to diagnose the presence of SARS-CoV-2. The principle of the test is to detect RNA in the virus using a pair of primers that specifically binds to the base sequence of the viral RNA. However, RT-PCR is a sophisticated technique requiring a time-consuming pretreatment procedure for extracting viral RNA from clinical specimens and to obtain<bold> </bold>high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity using artificial intelligent nanopores utilizing a simple procedure that does not require RNA extraction. Artificial intelligent nanopore platform consists of machine learning software on the servers, portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. Here we show that the artificial intelligent nanopores are successful in accurate identification of four types of coronaviruses, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2, which are usually extremely difficult to detect. The positive/negative diagnostics of the new coronavirus is achieved with a sensitivity of 95 % and specificity of 92 % with a 5-minute diagnosis. The platform enables high throughput diagnostics with low false negatives for the novel coronavirus.

DOI： 10.21203/rs.3.rs-97218/v1

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Other Link： https://www.researchsquare.com/article/rs-97218/v1.html

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Royal Society of Chemistry  

DOI： 10.1039/d0cc90423f

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Publishing type：Research paper (scientific journal)   Publisher：American Chemical Society (ACS)  

DOI： 10.1021/acssensors.0c00845

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Language：English   Publishing type：Research paper (scientific journal)  

PURPOSE: Glucose intolerance (GI), defined as either prediabetes or diabetes, promotes cardiovascular events in patients with myocardial infarction (MI). Using the pooled clinical data from patients with MI and GI in the completed ABC and PPAR trials, we aimed to identify their clinical risk factors for cardiovascular events. METHODS: Using the limitless-arity multiple testing procedure, an artificial intelligence (AI)-based data mining method, we analyzed 415,328 combinations of < 4 clinical parameters. RESULTS: We identified 242 combinations that predicted the occurrence of hospitalization for (1) percutaneous coronary intervention for stable angina, (2) non-fatal MI, (3) worsening of heart failure (HF), and (4) all causes, and we analyzed combinations in 1476 patients. Among these parameters, the use of proton pump inhibitors (PPIs) or plasma glucose levels > 200 mg/dl after 2 h of a 75 g oral glucose tolerance test were linked to the coronary events of (1, 2). Plasma BNP levels > 200 pg/dl were linked to coronary and cardiac events of (1, 2, 3). Diuretics use, advanced age, and lack of anti-dyslipidemia drugs were linked to cardiovascular events of (1, 3). All of these factors were linked to (4). Importantly, each finding was verified by independently drawn Kaplan-Meier curves, indicating that the determined factors accurately affected cardiovascular events. CONCLUSIONS: In most previous MI patients with GI, progression of GI, PPI use, or high plasma BNP levels were linked to the occurrence of coronary stenosis or recurrent MI. We emphasize that use of AI may comprehensively uncover the hidden risk factors for cardiovascular events.

DOI： 10.1007/s10557-020-06987-x

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Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr2009.html#abs-2009-12196

Publishing type：Part of collection (book)  

DOI： 10.1007/978-1-0716-0532-5_11

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s10618-019-00660-0

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Publishing type：Research paper (scientific journal)  

DOI： 10.1039/c9cc08526b

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PubMed

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Publishing type：Research paper (international conference proceedings)   Publisher：ACM  

DOI： 10.1145/3394486.3403062

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Other Link： https://dblp.uni-trier.de/db/conf/kdd/kdd2020.html#TingXWZ20

Publishing type：Research paper (scientific journal)  

Gas identification is one of the most important functions of a gas sensor system. To identify gas species from sensing signals without gas flow control such as pumps or mass flow controllers, it is necessary to extract decisive dynamic features from complex sensing signals due to uncontrolled airflow. For that purpose, various analysis methods using system identification techniques have been proposed, whereas a method that is not affected by a gas input pattern has been demanded to enhance the robustness of gas identification. Here we develop a novel gas identification protocol based on a transfer function ratio (TFR) that is intrinsically independent of a gas input pattern. By combining the protocol with MEMS-based sensors—Membrane-type Surface stress Sensors (MSS), we have realized gas identification with a free-hand measurement, in which one can simply hold a small sensor chip near samples. From sensing signals obtained through the free-hand measurement, we have developed highly accurate machine learning models that can identify odors of spices and herbs as well as solvent vapors. Since no bulky gas flow control units are required, this protocol will expand the applicability of gas sensors to portable electronics, leading to practical artificial olfaction.

DOI： 10.1038/s41598-019-46164-1

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：NATURE PUBLISHING GROUP  

Gas identification is one of the most important functions of a gas sensor system. To identify gas species from sensing signals without gas flow control such as pumps or mass flow controllers, it is necessary to extract decisive dynamic features from complex sensing signals due to uncontrolled airflow. For that purpose, various analysis methods using system identification techniques have been proposed, whereas a method that is not affected by a gas input pattern has been demanded to enhance the robustness of gas identification. Here we develop a novel gas identification protocol based on a transfer function ratio (TFR) that is intrinsically independent of a gas input pattern. By combining the protocol with MEMS-based sensors-Membrane-type Surface stress Sensors (MSS), we have realized gas identification with a free-hand measurement, in which one can simply hold a small sensor chip near samples. From sensing signals obtained through the free-hand measurement, we have developed highly accurate machine learning models that can identify odors of spices and herbs as well as solvent vapors. Since no bulky gas flow control units are required, this protocol will expand the applicability of gas sensors to portable electronics, leading to practical artificial olfaction.

