Many applications of wireless sensor network such as smart metering, environment monitoring and health care [1] use a large number of sensor nodes, which generate a huge amount of traffic with the specification of the different QoS requirements. Broadband transmission can be achieved through the mobile systems. Long Term Evolution (LTE) is the main efficient broadband technology in current mobile communications. IntroducingWireless sensor networks into the Long Term Evolution (LTE) networks, can be achieved successfully but with some challenges, such as the traffic overload due to a large number of sensor nodes. Traffic scheduling plays an important role in LTE technology; this can be achieved by assigning the shared resources among users in an efficient and optimized manner. This paper discusses the effect of many types of scheduling algorithms on the downlink performance, this can be done in terms of throughput, block error rate (BLER) and fairness measurements using a MATLAB-based system level Simulator is provide which from Vienna University under License Agreement for "Academic Usage" [8]. An effective radio scheduler to optimize the distribution of radio resources among the sensor nodes is also studied. The guaranteed QoS user demands can be considered as a great challenge in the current field of research.

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This paper proposes a Random early detection algorithm based on fuzzy logic Principles. The main target of using the fuzzy logic is to reduce the number of lost packets which are sent by a sender using RED algorithm in queue-buffer router of the network topology. The function of fuzzy logic is to dynamically tune the maximum drop probability (max p ) parameter of the RED algorithm. To realize this target, a twoinput-single-output fuzzy logic is implemented. The inputs of the fuzzy logic are average queue size, the difference in average queue size. To estimate the performance of the FLRED: simple network topology with FTP is suggested. In this research, the opnet modeler 14.5 has been used. The simulation results show that the FLRED algorithm is better than traditional RED algorithm as far as the number of lost packets is concerned. KeywordsActive queue management (AQM), Congestion Control , Fuzzy logic Random early detection (FLRED) , Random early detection algorithm (RED).

Thisstudy describes the person thinking that how brain communicates through handwriting styles, thinking behavior using brainwaves and brain activity models. Everything put on paper is a response of two way circuit between brain and motor reflex muscles of hand. Brain can work on different layers and multiple voxel. Different layers communication are interconnected with each other, Coding of brain with different brain parts activates using our emotions stress moods and ability to séance. In this paper BASH Analyzer technique take different samples and describe how brain communicate through handwriting and define the personality predictions according to brain functions. It evaluates behavior of different writing samplesby differentiating good or bad writer characteristic by evaluating five intelligence factors: chosen appropriate words, common words, Preposition analyzer, Case sensitive, Vowels analyzer are considered. These features are calculated by classification of Support Vector Machine through Artificial Neural Network and BrainIntelligence Technique. General TermsBrain Intelligence and Machine Learning.

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