Hybrid Deep Learning Techniques for Improved Anomaly Detection in IoT Environments by Hanan Abbas Mohammad

“…There are numerous deep learning competencies, but LSTM is one of the ones used to interpret big data or time series data. But, it is not easy to find what is the best weights for LSTMs in order to directly achieve performance. …”
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Association Between Deforestation and the Incidence of Snakebites in South Korea by Seoheui Lee, Junyeong Lee, Kyung-Duk Min

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Competencias del ingeniero industrial en la Industria 4.0 by Isidro Jesús González-Hernández, Rafael Granillo-Macías

“…Los resultados muestran que se deben desarrollar competencias específicas basadas en las Tecnologías de la Información y la Comunicación, como big data, Internet de las cosas y Simulación, con el propósito de interactuar en los ambientes inteligentes que propone la Industria 4.0. …”
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Credit Risk Contagion Based on Asymmetric Information Association by Shanshan Jiang, Hong Fan, Min Xia

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Crocodile optimization algorithm for solving real-world optimization problems by Fu Yan, Jin Zhang, Jianqiang Yang

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Design and Implementation of BIM-Based Construction Supervision Platform for Hydraulic Engineering by YANG Chuhua, RAO Fanwei, FU Zhihao, LIAO Xiangjun

“…With the continuous promotion of high-quality development of water conservancy in the new era,it has become an inevitable trend to make full use of information technologies such as BIM,digital twins,and simulations to integrate and innovate with the water conservancy industry.In hydraulic engineering,an intelligent management system focusing on “BIM+a whole life cycle” has been gradually formed.Centering on the construction stage of hydraulic engineering,this study uses the new generation of information technologies such as BIM,big data,3S,and three-dimensional (3D) visualization to build an advanced,practical,and safe construction supervision platform for hydraulic engineering that can integrate the basic and overall construction process information resources.It is expected that the platform can greatly reduce the risks and solve the problems such as insufficient cooperation among institutions,difficult information collection,poor data sharing and consistency,and low construction management efficiency. …”
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Access control scheme for medical data based on PBAC and IBE by Yi-ting ZHANG, Yu-chuan FU, Ming YANG, Jun-zhou LUO

“…Due to the large amount of personal privacy information contained,the medical big data formed in the health care industry was faced with potential threats of both external attacks and internal data leakages.However,traditional access control technology didn’t take into account the important role of user access purpose in the access control schemes that emphasized data privacy,and existing symmetric and asymmetric encryption technologies both face problems such as the complexity of key and certificate management.To address these problems,a novel access control scheme based on PBAC model and IBE encryption technology was proposed,which could provide flexible access control of encrypted medical data.By introducing the concept of conditioned purpose,the PBAC model was extended to achieve full coverage of purpose trees.Furthermore,the scheme used patient ID,conditioned bit and intended purpose as the IBE public key,with which patients’ data were encrypted.Only users who pass the authentication and whose access purposes conform to the intended purposes can obtain the corresponding private keys and the encrypted data,thereby achieving access to patients’ information.Experimental results prove that the scheme can achieve the goals of fine-grained access control and privacy protection with high performance.…”
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PERFORMANCE DEGRADATION ASSESSMENT OF ROLLING BEARING BASED ON SINGLE RING THEOREM IN RANDOM MATRIX THEORY by SHAN Qiang, NI GuangXian, WANG Heng

“…A rolling bearing performance degradation assessment algorithm based on single ring theorem in the random matrix theory is proposed to solve the problem that the traditional feature extraction algorithm is not sufficient to extract the useful information of the bearing under the industrial big data environment, and the constructed index is difficult to effectively characterize the bearing degradation process. …”
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An inside look into the complexity of box-office revenue prediction in China by Jia Xiao, Xin Li, Shanzhi Chen, Xuhui Zhao, Meng Xu

“…Indexes from seven mainstream video websites are retrieved by the designed big data system which is integrated with the Internet of things technology. …”
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Design and Implementation of One Map Platform for Water Conservancy Spatial Planning by YANG Chuhua, XU Bing, CHEN Yubing, ZHANG Bo, JIANG Maoxi

