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6th IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2024

作者： Chang, Chin-Chih Wei, Chi-Hung Hsiao, Sean Yang, Chyuan-Huei Thomas Chung Hua University Department of Computer Science and Information Engineering Hsinchu Taiwan Chung Hua University Ph.D. Program in Engineering Science Hsinchu Taiwan Chung Hua University Program in Applied Foreign Language and Smart Commerce Hsinchu Taiwan School of Information Engineering Shandong Vocational and Technical University of International Studies Shandong China

ISBN: (纸本)9798350396133

People increasingly prioritize a balanced diet to enhance well-being, yet making informed dietary choices remains challenging amidst the abundance of options. To address this, we developed a meal image recognition and healthy meal combination recommender system, integrating generative artificial intelligence (AI). Convolutional neural networks were used for precise meal image recognition to identify diverse food items. The generative AI-augmented recommendation engine offers personalized meal suggestions aligned with nutritional goals and dietary preferences, utilizing a nutrition knowledge base to ensure overall well-being. The system's feasibility was validated, illustrating its excellence in meal recognition accuracy, recommendation diversity, and user engagement. By integrating generative AI, the system shows its potential to enhance dietary recommendations and public health. © 2024 IEEE.

关键词： Generative adversarial networks

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Poultry raising light control system for laying hens and broilers 2

Poultry raising light control system for laying hens and bro...

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Pinthong, Thidarat Ganokratanaa, Thittaporn Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand

ISBN: (纸本)9798350336573

Chicken is an economic animal. one kind At present, it has been raised as a business and has expanded extensively. This is because both domestic and foreign populations have a greater demand for products and processed products from laying hens. which the raising of laying hens must be more attention to the productivity and quality of eggs in order to meet the needs of consumers with high or low temperatures Too low has an effect on the physiological system of laying hens. Reduce egg production or may result in inefficient production. And with the aforementioned problems, technology has been used to help in notifying. Warn whether the temperature in the house is suitable to increase the production of high-quality eggs. © 2023 IEEE.

关键词： Internet of things

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Home smart alarm system for the visually impaired 2

Home smart alarm system for the visually impaired

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Yimyam, Worawut Ganokratanaa, Thittaporn Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand

ISBN: (纸本)9798350336573

This research aims to study the working principles of IOT devices or Internet of Things in order to promote the use of information technology systems, both hardware and software, with visually impaired people. rehabilitation of persons with disabilities, enhancing the capacity or ability of persons with disabilities to improve their condition or or existing capabilities through the advancement of technology so that people with disabilities have the opportunity to work or live in society to the full potential of the researcher The concept of technology acceptance model (Technology Acceptance Model or TAM) to help further develop This research shows the importance of information technology systems, both hardware and software, to visually impaired people, which is the basis for product development of healthcare service businesses in the future. © 2023 IEEE.

关键词： Alarm systems

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Comparative Analysis of Tree Classifiers to Mitigate Fraud in Electronic Loan Application 2

Comparative Analysis of Tree Classifiers to Mitigate Fraud i...

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2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Yeboah, Foster Yeboah, Jones Yeboah, George Bampoh, Kofi Nyarko-Boateng, Owusu University of Cincinnati College of Engineering and Applied Science Cincinnati United States University of Cincinnati Maths Physics and Computer Science Department Cincinnati United States EProcess International S.A Information Technology Department Accra Ghana Ipmc School of It Accra Ghana University of Cincinnati School of Information Tevhnology Cincinnati United States

ISBN: (纸本)9798331529529

Loan disbursement is crucial and remains the core to every bank. With the advancement of technology and the proliferation of mobile devices financial institutions are working to bring the banking hall to the doorsteps of their clients. There are systems that allow applicants to apply for loans online. This inadvertently has enormous benefits and risks, but applicants may not be honest providing such data. To minimize risks and maximize benefits, a system for predicting fraud is necessary. This research, through experiments and comparative analysis, confirmed that data mining can effectively assess applicants' creditworthiness. The findings revealed that the Random Forest classifier produced the most robust model, offering the highest classification accuracy among the selected classifiers, with an accuracy rate of 0.7773. © 2024 IEEE.

