International Journal on Recent and Innovation Trends in Computing and Communication
Not a member yet
8613 research outputs found
Sort by
A Hybrid Probabilistic Privacy Preserving Based Community Detection Model on Online Social Networking Data
Get PDFPrivacy preserving plays a vital role on the online social networking sites due to high dimensionality and data size. Community detection is used to find the social relationships among the node edges and links. However, most of the conventional models are difficult to process the community structure detection due to high computational time and memory. Also, these models require contextual weighted nodes information for privacy preserving process. In order to overcome these issues, an advanced probabilistic weighted based community detection and privacy preserving framework is developed on the large social networking data. In this model, a filter based probabilistic model is developed to remove the sparse values and to find the weighted community detection nodes and its profiles for privacy preserving process. Experimental results show that the filter based probabilistic community detection framework has better efficiency in terms of normalized mutual information, Q, rand index and runtime (ms)
Virtual Eye – Revolutionizing Vision Assistance For People With Disabilities
Get PDFVisually challenged individuals have faced numerous challenges in their daily lives. These challenges include: Visually challenged individuals have difficulty reading printed materials, including books, magazines, and newspapers. This limitation can significantly impact their education, as they may not have access to all the materials they need to learn. Moving around in unfamiliar places can be a daunting task for the visually impaired. They may struggle to access digital or printed materials, as these are often not available in accessible formats. It might be difficult for those who are blind to identify objects. This can be frustrating, especially in situations where they are alone and need to identify objects.
To address this issue, we are developing a mobile application for visually challenged individuals by providing a range of features such as text-to-speech, speech-to-text, image-to-audio, and PDF-to-audio. It enables visually challenged individuals to access information, read books, identify objects, communicate, and navigate with ease and independence. The app's user-friendly interface can be accessed both manually and by voice command, making it easy to use for people with varying levels of technical expertise. Overall, the Virtual Eye app helps visually challenged individuals lead more fulfilling and independent lives.
Overall, Virtual Eye application is an essential tool for visually challenged individuals, helping them navigate their daily lives with ease and independence. With this app, they can access information, communicate, and identify objects without the need for a third party, enhancing their quality of life and sense of autonomy
Quantum Computing Algorithms for Solving Complex Mathematical Problems
Get PDFThe power of quantum mechanics, that is too complex for conventional computers, can be solved by an innovative model of computing known as quantum computing. Quantum algorithms can provide exponential speedups for some types of problems, such as many difficult mathematical ones. In this paper, we review some of the most important quantum algorithms for hard mathematical problems. When factoring large numbers, Shor's algorithm is orders of magnitude faster than any other known classical algorithm. The Grover's algorithm, which searches unsorted databases much more quickly than conventional algorithms, is then discussed.  
BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts
Get PDFThe rapid growth and integration of the Internet of Things (IoT) emphasizes the crucial need for effective data governance. This research unveils a novel framework, capitalizing on blockchain and smart contracts, aimed at decentralizing data governance in the IoT sphere. Our approach allows stakeholders to formulate and enforce data governance collaboratively, ensuring a balance between transparency, adaptability, and flexibility. Using the Ethereum platform and Solidity as our smart contract language, we constructed a demonstrative proof-of-concept. Our comparative evaluations highlighted our system's superiority, outpacing previous works with a scalability score of 95%, flexibility at 90%, and an unmatched transparency score of 100%. This framework presents a transformative paradigm for organizations and individuals working with IoT data, offering an efficient, transparent, and robust data governance mechanism
An Optimal Deep Learning Model With Effective Feature Learning Mechanism For Stock Market Prediction
Get PDFThe stock market has considered the active research fields today, and forecasting its behaviour is an enormous necessity. Predicting the stock market is complex, necessitating a thorough examination of data patterns. Correct forecasting outcomes can provide significant insight to investors, lowering investment risk. This paper proposes a novel Weight and Bias Tuned Long Short-term Memory (WBTLSTM) with an efficient feature extraction model, Bilateral ReLU-based Two-Dimensional Convolutional Neural Network (BR2DCNN), for stock price prediction (SPP). First, the stock data was collected from the publicly available dataset. Then the missing values imputation and data normalization is performed on the collected dataset. The preprocessed dataset extracts the most relevant features using BR2DCNN. Finally, the future stock events are predicted using the WBTLSTM. The weights and biases are tuned with the help of the Enhanced Butterfly Optimization Algorithm (EBOA). Experimental findings prove that the proposed one achieves superior outcomes compared to the conventional methods regarding some performance metrics
