The automobile industry is continuously evolving toward enhanced maneuverability, safety, and driving comfort. This project focuses on the fabrication of a 360-degree vehicle utilizing a four-wheel steering (4WS) system, designed to improve vehicle control and reduce turning radius in confined spaces. In the proposed design, all four wheels can be steered independently, allowing the vehicle to move not only forward and backward but also sideways and diagonally, achieving complete 360-degree movement. This system integrates mechanical linkages, servo motors, and an electronic control unit to coordinate wheel angles and directions accurately. The implementation of the four-wheel steering mechanism significantly enhances parking efficiency, cornering stability, and overall mobility, especially in urban environments. The project demonstrates that by employing an advanced steering mechanism and precise control logic, a conventional vehicle can be transformed into a highly maneuverable system suitable for next-generation transportation needs.

Keywords : Four-Wheel Steering (4WS), 360-Degree Vehicle, Vehicle Control, Maneuverability, Automotive Design, Steering Mechanism

Authors : M. Naga Kiran

Title : Fabrication of 360 Degrees Vehicle for a Four Wheel Streeing System a Car

Volume/Issue : 2019;1(1 (November - December))

Page No : 29 - 33

The exponential growth of social media platforms has generated massive amounts of unstructured text data, offering valuable insights into public opinion, trends, and behaviors. Text mining, when integrated with big data analytics, provides a powerful approach to process, analyze, and extract meaningful information from social media comments. This review paper focuses on various text mining techniques—such as sentiment analysis, topic modeling, and opinion extraction—applied to large-scale social media datasets. The study explores the role of big data frameworks like Hadoop and Spark in handling high-volume, high-velocity data efficiently. Additionally, it highlights preprocessing methods including tokenization, stop-word removal, and feature selection, which are critical for improving model accuracy. The paper also discusses challenges such as data noise, language ambiguity, scalability, and privacy concerns. Overall, this review emphasizes how big data-driven text mining can support decision-making in domains such as marketing, politics, and public health by uncovering patterns and sentiments hidden within social media interactions.

Keywords : Text Mining, Social Media Analytics, Big Data, Sentiment Analysis, Opinion Mining, Data Processing

Authors : P J V G PRAKASA RAO

Title : Review on Text Mining based on Social Media Comments using Big Data Analytics

Volume/Issue : 2019;1(1 (November - December))

Page No : 20 - 23

Wireless Sensor Networks (WSNs) are widely used in environmental monitoring, military surveillance, healthcare, and smart cities. However, due to their distributed nature and limited resources, WSNs are highly vulnerable to various security threats, especially forwarding attacks, where malicious nodes selectively drop or alter data packets to disrupt communication. This paper proposes an efficient method for identifying forwarding attacks using multiple resources, such as node reputation, energy consumption, transmission delay, and packet delivery ratio. By integrating these parameters, the system can accurately detect abnormal behaviors and isolate compromised nodes without significantly affecting network performance. The proposed approach enhances the reliability, security, and lifetime of the network while maintaining low computational overhead. Simulation results demonstrate that the multi-resource detection model provides better accuracy and faster response compared to conventional trust-based or single-parameter techniques. This method contributes to building a more secure and resilient WSN infrastructure for critical real-time applications.

Keywords : Wireless Sensor Networks (WSN), Forwarding Attacks, Network Security, Multi-Resource Detection, Node Trust, Intrusion Detection

Authors : K.S.N.V Someswara Rao

Title : Indentifying Forwarding Attacks in wireless Sensor Networks using Muliple Resources

Volume/Issue : 2019;1(1 (November - December))

Page No : 25 - 28

Medical image segmentation is a crucial step in computer-aided diagnosis, treatment planning, and biomedical image analysis. This paper presents a segmentation approach based on Weighted Identification Level Set Evolution (WILSE), which effectively integrates local edge features to improve boundary detection and region accuracy. Traditional segmentation methods often struggle with noise, weak boundaries, and intensity inhomogeneity in medical images. The proposed method overcomes these challenges by assigning adaptive weights to local image features, enhancing the sensitivity of the level set function to significant edges while suppressing irrelevant noise. The model evolves iteratively to refine object boundaries and achieve precise delineation of anatomical structures. Experimental results on various medical imaging modalities such as MRI, CT, and ultrasound demonstrate that the WILSE approach provides superior segmentation accuracy, robustness, and computational efficiency compared to conventional edge-based or region-based methods. This technique shows promising potential for clinical applications where high-precision segmentation is essential for diagnosis and quantitative analysis.

