检索结果-内蒙古大学图书馆

A Convolutional Neural Network-based Ancient Sundanese Character Classifier with data Augmentation

Procedia computer science 2021年 179卷 195-201页

作者： Alam Ahmad Hidayat Kartika Purwandari Tjeng Wawan Cenggoro Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

With an increasing interest in the digitization effort of ancient manuscripts, ancient character recognition becomes one of the most important areas in the automated document image analysis. In this regard, we propose a Convolutional Neural Network (CNN)-based classifier to recognize the ancient Sundanese characters obtained from a digital collection of Southeast Asian palm leaf manuscripts. In this work, we utilize two different preprocessing techniques for the dataset. The first technique involves the use of geometric transformations, noise background addition, and brightness adjustment to augment the imbalanced samples to be fed into the classifier. The second technique makes use of the Otsu’s threshold method to binarize the characters and only uses the usual geometric transformations for the data augmentation. The proposed network with different data augmentation processes is trained on the training set and tested on the testing set. Image binarization from the second technique can outperform the performance of the CNN-based classifier upon the first technique by achieving a testing accuracy of 97.74%.

关键词： ancient sundanese characters convolutional neural network data augmentation document image analysis Otsu’s threshold method

来源：评论

学校读者我要写书评

暂无评论

Quantum Fourier Transform of Atrial Fibrillation

Quantum Fourier Transform of Atrial Fibrillation

引用

Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Yu-Ching Chen Chih-Yu Chen Tsung-Wei Huang Chia-Ho Ou Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan Taiwan Department of Computer Science and Information Engineering National Pingtung University Pingtung Taiwan

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Electrocardiograms (ECGs) are crucial for detecting cardiac diseases like atrial fibrillation (AF). Traditional analysis methods like fast Fourier transform (FFT) face challenges with increasing data complexity. This study uses Taipei Veterans General Hospital data to explore quantum Fourier transform (QFT) for ECG analysis. Results show that QFT effectively analyzes ECG signals, matching FFT performance while benefiting from quantum computing's efficiency.

关键词： Heart Quantum computing Fast Fourier transforms Hospitals High performance computing Atrial fibrillation Machine learning Electrocardiography Real-time systems Signal analysis

来源：评论

学校读者我要写书评

暂无评论

Convolutional Neural Networks for Scops Owl Sound Classification

引用

Procedia computer science 2021年 179卷 81-87页

作者： Alam Ahmad Hidayat Tjeng Wawan Cenggoro Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Adopting a deep learning model into bird sound classification tasks becomes a common practice in order to construct a robust automated bird sound detection system. In this paper, we employ a four-layer Convolutional Neural Network (CNN) formulated to classify different species of Indonesia scops owls based on their vocal sounds. Two widely used representations of an acoustic signal: log-scaled mel-spectrogram and Mel Frequency Cepstral Coefficient (MFCC) are extracted from each sound file and fed into the network separately to compare the model performance with different inputs. A more complex CNN that can simultaneously process the two extracted acoustic representations is proposed to provide a direct comparison with the baseline model. The dual-input network is the well-performing model in our experiment that achieves 97.55% Mean Average Precision (MAP). Meanwhile, the baseline model achieves a MAP score of 94.36% for the mel-spectrogram input and 96.08% for the MFCC input.

关键词： acoustic features bird sound classification convolutional neural network mean average precision scops owl

来源：评论

学校读者我要写书评

暂无评论

Systematic Evaluation of Cross Population Polygenic Risk Score on Colorectal Cancer

引用

Procedia computer science 2021年 179卷 344-351页

作者： Bharuno Mahesworo Arif Budiarto Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The number of findings in cancer genomics research has grown rapidly in the last decade due to the decline in the cost of human sequencing and genotyping. However, the majority of the reported significant marker associated with cancer traits are based on European and East Asian population. Large population such as South Asian and South-East Asian population are under-represented in genomics research. In this study, we explored the possibility of computing a Polygenic Risk Score (PRS) of colorectal cancer on our test sample based on reported significant Single Nucleotide Polymorphism (SNP). The SNPs used to compute the risk score were collected from GWAS Central and GWAS Catalog. Significant SNPs from IC3 study were used as a benchmark. The result shows that calculating colorectal cancer risk score using reported significant marker from different population group is possible. The p-value of our statistic model shows significant differences between case and control group risk score.

