B.L.D.E.A's V.P. Dr. P.G. Halakatti College of Engineering and Technology

In the digital documentation identity era documents are most commonly shared and used for the authentication of the identity of a person. The various tools are used to create or produce fake identity documents. In the current scenario identification of forged or tampered document is the challenging task. In this paper, we proposed an identity document forgery detection technique with the help of the Haralick texture feature. The proposed system is organized into two sections document digitization and document verification. In the document digitization section first, convert the document image into binary and locate the template header and footer part. Eliminate the header and footer of the original image Then convert to gray level co-occurrence matrix (GLCM). The Haralick texture attributes are fetched from each block, find the sum and if it is greater than 0 then store it to the knowledge base. In the document verification section locate the header and footer template from the verification image after converting it to binary then convert to GLCM. The sum of Haralick texture features are calculated and predicted using probabilistic neural network (PNN). Finally based on the maximum occurrence of the blocks and the percentage of occurrence will display whether the document is original or forged. The result of the proposed system shows that it gives good accuracy as compared with the other systems.

Digital technology adoption for health monitoring has become essential in the quickly changing agricultural landscape. In order to protect sensitive data that is gathered from a variety of sources, including drones, sensors, and satellites, this chapter examines the crucial role that secure image transmission plays in agricultural health monitoring. In order to preserve data integrity and guarantee that agricultural stakeholders receive timely and accurate information for efficient decision-making, secure transmission techniques such as encryption and end-to-end protocols are crucial. This chapter outlines the many advantages of secure image transmission, such as improved data integrity, prompt decision-making, heightened stakeholder trust, and defense against cyberattacks. Strong security measures are also required for compliance with data privacy regulations and efficient resource management as agricultural data becomes more digitalized.

The speech-disabled people are facing difficulties in having normal communication with the world. Communication is the only means by which people with speech impairments can share their thoughts and communicate with others. However, there are several difficulties in communicating with a person who is speech challenged. With the development of wearable technology, it is now possible to put many innovative ideas into practice and benefit humanity in previously unimaginable ways. The previous work was done to develop sensors and a sign language translator as a wearable or assistive device. In order to aid such people, the hand-talking system is proposed in the present work as a wearable electronic device for speech-impaired people. The work consists of simple and friendly communication with speech-impaired people. This is achieved by developing a suitable sign language translator using gestures. The gestures are traced with the help of suitable sensors and accelerometers, which are later converted into recognizable text or speech. The goal of the current work is to develop an assistive device for identifying gesture-based communication that helps normal people and speech-impaired people communicate. The glove will function as a gesture-to-text translator. With the aid of appropriate sensors and accelerometers, gestures are tracked in sign language that can be easily translated into acceptable text or voice.

In recent years, growth in AI technologies has influenced Agile software development lifecycles with AI-powered code generators. The following concept is essential because code generators based on AI have the potential to improve the efficiency, accuracy, and speed of Agile software testing procedures. Although there is little research on the utilization of AI-powered code generators for Agile software testing, little information is known on this topic. Greater amounts of professional literature should cover the use of code generators for Agile software testing, with more focus on the disadvantages and benefits of their usage. This chapter will try to fill the information gap on this topic by thoroughly investigating the impact of AI-powered code generators on the Agile software testing life cycle. Specifically, the current chapter will try to identify the threats associated with their use and determine whether this technology supports or complicates the Agile testing life cycle.

Acetylcholinesterase enzyme, which is responsible for the breakdown of acetylcholine, is a key therapeutic target to cure the Alzheimer Disease(AD). Whenever this enzyme is blocked, there is more acetylcholine accessible in the synaptic knob for utilisation, improving cognition and memory. The objective of the current effort is to develop machine learning methods for differentiating among AChE inhibitors and non-inhibitors. Inhibiting AChE activity helps treat AD by raising acetylcholine levels, which facilitate better communication between brain cells. Dataset is collected using ChemBL database and the same contains around 5905 bioactivity molecules. The data contains 3 classes [active, inactive and intermediate] and is pre-processed for handling missing data and handling duplicate values and further used in generation of Lipinski’s descriptors or rules for applying Exploratory Data Analysis(EDA) and to get target feature for model building. Models are built using Random Forest regression technique which gives 87.8