Asian Journal of Convergence in Technology
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A Novel Antenna for 8 Element Beam Forming Antenna Array using Butler Matrix
Get PDFThis paper presents design of novel microstrip antenna for an 8-element linear array with 8x8 Butler Matrix as a beamforming network. The proposed structure resonates at 2.4 GHz frequency and is implemented using Microstrip Technology with FR-4 Substrate having εr=4.3 and height=1.6 mm. Simulation results are given for the components (microstrip antenna, quadrature couplers, crossovers, phase shifters) used to implement the matrix. The 8-element antenna array is connected to the matrix to form a beamforming system and produces eight orthogonal beams at −55◦, −36◦, -21◦, -7◦, 55◦, 36◦, 21◦, and 7◦. The reflection coefficients and isolations at all ports are below −10 dB at the center frequency and side lobes of radiation pattern are sufficiently low. The applications for this technique are in lower frequency bands of 5G and LTE, wearable devices and IEEE 802.11 WLA
Secure DLMS/COSEM communication for Next Generation Advanced Metering Infrastructure
Get PDFPower System infrastructure is one of the critical components of any nation. The automation of the power system is essential for the reliable and secure operation of the grid. Data plays a vital role in any automated system. So, data security should be inherently present in any automated system for the proper operation of the available components. For the automation of metering system, Advanced Metering Infrastructure (AMI) is being deployed in the power system. A smart meter is a critical component of AMI, whose data is used for load forecasting, scheduling, billing, and energy management. DLMS-COSEM acts as an application layer protocol for meter data exchange. This paper provides a detailed understanding of the DLMS-COSEM communication vulnerabilities, communication attack scenarios, high-security features, authentication procedures and suggests the best methodologies to be followed by a client or third-party system while communicating to the DLMS-COSEM servers in order to have a secure data exchange
Structural Health Monitoring of Old Industrial Structures
Get PDFRecent 2015 earthquake that had strike Katmandu region in Nepal have clearly indicated the negligence of the Government, engineers and the dwellers in following the Building code during its construction and use. If those buildings were evaluated structurally as per the norms, the picture would not have been so devastating. The structural engineers should have assessed the health and condition of old buildings. But the main problem here was lack of documents for conducting the survey. The whole survey was done in favor of client. It’s a need to create awareness and impose the building byelaws so that it will be followed strictly, at least when it comes to the part of human life. Loss of human life is a great loss to nation which cannot be recovered in terms of any compensation
Design the Boost Converter of Solar Photovoltaic Power System
Get PDFIn this paper, DC modulators are designed that raise the constant voltage to the operating values and that feed the loads The electrical elements that make up the lifter are designed for DC voltage. The main components are designed, which consists of three main phases connected in series with each other. The first stage contains an electric coil that is designed with specific specifications according to the requirements of the load. It also contains a suitable IGBT electronic key selected according to the specifications of the load. The three phases that make up the device are completely identical. The operating strategy of the various electronic switches is compatible with the load operation strategy and specifications. Feeding the step-up device from a group of batteries designed according to the needs of the load. And connect the batteries in series according to the needs of the designer. And the output voltage of the device is controlled at a constant value. This device feeds the DC/AC voltage changer, which in turn feeds the previous load. Determine the level of constant voltage 320VDC to obtain an alternating voltage of 220VAC. The electronic switches are controlled at each stage according to the strategy designed for operation. This strategy was programmed and placed in the memory of the microcontroller, where the Arduino was chosen for this purpose. This type was chosen for its simplicity and ease of programming and operation
Fault Tolerance in IoT: Techniques and Comparative Study
Get PDFFault tolerance increases system availability and reliability by making systems robust to failures and proactive enough to tackle failures. Fault tolerance can be introduced at different architectural layers of the Internet of Things (IoT), this is because a fault can occur at any of the layers. As for example, motion sensors, and motors can fail at the root layer, network connectivity could be disrupted in network layer, computation and storage nodes can perform erroneously in their layers, so it becomes crucial to introduce fault tolerance in IoT systems at every layer. The study paves the way for classifying current and possible fault tolerant approaches by presenting different techniques(replication, network control etc.), architectural patterns(centralized, hybrid etc.), layers(network, sense etc.) & styles(Microservices, Publish-Subscribe etc.) that can help in making a system fault tolerant efficiently. Paper also discusses current trends in fault tolerance, areas that have been widely worked upon and areas that can act as a future scope, in making IoT based systems fault tolerant and efficient
COMPARISON OF IMAGE CLASSIFICATION TECHNIQUES AND ITS APPLICATIONS
Get PDFImage classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of multispectral data make the accurate classification of such data challenging for traditional machine learning methods. In addition, multispectral imaging often deals with an inherently nonlinear relation between the captured spectral information and the corresponding materials. In this paper, we propose a novel classification method for multispectral imagery, named as support vector machine (SVM). Pixel multispectral imagery can be represented by amplitude, phase and residual in frequency. Its applicability and effects are assessed by the experiment using data set, in which CNN, and KNN based feature extraction methods are adopted for comparison, aiming to evaluate the performance of the proposed method. Experimental results illustrate that the proposed model gains the highest classification accuracy. Comparison of various performance parameters showed that KNN works better than SVM
Genetic Algorithm and its Applications - A Brief Study
Get PDFThis paper reviews and revisits the concepts, algo- rithm followed, the flow of sequence of actions and different op- erators used by Genetic Algorithm. GAs are the metaheuristic algorithm used for solving the searching problems. We will see that Genetic Algorithms has good searching properties which selects its operators depending upon the nature of the problem at hand, that is, if the problem has one optimal solution, Genetic Algorithm as well as Simulated Annealing can be used to solve it but if a problem has more than one solution, then only Genetic Algorithm proves to be suitable and the better choice as it creates several solutions for a problem
Medical B-Mode Ultrasound Imaging Reconstruction Algorithms: Evaluation and Simulation
Get PDFUltrasound is one of the most important imaging modalities in medical practice. It is the most technique development with a lot benefits and with little challenges that include low imaging quality and high variability. Medical field is the most application that exploit the ultrasonic technique widely in body imaging, especially the real time Feature which take advantage of diagnostic time.
