Business Cases
Here are some examples of our work,
based on our work experience or that of our engineers.
Details may be added for title and keywordonly cases in the future.
Research & System Development Cases
 Change point detection of time series  technical surveyAnomaly Detection
 Independent component analysis  technical survey and tutorial
 Bayesian networks  technical survey
 Periodic impulse waveform extraction  technical survey and implementation
 Process mining  technical survey
 Order tracking of mechanical vibration by Bayesian estimation  development
 Implementation of a program to detect natural vibrations of machine
 Tone representation and resynthesis system for speech and sound  R&D.Sound Processing
 Texttospeech synthesis program  porting and developmentAISound Processing
 Noise reduction algorithm by wavelet analysis  R&DSignal Processing
 Abnormal detection algorithm by mechanical vibrations and sounds  R&DAnomaly Detection
 Preprocessing and unsupervised machine learning methods for anomaly detection from spatiotemporal data  technical surveyAnomaly DetectionSignal ProcessingAI
 Optimized numerical control for semiconductor production device  software R&DOptimization
 An automated fragmentation library of low molecular weight compounds for application in the FMO method  development
 Advancement of biomolecular analysis workflows running on supercomputer "Fugaku"  R&DMolecular SimulationQuantum Chemical Computation
 Workflow program for binding free energy calculations of multiple ligands onto supercomputer "Fugaku"  deploymentDrug DiscoveryMolecular Simulation
 2D region optimal partitioning  software developmentOptimization
 Optimal fitting applications for nonlinear functions  development
 Data assimilation system for seismic waves  developmentOptimization
 Mathematical Optimization of Redundant Manipulator Inverse KinematicsRoboticsOptimization
 Experimental condition optimization program using Bayesian optimization  developmentOptimization
 Vehicle routing problem solver  research and developmentAI
 Machine design parameters analysis  tool development
 Circuit layout diagram visualization software for reconfigurable devices  development
 Sound propagation calculation  software development
 Surface variation in threedimensional euclidean space  numerical experiment application development
 Parallelization of algorithms with parallel programming modelsBig Data
 Research software enhancement and multiplatformization
 Phase recovery algorithms for coherent xray analysis  implementation and accelerationNumerical ComputationImage Processing
 Computational software for tomographic image reconstruction using GPGPU  developmentNumerical Computation
 Numerical analysis software development and theoretical analysis of superconducting circuitsNumerical Computation
 Machine translation algorithms  R&DAINatural Language Processing
 Automatic summarization algorithm  R&DAINatural Language Processing
 Document classification algorithms  R&DAINatural Language Processing
 Question answering from largescale unstructured data using LLM  R&DAINatural Language Processing
 Webembedded 3DCG editor  development
 Web information guidance system using ontology  developmentAINatural Language Processing
 3DCG display system using natural language processing  developmentNatural Language Processing
 Educational systems using natural language processing  developmentNatural Language Processing
 Natural language processing for Twitter timelines  technical surveyNatural Language Processing
 Remote control system for simultaneous measurement by multiple PCs  developmentRPA
 Zigbee wireless sensor network monitoring system  developmentIoT
 Validation of the accuracy of a realtime situation assessment model using timeseries sensor data  application developmentBig Data
 Multisensor simultaneous measurement management system for human body  developmentBig Data
 Medical support image processing system  development
 Layer discrimination method for tomographic image  R&DAI
 Estimating environmental conditions using metagenomic Data  R&DAI
 Medical data analysis and modeling  research support
 Stochastic process estimation algorithm  porting developmentAI
 Statistical causal inference algorithms  developmentAI
 Price prediction model using quantile regression  developmentAI
 Observer evaluation support software using item response theory  development
 Economic simulation result visualization program  development support
 Factor analysis for data with missing values  R&DAI
 State estimation program using unscented Kalman filter and particle filter  development
 Sensory evaluation program for gemstones  research and developmentAI
 Realtime object recognition agent system  developmentAI
 Highspeed detection of obstacles when traveling with moving objects  R&DObject Detection
 Consulting for the introduction of deep learning techniquesAI
 Face image recognition system  algorithm R&DAI
 Face identification method based on a small number of data  algorithm developmentAI
 Anomaly detection methods based on image reconstruction using deep Learning  survey and implementationAI
 Highresolution film scanner control system  developmentImage Processing
 Digital camera shooting system for aerial photography  developmentImage Processing
 Trademark similarity determining algorithms  algorithm developmentAI
 Machine learning on sets of samples where individual labels are unknown  R&DAI
 Complex problem guide system applying data mining  developmentAI
 Biometric coupling hardware control system  development
 EEG measurements  experimental support
 BMI framework  developmentBiomedical Data Analysis
 Decoding analysis of brain activity data  R&DAIBiomedical Data Analysis
 Visual stimulus presentation program  development
 Heart rate variability parameter calculation Android App  developmentIoTAIBiomedical Data Analysis
 BLE sensor data analysis windows application  developmentIoT
 Visualizing brain oscillatory activity using maximum entropy method  software development
 Neural spike sorting  algorithm development
 Evaluating the stimulus response of spike information  software development
 Image processing program for highspeed camera  developmentImage Processing
 Ca2+ imaging data processing program  development
 Digitizing and mapping system for animal behavior experiments  developmentImage Processing
 Small animal behavior recording system  developmentImage Processing
Change point detection of time series  technical survey
Surveyed theories and technologies of detecting change points on a given time series in some meaning and summarized as a report document.
These technologies are generally called "change point detection", "anomaly detection", or "motif discovery", and many methods have been developed. The fields in need of these technologies are wide, not only signal processing but also security system, bioinformatics, multimedia processing and so on.
Mainly surveyed the following methods.
 Symbolic Aggregation Approximation Method
 Random Projection Pursuit Method
 MarkovSuffix Tree Method
 Normalized Edit Distance Method
 Isomap Nonlinear Dimension Reduction Method
 Kolmogorov Complexity Anomaly Detection Method
 Motif Discovery by PCA and MDL Principal
Independent component analysis  technical survey and tutorial
We made a survey of various methods of Independent Component Analysis, summarized mathematical theories to understand these theories, submitted as a report document, and tutorial based on the report.
Mainly surveyed the following methods:
 Negentropy Minimizing Method (FastICA)
 Cumulant Tensor Eigen Decomposition Method (JADE)
 NonNormal Component Extraction by Projection Pursuit
 BetaDivergence Minimizing Method
 Space Mixture Separation utilizing Time Structures.
 Mutual Covariance Elimination (Simultaneous Diagonalization of SelfCovariance Matrix by Eigenvalue Decomposition)
 Mutual Decorrelation Method (Simultaneous Diagonalization of Nonstationary Covariance Matrix by Gradient Method)
 VarianceNonstationarity Maximizing Method.
Summarized the following mathematical theories:
 Information Theory
 Mutual Information
 KullbackLeibler Information
 Principal Component Analysis
 Factor Analysis
 Canonical Correlation Analysis
 Nonlinear PCA
 Kernel PCA
 Cumulant Decomposition
 Maximum Likelihood Method
 Pseudo Maximum Likelihood Method
 Negentropy
 GramCharlier Expansion
 GaussHermite Expansion
 Edgeworth Expansion
 CornishFisher Expansion
 BetaDivergence
 BRobustness
 Projection Pursuit
 Kernel Dimension Reduction
 Marcinkiewicz's Theorem
 Maximum Entropy Method
 Nonlinear Optimization
 Eigenvalue / Singular Value Decomposition
 Symmetrical Diagonalization of Matrix, and numerical calculation methods of these theories
Bayesian networks  technical survey
Bayesian Network is a technology of modeling causal relations between stochastic variables. In this work, we surveyed
 Inference Algorithms
 Parameter Learning Algorithms
 Structure Learning Algorithms
We made a report document which can be used until implementing as software program. We also surveyed concrete applied examples of Bayesian Networks to real world.
Mainly surveyed the following methods:
 Message Passing Algorithm (Probability Propagation)
 SPI Algorithm (Symbolic Probability Inference)
 Likelihood Weighted Sampling Method
 Parameter Learning by EM Algorithm based on Dirichlet Distribution
 K2 Structure Learning Algorithm
Mainly surveyed the following application examples:
 Abnormal Identification of Aircraft Gas Turbine Engine
 Abnormal Diagnosis of Ship Engine Room
 Abnormal Diagnosis of Turbine Power Generator
 Anomaly Detection of Machines by Vibrations and Sounds
 Anomaly Detection of Auto Door
 Anomaly Detection of Space Appliances
Periodic impulse waveform extraction  technical survey and implementation
Surveyed technologies which detect and extract periodic impulse waveform from time series data, and summarized as a report document. Also implemented five algorithm chosen from these many methods and compared accuracy and performance.
Mainly surveyed the following methods:
 SVR Spectrum Method
 Matrix Algebra Separation Method (MAS)
 Cumulant Harmonic Decomposition Method
 Orthogonal Partial Space Decomposition Method
 Periodic Transform Method (PT)
 FilterSelecting Adaptive Comb Filter (ACF)
 Uniform QComb Filter
 Fast Whitening Comb Filter
 Harmonic Wave Inference Whitening Comb Filter
 Latticetype IIR Adaptive Notch Filter
 Correlation Impulse Adaptive Filter (CIAF)
 Rotating Adaptive Filter (RAF)
 CyclicShift Intermissive Adaptive Filter (CSSGAF)
 Canonical Self Regression Decomposition (CARD)
 Global Amplitude Phase Modulation Method
 Fourier Linear Combinator (FLC)
 Recursive Discrete Fourier Transform Method
 Adaptive Fourier Analysis by Fast Filterbank
Process mining  technical survey
We investigated various methods of process mining, a technique for inferring the underlying process structure from timeseries event logs, and compiled them into a report. We also implemented one of the algorithms in Java.
Mainly the following methods are surveyed.
 Heuristic Algorithm
 Genetic Algorithm
 Duplicate Task GA Algorithm
 alpha Algorithm
 alpha++ Algorithm
 Parikh Languagebased Region Algorithm
 Region Algorithm
 Tsinghuaalpha Algorithm
 Fuzzy Algorithm
 DWS mining Algorithm
Order tracking of mechanical vibration by Bayesian estimation  development
Developed a MATLAB program of Bayesian estimation for order tracking which estimates frequency of rotating machines or reciprocating machines from vibration and sound coming up from them.
 Technologies