关键词： Polygenic Risk Score Cross Population Colorectal Cancer

来源：评论

学校读者我要写书评

暂无评论

A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

arXiv

引用

arXiv 2024年

作者： Tang, Xiangru Dai, Howard Knight, Elizabeth Wu, Fang Li, Yunyang Li, Tianxiao Gerstein, Mark Department of Computer Science Yale University New HavenCT06520 United States School of Medicine Yale University New HavenCT06520 United States Computer Science Department Stanford University CA94305 United States Program in Computational Biology & Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics & Biochemistry Yale University New HavenCT06520 United States Department of Statistics & Data Science Yale University New HavenCT06520 United States Department of Biomedical Informatics & Data Science Yale University New HavenCT06520 United States

Artificial intelligence (AI)-driven methods can vastly improve the historically costly drug design process, with various generative models already in widespread use. Generative models for de novo drug design, in particular, focus on the creation of novel biological compounds entirely from scratch, representing a promising future direction. Rapid development in the field, combined with the inherent complexity of the drug design process, creates a difficult landscape for new researchers to enter. In this survey, we organize de novo drug design into two overarching themes: small molecule and protein generation. Within each theme, we identify a variety of subtasks and applications, highlighting important datasets, benchmarks, and model architectures and comparing the performance of top models. We take a broad approach to AI-driven drug design, allowing for both micro-level comparisons of various methods within each subtask and macro-level observations across different fields. We discuss parallel challenges and approaches between the two applications and highlight future directions for AI-driven de novo drug design as a whole. An organized repository of all covered sources is available at https://***/gersteinlab/GenAI4Drug. © 2024, CC BY.

关键词： Proteins

来源：评论

学校读者我要写书评

暂无评论

Deep-learning triage of 3D pathology data for improved disease detection while reducing pathologist workloads

Deep-learning triage of 3D pathology data for improved disea...

引用

Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics

作者： Gao, Gan Wang, Fiona Brenes, David Song, Andrew H. Chow, Sarah S.L. Mahmood, Faisal Liu, Jonathan T.C. Department of Mechanical Engineering University of Washington SeattleWA98195 United States Department of Computer Science University of Washington SeattleWA98195 United States Department of Pathology Brigham and Women's Hospital Harvard Medical School BostonMA02115 United States Department of Pathology Massachusetts General Hospital Harvard Medical School BostonMA02114 United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA02142 United States Data Science Program Dana-Farber Cancer Institute BostonMA02215 United States Department of Bioengineering University of Washington SeattleWA98195 United States Department of Laboratory Medicine & Pathology University of Washington School of Medicine SeattleWA98195 United States

3D pathology can potentially improve disease detection, but the datasets are too large to review. We're developing a deep-learning-based triage method to identify the highest-risk 2D sections within 3D pathology d... 详细信息

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Fdm: Effective and Efficient Incident Detection on Sparse Trajectory data

SSRN

引用

SSRN 2023年

作者： Han, Xiaolin Grubenmann, Tobias Ma, Chenhao Li, Xiaodong Sun, Wenya Wong, Sze Chun Shang, Xuequn Cheng, Reynold The Northwestern Polytechnical University Xi’an China University of Southampton Southampton United Kingdom The Chinese University of Hong Kong Shenzhen China The University of Hong Kong Hong Kong HKU Musketeers Foundation Institute of Data Science Hong Kong Guangdong–Hong Kong-Macau Joint Laboratory Program 2020 China Department of Computer Science and Engineering Hong Kong School of Computer Science and Engineering China

