Titlebook: Innovative Mobile and Internet Services in Ubiquitous Computing; Proceedings of the 1 Leonard Barolli,Fatos Xhafa,Omar K. Hussain Conferenc

Cumbersome

A Balanced Energy Efficient (BEE) Routing Scheme for Underwater WSNs gas, pollution, and tsunami, ocean surveillance for defense strategies, seismic monitoring, equipment monitoring etc. The sensor node consumes more energy and load distribution suffer from imbalance at long distance. In this paper, we present a Balanced Energy Efficient (BEE) algorithm to diminish

征兵

CANT

Effects of Sharing Information for Available Routes by Ad-Hoc Communication on a Disaster Stricken A the distressed areas. So, it is hard to escape in safely by route selected based on only the known information before disaster. For the safe route selection for the evacuation on a disaster, evacuees need the realtime information for the available routes information at the disaster distressed areas

Optometrist

Design and Implementation of a Weather Measurement System Using Agile-Kanbanrk. Thus, the networks could be congested and the performance will degrade. For this reason, it is important to decrease the number of transmitted packets. Agile is a technique to develop the software and manage the work efficiency. Kanban is a method to support Agile development. In this work, we d

得意牛

是剥皮

协定

我不死扛

Impact of Mobile Network Operators’ Incentive for Public Health: A Study Based on Saudi 2030 Visionhe Saudi Health Ministry’s (SHM) latest reports with up to 60% of the total population classified as obese. This study is consistent with the vision of the SHM 2030 and its 2020 transformational program, which includes the creation of a health system that contributes to the promotion of both individ

傲慢人

Cyber Security Situation Prediction Model Based on GWO-SVMo predict the development trend of cyber safety more accurately, this paper establishes a kind of network safety situation forecast model based on Grey Wolf Optimization (GWO) algorithm to optimize support vector machine (SVM) parameters, and solves the problem of support vector machine (SVM) parame

连系

Half Hourly Electricity Load Forecasting Using Convolutional Neural Networkactor which plays major role in operations of Smart Grid (SM). For solving this problem, we propose a model which is based on preprocessing, selection and classification of historical data. Features are selected by Combine Feature Selection (CFS) using Decision Tree (DT) and Mutual Information (MI)