 MATLAB
 Signal Processing
 Numerical Computation
 Bayesian Estimation
 Maximum Likelihood Method
Implementation of a program to detect natural vibrations of machine
We implemented a program in MATLAB to estimate a machine's natural vibration from its vibration spectrum.
 Technologies

 MATLAB
 Signal Processing
 Spectrum Analysis
 Nonparametric Smoothing
 NadarayaWatson Estimator
 Gaussian Mixture Models
 EM Algorithm
Tone representation and resynthesis system for speech and sound  R&D.
This system extracts essential data structures which represents tone of sound (tone representation), and inversely reconstruct and resynthesis original tone from the data structures.
Developed the system which can experiment several algorithms, based on bandwidth extended sinusoidal model which improves McAulayQuatieri Sinusoidal Analysis utilizing auditory psychology model, making high accuracy of tone analysis using spectrogram reassignment method based on Cohen's kernel function classes, and adding auditory energy model of our own.
 Technologies

 MATLAB
 Signal Processing
 Sound Processing
 McAulayQuatieri Sinusoidal Analysis
 Auditory Psychology Model
 Spectrogram Reassignment Method
 Cohen's Kernel Functions Classes
Texttospeech synthesis program  porting and development
We ported texttospeech synthesis program which is originally developed in CMU and Edinburg University implemented in C++ and Scheme language to lightweight C language.
The original program is highly customizable software because it implements speech signal processing and various algorithms in C++ and call them through Scheme interpreter. But the original program is so large to use in real environments, and it includes redundant processing all over the place, we simplified these architectures as well as porting to lightweight C language.
In C language, we not embedded Scheme interpreter, but used simple Scheme object with reference counting instead. Various inference processing used in speech synthesis are realized by Viterbi algorithm with ngram dictionaries. We wrote Scheme program which converts prelearned decision trees written in Scheme to decision trees written in C.
 Technologies

 TextToSpeech Synthesis
 C++
 Scheme
 Viterbi Algorithm
 Decision Tree
Noise reduction algorithm by wavelet analysis  R&D
A system was developed which experiments and analyze reduction algorithms of noise included in speech or vibration by using wavelet analysis related techniques.
Global GCV Method, LevelDependent GCV Method
Calculating threshold of minimizing GCV (Global CrossValidation) against discrete wavelet coefficients, this method reduces noise by eliminating components less than the threshold.
TreeStructured Method
Calculating subtree having strength more than some threshold from wavelet coefficients tree, this method reduces noise which have no relations with the essential waveform. Implemented Dyadic CART (Classification And Regression Trees) algorithm for searching optimal subtree. This algorithm does model regression against (sparse) binarytree whose node has numerical value by posing penalty for complexity of the binarytree.
To develop this system, we have needed processing of complex data structure, but MATLAB is not so good at such a work, so we implemented core algorithm in C++ and let MATLAB call it as a plugin.
 Technologies

