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14th International Conference on information Security and Cryptology, ISCTURKEY 2021

作者： Cetinkaya, Alper Emin Akin, Murat Sagiroglu, Seref Gazi University Information Security Program Ankara Turkey Gazi Ai Center of Gazi University Basarsoft Information Systems Inc. Ankara Turkey Gazi University Gazi Ai Center Computer Engineering Dept. Ankara Turkey

ISBN: (纸本)9781665407762

Federated Learning (FL) is a suitable solution for making use of sensitive data belonging to patients, people, companies, or industries that are obligatory to work under rigid privacy constraints. FL mainly or partially supports data privacy and security issues and provides an alternative to model problems facilitating multiple edge devices or organizations to contribute a training of a global model using a number of local data without having them. Non-IID data of FL caused from its distributed nature presents a significant performance degradation and stabilization skews. This paper introduces a novel method dynamically balancing the data distributions of clients by augmenting images to address the non-IID data problem of FL. The introduced method remarkably stabilizes the model training and improves the model's test accuracy from 83.22% to 89.43% for multi-chest diseases detection of chest X-ray images in highly non-IID FL setting. The results of IID, non-IID and non-IID with proposed method federated trainings demonstrated that the proposed method might help to encourage organizations or researchers in developing better systems to get values from data with respect to data privacy not only for healthcare but also other fields. © 2021 IEEE.

关键词： Sensitive data

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International Conference of Computer and Informatics engineering (IC2IE)

作者： Wandy Wandy Kusworo Adi Media Anugerah Ayu Doctoral Program of Information Systems School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Computer Science Faculty of Engineering and Technology Sampoerna University South Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

Full-marathon and Half-marathon distances are categorized as road running. Full-marathon running is becoming increasingly popular, and Half-marathon is increasing worldwide in both sexes and all age groups. Some aspects might relate to Full-marathon and Half-marathon running performance during training and races. Technology also plays an essential role in supporting runners and running races. Technology like artificial intelligence (AI) now supports the running athlete, not only predicting performance and results. It can also be used later to help the coach generate training programs for the athlete. This research aimed to find many aspects of marathons and performance and analyze them to see if artificial intelligence could later support them. It used secondary data and a systematic literature review proposed by Kitchenham. Out of the 58 articles, 21 of them (36.21%) received a score of 1 from Q1. Additionally, 19 articles (32.76%) received a score of 1 from both Q2 and Q3. Among the 58 articles, 9 (15.52%) received a total score of 3, with all three Q1, Q2, and Q3 scores being 1. This indicates that artificial intelligence will likely support the content of these nine articles. Several factors were also discovered to be connected to marathons and athletic performance. These findings suggested that additional investigation into marathons and performance, later backed by artificial intelligence, remained pertinent and essential.

关键词： Training Roads Artificial intelligence Informatics

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Rotational Regrasping For a Stick-type Object Using Inertial Force Based on High-speed Swing-up Motion

Rotational Regrasping For a Stick-type Object Using Inertial...

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IEEE International Conference on Robotics and Biomimetics

作者： Taku Senoo Atsushi Konno Hayato Otsubo Idaku Ishii Course of Systems Science and Informatic Graduate School of Information Science and Technology Hokkaido University Sapporo Hokkaido Japan Smart Innovation Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Japan

In this paper, robotic regrasping is considered with the goal of achieving dexterous manipulation. The strategy using quick wrist snap is based on human regrasping, and involves rotating the grasped object due to the inertial force while maintaining the contact state. The posture of the grasped object is measured by high-speed vision in real time and is used for posture control. Experimental results are shown where regrasping of a stick-type object in the direction contrary to gravity can be achieved by a high-speed robot hand.

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A Study of the Ecological Dynamics of Batumi, on the Black Sea Coast, Analyzing Environmental Factors and Their Impact

A Study of the Ecological Dynamics of Batumi, on the Black S...

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International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Lily Petriashvili Irine Khomeriki Mzia Kiknadze Tamar Lominadze Nona Otkhozoria Dept. of Program Engineering Georgian Technical University Tbilisi Georgia Dept. of Interdisciplinary Informatics Georgian Technical University Tbilisi Georgia Dept. of Computer Engineering Georgian Technical University Tbilisi Georgia Dept. of Information Systems Georgian Technical University Tbilisi Georgia Dept. of Microprocessor and Measurement Systems Georgian Technical University Tbilisi Georgia

ISBN: (数字)9798350351859

ISBN: (纸本)9798350351866

This paper studies the complex ecological dynamics of Batumi on the Black Sea coast, through adetailed analysis of environmental factors and their impact. We use Business Intelligence (BI) methods to explore the complex interactions between natural and human impacts on the local ecosystems. By using data-focused approaches, including statistical analysis and predictive modeling, we aim to distinguish patterns and trends in ecological dynamics. This study aspires to make clear the complex relationships between environmental factors such as climate change, pollution levels, habitat degradation, and biodiversity loss, and their impacts on the coastal ecosystem of Batumi. Through this study, we aim to provide valuable information on sustainable management practices and conservation measures to protect the ecological integrity of this important coastal region.