This research makes a survey on the ultrasound image reconstruction and Display. First, the Ultrasound Imaging are reviewed as overall studying include the frequency ranges, advantages, main limitations, and applications. Second, the 2D or B-mode ultrasound imaging according to generation steps and mathematic studying are reviewed. Third, the stages of the 3D ultrasound object formation which is the data acquisition, data preprocessing, reconstruction method and 3D visualization, are discussed. Fourth, MATLAB Simulation to create B-Mode Ultrasound image with Synthetic phantom of a fetus in the third month of age, by using Field II software made specially for ultrasound environment, after initializing the ultrasound environment a phantom used to yield the B-Mode image. The complete B-Mode fetus scanned image creation need 5 hours and approximately 20 mins, that each line takes around 2min and 30 sec, with a processor 1.8 GHz Dual-Core Intel Core i5, MacOS. When the parameters of transducer have been changing then the clearness of the generated image the time taken will change in response
Design and Implementation of Artificial Intelligence Powered Agriculture Multipurpose Robot using Raspberry Pi
Get PDFThe agriculture field faces many problems such as crop diseases problem, pest outbreak problems, water problems, weeds, large use of fertilizer, and many more. These problems lead to crop loss, economic loss and also cause severe environmental problems due to the current agriculture practices. The AI and Robot Technologies had the potential to solve these problems very smartly. As agriculture is a dynamic sector, the problems in agriculture are not mid-core by AI and robotics, and a specific solution is provided to an expressly daedal problem. Diversity of systems have been developed to minimize and provide a better approach to the world. This paper contains significant contributions used to address the challenges that agriculture faces and through AI and robotic technology we eliminate problems
Identification of Normal and Abnormal Mammographic Images Using Deep Neural Network
Get PDFThis article presents an image retrieval strategy that considers the similarity of a selected image (CBIR-Content-Based Image Retrieval). The analogy is defined by the wavelet technique, combined with Hu moments, for removing features. The classification of mammography’s is conducted through the Artificial Neural Networks Auto-organizing System (SME). A Data Base (QUALIM), University of the Federal Republic of São Paulo (UNIFESP), and Medical Image Classification Laboratory are used to test the method. The system suggested is tested. We have employed two widely used pattern recognition approaches—facial recognition digital mammograms for examination. The techniques are based on the new classification schemes Ada Boost and Support Vector Machines (SVM).Several experiments were carried out to evaluate the accuracy of these two algorithms in different circumstances. The results for the Ada Boost classification system are positive, especially for mass lesions classification. In all cases, the algorithm was 76% exact, and only 90% accurate for mass. The SVM-based algorithm was not available. To improve the precision of the process, we need to choose enhanced image functionality for digital mammograms than those commonly used. Detection of breast cancer is the most challenging aspect in the field of health monitoring. This document has been used to evaluate breast cancer detection through a dataset of the mammographic image analysis company (MIAS). The suggested method has four key steps: preprocessing, segmentation, retrieval, and classification of images. Initially in mammograms, laplacian filtration was used to describe the edges' area and was thus particularly susceptible to noise. The modified adjustable Fuzzy-C-MEANS (ARKFCM) was used in the following segmentation to find the object within the complicated module. The conventional ARKFCM masses of undefined mass were painful to divide into mammograms. The Euclidean distance in ARKFCM was replaced with the correlation function to solve this problem to increase its segmental efficiency. In the segmented cancer region, the removal of representative subsets was performed by extracting hybrid properties (histogram of guided grade (HOG), uniformity, and energy). Each feature value was defined for the Deep Neural classifier—network (DNN) for detection in normal and pathological areas of mammograms. The findings of the study show that the technique shows an improvement of up to 3-9% in precision compared with other methods currently in use in breast cancer classifications. Describes a new way to identify borders between different brightness areas. The goal is to create distinctions between regions that are unclearly distinct and defined by tonal shifts. The limits are set by the coordinates of the start and endpoints. The proposed method can be used as a stage in advanced techniques for hierarchical image analysis that increases the semantically awareness of picture content with each step. This study applies and evaluates mammograms. Interpretation of mammograms is a complex research area discussed by many authors. The treatment of breast cancer is achieved using these approaches