 MATLAB
 C++
 MATLAB Plugin
 Wavelet Analysis
 GCV
 Tree Model Regression
Abnormal detection algorithm by mechanical vibrations and sounds  R&D
Researched and developed algorithms which detects abnormality of machines by vibrations and sounds originated from machines.
Features are extracted which are considered to be efficient for detecting abnormality using Spectrum Analysis and Statistic Analysis. These features are input to decision algorithms of various pattern recognition. We verified effectiveness of several combinations of these features and recognition algorithms.
 Technologies

 Spectrum Analysis
 Statistical Analysis
 Time Series Analysis
 Pattern Recognition
 MATLAB
 C++
Preprocessing and unsupervised machine learning methods for anomaly detection from spatiotemporal data  technical survey
 Technologies

 Proper Orthogonal Decomposition (POD)
 Dynamic Mode Decomposition (DMD)
 Robust Principal Component Analysis (Robust PCA)
 Local Outlier Factor (LOF)
 Isolation Forest (iForest)
 OneClass Support Vector Machine (OneClass SVM)
Optimized numerical control for semiconductor production device  software R&D
Existing program which solves AR model estimation problem by numerical iteration method was very slow and cannot endure for practical use.
We explored the existing program and suggested several alternative numerical calculation algorithm and implementation methods. Finally compared performance of these alternatives, we achieved 1000 times faster program than the existing program.
 Technologies

 Time Series Analysis
 AR model Estimation
 Numerical Computation
 C
An automated fragmentation library of low molecular weight compounds for application in the FMO method  development
 Technologies

 Quantum Chemical Calculation
 Fragment Molecular Orbital Method (FMO Method)
 Combinatorial Optimization
 C++
Advancement of biomolecular analysis workflows running on supercomputer "Fugaku"  R&D
 Technologies

 Prefect
 Workflow
 Supercomputer "Fugaku"
 HPC
 PJM
 AbinitMP
 Fragment Molecular Orbital Method (FMO Method)
 IFIE
 PIEDA
 Extensive exploration of biomolecular structures
 Gromacs
 CafeMOL
 Incremental PCA
 DaskML
 KMR
 Python
Workflow program for binding free energy calculations of multiple ligands onto supercomputer "Fugaku"  deployment
 Technologies

 Free Energy Perturbation
 Supercomputer "Fugaku"
 HPC
 PJM
 RDKit
 Gromacs
 Python
2D region optimal partitioning  software development
We have developed software that numerically finds an approximate solution to the optimization problem of partitioning a finite and connected twodimensional region in a twodimensional plane into a specified number of subregions and finding a region partitioning that minimizes the sum of the first eigenvalues (minimum eigenvalues) of the LaplaceDirichlet eigenvalue problem in each of these subregions.
Since it is difficult to solve such an optimization problem directly, a relaxed formulation was developed by introducing a density function that approximates the characteristic function of the partitioned region and imposing a penalty outside the region in order to compute approximate eigenvalues of the partitioned region. In such a relaxed formulation, it is known that the density function converges to the characteristic function of the region as the penalty approaches infinity.
Therefore, we implemented an algorithm in which each density function is optimized by the gradient descent method so that the sum of eigenvalues becomes small while solving the approximate eigenvalue problem for each partitioned regions with appropriate initial settings. Parallel computation was also used to speed up the process.
We have also implemented an algorithm to optimize the same problem from a thermodynamic point of view. Since the property that a multicomponent system of particles in Brownian motion is regionally distributed in such a way as to minimize Renyi entropy production in a stationary state is an equivalent formulation to this optimization problem, we implemented an algorithm to approximate this optimization problem by simulating this thermodynamic system.
 Technologies

 LaplaceDirichlet Eigenvalue Problem
 Eigenvalue Optimization
 Region Partitioning
 Parallel Computing
 C++
Optimal fitting applications for nonlinear functions  development
We developed an application to find a nonlinear function to fit to data from a measurement instrument.
This application allows you to find the coefficients of a desired nonlinear function.
The derivative free least squares method is used to estimate nonlinear functions.
Wavelet is used for data preprocessing, and cubic spline interpolation is used to interpolate data between measurement points.
 Technologies

 Nonlinear Least Squares Method
 Wavelet
 Spline Interpolation
 Jacobian
 QR Decomposition
 C#
Data assimilation system for seismic waves  development
We have developed a data assimilation system that optimizes the mass density and elastic constants of seismic wave simulation model based on groundbased pseudoseismic observation data.
Although it is difficult to directly observe the subsurface mass density and elastic constants, they can be estimated by data assimilation using seismic data from the ground.
The data assimilation method used was the fourdimensional variational method (4DVar or adjoint method). This method uses an adjoint model based on a simulation model. This allows us to optimize the parameters over a period of time to satisfy the governing equations of the simulation model.
 Technologies

 Data Assimilation
 4DVar
 Fortran
Mathematical Optimization of Redundant Manipulator Inverse Kinematics
This software development is for solving the inverse kinematics of redundant manipulators. We have derived analytical solutions using a mathematical processing system and calculated practical solutions by means of mathematical optimization.
In the inverse kinematics of redundant systems, there are countless analytical solutions, of which only a few are valid for practical use. Therefore, mathematical optimization is performed to select a solution that fits practical use from among analytical solutions with degrees of freedom. Also, although inverse kinematics theoretically yields an analytical solution, it involves the computation of an inverse matrix, and as the number of joints increases, the solution equation expands to a huge number of terms. If it is implemented as it is, it is not expected that a solution can be obtained within a practical time frame. By combining analytical solution and mathematical optimization, we developed an algorithm to obtain a solution at high speed and implemented it in software.
For the implementation of mathematical optimization, we implemented and compared several algorithms, including the conjugate gradient method, and selected the best algorithm with a good balance between accuracy and speed.
 Technologies

 Redundant Inverse Kinematics
 Mathematical Processing System
 Mathematical Optimization
 C++
Experimental condition optimization program using Bayesian optimization  development
 Technologies

 Bayesian Optimization
 RPA (Robotic Process Automation)
 Sequential Experimental Design
 Python
Vehicle routing problem solver  research and development
 Technologies

 Operations research
 Combinatorial optimization
 Metaheuristics
Machine design parameters analysis  tool development
We have developed a set of tools to analyze and visualize machine design parameters.
SelfOrganizing Map
The information necessary for 2D drawing by SOM is output and visualized by ESOM.
Clustering
The parameters are clustered by Kmeans, and the data for graphical display is output by automatically extracting the two axes for which the representative points of the clusters are easily visible.
LeastSquares
Given 𝒚 and 𝑿, we obtain 𝒘 which satisfies 𝒚≈𝑿𝒘 by leastsquares method. QR decomposition by GramSchmidt orthogonalization was used to compute the inverse matrix.
 Technologies

