Kexin Zhang¹, Bin Lin^2,*, Jixin Chen¹, Xinlong Wu¹, Chao Lu³, Desheng Zheng¹, Lulu Tian⁴

Computer Systems Science and Engineering, Vol.42, No.1, pp. 351-360, 2022, DOI:10.32604/csse.2022.021132

Abstract Deep learning techniques have outstanding performance in feature extraction and model fitting. In the field of aero-engine fault diagnosis, the introduction of deep learning technology is of great significance. The aero-engine is the heart of the aircraft, and its stable operation is the primary guarantee of the aircraft. In order to ensure the normal operation of the aircraft, it is necessary to study and diagnose the faults of the aero-engine. Among the many engine failures, the one that occurs more frequently and is more hazardous is the wheeze, which often poses a great threat to flight safety. On the basis… More >

Gowdham Chinnaraju^*, S. Nithyanandam

Computer Systems Science and Engineering, Vol.42, No.1, pp. 373-386, 2022, DOI:10.32604/csse.2022.020993

Abstract Wireless Sensor Networks (WSNs) gained wide attention in the past decade, thanks to its attractive features like flexibility, monitoring capability, and scalability. It overcomes the crucial problems experienced in network management and facilitates the development of diverse network architectures. The existence of dynamic and adaptive routing features facilitate the quick formation of such networks. But flexible architecture also makes it highly vulnerable to different sorts of attacks, for instance, Denial of Service (DoS). Grey Hole Attack (GHA) is the most crucial attack types since it creates a heavy impact upon the components of WSN and eventually degrades the performance of… More >

V. R. Balaji^1,*, T. Kalavathi², J. Vellingiri³, N. Rajkumar⁴, Venkat Prasad Padhy⁵

Computer Systems Science and Engineering, Vol.42, No.1, pp. 289-301, 2022, DOI:10.32604/csse.2022.020971

Abstract Data offloading at the network with less time and reduced energy consumption are highly important for every technology. Smart applications process the data very quickly with less power consumption. As technology grows towards 5G communication architecture, identifying a solution for QoS in 5G through energy-efficient computing is important. In this proposed model, we perform data offloading at 5G using the fuzzification concept. Mobile IoT devices create tasks in the network and are offloaded in the cloud or mobile edge nodes based on energy consumption. Two base stations, small (SB) and macro (MB) stations, are initialized and the first tasks randomly… More >

R. Malavika^1,*, M. L. Valarmathi²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 229-243, 2022, DOI:10.32604/csse.2022.020947

Abstract Web service applications are increasing tremendously in support of high-level businesses. There must be a need of better server load balancing mechanism for improving the performance of web services in business. Though many load balancing methods exist, there is still a need for sophisticated load balancing mechanism for not letting the clients to get frustrated. In this work, the server with minimum response time and the server having less traffic volume were selected for the aimed server to process the forthcoming requests. The Servers are probed with adaptive control of time with two thresholds L and U to indicate the… More >

E. Gothai^1,*, A. Baseera², P. Prabu³, K. Venkatachalam⁴, K. Saravanan⁵, S. SathishKumar⁶

Computer Systems Science and Engineering, Vol.42, No.1, pp. 149-163, 2022, DOI:10.32604/csse.2022.020619

Abstract The brain of humans and other organisms is affected in various ways through the electromagnetic field (EMF) radiations generated by mobile phones and cell phone towers. Morphological variations in the brain are caused by the neurological changes due to the revelation of EMF. Cellular level analysis is used to measure and detect the effect of mobile radiations, but its utilization seems very expensive, and it is a tedious process, where its analysis requires the preparation of cell suspension. In this regard, this research article proposes optimal broadcasting learning to detect changes in brain morphology due to the revelation of EMF.… More >

R. Punithavathi^1,*, M. Kowsigan², R. Shanthakumari³, Miodrag Zivkovic⁴, Nebojsa Bacanin⁴, Marko Sarac⁴

Computer Systems Science and Engineering, Vol.42, No.1, pp. 105-120, 2022, DOI:10.32604/csse.2022.020486

Abstract At present, health care applications, government services, and banking applications use big data with cloud storage to process and implement data. Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data. Sometimes, data may have highly sensitive information, leading users to consider using big data and cloud processing regardless of whether they are secured are not. Threats to sensitive data in cloud systems produce high risks, and existing security methods do not provide enough security to sensitive user data in cloud and big data environments. At present, several security solutions support cloud systems. Some of… More >

M. P. Viswanathan^*, B. Anand

Computer Systems Science and Engineering, Vol.42, No.1, pp. 165-181, 2022, DOI:10.32604/csse.2022.020400

Abstract In this research work, single-stage fifteen levels cascaded DC-interface converter (CDDCLC) is proposed for sun arranged photovoltaic technology (PV) applications. The proposed geography is joined with help DC chopper and H-associate inverter to upgrade the power converter to accomplish the diminished harmonic profile. In assessment with the customary inverter structures, the proposed system is used with diminished voltage stress, decreased switch count and DC source tally. The proposed research work with cascaded DC link converter design requires three DC sources for combining fifteen-level AC output. This investigation structure switching technique is phase opposition and disposition pulse width modulation technique (POPD)… More >

G. Anitha^1,*, S. Baghavathi Priya²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 87-103, 2022, DOI:10.32604/csse.2022.020361

Abstract Human fall detection plays a vital part in the design of sensor based alarming system, aid physical therapists not only to lessen after fall effect and also to save human life. Accurate and timely identification can offer quick medical services to the injured people and prevent from serious consequences. Several vision-based approaches have been developed by the placement of cameras in diverse everyday environments. At present times, deep learning (DL) models particularly convolutional neural networks (CNNs) have gained much importance in the fall detection tasks. With this motivation, this paper presents a new vision based elderly fall event detection using… More >

Narongkorn Uthathip^1,*, Pornrapeepat Bhasaputra¹, Woraratana Pattaraprakorn²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 69-86, 2022, DOI:10.32604/csse.2022.020120

Abstract Generally, road transport is a major energy-consuming sector. Fuel consumption of each vehicle is an important factor that affects the overall energy consumption, driving behavior and vehicle characteristic are the main factors affecting the change of vehicle fuel consumption. It is difficult to analyze the influence of fuel consumption with multiple and complex factors. The Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was employed to develop a vehicle fuel consumption model based on multivariate input. The ANFIS network was constructed by various experiments based on the ANFIS Parameter setting. The performance of the ANFIS network was validated using Root Mean Square… More >

Liang Jin^1,*, Qinghui Meng¹, Shuang Liang²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 387-395, 2022, DOI:10.32604/csse.2022.017745

Abstract The energy consumption of train operation occupies a large proportion of the total consumption of railway transportation. In order to improve the operating energy utilization rate of trains, a multi-objective particle swarm optimization (MPSO) algorithm with energy consumption, punctuality and parking accuracy as the objective and safety as the constraint is built. To accelerate its the convergence process, the train operation progression is divided into several modes according to the train speed-distance curve. A human-computer interactive particle swarm optimization algorithm is proposed, which presents the optimized results after a certain number of iterations to the decision maker, and the satisfactory… More >