Volume 11 | Issue 7 |

 Abstract

This paper is aimed toward vitality vanquish in routing that correlate the AODV with altered AODV. Our own shelves counseled a haul honest trounce protocol for migrant advert hoc networks. The tenet of the manner used hither selects a routing rail via bloating the heft a few of the expedient paths. There are 3 specs in mod-AODV which might be warn to forecast the substance of the viable route: the cumulative coalition echelon period, the itinerary electricity, and the hop depend. Itinerary choice is primarily based on the heft fee of each viable course. In a viable route, the better the heft cost, the higher is its suitability for site visitors distribution. Clone consequences pageant that the proposed AODV outrun AODV in particular in an state of affairs with slight mobility.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Energy Dynamic Routing, AODV, M-AODV(Altered AODV)

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

CNN algorithms built on deep learning were used to divide satellite images into three categories. Not only can this study categorize satellite photos, but it can also categorize three distinct classes and pinpoint the characteristics of those other classes, like cats and dogs. It is also simple because these other classifications have some standout features that make them simple to differentiate, making classification simple. The main issue with satellite photography is that different satellite images may have different characteristics, which makes satellite image classification challenging. Another issue is that the majority of safelight images include noise contamination. The wireless image's noise patterns are estimated using the CNN model.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SATELLITE IMAGE CLASSIFICATION USING CNN

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

There has been irreparable harm caused by the fashion industry, one of the world's biggest and most important industries and is well known for its adverse environmental effects. According to UN Environment estimates, the fashion sector is responsible for 10% of carbon emissions and 20% of the world's wastewater. The industry is known for its quick speed and ongoing search for new and inventive designs, which has led to a significant increase in synthetic materials, hazardous colors, and energy-intensive production methods, all of which hurt the environment. Thus, there is an increasing need to encourage sustainable growth in the fashion business and lessen its adverse environmental effects. In the fashion sector, sustainability is assessed using. The triple bottom line strategy, which takes into account social, environmental, and economic factors. It entails reducing the adverse environmental effects and advancing moral and ethical principles in developing, manufacturing, and disposing of clothes and accessories. The contribution of intellectual property rights (IPR) to the advancement of sustainability in the fashion industry has recently received more attention. Intellectual property rights are essential in the fashion business for protecting designers' and firms' distinctive designs, logos, and trademarks. By doing this, these designers and businesses may protect the exclusivity of their goods and stop illegal copying and inappropriate usage of their designs.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Intellectual Property Rights, Upcycling and Recycling Fashion, Sustainable Fashion, Fashion Industry.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Deep learning is one of the most unexpected machine learning techniques which is being used in many applications like image classification, image analysis, clinical archives and object recognition. With an extensive utilization of digital images as information in the hospitals, the archives of medical images are growing exponentially. Digital images play a vigorous role in predicting the patient disease intensity and there are vast applications of medical images in diagnosis and investigation. Due to recent developments in imaging technology, classifying medical images in an automatic way is an open research problem for researchers of computer vision. For classifying the medical images according to their relevant classes, a most suitable classifier is most important. Where we are proposing our model where the algorithm is trained for classifying medical images by deep learning technique. A pre-trained deep convolution neural network (GoogleNet) is used that which can classifies the various medical images for various body organs. This method of image classification is beneficial to predict the appropriate class or category of unknown images. The results of the experiment exhibit that our method is best suited to classify various medical images.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Medical image classification, pre-trained DCNN, convolution neural network, deep learning

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Only after the initial fermenting phase were some of the tobacco leaf insect bites visible. Pest attacks on tobacco leaves cause the quality to decrease. To preserve quality, it is necessary to separate diseased and pest-affected leaves from healthy leaves. Typically, sorting is done by hand, which leaves room for human error. In this work, we attempted to automatically classify the leaves impacted by various pest infestations. One of the most recent classification techniques suggested in this paper makes use of the well-known VGG19 architecture: the convolutional neural network (CNN). If trained with random weight initialization, VGG19 training can take a while. To increase accuracy and shorten training time, we chose beginning weights using transfer learning. Considering the outcomes, We achieved a very good accuracy by training with a single class of the disease using VGG19 and transfer learning. To achieve the best outcomes, some scenarios are examined depending on a combination of the number of learnable parameters and types of the optimizer. As a result, it was established that the suggested architecture can accurately identify all training and validation data.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tobacco Leaf Pest, VGG19, Transfer Learning.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study suggests a concept called Augmented Education (Augmented) to initially address the issues raised above. This model primarily comprises of the following three modules, as indicated in Fig. 2: Three modules are included: (1) a Data Module that combines data from multiple sources on campus, (2) a Prediction Module that uses machine learning (ML)-based algorithms to predict academic performance, and (3) a Feedback Module that delivers visualized feedback. The Data Module evaluates characteristics and features that can represent students' behavioral change from three different perspectives. In the end, AugmentED is evaluated using data from 156 actual college students. In this work, a model for the proposed system called Augmented Education (AugmentED) is put forth in an effort to initially address the issues raised above. This model primarily comprises of the following three modules of the proposed system:.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Predicting Performance of Students in Online Classes Using ML