DOI： 10.1038/s41598-019-46164-1

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1021/acsomega.9b00946

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1021/acs.jpcc.9b03908

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Publishing type：Research paper (scientific journal)  

DOI： 10.1039/c8me00097b

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Language：Japanese   Publisher：The Japan Society of Applied Physics  

DOI： 10.11470/jsapmeeting.2019.1.0_2513

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1039/C8NR09042D

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Publishing type：Research paper (international conference proceedings)  

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Publishing type：Research paper (international conference proceedings)   Publisher：PMLR  

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Other Link： https://dblp.uni-trier.de/rec/conf/acml/2019

Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/ISOEN.2019.8823511

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Other Link： https://dblp.uni-trier.de/db/conf/isoen/isoen2019.html#ShunoriYWHNNOOW19

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1902.html#abs-1902-03402

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1039/C8LC01371C

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Publishing type：Research paper (scientific journal)  

DOI： 10.1039/C8NR08632J

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DOI： 10.1007/s10994-018-5737-x

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Publishing type：Research paper (scientific journal)  

DOI： 10.7717/peerj-cs.169

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Other Link： https://dblp.uni-trier.de/db/journals/peerj-cs/peerj-cs5.html#BlobaumJWSS19

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Publishing type：Research paper (scientific journal)  

DOI： 10.1021/ACSSENSORS.9B00113

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1907.html#abs-1907-01104

Language：English   Publishing type：Research paper (scientific journal)  

Immunosensing is a bioanalytical technique capable of selective detections of pathogens by utilizing highly specific and strong intermolecular interactions between recognition probes and antigens. Here, we exploited the molecular mechanism in artificial nanopores for selective single-virus identifications. We designed hemagglutinin antibody mimicking oligopeptides with a weak affinity to influenza A virus. By functionalizing the pore wall surface with the synthetic peptides, we rendered specificity to virion-nanopore interactions. The ligand binding thereof was found to perturb translocation dynamics of specific viruses in the nanochannel, which facilitated digital typing of influenza by the resistive pulse bluntness. As amino acid sequence degrees of freedom can potentially offer variety of recognition ability to the molecular probes, this peptide nanopore approach can be used as a versatile immunosensor with single-particle sensitivity that promises wide applications in bioanalysis including bacterial and viral screening to infectious disease diagnosis.

DOI： 10.1021/jacs.8b10854

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Language：English   Publishing type：Research paper (scientific journal)  

Rapid diagnosis of flu before symptom onsets can revolutionize our health through diminishing a risk for serious complication as well as preventing infectious disease outbreak. Sensor sensitivity and selectivity are key to accomplish this goal as the number of virus is quite small at the early stage of infection. Here we report on label-free electrical diagnostics of influenza based on nanopore analytics that distinguishes individual virions by their distinct physical features. We accomplish selective resistive-pulse sensing of single flu virus having negative surface charges in a physiological media by exploiting electroosmotic flow to filter contaminants at the Si3N4 pore orifice. We demonstrate identifications of allotypes with 68% accuracy at the single-virus level via pattern classifications of the ionic current signatures. We also show that this discriminability becomes >95% under a binomial distribution theorem by ensembling the pulse data of >20 virions. This simple mechanism is versatile for point-of-care tests of a wide range of flu types.

DOI： 10.1038/s41598-018-34665-4

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Language：Japanese   Publisher：The Japan Society of Applied Physics  

DOI： 10.11470/jsapmeeting.2018.2.0_2648

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Nanomechanical sensors - emerging chemical sensors which detect changes in mechanical properties caused by gas sorption - have been attracting much attention owing to their high sensitivity and versatility. In the data analysis of sensing signals, empirically extracted signal features have been commonly employed to identify the gas species. Such an empiric approach cannot be optimized further without a solid guideline, resulting in a limited identification performance. Therefore, a new analytical protocol based on intrinsic physical properties of a target gas and a receptor material has been highly demanded. In this study, we have developed a parameter estimation protocol based on a theoretical model for a cantilever-type nanomechanical sensor coated with a viscoelastic material. This protocol provides a practical estimation method for intrinsic parameters, which can be used for gas identification. As a demonstration of gas identification based on intrinsic parameters, we focused on the time constant for gas diffusion τs, which reflects the physicochemical interaction between gas species and a receptor material. Based on τs estimated from different receptor materials, we succeeded in the identification of solvent vapors. This parameter estimation protocol not only enables the gas identification based on the intrinsic property of target gases, but also provides a scientific guideline for the selection and optimization of receptor materials for nanomechanical sensors.

DOI： 10.1063/1.5036686

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：AMER INST PHYSICS  

Nanomechanical sensors-emerging chemical sensors which detect changes in mechanical properties caused by gas sorption-have been attracting much attention owing to their high sensitivity and versatility. In the data analysis of sensing signals, empirically extracted signal features have been commonly employed to identify the gas species. Such an empiric approach cannot be optimized further without a solid guideline, resulting in a limited identification performance. Therefore, a new analytical protocol based on intrinsic physical properties of a target gas and a receptor material has been highly demanded. In this study, we have developed a parameter estimation protocol based on a theoretical model for a cantilever-type nanomechanical sensor coated with a viscoelastic material. This protocol provides a practical estimation method for intrinsic parameters, which can be used for gas identification. As a demonstration of gas identification based on intrinsic parameters, we focused on the time constant for gas diffusion tau(s), which reflects the physicochemical interaction between gas species and a receptor material. Based on tau(s) estimated from different receptor materials, we succeeded in the identification of solvent vapors. This parameter estimation protocol not only enables the gas identification based on the intrinsic property of target gases, but also provides a scientific guideline for the selection and optimization of receptor materials for nanomechanical sensors. (C) 2018 Author(s).