 SelfOrganizing Map
 ESOM
 Kmeans
 GramSchmidt
 QR Decomposition
 Java
Circuit layout diagram visualization software for reconfigurable devices  development
We have developed the software to create and visualize the layout diagrams of largescale circuits for reconfigurable devices.
Basic circuit layouts (basic tiles), which serve as the unit circuit, can be multiplied in a variety of placement patterns to create largescale circuit layouts. In addition, it is possible to search for circuit elements and find the corresponding wiring based on the wiring length and display it in the center of the view. Also, the software provides other functions to meet your research objectives, such as color highlighting of circuit elements to visualize the crowdedness of placement and routing in terms of the entire layout.
In order to draw largescale circuit layout diagrams at a high speed, we implemented it using the Java OpenGL (JOGL) library.
 Technologies

 Reconfigurable device
 FPGA
 Visualization
 Java
 C++
 OpenGL
Sound propagation calculation  software development
For a single sound source, we have developed a program that calculates the difference between the Aweighted sound pressure level of the reference point and the sound receiving point for each frequency. By visualizing the calculation results, it is possible to evaluate diffraction effects and road surface effects in the noise propagation from the road to the areas along the road.
In graphing the difference in sound pressure levels at different frequencies from the calculation results, we discovered an error in the calculation process of relative complex sound pressure that had been used.
 Technologies

 Sound Propagation
 Complex Claculation
 Numerical Integration
 C#
Surface variation in threedimensional euclidean space  numerical experiment application development
This system performs numerical experiments on boundary problems.
Functions for mapping polar coordinates to 3dimensional space can be entered in text format, and initial conditions for surfaces can be freely set. In addition, the conditions for numerical experiments can be freely changed, allowing a variety of experimental cases to be performed.
The surfaces on the screen can be viewed from any viewpoint by mouse operation. In addition, the progress of surface changes in numerical experiments can be replayed and animated.
Numerical computation and realtime 3D surface rendering are performed in native language for high speed. By adopting C++ and Java as implementation languages which have low environmental dependency, we developed both Mac OS X and Windows versions at low cost.
 Technologies

 Boundary Problem
 Numerical Experiment
 C++
 Java
 JNI
 OpenGL
 OpenCV
Parallelization of algorithms with parallel programming models
We developed software that runs efficiently in a multiprocessor environment by parallelizing programs that previously ran on a single CPU.
OpenMP is used for shared memory type parallelization and MPI for distributed memory type parallelization to achieve parallelization suitable for the execution environment.
 Technologies

 C++
 OpenMP
 MPI
 Parallel Programming Model
Research software enhancement and multiplatformization
We have enhanced the functionality of the research software for the Windows environment and made it multiplatform with the Java framework.
Threedimensional functions that rely on OpenGL were ported using JOGL. At the same time, the software's numerical simulation capabilities were extended.
 Technologies

 Java
 VB6.0
 OpenGL
 JOGL
 C
 C++
 Windows
 Mac OS
 Linux Numerical Simulation
Phase recovery algorithms for coherent xray analysis  implementation and acceleration
We implemented and accelerated the phase recovery algorithm for diffraction analysis using coherent Xrays produced at SPring8 and other beamlines.
Several algorithms, based on holography and other technologies specified by the customer, were implemented.
In terms of algorithm acceleration, the phase recovery algorithm used by the customer was parallelized on CPUs and GPUs. As a result, the analysis process, which used to take several hours, can now be processed in a few minutes.
 Technologies

 C/C++
 OpenMP
 CUDA
 Python
 XRay Diffraction
 Beam line
 Phase Recovery
Computational software for tomographic image reconstruction using GPGPU  development
Tomography, derived from the Greek word "tomos" meaning "to cut," is a technique for observing cross sections of a sample to evaluate its interior. CT, in CT scans performed in hospitals, is an abbreviation for Computerized Tomography, an examination technique that uses Xrays to capture crosssectional images of the body. The crosssectional image obtained in this way is called a tomographic image.
To reconstruct a tomographic image, it is necessary to calculate the scattering of a quantum beam penetrating a sample. In this case, we have streamlined and implemented the algorithm used for this calculation, and developed calculation software to generate the parameter space required for reconstruction.
The implemented algorithm uses a computer GPU to perform parallel computation of sparse matrices at high speed. As a result, highresolution processing that was previously impossible due to memory limitations can now be computed in about one minute.
 Technologies

 Tomography (ART)
 GPGPU
 Sparse Matrix
 OpenGL
Numerical analysis software development and theoretical analysis of superconducting circuits
We have developed numerical analysis software for basic research on circuit quantum electrodynamics. We also performed theoretical analysis to clarify the characteristics of superconducting circuits.
This numerical analysis software calculates the distribution function and calculates and outputs physical quantities such as specific heat when the Hamiltonian parameters of a superconducting circuit are entered.
In the theoretical analysis, parameters were added to the equations used in the numerical analysis to increase the degrees of freedom and provide a more general derivation.
 Technologies

 Numerical Analysis
 Quantum Mechanics
 Statistical Mechanics
 Circuit Quantum Electrodynamics
 MATLAB
Machine translation algorithms  R&D
We developed an algorithm to improve the accuracy of Neural Machine Translation (NMT) by combining the results of statistical machine translation for input sentences that are difficult to be translated with high accuracy.
We also implemented training and evaluation pipelines for neural machine translation and statistical machine translation. In addition, we developed and performancetuned an algorithm for aligning clauses to check for missing translations.
 Technologies

 GIZA++
 NMT
 Statistical Machine Translation
 SentencePiece
 Attention
Automatic summarization algorithm  R&D
We developed an algorithm for automatic summarization which is effective for documents in domains where a characteristic style of writing is used.
Specifically, multiple algorithms were selected for each of the two main approaches to automatic summarization  extractive and generative summarization  and a training and evaluation pipeline was implemented.
 Technologies

 Extractive Summarization
 Abstractive Summarization
 BertSum
 LexRank
 Deep Language Models
Document classification algorithms  R&D
We classified documents in a corpus with a small sample size compared to a large number of categories.
Due to the low accuracy of the usual supervised learning approach, a similaritybased approach was adopted. In selecting the best approach, several methods for generating document vectors were implemented and tested.
 Technologies

