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A Simulation-Optimization Model for Automated Parcel Lockers Network Design in Urban Scenarios in Pamplona (Spain), Zakopane, and Krakow (Poland) 22

A Simulation-Optimization Model for Automated Parcel Lockers...

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Proceedings of the Winter Simulation Conference

作者： Bartosz Sawik Adrian Serrano-Hernandez Aitor Ballano Javier Faulin Department of Business Informatics and Engineering Management AGH University of Science and Technology Krakow POLAND Institute of Smart Cities Department of Statistics Computer Science and Mathematics Public University of Navarre Pamplona SPAIN

The constant rise of e-commerce coupled with extremely fast deliveries is a significant contributor to saturate city centers' mobility. To address this issue, the development of a convenient Automated Parcel Lockers (APLs) network improves last-mile distribution by reducing the number of transportation vehicles, the distances driven, and the delivery stops. This article aims to define and compare APL networks in the cities of Pamplona (Spain), Zakopane and Krakow (Poland). Thereby, a bi-criteria weighted-sum simulation optimization model is developed for a representative year for the aforementioned cities. The simulation forecasts the e-commerce demands whereas the optimal APL network is obtained with a bi-criteria maximum APL revenues and minimum network costs. Meaningful results are obtained from the multi-criteria hybrid model outcomes as well as from the cities comparison. These outcomes suggest efficient APLs networks considering cultural and demographic factors for a massive use of APLs in high-demand periods.

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Minimum Mean Squared Error Holographic Beamforming for Sum-Rate Maximization

arXiv

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arXiv 2025年

作者： Sheemar, Chandan Kumar Khan, Wali Ullah Alexandropoulos, George C. Ahmed, Manzoor Chatzinotas, Symeon SnT department The University of Luxembourg Luxembourg Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens16122 Greece School of Computer and Information Science Institute for AI Industrial Technology Research Hubei Engineering University Xiaogan City432000 China

This paper studies the problem of hybrid holographic beamforming for sum-rate maximization in a communication system assisted by a reconfigurable holographic surface. Existing methodologies predominantly rely on gradient-based or approximation techniques necessitating iterative optimization for each update of the holographic response, which imposes substantial computational overhead. To address these limitations, we establish a mathematical relationship between the mean squared error (MSE) criterion and the holographic response of the RHS to enable alternating optimization based on the minimum MSE (MMSE). Our analysis demonstrates that this relationship exhibits a quadratic dependency on each element of the holographic beamformer. Exploiting this property, we derive closed-form optimal expressions for updating the holographic beamforming weights. Our complexity analysis indicates that the proposed approach exhibits only linear complexity in terms of the RHS size, thus, ensuring scalability for large-scale deployments. The presented simulation results validate the effectiveness of our MMSE-based holographic approach, providing useful insights. © 2025, CC BY.

关键词： Iterative methods

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Interpreting Industrial IoT Data Streams Through Fuzzy Querying With Hysteretic Fuzzy Sets on Apache Kafka

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IEEE Transactions on Fuzzy Systems 2024年第8期32卷 4671-4684页

作者： Bożena Małysiak-Mrozek Bartłomiej Ryba Marek Molęda Che-Lun Hung Witold Pedrycz Weiping Ding Dariusz Mrozek Department of Distributed Systems and Informatic Devices Silesian University of Technology Gliwice Poland Department of Applied Informatics Silesian University of Technology Gliwice Poland Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei City Taiwan Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Department of Measurements and Control Systems Silesian University of Technology Gliwice Poland Research Center of Performance and Productivity Analysis Istinye University Istanbul Türkiye School of Artificial Intelligence and Computer Science Nantong University Nantong China Faculty of Data Science City University of Macau Macau China

