Deep Reinforcement Learning With Dueling DQN for Partial Computation Offloading and Resource Allocation in Mobile Edge Computing by Ehzaz Mustafa, Junaid Shuja, Faisal Rehman, Abdallah Namoun, Mazhar Ali, Abdullah Alourani

“…Computation offloading transfers resource-intensive tasks from local Internet of Things (IoT) devices to powerful edge servers, which minimizes latency and reduces the computational load on IoT devices. …”
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Hardcoded vulnerability detection approach for IoT device firmware by Chao MU, Xin WANG, Ming YANG, Heng ZHANG, Zhenya CHEN, Xiaoming WU

“…With the popularization of IoT devices, more and more valuable data is generated.Analyzing and mining big data based on IoT devices has become a hot topic in the academic and industrial circles in recent years.However, due to the lack of necessary detection and protection methods, many IoT devices have serious information security risks.In particular, device hard-coded information is closely related to system encryption and decryption, identity authentication and other functions, which can provide confidentiality protection for core data.Once this information is exploited by malicious attackers, serious consequences such as sensitive information leakage, backdoor attacks, and unauthorized logins will occur.In response to this problem, a multi-type character recognition and positioning scheme was designed and a hard-coded vulnerability detection method in executable files was proposed based on the study of the characteristics of hard-coded vulnerabilities in IoT devices.The proposed method extracted the firmware of IoT devices and filtered all executable files as the source to be analyzed.Then, a solution to identify and locate three types of hard-coded characters was provided.Further, the reachability of the function, where the hard-coded character was located, was analyzed according to the function call relationship.Meanwhile, the instruction heterogeneity was mitigated by an intermediate representation (IR) model.The character and parameter hard-coded values was obtained through a data flow analysis approach.A symbolic execution method was devised to determine the trigger conditions of the hard-coded vulnerabilities, and then the vulnerability detection result was output.On the one hand, the proposed method introduced the method of symbolic execution based on the use of the intermediate representation model, which eliminated the dependency of instruction architecture and reduces the false positive rate of vulnerabilities; On the other hand, this method can integrate characters, files, and cryptographic implementation to realize the different characteristics of three types of hard-coded characters, which increased the coverage of vulnerability detection and improves the versatility of the detection method.The experimental results show that the proposed method can effectively detect three types of hard-coded vulnerabilities of characters, files and cryptographic implementation in various IoT devices, and has good detection accuracy, which can provide certain guidance for the deployment of subsequent security protection technologies.…”
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Exploring the impact of GeoGebra on preservice teachers’ proficiency in teaching grade 10 parabola functions by Abongile Ngwabe, Marc Schafer

“…This paper investigates the development of teaching proficiency among preservice teachers in Grade 10 parabola functions through the use of GeoGebra. A significant number of preservice teachers encounter challenges in effectively teaching parabola functions due to limited resources for illustrating complex mathematical relationships, which can impede both their teaching proficiency and the students' conceptual understanding. …”
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Narrow-spectrum resource-utilizing bacteria drive the stability of synthetic communities through enhancing metabolic interactions by Wei Wang, Yanwei Xia, Panpan Zhang, Mengqing Zhu, Shiyi Huang, Xinli Sun, Zhihui Xu, Nan Zhang, Weibing Xun, Qirong Shen, Youzhi Miao, Ruifu Zhang

“…Abstract The importance of synthetic microbial communities in agriculture is increasingly recognized, yet methods for constructing targeted communities using existing microbial resources remain limited. Here, six plant-beneficial bacterial strains with distinct functions and rhizosphere resource utilization profiles are selected to construct stable, multifunctional communities for plant growth promotion. …”
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Merging Surface Plasmon Optical Detection with Electronic Sensing by Wolfgang Knoll

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Web 2.0 as Catalyst: Virtually Reaching Out to Users and Connecting Them to Library Resources and Services. by Norah Xiao

“…These Web 2.0 technologies function as catalysts which help lower human barriers between my users and me, enable me to reach my users virtually, and attract users to resources from the library as well as various services I provided [ABSTRACT FROM AUTHOR] …”
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Antioxidant Peptides Derived from Woody Oil Resources: Mechanisms of Redox Protection and Emerging Therapeutic Opportunities by Jia Tu, Jie Peng, Li Wen, Changzhu Li, Zhihong Xiao, Ying Wu, Zhou Xu, Yuxi Hu, Yan Zhong, Yongjun Miao, Jingjing Xiao, Sisi Liu