 BERT
 Word2Vec
 fastText
 GloVe
 SIF
 TFIDF
 SCDV
 Sentence2Vec
 Doc2Vec
 Gensim
 Universal Sentence Encoder
 Sentence BERT
Question answering from largescale unstructured data using LLM  R&D
We built a system that enables question answering on large unstructured data without finetuning, using a largescale language model, and evaluated its accuracy.
 Technologies

 GPT4
 LangChain
 LlamaIndex
 incontext learning
 embedding
 Semantic Search
Webembedded 3DCG editor  development
We developed a system using Java3D that allows users to easily edit 3D animations from a web browser using a Java applet.
Animation data can be saved as its own file format, which is compatible with VRML and can import and export VRML files. This allows you to animate 3D characters exported from common 3D modelers. However, VRML animations exported from 3D modelers are sometimes described as vertex morphing rather than affine transformations of parts. Morphing cannot be supported by this webembedded sytem due to the increased data size.
To solve this problem, we developed an algorithm that approximates morphing animation to an affine transformation by leastsquares estimation.
 Technologies

 Java Applet
 Java Swing
 Java3D
 VRML
 Numerical Computation
Web information guidance system using ontology  development
This system uses an ontology (knowledge data structure) obtained through web mining to provide web information guidance. You can efficiently browse information, terms, links, reputations, metaphors, and episodes related to a specific topic and answer questions in natural language. It is equipped with a 3D character agent, which behaves in a specific way and speaks in response to the user's actions. Speech is automatically synthesized by commercially available texttospeech software, with a highly interactive and friendly interface using Ajax.
 Technologies

 Ontology
 Knowledge Processing
 Natural Language Processing
 Speech Synthesis
 C++
 PHP
 Ajax
3DCG display system using natural language processing  development
We developed a Java applet in Java3D for editing 3D animations in the browser.
The server stores the modeling files of the 3D characters. The Java applet connects to the server and fetches the 3D characters, allowing the user to easily create 3D animations with the mouse. This system performs 3D rendering on the web server and displays it as an animated GIF image in the browser.
 Technologies

 Java Applet
 Java Servlet
 Java3D
 Natural Language Processing
Educational systems using natural language processing  development
This system provides users with educational content in natural language. A natural language database and animation data are located on the server side, and asynchronous communication from the browser enables realtime communication with the server to provide interactive content to users.
 Technologies

 Natural Language Processing
 Servlet
Natural language processing for Twitter timelines  technical survey
Surveyed application cases of natural language processing for Twitter timelines and the use of the processed results.
Published papers were surveyed and a list of implementers, purpose of implementation, analysis methods, and tools/libraries used was summarized in the report.
 Technologies

 Natural Language Processing
 Python
Remote control system for simultaneous measurement by multiple PCs  development
Measurement equipment generally comes with dedicated measurement software, and a PC is generally prepared for each device for measurement. In order to perform multimodal measurement using multiple measurement devices, it is necessary to prepare multiple PCs and operate the measurement software installed on each PC.
Therefore, we developed a remote control system that remotely sends commands to start and end measurements from a management PC and operates the measurement software according to the commands received by each measurement PC.
AutoIt was used to operate the measurement software on the PCs, and PsExec was used to send commands remotely, enabling remote control of four PCs over a wireless LAN. We have also developed an interface for sending commands that can be flexibly adapted to increases or decreases in the number of measurement devices and PCs used for measurement.
 Technologies

 Remote Control
 Multimodal Measurement
 PsExec
 AutoIt
 RPA
 C#
Zigbee wireless sensor network monitoring system  development
This system receives measurement data from various sensors connected to a Zigbee specification wireless chip and monitors the data on a PC screen while operating various hardware via a control board.
For example, a cleanroom monitoring system uses sensors to measure temperature, humidity, static electricity, and particle volume in a cleanroom and transmits the data to a PC via a Zigbee wireless chip. The PC can display and monitor that sensor data. If the data meets certain conditions, the system determines that it is not clean and turns on a warning light or adjusts the fan air volume via the control board.
Other developed systems include one that detects earthquakes by receiving data from acceleration sensors installed in buildings and another that regulates CO2 concentration by controlling fans by receiving CO2 concentration in plant cultivation greenhouses.
 Technologies

 Zigbee Wireless Chip
 Serial Communication
 DIO Board Control
 C#
Validation of the accuracy of a realtime situation assessment model using timeseries sensor data  application development
We have developed an application that analyzes timeseries data measured by physical sensors, estimates a prediction model to determine the situation in real time, and verifies the accuracy of the prediction.
Situation judgments were made using binary values. To learn to judge the situation, we set a threshold value for the frequency distribution of each sensor data and developed a annotation support application to classify positive and negative cases.
We estimated two types of situation judgment prediction models: a logistic regression model and an SVM learning model. In order to verify the prediction accuracy of the situation judgment prediction model, we developed an application that synchronizes sensor data with corresponding video data, and visually verified the prediction accuracy in real time.
 Technologies

 R
 C++/CLI
 Feature Selection
 Logistic Regression
 SVM
 Cross Validation
Multisensor simultaneous measurement management system for human body  development
This system attaches various types of sensors to the human body for simultaneous measurement and examines the timeseries relationship of the data.
To prevent inaccurate measurements due to CPU load, a PC is installed for each sensor to perform measurements, and a server program for remote control is run on that PC. This server program receives requests from the measurement management PC and controls the sensor via the sensor's device API. The measured data is temporarily recorded on each PC, and the measurement management PC can collect the data, display graphs, and analyze the data.
 Technologies

 Biomedical Measurement
 Motion Capture
 Remoce Control
 C++
Medical support image processing system  development
We have developed a system to automatically detect abnormal tissue areas from HEstained tissue images.
In this field, pattern matching methods have been mainly used, but instead of using this, we adopt a method that uses topological geometry to extract image features.
Compared to similar systems, the processing speed is significantly improved.
 Technologies

 C#
 Histogram Processing
 Peak Extraction Algorithm
 Labeling Algorithm
 Shape Extraction Process
 Convolution Integral
 Histogram Correction
 Automatic White Balance Correction Algorithm
 Color Deviation Automatic Correction Algorithm
Layer discrimination method for tomographic image  R&D
In a 3D tomographic image consisting of multiple layers, we developed a method to discriminate the layer to which each image belongs.
This method is divided into a learning step and an estimation step.
In the learning step, the relationship between image features and layers is learned using support vector regression, a type of machine learning technique, to create a model.
In the estimation step, features are extracted from the image whose layer is to be discriminated and fed to a trained estimation model to estimate the layer to which the image belongs.
The above series of methods were implemented in Python.
 Technologies