DOI： 10.1063/1.5036686

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DOI： 10.1093/jmicro/dfy004

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1021/acs.analchem.7b04950

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1802.html#abs-1802-06698

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1812.html#abs-1812-03395

Publishing type：Research paper (international conference proceedings)   Publisher：SIAM  

DOI： 10.1137/1.9781611975321.64

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Other Link： https://dblp.uni-trier.de/db/conf/sdm/sdm2018.html#KisamoriWKF18

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DOI： 10.1021/ACSAMI.8B11819

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DOI： 10.1007/s10994-017-5693-x

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Publishing type：Research paper (international conference proceedings)   Publisher：PMLR  

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Other Link： https://dblp.uni-trier.de/rec/conf/aistats/2018

Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDM.2018.00015

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2018.html#TingAW18

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Publishing type：Research paper (scientific journal)  

DOI： 10.1021/ACSSENSORS.8B01214

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Language：English   Publishing type：Research paper (scientific journal)  

Conventional concepts of resistive pulse analysis is to discriminate particles in liquid by the difference in their size through comparing the amount of ionic current blockage. In sharp contrast, we herein report a proof-of-concept demonstration of the shape sensing capability of solid-state pore sensors by leveraging the synergy between nanopore technology and machine learning. We found ionic current spikes of similar patterns for two bacteria reflecting the closely resembled morphology and size in an ultra-low thickness-to-diameter aspect-ratio pore. We examined the feasibility of a machine learning strategy to pattern-analyse the sub-nanoampere corrugations in each ionic current waveform and identify characteristic electrical signatures signifying nanoscopic differences in the microbial shape, thereby demonstrating discrimination of single-bacterial cells with accuracy up to 90%. This data-analytics-driven microporescopy capability opens new applications of resistive pulse analyses for screening viruses and bacteria by their unique morphologies at a single-particle level.

DOI： 10.1038/s41598-017-17443-6

PubMed

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s10115-017-1046-0

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s10994-016-5586-4

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Publishing type：Research paper (international conference proceedings)  

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Other Link： https://dblp.uni-trier.de/rec/conf/esann/2017

Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

DOI： 10.1109/DSAA.2017.28

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Other Link： https://dblp.uni-trier.de/db/conf/dsaa/dsaa2017.html#WashioIY17

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1103/PhysRevA.94.042341

Web of Science

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1021/acsnano.5b05906

Web of Science

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-319-31753-3

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-319-31750-2

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Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1610.html#BlobaumWS16

Language：English   Publisher：The Japanese Society of Toxicology  

Structured regularization is a mathematical technique which incorporates prior structural knowledge among variables into regression analysis to make a sparse estimation reflecting relationships among them. Abundance of structural information in biology, such as pathways formed by genes, transcripts, and proteins, especially suits well its application. Previously, we reported on the first application of latent group Lasso, a group-based regularization method, in toxicogenomics, with genes regulated by the same transcription factor treated as a group. We revealed that it achieved good predictive performances comparable to Lasso and allowed us to discuss mechanisms behind liver weight gain in rats based on selected groups. Latent group Lasso, however, does not lead to a sparse estimation, due to large group sizes in our analytical setting. In this study, we applied graph-based regularization methods, generalized fused Lasso and graph Lasso, for the same data, with regulatory networks formed by transcription factors and their downstream genes as a graph. These methods are expected to make a sparser estimation since they select variables based on edges. Comparisons showed that graph Lasso generated an accurate, biologically relevant and sparse model that could not have been possible with latent group Lasso and generalized fused Lasso.

DOI： 10.2131/fts.3.39

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Other Link： http://search.jamas.or.jp/link/ui/2017038113

Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s41060-016-0035-9

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Publishing type：Research paper (scientific journal)  

DOI： 10.1145/2710025

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

DOI： 10.1007/978-3-319-28379-1_15

Scopus

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Language：English   Publisher：The Japanese Society of Toxicology  

Regression analysis such as linear regression and logistic regression has often been employed to construct toxicogenomic predictive models, which forecast toxicological effects of chemical compounds in human or animals based on gene expression data. While in general these techniques can generate an accurate and sparse model when a regularization term is added to a loss function, they ignore structural relationships behind genes which form vast regulatory networks and interact with each other. Recently, several reports proposed structured sparsity-inducing norms to incorporate prior structural information and make a model reflecting relationships between variables. In this study, assuming that genes regulated by the same transcription factor should be selected together, we applied the latent group Lasso technique on toxicogenomic data with transcription factor networks as prior knowledge. We compared generated classifiers for liver weight gain in rats between the latent group Lasso and Lasso. The latent group Lasso was comparable or superior to the Lasso in terms of predictive performances (balanced accuracy: 74% vs. 72%, sensitivity: 62% vs. 62%, specificity: 86% vs. 83%). Besides, groups selected by the latent group Lasso suggested involvement of Wnt/β-catenin signaling pathway. Such mechanism-related analysis could not have been possible with the Lasso and is one of the advantages of the latent group Lasso.

DOI： 10.2131/fts.2.161

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Other Link： http://search.jamas.or.jp/link/ui/2016381691

Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s10994-015-5524-x

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Institute of Electronics Information Communication Engineers  

Scopus

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier Inc.  

DOI： 10.1016/j.toxrep.2014.10.014

Scopus

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Language：Japanese   Publisher：The Japanese Society for Artificial Intelligence  

This paper considers causal discovery between discrete and continuous variables based on additive noise model. In many database, some fields are discrete while others continuous. However, the previous notion assumes that all the variables are either discrete or continuous. In this paper, we prove that for discrete (m values) and continuous variables X, Y , causality X ! Y cannot be identified for m = 2 under regular conditions, and conjecture that X ! Y can be identified for m · 3, and that Y ! X can be identified for any m. Several experiments support those properties successfully. Furthermore, using R, the program language, we implemented causal discovery between X ="month" and Y ="average temperature" in the data provided by the US National Weather Service Weather Forecast Office.

