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21st ACM/IEEE International conference on Information Processing in Sensor Networks, IPSN 2022

ISBN: (纸本)9781665496247

The proceedings contain 65 papers. The topics discussed include: Vildehaye: a family of versatile, widely-applicable, and field-proven lightweight wildlife tracking and sensing tags;a low-cost in-situ system for continuous multi-person fever screening;eclipse: an end-to-end platform for low-cost, hyperlocal environmental sensing in cities;DRLIC: deep reinforcement learning for irrigation control;placement optimization for UAV-enabled wireless networks with multi-hop backhauls in urban environments;PCTC: parallel cross technology communication in heterogeneous wireless systems;SPARCS: a sparse recovery approach for integrated communication and human sensing in mmWave systems;understanding and mitigating the impact of Wi-Fi 6E interference on ultra-wideband communications and ranging;individualizing head-related transfer functions for binaural acoustic applications;and VMA: domain variance- and modality-aware model transfer for fine-grained occupant activity recognition.

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GWO-CNN: Trust and Intelligent Recommendation system based model to improve marketing strategies on e-commerce 2

GWO-CNN: Trust and Intelligent Recommendation system based m...

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2nd IEEE International conference for Women in Innovation, Technology and Entrepreneurship, ICWITE 2024

作者： Sethi, Vikas Kumar, Rajneesh Mehla, stuti Department of Computer Science and Engineering Mullana Ambala India Panipat Institute of Engineering and Technology Department of Computer Science and Engineering Panipat India

ISBN: (纸本)9798350383287

In 21st century, AI-based intelligent recommendation system uses rating predictions, which are frequently utilized and helps users swiftly filter down their options and make informed judgements from an abundance of material. Nevertheless, as recommender systems only contain a small number of explicit data and are subject to cold start and sparsity issues, the majority of existing recommendation models have poor accuracy. The majority of conventional algorithms used to make recommendations simply take into account the straight-forward connection among consumers and products, largely ignoring the interests, prospective employment factors, or other social aspects of the products being *** this study focus is on user preferences, as they are key to tailoring recommendations to individual needs. By combining trust values with user preferences, the system can recommend items that not only have a high trust value but also align with a user's individual tastes or needs. For this proposed model used feature matrix, Grey Wolf Optimizer (GWO) and Convolution Neural Network (CNN). GWO is an optimization algorithm used to find optimal weights or parameters for the recommendation system. Once the GWO has found optimal or near-optimal weights, they are integrated into the feature matrix. These weights can help prioritize or scale certain features to improve the recommendation quality. Then CNN will extract patterns and relationships from the feature matrix. Based on the processed feature matrix, the system predicts the top 'K' items to recommend to the user. © 2024 IEEE.

关键词： Recommender systems

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A New Reconfigured Electricity Market Bidding strategy in View of Players' Concerns

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IEEE TRANSACTIONS ON INDUstRY APPLICATIONS 2022年第6期58卷 7034-7046页

作者： Abedinia, Oveis Ghasemi-Marzbali, Ali Nurmanova, Venera Bagheri, Mehdi Nazarbayev Univ Dept Elect & Comp Engn Nur Sultan 010000 Kazakhstan Mazandaran Univ Sci & Technol Dept Elect & Biomed Engn Babol *** Iran

The electricity market has become a competitive model due to generation, transmission, distribution, and large-scale investments in microgrids where no electricity supplier intends to set the price. However, the competition itself provides opportunities for the buyer to be able to experience more profit. Based on the available optimal bidding model, the supplier can only offer the final bid. Hence, active participation on the demand side creates an efficient and reasonable electricity market, and also promotes additional optimal allocation of economic resources. This article has concentrated over the final marginal bidding price and creating an optimal bidding strategy for consumers. It has specifically focused and proposed a new optimized model for electricity market bidding to improve and obtain a maximum turnover and profit for players. Since the solution of the aforementioned issue is inadequate due to multiple decision variables in mathematical and classical methods;a new enhanced Harris Hawks optimization (HHO) is proposed. Trapping into local optimum point can be occurred in different optimization algorithms, while the proposed model has simple and efficient structure, without derivative operator, which is integrated with mathematical techniques to increase local and global search abilities. The standard HHO algorithm is utilized to increase the probability of entrapment in local optima through increasing the number of optimization variables;however, the challenge of large number of variables is resolved through proposing a novel local/global operators. The proposed model is examined with a standard IEEE system in 2-scenarios, with symmetric and asymmetric information through finding the optimal solution desirably.

关键词： Auction bidding optimization competitive electricity market electricity bidding strategy electricity market Harris Hawks optimization algorithm

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Multidirectional Magnetic Field Decoupling Model Based on Particle Swarm optimization

Multidirectional Magnetic Field Decoupling Model Based on Pa...