 Image Analysis
 Python
 OpenCV
 Machine Learning
 Support Vector Regression
Estimating environmental conditions using metagenomic Data  R&D
We developed a method for estimating environmental conditions using information on microbial communities obtained from metagenomic data acquired using nextgeneration sequencers.
In this work, we create regression models (Lasso regression and support vector regression) to estimate environmental conditions based on the abundance of each microorganism.
In addition, to forecast future microbiota, we created regression models that estimates species abundance of the following month based on data from a given month.
We used Python for the above work.
 Technologies

 Metagenomics
 Machine Learning
 Lasso regression
 Support Vector regression
 Python
Medical data analysis and modeling  research support
 Technologies

 Python
 Stan
 TensorFlow Probability
 Probabilistic Programming
 Variational Inference
 MCMC
Stochastic process estimation algorithm  porting development
 Technologies

 Stochastic Process
 PseudoLikelihood
 R
 Python
Statistical causal inference algorithms  development
 Technologies

 Causal Inference
 Hierarchical Bayes
 Confounding
 MCMC
 Variational Bayes
 Hamiltonian Monte Carlo
Price prediction model using quantile regression  development
A model has been developed to predict the resale price of products with large value fluctuations over time.
Data on product attributes and data on the auction history of products were used to develop the model.
By using quantilepoint regression models, the output from the model is not a single predicted value of resale price, but a predictive distribution.
The predictive distribution of resale prices can be used to optimize purchase prices. It can also identify highrisk, highreturn transactions, as the predictive distribution contains certainty information. This can also help determine whether resale price forecasts should be transferred from the AI to an expert (called the reject option).
 Technologies

 Quantile Regression
 Decision Making
 Demand Function
 Optimal Bidding
Observer evaluation support software using item response theory  development
We developed an observational assessment support software that can take into account the rater's level of severity by using item response theory.
Severity refers to the strength of the rater's tendency to rate the performance strictly (or leniently).
This software consists of an evaluation tool and a management tool.
Assessment tools are software used to assess a subject, which takes into account the severity of the evaluator's own severity and allows for a common scale that is independent of the evaluator.
Management tools can create evaluation tools with parameters tuned to take into account the severity of the evaluator, using a statistical model that takes severity into account. It can also quantitatively determine whether each evaluator is able to evaluate from the same perspective as the other evaluators. Using the results of this analysis, licences can be issued to give access to the evaluation tool to evaluators whose evaluations meet the criteria for quality.
 Technologies

 Python
 Item Response Theory
 Rasch Model
 Social Psychology
 Psychometric Scales
 Bayesian Models
 Multiple OS
 JAX
 AMPS
Economic simulation result visualization program  development support
 Technologies

 GitHub
 R
 Shiny
 ggplot2
 Package Release
 Open Source
 Travis CI
Factor analysis for data with missing values  R&D
 Development Environment and Technical Field

 Multiple Imputation Method
 Structural Equation Modeling
 Factor Analysis
 Principal Component Analysis
State estimation program using unscented Kalman filter and particle filter  development
 Development Environment and Technical Field

 C++
 Unscented Kalman Filter
 Particle Filter
 State Space Model
Sensory evaluation program for gemstones  research and development
 Technologies

 Machine Learning
 Image Processing
Realtime object recognition agent system  development
 Technologies

 Local feature
 Octree
 Complex background
 C++
Highspeed detection of obstacles when traveling with moving objects  R&D
As an assistive technology to help moving objects avoid hazards during automatic driving, we have developed an algorithm to detect obstacles at high speed from images acquired by a camera in the direction of travel.
The algorithm had two requirements
(1) High speed processing
(2) Ability to adapt to changing daylight and lighting conditions
The algorithm used was the grid partitioning pattern matching method.
The pattern matching algorithm implements logic to find robust correlation coefficients for illumination change, shape deformation, and magnification change.
This has confirmed that obstacles can be detected at high speed even in situations where daylight and proving conditions change.
 Technologies

 Zero Mean Normalized Crosscorrelation
 Incremental Code Correlation
 C/C++
 C#
Consulting for the introduction of deep learning techniques
We provided technical consulting on deep learning to a client who was considering introducing deep learning technology to a new business.
The content of the consulting services centered on practical training that focused on practical work so that the client could independently develop deep learning technology after the consulting was completed, and tutorials were given on theory, evaluation methods, and concepts that were essential to the practical training.
In the practical training, we built a model trained on data used in customer practices and evaluated its accuracy.
The customer has since developed and commercialized deep learning technology.
 Technologies

 Deep Learning
 Technical Consulting
 Python
Face image recognition system  algorithm R&D
We developed Face Image Recognition System with cameras placed in real environments.
Roughly speaking, face recognition systems are classified in two application form: "Validation" and "Identification". Validation is used for users to identify themselves in front of door access control system. Meanwhile, identification is used for estimating identity of unspecified person from candidate list in such a system as urban monitoring.
Identification results are computed based on face image of unspecified person and validation results of the face image in candidate list It is said that identification is more difficult in general than validation. For example, because of dispersion of validation scores of each person and face feature changes by disturbances, identification results sometimes contain rejection of identical person or misidentification of person.
In this work, to improve identification accuracy, we implemented validation score normalization algorithm in C++. Also we implemented tuning tools in MATLAB which choose learning data tolerant of disturbances and image processing parameters.
 Technologies

 Biometrics
 Image Processing
 Pattern Recognition
 Statistical Analysis
 MATLAB
 C++
Face identification method based on a small number of data  algorithm development
Face recognition by deep learning often requires large amounts of labeled training data, which can be very costly. To overcome this problem, we have developed a method for face identification with a small number of samples in this work.
This method pretrains a deep network based on existing labeled data, and then transfers the feature extraction part obtained from the pretraining to the deep network for the data given the label of the person to be recognized. We have confirmed that this method can achieve a high discrimination rate even with a small amount of data.
Because training deep networks is very time consuming, multiple GPU instances were launched on AWS to evaluate discrimination accuracy for multiple network structures in parallel.
 Technologies

 Python
 Deep Learning
 finetuning
 CNN
 AWS
 GPGPU
Anomaly detection methods based on image reconstruction using deep Learning  survey and implementation
 Technologies

 Automated Visual Inspection
 Anomaly Detection
 Autoencoder
 Variational Autoencoder (VAE)
 Python
 TensorFlow/Keras
Highresolution film scanner control system  development
This system controls a highresolution film scanner capable of scanning large format film of aerial photographs with a resolution of up to 6.2 μm and converting it into digital data.
The highresolution film scanner consists of a table driven by the XY axis and a line sensor mounted on the table. Since large format film is approximately four times wider than the line sensor can capture, the entire film cannot be converted to digital data in a single scan. Therefore, this system scans the entire film in four areas, aligns each area, and combines them into a single image. If alignment lines are noticeable due to the limitations of the drive system's accuracy, they are corrected by image processing.
To increase the scanning speed per film, this system utilizes multicore CPUs for parallel processing.
 Technologies