DOI： 10.11517/jsaifpai.94.0_09

CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I025861071

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1103/PhysRevA.89.022104

Web of Science

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Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDM.2014.33

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2014.html#AryalTHW14

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-319-06605-9_42

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd2014-2.html#AryalTWW14

Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1401.html#InazumiWSSYK14

Publishing type：Research paper (scientific journal)  

DOI： 10.1162/NECO_a_00533

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Other Link： https://dblp.uni-trier.de/db/journals/neco/neco26.html#TashiroSHW14

Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.patcog.2014.01.013

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.neunet.2012.11.004

Web of Science

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Other Link： https://dblp.uni-trier.de/db/journals/nn/nn38.html#HaraW13

DOI： 10.1527/tjsai.28.13

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Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDMW.2013.17

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdmw2013.html#DemeshkoWK13

Publishing type：Research paper (international conference proceedings)   Publisher：ACM  

DOI： 10.1145/2487575.2488211

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Other Link： https://dblp.uni-trier.de/db/conf/kdd/kdd2013.html#KengneFTIRWS13

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/MLSP.2013.6661912

Web of Science

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：American Nuclear Society  

Scopus

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Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.neunet.2013.05.007

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Other Link： https://dblp.uni-trier.de/db/journals/nn/nn46.html#SogawaUKW13

Language：Japanese   Publisher：一般社団法人 人工知能学会  

近年様々な分野で大量の観測データが蓄積されており，因果分析法に対するニーズは高まっている。最近の研究により，データの非ガウス性を利用することで変数間の因果的順序を同定できる場合があることがわかっている。本研究では未観測交絡変数がある場合にその値を離散化してベイズ推定を行い，二変数間の因果順序を同定する手法を提案する。これにより，潜在交絡変数が存在しても頑健な推定することが可能となる。

DOI： 10.11517/pjsai.jsai2013.0_3d15

CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I025962897

Language：Japanese   Publisher：一般社団法人 人工知能学会  

近年，膨大な観測データに潜む因果構造を推定するための統計的手法が必要とされている．本研究では経時データと呼ばれる，時間の推移とともに観測されたデータを用いた因果構造の推定法を提案する．経時データの性質とデータの非ガウス性を利用することで、従来よりも緩い仮定の下で因果構造推定が可能である．更に推定された因果構造に対して時間の経過とともに有意な変化をしている部分を統計的に検出する方法も提案する．

DOI： 10.11517/pjsai.jsai2013.0_3d14

CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I025960543

Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s10115-013-0612-3

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.neunet.2012.04.001

Web of Science

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Other Link： https://dblp.uni-trier.de/db/journals/nn/nn33.html#HaraKWBTY12

Language：English   Publishing type：Research paper (scientific journal)   Publisher：The Institute of Electronics, Information and Communication Engineers  

The mining of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences. A method, called GTRACE, has been proposed to mine frequent patterns from graph sequences under the assumption that changes in graphs are gradual. Although GTRACE mines the frequent patterns efficiently, it still needs substantial computation time to mine the patterns from graph sequences containing large graphs and long sequences. In this paper, we propose a new version of GTRACE that permits efficient mining of frequent patterns based on the principle of a reverse search. The underlying concept of the reverse search is a general scheme for designing efficient algorithms for hard enumeration problems. Our performance study shows that the proposed method is efficient and scalable for mining both long and large graph sequence patterns and is several orders of magnitude faster than the original GTRACE.

DOI： 10.1587/transinf.E95.D.1947

CiNii Books

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：The Institute of Electronics, Information and Communication Engineers  

The mining of a complete set of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences (dynamic graphs or evolving graphs). In this paper, we define a novel subgraph subsequence class called an "induced subgraph subsequence" to enable the efficient mining of a complete set of frequent patterns from graph sequences containing large graphs and long sequences. We also propose an efficient method for mining frequent patterns, called "FRISSs (<u>F</u>requent <u>R</u>elevant, and <u>I</u>nduced <u>S</u>ubgraph <u>S</u>ubsequences)", from graph sequences. The fundamental performance of the method is evaluated using artificial datasets, and its practicality is confirmed through experiments using a real-world dataset.

DOI： 10.1587/transinf.E95.D.1590

CiNii Books

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Language：Japanese   Publisher：一般社団法人 人工知能学会  

近年様々な分野で大量の観測データが蓄積されており，データ生成過程の推定手法に対するニーズは高まっている。最近の研究により，データの非ガウス性を利用することでデータ生成過程を同定できる場合があることがわかっている。本研究ではデータ生成過程の推定と同時にモデルがデータに適合しているかを確認する手法を提案する。これにより，モデル適合部分についてのみデータ生成過程を推定することが可能となる。

DOI： 10.11517/pjsai.jsai2012.0_4b1r26

CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I025970995

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1007/978-3-642-34487-9_72

Web of Science

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Publishing type：Research paper (scientific journal)  

DOI： 10.1002/sam.11136

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-33269-2_62

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Other Link： https://dblp.uni-trier.de/rec/conf/icann/2012-1

Publishing type：Research paper (international conference proceedings)  

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Other Link： http://papers.nips.cc/paper/4815-weighted-likelihood-policy-search-with-model-selection

Language：English   Publishing type：Research paper (international conference proceedings)  

Web of Science

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Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/ICDMW.2012.10

Web of Science

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Publishing type：Research paper (scientific journal)  

DOI： 10.1587/transinf.E95.D.2599

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Other Link： https://dblp.uni-trier.de/db/journals/ieicet/ieicet95d.html#KuwajimaWL12

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-32695-0_14

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Other Link： https://dblp.uni-trier.de/db/conf/pricai/pricai2012.html#InokuchiYWMAIK12

Publishing type：Research paper (scientific journal)   Publisher：AUAI Press  

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1202.html#abs-1202-3736

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/ICDMW.2012.134

Web of Science

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.neunet.2011.05.017

Web of Science

PubMed

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Other Link： https://dblp.uni-trier.de/db/journals/nn/nn24.html#SogawaSSHWI11

Language：Japanese   Publisher：一般社団法人 人工知能学会  

定常な多変数時系列データにARMAモデルを適用し、過去変数からの影響を解析する手法はよく知られている。近年、ARMAモデルと構造方程式を組み合わせることで同時変数間の影響も説明可能としたARMA-LiNGAMモデルが提案された。本論文ではデータの非ガウス性を利用したARMA-LiNGAMモデルの推定手法を説明し、従来の推定手法の問題点を指摘したうえでその問題点を解決する推定手法を提案する。