Incident detection (ID), or the automatic discovery of anomalies from road traffic data (e.g., road sensor and GPS data), enables emergency actions (e.g., rescuing injured people) to be carried out in a timely fashion. Existing ID solutions based on data mining or machine learning often rely on dense traffic data;for instance, sensors installed in highways provide frequent updates of road information. In this paper, we ask the question: can ID be performed on sparse traffic data (e.g., location data obtained from GPS devices equipped on vehicles)? As these data may not be enough to describe the state of the roads involved, they can undermine the effectiveness of existing ID solutions. To tackle this challenge, we borrow an important insight from the transportation area, which uses trajectories (i.e., moving histories of vehicles) to derive incident patterns. We study how to obtain incident patterns from trajectories and devise a new solution (called Filter-Discovery-Match (FDM)) to detect anomalies in sparse traffic data. We have also developed a fast algorithm to support FDM. Experiments on a taxi dataset in Hong Kong and a simulated dataset show that FDM is more effective than state-of-the-art ID solutions on sparse traffic data, and is also efficient. © 2023, The Authors. All rights reserved.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Identification of Meteorological Parameters Affecting Dengue Hemorrhagic Fever Incidences

Identification of Meteorological Parameters Affecting Dengue...

引用

International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Faisal Asadi Joko Pebrianto Trinugroho Alam Ahmad Hidayat Reza Rahutomo Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665473286

Tropical disease is one of the infectious diseases that affect Indonesia. Many people die because of tropical diseases, such as dengue hemorrhagic fever (DHF), chikungunya, leprosy, lymphatic, and filariasis. The Indonesian government's lack of public policy is the main problem in treating and preventing tropical diseases. The paper aims to describe the analysis results of the incidence of DHF in Jakarta, Indonesia. The analysis used the DHF incidences data from the Jakarta Health service surveillance office representative and combined it with the meteorological parameters data. The meteorological parameters were collected from the Bureau of Meteorological Climatology and Geophysics (BMKG). The statistical analysis of this research used Pearson's correlation. The results show that the meteorological parameters affecting DHF incidences are temperature, humidity, and wind speed.

关键词： Correlation Statistical analysis Wind speed Surveillance Multimedia systems Sociology Humidity

来源：评论

学校读者我要写书评

暂无评论

A Design of Childhood Stunting Assessment Feature with Agile UX Approach

A Design of Childhood Stunting Assessment Feature with Agile...

引用

HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Reza Rahutomo Anzaludin Samsinga Perbangsa Faisal Asadi Rudi Nirwantono Bens Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665476652

multidisciplinary collaboration between public health, system engineering, and UX is able to generate a solution in healthcare problem like stunting. The principle of Agile UX gathers requirements to generate an application design. Currently, various website and mobile applications are available to be utilized for stunting research. StuntingDB is one of many web-based applications that specialized in stunting data management. The application required several types of users to operate hierarchically. This research focused on Public Health Officers’ workflow that require a solution to in the form of assessment module for stunting DBMS by using Agile UX principle. The method collaborates agile team and UX team to solve Public Health Officer's difficulty in changing stunting status at pre-saved child patient's profile. Collaboration of both agile team and UX team successfully proposed an application design that system design.

关键词： Human computer interaction Pediatrics Collaboration Companies Mobile applications Public healthcare System analysis and design

来源：评论

学校读者我要写书评

暂无评论

The Technology Behind Genomic database

The Technology Behind Genomic Database

引用

International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Joko Pebrianto Trinugroho Anzaludin Samsinga Perbangsa Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453967

In this digital era, we are exposed to a large amount of data. This includes biological data, which stores information about living organisms, including Deoxyribonucleic acid (DNA), genes, and proteins. With the development of information technology and information system, most of available biological data are stored in an online public database. Many of the databases are free-access and easily used, which helps the users, especially researchers, to make use of the data. Among the known public biological databases are the University of California Santa Cruz (UCSC) Genome Browser database and the Rat Genome database (RGD). These two databases provide access to the biological data from different organisms. This paper aims to describe the technology of public biological databases. Also elucidated in this paper are the differences features between UCSC Genome Browser database and the RGD. Our results showed that the UCSC contains much more biological data and features than the RGD. However, the genome browser of UCSC has a complex display, while the RGD has a simple display. Overall, both databases give the users the option to choose the most suitable database for them.

关键词： Proteins databases Genomics DNA Rats Biology Organisms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：