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This paper inspects the consensus problem of nonlinear mixed delay multi-agent systems with random packet losses through the sampled-data control using the undirected graph without any specified leader for the other following agents. The probabilistic time varying delay is taken in the control input delay that Bernoulli distributed white sequence is engaged to formulate the random packet losses between the agents. The consensus problem can be changed over into a stabilization problem by using the Laplacian matrix which can be obtained by undirected graph. By framing a Lyapunov-Krasovskii functional with triple integral terms and implementation of the property of Kronecker product together with some well known matrix inequality techniques, a mean square consensus for mixed delay multi-agent system can be achieved. Terminally, two numerical examples are provided to illuminate the advantages of the suggested techniques.

In this project, we introduce a waste management system that uses Internet of Things to monitoring garbage level in cans. Due to a lack of manpower, the local corporation does not collect reports on overflowing garbage cans. It could lead to unsanitary conditions in cities, putting people's health at risk. It can be reduce human intervention and also reduce the fuel consumption in waste collecting system. The Internet of Things could provide a solution to this conundrum. The Internet of Things (IoT) is a network of physical objects that are installed with software and sensors, as well as internet connectivity, to collect information and data. We may be able to create a smart garbage collector system by employing the Iot technologies. We might be able to create a smart garbage collector system using IoTThe system is intended to collect information and transfer it over a wifi module. The main goal of this design is to develop a system for monitoring garbage using data obtained from sensors.

This study examines the non-fragile synchronization of genetic regulatory networks (GRNs) with time-varying delays. Genetic regulatory network is formulated and sufficient conditions are derived to guarantee its synchronization based on master-slave system approach. The non-fragile observer based feedback controller gains are assumed to have the random fluctuations, two different types of uncertainties which perturb the gains are taken into account. By constructing a suitable Lyapunov-Krasovskii stability theory together with linear matrix inequality (LMI) approach we derived the delay-dependent criteria to ensure the asymptotic stability of the error system, which guarantees the master system synchronize with the slave system. The expressions for the non-fragile controller can be obtained by solving a set of LMIs using standard softwares. Finally, some numerical examples are included to show that the proposed method is less conservative than existing ones.

Simple and sensitive infrared spectrophotometric method has been developed for the estimation of modafinil in tablet dosage form and the Beer’s Law concentration range was found to be 1.0mg to 2.5mg. The correlation coefficient for the method was found to be 0.999 and the developed method was analyzed for specificity, limit of detection (LOD), limit of quantification (LOQ), linearity of response, precision and accuracy; thus the proposed method could be adopted for routine analysis of bulk drug and its formulation.

This paper establishes a novel non-fragile sampled data control framework for non linear multi-agent systems with additive time varying delays and Markovian jump parameters. The Laplacian matrix represents the interconnection between the agents which are denoted by an undirected graph. Relevant Lyapunov Krasovskii functional (LKF) is constructed which contain major information about the additive time-varying delays. The major goal of this paper is to model a non-fragile sampled-data control scheme which guarantees the stabilization for the proposed system. Apart from that, the Jensen’s and some improved integral inequalities are used for deriving the derivatives of LKFs with single, double and triple integral terms and the adequate conditions are expressed in terms of linear matrix inequalities. At last two numerical examples are given to verify the theoretical results.

One of the key targets in twist of fate information analysis is to become aware of the primary factors related to an avenue traffic coincidence. However, heterogeneous nature of street twist of fate data results in the evaluation tough. Records has been used extensively to triumph over this heterogeneity of the twist of fate facts. So as to conquer heterogeneity we propose a technique to categorize the twist of fate information into different classes. Herewe use clustering as a preliminary mission for segmentation of 21,436 road injuries on road community of united kingdom between 2009 and 2016 (each inclusive). On clustered records affiliation rule mining method (apriori algorithm) is carried out to become aware of the semantics of coincidence incidence and to quantify quantity of accident occurrences based on type of vehicle, weather conditions, lighting fixtures.

Generally, VLSI Circuits are very complex due to the technology scaling. Post-silicon validation is a critical part of Integrated Circuits. It is the process of finding the bugs that have escaped from the pre-silicon phase. According to International Technology Roadmap for Semiconductors (ITRS), time-to-market is the major constraint for verification and testing. The main challenge of post-silicon validation is that it has limited observability and controllability of internal signals in the manufactured chips. On-chip buffers are used to improve the observability and controllability of these signal states during runtime. Compared to existing techniques Trace-based debug technique has been widely utilized by the industries for the past few years to overcome the challenges. The aim of this work is to provide a framework for understanding insights and research opportunities, how the problems are dealt from different perspectives in trace-based post-silicon validation and debug. It also provides the various parametric analyses and comparisons of verification and validation techniques.

Post-silicon validation is the most vital parts of modern Integrated Circuits. The key challenge of silicon validation is that it has limited observability and controllability of internal signals. To improve those, a profitable set of signals should be selected. An automated procedure is proposed to select those signals which are used to facilitate early malfunctions of the design. Given the input vector set to the design an error transmission matrix is generated. From that, both relatively independent and dependent flip-flops are identified for grouping the signals through Mixed-Integer Linear programming. This method precisely identifies the paths which improves observability and can speed up the process.

As per Moore's Law the growth of transistors in VLSI (Very Large Scale Integration) chip is doubled for every 18 months. Due to this rapid improvement, testing the VLSI integrated circuit for fault free conditions requires large duration of times. Hence this research paper going to propose the data compression technique using Hamming Encoder and Decoder to reduce the test time with small area overhead on chip. The novel methodology also reduces the switching activity between the modified test inputs which lead us to reduce the test power dissipation during testing. The estimation of area overhead is also determined through implementing the additional hardware component of novel circuit with the Field Programmable Gated Array (FPGA) SPARTAN III kit using XILINX ISE Design Suite 14.7 version tool. The entire hardware component of the chip is described using Hardware Description Language (HDL) Verilog. The estimation result shows as its required only minimum amount of hardware component approximately 5% is added to the chip.