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IEEE conference on Electromagnetic Field Computation

作者： Leran Zhang Minxia Shi Jianzhi Yang Ziyang Shi Yuzheng Ma Ao Zhang School of Instrumentation Science and Optoelectronics Engineering Beihang University Beijing China

ISBN: (数字)9798350348958

ISBN: (纸本)9798350348965

Active magnetic compensation is required to achieve near-zero magnetic environment for Magnetocardiography (MCG). The coupling relations between the magnetic fields of passive field cause difficulties in compensation. In this paper, we establish a multidirectional magnetic field decoupling model which build adjustive vector and unidirectional magnetic field matrix (AV-UMFM) equations. Based on Particle Swarm optimization (PSO) algorithm, the adjustive vector of the model can be acquired despite ill-conditioned problems. Finally, adjustive vector controls currents to simultaneously compensate for multidirectional residual magnetic fields and builds magnetic compensation system.

关键词： Couplings Computational modeling Mathematical models Vectors Magnetic fields Electromagnetic fields Particle swarm optimization

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FROM MIDI TO RICH TABLATURES: AN AUTOMATIC GENERATIVE system INCORPORATING LEAD GUITARIstS' FINGERING AND stYLIstIC CHOICES 21

FROM MIDI TO RICH TABLATURES: AN AUTOMATIC GENERATIVE SYSTEM...

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21st Sound and Music Computing conference, SMC 2024

作者： Bontempi, Pierluigi Manerba, Daniele D'Hooge, Alexandre Canazza, Sergio Centro di Sonologia Computazionale Department of Information Engineering University of Padua Italy Department of Information Engineering Università degli Studi di Brescia Italy Univ. Lille CNRS Centrale Lille UMR 9189 CRIStAL LilleF-59000 France

ISBN: (纸本)9789893520758

Although the automatic identification of the optimal fingering for the performance of melodies on fretted string instruments has already been addressed (at least partially) in the literature, the specific case regarding lead electric guitar requires a dedicated approach. We propose a system that can generate, from simple MIDI melodies, tablatures enriched by fingerings, articulations, and expressive techniques. The basic fingering is derived by solving a constrained and multi-attribute optimization problem, which derives the best position of the fretting hand, not just the finger used at each moment. Then, by analyzing statistical data from the mySongBook corpus, the most common clichés and biomechanical feasibility, articulations, and expressive techniques are introduced. Finally, the obtained output is converted into MusicXML format, which allows for easy visualization and use. The quality of the tablatures derived and the high configurability of the proposed approach can have several impacts, in particular in the fields of instrumental teaching, assisted composition and arranging, and computational expressive music performance models. © 2024. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original.

关键词： Constrained optimization

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Resource-Efficient Sensor Fusion via system-Wide Dynamic Gated Neural Networks 21

Resource-Efficient Sensor Fusion via System-Wide Dynamic Gat...

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21st Annual IEEE International conference on Sensing, Communication, and Networking, SECON 2024

作者： Singhal, C. Wu, Y. Malandrino, F. de Guevara Contreras, S. Ladron Levorato, M. Chiasserini, C.F. INRIA France UC Irvine United States CNR-IEIIT Italy CNIT Italy Politecnico di Torino Italy Chalmers University of Technology Sweden

ISBN: (纸本)9798331519186

Mobile systems will have to support multiple AI-based applications, each leveraging heterogeneous data sources through DNN architectures collaboratively executed within the network. To minimize the cost of the AI inference task subject to requirements on latency, quality, and - crucially - reliability of the inference process, it is vital to optimize (i) the set of sensors/data sources and (ii) the DNN architecture, (iii) the network nodes executing sections of the DNN, and (iv) the resources to use. To this end, we leverage dynamic gated neural networks with branches, and propose a novel algorithmic strategy called Quantile-constrained Inference (QIC), based upon quantile-Constrained policy optimization. QIC makes joint, high-quality, swift decisions on all the above aspects of the system, with the aim to minimize inference energy cost. We remark that this is the first contribution connecting gated dynamic DNNs with infrastructure-level decision making. We evaluate QIC using a dynamic gated DNN with stems and branches for optimal sensor fusion and inference, trained on the RADIATE dataset offering Radar, LiDAR, and Camera data, and real-world wireless measurements. Our results confirm that QIC matches the optimum and outperforms its alternatives by over 80%. © 2024 IEEE.

关键词： Constrained optimization

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An Energy Supervisor Architecture for Energy-Harvesting Applications 21

An Energy Supervisor Architecture for Energy-Harvesting Appl...

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21st ACM/IEEE International conference on Information Processing in Sensor Networks (IPSN)

作者： Saoda, Nurani Wang, Wenpeng Billah, Md Fazlay Rabbi Masum Campbell, Bradford Univ Virginia Charlottesville VA 22903 USA