DOI： 10.11517/pjsai.jsai2011.0_2e35

CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I025900145

Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.neucom.2011.02.008

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Other Link： https://dblp.uni-trier.de/db/journals/jmlr/jmlr12.html#ShimizuISHKWHB11

Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDM.2011.47

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2011.html#TingWWL11

Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1108.html#abs-1108-4217

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1007/978-3-642-23783-6_1

Web of Science

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Other Link： https://dblp.uni-trier.de/db/conf/pkdd/pkdd2011-2.html#HaraW11

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/ICDMW.2011.30

Scopus

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Publisher：AUAI Press  

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Other Link： http://dblp.uni-trier.de/db/conf/uai/uai2011.html#conf/uai/InazumiWSSYK11

Publishing type：Research paper (scientific journal)  

Scopus

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Language：English   Publishing type：Research paper (international conference proceedings)  

Web of Science

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s10115-010-0346-4

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Publishing type：Research paper (scientific journal)  

DOI： 10.1504/IJKESDP.2010.037492

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Publishing type：Research paper (scientific journal)  

DOI： 10.1504/IJAIP.2010.030538

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Publishing type：Research paper (scientific journal)  

DOI： 10.1587/transinf.E93.D.2792

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Other Link： https://dblp.uni-trier.de/db/journals/ieicet/ieicet93d.html#InokuchiW10

Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/corr/corr1006.html#abs-1006-5041

Publishing type：Research paper (international conference proceedings)   Publisher：SIAM  

DOI： 10.1137/1.9781611972801.41

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Other Link： https://dblp.uni-trier.de/db/conf/sdm/sdm2010.html#InokuchiW10

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-13672-6_18

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd2010-2.html#InokuchiW10

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-16184-1_15

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Other Link： https://dblp.uni-trier.de/db/conf/dis/dis2010.html#VinhIW10

Language：English   Publishing type：Research paper (international conference proceedings)  

Web of Science

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Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1007/978-3-642-17537-4_52

Web of Science

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Other Link： https://dblp.uni-trier.de/db/conf/iconip/iconip2010-1.html#HaraKWB10

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/GrC.2010.168

Scopus

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Other Link： https://dblp.uni-trier.de/db/conf/grc/grc2010.html#IchikawaYW10

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-15819-3_10

Scopus

arXiv

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Other Link： https://dblp.uni-trier.de/rec/conf/icann/2010-1

Language：Japanese   Publisher：一般社団法人 人工知能学会  

構造方程式モデルと呼ばれる統計モデルを用いた因果構造探索を議論する。従来法はデータ共分散行列の情報しか用いないことが多いため、モデルを一意に同定できない問題があった。最近、データの非正規性を活用することで、この問題を解消できる場合があることがわかってきた。だが、現在の非正規性を使う方法は、データ情報のみを用い、事前情報があっても利用しない。本発表では、事前情報も利用することで探索性能の向上を図る。

DOI： 10.11517/pjsai.jsai2010.0_1a53

CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I025892825

Language：English   Publishing type：Research paper (international conference proceedings)  

Web of Science

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Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1007/978-3-642-01715-5_5

Scopus

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Publishing type：Research paper (international conference proceedings)  

Scopus

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s00354-009-0065-0

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s12626-008-0005-3

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-05224-8

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-00399-8

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-642-04592-9_34

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Other Link： https://dblp.uni-trier.de/db/conf/kes/kes2009-2.html#IchikawaYNW09

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-540-68125-0

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Publishing type：Research paper (scientific journal)  

DOI： 10.1109/TKDE.2007.190695

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Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDM.2008.106

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2008.html#InokuchiW08

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-540-85565-1_87

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Other Link： https://dblp.uni-trier.de/db/conf/kes/kes2008-2.html#YadaWUN08

Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/ida/ida12.html#NguyenW08

Publishing type：Research paper (international conference proceedings)   Publisher：SIAM  

DOI： 10.1137/1.9781611972788.35

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Other Link： https://dblp.uni-trier.de/db/conf/sdm/sdm2008.html#KidoKW08

Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s00354-007-0015-7

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Publisher：Springer  

DOI： 10.1007/978-3-540-73920-3_5

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Other Link： https://dblp.uni-trier.de/db/conf/dis/book2007.html#WashioM07

Language：English   Publishing type：Research paper (international conference proceedings)  

Web of Science

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

DOI： 10.1007/978-3-540-71009-7_2

Scopus

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Language：English   Publishing type：Part of collection (book)   Publisher：John Wiley &amp; Sons, Inc.  

DOI： 10.1002/9780470073049.ch9

Scopus

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/11731139_45

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd2006.html#NguyenOMMW06

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Institute of Electrical and Electronics Engineers Inc.  

DOI： 10.1109/icdmw.2006.10

Scopus

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

DOI： 10.1007/11961239_6

Scopus

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Language：Japanese   Publisher：The Society of Instrument and Control Engineers  

DOI： 10.11499/sicejl1962.44.307

CiNii Books

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Other Link： https://jlc.jst.go.jp/DN/JALC/00250229404?from=CiNii

Publishing type：Research paper (international conference proceedings)   Publisher：Professional Book Center  

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Other Link： https://dblp.uni-trier.de/rec/conf/ijcai/2005

Publishing type：Research paper (scientific journal)  

DOI： 10.1007/BF03037635

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/11563983_22

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Other Link： https://dblp.uni-trier.de/db/conf/dis/dis2005.html#WashioAM05

Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDM.2005.55

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2005.html#TermierRSOWM05

Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDM.2005.100

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2005.html#WashioMM05

Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/fuin/fuin66.html#InokuchiWM05

Publishing type：Research paper (scientific journal)  

DOI： 10.1080/09528130512331315837

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Language：English   Publishing type：Research paper (international conference proceedings)  