关键词： Decentralized finance

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All-photonic artificial-neural-network processor via nonlinear optics

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Physical Review applied 2024年第1期22卷 014009-014009页

作者： Jasvith Raj Basani Mikkel Heuck Dirk R. Englund Stefan Krastanov Department of Electrical and Electronics Engineering Department of Electrical and Computer Engineering Institute for Research in Electronics and Applied Physics and Department of Electrical Engineering and Computer Science Department of Electrical and Photonics Engineering College of Information and Computer Sciences

Optics and photonics have recently captured interest as a platform to accelerate linear matrix processing, otherwise a bottleneck in traditional digital electronics. In this paper we propose an all-photonic computational accelerator wherein information is encoded in the amplitudes of frequency modes stored in a single ring resonator. Interaction among these modes is enabled by nonlinear optical processes. Both the matrix multiplication and elementwise activation functions on these modes (the artificial neurons) are performed through coherent processes, enabling the direct representation of negative and complex numbers without having to pass through digital electronics, a common limitation in today’s photonic architectures. This design also has a drastically lower hardware footprint compared with today’s electronic and optical accelerators, as the entirety of the matrix multiplication happens in a single multimode resonator on chip. Our architecture is unique in providing a completely unitary, reversible mode of computation, enabling on-chip analog Hamiltonian-echo backpropagation for gradient descent and other self-learning tasks. Moreover, the computational speed increases with the power of the pumps to arbitrarily high rates, as long as the circuitry can sustain the higher optical power. Lastly, the design presented here is a less demanding version of a future room-temperature quantum computational device. Therefore, while this architecture is already viable today, direct reinvestments in it would be enabling its evolution into quantum computational hardware.

关键词： Machine learning Neuromorphic computing Nonlinear optics Photonics Artificial neural networks Deep learning Neural network simulations Optical computing

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A Low Complexity ML-Based Methods for Malware Classification

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computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura Ahmad Alkhatib Deema Mohammed Alsekait Mohammad Alshinwan Sahar A.El-Rahman Didi Rosiyadi Diaa Salama Abd Elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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Detachable Robot That Moves the Baby Bouncer

Detachable Robot That Moves the Baby Bouncer

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IEEE/SICE International Symposium on System Integration

作者： Natsumi Onosato Naoharu Sawada Yohei Kawasaki Masahiko Takeda Masaki Inoue Yuta Sugiura Department of Information and Computer Science Keio University Japan Department of Applied Physics and Physico-Informatics Keio University Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

A baby bouncer is a type of cradle that allows for rocking and soothing through the baby’s own movements or the use of hands by an adult. An electric baby bouncer is designed to automatically rock the baby, enabling parents to soothe their child without using their hands and reducing the effort required. However, existing electric baby bouncers have the drawback of being expensive, heavy, and bulky. In this study, we propose an external attachment device that can be easily added to existing manual baby bouncers to enable automatic rocking. This device operates by transmitting the rotation of a servo motor to the baby bouncer, facilitating the rocking motion. Through experimentation, we validated that the device can adapt to variations in the baby’s weight and changes in the servo motor’s rotation cycle, thereby allowing for adjustments in the swing range of the baby bouncer.

关键词： Hands Pediatrics System integration Rocks Servomotors Robots

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Optical Design for Automatic Inspection System of Defects on Disposable Surgical Scalpel Blades Using Machine Vision 9th

Optical Design for Automatic Inspection System of Defects on...

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9th International Conference on the Development of Biomedical Engineering in Vietnam, BME 2022

作者： Dau, Sy Hieu Dang, Thi Phuc Han, Doan Quang My Hy, Ta Chiu Khang, Le Nguyen An Dat, Khau Nguyen Thanh Department of Applied Physics Applied Sciences Faculty University of Technology Vietnam National University HCMC Ho Chi Minh City Viet Nam Department of Computer Science Faculty of Information Technology Industrial University of Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9783031446290

