Computation of Parity Check Matrices for Binary EG-LDPC Codes used in Communication Systems

Abstract The Low Density Parity Check (LDPC) are direct codes, which are true block and Shannon Limit codes. These codes are attained least error floors of data bits for data transfer applications used in communication systems. However, the proposed LDPC codes are more beneficial than Turbo codes because of reduction in the decoding complexity and […]

Switching Party and Anti-Defection Law: Implementation and Impact on Democracy in Indonesia

Abstract This analysis purposes to provide an overview of the legal framework regarding the transfer of membership of political parties in Indonesia and its impact on the realm of democracy. This study uses qualitative-normative research methods by examining library materials or secondary data, as well as primary and secondary legal materials. The study uses the […]

Socio-Psychological Factors of Preferences Regarding Socio-Economic and Socio-Political Activity of the Russian Provincial Youth

Abstract The urgency of the problem lies in the need to analyse socio-psychological determinants of young people’s economic and political activity preferences. The purpose of the study is to investigate the directions of the relationships between preference of socio-economic and socio-political activity among young people and satisfaction of basic needs, riskiness, preference for sources of […]

Classifying Unbalanced Datasets Using Iterative Fuzzy Support Vector Machine

Abstract In real world applications, training the classifier using unbalanced dataset is the major problem, as it decreases the performance of Machine Learning algorithms. Unbalanced dataset can be prominently classified based on Support Vector Machine (SVM) which uses Kernel technique to find decision boundary. High Dimensionality and uneven distribution of data has a significant impact […]

A Review of Machine Learning Models for Predicting Autism Spectrum Disorder

Abstract Autism spectrum disorder (ASD) is a neurological and developmental disorder that impacts the behavior of the person throughout a life. Every individual with ASD exhibits the difficulty in communication and social interaction with restricted interests and repetitive behaviors. There is no standard diagnosis and treatment for ASD. The social behavior of the children can […]

A Revisit to Classification Algorithms

Abstract Artificial Intelligence is the term often heard in the field of technology over the past few years. The vision of this paper is to provide a keen understanding about three Classification techniques for Machine Learning. They are Decision trees, Naive Bayes algorithm and Support Vector Machines. The foundation for this paper is based on […]

A Novel Approach of Association Rule Hiding Using DBCT (Distortion, Blocking and Cryptographic Technique)

Abstract Associative rule hiding is a technique used in hiding sensitive data, during data processing to secure the sensitive association rules generated using association rule mining. Several methods were planned within the literature for hiding sensitive data items. Few apply distributed databases across various sites, few indulged data perturbation, and few utilized clustering and few […]

Prediction of Neurological Disorders among Children Using Machine Learning Techniques

Abstract Diagnosis of neurological problems in children at the earliest helps the medical associates to improve the children’s health conditions. Hence, there is an important need to diagnose neurological disorders that occur which may lead to critical problems if care is not taken in advance. Machine learning Techniques helps for analyzing medical data and the […]