Systematic plant-based categorization has never been difficult. Targeted crop safety is dependent on automated technologies that detect and classify plants. Classical machine learning approaches have been used to categorize leaves using handcrafted features from the shape of plant leaves, which have yielded promising results. However, we concentrate on classifying plant leaves using non-handcrafted traits. To accomplish this, we employ the use of deep learning for extraction of features and categorization. Deep Convolution Neural Networks have recently demonstrated impressive achievements in picture classification and object detection challenges. This paper proposes using the built-in, compact VGG-16 model to detect and classify ten plant species from the Plant dataset. The proposed models are utilized to classify ten other classes.When contrasted with other pre-trained models, VGG -16 fared better in categorizing leaf images. Computerized plant species categorization could be beneficial to food engineers, agricultural professionals, researchers, and the general public.

Keywords : Machine learning, Deep Convolution Neural Networks, Agricultural professionals, Categorization

Author : K.Abinaya, K.Ishwarya, S.Saraswathi AND Mr. PRABAKARAN KASINATHAN

Title : Plant Leaf Classification Using a Compact Deep Learning Model Use of VGG-16

Volume/Issue : 2024;06(01)

Page No : 1-5

Alzheimer’s Disease is a leading cause of damage or loss of nerve cells and their connection in the brain. Depending on the area of the brain that is damaged, it can affect people differently and cause different symptoms. There is no cure for this disease, although treatments are available that may improve some symptoms. Symptoms of this disease depend on the stage of the disease, they usually develop slowly and get worse over time, becoming severe enough to interfere with daily tasks. An android application has been proposed that provides various tests in the form of levels of a game to detect whether a person suffers from Alzheimer’s disease or not and also tells them the stage of the disease i.e. Mild, Moderate, Severe which helps to track the status of the patient. The main intention of this application is to make the player feel like the person is not being tested but rather is playing a game full of fun and excitement. At the same time, the application determines the ability to remember everyday things. People who have Alzheimer's are characterized as having problems with their cognitive functions, memory loss, and personality changes that affect large areas of brain certainty.

Keywords : Mobile Application, Alzheimer’s Disease, Cognitive Functions

Author : Aruna Rao S L, K. Sanjana Reddy, M. Deepthi Sharvani, R. Rajani and K.Aarthi

Title : GAMING APPLICATION FOR ALZHEIMER DISEASE DETECTION

Volume/Issue : 2024;06(01)

Page No : 6-11

A blockchain is a revolutionary system that connects computer networks in a decentralized and distributed manner. Blockchain allows the process of current transactions to be peer-topeer (P2P) without relying on a single server. Once entered, information can never be erased. The blockchain contains a certain and verifiable record of every single transaction ever made. This study evaluated the development of research publications in the implementation process and future trend of Blockchain Technology. Private blockchains are often referred to as 'permissioned' blockchains. Unlike public blockchains, where anyone can download the software, form a node, view the ledger and interact with the blockchain, private blockchains are often run and operated by an entity (the "trusted intermediary"). As the trusted intermediary is in charge of the running of the blockchain it will control who can access the private blockchain and may also control the type of access rights each participant has. For example, some participants may be restricted to viewing (some or all of) the data on the ledger , whereas others may also have permission to submit new transactions for recording on the blockchain. The aim of this study is to analize the characteristics of private blockchain.Blockchain, database, technology, private

Keywords : Blockchain, database, technology, private

Author : Iskandar Muda, Gioia Amone, Normah Omar, Noor Marini Haji Abdullah, Cristine Youvira, Cherry, Malinda Sari Sembiring and Windi Astuti

Title : WHAT IS TYPE OF BLOCKCHAIN? AND HOW TO RELEVANT IN PRIVATE SECTOR?

Volume/Issue : 2024;06(01)

Page No : 12-16

The article aims to find out how blockchain accounting on ifrs and psak. Research USES secondary sources of documentation, notulency, previous observations and research. The study aims to deepen the theoretical study of how blockchain accounting on ifrs and psak. Blockchain is a decentralized system, where there is no centralized person or institution that regulates it. Blockchain technology is considered to be a very secure technology. In addition to being permanently compiled based on historical transactions, the level of security of information spread in this technology is also protected by cryptographic technology. Based on IFRS (Financial Reporting Standards) and PSAK (Financial Accounting Standards) there is no prior or current accounting treatment regarding Crypto Currency transactions. Cryptocurrencies are difficult to obtain accounting treatment for in Indonesia because they do not meet the definition of cash, intangible assets, according to this study.

Keywords : Blockchain, Cryptocurrency, IFRS, PSAK

Author : Iskandar Muda, Gioia Amone, Normah Omar, Noor Marini Haji Abdullah, Cristine Youvira, Cherry, Malinda Sari Sembiring and Windi Astuti

Title : HOW BLOCKCHAIN ACCOUNTING ON IFRS AND PSAK?