 Line Sensor
 Serial Communication
 Motor Control
 Image Processing
 Parallel Processing
 CameraLink
 C++/CLI
 C#
Digital camera shooting system for aerial photography  development
This system is designed to take high speed interval shots with a highresolution digital camera for aerial photography and store the images on an external storage device.
In aerial photography for surveying, the speed of the aircraft and the field of view of the camera require that hundreds of images be taken at high speed intervals, but the camera itself cannot hold that much memory. Therefore, the highresolution camera used by this system distributes the Bayer array image data output by the CCD to multiple CameraLink channels and transfers it to the PC via grabber board at high speed. This system saves Bayer array image data transferred from the camera to the storage device at high speed. It also provides a preview function for test photography.
 Technologies

 CCD Bayer array
 CameraLink
 Image Processing
 C++/CLI
 C#
Trademark similarity determining algorithms  algorithm development
We worked with an international patent firm to develop a machine learning algorithm that automatically determines the similarity of designations based on examples of trademark designation examinations over the past decade.
In applying for a trademark designation, it is necessary to determine whether the designation sought to be applied for is similar to an existing one. The determination of similarity is based on experience, and can be so difficult that there are sometimes differences of opinion between patent attorneys and the JPO, which has been a factor preventing automation.
This algorithm makes it possible to evaluate similarity numerically, for example, "Amazon" and "Amason" are 80% similar, thus automating similarity judgments.
In developing the algorithm, we used the Python library TensorFlow and deep learning technologies.
Services using this algorithm were featured in a newspaper (Nikkei Sangyo Shimbun, December 26, 2016). It is expected to help reduce human costs in trademark registration and accelerate business.
 Technologies

 Python
 Deep Learning
 TensorFlow
Machine learning on sets of samples where individual labels are unknown  R&D
We developed a machine learning algorithm to estimate whether a certain number of samples of a given type are present in a large number of samples.
The underlying technique is Multiple Instance Learning (MIL), which is a learning method used when labels for a set of samples are given as supervised data. In general supervised learning, each sample needs to be labelled in advance, but it can be applied when individual samples do not have labels.
Standard MIL assumes that the presence or absence of a certain type of sample in the set is used as a label. Even if the available label is whether or not a certain number of samples of a certain species in a set are present, it can be treated as standard MIL with special preprocessing.
 Technologies

 Machine Learning
 Multiple Instance Learning
 Python
Complex problem guide system applying data mining  development
This system extracts tacit knowledge in a specific field by data mining and automatically converts it into formal knowledge. The extracted formal knowledge is used to guide beginners in the field through various problems.
Process mining, Bayesian networks, selforganizing maps, and ontology were used as data mining techniques.
In this R&D, several algorithms were surveyed in papers and selected and implemented to be effective for the purposes of this system.
 Technologies

 Java Servlet
 MySQL
 Cloud
 Process Mining
 Bayesian Networks
 SelfOrganizing Map
 Ontology
Biometric coupling hardware control system  development
We developed a research system that uses measurement data from a living body as input to operate externally connected equipment.
The system takes everchanging biological information as input and generates signals to control external devices accordingly. In this example, a control time resolution of 1 millisecond was achieved.
 Technologies

 C#
 Laser Control
 Realtime Processing
EEG measurements  experimental support
In a project to build a largescale brain activity database, we provided experimental support for measuring the EEG of a large number of subjects by installing and adjusting electrodes, recording and monitoring EEG data, and detecting and recording the causes of noise generation.
Electrode placement is the key to EEG measurement. If the electrodes are not placed properly, the measurement data will contain large noise, and accurate analysis will not be possible. Therefore, it is necessary to adjust the placement while checking the measurement data from time to time.
In addition, because EEG is a very small electrical signal, slight movements of the subject or changes in the environment can result in significant noise. In this case, too, later analysis cannot be performed correctly, so it is necessary to constantly check the measurement data, estimate what kind of noise has been mixed in, and record it.
In this way, we provided consistent experimental support from measurement preparation to recording in experiments that required experience and expertise in EEG measurement.
 Technologies

 Human electroencephalography
BMI framework  development
We have developed a brainmachine interface (BMI) framework that detects targeted brain activity from brain signals such as electroencephalogram (EEG) in real time and outputs feedback signals to operate external devices.
Since realtime performance is important for BMI, a C++ multithreading mechanism was used to minimize the delay time to feedback. The framework is designed to be flexible enough to incorporate MATLAB or Python scripts which implemented the algorithms for brain signal preprocessing and brain activity detection, depending on the experiment. The BMI also uses the lab streaming layer communication technology to provide multimodal input from multiple devices (e.g., eyetracking devices) in addition to brain signals.
 Technologies

 Brainmachine interface (BMI)
 Electroencephalogram (EEG)
 C++
 MATLAB
 Python
 Lab streaming layer (LSL)
Decoding analysis of brain activity data  R&D
Decoding analysis was performed to estimate the task being performed by the subject from electroencephalogram (EEG) data and functional magnetic resonance imaging (fMRI) data, which measure human brain activity.
A person's actions, thoughts, and stimuli to the five senses are always affecting brain activities. The decoding technique which uses machine learning technologies, has been attracting attention as a method to decipher a person's state from the data recorded in this brain activity.
In this case, we used machine learning to learn the relationship between EEG and fMRI data, which record brain activity during task execution, and the corresponding task. Using the learning results, we implemented a program to estimate the type of task from brain activity and performed decoding analysis.
EEGLAB, VBMEG, and SPM, which are standard tools, were used to analyze brain activity. The Python library scikitlearn was used for machine learning.
 Technologies

 Human brain activity analysis
 Decoding
 Machine Learning
 MATLAB
 Python
 EEGLAB
 VBMEG
 SPM
Visual stimulus presentation program  development
We have developed a visual stimulus presentation program for experiments to acquire brain activity data (EEG, fMRI, etc.) in humans and monkeys.
In this experiment, a various patterns of brain activities are recorded in response to visual stimuli by image presentation or during locomotion instructed by a text presented on a screen. In order to correctly analyze the recorded data, it is important to strictly control and manage the timing of visual presentation on the millisecond order. To develop such programs, the frameworks such as Presentation, MATLAB's Psychtoolbox, Python's PsychoPy will be generally used.
 Realization of experimental scenarios with complex stimulus presentation
 Development of the program with which the maintenance and modifications will be easier
To realize the above things, not only knowledge of the experimental field, but also expertise in programming techniques and experimental system construction will be required.
This was achieved by having an engineer with extensive experience in building experimental systems, in addition to expertise in the field of neuroscience, take direct charge of the development.
 Technologies