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Globally, a sport as an industry has a unifying appeal. The sports industry boasts of a dynamic appeal that many other, even bigger industries look at with envy. It has the power to define nations as a whole. Sports offer a perfect opportunity to explore scientific concepts such as force, motion, potential energy, velocity, and torque. For many students school-organised sports play an important role in their academic and social experiences. Every school has sports embedded in their curriculum as they understand the importance of physical health and activity. However, the importance given to sports ends there as this inclusion is just for the sake of a formality. Whether it be high performance sports at the Olympics or the development of sports locally, sports education is becoming increasingly important in the modern world. Even though there is a growing awareness of including sports education as a compulsory subject in Indian schools, there lie some endemic obstacles which are preventing its growth trajectory. Roselin Kiro of Elets News Network (ENN) finds out the scenario of sports education in schools in India. India For Sports (IFS) was set up with a vision to provide a same level playing field to the Indian athletes when they compete at international events.[3] The organization tries to solve the basic issue of funding for the deserving athletes. It also provides the athletes visibility by covering their stories, hardships, achievements and activities. The organization also connects the athletes to corporate sponsors and other sports aiding organization to provide facilities such as dietitians, nutritionists, psychologists etc. India For Sports was a crowd funding platform for Indian athletes. It was incepted in June, 2014 to help Indian athletes with funding. It is running 6 fund raising campaigns [2] for athletes in individual sports disciplines such as athletics, table tennis and wrestling.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key words : Relevance, Sports, Education, Schools, Concepts.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The main objective of this study is to examine farmers' aperception towards purchasing crop insurance, aiming to help researchers understand how to mitigate or avoid risks faced by farmers through crop insurance subscriptions. The chosen location for this investigation is Erode District in the Western part of Tamil Nadu, as the attitudes and perceptions of farmers in this area are indicative of their behavior towards crop insurance. The researcher analyzed various factors that influence farmers' perceptions and attitudes towards buying crop insurance. For this study, a sample of 426 farmers from Erode District was selected using the convenience sampling method. To establish significant relationships between variables, the researcher utilized Cluster Analysis, Multiple Regression, Factor Analysis, Chi-Square Analysis, and Percentage Analysis. Additionally, Cronbach's alpha was used to assess the questionnaire's reliability.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Attitude, Crop Insurance, Perception, Farmers' Risk, Natural Calamities, Government, Agro Economy, etc.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In India by the year 2025, approximately 75% of the population would be employable. For the overall development of the country, we need better skills and opportunities at the same time. The population with proper skills could help the nation to generate revenue, create job opportunities and mitigate poverty. Small-scale industries in India are crucial for the development of the nation as a developed country, despite that this sector is facing a shortage of skilled workforce. Understanding and mitigating the challenge of skilled workforce shortage is crucial for the growth and success of small-scale industries in India. By analysing the factors contributing to the shortage, evaluating its impacts, and exploring potential solutions, this research paper aims to provide valuable insights for policymakers, industry leaders, and stakeholders in addressing this pressing challenge. Ultimately, the findings and recommendations from this study can contribute to fostering a skilled and competitive workforce that supports the sustainable development of small-scale industries in India.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skilled workforce, Sustainable development, employment generation, Vocational training, small-scale industry.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Image dehazing is a critical task in computer vision and image processing that aims to restore clear visibility in hazy or foggy images. In recent years, significant advancements have been made in image dehazing algorithms, leading to improved results and enhanced visual quality. This paper presents a comprehensive review and comparative analysis of state-of-the-art image dehazing techniques. We categorize the existing methods into different groups based on their underlying principles and analyze their strengths and limitations. Additionally, we provide a comparative evaluation of these techniques based on various metrics, including visual quality, computational complexity, and robustness to different hazing conditions. This analysis aims to assist researchers and practitioners in understanding the current landscape of image dehazing methods and identifying avenues for future research.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image dehazing, computer vision, image processing, visibility restoration, hazy images, foggy images

  License

Creative Commons Attribution 4.0 and The Open Definition