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5th International Conference on Variable Neighborhood Search (ICVNS'17)

Electronic Notes in Discrete Mathematics 2018年 66卷 1-5页

作者： Vitor Nazário Coelho Haroldo Gambini Santos Igor Machado Coelho Puca Huachi Vaz Penna Thays A. Oliveira Marcone Jamilson Freitas Souza Angelo Sifaleras Institute of Computer Science Universidade Federal Fluminense Niterói Brazil Grupo da Causa Humana Ouro Preto Brazil Department of Computing Universidade Federal de Ouro Preto Ouro Preto Brazil Institute of Mathematics Statitics Universidade Estadual do Rio de Janeiro Rio de Janeiro Brazil Graduate Program of the Department of Engineering and Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Department of Applied Informatics School of Information Sciences University of Macedonia 156 Egnatia Str. Thessaloniki 54636 Greece

This volume presents selected, peer-reviewed, short papers that were accepted for presentation in the 5th International Conference on Variable Neighborhood Search (ICVNS'17) which was held in Ouro Preto, Brazil, d... 详细信息

关键词： Metaheuristics Variable Neighborhood Search Discrete Optimization Nonlinear optimization

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Internet and learning resources: A case study of the Library and information Science Students at Universitas Padjadjaran

Internet and learning resources: A case study of the Library...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer Science, information Systems, and information Technology, WMA-Mathcomtech 2018

作者： Kurniasih, Nuning Rhefhansha, Rian Fiqih Yulianti, Y. Wajdi, Muh Barid Nizarudin Sujito, S. Haluti, Armin Haimah, H. Sari, Deffi Ayu Puspito Manurung, Rosida Tiurma Mudjanarko, Sri Wiwoho Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Sekolah Menengah Pertama Islam Rajapolah Tasikmalaya Indonesia Sekolah Dasar Negeri 3 Rajapolah Tasikmalaya Indonesia STAI Miftahul Ula Nganjuk Indonesia Department of English Language Education IAIN Surakarta Surakarta Indonesia Faculty of Teacher Training and Education Universitas Muhammadiyah Luwuk Banggai Indonesia Faculty of Teacher and Education Universitas Prof. Dr. Hazairin S.H Indonesia Department of Envinronmental Engineering Universitas Bakrie Jakarta Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Narotama University Surabaya Indonesia

Student learning and reading activities today cannot be separated from internet media. This study aims to determine the benefits of information retrieval systems, the positive impacts and negative impacts of internet use and learning activities, especially those related to the student reading activities in the internet era. This study uses a case study approach with purposive sampling by selecting 20 students of class 2014 from the Library and information Science program of the Faculty of communication Sciences, Universitas Padjadjaran as the research informants. Data collection techniques were obtained through in-depth interviews, observation and literature review. The results showed that the internet became the primary source of information for most students of the Library and information Science program at the Faculty of communication Sciences, Universitas Padjadjaran. However, they still assume that the credibility of printed information sources is stronger than online information sources. This can be seen from printed books or online and electronic sources which become the results of the form of printed books being the main reference for the college assignments which are considered to be done more seriously by the informants. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey

arXiv

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arXiv 2024年

作者： Saberi-Movahed, Farid Berahmand, Kamal Sheikhpour, Razieh Li, Yuefeng Pan, Shirui Department of Applied Mathematics Faculty of Sciences and Modern Technologies Graduate University of Advanced Technology Kerman Kerman Iran Brisbane Brisbane Australia Department of Computer Engineering Faculty of Engineering Ardakan University P.O. Box 184 Ardakan Ardakan Iran School of Information and Communication Technology Griffith University Gold Coast4222 Australia

Dimensionality Reduction plays a pivotal role in improving feature learning accuracy and reducing training time by eliminating redundant features, noise, and irrelevant data. Nonnegative Matrix Factorization (NMF) has emerged as a popular and powerful method for dimensionality reduction. Despite its extensive use, there remains a need for a comprehensive analysis of NMF in the context of dimensionality reduction. To address this gap, this paper presents a comprehensive survey of NMF, focusing on its applications in both feature extraction and feature selection. We introduce a classification of dimensionality reduction, enhancing understanding of the underlying concepts. Subsequently, we delve into a thorough summary of diverse NMF approaches used for feature extraction and selection. Furthermore, we discuss the latest research trends and potential future directions of NMF in dimensionality reduction, aiming to highlight areas that need further exploration and development. © 2024, CC BY.

关键词： Matrix algebra

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Application of Interpolation Image by using Bi-Cubic Algorithm

Application of Interpolation Image by using Bi-Cubic Algorit...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer Science, information Systems, and information Technology, WMA-Mathcomtech 2018

作者： Abdullah, Dahlan Fajriana, F. Maryana, M. Rosnita, Lidya Utama Siahaan, Andysah Putera Rahim, Robbi Harliana, P. Harmayani, H. Ginting, Zainuddin Erliana, Cut Ita Irwansyah, Defi Zulmiardi, Z. Khaddafi, Muammar Milanie, Feby Aspan, Henry Huda, Ismul Saddhono, Kundharu Mulyaningsih, Indrya Moonti, Roy Marthen Parwito, P. Djanggih, Hardianto Amalia, Ainna Winarno, Edy Hadikurniawati, Wiwien Department of Informatics Universitas Malikussaleh Aceh Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia Department of Informatics Engineering Sekolah Tinggi Teknik Harapan Medan Indonesia Department of Informatics AMIK Intel Com Global Indo Indonesia Department of Chemical Engineering Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Mechanical Engineering Universitas Malikussaleh Aceh Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Universitas Syiah Kuala Aceh Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Indonesian Language Teaching Department Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia Department of Law Universitas Gorontalo Gorontalo Indonesia Department of Agrotechnology Universitas Ratu Samban Bengkulu Indonesia Department of Law Universitas Tompotika Luwuk Banggai Luwuk Indonesia Islamic Institut of Miftahul Ula Kertosono Nganjuk-East-Java Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Image magnification is one of the branches in digital image processing that is often required in various applications such as in the field of medicine, multimedia, and in satellite imagery. As technology grows, more and more methods are used for image enlargement. In this study, the image enlargement process performs by using Bi-Cubic spline interpolation method, and the result of image try to compare between the original one and picture after enlargement. © Published under licence by IOP Publishing Ltd.