 Visual presentation
 Neuroscience
 Presentation
 Psychtoolbox
 MATLAB
 PsychoPy
 Python
Heart rate variability parameter calculation Android App  development
Developed an Android application that acquires data from a heart rate (pulse wave) detection device via Bluetooth communication and calculates heart rate variability parameters.
Both Bluetooth Classic and BLE standards were supported, and an autoregressive model (AR model) power spectrum density calculation method was used to calculate heart rate variability parameters.
Heart rate variability parameters calculated in real time are displayed graphically and simultaneously output to a CSV file for separate analysis and confirmation after measurement is finished. In the development process, we designed the algorithm to be easily extended and designed to be easily ported to a separate Java platform.
 Technologies

 Android
 Java
 Bluetooth Classic
 BLE
 Heart Rate Variability Analysis
 AR Model
 Time Series Analysis
BLE sensor data analysis windows application  development
We developed an application that can acquire sensor data in real time via BLE communication on Windows and analyze the data in the MATLAB environment.
Unlike iOS and Android, Windows does not support the BLE standard at the OS level, so a dedicated dongle and SDK were used to realize BLE communication.
Furthermore, to achieve realtime analysis of sensor data on the MATLAB environment, interprocess communication was used for realtime sensor data acquisition.
 Technologies

 Windows
 BLE
 MATLAB
 InterProcess Communication
 C/C++
Visualizing brain oscillatory activity using maximum entropy method  software development
We developed software that performs frequency analysis using the maximum entropy method on data obtained by optical imaging technique.
In order to capture the oscillatory phenomenon, a form of neural activity, in the brain in a spatiotemporal manner, we performed frequency analysis on the imaging data. The duration of oscillatory activity in the brain is short and the number of timeseries data obtained during oscillatory activity is small, we applied the maximum entropy method.
The following processing functions have been implemented for over 10,000 pieces of pixel data output by imaging devices.
 Photobleaching correction of voltagesensitive dyes
 FIR Filtering
 Calculation of power spectrum by maximum entropy method
 Image smoothing using a Gaussian filter
 Calculation of oscillatory power distribution at each frequency and derivation of contour plot in brain
 Deriving spectrograms of specific brain regions
 Development environment/Technical field

 FIR Filter
 Detrending
 Maximum Entropy Method
 C
Neural spike sorting  algorithm development
A widely used method for recording neural signals is to simultaneously record signals from multiple nerves (recording of population potentials). In this case, one measurement record is recorded as a composite signal of multiple neural spikes. The process of the features of each spike from the recording of the population potential and separating the spikes specific to each nerve is called spike sorting.
In spike sorting, spike amplitude and spike duration are usually used as features. To improve the accuracy of spike sorting, we developed an algorithm that compares spike amplitude and spike shape itself.
We succeeded in isolating about 10 spike types from a single nerve bundle measurement signal, and then, for confirmation, we histologically confirmed the number of nerves that the nerve bundle, and the number of isolated nerve spike types and the histologically confirmed nerve number matched well.
Finite impulse response filter (FIR)
Spike sorting results (separation of 11 types of spikes)
 Technologies

 FIR Filter
 Detrending
 Histogram
 Spline Interpolation
 Peak Detection Logic
 C
 Visual Basic
Evaluating the stimulus response of spike information  software development
We developed software that recorded population potentials and then used a sorting technique to separate each spike signal from the population potential, then clustered them by using their responsiveness to stimuli.
In this example, we gave 11 types of oscillatory stimuli. The evaluation items of the neural response to each stimulus were (1) the presence or absence of a response, (2) the dominant frequency when a constant frequency response was observed, and (3) the time variation of the dominant frequency.
The main frequency components were evaluated using the autocorrelation function. The response oscillatory characteristics were classified based on the time change of the autocorrelation function. These parameters were automatically extracted and an interface was created so that they could be passed to statistical processing software.
 Technologies

 autocorrelation function
 C
 Visual Basic
Image processing program for highspeed camera  development
We performed information extraction processing on highspeed video images that measured the behavior of insects when they were given an odor stimulus.
In highspeed photography, highintensity lights are generally used to overcome the lack of light caused by the short exposure time. However, when photographing living organisms, highintensity lights can not be used to eliminate the effects of light, and the images may be insufficient in light.
Edges were extracted from this image data using differential filtering, and optical flow was obtained using the frame difference method. This revealed the locations where insect behavior in response to odor stimuli occurs and the sequence in which it occurs.
 Technologies

 Differential Filter
 Optical Flow
 Frame Difference Method
 Highspeed Camera
 C
Ca2+ imaging data processing program  development
We developed a program that directly inputs the binary output data from the Ca2+ imaging device into the program and performs processes such as calcium indicator bleaching correction, noise filtering using a digital filter, calculation of relative light intensity change, and spatial noise filtering using a Gaussian filter and a median filter.
The processed image data was output in the same format as the Ca2+ imaging device output, allowing the use of the functions of the software that comes with the Ca2+ imaging device.
 Technologies

 Bleaching Correction
 FIR Filter
 DF/F Calculation
 Gaussian Filter
 Median Filter
 C
Digitizing and mapping system for animal behavior experiments  development
In animal behavior experiments such as the Morris water maze, this system acquires location information from video footage of the target animal (e.g., mouse) moving (digitizing), and creates a heatmap that indicates the frequency of the target animal's stay using colors based on the location information (mapping).
In digitizing, each frame of the video image is processed to detect the position of the target animal. Simple GUI operation can be used to set image processing settings for digitizing, as well as markers, color bars, and other settings related to mapping.
 Technologies

 Image Processing
 C#
 OpenCV
 Animal Behavior Experiments
Small animal behavior recording system  development
In neuroethology experiments, we have developed a system to simultaneously monitor neural activity and behavioral changes in small animals such as mice and insects.
Imaging techniques that use cameras to record the movement of a trackball are often used to measure the behavior of small animals. However, the use of inexpensive cameras with a time resolution of about 30 milliseconds makes it impossible to compare brain activity (on the order of a few milliseconds) and behavioral records, and therefore requires expensive highspeed camera systems.
This system is an inexpensive configuration that measures trackball movements with two optical mice. This enables behavioral recording with a high time resolution of up to 2 milliseconds.
 Technologies

 C#
 RawInput API
 Behavioral Measurement
 Animal Behavior Experiments
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