Nowadays, many products in the medical area are disposable, such as needles, daily contact lenses, disposable ultra-thin surgical scalpel blades, infusion tubes. With the increasing demand in the market, manufacturers are striving to enhance production output while maintaining acceptable quality standards. Consequently, the implementation of an automatic inspection system for these products has become imperative. The main challenge with automatic quality inspection systems is the input data, consisting mainly of images captured during production. Image processing algorithms or deep learning models are used to analyze these images, classifying the products as "pass" or "fail" based on the inspection results. To minimize inspection time, high-quality input images are crucial, clearly distinguishing defects from the background. The optical system used for inspection must be carefully designed, considering the unique characteristics of each product, such as surface properties and external features that may pose challenges. In this article, we present a research study in which an optical system is designed using Dark Field, Coaxial and Dome lighting techniques to highlight defects on disposable surgical scalpel blades with metallic reflection surface. The Dark Field technique effectively reveals missing portions, cracks, or fractures on the cutting edge, while Coaxial lighting detects faults on the blade body. The Dome lighting technique provides illumination, preventing reflections on the metallic surface. We employed the Dome technique to inspect the quality of printed details on the aluminum foil sheet of the sealed blade’s pocket. The resulting images enable efficient defect detection due to their well-highlighted nature. © The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024.

关键词： computer vision

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Air Particulate Matters Auto-Rule-Based Labeling to Support Long-Distance Run Environment Data Classification 13

Air Particulate Matters Auto-Rule-Based Labeling to Support ...

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13th IEEE Symposium on computer Applications and Industrial Electronics, ISCAIE 2023

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

ISBN: (纸本)9798350347319

Sports science is an interdisciplinary and multidisciplinary science that strives to increase athletic performance and endurance. Sport science recognizes and prevents injuries. Sensors and statistics formalize Sports science. Runners need coaches and teams to support them before, during, and after the run race. Coaches generate running training plans to boost performance. Running race performances may be impacted by air pollution exposure while training, so coaches should consider limiting air pollution exposure when training. One of the external factors is Particulate Matter (PM2.5 and PM10). Sensors connecting to the Internet can record external factors and produce csv data. The foundation of supervised machine learning is the labeling process. Labeling a set of data is one of the laborious and time-consuming phases in every machine-learning application because it requires verifying the accuracy of the labels and making any necessary revisions. This research aimed to find a solution to automatically label numerous air particulate matter raw data using a rule based on parameters to reduce manual work, human errors and faster processes. This labeled data will later be used for supervised machine learning classification to support the coach in generating training programs for the runners in a Sports information System. Based on Indonesia Air Quality index rule-based approach, labeled text data in csv has been generated and tested with PM2.5 and PM10 parameters in three scenarios with a 100% success rate. It was possible to automate the labeling process, and it explained how automation results in fast and accurate results. © 2023 IEEE.

关键词： Classification (of information)

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Quantum Nonlocality: Multicopy Resource Interconvertibility and Their Asymptotic Inequivalence

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Physical Review Letters 2024年第25期132卷 250205-250205页

作者： Subhendu B. Ghosh Snehasish Roy Chowdhury Guruprasad Kar Arup Roy Tamal Guha Manik Banik Physics and Applied Mathematics Unit Department of Physics A B N Seal College Cooch Behar West Bengal 736101 India QICI Quantum Information and Computation Initiative Department of Computer Science Department of Physics of Complex Systems

Quantum nonlocality, pioneered in Bell’s seminal work and subsequently verified through a series of experiments, has drawn substantial attention due to its practical applications in various protocols. Evaluating and comparing the extent of nonlocality within distinct quantum correlations holds significant practical relevance. Within the resource theoretic framework this can be achieved by assessing the interconversion rate among different nonlocal correlations under free local operations and shared randomness. In this study we, however, present instances of quantum nonlocal correlations that are incomparable in the strongest sense. Specifically, when starting with an arbitrary many copies of one nonlocal correlation, it becomes impossible to obtain even a single copy of the other correlation, and this incomparability holds in both directions. Such incomparable quantum correlations can be obtained even in the simplest Bell scenario, which involves two parties, each having two dichotomic measurements setups. Notably, there exist an uncountable number of such incomparable correlations. Our result challenges the notion of a “unique gold coin,” often referred to as the “maximally resourceful state,” within the framework of the resource theory of quantum nonlocality. To this end, we provide examples of isotropic quantum correlations that cannot be distilled up to the Tsirelson point, and thus partially answer a long-standing open question in nonlocality distillation.

关键词： Quantum correlations, foundations & formalism Quantum foundations Resource theories

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