关键词： Sea coast Pollution Statistical analysis Ecosystems Habitats Sea measurements Predictive models

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IoT human needs inside compact house

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Journal of Open Innovation: Technology, Market, and Complexity 2023年第1期9卷 1-9页

作者： Azis, Baskoro Ong, Ardvin Kester S. Prasetyo, Yogi Tri Persada, Satria Fadil Young, Michael N. Sari, Yanuarita Kusuma Permata Nadlifatin, Reny Interior Design Department School of Design Bina Nusantara University Jakarta 11480 Indonesia School of Industrial Engineering and Engineering Management Mapua University Manila 658 Muralla St. Intramuros Manila 1002 Philippines Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta 11480 Indonesia Communication Science Department Faculty of Digital Communication and Hotel & Tourism Bina Nusantara University Jakarta 11480 Indonesia Department of Information Systems Institut Teknologi Sepuluh November Kampus ITS Sukolilo Surabaya 60111 Indonesia

Indonesia is entering Industry 4.0, but is still not using supportive technology, especially in residential areas. A compact house is one of the dwellings built on limited modern land, providing flexible use of space according to the activities carried out by residents. The current version of this type of residence, namely smart homes, is still far from what is expected. There is a need for the modern use of IoT in every room, which can adapt to the activities of residents to make it easier for residents to move. A grounded theory and descriptive approach was used to find the continuity of modern Industry 4.0 and IoT technology in smart homes with the compact house concept to find the novelty of design standards. The findings are in the form of lighting that can be adjusted via IoT to reduce the crime rates in abandoned homes or in homes that are not active because the residents are traveling. © 2023 The Authors

关键词： Activity Compact house IoT Light Smart home

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A Comparison Diagnosis Algorithm for Conditional Fault Local Diagnosis of Multiprocessor systems 25th

A Comparison Diagnosis Algorithm for Conditional Fault Loca...

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25th International Computer Symposium on New Trends in Computer Technologies and Applications, ICS 2022

作者： Lv, Yali Lin, Cheng-Kuan Hsu, D. Frank Fan, Jianxi School of Information Technology Henan University of Chinese Medicine Zhengzhou China Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Computer Science and Information Engineering Chung Cheng Institute of Technology NDU Taoyuan City Taiwan Department of Computer and Information Science Fordham University New York United States School of Computer Science and Technology Soochow University Suzhou China

ISBN: (纸本)9789811995811

An efficient diagnosis is very important for a multiprocessor system. In this paper, we present a (α, β) -trees combination S(u, X, α, β) and give some conclusions about the local diagnosis. Based on the (α, β) -trees combination, we give a conditional fault local diagnosis algorithm to identify the fault or fault-free status of each processor correctly under the MM ∗ model when the number of faulty nodes does not exceed α+ 2 β- 3 and every node has at least one fault-free neighboring node. According to our results, a connected network with a (α, β) -trees combination S(u, X, α, β) for a node u is conditionally locally (α+ 2 β- 3 ) -diagnosable at node u and the time complexity of our algorithm to diagnose u is O(α2β+ αβ2). As an application, we show that our algorithm can identify all the faulty nodes of n-dimensional star graph Sn if the faulty node number does not exceed 3 n- 8. Compared with existing algorithms, our algorithm allows more faulty node in a multiprocessor system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computational complexity

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Performance Evaluation of Multi-ONU Customers Access Network using Spectrum Slicing and Duplication Techniques 5

Performance Evaluation of Multi-ONU Customers Access Network...

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5th International Conference on Emerging Electrical Energy, Electronics and Computing Technologies, ICE4CT 2024

作者： Rahman, Juwairiyyah Abdul Mugunthan, Sivaguru A.L. Hassan, Hasliza Abu Muslim, Norliana Ab-Rahman, Mohammad Syuhaimi Department of Electrical Engineering Faculty of Engineering and Life Sciences Universiti Selangor Selangor Bestari Jaya45600 Malaysia Department of Computer and Communication Technology Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Perak Kampar31900 Malaysia Department of Electrical Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Malaysia Electrical and Computer Engineering Program Faculty of Engineering Sohar University PC:311 Sohar Oman

