Applied Science and Engineering Journal for Advanced Research
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A Study of Big Data: An Importance to Create New Trend in E-Business
Get PDFIn the developing world it is require providing services in the financial, agricultural, business, government, healthcare, information technology and e-business sectors. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future. Big data is not a precise term; rather it’s a characterization of the never-ending accumulation of all kinds of data, most of it unstructured. It describes data sets that are growing exponentially and that are too large, too raw or too unstructured for analysis using relational database techniques. Whether terabytes or petabytes, the precise amount is less the issue than where the data ends up and how it is used. Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering areas, including physical, biological and biomedical sciences. This paper presents the features of the Big Data revolution, and proposes a Big Data processing in e-business, from the data mining perspective. This big-data model involves finding of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues and importance to create new trend in e-business
Development in Deep Convolutional Neural Networks by using Machine Learning Framework
Get PDFIn recent years, the machine learning technology has drawn more interest in a variety of vision tasks such image classification, image detection, and picture identification. Recent improvements in machine learning methods, in particular, stimulate the use of convolutional neural networks for image classification. CNNs are recognised as a potent class of models for image identification issues, sometimes even outperforming humans. The study described in this paper\u27s major objective is to provide an overview of the rise and development of machine learning, deep learning, CNN, and the use of machine learning for image categorization. The CNN and conventional methods are contrasted at the conclusion
Ultrathin Polarization Insensitive Dual/Triple Band Reconfigurable Metamaterial Microwave Absorber for C, X and Ku Band Applications
Get PDFA polarization independent dual/triple band metamaterial microwave absorber is designed and characterized. The absorber design comprise two square loop resonators and a circularly slotted square patch resonator designed with 0.03 mm thick copper plate. These resonators are separated by 1.56 mm thick FR4 dielectric from back annealed 0.03mm thick continuous copper plate. The simulated responses derived using HFSS shows that the intended absorber exhibits three absorption peaks at 4.75, 8.52 and 14.16 GHz with an absorption of 94.5%, 97.6% and 98.2%, respectively. The electrical dimensions of the unit cell are 0.158λ × 0.158λ computed at 4.75 GHz. The designed structure is polarization independent due to four-fold symmetric design configuration and therefore exhibit the same absorption response for both TE and TM polarizations for normal incident of the EM wave. The absorption response for oblique incidence angles has also been examined for both polarizations and the absorber exhibit above 80% absorption at oblique angles of incidence. Further, the designed is made frequency reconfigurable by embedding RF switches at circularly slotted square patch resonator. At off conditions of the switches, the design shows dual band behavior (for C, X) which makes it a potential candidate for reconfigurable RF applications such as RCS reduction, energy harvesting, wireless communication and sensors etc
Design and Development of Underground Cable Fault Location
Get PDFThis abstract presents an overview of the design and development of an underground cable fault detector. The system aims to provide an efficient and reliable solution for detecting faults in underground power cables, facilitating quick identification and repair of faults to ensure uninterrupted power supply. The underground cable fault detector comprises several essential components and functionalities. It incorporates sensors, data processing algorithms and a user interface for fault detection and localization. The sensors are deployed along the underground cable network to monitor parameters such as voltage, current. The data processing algorithms analyse the sensor data in real-time to identify abnormal patterns and deviations that indicate cable faults. These algorithms employ advanced signal processing techniques, pattern recognition, and fault signature analysis to distinguish between normal cable operation and fault conditions. The fault detector system also includes a user interface which provides visual indications to alert operators about the presence and location of cable faults. The interface may display fault information such as fault type and distance from the detection point to aid in efficient fault location and repair. During the design and development process, considerations are given to factors such as system sensitivity, accuracy, and reliability. Extensive testing and validation procedures are conducted to ensure the system\u27s performance under various fault scenarios and environmental conditions
Design, Development and Performance Evaluation of Semi Automated Citrus Juice Extractor Machine
