We'Ken- International Journal of Basic and Applied Sciences

Rajkumar Sarode ¹, Snehal Nirmal ¹

Affiliations
1 Assistant professor, DDVPF’s, Institute of Business Management & Rural Development, Ahmednagar, IN

Abstract

Information and communication technology has become an integral part of human life, allowing people to achieve more in less time and at less cost. The purpose of this study is to see how information and communication technology can affect the progress of education for third grade high school students in Hash, Iran. Adescriptive study was used in the study. In 2010, the population was about 1,900 third-year high school students in Hash City, who were enrolled in 35 educational units. The sample size was calculated to be 320 using the Kyrgyz and Morgan statistics tables. Male and female students were selected in relation to the size of the community using a randomized, step-by-step approach. Cranach's Alpha was used to confirm the validity and reliability of a 24-item survey created by researchers using a Likret-type scoring system. The measurement method was used for data analysis. Descriptive statistics included frequency distribution tables, frequency percentages, and graphs. Inference statistics included the Khi (Chisquare), U MannWhitney, and Kruskal Wallis statistical tests associated with the measurement scale. The data was analyzed in SPSS. Studies show that the use of information and communication technology can help improve educational motivation, develop questioning skills, improve inquiry, and improve school performance. It has a great impact on improving the academic ability of third-year high school students. Male and female students with different average scores, age groups, and subjects experienced the same effect. However, it had a clear impact on children in vocational and junior high schools.

Keywords

Information and Communication Technology, Education Improvement, Internet, Effectiveness.

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Snehal Nirmal ¹, Rajkumar Sarode ¹

Affiliations
1 Research Scholar, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon

Abstract

The primary purpose of this research is to develop a non-blind image watermarking system that is both robust and unnoticeable using wavelet transforms and fuzzy inference. The emphasis is on developing discrete wavelet transform, human visual system, and fuzzy inference system-based picture watermarking that makes optimal use of human vision constraints. The purpose of this research is to develop a novel technique for embedding perfect measure watermark data into the host image without creating perceptual damage. The methodology is to combine discrete wavelet transforms, the human visual system, and fuzzy inference to enable the utilisation of human vision limits in a viable manner. Additionally, the idea is to insert a significant logo as a watermark rather than the more traditional pseudorandom paired grouping for robust image watermarking. The purpose of this project is to develop image watermarking using the discrete wavelet transform. The objective is to investigate wavelet basis functions that are ideal for picture watermarking and to empirically estimate the strength of the watermark in order to inject the maximum amount of watermark information into the host image without degrading its perceptual quality. To model and execute various assaults on watermarked photos in order to degrade their quality in order to assess performance for resilience. Additionally, performance is evaluated in the presence of the maximum potential degradation of the watermarked image in order to define effective robustness requirements. To evaluate the performance of suggested approaches based on DWT, DWT-HVS, and DWT-HVS-FIS image watermarking, as well as to compare the proposed approach's performance to that of existing approaches utilising performance parameters.

Keywords

Fuzzy Inference system, Image watermarking, host image, human visual system

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Rajkumar Sarode ¹, Snehal Nirmal ¹

Affiliations
1 Research Scholar, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, IN

Abstract

The shared and stored mixed media information is growing, and looking for or retrieving a significant image from a chronicle is a challenging exploration issue. Any image retrieval model's primary objective is to hunt for and mastermind photos that have a visual semantic association with the user's query. The bulk of web indexes on the Internet fetch photos using content-based algorithms that require subtitles as additional information. The user submits a query by inputting some text or keywords that match the file's keywords. )e yield is generated based on keyword matching, and this cycle can obtain insignificant photos. The distinction between human visual understanding and manual naming/commenting is the fundamental reason for producing the irrelevant yield. Any image retrieval framework must meet the fundamental criterion of searching for and sorting comparable photos from the archive with as little human interaction as possible. As implied by the writing, the choice of aesthetic characteristics for any framework is determined by the end user's requirements. Discriminative feature representation is another fundamental requirement for any image retrieval framework. To make the feature more robust and unique in terms of depiction fusion of low-level visual features, a large computational cost is required to obtain more dependable results. Regardless of the case, an ill-advised feature selection can degrade the performance of an image retrieval model. Contrary to conventional ideabased approaches, content-based picture retrieval is incompatible with them. "Content-based" refers to the fact that the hunt evaluates the image's contents rather than its metadata, such as keywords, labels, or depictions associated with the image.

Keywords

Content Based Image Retrieval, Similarity Computation, Internet retrieve, information, human communication

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Rajkumar Sarode ¹, Snehal Nirmal ¹

Affiliations
1 Research Scholar, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, IN

Abstract

Image fusion is the process of combining relevant data from a collection of data images into a single image. Image fusion has emerged as a new and attractive investigation zone as multi-sensor information has been more widely available in sectors such as distant detecting, clinical imaging, machine vision, and military applications. In remote detection, image fusion aims to create new images with both low spatial goal multispectral information (shading data) and high spatial goal panchromatic information (subtleties). Different programming calculations can be used to create an entangled image with a greater spatial aim; nevertheless, the bulk of image preparation calculations are timeconsuming due to the large number of figures involved. It is appealing to use a quick reconfigurable equipment framework, such as a Field Programmable Gate Array, to handle difficult calculating calculations and execute similar operations with swift qualities (FPGA). The use of multisensor image fusion on FPGA, on the other hand, appears to be a promising area of research. As a result, the primary goal of this study is to create and implement a rapid discrete wavelet transform (DWT) based multisensory image fusion via equipment programming co-reenactment.

Keywords

Image Fusion, Denoising Techniques, Different Transform, Image fusion, applicable data, discrete wavelet transform

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Snehal Nirmal ¹, Kalpana M. Gholap ², Yogesh V. Torawane ³

Affiliations
1 Research Scholar, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, IN
2 Assistant Professor & Head (Commerce) JETs Zulal Bhilajirao Patil College, Dhule, IN
3 Assistant Professor & Head (Commerce) KES'S Pratap College, Amalner, IN

Abstract

While computer vision is widely employed in a wide variety of applications, the precise and efficient identification of human behaviour remains a challenging area in computer vision science. Recent research has concentrated on smaller issues such as approaches for human action recognition of depth data, 3D skeleton data, photographic data, spatiotemporal methods focusing on interest and the identification of human activity. Despite this, no systematic survey of human behaviour appraisal has been conducted. To that end, we present a comprehensive review of methods for identifying human actions, including advances in the hand design of action characteristics in RGB and depth data, established methods for representing deeper learning action-based features, advancements in the methodology for identifying human-object interaction, and prominent present methods of deeper information.

Keywords

Action detection; action feature; human action recognition; human–object interaction recognition; systematic survey.

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