“…,are better solved.This study utilizes Big data,3S,VR and other new generation information technology to construct a map platform for water conservancy spatial planning,develop function modules such as large data portal in time and space,auxiliary audit of planning results,management of planning results,display of planning aggregation,statistics and post-evaluation,and realize auxiliary audit,evaluation and visual expression of water conservancy planning data on one map.To realize the integrated management of water planning from the planning,implementation,post evaluation,life cycle,to provide the key technical means for the water conservancy spatial planning business objectives of “working basis from the diagram,working process to map synergy,work results to map”,and ultimately improve the level of refinement and intelligence of water conservancy planning and management.…”
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Improving the Machine Learning Stock Trading System: An N-Period Volatility Labeling and Instance Selection Technique by Young Hun Song, Myeongseok Park, Jaeyun Kim

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Parallel division clustering algorithm based on Spark framework and ASPSO by Yimin MAO, Dejin GAN, Liefa LIAO, Zhigang CHEN

“…To deal with the problems that the partition clustering algorithm for processing massive data encountered problems such as large data dispersion coefficient and poor anti-interference, difficulty to determine the number of local clusters, local cluster centroids randomness, and low efficiency of local cluster parallelization and merging, a parallel partition clustering algorithm based on Spark framework and ASPSO (PDC-SFAS PSO) was proposed.Firstly, a meshing strategy was introduced to reduce the data dispersion coefficient of the data division and improve anti-interference.Secondly, to determine the number of clusters, meshing strategy based on potential function and Gaussian function were proposed, which formed an area with different sample points as the core clusters, and obtained the number of local clusters.Then, to avoid local cluster centroids randomness, ASPSO was proposed.Finally, a local cluster merging strategy based on cluster radius and neighbor nodes was introduced to merge clusters with large similarity based on the Spark parallel computing framework, which improved the efficiency of parallel merging of local clusters.Experimental results showed that the PDC-SFASPSO algorithm has good performance in data partitioning and clustering in a big data environment, and it was suitable for parallel clustering of large-scale data sets.…”
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Forest Ecological Diversity Change Prediction Discrete Dynamic Model by Jingxia Li, Aijun Zhou, Yongfeng Liao, Zixin Zhao, Xiaoli Mao, Shuoxin Zhang

“…In recent years, the mining and application of big data have become the frontier content of international ecological diversity and macroecology research. …”
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Trends in data literacy, 2018-2023: a review of the literature by Leanne Bowler, Charlie Shaw

“…The focus of data literacy tends to be on digital data, interactions with big data systems, and the datafication of life. Critical data literacy approaches were identified in one third of the sample papers - a small but emerging stance to data literacy education. …”
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WBS-Based Method in Teaching Management Information Project by Yuling Su

“…In addition, the enrichment and sharing of educational materials, the informatization, and big data of educational management also contribute to the improvement of time efficiency and optimization of time structure in higher education. …”
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Utilizing Google Trends Data to Examine the Impact of Unemployment Rates on Indonesia's Gross Domestic Product by Giani Jovita Jane, Rafif Hasabi, Sinatrya Dwi Purnatadya, Fitri Kartiasih

“…So, frequency conversion is required to conduct simple regression modelling using these data. On the other hand, big data such as Google Trends is an additional predictor to estimate OUR and GDP data to overcome delays in publication time. …”
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Intelligent shipping: integrating autonomous maneuvering and maritime knowledge in the Singapore-Rotterdam Corridor by Liang Zhao, Mengqiao Xu, Lei Liu, Yong Bai, Mingyang Zhang, Ran Yan

“…Based on historical maritime big data, the framework offers customized routes for companies with specific routing preferences. …”
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Application of Rotating Machinery Fault Diagnosis Based on Deep Learning by Wei Cui, Guoying Meng, Aiming Wang, Xinge Zhang, Jun Ding

“…Deep learning is a useful tool for analyzing and processing big data, which has been widely used in various fields. …”
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The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends by Rachid ZIKY, Hicham BAHIDA, Ahmed ABRIANE

“…Bibliometric analysis identified the most influential authors and institutions, highlighting predominant keywords such as "big data," "automation," and "predictive analytics." …”
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Analysis of Logistics 4.0 Service Provider Alternatives with CRITIC-Based WASPAS Method by Muhammet Enes Akpınar

“…Logistics 4.0 seeks to optimize logistics processes using innovative technologies such as smart systems and big data analytics. In this context, selecting the right service provider is of strategic importance for businesses. …”
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