Energy-efficient and privacy-preserving spatial range aggregation query processing in wireless sensor networks by Liang Liu, Zhenhai Hu, Lisong Wang

“…The algorithm does not rely on the pre-established topology but considers only the query area that the user is interested in, abandoning all nodes to participate in distributing the query messages while gathering the sensory data in the query range. …”
Get full text

A Comparative Analysis of Artificial Intelligence Regulatory Law in Asia, Europe, and America by Alfiani Francisca Romana Nanik, Santiago Faisal

“…While the regulatory approaches differ across these regions, they share a common goal: ensuring that AI benefits society while minimizing negative impacts.…”
Get full text

An exploratory network analysis to investigate schizotypy’s structure using the ‘Multidimensional Schizotypy Scale’ and ‘Oxford-Liverpool Inventory’ in a healthy cohort by Pierfrancesco Sarti, Werner Surbeck, Giacomo Cecere, Noemi Dannecker, Rahel Horisberger, Nils Kallen, Wolfgang Omlor, Anna Steiner, Dario Palpella, Marius Brandenberg, Victoria Edkins, Nicolas Langer, Johanna M. C. Blom, Philipp Homan

“…Abstract Schizophrenia spectrum disorders and schizotypy share traits across positive, negative, and disorganised domains. …”
Get full text

Dual-Layer Dynamic Optimization Model for Carbon-Conscious Transport Mode Allocation by Jing Gan, Dongmei Yan, Linheng Li

“…A critical challenge lies in minimizing CO2 emissions from road networks while meeting diverse transport demands. However, at present the mode shares are set arbitrarily and may not be realistically achievable. …”
Get full text

Analysis of influencing factors and equity in hospitalization expense reimbursement for mobile populations based on random forest model: a cross-sectional study from China by Lisheng Shen, Xinan Lu, Yanyun Zhang, Lin Fei, Bo Dong

“…Secondly, the random forest algorithm was applied to evaluate the importance of the factors influencing hospitalization expense reimbursement. …”
Get full text

DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…Additionally, a lightweight cross-attention fusion module is introduced, optimizing the use of differential and shared features while minimizing computational complexity. …”
Get full text

Digital culture in the light of educational processes. Ad vocem for the remarks and musings of Jordan Shapiro concerning the digital childhood by Łukasz Androsiuk, Małgorzata Obrycka

“…The aim of this article is to analyze Jordan Shapiro’s concept of digital childhood and to critically engage with some of its fundamental assumptions. While the authors share the conviction that digital culture plays a crucial role in both institutional and non-institutional education, they emphasize, more than Shapiro does, its structural conditions, including algorithmic control mechanisms and the commercialization of educational processes. …”
Get full text

Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
Get full text

Determinants of depressive symptoms in multinational middle-aged and older adults by Can Lu, Shenwei Wan, Zhiyong Liu

“…Abstract This study harnesses machine learning to dissect the complex socioeconomic determinants of depression risk among older adults across five international cohorts (HRS, ELSA, SHARE, CHARLS, MHAS). Evaluating six predictive algorithms, XGBoost demonstrated superior performance in four cohorts (AUC 0.7677–0.8771), while LightGBM excelled in ELSA (AUC 0.9011). …”
Get full text

Control strategy of robotic manipulator based on multi-task reinforcement learning by Tao Wang, Ziming Ruan, Yuyan Wang, Chong Chen

“…To tackle this issue, instead of uniform parameter sharing, we propose an adjudicate reconfiguration network model, which we integrate into the Soft Actor-Critic (SAC) algorithm to address the optimization problems brought about by parameter sharing in multi-task reinforcement learning algorithms. …”
Get full text

Fog Service Placement Optimization: A Survey of State-of-the-Art Strategies and Techniques by Hemant Kumar Apat, Veena Goswami, Bibhudatta Sahoo, Rabindra K. Barik, Manob Jyoti Saikia

“…To process these data, it requires substantial computing and storage resources for smooth implementation and execution. While centralized cloud computing offers scalability, flexibility, and resource sharing, it faces significant limitations in IoT-based applications, especially in terms of latency, bandwidth, security, and cost. …”
Get full text

Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

“…The algorithm is designed to significantly enhance the inference and training speed of the model while improving detection accuracy, thus achieving more efficient and robust detection of water surface targets. …”
Get full text

A novel approach for music genre identification using ZFNet, ELM, and modified electric eel foraging optimizer by Shuang Zhang, Zhiyong Sun, Hasan Jafari

“…The present research suggests a new method for music genre identification via integrating deep learning models with a metaheuristic algorithm. The proposed model uses a pre-trained Zeiler and Fergus Network (ZFNet) to extract high-level features from audio signals, while an Extreme Learning Machines (ELM) is utilized for efficient classification. …”
Get full text

Low latency Montgomery multiplier for cryptographic applications by khalid javeed, Muhammad Huzaifa, Safiullah Khan, Atif Raza Jafri

“…The proposed Montgomery multiplier is based on school-book multiplier, Karatsuba-Ofman algorithm and fast adders techniques. The Karatsuba-Ofman algorithm and school-book multiplier recommends cutting down the operands into smaller chunks while adders facilitate fast addition for large size operands. …”
Get full text

Injustice épistémique et démocratie délibérative à l’ère du numérique : l’envers du mouvement #BalanceTaStartUp by Coline Sénac

“…I point out that anonymity, while allowing victims to share their experiences, becomes a weapon for online trolls and detractors, seeking to discredit these testimonies. …”
Get full text

Machine learning based on pangenome-wide association studies reveals the impact of host source on the zoonotic potential of closely related bacterial pathogens by Cheng Han, Shiying Lu, Pan Hu, Jiang Chang, Deying Zou, Feng Li, Yansong Li, Qiang Lu, Honglin Ren

“…Integrating these genes into an ML model based on the support vector machine (SVM) algorithm allows us to predict the zoonotic potential of various Brucella strains with high accuracy. …”
Get full text

Implementation and Performance of Lightweight Authentication Encryption ASCON on IoT Devices by Gabriela Cagua, Valerie Gauthier-Umana, Carlos Lozano-Garzon

“…The Internet of Things (IoT) is growing rapidly, enabling interconnected devices to communicate and share data seamlessly. While this expansion drives significant advancements across industries, it also introduces critical challenges in ensuring secure device communication. …”
Get full text

HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks by Luca Marchetti, Rosario Lombardo, Corrado Priami

“…HSimulator provides optimized implementation of a set of widespread state-of-the-art stochastic, deterministic, and hybrid simulation strategies including the first publicly available implementation of the Hybrid Rejection-based Stochastic Simulation Algorithm (HRSSA). HRSSA, the fastest hybrid algorithm to date, allows for an efficient simulation of the models while ensuring the exact simulation of a subset of the reaction network modeling slow reactions. …”
Get full text

Data augmentation scheme for federated learning with non-IID data by Lingtao TANG, Di WANG, Shengyun LIU

“…To solve the problem that the model accuracy remains low when the data are not independent and identically distributed (non-IID) across different clients in federated learning, a privacy-preserving data augmentation scheme was proposed.Firstly, a data augmentation framework for federated learning scenarios was designed.All clients generated synthetic samples locally and shared them with each other, which eased the problem of client drift caused by the difference of clients’ data distributions.Secondly, based on generative adversarial network and differential privacy, a private sample generation algorithm was proposed.It helped clients to generate informative samples while preserving the privacy of clients’ local data.Finally, a differentially private label selection algorithm was proposed to ensure the labels of synthetic samples will not leak information.Simulation results demonstrate that under multiple non-IID data partition strategies, the proposed scheme can consistently improve the model accuracy and make the model converge faster.Compared with the benchmark approaches, the proposed scheme can achieve at least 25% accuracy improvement when each client has only one class of samples.…”
Get full text

Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…This algorithm integrates the RepViT (Representation Learning with Visual Tokens) network to reduce computational complexity while capturing the global context of images. …”
Get full text