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Scheduling Bi-Objective Lot-Streaming Hybrid Flow Shops with Consistent Sublots via an Enhanced Artificial Bee Colony Algorithm

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Complex System Modeling and Simulation 2025年第1期5卷 46-67页

作者： Benxue Lu Kaizhou Gao Peiyong Duan Adam Slowik School of Computer Science Liaocheng UniversityLiaocheng 252000China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Information and Automation Engineering Qilu University of TechnologyJinan 250353China Department of Electronics and Computer Science Koszalin University of TechnologyKoszalin 75-453Poland

This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy ***,the Bi-HFSP_CS is formalized,followed by the establishment of a mathematical ***,enhanced version of the artificial bee colony(ABC)algorithms is proposed for tackling the Bi-HFSP_***,fourteen local search operators are employed to search for better *** different Q-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration ***,the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm,its three variants,and three effective algorithms in resolving 95 instances of 35 different *** experimental results and analysis showcase that the enhanced ABC algorithm combined with Q-learning(QABC1)demonstrates as the top performer for solving concerned *** study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength,offering beneficial perspectives for exploration and research in relevant domains.

关键词： hybrid flow shop scheduling Q-learning lot streaming local search

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Channels engineering in Magnetic Recording: From Theory to Practice

IEEE BITS the Information Theory Magazine

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IEEE BITS the Information Theory Magazine 2023年第3期3卷 6-49页

作者： Garani, Shayan Srinivasa Vasic, Bane Indian Institute of Science Department of Electronics Systems Engineering Bengaluru560012 India University of Arizona Department of Electrical and Computer Engineering TucsonAZ85721 United States

Information theory, coding theory, and signal processing have significantly shaped magnetic read/write channels engineering through a chronological sequence of innovations and research advancements, cognizant of the underlying physical processes. In this magazine article, we provide an overview of magnetic recording technologies leading to the channels engineering aspects, central to this article. We survey important coding and signal processing algorithms along with some design architectures that have made it to practice within hard disk drives for magnetic recording channels. The push toward realizing ultrahigh densities (> 4 Tb/in2>) on magnetic disks with ultrahigh throughput rates (>10 Gb /s) necessitates the development of native two-dimensional (2-D) coding and signal processing algorithms and architectures within the framework of 2-D magnetic recording (TDMR) along with read head engineering and changes to the recording physics. We also provide an overview of novel channels engineering solutions covering all aspects of TDMR channels driven from a systems science perspective. The innovations and research advances described in this article may serve a broad engineering audience in other areas as well. © 2021 IEEE.

关键词： Magnetic recording

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Influence of Local Lag on Reaction Force in Networked Virtual Environment with Haptic Sense 21

Influence of Local Lag on Reaction Force in Networked Virtua...

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21st IEEE International Conference on computer Applications, ICCA 2024

作者： Win, Khaing Zar Ishibashi, Yutaka Win, Khaing Htet University of Computer Studies Yangon Faculty of Computer Science Yangon Myanmar School of Engineering Nagoya Institute of Technology Nagoya Japan University of Computer Studies Yangon Faculty of Computer Systems and Technologies Yangon Myanmar

ISBN: (纸本)9789998601673

This paper investigates the influence of local lag on the reaction forces in a networked virtual maze system incorporating haptic feedback by experiment. In the experiment, participants move a box from the starting position to the target point by using Raising method with haptic device. We measure the average operation time and the average of average reaction force for three different moving velocities and three distinct local lags. Experimental results reveal that as the moving velocity increases and the local lag becomes higher, the two measures become larger. Thus, we illustrate that there exists a strong relationship among the average operation time, the average of average reaction force, moving velocity, and local lag, through multiple regression analysis. © 2024 IEEE.

关键词： Virtual reality

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Digital Regimen for Parkinson Disease: An Informative Approach Using Mobile Application 2

Digital Regimen for Parkinson Disease: An Informative Approa...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Seya Prakash, P. Gunasekaran, G. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Vellore Institute Technology Department of Smart Computing Vellore India

ISBN: (纸本)9798350328202

Parkinson's disease (PD) is an advanced neuro-degenerative condition where a large number of people around the world are profoundly affected. The scarcity of precise data regarding the typical circumstances faced by humans with PD severely restricts ongoing research and therapeutic endeavours. This proposed work aims to investigate various innovations to address this issue comprehensively. Specifically, this proposed work intends to develop a versatile application tailored to help the PD patients and incorporating smart medication reminders. Moreover, this proposed work will focus on creating exercise/workout plans & diet plans based on continuous data collection and patient feedback to enhance prescription management while minimizing side effects. Simultaneously, initiatives aimed at reducing the stress level and improve mental health. The development and implementation of this versatile applications hold significant promise in improving patient outcomes. By addressing the dearth of accurate information and fostering a systematic support ecosystem, it aspires to enhance the lives of individuals grappling with PD on a global scale. © 2024 IEEE.

