With recent advancements made in wireless communication techniques,wireless sensors have become an essential component in both data collection as well as tracking *** Sensor Network(WSN)is an integral part of Internet...
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With recent advancements made in wireless communication techniques,wireless sensors have become an essential component in both data collection as well as tracking *** Sensor Network(WSN)is an integral part of Internet of Things(IoT)and it encounters different kinds of security *** is designed as a game changer for highly secure and effective digital ***,the current research paper focuses on the design of Metaheuristic-based Clustering with Routing Protocol for Blockchain-enabled WSN abbreviated as *** proposed MCRP-BWSN technique aims at deriving a shared memory scheme using blockchain technology and determine the optimal paths to reach the destination in clustered *** MCRP-BWSN technique,Chimp Optimization Algorithm(COA)-based clustering technique is designed to elect a proper set of Cluster Heads(CHs)and organize the selected *** addition,Horse Optimization Algorithm(HOA)-based routing technique is also presented to optimally select the routes based onfitness ***,HOA-based routing technique utilizes blockchain technology to avail the shared mem-ory among nodes in the *** nodes are treated as coins whereas the ownership handles the sensor nodes and Base Station(BS).In order to validate the enhanced performance of the proposed MCRP-BWSN technique,a wide range of simulations was conducted and the results were examined under different *** on the performance exhibited in simulation outcomes,the pro-posed MCRP-BWSN technique has been established as a promising candidate over other existing techniques.
Reconfigurable computing has shown significant promise in many fields. The lack of high-level design tools hampers the widespread adoption of reconfigurable computing systems. The designer needs both in-depth software...
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Reconfigurable computing has shown significant promise in many fields. The lack of high-level design tools hampers the widespread adoption of reconfigurable computing systems. The designer needs both in-depth software and hardware design knowledge to develop applications for GPP/RAU hybrid system. This paper presents an initial ASCRA (Application-Specific Compiler for Reconfigurable Architecture) compilation framework for automatic mapping of C to VHDL that brings the gap in automatic compilation tools for reconfigurable computing. In ASCRA, the loop pipelining is mainly concerned. The loop pipelining framework is presented in this paper. Most compilers use a modulo scheduling with a constant initiation interval to schedule the start of each iteration and use a directed pipelining division method to generate pipeline. In order to increase throughput and reduce the pipeline depth, a modulo scheduling with the variable initiation interval and an improved pipelining division method are presented in ASCRA. In modulo scheduling, the variable initiation interval is generated by the two-dimensional vector algorithm. The improved pipelining division method mergers the shorter delay pipeline stage without changing the maximum frequency to generate pipeline. A verification platform of ASCRA is also built on a ML509 development board. The experiment on selected kernels that shows the methods give significant performance improvement.
As a significant measure of software security evaluation, software reliability evaluation is also the basis of software safe operation. Traditional software system security evaluation methods are qualitative evaluatio...
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As a significant measure of software security evaluation, software reliability evaluation is also the basis of software safe operation. Traditional software system security evaluation methods are qualitative evaluation based on the functional and structural measurements, and it often ignores quantitative research based on invalidity and fault. This paper propose a stochastic transition function as a measure parameters of the reliability of stochastic Petri nets （SPN） theory. By calculating the probability of stability of the system, failure and mean time to first failure, it establishes an evaluation and measurement method for software reliability. With example analysis, the method can conduct effective evaluation on the software reliability index quickly and accurately, and meanwhile provides a new method for the software security evaluation.
Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single *** data of water quality in the environment comes from different sensors,thus the data must be *...
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Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single *** data of water quality in the environment comes from different sensors,thus the data must be *** our research,self-adaptive weighted data fusion method is used to respectively integrate the data from the PH value,temperature,oxygen dissolved and NH3 concentration of water quality *** on the fusion,the Grubbs method is used to detect the abnormal data so as to provide data support for estimation,prediction and early warning of the water quality.
An accurate and rapid method is proposed to optimize anharmonie linear surface-electrode ion trap design. Based on the method, we analyze the impact of the architectural parameters, including the width, number, and ap...
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An accurate and rapid method is proposed to optimize anharmonie linear surface-electrode ion trap design. Based on the method, we analyze the impact of the architectural parameters, including the width, number, and applied voltage of prerequisite active electrodes, on the number and spacing of trapped ions. Sets of optimal anharmonic trap design are given. Then the optimal designs are verified by using an ant colony optimization algorithm. The results show that the maximum ion position errors and maximum ion spacing errors are less than 1 μm up to 80. The mean of the maximum errors is nearly linear with respect to the number of trapped ions.
In the realm of data mining, outlier detection has emerged as a pivotal research focus, aimed at uncovering anomalies within datasets to extract meaningful and valuable insights. The objective is to leverage data mini...
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The standard Glowworm Swarm Optimization(GSO) has poor global search ability and easily trap into local optimum. In order to solve these problems, a Quantum Glowworm Swarm Optimization Algorithm based on Chaotic Seque...
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LiDAR-camera extrinsic calibration (LCEC) is the core for data fusion in computer vision. Existing methods typically rely on customized calibration targets or fixed scene types, lacking the flexibility to handle varia...
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Depression has grown to be a common mental disorder worldwide, and suicidal attempts are a common complication among depressed people. Despite the broad healthcare programs and treatment availability, the detection ra...
Depression has grown to be a common mental disorder worldwide, and suicidal attempts are a common complication among depressed people. Despite the broad healthcare programs and treatment availability, the detection rateremains rather low, and most depressed people refuse to look for treatment. Social media has become essential in people’s lives, where they share daily activities, thoughts, and feelings with others. In addition, machine learning techniques and deep learning are widely used in sentiment analysis. Therefore, it is easy to utilize them for the early detection of depression. This paper will focus on three main objectives. The first is developing a classifier model for the early detection of depression among Twitter users. The second is studying the impact of some pre-processing steps on the performance of classifiers that were ignored in previous studies. The third is comparing the performance of different machine learning techniques and pre-processing. Support Vector Machine (SVM), Logistic Regression (LR), and Light GBM (LGBM) as three machine learning approaches are applied. The results indicate that the best accuracy obtained is 93% with stemming, replacing slang words and emoji, and not removing some stop words with the SVM technique.
Delays of both pedestrians,who are classified according to whether complying with traffic law,and vehicles at a signalized crosswalk are analyzed in this *** truncated Adams' model is applied to generate the proba...
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Delays of both pedestrians,who are classified according to whether complying with traffic law,and vehicles at a signalized crosswalk are analyzed in this *** truncated Adams' model is applied to generate the probability and mean of delay of pedestrians non-complying with traffic *** the section-based traffic queuing-theory and the stochastic decomposition property of M/G/1vacation system with exhaustive service,the mean delay of vehicles is formulated.A multi-objective optimization model simultaneously minimizing the delays of pedestrians and vehicles during a signal period is *** effects,which several model parameters have on the delays and the optimal solution of the model,are illustrated by numerical examples.
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