Energy Efficient Handover Management in Cluster Based Wireless Sensor Network

Wireless sensors are compact-size, low power, inexpensive devices which are capable to measure local environmental conditions or other parameters such as temperature, acceleration, and forward such information to a sink for proper processing. Wireless sensor networks (WSNs) have been under development by both academic and industrial societies for a while. By moving toward applications such as the area of medical care and disaster response mobility in wireless sensor networks has attracted a lot of attentions. In energy constraint sensor network, mobility handling introduces unique challenges in aspects like resource management, coverage, routing protocols, security, etc. This paper, proposes an energy-efficient mobility-aware MAC protocol to handle node handover among different clusters. The simulation-based experiments show that the proposed protocol has better performance compared to the existing S-MAC method

An overview on dynamic wireless sensor network architectures

Typically, the sensor nodes of a Wireless Sensor Network have a large coverage area and longer range. They are also self-configuring or self-organizing. Clustering is used to leverage the underlying flat sensor network topology and provide a hierarchical organization. A Wireless Sensor Network can be called as dynamic if it is supported by two atomic operations: node-move-in and node-move-out, which means nodes getting out of and nodes joining into an existing network, respectively. In this paper, we study and examine Dynamic Wireless Sensor Network Architectures. Based on the review results we then conclude the best architectures that can support communication protocols such as broadcasting/flooding, multicasting, routing, and gathering

ELECTROENCEPHALOGRAPHY (EEG) APPLICATION ON QUANTIFYING EMOTIONAL INTELLIGENCE DURING MEDITATION

Humans have two distinctive quotients that need to be considered such as Emotional Quotient (EQ) and Intelligence Quotient (IQ). Emotional quotient is also known as Emotional Intelligence (EI) which can be defined as the ability of a person on how they understand themselves and handle their emotion, as well as understanding society around them. Quantifying EI is an issue that has attracted various field of work. This manuscript aims to investigate the relation of EI in meditation using the human electroencephalogram (EEG) device. Low-cost 16 electrodes Emotiv Epoch neuroheadset was used in this study. A stimulus on a Quran recitation audio-visual was setup as the meditation intervention. The EEG signal obtained from this experiment showed that the Power Spectral Densities (PSD) of alpha brainwaves on the right frontal lobe were gradually reduced when the subjects are watching and listening to the Quran recitation’s video. Hence, the negative feelings were reduced which indicated that the participants are emotionally stable. This finding may suggest that humans are prone to relax when the Quran is being recited repeatedly. This finding further confirms that Quran recitation correlate with the self-awareness and self-regulate attributes of EI. Additionally, differences in response were observed from the male and female subjects