Keywords : Medical Image Segmentation, Level Set Evolution, Local Edge Features, Weighted Identification, Image Processing, Biomedical Imaging

Authors : Nirmal Jyocee

Title : Medical Image Segementation using Weighted Identification Level Set Evolution based on Local Edge Features

Volume/Issue : 2019;1(1 (November - December))

Page No : 15 -19

The rapid advancement of the Internet of Things (IoT) has revolutionized traditional agricultural practices by enabling real-time monitoring, automation, and data-driven decision-making. Smart agriculture integrates IoT-based technologies such as sensors, wireless communication, and cloud computing to enhance productivity, resource management, and sustainability in farming. IoT devices collect data on soil moisture, temperature, humidity, and crop health, allowing farmers to make informed decisions and optimize irrigation, fertilization, and pest control. The use of automated systems and predictive analytics further supports precision agriculture, reducing resource wastage and operational costs. Cloud-based platforms enable seamless data storage and remote access, improving efficiency and scalability across large agricultural fields. Additionally, IoT integration promotes sustainable farming by minimizing environmental impact and maximizing yield quality. This paper provides an overview of IoT applications in agriculture, highlighting the benefits, challenges, and future potential of smart farming systems in transforming the agricultural sector.

Keywords : Internet of Things (IoT), Smart Agriculture, Precision Farming, Sensor Networks, Data Analytics, Sustainable Farming

Authors : Bosubabu Sambana

Title : Smart Agriculture using Internet of Things

Volume/Issue : 2019;1(1 (November - December))

Page No : 9 - 14

Cryogenics is the branch of science that deals with the production, behavior, and application of materials at extremely low temperatures, typically below –150°C. A cryogenic system consists of essential components such as cryocoolers, storage vessels, transfer lines, and insulation systems, all designed to maintain and control low-temperature environments efficiently. These systems play a vital role in various scientific, industrial, and medical applications. In engineering, cryogenics is used in the liquefaction and storage of gases like oxygen, nitrogen, and hydrogen. In the medical field, cryogenic techniques are employed for cryosurgery, biological sample preservation, and medical imaging technologies such as MRI. Furthermore, cryogenic systems are integral to space exploration, superconductivity research, and particle accelerators, where maintaining ultra-low temperatures is crucial for performance and stability. Advancements in materials and refrigeration technologies continue to improve efficiency and safety in cryogenic operations. This overview highlights the fundamental principles, components, and wide-ranging applications of cryogenic systems in modern science and technology.

Keywords : Cryogenics, Low Temperature, Cryogenic System, Liquefied Gases, Superconductivity, Space Applications

Authors : Viruty Sridhar Patnaik

Title : An Overview of Cryogenic System and Applications

Volume/Issue : 2019;1(1 (November - December))

Page No : 5 - 8

The rapid growth of digital education has led to increased demand for scalable and flexible learning solutions. This paper presents an automatic e-learning platform powered by cloud computing, designed to enhance accessibility, efficiency, and personalization in online education. The proposed system leverages cloud-based infrastructure to manage educational resources, support real-time collaboration, and deliver adaptive learning experiences to users regardless of location or device. By integrating automation technologies such as machine learning and data analytics, the platform can assess learner performance, recommend suitable learning materials, and optimize content delivery dynamically. Cloud computing ensures cost-effective deployment, high availability, and elastic scalability, enabling institutions to handle varying user loads efficiently. Additionally, data security and privacy are maintained through cloud-based encryption and access control mechanisms. This approach not only reduces infrastructure costs but also simplifies system maintenance and updates. Overall, the automatic e-learning platform through cloud computing represents a significant advancement toward intelligent, inclusive, and sustainable digital education.

Keywords : Cloud Computing, E-Learning Platform, Automation, Adaptive Learning, Scalability,Data Security

Authors : MOLLI SRINIVASA RAO

Title : Automatic e-Learing platform through Cloud Computing

Volume/Issue : 2019;1(1 (November - December))

Page No : 1 - 4