URcon: Unified and Reconfigurable Control and Verification Platform for Multi-Mode Customized eDRAM and SRAM Macros by Ho-Sung Lee, Ik-Hyeon Jeon, Jiwon Lee, Hyeonjun Cheon, Joo-Hyung Chae

“…With the rapid development of various technologies, processing large amounts of data has become essential. …”
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DEVELOPMENT OF AN INFORMATION SYSTEM FOR MANAGING SCIENTIFIC ACHIEVEMENTS AND CAREER GROWTH OF ACADEMIC STAFF IN HIGHER EDUCATION INSTITUTIONS by D. Semonkin, O. Sakaliuk, P. Lomovtsev

“…This article explores the development of an information system that ensures centralized storage, processing, and analysis of data on research and teaching activities in HEIs. …”
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FPGA-Based Sensors for Distributed Digital Manufacturing Systems: A State-of-the-Art Review by Laraib Khan, Sriram Praneeth Isanaka, Frank Liou

“…Here, DTs serve as a virtual replica of physical machines, allowing accurate monitoring and control of a given manufacturing process. These DTs are supplemented by sensors, providing near-real-time data to assure the effectiveness of the manufacturing processes. …”
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Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis by Fatma Hilal Yagin, Cemil Colak, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

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Healthcare Internet of Things system implementations for COVID-19 prevention by Jichao Leng, Zihuai Lin, Soojeong Yoo, Gabriella Scandurra, Michael Dickinson, Branka Vucetic, Audrey P. Wang

“…This solution integrated a contactless health self-service web app, thermal camera, and physical barrier to automate the COVID-19 health screening and data recording process. During the 3-month pilot period, we deployed the eGate at multiple entrances to the hospital, and monitored the number of users of the system in different periods. …”
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Recurrent Neural-Based Vehicle Demand Forecasting and Relocation Optimization for Car-Sharing System: A Real Use Case in Thailand by Peerapon Vateekul, Panyawut Sri-iesaranusorn, Pawit Aiemvaravutigul, Adsadawut Chanakitkarnchok, Kultida Rojviboonchai

“…The data preprocessing is presented in order to automatically remove fake demands caused by search failures and application errors. …”
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Development of Integrated Neural Network Model for Identification of Fake Reviews in E-Commerce Using Multidomain Datasets by Saleh Nagi Alsubari, Sachin N. Deshmukh, Mosleh Hmoud Al-Adhaileh, Fawaz Waselalla Alsaade, Theyazn H. H. Aldhyani

“…Convolutional and max-pooling layers of the CNN technique are implemented for dimensionality reduction and feature extraction, respectively. Based on gate mechanisms, the LSTM layer is combined with the CNN technique for learning and handling the contextual information of n-gram features of the review’s text. …”
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Homomorphic Evaluation Cluster Architecture for Fully Homomorphic Encryption by Hanyoung Lee, Ardianto Satriawan, Hanho Lee

“…Fully Homomorphic Encryption (FHE) allows computational processing of encrypted data on cloud servers, providing high security and enabling safe data utilization. …”
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Leveraging life cycle assessment for energy transition in iron ore production by Mahdi Pouresmaieli, Ali Nouri Qarahasanlou, Abbas Barabadi

“…In this study, titled “Reducing the Carbon Footprint of a Medium-Scale Iron Ore Complex with a Sustainable Development Approach”, a Cradle-to-Gate Life Cycle Assessment (LCA) was conducted across the stages of extraction, concentrate processing, and pellet production. …”
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Evaluating environmental impacts of thorium extraction: A comparative study of solvent and electrosorption technologies using life cycle assessment (LCA) by Naseem Akhtar, Aznan Fazli Ismail, Marlia Mohd Hanafiah, Syazwani Mohd Fadzil, Sulgiye Park

“…The LCA was conducted from cradle to gate, incorporating inventory data from the Ecoinvent database 3 and SimaPro software version 9, with inputs of raw material extraction, transportation, energy consumption, and chemical uses. …”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