Get PDFCitrus juice extractor machine has been design, fabricated and can be found in numerous studies at different areas. These citrus juice extractor machine is a semi automated one that operates from the entrance of citrus into the hopper basket till the filteration of the juice for consumption. The operational procedure for the extraction of juice starts from the stacking of neatly cleaned citrus of same size in the basket position ontop of the extractor machine which in turn passes through the hopper to the extraction chamber where the oranges are cut into two equal halves for the twin knaggy ball shearing then the pulps are dropped through the remaning collector to the residue collection bin while the extracted juice flows through the seize to a container for consumption. The optimal operating speed of the juice extraction machine was found to be 15rpm, while the optimum feed was found to be F1 (2.5 kg/min). The average juice extraction efficiency at optimum speed (S) and feed rate (F) was 64%; juice yield at optimum Speed and Feed was 60%; juice extraction losses was 35% at optimum Speed and Feed
A Perceiving and Recognizing Automaton Prediction for Stock Market
Get PDFThe skill of forecasting the value of a company\u27s equity on the stock market In order to forecast stock market prices, this research suggests a machine-learning (ML) artificial neural network model. The back-propogation algorithm is integrated into the suggested algorithm. Here, we use the back-propogation algorithm to train our ANN network model. Additionally, we conducted research using the TESLA dataset for this publication
Data Clustering and Techniques with Weights Over Data Stream
Get PDFData mining refers to extract and identify useful information from large sets of data. This term is really a misnomer. Thus, data mining should be named as knowledge mining which rely stress on mining from vast sets of data . An enormous quantity of data is present in the information industry. This data is meaningless until it is converted into useful form of information or help the industries in their business. It is essential to analyze this plenty of data and extract the valuable information from it. In data mining, extraction of information is not only the process to be performed it also involves various other process such as cleaning, integration, data transformation, data mining, pattern evaluation and presentation. When all these processes are completed one will be able to use this valuable information in many applications such as Fraud Detection, Market Analysis, Production Control, Science Exploration, etc.(Dhaka et al.,2018)
This paper introduces the significance use of data mining techniques such as clustering, association-rules, sequential pattern, statistics analysis, characteristics rules and so on can be used to find out the useful knowledge. Finally, various tools has been explained in this paper
Cloud Computing Scheduling Algorithms and Resource Sharing
Get PDFA flexible, affordable, and trustworthy platform for delivering IT services to customers or businesses online is cloud computing. It is a collection of applications, infrastructure, distributed services, and information. It is described as a collection of services that offer internet-based infrastructure resources and data storage on a third server. In comparison to other infrastructure, it offers its users scalability, dependability, high performance, and an affordable option. However, because crucial services are frequently contracted out to a third party, it is more difficult to ensure data security and privacy, support data and service availability, and mitigate risk associated with cloud computing. With relation to cloud-connected automobiles, we examine here vulnerabilities, related dangers, and potential solutions for assessing algorithms
Automatic Control and Mathematical models for Three Phase Transformer using MATLAB
Get PDFOur paper\u27s primary goal is to use MATLAB to create a tool for transformer design. Manufacturers of transformers can expand their design capacity and save design man-hours by using the suggested methodology, which has several benefits. By running the values through the MATLAB software, we can construct a distribution transformer with any value (power, primary voltage/secondary voltage), a 50 HZ frequency, and a delta/star, shall and core type, oil immersed natural cooling design. In comparison to conventional methods using the same set of constraints, the dimensions as well as the active cost have been decreased. Therefore, this study shows how to use MATLAB to build power transformers in a better and more effective manner. Even though it is anticipated that the present power load will increase by 150% in 2017, it is challenging to find a solution to improve the capacity of facilities, particularly for power transformers. Using MATLAB to create a transformer design will be beneficial in the future
Multiple Description Coding for Efficient, Low-Complexity Image Processing
Get PDFThis study uses Set Partitioned Embedded bloCK based coding, which is quick, effective, straightforward, and often used, to code several descriptions of changed images. Using images\u27 discrete wavelet transform (DWT), this type of coding can be used to its fullest capacity. To enable accurate transmission of the image over noisy wireless channels, two associated descriptions are created from a wavelet processed image. These associated descriptions are broadcast across wireless channels using the set partitioning technique and SPECK coders. The quantity of descriptions received affects the quality of the image reconstruction at the decoder side. The quality of the reconstructed image improves as the number of descriptions received at the output side increases. When a description is lost from the various descriptions, the receiver can still guess it by using the correlation between the descriptions. Even when half of the descriptions are lost in transmission, the simulations run on an image in MATLAB still produce respectable performance and outcomes