Journal of Electronics and Communication Systems

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Naazaan Shaheen, Yogendra Singh
Abstract:
Intrusion Detection is an important step to ensure security in computer networks. In this paper, a novel model for intrusion detection is presented. The model has been developed using various existing machine learning techniques viz. decision tree, Naive Bayes, KNN  and logistic regression techniques. Preexisting database of network intrusion is used to analyze the performance of the proposed model. As seen from the experimental results, the decision tree gives the best outcome with an accuracy of 96%
Akash Gupta
Abstract:
Breakages of both warp and weft yarns are one of the most prevalent issues in textile technology today. This issue lowers the quality of the fabric produced as well as the production pace. Numerous forms of fabric flaws still need to be found by hand examination in the case of contemporary weaving techniques. The purpose of this work is to present an efficient and precise technique for automatically identifying fabric defects. Using Aphelion Dev software, statistical characteristics including mean, standard deviation, kurtosis, skewness, and histogram representation of fabric photographs are taken into consideration when comparing fabrics with and without faults. To provide a precise result for fabric flaws, morphological approaches are applied. The finished image has been integrated into an open platform for multimedia applications, speeding up processing time by 60ns. This method excels at finding fabric flaws with greater accuracy, effectiveness, and in less time.
Deepa K, Prashant Sangulgi
Abstract:
Presently days the method involved with removing significant principles from large and complex data are called data mining. Data mining has a rising fame in each field today. Data units are laid out in client situated enterprises, for example, showcasing, money and telecom to deal with the client beat and obtaining, specifically. Among the data mining techniques, order calculations are utilised in examinations led for client securing to anticipate the likely clients of the organization being referred to in the connected business. The idea of Data Mining has arisen to meet the prerequisite of speedy and exact data support for dynamic cycle. Data Mining is investigation of data to distinguish connection between various data components or substances. The course of data mining can likewise include connection or relationship between at least two data components, substances or occasions. They permit associations to make proactive, information-driven choices and answer questions that were already excessively tedious to determine. In this exploration we have zeroed in on the correlation of different Data Mining apparatuses which are useful and set apart as the significant field of data mining Technologies. As we know that numerous public and Multinational organisations and little or enormous associations are worked in better places of the various nations. Every activity might produce large data or unstructured. This sort of huge data is accessible as byte which has definitely changed in different regions. To examine, oversee and pursue a choice of such sort of colossal measure of data we really want strategies called the data mining which will changing in many fields.  Bank advertising data set in UCI Machine Learning Data Set was utilised by making models with similar grouping calculations in various data mining programs. Exactness, accuracy and measure measures were utilised to test exhibitions of the characterisation models. While making the grouping models, the test and preparing data sets were arbitrarily separated by the holdout technique to assess the exhibition of the data set.
M Snehalatha, N. Ramamurthy, K Swetha, K Vishnupriya, P Sreelekha, N Niharika
Abstract:
The use of bilateral filters is one of the most efficient and resource-saving image processing techniques. This method does not use edge smoothing to filter the image, but it does use non-linear spatial averaging. The characteristics of the filters in the filtering process outlined above are quite important. The outputs and results are dramatically affected by even minor changes in filter parameter values. The author contributed two pieces to this publication. The author has contributed to the study of parameter selection of bilateral filters that are optimal in nature in the context of picture denoising applications. The second contribution focuses on expanding the current work, the bilateral filters.
T. Tirupal, K. Joshna, M. Laharika, A. Gouthami, M. Dhana Lakshmi
Abstract:
The solar industry is a worth billions of dollars industry. This produces 20 GW of power, which is insufficient for processing. Every day, the Sun brightens the globe by irradiating a massive amount of energy, the bulk which one is lost or not utilized as a result of improper solar panel installation the conversion of solar energy to electrical energy is significantly higher when the solar panel is constantly placed 90 degrees to the sun. To build an automatic solar panel using ATMega328 controller, we'll use two Light sensors (Light dependent resistors) to detect light and a servo motor to spin the solar panel in the position of the sun rays. The benefit of this concept is that the solar panel will constantly track light from the sun and will regularly charge when facing the sun, and offer the maximum amount of power.
Swapnil Bandal, Jakkan D. A.
Abstract:
The framework proposed in this paper is a cutting-edge method for tracking weather conditions in a specific location and making the data available to everyone, anywhere in the world. The Internet of Things (IoT) is the technology behind this, which is a cutting-edge and cost-effective approach for connecting things to the internet and connecting the whole universe of things in a network. Things could go either way here.
Ranjana Battur, Jagadisha N.
Abstract:
One of the important concepts in information & data analytics is the content-based image retrieval process. We are living in the information age. In the modern-day digital information technology imaging world, this is playing a predominant role in different sectors ranging from defense to research fields. Content-based image retrieval, also known as query by image content is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images or textual matters in large databases. The usage of digital images has been increased enormously from the last decade due to the drastic growth in storage & network technology. These technological changes have led professional users to use, store and manipulate remotely stored images. Information Retrieval (IR) deals with the location and retrieval of related documents or images based on user inputs such as keywords or examples as a query from the repository. This has motivated us to take up the research work on the CBIR concepts. Hence, to throw light into this chosen research topic, we are carrying out extensive research on the image feature synthesis and matching in content-based image retrieval systems using the concepts of AI, ML & Fuzzy Logic schemes, which could be used to improve the retrieval system's performance in CBIRs. A brief survey, i.e., an insight into the chosen research area in the field of content-based image retrievals was made & the same is being presented w.r.t. the work done by various researchers across the globe in the form of an extensive literature review. The work done by them was studied, lacunas observed & the problem was defined with a couple of good objectives to be solved four objectives were proposed as O1 - Investigation of the effectiveness of evolutionary computation in generating composite operator vectors for image, so that feature dimensionality is reduced to improve retrieval performances; O2 - Construction of the image-leve
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