Volume/Issue : 2024;06(01)

Page No : 17-21

The project entitle “IOT Based Safety Gadget For Child Safety Monitoring & Notification” is developing a gadget which can be tracked via its GPS locations and also a panic button on gadget is provided to alert the parent via GSM module calling for help. Parental android app is developed to manage and track the device anytime. Smart gadget device is always connected to parental phone which can receive and make phone calls and also receive SMS on gadget via GSM module, also a wireless technology is implemented on device which is useful to bound the device within a region of monitoring range, if devices moving out of monitoring range, then an alert will be triggered on binding gadget, this helps you keep a virtual eye on child. Health monitoring system on gadget checking for parameters like heart beat/pulse rate and temperature is included which can be monitored on parental app. Gadget also monitors whether it is plugged on hand or not using contact switch and alert the parent as soon as it is unplugged

Keywords :

Author : S.Karkulazhi and D. Balakrishnan

Title : IOT BASED SAFETY GADGET FOR CHILD SAFETY MONITORING &NOTIFICATION

Volume/Issue : 2024;06(01)

Page No : 22 - 29

Recent days an unprecedented increase in cyber- attacks is seen globally. There are several cyber-bullied victims that commit suicide every year consequence of their sensitive information being publicized. The victims who are being bullied or blackmailed need mental support and guidance on how to react. And some of the victims due to defamation may go as far as taking their lives. So we’ve built an AI chat-bot specifically for cyber bully victims as they may not directly plea for human help. Conversing with bots might seem secure and reassuring than to have a conversation with humans as bots maintain secrecy. The bot comprehends user's query and responds accordingly using Natural language Processing (NLP) and Natural language understanding (NLU), which mainly includes three features such as providing guidance on how to approach concerned authorities, providing information regarding cyber bullying as well as mental health and also assisting their mental health. We integrated our chatbot into a website which is created using html, css and javascript and then deployed it locally.

Keywords : Cyber-Crime, Victim Mental Health Support, Chat Bot, Natural Language Understanding, Natural Language Processing, Botpress, Brainshop.AI

Author : Y. Naga Himaja, G. Anuradha, V. Lalitha Nagaveni and M. Pravardhitha

Title : An AI based mental health support chat-bot for cyber bullied victims

Volume/Issue : 2024;06(01)

Page No : 30 -37

Yamuna River Delhi stretch is a severely polluted reach with dissolved oxygen concentration below the detected limit almost the entire length with a higher concentration of oxygen-demanding substances. This stretch needs a management tool to predict the conditions and management of the river with the contributing load. QUAL2Kw is used to simulate the parameter DO. The framework has been calibrated and validated for the secondary data of February data of 1999-2006 and 2007-2009 respectively. DO prediction was done by keeping BOD and COD for all outfalling drains 10 mg/l and 50 mg/l as the effluent standard set for this reach. The scenarios have been developed changing the upstream flow. With the fixed pollutant load, it was observed that if the flow is increased by 50 cumecs of the minimum suggested flow, the reach could not attain the required minimum DO concentration.

Keywords : Dissolved Oxygen, Water Quality Model, QUAL2Kw, Urban river reach, Biochemical Oxygen Demand

Author : Nibedita Verma, Dr. Geeta Singh and Prof. Naved Ahsan

Title : DO Modeling for the Yamuna River, Delhi

Volume/Issue : 2024;06(01)

Page No : 38-42

In recent years, it has become vita to construct energy-efficient buildings. Maintaining a good quality of life while simultaneously lowering the building's energy requirements has been and will continue to be one of the most difficult challenges. Due to its large population, India's business and residential sectors account for around 30% of the country's overall power usage. Thus, the goal is to develop a plan to cut down on greenhouse gas emissions and energy consumption in buildings. An emerging innovation in the building industry is translucent concrete. It's a plan to switch commercial buildings over to using green energy. Light-Transmitting Concrete (LTC) has the potential to transform the inside of a concrete structure from darkish, boring, and greyish to bright, open, and expansive by letting natural light in through the building's outside walls. Using it may deplete energy usage in buildings by a significant amount, which is great for the environment and the economy. In this experimental study, LTC is developed by inducing 4% or 5% of optical fibre by volume in concrete mix and also to investigate the mechanical and optical properties of translucent concrete by the inclusion of 0.75mm diameter plastic optical fibre with three different densities in a cement mortar cube and incorporating Alccofine for cement replacement. The perpendicularly drilled holes on the two opposing faces of the moulding were used to weave the optical fibre. As a lighttransmitting component in the current work, a plastic optical fibre with a 0.75mm diameter and three distinct densities—5x5, 6x6, and 7x7—is used. According to this study, the compression resistance is influenced by the amount of plastic optical fibre utilised. Between 7x7 and 6x6 ( number of fibre strand in a surface area of 351896 mm2), the ideal density for 0.75mm diameter fibre to be employed in translucent mortar sample, was discovered. The 5x5 fibre density specimen, which at 28 days of age was approximately 59.93% more dense than the 5x5 density specimen, provides the strength. Above this fibre density, the additional fibre content resulted in a loss of strength and may have increased the amount of voids or gaps within the concrete sample. Despite its humble beginnings, long-term care has recently garnered widespread support among academics, and researchers have also tried to provide answers to long-term carerelated concerns through scientific research.