ISBN: (纸本)9781665496247

Energy-harvesting designs typically include highly entangled application-level and energy-management subsystems that span both hardware and software. This tight integration makes developing sophisticated energy-harvesting systems challenging, as developers have to consider both embedded system development and intermittent energy management simultaneously. Even when successful, solutions are often monolithic, produce suboptimal performance, and require substantial effort to translate to a new design. Instead, we propose a new energy-harvesting power management architecture, ALTAIR that offloads all energy-management operations to the power supply itself while making the power supply programmable. ALTAIR introduces an energy supervisor and a standard interface to enable an abstraction layer between the power supply hardware and the running application, making both replaceable and reconfigurable. To ensure minimal resource conflict on the application processor, while running resource-hungry optimization techniques in the supervisor, we implement the ALTAIR design in a lower power microcontroller that runs in parallel with the application. We also develop a programmable power supply module and a software library for seamless application development with ALTAIR. We evaluate the versatility of the proposed architecture across a spectrum of IoT devices and demonstrate the generality of the platform. We also design and implement an online energy-management technique using reinforcement learning on top of the platform and compare the performance against fixed duty-cycle baselines. Results indicate that sensors running the online energy-manager perform similar to continuously powered sensors, have a 10x higher event generation rate than the intermittently powered ones, 1.8-7x higher event detection accuracy, experience 50% fewer power failures, and are 44% more available than the sensors that maintain a constant duty-cycle.

关键词： Energy-harvesting system Design Dynamic Power Management

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Design and optimization of Air Supply system to Satisfy the Thermal Comfort of Human Body 21st

Design and Optimization of Air Supply System to Satisfy the ...

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21st International conference on Man-Machine-Environment system Engineering (MMESE)

作者： Qu, Jue Xue, Hongjun Wang, Wei Dang, Sina Zhang, Xiaoyan Northwestern Polytech Univ Xian 710072 Peoples R China Air Force Engn Univ Air & Missile Def Coll Xian 710051 Peoples R China

ISBN: (纸本)9789811659638;9789811659621

In view of this problem that the existing cockpit air supply system cannot meet the thermal comfort requirement of human body, causes the physical/psychological discomfort of pilots, and affects the work efficiency and safety of pilots, the design and optimization of the cockpit air supply system is studied to satisfy the thermal comfort of human body, in this paper. Firstly, a standard two-equation turbulence model is used to simulate the thermal environment of the cockpit in a large airliner under the original air supply system. It is concluded that the original air supply scheme does not meet the thermal comfort requirements of pilots. Secondly, the air supply condition of the cockpit air supply system is optimized and improved, and 18 optimization schemes are proposed. Finally, each optimization scheme is evaluated to obtain the optimal scheme which can satisfy the thermal comfort of human body. The design and optimization method of the air supply system established in this paper can be used in the study of thermal comfort and the design of the air supply system in the cockpit of large airliners.

关键词： Thermal comfort Air supply system Turbulence model Cockpit

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Application of energy performance contracts for rural remote areas electrification

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ENERGY REPORTS 2022年 8卷 1377-1386页

作者： Karamov, Dmitriy N. Minarchenko, Ilya M. Ilyushin, Pavel, V Suslov, Konstantin, V Filippov, Sergey P. Russian Acad Sci Energy Res Inst Nagornaya St31Bldg 2 Moscow 117186 Russia Russian Acad Sci Melentiev Energy Syst Inst Lermontov St 130 Irkutsk 664033 Russia Irkutsk Natl Res Tech Univ Lermontov St 83 Irkutsk 664074 Russia

The article is devoted to the application of energy performance contracts for the electrification of rural remote areas. The research presents a universal methodology for determining the main parameters of an energy performance contract. This methodology includes four main parts. The first part has a description of the climatic parameters on the territory under consideration and their use in mathematical modeling of isolated photovoltaic system operating modes. The second part has the mathematical models of an isolated photovoltaic system with battery energy storage system and diesel power plant. The third part consist of relevant questions and features of battery energy storage system operation in isolated energy systems. The fourth part is a hierarchical model of an energy performance contract. The model has the main indicators required for the client and contractor. These parameters are contract duration, contractor fee, modified levelized cost of energy and optimal composition of isolated energy system equipment. An isolated energy system located on the territory of Siberia was considered. The optimization results have the following key indicators: photovoltaic system (80 kW) with battery energy storage system (240 kW.h) reduces diesel fuel consumption by 68%. The energy performance agreement duration is 5 years and the modified levelized cost of energy is 15.53 RUB/kW.h. (C) 2022 Published by Elsevier Ltd.

关键词： Renewable energy sources Energy performance contract Hierarchical bilevel model Battery energy storage system Isolated energy system Rural remote areas

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Novel Hybrid 3-D Shape optimization Method Combining Parameter and Topology optimizations: Application to Permanent Magnet Motor

Novel Hybrid 3-D Shape Optimization Method Combining Paramet...

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IEEE conference on Electromagnetic Field Computation

作者： Yoshitsugu Otomo Takashi Abe Graduate School of Engineering Nagasaki University Nagasaki Japan

ISBN: (数字)9798350348958

ISBN: (纸本)9798350348965

This paper proposes a novel hybrid 3-D shape optimization method combining the parameter and topology optimizations. In the proposed optimization, the 3-D magnetic core shape is determined by topology optimization, whereas the magnet shape is determined by parameter optimization using the Boolean operation. It is shown that the 3-D optimized rotor structure leads to superior torque performance than the reference model which has uniform rotor structure along the rotating shaft.

关键词： Shafts Solid modeling Torque Shape Magnetic cores Rotors optimization methods

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