In industrial settings, querying data streams from Internet of Things (IoT) devices benefits from utilizing elastic criteria to enhance the interpretability of the current state of the monitored environment. Fuzzy sets provide this elasticity, enabling the aggregation and representation of similar values in a human-comprehensible manner. However, many sensor signals exhibit temporal oscillations, leading to varying interpretations of the signal based on its current trend (rising or falling). This hysteresis in signal (and subsequently of the production device) interpretation inspired us to introduce this phenomenon into data stream processing, resulting in the novel concept of hysteretic fuzzy sets. This article demonstrates how fuzzy searching and grouping can be applied to IoT sensor signals in flexible Big Data stream processing on Apache Kafka. We illustrate the impact of data stream querying with KSQL queries involving fuzzy sets (encompassing fuzzy filtering of data stream events, fuzzy transformation of data stream attributes, fuzzy grouping, and joining) on the flexibility of executed operations and computational resources utilized by the Kafka processing engine. Finally, our experiments with hysteretic fuzzy sets while analyzing sensor signals in power plants demonstrate that this novel approach effectively reduces the number of alarms while monitoring the state of the production machine.

关键词： Streams Fuzzy sets Internet of Things Big Data Monitoring Production Real-time systems

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Sentence Embedding Models for Similarity Detection of Software Requirements

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SN computer Science 2021年第2期2卷 1-11页

作者： Das, Souvick Deb, Novarun Cortesi, Agostino Chaki, Nabendu Department of Computer Science and Engineering University of Calcutta Kolkata 700106 India Indian Institute of Information Technology Vadodara Gujarat Gandhinagar 382028 India Department of Environmental Science Informatics and Statistics Ca’ Foscari University Venezia 30172 Italy Department. of Computer Science and Engineering University of Calcutta Kolkata 700106 India

Semantic similarity detection mainly relies on the availability of laboriously curated ontologies, as well as of supervised and unsupervised neural embedding models. In this paper, we present two domain-specific sentence embedding models trained on a natural language requirements dataset in order to derive sentence embeddings specific to the software requirements engineering domain. We use cosine-similarity measures in both these models. The result of the experimental evaluation confirm that the proposed models enhance the performance of textual semantic similarity measures over existing state-of-the-art neural sentence embedding models: we reach an accuracy of 88.35%—which improves by about 10% on existing benchmarks. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature.

关键词： Requirements similarity Semantic similarity Sentence embedding

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Harnessing Data Mining for Improved Hindi Isolated Speech Recognition

Harnessing Data Mining for Improved Hindi Isolated Speech Re...

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Futuristic Technologies in Control Systems & Renewable Energy (ICFCR), International Conference on

作者： Ayasha Malik Veena Parihar Shrikant Mapari Malathy Sathyamoorthy Shilpa Saini Department of CSE IIMT College of Engineering (AKTU) Greater Nida India Symbiosis Institute of Geo-informatics Symbiosis International (Deemed University) Pune India Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) Pune India Department of Information Technology KPR Institute of Engineering and Technology Coimbatore India Chandigarh University Mohali

ISBN: (数字)9798331504601

ISBN: (纸本)9798331504618

Speech is the primary medium for the exchange and transfer of messages, making recognition of speech an extensive area of study. The phonic and linguistic outline is probable for this, mostly for the English verbal. In India, a considerable portion of the population faces challenges to communicate in English. Henceforward, English speech detection is not useful for such persons. The recognition method of Hindi words is an integral segment of the automatic speech detection technique that has been proposed in this paper. The primary objective of Automatic Speech Recognition (ASR) is to recognize and interpret spoken input from a device or microphone and convert it into a textual document to execute the appropriate action. The procedure of detecting speech solely relies on the abstraction of attributes and the detection of patterns within the content. This research paper employs the Hidden Markov Model (HMM) along with the Hidden Markov Toolkit (HMT) and Pratt software for attribute detection. In the proposed scheme, a set of data is apprehended having 10 Hindi words: from “Shunya” to “Nau” (Shunya, Ek, Do, Teen, Chaar, Paanch, Chae, Saat, Aath, Nau) from the 15 voices of different age group then applying training along with testing over the set of data. The projected structure computes and compares the Linear Predictive Coding (LPC), Perceptual Linear Prediction (PLP), and Mel Frequency Cepstral Coefficients (MFCC) algorithms. These algorithms are applied to talker-reliant ASR and talker-free ASR in sound-dependent and word-based environments to figure out the top feature mining technique which is MFCC in our proposed system.