Keywords : Translucent concrete, optical Fibre, luminance, compressive strength

Author : R.Harshani, S.Sona, M.Ragu, R.Padma Rani, and S.DharmaSankar

Title : A study on Performance of Luminance and strength characteristics of High Strength Translucent concrete

Volume/Issue : 2024;06(01)

Page No : 63 -67

Several approaches have been proposed in the published and existing scientific literature to assist farmers decrease the possibility of human error, but these approaches are expensive to execute since they rely on sensors and imagecapturing equipment. Machine Learning's (ML) subfield of Deep Learning (DL) has changed the course of study toward how to classify epidemics. DL systems have very great potential for accurately identifying grape leaf diseases. In this work, we studied and analyzed different existing approaches that accurately identify grape leaf diseases. The biggest challenge of the current research is to examine and evaluate ML and DL methodologies that can effectively analyze grape plant diseases using leaf images. Leaves are considered reliable indicators of plant health, and this research aims to address the urgent national concern of enhancing agricultural productivity. The emergence of computerized identification and categorization of disease technologies for grape trees is still in its infancy, according to analysts. Farmers need new, better systems for identifying and classifying grape plant leaf ailments to avoid financial catastrophe and increase fruit harvest. This study presents a thorough systematic analysis of DL and ML techniques for identifying grape leaf disease. This study is expected to be useful for the field of agricultural disease research in the early detection and management of illnesses affecting grape leaves.

Keywords : Grape Leaves, Pesticides, Pests, Profit, Disease Analysis, Leaf Diseases

Author : N Saikiran, P Kiran, D Ashok, P Anuradha and D Divya Kalpana

Title : A Comprehensive Overview of Deep Learning and Machine Learning for Grape Leaf Disease Recognition

Volume/Issue : 2024;06(01)

Page No : 68 - 73

The concrete structures do not have much capability to withstand impact loads for a longer period. The sudden impact loads acting on concrete structures affect the structural integrity, which lowers the member's stiffness capacity and reduces the structure's service life. The service life of concrete structures directly depends on the stress level, stress range, and intensity of loading. In India, problems due to impact loading are frequently encountered in structure like airport pavements, Highways, railways, bridges, road pavements and highspeed wind turbines. The addition of tyre waste crumb rubber (TWCR) to polymer-modified concrete improves the ductility and toughness performance of the concrete. In this experimental study, tyre waste crumb rubber is used as an alternative sustainable material that partially replaces the fine aggregate in the concrete mixture. Also, for additional support against the strength, a fixed percentage of silica fume is to be used. Tyre waste is one of the predominant wastes that is produced on earth day by day. The National Green Tribunal says that 2,75,000 tyres were discarded daily in India. Disposing of tyre waste causes health, economic, and environmental risks through air, water, and soil pollution. Hence, the problem may be reduced by using it as an alternate aterial in concrete

Keywords : Crumb rubber, silica fume, Paver block, fine aggregate, sustainable

Author : S.Sona, R.Harshani, S.Shalini, A.S.Pranav and T.Dhrowshika Viji

Title : Study on Mechanical Properties of Polymer-Modified Interlocking Paver Block using crumb rubber and silica fume

Volume/Issue : 2024;06(01)

Page No : 74 -79

Fake news has become a significant concern in today's digital age, as it can easily mislead and deceive people. One of the fundamental steps to combat fake news is through fake news detection. In recent years, research has focused on developing effective techniques for detecting fake news using Natural Language Processing. It further affects their emotions and cultural values, creating a tense among people, and instigating anger against fellow people or the government. This further changes the order in society causing hate speeches, riots, strikes, or even fatal accidents that affect innocent lives. When situations like these affect society, it’s wise that we utilize the necessary technologies in aid to eliminate this kind of issue. One such tech that’s disrupting human language processing is Natural Language Processing (NLP) which processes information like text, audio, etc. between languages and text, and audio formats. Leveraging this technology to process the text and analyze the motive and sentiment could shed light on the reliability of the trueness of the text. As a result of this, we could develop a fake news detection system using NLP. To develop such a system, we have to train the machine learning model with an existing dataset. Based on the knowledge gained from this training, the model would be able to identify a pattern in the test data we give. Here, training the model plays an important role as it affects the accuracy of the model in giving the final output. This model can be evaluated by testing it with real and fake news articles. We can develop a better understanding of how to detect fake news from the result generated by the model and we can fine-tune it in order to attain a higher accuracy level. These developed accuracy models can be used by others for various purposes in NLP to build better adapting models that make the life of humans easier.

Keywords : Fake News, Natural Language Processing, Machine Learning, detection.

Author : Tarun Kumar

Title : DETECTING FAKE NEWS WITH LSTM: A DEEP LEARNING APPROACH

Volume/Issue : 2024;06(01)

Page No : 80 -95