Cloud Removal Advances: A Comprehensive Review and Analysis for Optical Remote Sensing Images by Jin Ning, Lianbin Xie, Jie Yin, Yiguang Liu

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A Micro-Segmentation Method Based on VLAN-VxLAN Mapping Technology by Di Li, Zhibang Yang, Siyang Yu, Mingxing Duan, Shenghong Yang

“…However, this shift has introduced a new array of security challenges, necessitating innovative approaches distinct from traditional network security architectures. …”
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Does Digitalization Lead to Better Transparency: Bibliometric Approach by Pavlo Kostetskyi

“…The density visualization showed that the most relevant keywords in publications on transparency and digitalization are digitalization, blockchain, and industry 4.0. …”
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INFORMATION-ANALYTICAL SYSTEM OF MONITORING OF THE SHADOW OF NON-CASH FLOW: BASIC ELEMENTS, AUTHOR’S SIMULATION ALGORITHM by E. Baturina

“…The purpose of this article is to present the economic and mathematical toolkit for the analysis of information about the shadow activity of subjects of economic crimes and visualization of the structure of the information and analytical system for monitoring the shadow cash flow. …”
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Modelling and simulation of the block pouring construction system considering spatial–temporal conflict of construction machinery in arch dams by Zhipeng Liang, Jiayao Peng, Chunju Zhao, Huawei Zhou, Dongfeng Li, Yihong Zhou, Quan Liu, Xiaodong Li, Cheng Zhang, Fang Wang

“…Combined with the typical pouring block in Baihetan arch dam, the construction process is simulated and the visualization system is developed, which achieves the information integration such as the quantification of the spatial–temporal conflict, the analysis of the influence effects, and the visualization of conflict information. …”
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Investigating the Performance of Retrieval-Augmented Generation and Domain-Specific Fine-Tuning for the Development of AI-Driven Knowledge-Based Systems by Róbert Lakatos, Péter Pollner, András Hajdu, Tamás Joó

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Ultrasound Guidance for Deep Peripheral Nerve Blocks: A Brief Review by Anupama Wadhwa, Sunitha Kanchi Kandadai, Sujittra Tongpresert, Detlef Obal, Ralf Erich Gebhard

“…The use of ultrasound does not replace experience and knowledge of relevant anatomy, especially for visualization of deep structures. In certain scenarios, ultrasound may not offer additional value and substantial amount of time may be spent trying to find relevant structures or even provide a false sense of security, especially to an inexperienced operator. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“… Dangerous insects are a significant risk to the global agricultural industry, threatening food security, economic stability, and crop quality. This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“… Dangerous insects are a significant risk to the global agricultural industry, threatening food security, economic stability, and crop quality. This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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Modellierung von Zweifel – Vorbild TEI im Graphen by Andreas Kuczera, Dominik Kasper

“…This applies in particular if additional information on the degree of security of a resolution is possible. Graph technologies offer possibilities for modeling, visualization and analysis of uncertainty and responsibility. …”
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Biochar soil amendments affect mycorrhizal colonization, root nodulation and dry matter accumulation in cowpeas (Vigna unguiculata (L.) Walp.) by Ifeyinwa Monica UZOH, Keabetswe Chriscellda RAMADILE, Uchechukwu Paschal CHUKWUDI, Ozede Nicholas IGIEHON, Akinlolu Olalekan AKANMU, Olubukola Oluranti BABALOLA

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An Evaluation Method for Distribution Network Operation Based on Multi-source Data Deep Fusion by Junfeng QIAO, Aihua ZHOU, Lin PENG, Yiqing WANG, Xiaofeng SHEN, Sen PAN, Pei YANG, Chenhong HUANG

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Design and development of an efficient RLNet prediction model for deepfake video detection by Varad Bhandarkawthekar, T. M. Navamani, Rishabh Sharma, K. Shyamala

“…This research significantly contributes to digital media forensics by providing an advanced tool for detecting deepfake videos, enhancing digital content's security and integrity. The efficacy and resilience of the proposed system are evidenced by deepfake detection, while our visualization-based interpretability provides insights into our model.…”
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Adaptable Reduced-Complexity Approach Based on State Vector Machine for Identification of Criminal Activists on Social Media by Imran Shafi, Sadia Din, Zahid Hussain, Imran Ashraf, Gyu Sang Choi

“…Security agencies face an emerging challenge of identifying and counter the malicious contents spread on the social media by the terrorists. …”
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Detection of SSL/TLS protocol attacks based on flow spectrum theory by Shize GUO, Fan ZHANG, Zhuoxue SONG, Ziming ZHAO, Xinjie ZHAO, Xiaojuan WANG, Xiangyang LUO

“…Network attack detection plays a vital role in network security.Existing detection approaches focus on typical attack behaviors, such as Botnets and SQL injection.The widespread use of the SSL/TLS encryption protocol arises some emerging attack strategies against the SSL/TLS protocol.With the network traffic collection environment that built upon the implements of popular SSL/TLS attacks, a network traffic dataset including four SSL/TLS attacks, as well as benign flows was controlled.Considering the problems that limited observability of existing detection and limited separation of the original-flow spatiotemporal domains, a flow spectrum theory was proposed to map the threat behavior in the cyberspace from the original spatiotemporal domain to the transformed domain through the process of “potential change” and obtain the “potential variation spectrum”.The flow spectrum theory is based on a set of separable and observable feature representations to achieve efficient analysis of network flows.The key to the application of flow spectrum theory in actual cyberspace threat behavior detection is to find the potential basis matrix for a specific threat network flow under the condition of a given transformation operator.Since the SSL/TLS protocol has a strong timing relationship and state transition process in the handshake phase, and there are similarities between some SSL/TLS attacks, the detection of SSL/TLS attacks not only needs to consider timing context information, but also needs to consider the high-separation representation of TLS network flows.Based on the flow spectrum theory, the threat template idea was used to extract the potential basis matrix, and the potential basis mapping based on the long-short-term memory unit was used to map the SSL/TLS attack network flow to the flow spectrum domain space.On the self-built SSL/TLS attack network flow data set, the validity of the flow spectrum theory is verified by means of classification performance comparison, potential variation spectrum dimensionality reduction visualization, threat behavior feature weight evaluation, threat behavior spectrum division assessment, and potential variation base matrix heatmap visualization.…”
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A dynamic airspace grid map based on 3D subdivision framework by B. Han, T. Qu

“…Grid map also models static and dynamic airspace, including obstacles, dynamic airspace attributes, aircraft, and can achieve intelligent visualization of time- variance airspace. Finally, the dynamic airspace grid map can organize and store static and dynamic spatial data based on a 3D subdivision framework to ensure the orderliness and security of the airspace domain.…”
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Land Target Detection Algorithm in Remote Sensing Images Based on Deep Learning by Wenyi Hu, Xiaomeng Jiang, Jiawei Tian, Shitong Ye, Shan Liu

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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…Abstract The defense of malware remains an important research hotspot in the field of cyberspace security. Recognizing its profound research significance, our defense against malware is still an important research hotspot in the field of cyberspace security. …”
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YOLOv8 framework for COVID-19 and pneumonia detection using synthetic image augmentation by Uddin A Hasib, Raihan Md Abu, Jing Yang, Uzair Aslam Bhatti, Chin Soon Ku, Lip Yee Por

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New Images of the Globalized World Crossed by Artificial Intelligence by Vanina Rodríguez

“…Finally, there must be more robust data privacy and security regulations to protect users' data and ensure that it is not misused.…”
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