{"title":"Problems from the Past, Problems from the Future, and Data Science Solutions","authors":"M. Pasupuleti","doi":"10.18034/abcjar.v4i2.614","DOIUrl":"https://doi.org/10.18034/abcjar.v4i2.614","url":null,"abstract":"According to the findings of this study, the usual workday for a Data Scientist varies based on the sort of project on which they are working at the time. In order to extract insights from data, a variety of algorithms are employed. Because Data Scientists can access algorithms, tools, and data over the Cloud, they can keep up to date and collaborate more readily than ever before.","PeriodicalId":130992,"journal":{"name":"ABC Journal of Advanced Research","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132664432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integrated Reasoning Engine for Code Clone Detection","authors":"N. Bynagari","doi":"10.18034/abcjar.v3i2.575","DOIUrl":"https://doi.org/10.18034/abcjar.v3i2.575","url":null,"abstract":"This article seeks to foray into the nitty-gritty of integrated reasoning for code clone detection and how it is effectively carried out, given the amount of analytics usually associated with such activities. Detection of codes requires high-pitch familiarity with cloning systems and their workings. Hence, discovering similar code segments that are often regarded and seen as code imitations (clone) is not an easy responsibility. More especially, this very detection process might possess key purposes in the context of susceptibility findings, refactoring, and imitation detecting. Through the voyage of discovery this article intends to expose you to, you will realize that identical code segments, more often than not described as code clones, appear to be a serious duty, especially for large code bases <1; 2; 3; 4>. There are certain approaches and deep technicalities that this sort of detection is known for. Still, from the avalanche of resources that formed the bedrock of this article, one would discover the easiest formula to adopt in maneuvering such strenuous issues.","PeriodicalId":130992,"journal":{"name":"ABC Journal of Advanced Research","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125586392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Relationship between Bank Specific Characteristics and the Extent of Disclosure: Evidence from the Banking Sector in Bangladesh","authors":"S. Saha, Taposh Kumar Neogy","doi":"10.18034/abcjar.v10i2.589","DOIUrl":"https://doi.org/10.18034/abcjar.v10i2.589","url":null,"abstract":"The fundamental motive of this study is to inspect the extent of disclosure of the banking companies in Bangladesh. To calculate the disclosure score of each sample bank, the un-weighted disclosure index has been used. To reveal the findings of this study, researchers have considered five conventional private commercial banks. A period of five years ranging from 2013 to 2017 has been selected for the study. Data have been collected from secondary sources and different statistical techniques like descriptive statistics as well as regression analysis with the respective models have been employed. The study reveals that the average disclosures scores of the sample banks are at a satisfactory level and the significant variation doesn’t exist in the disclosure scores among the sample banks. Multiple regression analysis has been conducted to know whether the significant relationship is available between the extent of disclosure and the specific characteristics of banks and the evidence confirm that the significant relationship is existing between the extent of disclosure and earnings per share, return on assets as well as net profit but not between the disclosure scores and capital adequacy ratio, debt-equity ratio, current ratio, loan deposit ratio, market capitalization ratio as well as total assets. ","PeriodicalId":130992,"journal":{"name":"ABC Journal of Advanced Research","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117036598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of Artificial Neural Network to ANPR: An Overview","authors":"Harish Paruchuri","doi":"10.18034/abcjar.v4i2.549","DOIUrl":"https://doi.org/10.18034/abcjar.v4i2.549","url":null,"abstract":"Vehicle owner documentation and traffic flow mechanism have contributed to a major issue in each country. From time to time it turns out to be challenging to detect car owners who fault traffic regulations. Hence, it of interest to us to investigate designs for automatic number plate detection structure as a clarification and proffer solution to this issue. There are several automatic number plate detection or recognition structure existing today. The structure is according to diverse methods nonetheless automatic number plate recognition is still a difficult job as many of the parameters such as a fast-moving vehicle, non-uniform car number plate, the language used