Single-cell RNA-seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-seq by genetic and contextual informat... by Thatchayut Unjitwattana, Qianhui Huang, Yiwen Yang, Leyang Tao, Youqi Yang, Mengtian Zhou, Yuheng Du, Lana X. Garmire

“…Abstract Single-cell RNA sequencing (scRNA-seq) data from complex human tissues have prevalent blood cell contamination during the sample preparation process. They may also comprise cells of different genetic makeups. …”
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Parallel and distributed chimp-optimized LSTM for oil well-log reconstruction in China by Zisong Wang, Zhiliang Cheng, Wenxiang Wang, Xiujian Ding, Lu Xia

“…PDCOA’s primary goal is to speed up the process of hyperparameter tuning for LSTMs by letting them work in parallel and across multiple computers, with separate groups of computers communicating with each other regularly to ensure the system is diverse and reliable. …”
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Damage toughness assessment method of power backbone communication network based on power big data by Xue HAN

“…The damage toughness assessment method of power backbone communication network based on power big data was studied, and the damage toughness assessment results were used to formulate protection strategies and improve the network survivability.The power backbone communication network and the attacker were set as the two sides of the game, and the Nash equilibrium strategy of both sides was determined by the minimax method.The damage probability of nodes was obtained by the Nash equilibrium strategy, and the node damage probability was transformed into the network damage form.According to the network damage pattern, the repair conditions contained in the power big data were obtained by cloud computing technology.According to the importance of each node, the repair resources and repair budget were allocated to the nodes in order.The performance time-history response curve of the power backbone communication network was constructed, and the dynamic evaluation results of the network damage toughness were output.The experimental results show that all operations using cloud computing technology to process massive power big data can not exceed 330 ms.When the repair budget and repair resources are the highest, the damage toughness of the power backbone communication network can reach 0.925 at most, indicating that this method can effectively evaluate the damage toughness of the power backbone communication network.…”
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Quality of Experience Optimization for AR Service in an MEC Federation System by Huong Mai do, Tuan Phong Tran, Myungsik Yoo

“…Augmented reality (AR) in the internet of things requires ultra-low latency, high-resolution video, and fairness in multi-user environments, which pose challenges for traditional cloud and edge computing. To address this shortcoming, we studied AR subtask offloading and resource allocation in a multi-hop, multi-access edge computing federation. …”
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Damage toughness assessment method of power backbone communication network based on power big data by Xue HAN

“…The damage toughness assessment method of power backbone communication network based on power big data was studied, and the damage toughness assessment results were used to formulate protection strategies and improve the network survivability.The power backbone communication network and the attacker were set as the two sides of the game, and the Nash equilibrium strategy of both sides was determined by the minimax method.The damage probability of nodes was obtained by the Nash equilibrium strategy, and the node damage probability was transformed into the network damage form.According to the network damage pattern, the repair conditions contained in the power big data were obtained by cloud computing technology.According to the importance of each node, the repair resources and repair budget were allocated to the nodes in order.The performance time-history response curve of the power backbone communication network was constructed, and the dynamic evaluation results of the network damage toughness were output.The experimental results show that all operations using cloud computing technology to process massive power big data can not exceed 330 ms.When the repair budget and repair resources are the highest, the damage toughness of the power backbone communication network can reach 0.925 at most, indicating that this method can effectively evaluate the damage toughness of the power backbone communication network.…”
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Federated deep reinforcement learning-based edge collaborative caching strategy in space-air-ground integrated network by LIU Liang, JING Tengxiang, DUAN Jie, MAO Wuping, YAN Hongcheng, MA Wenjie

“…To address the problem of limited network coverage in remote areas, combining space-air-ground integrated network with mobile edge computing could provide low-latency and high-reliability transmissions for user requests in these areas, as well as timely caching services. …”
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5G defense network using commercial gNodeB with zero trust architecture by Woocheol Kim, Sunji Oh, Chang-Gyu Lim, Kiwon Kim, Jongkuk Lee, Hea-Sook Park

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Computational approach to identify novel genomic features conferring high fitness in Bacillus atrophaeus CNY01 and Bacillus velezensis AK-0 associated with plant growth promotion (... by Vandana Apurva Das, Budhayash Gautam, Pramod Kumar Yadav, Pritish Kumar Varadwaj, Gulshan Wadhwa, Satendra Singh

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Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems by Maham Nayab, Asim Waris, Muhammad Jawad Khan, Dokhyl AlQahtani, Ahmed Imran, Syed Omer Gilani, Umer Hameed Shah