Irregularity Behaviour Detection - Ad-hoc On-Demand Distance Vector Routing Protocol (IBD - AODV): A Novel Method for Determining Unusual Behaviour in Mobile Ad-hoc Networks (MANET)
Get PDFAll the communication in the mobile ad-hoc network (MANET) will depend on the intermediate neighbour nodes or router nodes. Routing protocol is very important in MANET, because all the communication will be done in the MANET depending on the neighbour or intermediate node. If the intermediate node is a malicious node, all the data will be lost or changed by the intermediate or malicious node. Ad-hoc On-demand Distance Vector routing protocol is one of the moderate routing protocol in MANET. The Ad-hoc On-demand Distance Vector Routing protocol does not have any security mechanism. This work is going to find the Irregularity Behaviour Detection (IBD) over the Ad-hoc On-Demand Distance Vector Routing (AODV) protocol. IBD is finding a trusted node by using the trust value (TV) of the node. This TV includes network performance, node energy level, and node position value. IBD-AODV is implemented and tested in the OmNetpp 6.0 simulator
Hyperspectral Image Compression Using Prediction-based Band Reordering Technique
Get PDFThe hyperspectral image represents various spectral properties Because it consists of broad spectral information of ground materials that can be used for various applications, These images are collected as large amounts of data that must be processed and transmitted to the ground station. These acquired images contain redundant spectral information that has to be reduced in order to reduce transmission and storage capacity. This work focuses on preserving their quality while compressing them using band reordering techniques and prediction coding. This can be accomplished by preprocessing in which sub-bands are decomposed and bands are reordered into unsequenced compression can be accomplished through using the technique of linear prediction. The report discusses the Pavia University hyperspectral image data cube, which was acquired via a sensor known as a reflected optics system imaging spectrometer (ROSIS-3) over the city of Pavia, Italy
Improve the Onion Routing Performance and Security with Cryptographic Algorithms
Get PDFOnion Routing and Cryptographic Algorithms are two essential components of online privacy and secure data transmission. Onion Routing is a technique used to protect internet users' anonymity by routing their communication through a network of servers, while Cryptographic Algorithms are used to encrypt and decrypt data to ensure its confidentiality. As technology advances, there is a need to consider the development of new cryptographic algorithms for TOR to ensure its continued effectiveness. The combination of Onion Routing and Cryptographic Algorithms has proven to be an effective way to protect online privacy and security. This paper aims to explore the benefits of combining Onion Routing and Cryptographic Algorithms and to propose a hybrid symmetric and hashing algorithm technique to transmit data securely. By the end of this paper, researchers will have a comprehensive understanding of the Onion Routing and Cryptographic Algorithms, their implementation in TOR, and the limitations and risks associated with using such tools
Social and Institutional Analysis of the Sustainability of Fish Fishing Practices in the Tempe Flood (Case Study on Palawang Practices)
Get PDFOne form of fishing practice in Tempe Lake that still takes place today is palawang, which is a particular place on the edge of the lake whose boundaries have been determined to be controlled by using a splint, which is a fishing tool made of woven bamboo which is installed around it according to predetermined limits. This study aims to determine the potential sustainability of the palawang practice in terms of its social and institutional dimensions. The qualitative method used in this research uses the primary data collection instrument, namely interview guidelines. The results showed that the sustainability of palawang practices in Tempe Lake depends on the bonds of fishing traditions institutionalized through the Maccera Tappareng tradition as well as compliance with the rules set in the palawang practice from the time of the auction to the time of work starting with the installation of fishing aids until the completion of the fishing period in the palawang land area
Liver Cancer Segmentation through Enhanced Feature Extraction and Mapping using Improved Transfer Learning Techniques
Get PDFThe largest solid organ in the body is the liver. Numerous other vital functions it carries out include removing impurities from the blood flow, controlling blood coagulation, and maintaining healthy blood sugar levels. All blood leaving the intestines and stomach is directed to the liver as its final destination. Liver illness may be brought on by infections, inherited diseases, cancer, too many harmful substances, or other conditions. Medical experts estimate that 1.6% of men and women in India could be diagnosed with liver cancer at some time in their life. The interpretation of liver CT scans often involves semi-manual or manual techniques; however these techniques are costly, time-consuming, subjective, and prone to error. To improve the detection of liver cancer, these issues have been addressed and a number of computer algorithms have been developed. To create a fully automated method for quickly extracting liver tumours from CT scan images