关键词： Satellite imagery

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Application of WMN-HC Web Interface and NS-3 for Optimization and Analysis in WMNs Considering Different Number of Mesh Routers and Architectures

Application of WMN-HC Web Interface and NS-3 for Optimizatio...

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International Conference on Network-Based information Systems (NBIS)

作者： Algenti Lala Tetsuya Oda Admir Barolli Vladi Kolici Leonard Barolli Fatos Xhaf Faculty of Information Technologies Polytechnic University of Tirana Tirana Albania Graduate School of Engineering Fukuoka Institute of Technology (FIT) Fukuoka Japan DI - University of Salerno Fisciano Italy Department of Information and Communication Engineering Fukuoka Institute of Technology (FIT) Fukuoka Japan Dept. of Languages & Inf. Syst. Tech. Univ. of Catalonia Barcelona Spain

Wireless Mesh Networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In this work, we evaluated WMN-HC system which is based on Hill Climbing (HC) to find an optimal location assignment for mesh routers. As evaluation metrics, we used throughput, one-way delay, jitter, fairness index and residual energy. For simulations, we used ns-3 and Optimized Link State Routing (OLSR). We compare the performance of the optimized network topologies by sending multiple constant bit rate flows in the network. The simulation results show that the throughput of 24 mesh routers is higher than other number of mesh routers for both WMN architectures. The delay and jitter of 24 mesh routers is lower than other number of mesh routers. The fairness index of 16 mesh routers is higher than other number of mesh routers for Hybrid WMN architecture. For 16 mesh router, the remaining energy is higher than 24 and 32 mesh routers.

关键词： Servers information systems Electronic mail

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Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer

Predicting Microsatellite Instability from Histology Images ...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yun-Chi Chen Tung Chao Wimaya Nitya Phandita Tzu-Yu Sun Huai-Zhi Wang Yi-Hsien Hsieh Le-Yin Hsu Che Lin Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University (NTU) Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan Data Science Degree Program NTU Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.

关键词： Attention mechanisms Histopathology Computational modeling Precision medicine Small satellites Immunotherapy Colorectal cancer Predictive models Transformers Genetics

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Floor plan construction via anonymous Wi-Fi signal fragment matching

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ICIC Express Letters, Part B: Applications 2014年第4期5卷 981-987页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Wang, Zhuoran Chongqing Key Lab of Mobile Communications Technology School of Communication and Information Engineering Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nan'an Dist. Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh PA 15260 United States

Floor plan construction is the basis for fingerprint-based localization and people's activity learning, especially in the environments where the geometrical map is not available or does not exist. To this end, we propose a new received signal strength (RSS) fragment matching approach to identify the location points (LPs) in floor plan as the overlapped pieces between the fragments. Then, by means of the Smith-Waterman alignment, each LP can be recognized as a winning path in scoring space. Finally, we use the Allen's interval algebra to assemble the time-stamped LPs into a floor plan in target area. The experiments with the actual Wi-Fi RSS measurements recorded in HKUST campus demonstrate that our proposed approach performs better than the conventional K-means clustering and spectral clustering in floor plan construction. © 2014 ICIC International.

关键词： Algebra

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Computer Vision and Eyetracking Approach for Assessing Visual Disorders in Premature Infants

Computer Vision and Eyetracking Approach for Assessing Visua...

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Annual IEEE Symposium on Computer-Based Medical Systems

作者： Rodrigo Ferraz Souza Manoella Rockembach Bruna Samantha Marchi Marcelo Fernandes Costa Cristiane Aparecida Moran Antonio Carlos Sobieranski Department of Computing - DEC Federal University of Santa Catarina Araranguá Brazil Department of Health Sciences Federal University of Santa Catarina Araranguá Brazil Neurosciences and Behavior Postgrad. Program Institute of Psychology São Paulo University São Paulo Brazil Department of Rehabilitation Sciences Federal University of Santa Catarina Araranguá Brazil Department of Computing - DEC Graduate Program in Information and Communication Technologies - PPGTIC Federal University of Santa Catarina Araranguá Brazil

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

Premature infants are subjected to an elevated risk of abnormal visual development, leading to potential visual impairments such as field defects, optic nerve dysfunctions, eye movement abnormalities, and nystagmus. To mitigate these dangers, early and exact assessment is important. This paper presents a computer vision approach that uses face mapping and eye-tracking technologies to objectively and accurately assess further visual disorders in infants. Our methodology integrates eye-tracking with facial recognition techniques to quantify eye movements and gaze stability accurately. Detailed video recordings of infants responses to visual stimuli are analyzed using a custom-developed algorithm, which processes eye and head movements to generate precise metrics of visual function. The results demonstrate that our computational tool significantly enhances the diagnostic capabilities by providing quantifiable and objective metrics that supports the clinical observations, thus assisting healthcare professionals in identifying and addressing potential visual abnormalities at early stages effectively.

关键词： Measurement Visualization Pediatrics Computer vision Face recognition Visual impairment Gaze tracking

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, Computer Retrospective Study

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