“…Antioxidant peptides derived from woody oil resource by-products exhibit strong free radical scavenging abilities and offer potential applications in functional foods, nutraceuticals, and cosmetics. …”
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Optimization of D2D emergency communication resources for UAV relay based on DA-STD3 by Xiaofang Deng, Zijian Deng, Lin Zheng, Chao Yang, Chuanxu Chen

“…By designing the reward function and training mechanism, we can achieve good power control and reduce communication interference. …”
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Kriging-Based Variable Screening Method for Aircraft Optimization Problems with Expensive Functions by Yadong Wang, Xinyao Duan, Jiang Wang, Jin Guo, Minglei Han

“…The computational complexity of airfoil optimization for aircraft wing designs typically involves high-dimensional parameter spaces defined by geometric variables, where each Computational Fluid Dynamics (CFD) simulation cycle may require significant processing resources. Therefore, performing variable selection to identify influential inputs becomes crucial for minimizing the number of necessary model evaluations, particularly when dealing with complex systems exhibiting nonlinear and poorly understood input–output relationships. …”
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Sensory integration research: priority scientific directions based on the analysis of Web of Science Core Collection resources by Olha Podrihalo, Wladyslaw Jagiello, Guo Xiaohong, Leonid Podrigalo, Tetiana Yermakova, Miroslawa Cieslicka

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AI for Sustainable Recycling: Efficient Model Optimization for Waste Classification Systems by Oriol Chacón-Albero, Mario Campos-Mocholí, Cédric Marco-Detchart, Vicente Julian, Jaime Andrés Rincon, Vicent Botti

“…We introduce an expanded dataset that includes an organic waste class and more heterogeneous images, and evaluate a range of quantized CNN models to reduce inference time and resource usage. Additionally, we explore ensemble strategies using aggregation functions to boost classification performance, and validate selected models on real embedded hardware and under simulated lighting variations. …”
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Image Processing for Laser Impact Detection in Shooting Simulators by José Antonio García Torres, Daniel Guzmán Pérez, Jhon Fredy Rincón Morantes, Daniel Felipe Molina Martínez, Cristian Camilo García Rodríguez, Jhonnatan Eduardo Zamudio Palacios

“…Moreover, wired setups limit their use in outdoor environments due to the lack of access to a power source. This study developed an image-processing-based method to replace live ammunition with a laser-emitting device. …”
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Functional Data Analysis for Prediction of Employee Presence by Nouhaila Goujili, Matthieu Saumard, Nicolas Cochard, Maher Jridi

“…Accurate presence prediction tools can optimize resource utilization and support strategic decisions in corporate real estate. …”
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Infrared Satellite Detection Limits for Monitoring Atmospheric Ammonia by Mark W. Shephard, Shailesh K. Kharol, Enrico Dammers, Christopher E. Sioris, Andrew Bell, Rik Jansen, Jerome Caron, Ralph Snel, Emanuela Palombo, Karen E. Cady-Pereira, Chris A. McLinden, Erik Lutsch, Robert O. Knuteson

“…Information on the frequency of a given detection limit, and the cumulative probability of detection, are provided as a function of instrument spectral resolution and noise. …”
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Nitrogen and CO2 enrichment interact to decrease biodiversity impact on complementarity and selection effects by Mengjiao Huang, Peter B. Reich, Shaopeng Wang, Yanhao Feng, Pubin Hong, Kathryn E. Barry, Miao He, Shengman Lyu, Shurong Zhou, Neha Mohanbabu, Forest Isbell, Yann Hautier

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Identification of positive selection signatures associated with milk and composition traits in Murciano-Granadina and Barki by Hossein Mohammadi, amir hossien khaltabadi farahani, Mohammad Hossein Moradi

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Forecasting dengue in Bangladesh using meteorological variables with a novel feature selection approach by Mahadee Al Mobin

“…A novel wrapper feature selection algorithm employing a custom objective function is proposed in this study, which significantly improves model accuracy by 12.63% and reduces the mean absolute percentage error by 70.82%. …”
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A Hybrid Decision-Making Model for Optimal Portfolio Selection under Interval Uncertainty by Mohsen Zahmati Iraj, Meysam Doaei

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Educational content selection in human rights education at the early childhood education and care level by Anette Ringen Rosenberg

“…It aims to discuss the function of four content selection dimensions for discussing HRE content at the ECEC level. …”
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Client Selection for Generalization in Accelerated Federated Learning: A Multi-Armed Bandit Approach by Dan Ben Ami, Kobi Cohen, Qing Zhao

“…It has attracted a growing interest in recent years due to its advantages in terms of privacy considerations, and communication resources. In FL, selected clients train their local models and send a function of the models to the server, which consumes a random processing and transmission time. …”
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