in writing the vehicle number and various lighting situations may hinder 100% detection rate. Many of the structure-function underneath these boundaries. This paper review diverse methods of automatic number plate recognition considering success rate, picture size, and processing time as factors. However, automatic number plate detection is recommended for traffic regulating agencies. \u0000 ","PeriodicalId":130992,"journal":{"name":"ABC Journal of Advanced Research","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132483561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bank Specific and Macroeconomic Determinants of Commercial Bank Performance in Bangladesh","authors":"S. Bony","doi":"10.18034/abcjar.v10i2.591","DOIUrl":"https://doi.org/10.18034/abcjar.v10i2.591","url":null,"abstract":"The main purpose of this study is to examine the impacts of bank-specific and macroeconomic factors on the commercial bank performance measures (ROA, NIM, and ROE in this case) in Bangladesh. The study identifies bank-specific characteristics and macroeconomic determinants of performance in Bangladesh’s banking sector over the years 2009 to 2018. The study uses relevant data from a sample of 10 commercial banks in Bangladesh. The determinants are identified by using correlation and regression analysis. This finding serves as an indicator that the bank-specific and macroeconomic variables selected for this study provide a better description of ROA rather than net interest margin (NIM) and ROE. Among all the bank-specific determinants board size, audit committee meetings, and foreign ownership have a positive relationship with the bank’s performance. Specifically, inflation and GDP are observed to have a positive relationship with bank performance. The findings of this research can be of great help to a wide range of entities such as academicians, bankers, the government, students, and investors. This study can be helpful to bank management by providing valuable information thus assisting in the construction of efficient management policy decisions in order to ensure higher profits.","PeriodicalId":130992,"journal":{"name":"ABC Journal of Advanced Research","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122185578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Sample-based Criterion for Unsupervised Learning of Complex Models beyond Maximum Likelihood and Density Estimation","authors":"Mani Manavalan, Praveen Kumar Donepudi","doi":"10.18034/abcjar.v5i2.581","DOIUrl":"https://doi.org/10.18034/abcjar.v5i2.581","url":null,"abstract":"Many unsupervised learning processes have the purpose of aligning two probability distributions. Recoding models like ICA and projection pursuit, as well as generative models like Gaussian mixtures and Boltzmann machines, can be seen in this perspective. For these types of models, we offer a new sample-based error measure that can be used even when maximum likelihood (ML) and probability density estimation-based formulations can't be used, such as when the posteriors are nonlinear or intractable. Furthermore, the challenges of approximating a density function are avoided by our sample-based error measure. We show that with an unconstrained model, (1) our technique converges on the correct solution as the number of samples increases to infinity, and (2) our approach's predicted answer in the generative framework is the ML solution. Finally, simulations of linear and nonlinear models on mixtures of Gaussians and ICA issues are used to evaluate our approach. Our method's applicability and generality are demonstrated by the experiments. \u0000 ","PeriodicalId":130992,"journal":{"name":"ABC Journal of Advanced Research","volume":"22 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134559454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Speech Emotion Recognition Using Deep Learning Techniques","authors":"Apoorva Ganapathy","doi":"10.18034/abcjar.v5i2.550","DOIUrl":"https://doi.org/10.18034/abcjar.v5i2.550","url":null,"abstract":"The developments in neural systems and the high demand requirement for exact and close actual Speech Emotion Recognition in human-computer interfaces mark it compulsory to liken existing methods and datasets in speech emotion detection to accomplish practicable clarifications and a securer comprehension of this unrestricted issue. The present investigation assessed deep learning methods for speech emotion detection with accessible datasets, tracked by predictable machine learning methods for SER. Finally, we present-day a multi-aspect assessment between concrete neural network methods in SER. The objective of this investigation is to deliver a review of the area of distinct SER.","PeriodicalId":130992,"journal":{"name":"ABC Journal of Advanced Research","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129634279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}