Selected Topics in Management and Modeling of Complex Systems: Editorial Introduction to Issue 16 of CSIMQ by Peter Forbrig

“…The range of topics ends with the discussion of specific algorithms that allow entity clustering for Big Data analysis. The goal of these algorithms is the identification of different notations of references that refer to the same real-world object. …”
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Simple-Random-Sampling-Based Multiclass Text Classification Algorithm by Wuying Liu, Lin Wang, Mianzhu Yi

“…The space-time overhead of the algorithms must be concerned about the era of big data. Through the investigation of the token frequency distribution in a Chinese web document collection, this paper reexamines the power law and proposes a simple-random-sampling-based MTC (SRSMTC) algorithm. …”
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Prediction of the waterborne navigation density based on the multi-feature spatio-temporal graph convolution network by Wei DONG, Leilei ZHANG, Ziheng JIN, Wei SUN, Junbo GAO

“…In the face of the development of the information technology in the port and waterway,the Internet of things (IoT) technology can help to build China’s water transport perception network.The big data analysis of the waterborne transport has become a hot topic for researchers and practitioners in the field of transportation.The navigation density of each port in the water transportation is nonlinear and spatio-temporal correlation,so it is a great challenge to accurately predict it.A multi-feature spatiotemporal graph convolution network (MFSTGCN) was proposed to solve the problem of the traffic density prediction.MFSTGCN effectively captured the spatial-temporal correlation of the ship navigation density data by using the spatial convolution and temporal convolution through three features,which were navigation volume,average ship speed and ship density.The experiment was carried out on the automatic identification system (AIS) data set collected from a shipping platform.The results show that the prediction effect of the MFSTGCN model is better than the spatio-temporal graph convolution network (STGCN) model.…”
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Interoperable Internet of Medical Things platform for e-Health applications by Jesús Noel Sárez Rubí, Paulo Roberto de Lira Gondim

“…Moreover, the heterogeneity in the large volume of health data generated by Internet of Medical Things platforms must be attenuated for the proper application of big data processing techniques. This article proposes the joint use of openEHR and Semantic Sensor Network semantics for the achievement of interoperability at the semantic level and use of a machine-to-machine architecture for the definition of an interoperable Internet of Medical Things platform.…”
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Multistep Hybrid Iterations for Systems of Generalized Equilibria with Constraints of Several Problems by Lu-Chuan Ceng, Cheng-Wen Liao, Chin-Tzong Pang, Ching-Feng Wen

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Predicting the Elastic Modulus of Nanoparticle-Reinforced Polymer Matrix Composites Based on Digital Image Processing and Finite Elements by Zhenghong Jiang, Chunrong Zhou

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Provably secure rational delegation computation protocol by Youliang TIAN, Qiuxian LI, Duo ZHANG, Linjie WANG

“…A provably secure rational delegation computation scheme was proposed to solve the requirement of security issues in rational delegate computation.Firstly,game theory was introduced into delegation computation and according to rational participants behavior preferences analysis,a rational delegate computing game model was designed.Secondly,according to the equilibrium demand of game model and the security requirement of rational delegation computation,a rational security model was established.Thirdly,combining Yao's garbled circuit with its advantages of re-randomization,as well as full homomorphic encryption technology,the rational delegation computation protocol was constructed.And the combination of strategies in the protocol could reach the Nash equilibrium state.Finally,the security of the protocol and the privacy of the input and output were proved according to the rational security model,and the performance analysis shows the validity of the protocol.The proposed rational delegation computing protocol not only satisfies the traditional security,but also considers the behavioral preference of participants,which is more in line with the delegationcomputing mode under the big data environment.…”
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EC-Structure: Establishing Consumption Structure through Mining E-Commerce Data to Discover Consumption Upgrade by Lin Guo, Dongliang Zhang

“…With the development of Internet economy, many scientific researchers focus on mining knowledge of consumer behavior using big data analysis technology. Because consumption decisions are influenced by not only personal characteristics but also social trends and environment, it is one-sided to analyze the impact of one single factor on the phenomenon of consumption. …”
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Cost-Sensitive Support Vector Machine Using Randomized Dual Coordinate Descent Method for Big Class-Imbalanced Data Classification by Mingzhu Tang, Chunhua Yang, Kang Zhang, Qiyue Xie

“…Aiming at class-imbalanced problem on big data, a cost-sensitive support vector machine using randomized dual coordinate descent method (CSVM-RDCD) is proposed in this paper. …”
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Risks in Work-Integrated Learning: A Data-Driven Analysis by Xiao Xu