“…At present, most of the gait-based smartphone authentication researches focus on a single controlled scenario without considering the impact of multi-scenario changes on the authentication accuracy.The movement direction of the smartphone and the user changes in different scenarios, and the user’s gait data collected by the orientation-sensitive sensor will be biased accordingly.Therefore, it has become an urgent problem to provide a multi-scenario high-accuracy gait authentication method for smartphones.In addition, the selection of the model training algorithm determines the accuracy and efficiency of gait authentication.The current popular authentication model based on long short-term memory (LSTM) network can achieve high authentication accuracy, but it has many training parameters, large memory footprint, and the training efficiency needs to be improved.In order to solve the above problems a multi-scenario gait authentication scheme for smartphones based on Gate Recurrent Unit (GRU) was proposed.The gait signals were preliminarily denoised by wavelet transform, and the looped gait signals were segmented by an adaptive gait cycle segmentation algorithm.In order to meet the authentication requirements of multi-scenario, the coordinate system transformation method was used to perform direction-independent processing on the gait signals, so as to eliminate the influence of the orientation of the smartphone and the movement of the user on the authentication result.Besides, in order to achieve high-accuracy authentication and efficient model training, GRUs with different architectures and various optimization methods were used to train the gait model.The proposed scheme was experimentally analyzed on publicly available datasets PSR and ZJU-GaitAcc.Compared with the related schemes, the proposed scheme improves the authentication accuracy.Compared with the LSTM-based gait authentication model, the training efficiency of the proposed model is improved by about 20%.…”
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Enhancing Spatial Ability Assessment: Integrating Problem-Solving Strategies in Object Assembly Tasks Using Multimodal Joint-Hierarchical Cognitive Diagnosis Modeling by Jujia Li, Kaiwen Man, Joni M. Lakin

“…We proposed a novel approach to investigate how problem-solving strategies, identified using response time and eye-tracking data, can impact individuals’ performance on the Object Assembly (OA) task. …”
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EDB-Net: Efficient Dual-Branch Convolutional Transformer Network for Hyperspectral Image Classification by Hufeng Guo, Wenyi Liu

“…Hyperspectral image (HSI) classification, as a pivotal technology in remote sensing data processing, has garnered significant attention in recent years. …”
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Improving the Fast Fourier Transform for Space and Edge Computing Applications with an Efficient In-Place Method by Christoforos Vasilakis, Alexandros Tsagkaropoulos, Ioannis Koutoulas, Dionysios Reisis

“…The execution of inputs ranging from 1K to 16K FFT points, using 8-bit or 16-bit as FP or BFP numbers, on the space-proven Atmel AVR32 and Vision Processing Unit (VPU) Intel Movidius Myriad 2, the edge device Raspberry Pi Zero 2W and a low-cost accelerator on Xilinx Zynq 7000 Field Programmable Gate Array (FPGA), validates the method’s performance improvement.…”
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Hardware Implementation for Triaxial Contact-Force Estimation from Stress Tactile Sensor Arrays: An Efficient Design Approach by María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín, José A. Hidalgo-López

“…This paper presents a contribution to the state of the art in the design of tactile sensing algorithms that take advantage of the characteristics of generalized sparse matrix-vector multiplication to reduce the area, power consumption, and data storage required for real-time hardware implementation. …”
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Intelligent prediction method of virtual network function resource capacity for polymorphic network service slicing by Julong LAN, Di ZHU, Dan LI

“…Results: From the experimental results, the prediction performance of this method is mainly reflected in the following aspects:1.The prediction accuracy of this method is stable.The primary reason is that the method adopts a reasonable spatiotemporal feature extraction structure, which can effectively deal with both the spatial structure with non-Euclidean features and the time series features with contextual dependencies.The secondary reason is that the weighted preprocessing process of the input data stream sequence in this method effectively avoids the characteristic mutation caused by the burst flow in the network,and can truly reflect the changing trend of the data stream and slicing capacity requirements, thus obtaining stable prediction effect. 2. …”
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Adaptive Quantum-Inspired Evolution for Denoising PCG Signals in Unseen Noise Conditions by Lubna Siddiqui, Ashish Mani, Jaspal Singh

“…The results position the proposed algorithm as a data-efficient, noise-adaptable alternative solution critical in resource-constrained dynamic situations across unseen noise patterns. …”
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Environmental Assessment of Cellulose Pulp Production from Wood Waste using Organosolv Treatment by Pazzaglia Aron, Romagnoli Francesco, Castellani Beatrice

“…Further research is warranted to explore energy consumption during the organosolv process for obtaining more precise data and optimizing the process. …”
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Research on Fault Prediction of Power Devices in Rod Control Power Cabinets Based on BiTCN-Attention Transfer Learning Model by Zhi Chen, Liqi Ye, Yifan Jian, Meiyuan Chen, Yuan Min

“…Then, after pre-processing such as removing outliers, kernel principal component analysis (KPCA) was used to integrate all source domain data, obtain source domain characterization data, and train the BiTCN-attention model. …”
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CircuitHD: Brain-Inspired Hyperdimensional Computing for Circuit Recognition by Paul R. Genssler, Lilas Alrahis, Ozgur Sinanoglu, Hussam Amrouch

“…Circuits possess an irregular representation. Hence, their data structure (e.g., gate-level netlists) necessitate the encoding into fixed formats like vectors. …”
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