Janyl Jumadinova¹, Oliver Bonham-Carter¹, Hanzhong Zheng^1,2,*, Michael Camara¹, Dejie Shi³

Journal on Big Data, Vol.2, No.4, pp. 145-155, 2020, DOI:10.32604/jbd.2020.010090

Abstract Text mining has emerged as an effective method of handling and extracting useful information from the exponentially growing biomedical literature and biomedical databases. We developed a novel biomedical text mining model implemented by a multi-agent system and distributed computing mechanism. Our distributed system, TextMed, comprises of several software agents, where each agent uses a reinforcement learning method to update the sentiment of relevant text from a particular set of research articles related to specific keywords. TextMed can also operate on different physical machines to expedite its knowledge extraction by utilizing a clustering technique. We collected the biomedical textual data from… More >

Chengrong Yang¹, Rongjing Bu², Yan Kang², Yachuan Zhang², Hao Li^2,*, Tao Li², Junfeng Li²

Journal on Big Data, Vol.2, No.4, pp. 135-144, 2020, DOI:10.32604/jbd.2020.010000

Abstract With the rise of open-source software, the social development paradigm occupies an indispensable position in the current software development process. This paper puts forward a variant of the PageRank algorithm to build the importance assessment model, which provides quantifiable importance assessment metrics for new Java projects based on Java open-source projects or components. The critical point of the model is to use crawlers to obtain relevant information about Java open-source projects in the GitHub open-source community to build a domain knowledge graph. According to the three dimensions of the Java opensource project’s project influence, project activity and project popularity, the… More >

Yanan Zhang^1,*, Lin Ouyang², Qinqin Li², Haichen Ju²

Journal on Big Data, Vol.2, No.3, pp. 125-133, 2020, DOI:10.32604/jbd.2020.012879

Abstract Under the traditional dynamic model, the conventional method for solving the rotation angle of a rigid body is to use the fixed-axis rotation law of the rigid body, but the known rotation shaft position must be used as a prerequisite. In practical work, for the rotation of a rigid body under multiple forces, solving the shaft is often a difficult problem. In this paper, we consider the rigid body of the disc is subjected to the force of uneven magnitude from multiple angles, the position of the rotating shaft is obtained by iterative inversion through the rigid body rotation law… More >

Zuwei Tian^*, Shubo Tian, Tuo Wang, Zhen Gong, Zhenqin Jiang

Journal on Big Data, Vol.2, No.3, pp. 117-123, 2020, DOI:10.32604/jbd.2020.011420

Abstract In order to provide a good practice platform for the program design contestants and algorithm enthusiasts, this paper designs and implements a programming online evaluation system based on cloud platform, which is a web system that can return the test results of the program source codes submitted by users in real time. It realizes the automatic evaluation of the program design training questions. The system is implemented by the way of front-end and backend separation and modular programming. The front-end of the web is implemented by Vue framework, the back-end is implemented by Django framework. The judgment core is written… More >

Tengfei Yang^1,2, Xiaojun Shi³, Yangyang Li^1,*, Binbin Huang⁴, Haiyong Xie^1,5, Yanting Shen⁴

Journal on Big Data, Vol.2, No.3, pp. 105-115, 2020, DOI:10.32604/jbd.2020.010958

Abstract Mobile Edge Computing (MEC) has become the most possible network architecture to realize the vision of interconnection of all things. By offloading compute-intensive or latency-sensitive applications to nearby small cell base stations (sBSs), the execution latency and device power consumption can be reduced on resource-constrained mobile devices. However, computation delay of Mobile Edge Network (MEN) tasks are neglected while the unloading decision-making is studied in depth. In this paper, we propose a workload allocation scheme which combines the task allocation optimization of mobile edge network with the actual user behavior activities to predict the task allocation of single user. We… More >

Chao Zhu¹, Yike Wang¹, Dongbing Pu¹,Miao Qi^1,*, Hui Sun^2,*, Lei Tan^3,*

Journal on Big Data, Vol.2, No.3, pp. 95-104, 2020, DOI:10.32604/jbd.2020.010431

Abstract Nowadays, action recognition is widely applied in many fields. However, action is hard to define by single modality information. The difference between image recognition and action recognition is that action recognition needs more modality information to depict one action, such as the appearance, the motion and the dynamic information. Due to the state of action evolves with the change of time, motion information must be considered when representing an action. Most of current methods define an action by spatial information and motion information. There are two key elements of current action recognition methods: spatial information achieved by sampling sparsely on… More >

Xuguang Liu¹, Ruqing Zhao², Qifei Chen², Ming Shi³, Ziling Xing², Yanan Zhang^4,*

Journal on Big Data, Vol.2, No.2, pp. 85-93, 2020, DOI:10.32604/jbd.2020.013845

Abstract The shooting state during shooting refers to the basketball’s shooting speed, shooting angle and the ball’s rotation speed. The basketball flight path is also related to these factors. In this paper, based on the three forces of Gravity, Air Resistance and Magnus Force, the “Three Forces” model is established, the Kinetic equations are derived, the basketball flight trajectory is solved by simulation, and the best shot state when shooting is obtained through the shooting percentage. Compared with the “Single Force” model that only considers Gravity, the shooting percentage of the “Three Forces” model is higher. The reason is that the… More >

Kai Chen^1,*, Haoqi Zhu², Leiming Yan¹, Jinwei Wang¹

Journal on Big Data, Vol.2, No.2, pp. 71-84, 2020, DOI:10.32604/jbd.2020.012294

Abstract Adversarial examples are hot topics in the field of security in deep learning. The feature, generation methods, attack and defense methods of the adversarial examples are focuses of the current research on adversarial examples. This article explains the key technologies and theories of adversarial examples from the concept of adversarial examples, the occurrences of the adversarial examples, the attacking methods of adversarial examples. This article lists the possible reasons for the adversarial examples. This article also analyzes several typical generation methods of adversarial examples in detail: Limited-memory BFGS (L-BFGS), Fast Gradient Sign Method (FGSM), Basic Iterative Method (BIM), Iterative Least-likely… More >

Huiyu Long¹, Yan Ma¹, Xiang Mao¹, Xinyuerong Sun^2,*

Journal on Big Data, Vol.2, No.2, pp. 63-70, 2020, DOI:10.32604/jbd.2020.011214

Abstract Under the background of big data, Informatization plays an important role in the development of the engineering cost industry. The rapid development of the industry and the increasing complexity of construction projects require higher standards of informatization. The current information processing methods and models have been difficultly to meet new requirements. Based on this, this study deeply analyzes the key factors that impede the informatization of engineering cost development, and tries to find corresponding solutions through theoretical analysis and empirical research to break these constraints. This will play a guiding role in the development of informatization in China's engineering cost… More >

Lulu Cui^2,3,*, Yabin Xu^1,2,3

Journal on Big Data, Vol.2, No.2, pp. 53-62, 2020, DOI:10.32604/jbd.2020.010590

Abstract In order to effectively solve the problem of copyright protection of materials genome engineering data, this paper proposes a method for copyright protection of materials genome engineering data based on zero-watermarking technology. First, the important attribute values are selected from the materials genome engineering database; then, use the method of remainder to group the selected attribute values and extract eigenvalues; then, the eigenvalues sequence is obtained by the majority election method; finally, XOR the sequence with the actual copyright information to obtain the watermarking information and store it in the third-party authentication center. When a copyright dispute requires copyright authentication… More >