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Due to the peculiarity of wireless sensor networks (WSNs), where a group of sensors continuously transmit data to other sensors or to the fusion center, it is crucial to compress the transmitted data in order to save the consumed power, which is paramount in the case of portable devices. There exists several techniques for data compression such as discrete wavelet transform (DWT) based, which fails...
Agriculture is one of the most significant domains in need of knowledge sharing and Decision Support Systems (DSS) that can help farmers make decisions to solve complex problems. Monoculture agriculture has many problems such as plant disease dramatically decreasing product price. Intercropping is an alternative way to reduce a risk of market price and plant disease. This research proposes three research...
Wireless body sensor networks (WBSN) provide an appreciable aid to patients who require continuous care and monitoring. One key application of WBSN is mobile health (mHealth) for continuous patient monitoring, acquiring vital signs e.g. EEG, ECG, etc. Such monitoring devices are doomed to be portable, i.e., batter powered, and agile to allow for patient mobility, while providing sustainable, energy-efficient...
Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems. Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes. In this paper, we conduct a performance evaluation based on the noiseless...
Brain is the most important part in the human body controlling muscles and nerves; Electroencephalogram (EEG) signals record brain electric activities. EEG signals capture important information pertinent to different physiological brain states. In this paper, we propose an efficient framework for evaluating the power-accuracy trade-off for EEG-based compressive sensing and classification techniques...
The paper aims to develop a model that can explain the critical determinants that influencing the behavioral intention (BI) of mobile commerce (m-commerce) in collectivist cultures such as the Arab culture; particularly Jordan. The proposed model employs the technology acceptance model (TAM). TAM has been augmented with subjective norms (SN) from the Theory of Reasoned Action (TRA). The augmented...
This paper discusses on developing a hybrid model to tackle the problem of changing environment in the job shop scheduling problem. The main idea is to develop building blocks of partial schedules using the model developed that can be used to provide backup solutions when disturbances occur during production. This model hybridizes genetic algorithm (GA) with artificial immune systems (AIS) techniques...
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