Scopus

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/11564126_74

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Other Link： https://dblp.uni-trier.de/db/conf/pkdd/pkdd2005.html#WashioNM05

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

DOI： 10.1007/11423270_8

Scopus

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Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/AMT.2005.1505269

Scopus

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Language：English   Publishing type：Research paper (international conference proceedings)  

Scopus

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/11780496_46

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Other Link： https://dblp.uni-trier.de/db/conf/jsai/jsai2005.html#WashioNMO05

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/11430919_74

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd2005.html#NguyenOMW05

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-540-30116-5_33

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Other Link： https://dblp.uni-trier.de/db/conf/pkdd/pkdd2004.html#NguyenWOM04

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Verlag  

DOI： 10.1007/978-3-540-30133-2_105

Scopus

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Publishing type：Research paper (international conference proceedings)   Publisher：ACM  

DOI： 10.1145/1014052.1014107

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Other Link： https://dblp.uni-trier.de/db/conf/kdd/kdd2004.html#YoshidaAWMHNFY04

Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/ida/ida8.html#YoshidaWMW04

Publishing type：Research paper (scientific journal)  

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Other Link： https://dblp.uni-trier.de/db/journals/ieicet/ieicet87d.html#YoshidaAWMHNFY04

Language：Japanese   Publisher：The Society of Instrument and Control Engineers  

DOI： 10.11499/sicejl1962.42.480

CiNii Books

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Other Link： https://jlc.jst.go.jp/DN/JALC/00229788444?from=CiNii

Publishing type：Research paper (scientific journal)  

DOI： 10.1023/A:1021726221443

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/978-3-540-39644-4_12

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Other Link： https://dblp.uni-trier.de/db/conf/dis/dis2003.html#GeamsakulMYMW03

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-36175-8_6

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd2003.html#GeamsakulMYMW03

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

DOI： 10.1007/978-3-540-39592-8_69

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Language：Japanese   Publisher：Division of Chemical Information and Computer Sciences The Chemical Society of Japan  

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DOI： 10.11546/cicsj.21.37

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1002/eej.10034

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Language：Japanese   Publisher：The Society of Instrument and Control Engineers  

DOI： 10.11499/sicejl1962.41.319

CiNii Books

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Other Link： https://jlc.jst.go.jp/DN/JALC/00157320235?from=CiNii

Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/ICDM.2002.1183998

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Other Link： https://dblp.uni-trier.de/db/conf/icdm/icdm2002.html#YoshidaMW02

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45683-X_25

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Other Link： https://dblp.uni-trier.de/db/conf/pricai/pricai2002.html#WadaYMW02

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45683-X_26

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Other Link： https://dblp.uni-trier.de/db/conf/pricai/pricai2002.html#FujiwaraYMW02

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45683-X_29

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Other Link： https://dblp.uni-trier.de/db/conf/pricai/pricai2002.html#MatsudaMYW02

Publishing type：Research paper (scientific journal)  

DOI： 10.1016/S1474-0346(02)00005-8

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s101150200010

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-36182-0_44

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Other Link： https://dblp.uni-trier.de/db/conf/dis/dis2002.html#MatsudaMYW02

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45884-0_28

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Other Link： https://dblp.uni-trier.de/db/conf/dsp/dsp2002.html#HasegawaWI02

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45884-0_42

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Other Link： https://dblp.uni-trier.de/db/conf/dsp/dsp2002.html#WashioM02

Language：Japanese   Publisher：The Japanese Society for Artificial Intelligence  

A machine learning technique called Graph-Based Induction (GBI) efficiently extracts typical patterns from graph data by stepwise pair expansion (pairwise chunking). In this paper, we introduce Graph-Based Induction for general graph structured data, which can handle directed/undirected, colored/uncolored graphs with/without (self) loop and with colored/uncolored links. We show that its time complexity is almost linear with the size of graph. We, further, show that GBI can effectively be applied to the extraction of typical patterns from DNA sequence data and organnochlorine compound data from which to generate classification rules, and that GBI also works as a feature construction component for other machine learning tools.

DOI： 10.1527/tjsai.16.363

CiNii Books

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Other Link： https://jlc.jst.go.jp/DN/JALC/00151428081?from=CiNii

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

DOI： 10.1007/3-540-45490-x_36

Scopus

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Publishing type：Research paper (scientific journal)  

DOI： 10.1007/PL00011663

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

DOI： 10.1007/3-540-45548-5_72

Scopus

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-44795-4_46

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Other Link： https://dblp.uni-trier.de/db/conf/ecml/ecml2001.html#WashioMN01

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-44816-0_18

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Other Link： https://dblp.uni-trier.de/db/conf/ida/ida2001.html#TerabeWM01

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45357-1_58

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd2001.html#WadaMW01

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-44418-1_35

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Other Link： https://dblp.uni-trier.de/db/conf/dis/dis2000.html#HasegawaWIS00

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-44418-1_9

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Other Link： https://dblp.uni-trier.de/db/conf/dis/dis2000.html#MatsudaHMW00

Publishing type：Research paper (international conference proceedings)   Publisher：Morgan Kaufmann  

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Other Link： https://dblp.uni-trier.de/db/conf/icml/icml2000.html#WashioMN00

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45571-X_49

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd2000.html#MatsudaHMW00

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-45372-5_2

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Other Link： https://dblp.uni-trier.de/db/conf/pkdd/pkdd2000.html#InokuchiWM00

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-46846-3_35

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Other Link： https://dblp.uni-trier.de/db/conf/dis/dis99.html#InokuchiWM98

Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s101110050017

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-46846-3_33

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-48912-6_40

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd99.html#WadaHMW99

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-48912-6_56

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-46846-3_39

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Publishing type：Research paper (international conference proceedings)   Publisher：Morgan Kaufmann  

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Other Link： https://dblp.uni-trier.de/rec/conf/ijcai/99