“…By analysing variables related to work placements, student loans, financial assistance, and the alignment of WIL experiences with students’ post-graduation employment, this research provides critical insights into the effectiveness of WIL programs from a large-scale, survey-based, big data perspective. The findings highlight key areas for improvement to mitigate these risks and enhance the overall value of WIL for students across various disciplines.…”
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A BP Neural Network-Based GIS-Data-Driven Automated Valuation Framework for Benchmark Land Price by Lei Wu, Yu Zhang, Yongchang Wei, Fangyu Chen

“…The automated valuation of benchmark land price plays an essential role in regulating land demand in Chinese real-estate market as the big data are currently accumulated rapidly. However, this problem becomes highly challenging due to the multidimension, large volume, and nonlinearity of the land price-influencing factors. …”
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Model of cyberspace threat early warning based on cross-domain and collaboration by Gang XIONG, Yuwei GE, Yanjie CHU, Weiquan CAO

“…The development of network threat shows the characteristics of initiative,concealment and ubiquity.It poses a severe challenge to the passive,local and isolated traditional network defense mode.In view of the new trend of integration of big data，artificial intelligence and network security,a cross-domain collaborative network threat early warning model was proposed,which could enable and increase efficiency for cyberspace security.Firstly,starting from the overall structure of the protected network space,the model constructs a cross-domain function framework with the vertical and horizontal conjunction by dividing the security threat domain,decomposing the system function,designing the information sharing mechanism.Secondly,to enhance the ability of threat information detection,the collaborative technology architecture is designed by the logic of hierarchical management,and the key technologies involved in threat information perception,processing and application,are systematically introduced.Finally,with the help of application scenarios,qualitatively the capability increment of the proposed threat early warning model was described.…”
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A computing allocation strategy for Internet of things’ resources based on edge computing by Zengrong Zhang

“…In order to meet the demand for efficient computing services in big data scenarios, a cloud edge collaborative computing allocation strategy based on deep reinforcement learning by combining the powerful computing capabilities of cloud is proposed. …”
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Enhancing 5G Networks with Edge Computing: An Overview Study by Chaouki Halima, Iqdour Radouane, Boulouird Mohamed

“…MEC is a new computing model proposed within the framework of the rapid development of IoT, AI, and big data, aiming to bring cloud capabilities closer to the network edge. …”
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Research Progress of Causal Inference in Bias Elimination by Chen Limanxi

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Algorithm Domination As A New Surveillance System by Ahmet Ayhan Koyuncu, Muhittin Evren

“…It profiles people thanks to the information obtained with big data. In this way, people can be easily manipulated and directed by algorithms. …”
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Smart universities: Adaption challenges for Historically black universities in South Africa: A concept overview. by Dr. Victor H Mlambo, Dr. Hlanganani Mnguni

“… Universities today are experimenting with AI and big data to improve how students live and learn on campus; however, from a South African perspective, the question is: can historically black universities adapt to this ever-changing higher education environment? …”
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Artificial Intelligence in Automotives: ANNs’ Impact on Biodiesel Engine Performance and Emissions by Ramozon Khujamberdiev, Haeng Muk Cho

“…The integration of ANNs with big data and sophisticated algorithms paves the way for more accurate and reliable engine modeling, essential for advancing sustainable and eco-friendly automotive technologies. …”
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Efficient privacy-preserving decision tree classification protocol by Lichuan MA, Jiayi PENG, Qingqi PEI, Haojin ZHU

“…To provide privacy-preserving decision tree classification services in the Internet of things (IoT) big data scenario, an efficient privacy-preserving decision tree classification protocol was proposed by adopting the secure multiparty computation framework into the classification model.The entire protocol consisted of three parts: the original decision tree model mixing, the Boolean share-based privacy-preserving comparing, and the 1-out-of-n oblivious transfer-based classification result obtaining.Via the proposed protocol, the service providers could protect the parameters of their decision tree models and the users were able to derive the classification result without exposing their privately hold data.Through a concrete security analysis, the proposed protocol was proved to be secure against semi-honest adversaries.By implementing the proposed protocol on various practical decision tree models from open datasets, the classification accuracy and the average time cost for completing one privacy-preserving classification service were evaluated.After compared with existing related works, the performance superiority of the proposed protocol is demonstrated.…”
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Approximation Theorem for New Modification of q-Bernstein Operators on (0,1) by Yun-Shun Wu, Wen-Tao Cheng, Feng-Lin Chen, Yong-Hui Zhou

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