International Journal of New Practices in Management and Engineering
Not a member yet
136 research outputs found
Sort by
Investigating Role of Deep Learning in Metaverse
Full text link
Avatars are computer-generated digital representations that people may use in the metaverse to communicate and interact with one another as well as with digital goods. Imagine a setting that combines elements of virtual reality, an online performance game, and the World Wide Web. In the modern world, one does not have the option of avoiding the usage of bitcoin. In this rapidly evolving hybrid setting, Bitcoin is the proper medium of exchange because of the inherent decentralisation it has. In addition to this, it is essential to integrate data compression and safety precautions. Compression is an area of study that is constantly undergoing new developments as well as technological leaps and bounds. This study looks on other aspects of the metaverse as well, such as data compression and security concerns related to the metaverse. Before training and testing the DL model, an image processing approach was included in order to reduce its size. This was done so that object identification may be improved even more.
 
Investigating Role of Data Mining in Software Engineering
Full text link
Companies that focus on software development produce vast volumes of data. Every stage of software development, from gathering requirements to ongoing upkeep, generates its own set of data. To better the software, efforts are undertaken to collect and store data produced in software repositories. Data mining techniques are used to the massive amounts of data found in software repositories in order to extract previously unseen patterns and insights. Researchers from the fields of Software Engineering and Data Mining have lately made this area of study a top priority. This research aims to examine the many uses of data mining in software engineering, the many types of software engineering data that can be mined, and the many data mining techniques that are available and have been used by researchers to solve the problems that this research focuses on. The next step is to use this classification to determine which subfield within software engineering has the highest scholarly interest.
 
A Study on the Impact of Sri Lankan Crisis on Kerala Tourism
Full text linkTourism is a major sector in the world that has a significant role in the economic development of various countries. Tourism sector also helps in the generation of employment opportunities. Sri Lanka and Kerala are two major tourist destinations in South Asia. Millions of tourists visit Sri Lanka and Kerala every year. Sri Lanka as a nation suffered from a brutal civil war and it adversely affected all the major sectors in the country. After the end of civil war, Sri Lanka achieved significant growth and development in multiple fields. Millions of tourists visited the nation and Sri Lanka received foreign exchange earnings worth billions of Dollars. But the terrorist attacks in the year 2019, COVID-19 pandemic and ongoing economic and political crisis shattered the nation and especially the tourism sector. Kerala, the southern state of India is currently benefitting from the Sri Lankan crisis. Kerala is a major rival to Sri Lanka in terms of tourism. Both Sri Lanka and Kerala has similar climate, landscape, food cuisine, geography etc. As a result of the Sri Lankan crisis, international tourists started preferring Kerala over Sri Lanka. This article aims to analyze the impact of Sri Lankan crisis on Kerala tourism
Optimizing the Failure Prediction in Deep Learning
Full text link
Avatars are computer-generated digital representations that people may use in the Predicting issues with software systems built from modules is the focus of this research. This data collection was used as a reference in order to accomplish this objective. The evaluation framework for reusable software components is provided by this research. The dataset of factors that play a role in the decision-making process has been run through the PSO algorithm. The primary objective is to provide a clever and time-saving method of choosing components. After filtering for ideal values, the dataset is utilized to train a deep learning model. Accuracy measurements including recall value, precision, and F1 score will be used to evaluate the effectiveness of the optimized component selection model. This research is significant because it provides a high-performance and accurate solution to a major problem in predicting. We have done our best to estimate the number of lines of code, the complexity, the design complexity, the projected time, the difficulty, the intelligence, and the efforts required. A model for discovering mistakes has been developed after the dataset was filtered to account for the ideal value. By keeping just the most crucial characteristics and getting rid of all optimized data, we have made the model more trustworthy.
 