关键词： Neurodegenerative diseases

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Next Generation Memristor Reservoir Computing 3

Next Generation Memristor Reservoir Computing

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： Nikiruy, K. Ivanov, T. Ziegler, M. Rossetti, D. Corinto, F. Ascoli, A. Tetzlaff, R. Demirkol, A.S. Schmitt, N. Micro-and Nanoelectronic Systems Tu Ilmenau Department of Electrical Engineering and Information Technology Ilmenau Germany Turin Italy Institute of Circuits and Systems Tu Dresden Faculty of Electrical and Computer Engineering Dresden Germany

ISBN: (纸本)9798350378009

The nonlinear transformation used in reservoir computing can be effectively replaced by nonlinear vector autoregression (NVAR) for data prediction. In such a method, also known as next generation reservoir computing (NGRC), the input signal consists of a linear part, including several previous data points, and their nonlinear combinations. Here we show that the application of this method to a network with memristive weights (memristors) can be used to predict signals, depending on the nature of the nonlinear functions and the number of memristors. The network allows an accurate prediction of chaotic time series of Mackey-Glass and Duffing oscillators. © 2024 IEEE.

关键词： Memristors

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Early Detection of Premature Retinopathy using Deep Learning Techniques 2

Early Detection of Premature Retinopathy using Deep Learning...

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2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Shaik, Ayesha Shaik, Mohammad Shaad Gaurav, Adarsh Balasundaram, A. Vellore Institute of Technology Chennai Center for Cyber Physical Systems Chennai India Vellore Institute of Technology Chennai Computer Science Engineering Chennai India

ISBN: (纸本)9798331534950

Retinopathy of prematurity (ROP) can be cured with laser therapy or surgery, early identification is crucial. In most situations, treatment can avert blindness. On the other hand, ROP can result in irreversible blindness if it is not identified and treated quickly. Using InceptionV3, ResNet50, VGG16, VGG19, DenseNet201, MobileNet, AlexNet, and Ensemble Model, the proposed study seeks to classify various stages of Retinopathy of prematurity (ROP). Initially, 91 retinal fundus images were gathered, comprising no ROP, stage one, stage two, and stage three images. Subsequently, four discrete datasets were generated through the use of four image processing techniques: histogram equalization, canny filter, sobel filter, and enhanced multispectral colour composite. The dataset's size was raised from 91 to 1000 images using image augmentation techniques, with 250 images each class. After comparing the outcomes, it was discovered that, out of all the combinations, employing MobileNet in Contrast with Histogram equalisation and enhanced multispectral colour composite datasets produced the greatest test accuracy, at 99.85% and 95.55%, respectively. © 2024 IEEE.

关键词： Laser surgery

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Photonics Applications and Web engineering – WILGA 2024

Photonics Applications and Web Engineering – WILGA 2024

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Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2024

作者： Romaniuk, Ryszard S. Smolarz, Andrzej Wójcik, Waldemar Warsaw University of Technology Institute of Electronic Systems Poland Lublin University of Technology Faculty of Electrical Engineering and Computer Science Poland

ISBN: (数字)9781510685796

ISBN: (纸本)9781510685789

Wilga 2024 Summer Symposium on Photonics Applications and Web engineering was the 52th edition of the research and technical meetings series. Traditionally, the annual series of technical conferences and topical sessions lasted the whole week. They usually were split to one winter meeting in January and one or two summer events in May/June, and in September. The Covid epidemic and the war in Ukraine has changed a lot. The hybrid meetings were held in Wilga resort near Warsaw, owned by the Warsaw University of Technology. Now the meetings since 2022 were shifted to Lublin. Nearly 100 participants took part in all of the Wilga 2022 events, most of them being young researchers active in all aspects of photonics, electronics and ICT science and technology. Over 60 participants took part in Wilga 2024 meetings. Wilga Symposium embraces hardware and software technologies associated with photonics like optics, optical engineering, optoelectronics, electronics and electrical engineering, mechatronics, chemical and material engineering, applied physics, industrial solutions and applications. Around 50 papers were presented during Wilga 2024, oral and poster. Out of this number, some papers chosen by authors are published in this volume of Proc. SPIE mostly related to photonics. The major change was that during Wilga 2020, 2021, 2022 and 2024 Symposia, during summer editions, no traditional large young researcher sessions at large were possible to be organized. We hope that this will change and Wilga 2025 will return to a good tradition to organize concurrent social research sessions full of young researchers like was during Wilga 2019 and earlier. © 2024 SPIE.

