Our Business
Services
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Research Paper Implementation
Implement specified research papers as software.
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Algorithm Implementation
Make modules or APIs of specified algorithms as you request.
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Development of User-Friendly Tools
We provide services to develop user-friendly application tools that can simplify a variety of data processing tasks at low cost.
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Research Software Development
Create software for academic research. We can also speed up existing software or add functionalities to existing software.
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Consigned Research Services
We can execute parts of your research, including surveying papers, developing necessary systems, validation, and preparing reports.
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Large Language Models
Develop large language models for practical applications to meet a wide range of needs, from practical applications to pure research purposes.
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Optimization Software Development
Develop optimization software to find optimal solutions to problems with various constraints.
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Automated Analysis
Using RPA (Robotic Process Automation), build systems for efficient analysis.
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Neuroscience Software Development
Develop software tailored to the needs of each individual researcher in the field of neuroscience.
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Food Science Software Development
Supports a wide range of food processing stages from experimental design to analysis of results.
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Geophysical Exploration and Nondestructive Testing
Develop software for signal processing of measurement data, simulation, and data assimilation.
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Quantum Beam Research Software Development
Develop specialized software to implement and accelerate the algorithms used in quantum beam research.
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Business Cases
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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 pre-trains a deep network based on existing labeled data, and then transfers the feature extraction part obtained from the pre-training 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.
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- Python
- Deep Learning
- fine-tuning
- CNN
- AWS
- GPGPU
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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 next-generation 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
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- Metagenomics
- Machine Learning
- Lasso regression
- Support Vector regression
- Python
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State estimation program using unscented Kalman filter and particle filter - development
- Development Environment and Technical Field
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- C++
- Unscented Kalman Filter
- Particle Filter
- State Space Model
Engineers
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- Image Analysis
- Machine Learning
- Behavioral Ecology
- Statistical Analysis
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I have conducted decision-making and collective behavior research with non-model organisms such as termites and bean beetles.
I am glad to work with you solving various research issues with the analytical skills I developed in experimental research, such as development of experimental systems, image analysis and animal tracking technology.
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- Computational Mechanics
- Computational Electromagnetics
- Structual Optimization
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I have been studying accurate, stable and fast formulations of boundary element method, its related eigenvalue solver in conjunction with the Sakurai-Sugiura ( contour integral ) method, as well as topology and shape optimization problems.
I am thus fluent in numerical solvers and their application to structual optimizations in computational mechanics and computational electromagnetics. I hope to apply my knowledge and experience with numerical methods to support customers' research and developments.
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- Data Analysis and Simulation for Food Quality
- Kinetic Analysis
- Simulations
- [Introduction]
- I have applied various analysis and simulation methods in food engineering research to improve food quality. I would be grad to employ my research experience to suggest approaches for analyzing experimental data and also to support your software needs in R&D.
Products
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Visualize correlations by high-speed partial correlation analysis with sparse structure estimation. This is useful for connectome analysis in the field of neuroscience.
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Analyzes image stacks and performs automatic counting and visualization. This is useful for analysis of confocal microscope images, etc.
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Separates and clusters spike signals from aggregate potentials of neural signals. Dramatically improves the efficiency of neurophysiology research!
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Automatically extracts location information from video footage of behavioral experiments and easily creates trajectory graphs and heat maps. No more manual work!
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Ultra-fast metagenome analysis compatible with next-generation sequencers. Rich visual functions are powerful for microbiological research and other applications! (Scheduled for release)
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News
- 2024/08/19
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We presented our services in the corporate exhibition at the 25th Annual Meeting of the Japanese Society of Food Engineering (2024), and the presentation received the Outstanding Presentation Award.
- 2024/04/08
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A Ph.D. (Science) researcher was hired.
- 2024/02/21
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Participated in Kyoto University 18th ICT Innovation Industry Briefing Session.
Contact Us
If you have any inquiry
about our company, please contact us.
(Phone hours: 10:00 - 17:00, Japan Standard Time)
+81-75-321-7300