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-48912-6_20

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd99.html#TerabeKSWM99

Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-64383-4_50

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Other Link： https://dblp.uni-trier.de/db/conf/pakdd/pakdd98.html#WashioM98

Publishing type：Research paper (scientific journal)  

DOI： 10.1016/S0950-7051(98)00034-3

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-49292-5_31

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Publishing type：Research paper (scientific journal)  

DOI： 10.1137/S1064827596305829

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Publishing type：Research paper (international conference proceedings)   Publisher：AAAI Press / The MIT Press  

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Other Link： https://dblp.uni-trier.de/rec/conf/aaai/1998

Publishing type：Research paper (international conference proceedings)   Publisher：Morgan Kaufmann  

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Other Link： https://dblp.uni-trier.de/rec/conf/ijcai/1997

Publishing type：Research paper (scientific journal)  

DOI： 10.1016/S0004-3702(96)00060-4

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Language：Japanese   Publisher：Japan Ergonomics Society  

DOI： 10.5100/jje.32.Supplement_308

CiNii Books

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Publishing type：Research paper (international conference proceedings)   Publisher：Springer  

DOI： 10.1007/3-540-61532-6_27

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Other Link： https://dblp.uni-trier.de/db/conf/pricai/pricai96.html#WashioM96

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier  

DOI： 10.1016/S0921-2647(06)80146-2

Scopus

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Language：Japanese   Publisher：Japan Society for Fuzzy Theory and Intelligent Informatics  

DOI： 10.3156/jfuzzy.5.5_958

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J-GLOBAL

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Language：Japanese   Publisher：応用物理学会有機分子・バイオエレクトロニクス分科会  

CiNii Books

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J-GLOBAL

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J-GLOBAL

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J-GLOBAL

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J-GLOBAL

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J-GLOBAL

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Language：Japanese   Publisher：The Japanese Society for Artificial Intelligence  

&lt;p&gt;We propose to apply Recursive Bayesian Computation to image estimation of SPoD-ExPAN microscopy.The method does not need derivatives of the optimality measure and is supposed to derive images globally better than those of gradient dissent based approaches.In this paper, we present an implementation of the Recursive Bayesian Computation by using Kernel density estimation.Moreover, we introduce regularization to the estimation, and experimentally compare its performance with the case without the regularization.&lt;/p&gt;

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J-GLOBAL

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Language：Japanese   Publisher：応用物理学会有機分子・バイオエレクトロニクス分科会  

CiNii Books

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Language：Japanese   Publisher：化学同人  

CiNii Books

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J-GLOBAL

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J-GLOBAL

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Language：Japanese   Publisher：一般社団法人 人工知能学会  

&lt;p&gt;近年の超解像蛍光顕微鏡技術開発により、電子顕微鏡に頼らずに細胞内の微細構造の可視化が可能になった。しかし、細胞挙動の理解を今後進めるには、細胞内の構造のみならず、情報伝達物質の動き、温度、酵素反応等の生理パラメータを超解像イメージングで計測し、そこから潜在的要因の検出や状態の推定をすることが必要になってくる。本論文では、蛍光プローブ開発と生理機能超解像イメージングへ向けた取り組みについて発表する。&lt;/p&gt;

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Language：English   Publisher：Springer Verlag  

Scopus

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Language：Japanese  

CiNii Books

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Other Link： http://id.nii.ac.jp/1004/00001792/

Language：Japanese  

CiNii Books

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Language：Japanese   Publisher：Institute of Systems, Control and Information Engineers  

CiNii Books

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Language：Japanese  

CiNii Books

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Language：Japanese   Publisher：The Physical Society of Japan (JPS)  

CiNii Books

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CiNii Books

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CiNii Books

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

Reinforcement learning (RL) methods based on direct policy search (DPS) have been actively discussed to achieve an efficient approach to complicated Markov decision processes (MDPs). Although they have brought much progress in practical applications of RL, there still remains an open problem in DPS related to model selection for the policy. In this paper, we propose a new DPS method, weighted likelihood policy search (WLPS), where a policy is efficiently learned through the weighted likelihood estimation. WLPS naturally connects DPS to the statistical inference problem and thus various sophisticated techniques in statistics can be applied to DPS problems directly. Hence, by following the idea of the information criterion, we develop a new measurement for model comparison in DPS based on the weighted log-likelihood.

CiNii Books

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

In this paper, we propose a graphical model learning algorithm for an anomaly localization. We introduce a new regularization term that penalizes the row/column-wise difference between two precision matrices and formulate the task as a convex optimization problem. We further provide an optimization algorithm based on an alternating direction method. The validity of the proposed method is presented through a simulation using a real world data.

CiNii Books

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Language：Japanese  

CiNii Books

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CiNii Books

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Other Link： http://id.nii.ac.jp/1004/00007980/

Language：Japanese  

CiNii Books

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Language：Japanese  

CiNii Books

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Language：English   Publisher：人工知能学会  

We consider the problem of finding significant connection strengths of variables in a linear non-Gaussian causal model called LiNGAM. In our previous work, bootstrapping confidence intervals of connection strengths were simultaneously computed in order to test their statistical significance. However, such a naive approach raises the multiple comparison problem which many directed edges are likely to be falsely found significant. Therefore, in this study, we tested two multiple testing correction approaches, Bonferroni correction and Mandel's approach, then evaluated their performance. We found that both Bonferroni correction and Mandel's approach are able to eliminate some of falsely found directed edges.

DOI： 10.11517/pjsai.jsai2012.0_4b1r24

CiNii Books

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CiNii Books

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CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I023433809

Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

In this paper, we propose the first exact algorithm for minimizing the difference of two submodular functions (D.S.), i.e., the discrete version of the D.C. programming problem. The developed algorithm is a branch-and-bound-based algorithm which responds to the structure of this problem through the relationship between submodularity and convexity. The D.S. programming problem covers a broad range of applications in machine learning because this generalizes any set-function optimization. We empirically investigate the performance of our algorithm, and illustrate the difference between exact and approximate solutions respectively obtained by the proposed and existing algorithms in feature selection.

