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One of the most common factors of road accidents is the drowsiness of drivers. The project's key purpose is to define the strategies for detecting and alerting driver somnolence, thus growing transportation safety. Via uses several physiological variables, such as pulse rate, EEG, ECG, eyelid closure, skin conductance. This scenario indicates that the driver is not in reasonable driving shape. EOG signals are used in this suggested framework. The Electrooculogram (EOG) is an electrical activity indicator related to eye motions. Other signal origins, called objects, may contaminate the electrooculography signal. Eye wink is one of the key causes of disturbance in the EOG signals among the various artefact sources. Blink attributes are determined from these signals, and they are evaluated using Fuzzy logic.

This paper uses a nine-transistor full adder model to design an eight-bit ripple carry adder for less power consumption. The conventional full adder design consists of 28 transistors which constitute high power consumption. Decreasing the transistor count decreases the power consumption in the circuit. A single bit full adder using a nine-transistor is implemented and using this adder, an eight-bit ripple carries adder is designed. A conventional CMOS adder, both single bit and 8-bit ripple carry adder remain also designed to compare the power outputs. Microwind-2.6a and DSCH 2.6 are used to acquire the power outputs of each circuit. To conclude, power comparisons for both single and eight-bit adders using the 9-transistor and conventional CMOS models are made.

The exponential growth of high dimensional biological data has led to a rapid increase in demand for automated approaches for knowledge production. Existing methods rely on two general approaches to address this challenge: 1) the Theory-driven approach, which utilizes prior accumulated knowledge, and 2) the Data-driven approach, which solely utilizes the data to deduce scientific knowledge. Both of these approaches alone suffer from bias toward past/present knowledge, as they fail to incorporate all of the current knowledge that is available to make new discoveries. In this paper, we show how an integrated method can effectively address the high dimensionality of big biological data, which is a major problem for pure data-driven analysis approaches. We realize our approach in a novel two-step analytical workflow that incorporates a new feature selection paradigm as the first step to handling high-throughput gene expression data analysis and that utilizes graphical causal modeling as the second step to handle the automatic extraction of causal relationships. Our results, on real-world clinical datasets from The Cancer Genome Atlas (TCGA), demonstrate that our method is capable of intelligently selecting genes for learning effective causal networks.

This paper proposes the effective solution for the power transmission lines under faulted conditions. In this analysis generally three transmission system technologies are existed for the industrial applications. New six phase transmission system technology implemented with two-double line model and special transformer based six phase transmission methodologies are provided. Six stage transmission lines are very encouraging for development in force conveying limit of existing frameworks keeping the same right-of- way. The execution of 6-stage transmission line goes basic as its insurance against different shortcomings is entirely complicated assignment. The simulation results are presented to verify the proposed concept using MATLAB/SIMULINK.

Internet of things is one of the rapidly growing fields for delivering social and economic benefits for emerging and developing economy. The field of IOT is expanding its wings in all the domains like medical, industrial, transportation, education, mining etc. Now-a-days with the advancement in integrated on chip computers like Arduino, Raspberry pi the technology is reaching the ground level with its application in agriculture and aquaculture. Water quality is a critical factor while culturing aquatic organisms. It mainly depends on several parameters like dissolved oxygen, ammonia, pH, temperature, salt, nitrates, carbonates etc. The quality of water is monitored continuously with the help of sensors to ensure growth and survival of aquatic life. The sensed data is transferred to the aqua farmer mobile through cloud. As a result preventive measures can be taken in time to minimize the losses and increase the productivity.

In this paper, we propose and analyze a novel idea of performing interference cancellation (IC) in a distributed/cooperative manner, with a motivation to provide multiuser detection (MUD) benefit to nodes that have only a single user detection capability. In the proposed distributed interference cancellation (DIC) scheme, during phase-1 of transmission, an MUD capable cooperating relay node estimates all the sender nodes' bits through multistage interference cancellation. These estimated bits are then sent by the relay node on orthogonal tones in phase-2 of transmission. The destination nodes receive these bit estimates and use them for interference estimation/cancellation, thus achieving IC benefit in a distributed manner. For this DIC scheme, we analytically derive an exact expression for the bit error rate (BER) in a basic five-node network (two source-destination node pairs and a cooperating relay node) on AWGN channels. Analytical BER results are shown to match with simulation results. For more general system scenarios, including more than two source-destination pairs and fading channels without and with space-time coding, we present simulation results to establish the potential for improved performance in the proposed distributed approach to interference cancellation. We also present a linear version of the proposed DIC.