关键词： Photonic devices

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Landslide Hazard Zonation Mapping Using ML Techniques - A Study Over Kodagu District, Karnataka 6

Landslide Hazard Zonation Mapping Using ML Techniques - A St...

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6th IEEE PhD Colloquium on Emerging Domain Innovation and Technology for Society, PhD EDITS 2024

作者： Narayana, Sreedevi Jayaraman, Karthikeyan CMR Institute of Technology Department of CSE Bengaluru India School of Computer Engineering and Information Systems VIT University Vellore India

ISBN: (纸本)9798331541965

This study explores two advanced machine learning techniques-The Gradient Boost (GB) and Extreme Gradient Boost (XGBoost) for landslide hazard zonation (LHZ) mapping in the Kodagu district of karnataka, India. Gradient Boost is a machine learning approach which constructs a predictive model by combining the output of weaker models. This iterative improvement process results in a better model to identify landslide-prone areas. In contrast, XGBoost is an enhanced version of Gradient Boost, it incorporates L1 and L2 regularization to prevent over-fitting, handles missing data and utilizes parallel computing for more efficient model training. The study has used nine thematic layers along with landslide occurrence data to train and test both models in R language. The results point to the fact that XG Boost outperforms Gradient Boosting, with 85.90% of landslides falling within the identified hazard zones compared to 69.23% for Gradient Boosting. The findings highlight the superior predictive capability of XGBoost, attributed to its advanced features such as regularization and efficient handling of sparse data. © 2024 IEEE.

关键词： Landslides

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Endoscopic Bladder Tissue Classification Using Seventeen Layered Deep Convolutional Neural Network 2

Endoscopic Bladder Tissue Classification Using Seventeen Lay...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Devi, M. Shyamala Pandian, J. Arun Umanandhini, D. Viknesh, V. Vishal, G.P. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Computer Science & Engineering Tamilnadu Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350370188

After a diagnosis of bladder cancer, endoscopic surgery is carried out as it is thought to be the most efficient and appropriate method of treating superficial tumors. It is essential to classify the bladder tissues accurately using MRI since early diagnosis of the problem can aid in treatment and perhaps save lives. Early-stage diagnosis is still challenging due to the delayed onset of indications and tiny alterations in urinary tract tissue that are imperceptible to the naked eye for diagnosis. The automated approach might be utilized to automatically determine the type of endoscopic bladder tissue by using the proper deep learning model with the necessary convolutional layers. This paper suggests the Seventeen Layered Deep Convolutional Neural Network (17-DCNN) to classify the bladder tissue classes effectively. The Endoscopic bladder tissue Dataset from Kaggle is used for the implementation of DOMN that contains 1785 images with four classes as HGC, LGC, NTL, and NST. The 17-DCNN model's initial phase is an analysis of distribution of bladder tissue data images. After data preparation, the existing CNN like DenseNet121, ResNet152, VGG19Net, InceptionV3Net and proposed 17-DCNN model is chosen by fitting the Endoscopic bladder tissue images. The accuracy of the proposed 17-DCNN was 99.32% when compared to other CNN models after implementation. © 2024 IEEE.

关键词： Convolutional neural networks

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Intelligent Daycare: Enhancing Child Safety with IoT and Machine Learning Innovations 9

Intelligent Daycare: Enhancing Child Safety with IoT and Mac...

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9th International Conference on Communication and Electronics systems, ICCES 2024

作者： Prathyanga, Amisha Shyaminda, Pasindu Chamikara, Pasan Lakshan, Sachin Thelijjagoda, Samantha Kasthurirathna, Dharshana Sri Lanka Institute of Information Technology Department of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350377972

Child safety and well-being in daycare settings are important, thus it is vital that the persons in charge be attentive to them. This research tries to solve the problem by introducing a smart and detailed monitoring system that utilizes new technology to enhance safety and support caretakers. The system has various innovative features, such as child missing detection, behavior and facial expression analysis, cry analysis and categorization, and fall detection. Using high-resolution cameras and on-device Edge AI capabilities, it ensures real-time surveillance of children's activities while protecting privacy. The approach integrates behavior and facial expression analysis to assess emotional states, cry recognition to discover childcare needs, as well as a useful fall detection system that can tell the difference between falls and other movements. All these parts synergize to hand over the necessary information to the caregivers on time and in a way that they can act upon. The quantitative experiments in real-time childcare centers show high accuracy through all the components, attesting to the system's reliability and durability. This research has important significance in improving the safety and the frequency response in daycare centers because it gives caregivers automated tools to quickly address the needs of children. While promising, the system has drawbacks, such as potential biases in data models and a reliance on ideal environmental circumstances. Future work intends to improve flexibility across varied daycare situations, improve accuracy through larger datasets, and investigate ethical frameworks for wider application. © 2024 IEEE.

关键词： Fall detection

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