CiNii Books

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

In our previous study, we proposed a method to identify a data generation process governing its given binary data set. However, statistics used in the method were not optimal. In this paper, we report a preliminiary result bu using more proper statistics. The experimental evaluation shows promising performance.

CiNii Books

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

In this paper, we propose an estimation technique of a graphical model with some unknown clusters. We introduce a new regularization term based on a graph Laplacian matrix which captures the cluster structure. We confirm the validity of the proposed method through numerical simulation.

CiNii Books

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Language：Japanese   Publisher：東京 : 電子情報通信学会  

CiNii Books

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Other Link： https://ndlsearch.ndl.go.jp/books/R000000004-I023346021

Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

CiNii Books

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

Dependency structure among variables is closely tied to an underlying data generating process. Therefore, learning a dependency structure from observations is an important task in data mining. Especially when multiple data sources involve common substructure among their dependency structures, it implies an existence of an underlying fundamental mechanism. In this paper, we propose a learning algorithm for finding such a common dependency structure from multiple datasets in the case of Gaussian Graphical Model (GGM). Our proposed algorithm is based on a block coordinate descent method and is a natural extension of an existing learning algorithm for GGM. We show the validity of our approach in a numerical simulation.

CiNii Books

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CiNii Books

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CiNii Books

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CiNii Books

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Language：Japanese   Publisher：人工知能学会  

DOI： 10.11517/pjsai.jsai2011.0_2e36

CiNii Books

J-GLOBAL

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J-GLOBAL

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

Under development of sensing techniques to ease simultaneous measurements of many variables and features on objects, the need increases to systematically understand an objective system underlying data generation process where the data is generated under influences from some variables/relations to the other variables/relations. While graphical modeling techniques and time series analyses have been used for this need in the long past period, novel techniques are emerging in recent years. Members in our laboratory currently work on development of novel relational data mining methods focusing on data generation process based on the causality between many variables/elements by using graph mining, statistical causal inference and optimization algorithm. In this talk, we introduce these studies and their application examples and further prospect the future possibility of relational data mining for understanding the data generation process.

CiNii Books

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Language：Japanese  

DOI： 10.11517/pjsai.jsai2010.0_1a14

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J-GLOBAL

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CiNii Books

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Language：Japanese   Publisher：人工知能学会  

DOI： 10.11517/pjsai.jsai2009.0_2c13

CiNii Books

J-GLOBAL

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Language：English  

DOI： 10.1007/s10463-008-0208-y

Web of Science

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CiNii Books

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Other Link： http://id.nii.ac.jp/1004/00006982/

Language：Japanese  

CiNii Books

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CiNii Books

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Other Link： http://id.nii.ac.jp/1004/00006719/

Language：Japanese  

CiNii Books

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CiNii Books

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Language：Japanese   Publisher：一般社団法人 人工知能学会  

本研究ではバイオインフォマティクスのデータから飽和頻出木をマイニングすることを試みる。対象データの構造はDAGなので、我々のツリーマイニングアルゴリズムDryadeをＤＡＧに適用可能なように改良した。実験でこの効果を確かめる。

DOI： 10.11517/pjsai.JSAI06.0.7.0

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Language：Japanese   Publisher：Information Processing Society of Japan (IPSJ)  

CiNii Books

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CiNii Books

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Other Link： http://id.nii.ac.jp/1004/00006019/

Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

Data mining is a, technology attracting many researchers and practitioners in recent years. It. is a synthetic technology of various elemetary theories and techniques for data analysis. This fact causes some difficulties to understand data mining, and prevents its collaborative synthesis with the other thechnologies such as pattern recognition. In this note, the state of the art, the recent trend, the issues of data mining are briefly reviewed, and some problems caused by the differences of objectives, scopes and terminologies between data mininig and pattern recognition are discussed.

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Language：Japanese   Publisher：Human Interface Society  

Current difficulty to formulate complex systems may be resolved by introducing scale constraints thanks to the development of advanced information technology. This paper concerns the identification of the first principle equation that governs complex system beviour by applying machine learning and trial study of the relationship between the public affinity and earthquake risk. The basic research of the discovery of the first principle equation has been made in the area of artificial intelligence, a kind of engineering. This outcome was extended to socio-psychology. Thus the framework is considered to be a symbiosis of natural and cultural sciences.

DOI： 10.11184/hisrm.4.2_1

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Other Link： https://jlc.jst.go.jp/DN/JALC/10015804463?from=CiNii

Language：Japanese   Publisher：Information Processing Society of Japan (IPSJ)  

CiNii Books

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Other Link： http://id.nii.ac.jp/1001/00063806/

Language：Japanese  

CiNii Books

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Other Link： http://id.nii.ac.jp/1004/00005190/

Language：Japanese   Publisher：The Japan Society of Mechanical Engineers  

Since design knowledge plays a crucial role in design process, we are conducting research on design reasoning model that takes notice of design knowledge. To make a design reasoning model, we have already proposed a reasoning framework of design and analyzed basic operations for the framework, and then propose a synthesis language for describing design operational knowledge. In this paper, we propose our implementation of this model, and verify it to compare design processes replayed in the system with ones of actual design sessions.

DOI： 10.1299/jsmedsd.2001.10.285

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Language：Japanese   Publisher：The Japan Society of Mechanical Engineers  

Since design knowledge plays a crucial role in design process, we are conducting research on design reasoning model that takes notice of design knowledge. To make a design reasoning model, we have already proposed a reasoning framework of design and analyzed basic operations for the framework. However, since these operations are just fragments of whole design process, it is necessary to describe design operational knowledge that can control the entire reasoning operations by constructing the sequence of these fragments. So, in this paper, we propose a synthesis language for describing design operational knowledge.

DOI： 10.1299/jsmedsd.2001.10.281

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CiNii Books

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