Enhancing Image Segmentation: A Novel Grow Cut Algorithm with Advanced Cellular Automata
Full text linkImage segmentation is a fundamental technique pivotal in a myriad of vision-related applications, yet the field lacks a universally accepted methodology for selecting and comparing segmentation algorithms. This absence of standardization can lead to inaccurate interpretations and unexpected results, underscoring the inherent challenges of image segmentation, which lacks a definitive meaning. In computer graphics, segmentation refers to the division of a pixel collection into subsets, a concept that aligns with other scholarly interpretations, albeit with debated criteria. This process echoes human cognitive behaviour, specifically pattern recognition, amplifying the complexity of segmentation challenges. Various methodologies characterize the landscape of image segmentation, where one prevalent approach involves text retrieval to generate localized feature sets. Object recognition in computer science, which entails the automatic classification of objects, intertwines deeply with image segmentation, enhancing the understanding of objects within images. The chosen segmentation algorithm critically influences the overall outcome, necessitating meticulous selection tailored to specific frameworks. Despite the availability of numerous segmentation techniques, their complexity often deters practical research applications. This research delves into an enhanced graph cut method for distinguishing foreground and background elements through image labelling and segmentation. This approach is scrutinized against performance metrics to evaluate the efficacy of the proposed algorithm in image segmentation. By methodically comparing results, this study aims to provide insights into the algorithm's effectiveness, contributing to the broader discourse on segmentation techniques and their applicability in various vision-related fields
Liver Cancer Identification Grid Search RFC Model using Machine Learning
Full text linkLiver is essential to the body's digestion of sugar and fats, absorption, and immunological system. This substance is present in almost everything a man takes in, breathes, or absorbs through his skin. Liver disorders are a significant health burden. It is increasing daily and is difficult to detect in its early stages since the liver may function normally even when partially damaged. Doctors have widely employed machine learning algorithms to diagnose liver illness in order to increase the efficiency of medical diagnosis. The study's primary aim is to evaluate how machine learning algorithms may be used to prevent postponing medical care, accurately diagnose liver illness, and minimize the number of erroneous diagnoses provided to sick patients. The main objective is to ensure that liver patients receive an accurate diagnosis as soon as possible
Extending Classical Technology Acceptance Models, A Review of Potential Mobile Device and Consumer Individual Factors to Better Explain Mobile Commerce Acceptance
Full text linkPurpose - Technology adoption theories are very general, however the factors influencing acceptance could vary on the specific technology and the segments of consumers with their individual traits. This study accomplishes a comprehensive review of literature and to find potential variables to extend classical technology acceptance models specifically in the contexts of mobile technology and mobile commerce with consumer individual traits in mind. Methodology - 1. Methodical Review of key journal articles on Technology Acceptance across multiple key publishers, 2. Review of popular extant models in the context of general technology, 3. Elicit Mobile and Consumer specific considerations 4. Identify theories relevant to mobile devices and consumers as individuals Result - The result showed that the three were multiple mobile device/ commerce and consumer related theories including convenience, perceived risk, trust and deal proneness Study Implications - The theories and the constructs identified in this review could be used by future researchers working to further the acceptance science in the context of mobile devices taking consumer individual factors into consideratio
Design Simulation and Assessment of Cellular Automata Based Improved Image Segmentation System
Full text linkA variety of methods may be found in the numerous image segmentation techniques. Here a method of text retrieval conducted is typically to produce a collection of localized features. In computer science, object recognition is the problem of automatically "identifying", or classifying, an object. In certain instances, the awareness of artifacts is deeper into image in image segmentation through image processing. The algorithm used for image segmentation has a direct impact on the outcome of the whole approach, therefore it is important to choose carefully. It is important to choose a segmentation method appropriate for a certain framework. There are several ready-to-use segmentation methods, so one by one evaluate the tools to see which works best. Segmentation algorithms have reached such a level of complexity that a research employing them is often considered impractical. The given research undertakes the process of improved graph cut method to select the foreground and background of image through labelling and segmentation of the image. Results have been compared on the performance parameter to analyse the effectiveness of the proposed algorithm for segmentation of the images
Optimizing Brain-Computer Interface Reception: A GUI Design for Enhanced Signal Acquisition from the Peripheral Nervous System
Full text linkThis paper presents a novel approach to optimizing the reception of brainwave signals from the Peripheral Nervous System (PNS) through the design of a Graphical User Interface (GUI) for Brain-Computer Interface (BCI) systems. The efficient acquisition of signals from the PNS is essential for the accurate interpretation of neural activity and subsequent interaction with external devices. Our proposed GUI design focuses on enhancing signal acquisition by providing intuitive visualization tools and real-time feedback mechanisms. Through a combination of user-centered design principles and advanced signal processing algorithms, the GUI facilitates the seamless integration of PNS signals into BCI systems, enabling more robust and responsive neurofeedback applications. We discuss the key features of our GUI design, its potential applications in neurorehabilitation, cognitive enhancement, and assistive technology, and outline future directions for research in this rapidly evolving field
The Role of E-Government in Bangladesh’s Housing Market: A Study on Bogura, Rajshahi, Bangladesh
Full text linkBangladesh is a developing country on e-government sector day by day. Now the E-Government mainly focusing on the housing market sector day by day because it needs a vas attention so that people can easily get this service. Bangladesh has begun to use Information Communication Technology in E-Government sector firms to improve service delivery via improved governance processes. The ICT-based governing process known as e-government provides benefits to governments while also posing obstacles. Because of the government's complexity, adoption of e-government in housing market is challenging, which may subtract from the ultimate result. E-government is the delivery of universal services to citizens. E-government opens up new road for citizens to connect with government in a more direct and convenient way, as long as allowing e-government is providing services to city’s people directly. Individuals and their governments, as well as governments and other government agencies, people and governments, governments and employees, and governments and corporations, are all included by the phrase. This research focus on the impact of Bangladesh e-government on Bangladesh's property markets, and find out the potential consequences and repercussions