关键词： Voice activity detection Training Renewable energy sources Hidden Markov models Speech recognition Prediction algorithms Software Data mining Mel frequency cepstral coefficient Testing

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Safety Guaranteed Power-Delivered-to-Load Maximization for Magnetic Wireless Power Transfer

Safety Guaranteed Power-Delivered-to-Load Maximization for M...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Wangqiu Zhou Xinyu Wang Hao Zhou Shenyao Jiang Zhi Liu Yusheng Ji LINKE Lab School of Computer Science and Technology University of Science and Technology of China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China Deqing Alpha Innovation Institute Huzhou China Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Electromagnetic radiation (EMR) safety has always been a critical reason for hindering the development of magneticenabled wireless power transfer technology. People focus on the actual received energy at charging devices while paying attention to their health. Thus, we study this significant problem in this paper, and propose a universal safety guaranteed power-delivered-to-load (PDL) maximization scheme (called SafeGuard). Technically, we first utilize the off-the-shelf electromagnetic simulator to perform the EMR distribution analysis to ensure the universality of the method. Then, we innovatively introduce the concept of multiple importance sampling for achieving efficient EMR safety constraint extraction. Finally, we treat the proposed optimization problem as an optimal boundary point search problem from the perspective of space geometry, and devise a brand-new grid-based multi-constraint parallel processing algorithm to efficiently solve it. We implement a system prototype for SafeGuard, and conduct extensive experiments to evaluate it. The results indicate that our SafeGuard can obviously improve the achieved PDL by up to 1.75× compared with the state-of-the-art baseline while guaranteeing EMR safety. Furthermore, SafeGuard can accelerate the solution process by 29.12× compared with the traditional numerical method to satisfy the fast optimization requirement of wireless charging systems.

关键词： Performance evaluation Monte Carlo methods System performance Inductive charging Prototypes Wireless power transfer Parallel processing

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Human Activity Recognition in Smart Cities from Smart Watch Data using LSTM Recurrent Neural Networks

Human Activity Recognition in Smart Cities from Smart Watch ...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Meenakshi Kandpal Bhisham Sharma Rabindra K. Barik Subrata Chowdhury Sudhansu Shekhar Patra Imed Ben Dhaou School of Computer Engineering KIIT Deemed to be University Bhubaneswar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computer Applications KIIT Deemed to be University Bhubaneswar India MCA Department Sri Venkateshwara College of Engineering and Technology (A) Chittoor AP India Department of Computer Science Hekma School of Engineering Computing and Informatics Dar Al-Hekma University Jeddah Saudi Arabia

Due to the convergence of healthcare and smart cities, information and technology are employed in health and medical procedures worldwide. Residents of smart cities now enjoy better lives and healthier bodies because to integration. The advent of smart watch technology and deep learning techniques has engendered a potential increase in performance and accuracy of such tasks. Our paper explores the application of recurrent neural networks particularly LSTM for action recognition task using smart watch sensor data, i.e., gyroscope and accelerometer data. We have taken into consideration some general activities like standing, walking, sitting, etc. and implemented a LSTM network for the action recognition job using the time sequences sensor data. This model can be useful for other health-based applications which can monitor the health conditions of a user by keeping record of his activities.

关键词： Legged locomotion Deep learning Technological innovation Recurrent neural networks Smart cities Medical services Watches

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Equitable and Fair Performance Evaluation of Whale Optimization Algorithm

arXiv

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arXiv 2023年

作者： Hassan, Bryar A. Rashid, Tarik A. Ahmed, Aram Qader, Shko M. Majidpour, Jaffer Abdalla, Mohmad Hussein Tayfor, Noor Hamarashid, Hozan K. Sidqi, Haval Noori, Kaniaw A. Ramadhan, Awf Abdulrahmam Department of Computer Science College of Science Charmo University Chamchamal KRI Sulaimani46023 Iraq Department of Computer Science and Engineering University of Kurdistan Hewler KRI Iraq Department of Information Technology College of Science and Technology University of Human Development Sulaimani Iraq Computer Science Institute Sulaimani Polytechnic University Information Technology Department Sulaimani Iraq The Department of Computer Science Kurdistan Technical Institute Sulaimani Iraq Department of Computer Science University of Raparin Sulaimani Iraq Department of Information Technology Kurdistan Technical Institute Sulaimani Iraq Information Technology Department Computer Science Institute Sulaimani Polytechnic University Sulaimani46001 Iraq Technical College of informatics Sulaimani Polytechnic University Sulaimani46001 Iraq Department of Database Technology Technical College of Informatics Sulaimani Polytechnic University Sulaimani Iraq Public Health Department College of Health and Medical Techniques - Shekhan Duhok Polytechnic University Duhok Iraq