“…This approach aims to improve the classification accuracy of EMG signals while substantially reducing computational costs, offering valuable implications for all EMG-related processes on such data. …”
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A GDPR-compliant solution for analysis of large-scale genomics datasets on HPC cloud infrastructure by Silvia Gioiosa, Beatrice Chiavarini, Mattia D’Antonio, Giuseppe Trotta, Balasubramanian Chandramouli, Juan Mata Naranjo, Giuseppa Muscianisi, Mirko Cestari, Elisa Rossi

“…Abstract This paper outlines the technical and organizational measures implemented by the Italian supercomputing center, CINECA, to efficiently collect, process, and store sensitive-omics data in compliance with GDPR regulations. …”
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DRL-Driven Intelligent SFC Deployment in MEC Workload for Dynamic IoT Networks by Seyha Ros, Intae Ryoo, Seokhoon Kim

“…The framework introduces task offloading and a dynamic resource orchestration strategy, where task offloading to the MEC server ensures an efficient distribution of computation workloads. The dynamic resource orchestration process, Service Function Chaining (SFC) for Virtual Network Functions (VNFs) placement, and routing path determination optimize service execution across the network. …”
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Demand Response Management with Latency Difference in Distributed Wireless Network by Qingfeng Ding, Qianliang Liu, Hui Shi, Jing Luo

“…Notably, the local solution can handle, in terms of the emergency DR, the emergency tasks in time, and the centralized processing solution can update and process the general DR.…”
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Addressing process-induced porosity variations in multiscale composite materials analysis using aggregated projection clustering and Halton sequence RVE sampling by Hamidreza Dehghani, Henri Perrin, Elias Belouettar-Mathis, Borek Patzák, Salim Belouettar

“…To address this, we propose an unsupervised machine learning approach integrated with micro-computed tomography (μCT) image processing and Asymptotic Homogenization (AH) for accurate and robust consideration of real microstructure as the basis for an upscaling process. …”
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Towards smart fruit dryers: Integrating machine vision and response surface methodology for multi-objective monitoring and optimization of kiwifruit drying process by Sadegh Azizi Ishkooh, Hemad Zareiforoush, Adel Bakhshipour

“…This study aimed to monitor and optimize the kiwifruit drying process in a combined convection–infrared hot air dryer using computer vision and Response Surface Methodology (RSM). …”
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Process Monitoring and Control in Dermatological Diagnosis: A Deep Learning Approach Using Python, NumPy, Pandas, Keras, and TensorFlow by Neelamadhab Padhy, T. Bhubaneswari, Sushree Sangita Das, Meetali Sinha

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HyperCell: A Bio-inspired Design Framework for Real-time Interactive Architectures by Jia-Rey Chang

“…“Form” has always been the most critical focus in architectural design, and this focus has also been a major driver behind the application computational design in Architecture. Nonetheless, this research will interpret the term “Form” in architecture as a continual “information processor” rather than the result of information processing. …”
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Framework for Analysis of Queueing Systems with Correlated Arrival Processes and Simultaneous Service of a Restricted Number of Customers in Scenarios with an Infinite Buffer and R... by Alexander Dudin, Sergei Dudin, Agassi Melikov, Olga Dudina

“…This chain behaves as the finite-state quasi-death process between successive service-beginning epochs, with jumps occurring at these epochs. …”
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Context-dependent similarity analysis of analogue series for structure–activity relationship transfer based on a concept from natural language processing by Atsushi Yoshimori, Jürgen Bajorath

“…Pairs of active AS consisting of compounds with corresponding substituents and comparable potency progression represent SAR transfer events for the same target or across different targets. We report a new computational approach to systematically search for SAR transfer series that combines an AS alignment algorithm with context-depending similarity assessment based on vector embeddings adapted from natural language processing. …”
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RESEARCH OF PROCESSES OF HEAT TRANSFER IN THE COOLING SYSTEM ELEMENTS REA, MADE ON THE BASIS OF MELTING HEAT ACCUMULATORS WITH ADDITIONAL LIQUID HEAT SINK by T. A. Ismailov, O. V. Evdulov, D. V. Evdulov, D. K. Ramazanova

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Double Deep Q-Network-Based Solution to a Dynamic, Energy-Efficient Hybrid Flow Shop Scheduling System with the Transport Process by Qinglei Zhang, Huaqiang Si, Jiyun Qin, Jianguo Duan, Ying Zhou, Huaixia Shi, Liang Nie

“…In addition, 36 test instances of varying sizes, simplified from the excavator boom manufacturing process, are designed for comparative experiments with traditional algorithms. …”
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