This study aims to increase the number of access users by limiting the sample size to 30 users while ensuring that every Optical Network Unit (ONU) receives data from the Optical Line Terminal (OLT). The proposed solution allows for the determination of power requirements at each ONU based on bus-star topologies, facilitating an increase in user capacity. The power received by each ONU is a critical parameter that system designers must consider when planning the implementation of Fiber to the Home (FTTH), as it impacts the output data in terms of Bit Error Rate (BER) and Signal Quality Factor (QF) for each user. Various parameters were evaluated to ensure that the enhanced network improves scalability while adhering to standard specifications. These parameters included the Q-factor, BER, eye diagram, user count, and received power. The study employed slicing and duplication techniques, utilizing Arrayed Waveguide Grating (AWG) for signal duplication and Wavelength Division Multiplexing for signal slicing. The simulations were conducted using a transmitter operating at a frequency of 1491 nm with a power output of 0 dBm, utilizing the latest version of OptiSystem 20 software. The results highlighted the system's capability to support a total of 73,728 users, meeting stringent performance criteria. Specifically, the system achieved a Q-factor greater than 6, indicating high signal quality, and a bit error rate (BER) lower than 1 × 10-9, ensuring reliable data transmission. For the sampled 30 users, the average Q factor was 8.1527, and the average BER was 5.3648 × 10^-11, with an output power level of -54.278 dBm. Despite an increase in users, the quality of the data supplied to clients remained unchanged. These outcomes underscore the robustness and efficiency of the design in delivering high-capacity, error-resilient optical communication. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Q factor measurement

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Improvement of Spatial Ambiguity in Multi-Channel Speech Separation Using Channel Attention

Improvement of Spatial Ambiguity in Multi-Channel Speech Sep...

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2021 Asia-Pacific Signal and information Processing Association Annual Summit and Conference, APSIPA ASC 2021

作者： Hong, Qian-Bei Wu, Chung-Hsien Nguyen, Thanh Binh Wang, Hsin-Min National Cheng Kung University and Academia Sinica Graduate Program of Multimedia Systems and Intelligent Computing Tainan Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan Taiwan

ISBN: (纸本)9789881476890

Multi-channel speech separation has been successfully applied in a complex real-world environment such as the far-field condition. The common solution to deal with the far-field condition is using a multi-channel signal captured by a structured microphone array and leveraging the inner difference between channels to enhance the speech separation performance. The spatial feature has been widely used in recent speech separation research. This feature appears to be insufficient when the location information becomes ambiguous. This is known as the spatial ambiguity problem. In order to deal with the spatial ambiguity problem, this study proposes an attention mechanism for the Temporal-Spatial Neural Filter (TSNF), in which the channel attention on merged features and the feature map of 1D convolution block in the temporal convolution network is proposed. The proposed method is evaluated on the multi-channel reverberant dataset which is built based on the WSJ0-2mix dataset. The dataset is simulated in the real-environment room by using the Room Impulse Response generator. In the experimental results, the proposed methods produced the SI -SNR improvement of about 1.2dB in close speakers' case, while a small decrease of 0.1dB in other cases. © 2021 APSIPA.

关键词： Convolution

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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International Seminar on Application for Technology of information and Communication (ISemantic)

作者： Jasmine Iswarini Dyah Prabandari Christy Atika Sari Eko Hari Rachmawanto Candra Irawan Bilal R. Altamer Mohamed Ayad Alkhafaji Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Study Program in Information Systems University of Dian Nuswantoro Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq Department of Computer Science National University of Science and Technology DhiQar Iraq

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant.

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AI-Powered Precision: Revolutionizing Skin Cancer Detection with Advanced Machine Learning

AI-Powered Precision: Revolutionizing Skin Cancer Detection ...

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Novel Intelligent and Leading Emerging Sciences Conference (NILES)

作者： Mariam M. Abd-elaziz Basma M. Elshafie Hagar Abdullah Karen Y. Gerges Ingy A. Ghanem Khaled M. Fouad Amir El-Ghamry Ibrahim F. Moawad Sara El-Metwally Faculty of computer science and engineering New Mansoura university Dakahlia Egypt Faculty of Engineering Computer and Communication program Faculty of Computer Science and Engineering Mansoura University New Mansoura University Information Systems Faculty of Computers and Artificial Intelligence Benha University Egypt Faculty of Computer and Information Sciences Faculty of Computer Science and Engineering Mansoura University New Mansoura University Egypt School of Engineering and Computer Science University of Hertfordshire GAF Egypt Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Department of Artificial Intelligence College of Computer Science and Engineering Taibah University Medina Saudi Arabia

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

Skin cancer's increasing incidence rates necessitate advanced diagnostic tools. This research uses MobileNet architecture to develop an enhanced system for skin cancer detection. MobileNet's efficient CNN architecture, combined with Keras for model lifecycle management and TensorFlow for real-time inference, forms the foundation of this study. Using 10,015 dermatoscopic pictures from seven different classifications of skin cancer in the HAM10000 dataset, the methodology includes several key stages: image preprocessing to correct illumination and adjust resolution, data augmentation to balance the dataset, and model training using Transfer Learning. The MobileNet model was trained over 50 epochs with a comprehensive architecture incorporating multiple specialized layers. By combining large-scale data analysis and adaptive learning, this methodology demonstrates The revolutionary possibilities of AI and ML in improving skin cancer diagnostics and public health outcomes. Keywords Skin Cancer Detection, Dermatoscopic Images, Machine Learning, Deep Learning

关键词： Training Deep learning Adaptation models Image resolution Transfer learning Lighting Real-time systems Image preprocessing Public healthcare Skin cancer

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