David Corral-Plaza¹, Juan Boubeta-Puig¹, Guadalupe Ortiz¹, Alfonso Garcia-de-Prado^2,*

Computer Systems Science and Engineering, Vol.35, No.1, pp. 5-12, 2020, DOI:10.32604/csse.2020.35.005

Abstract Air pollution is currently receiving more attention by international governments and organizations. Nevertheless, current systems for air quality monitoring lack essential requirements which are key in order to be effective concerning users’ access to the information and efficient regarding real-time monitoring and notification. This paper presents an Internet of Things platform for air station remote sensing and smart monitoring that combines Big Data and Cloud Computing paradigms to process and correlate air pollutant concentrations coming from multiple remote stations, as well as to trigger automatic and personalized alerts when a health risk for their particular context is detected. This platform… More >

Fanxiu Dong^*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 617-624, 2020, DOI:10.32604/iasc.2020.013940

Abstract At present, the allocation of the medical service resources is directed at a single service resource, and there are many unreasonable problems, which causes medical cost to be high. Based on this, the application of the DRGs and the fuzzy demand in the medical service resource allocation based on the data mining algorithm is proposed. The application research of the DRGs and the data mining algorithm is simply analyzed, then the uncertain demand estimation is applied to the fuzzy demand processing based on the fuzzy demand theory and the medical service resources are configured under the established demand satisfaction rate.… More >

Chen Yu^∗, Qinmin Hong, Dezhong Yao, Hai Jin

Computer Systems Science and Engineering, Vol.33, No.2, pp. 87-94, 2018, DOI:10.32604/csse.2018.33.087

Abstract The rapid expansion of GPS-embedded devices has showed the emerging new look of location-based services, enabling such offerings as travel guide services and location-based social networks. One consequence is the accumulation of a rich supply of GPS trajectories, indicating individuals’ historical position. Based on these data, we aim to mine the hot route by using a collaborative tensor calculation method. We present an efficient trajectory data processing model for mining the hot route. In this paper, we rst model the individual’s trajectory log, extract sources and destinations, use map matching to get the corresponding road segments, and nally apply the… More >

Dumitru Baleanu^1,2, Behzad Ghanbari³, Jihad H. Asad^4,*, Amin Jajarmi⁵, Hassan Mohammadi Pirouz⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 953-968, 2020, DOI:10.32604/cmes.2020.010236

Abstract In this work, a system of three masses on the vertices of equilateral triangle is investigated. This system is known in the literature as a planar system. We first give a description to the system by constructing its classical Lagrangian. Secondly, the classical Euler-Lagrange equations (i.e., the classical equations of motion) are derived. Thirdly, we fractionalize the classical Lagrangian of the system, and as a result, we obtain the fractional Euler-Lagrange equations. As the final step, we give the numerical simulations of the fractional model, a new model which is based on Caputo fractional derivative. More >

Wenbin Bi¹, Fang Yu², Ning Cao³, Wei Huo³, Guangsheng Cao^{4, *}, Xiuli Han⁵, Lili Sun⁶, Russell Higgs⁷

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1837-1854, 2020, DOI:10.32604/cmc.2020.010420

Abstract Software defect feature selection has problems of feature space dimensionality reduction and large search space. This research proposes a defect prediction feature selection framework based on improved shuffled frog leaping algorithm (ISFLA).Using the two-level structure of the framework and the improved hybrid leapfrog algorithm's own advantages, the feature values are sorted, and some features with high correlation are selected to avoid other heuristic algorithms in the defect prediction that are easy to produce local The case where the convergence rate of the optimal or parameter optimization process is relatively slow. The framework improves generalization of predictions of unknown data samples… More >

Shihong Zou¹, Huizhong Sun^{1, *}, Guosheng Xu¹, Ruijie Quan²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1321-1334, 2020, DOI:10.32604/cmc.2020.09649

Abstract In the information era, the core business and confidential information of enterprises/organizations is stored in information systems. However, certain malicious inside network users exist hidden inside the organization; these users intentionally or unintentionally misuse the privileges of the organization to obtain sensitive information from the company. The existing approaches on insider threat detection mostly focus on monitoring, detecting, and preventing any malicious behavior generated by users within an organization’s system while ignoring the imbalanced ground-truth insider threat data impact on security. To this end, to be able to detect insider threats more effectively, a data processing tool was developed to… More >

Sudan Jha¹, Lewis Nkenyereye^{2, *}, Gyanendra Prasad Joshi³, Eunmok Yang⁴

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1059-1079, 2020, DOI:10.32604/cmc.2020.011754

Abstract The present trends in smart world reflects the extensive use of limited resources through information and communication technology. The limited resources like space, mobility, energy, etc., have been consumed rigorously towards creating optimized but smart instances. Thus, a new concept of IoT integrated smart city vision is yet to be proposed which includes a combination of systems like noise and air loss monitoring, web monitoring and fire detection systems, smart waste bin systems, etc., that have not been clearly addressed in the previous researches. This paper focuses on developing an effective system for possible monitoring of losses, traffic management, thus… More >

Taemin Lee¹, Dongwann Kang², Kyunghyun Yoon¹, Sanghyun Seo^3,*

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 181-192, 2020, DOI:10.31209/2019.100000139

Abstract As mobile devices have tremendously developed, people can now get sensor data easily. These data are not only physical data such as temperature, humidity, gravity, acceleration, etc. but also human health data such as blood pressure, heart pulse rate, etc. With this information, Internet of Things (IoT) technology has provided many systems to support human health care. Systems for human health care support physical health care like checking blood pressure, pulse rate, etc. However, the demand for physical health care as well as mental health care is increasing. So, a system, which automatically recommends a painting to users based on… More >

M. Carmel Sobia¹, A. Abudhahir²

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 869-881, 2018, DOI:10.31209/2018.100000014

Abstract In this paper, an efficient facial expression recognition system using ANFIS-MHS (Adaptive Network-based Fuzzy Inference System with Mosquito Host-Seeking) has been proposed. The features were extracted using MLDA (Modified Linear Discriminant Analysis) and then the optimized parameters are computed by using mGSO (modified Glow-worm Swarm Optimization).The proposed system recognizes the facial expressions using ANFIS-MHS. The experimental results demonstrate that the proposed technique is performed better than existing classification schemes like HAKELM (Hybridization of Adaptive Kernel based Extreme Learning Machine), Support Vector Machine (SVM) and Principal Component Analysis (PCA). The proposed approach is implemented in MATLAB. More >

Samia Allaoua Chelloug^a, Mohamed A. El-Zawawy^b,c

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 309-318, 2018, DOI:10.1080/10798587.2017.1290328

Abstract The Internet of things (IoT) applications span many potential fields. Furthermore, smart homes, smart cities, smart vehicular networks, and healthcare are very attractive and intelligent applications. In most of these applications, the system consists of smart objects that are equipped by sensors and Radio Frequency Identification (RFID) and may rely on other technological computing and paradigm solutions such as M2 M (machine to machine) computing, Wifi, Wimax, LTE, cloud computing, etc. Thus, the IoT vision foresees that we can shift from traditional sensor networks to pervasive systems, which deliver intelligent automation by running services on objects. Actually, a significant attention has… More >