It is essential that all algorithms are exhaustively, somewhat, and intelligently evaluated. Nonetheless, evaluating the effectiveness of optimization algorithms equitably and fairly is not an easy process for various reasons. Choosing and initializing essential parameters, such as the size issues of the search area for each method and the number of iterations required to reduce the issues, might be particularly challenging. As a result, this chapter aims to contrast the Whale Optimization Algorithm (WOA) with the most recent algorithms on a selected set of benchmark problems with varying benchmark function hardness scores and initial control parameters comparable problem dimensions and search space. When solving a wide range of numerical optimization problems with varying difficulty scores, dimensions, and search areas, the experimental findings suggest that WOA may be statistically superior or inferior to the preceding algorithms referencing convergence speed, running time, and memory utilization. © 2023, CC BY.

关键词： Benchmarking

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Numerical Approach of Laser-Induced Spherical Microcavitation Bubbles: Effect of Enthalpy

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Bulletin of the Russian Academy of Sciences: Physics 2024年第Suppl 3期88卷 S287-S292页

作者： Ali F. Abu-Bakr Abu-Nab, Ahmed K. AbuShaeer, Zain Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom32511 Egypt Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Dolgoprudny Moscow141700 Russia Center for Photonics and 2D Materials Moscow Institute of Physics and Technology Dolgoprudny141700 Russia Department of Basic Science Higher Institute of Engineering and Technology Kafrelsheikh33511 Egypt

Abstract: Over the past decades, interest has increased in studying different techniques to detect the importance of microbubbles in many industrial and medical applications such as mechanisms of hydraulic machinery cavitation erosion, histotripsy, and lithotripsy. The behavior from early irregular oscillations to late regular oscillations of spherical microcavitation bubbles produced by lasers in water was studied by means of plasma photography. Repetition of such delayed oscillations results in quantities of gas/vapour inside the spherical bubbles. Using the modified Gilmore model of cavitation microbubble dynamics, calculations were made for the laser pulse energy, microbubble radius behavior, and microbubble growth rate. Additionally, the pressure evolution inside the bubble, and pressures distribution surrounding of microbubbles in liquid are investigated under the effect of different values of initial cavitation of microbubble radius. The effect of enthalpy is considered into account. The proposed model is solved numerically using numerical techniques as a finite difference method. In addition, the radius of the microbubbles is calculated as a function of time under the influence of the initial radius of these laser-induced microcavitations. Moreover, some physical properties and numerical calculations of the presented mathematical model for cavitation induced by lasers bubbles are deduced, analyzed and investigated. © Pleiades Publishing, Ltd. 2024.

关键词： Cavitation

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Smart watering system based on framework of low-bandwidth distributed applications (LBDA) in cloud computing 12th

Smart watering system based on framework of low-bandwidth di...

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12th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2020

作者： Sirimorok, Nurdiansyah As, Mansur Yoshida, Kaori Köppen, Mario Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Creative Informatics Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9783030577957

The estimation of soil moisture content is required for agriculture, mainly to build the irrigation scheduling model. In this study, we present a smart watering system to deal with various factors derived from the stochastic information in the agricultural operational, i.e., air temperature, air humidity, soil moisture, soil temperature, and light intensity. The methodology consists of exploiting the Internet of Things (IoT) using Low-Bandwidth Distributed Applications (LBDA) in cloud computing to integrate the real data sets collected by the several sensor technologies. We conducted experiments for the watering system used two types of soil and different plant. Here, the Long Short Term Memory Networks (LSTMs) approach in deep learning techniques used to build smart decisions concerning watering requirements and deal with heterogeneous information coming from agricultural environments. Results show that our models can effectively improve the prediction accuracy for the watering system over various soil and plants. © Springer Nature Switzerland AG 2021.

关键词： Cloud computing

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