bluuebunny/crossref_metadata_2025 huggingface dataset:
Limitations Of Pert/Cpm In Construction Management Planning: Inputs To Mathematics In Architecture Education
Authors: Et. al. Lexphil John B. Ragel,
Published: January 2024

This research identified the roadblocks or shortcomings of PERT/CPM in the context of a construction company and suggested a plan to address the identified gaps. The researchers used a descriptive research design to discover the shortcomings of the PERT/CPM in construction management planning, especially in the Cabanatuan City, Nueva Ecija, Philippines construction industry. As a result, PERT/CPM is a project management approach that is useful in the basic administrative functions of planning, scheduling, and control. These days, business houses undertake massive projects that take years to complete before commercial development can begin. While this tool can be very useful, the majority of respondents agreed that it has limitations, such as; PERT/CPM can become ineffective and difficult to manage if it is not well-defined and stable for active control of a project; PERT/CPM requires frequent updating and revising of calculations, which is an extensive and time-consuming exercise that requires highly specialized knowledge; PERT/CPM requires frequent updating and revising of calculations, which is an expansive and time-consuming exercise that requires highly specialized knowledge; Furthermore, it is unable to efficiently accommodate abrupt shifts in the ground plan's execution. However, despite its limitations, PERT/CPM is still recommended for construction management planning, especially in large projects. The project manager must always have a contingency plan in place so that the quality of his or her work and projects won’t be jeopardized. In order to make the best use of all available resources in their production, a cost-benefit analysis must be performed, as well as additional research about PERT/CPM. The study's findings have implications for mathematics education in architecture.
Performance analysis of a Scalar Coupled and Decoupled PWM Technique for a Three Level symmetrical Dual Inverter Fed OEWIM Drive
Authors: Et. al. Kavya Venugopalan,
Published: January 2024

Dual inverter fed IM drive is commonly employed in EV applications. In this application, SVPWM based PWM generator was utilised. However, they produce a high common-mode voltage(CMV). Because of this, bearing of motor will be affected and in turn, results in EMI problems. Hence, to overcome this problem, this work introduced a novel PWM generation techniques named scalar coupled and decoupled PWM topology to control a three-level symmetrical DI fed OEWIM. Hence, to find out the effectiveness of the proposed topologies, its operation is examined under both continuous and discontinuous modes of operation using MATLAB simulation. From the acquired results, it is concluded that this coupled PWM topology topology exhibits reduced CMV and harmonics when compared to decoupled topology
Multi-Heuristic Based Technique in Multi-SVCs Installation Scheme for Loss Control in Transmission System
Authors: Et. al. Shahrizal Jelani,
Published: January 2024

Increasing demand of power system has been identified as one of the dominant factors in under-voltage phenomenon, instability condition and increment of transmission loss in power system. To alleviate this condition for the purpose of maintaining secure delivery of electricity, appropriate remedial actions are mandatory to be performed in either real time or offline studies. Amongst the popular remedial actions to avoid the loss control is the installation of static VAR compensator (SVC) scheme. This scheme requires a robust optimization technique which should be able to achieve optimal solution with less computation burden. This paper presents the application of multi-heuristic techniques for optimizing the sizing and locations of the SVC installation. Two optimization techniques are proposed in this study; namely the evolutionary programming (EP) and artificial immune system (AIS) for the purpose of optimal determination of locations and sizing of SVCs. Several cases are considered, based on number of units for the installation process; solved under different loading conditions subjected to the system. A reliability test system (RTS) model was utilized as the test specimen in this study; which ultimately highlights the merit of the optimization techniques.
A novel supervised machine learning algorithm to detect Parkinson’s disease on its early stages
Authors: Et. al. Lavanya Madhuri Bollipo,
Published: January 2024

Early and accurate Parkinson’s disease (PD) diagnosis are usually complex as clinical symptoms often onset only when there is extensive loss of dopaminergic neurons in substantia-nigra and symptoms are atypical at an early stages of the disease. Recent brain imaging modality such as single photon emission computed tomography (SPECT) with 123I- Ioflupane (DaTSCAN) have shown to be a better diagnostic tool for PD even in its initial stages. Presently machine learning algorithms have become trendier and play important role to automate PD diagnosis and predict its progression. In machine learning community, support vector regression (SVR) has recently received much attention due to its ability to negotiate between fitting accuracy and model complexity in training prediction models. This work presents an optimized SVR with weights associated to each of the sample data to automate PD diagnosis and predict its progression at primary stages. The proposed algorithm (W-SVR) is trained with motor and cognitive symptom scores in addition to striatal binding ratio (SBR) values calculated from the 123I-Ioflupane SPECT scans (taken from the Parkinson’s progression markers initiative (PPMI) database) for early PD prognosis accurately. In model building, different kernels are used to check the accuracy and goodness of fit. We observed promising results obtained by W-SVR in comparison with classic Support vector regression.
Relevance of Municipal Waste Management: An Empirical Investigation at Katwa Municipality in West Bengal
Authors: Et. al. Dr. Shatrajit Goswami ,
Published: January 2024

The successful waste management programme, well managed, enhances the country's health and environmental quality. This survey examines the position of the management of solid waste in the district town. For primary data collection covering around 70 to 90 randomly selected populations, the questionnaire was used. This survey is useful for people to raise awareness of waste management. Households were not aware of waste recycling, reuse & reduction of various organic or organic waste. Compared to the rest of the defined administrative area, small district town is defined. It is an important issue to identify backwardness, which is the urgent need for growth. This paper uses available data from Katwa Municipality to try the block level backwardness index.
An empirical study to evaluate factors affecting customer satisfaction on the adoption of Mobile Banking Track: Financial Management
Authors: Et. al. Dr. Viral Bhatt ,
Published: January 2024

Researcher needs to drive the effect of factors like ease of use, mobile atmosphere, perceived responsive, image of bank, perceived security, perceived risk, performance benefits, social influence, and hedonic motivation towards mobile banking. Here researcher measure direct and indirect effects of factors influences. In this research, luenlufeuu trust and performance expectancy are consider as mediating variableu whereas innovative is crfuiseo as ctaerroitu moderating variable. The data was gathered from 251 users of mobile banking through structure questionnaire with seven point scale. Descriptive Analysis Research Methodology was performed to test the research hypotheses where as multiple regression and path analysis performed with Advance. research sepeurpes an efficient model to evaluate intra-relationships amongst the factors affecting customer satisfaction on adopting of mobile banking. The results of research confirmed significant direct effects of factors like ease of use, mobile atmosphere, perceived responsive, image of bank, perceived security, perceived risk, performance benefits, social influence, and hedonic motivation towards mobile banking. Research also ensures the significant mediating effect of  ,luenlufeuutrust and performance expectancy as well as ctaerroitu moderating effect of innovative. This is unique effort of researcher for developing structural model for mobile .gtfkifr This study will help in understanding the concept of interrelation between different factors directly and indirectly correlated to mobile banking. These results provide insights for banks and mobile application providers to develop strategies that will enhance perceived value, customer experience and customer satisfaction. The main limitation of this paper is that sample population has been restricted to the users of mobile banking in major cities of Gujarat region only.
The Impact Of Current Fiscal Policy On Small And Medium Enterprises In The Kingdom Of Bahrain
Authors: Et. al. Mohamed Hasan Ali Thabet,
Published: January 2024

In economies all around the world the small and medium enterprises (SMEs) play a major role in the development of the economies, this impact is especially shown in developing countries. SMEs are the most contributors to the economic development of the country and the creation of jobs in the economies worldwide. Therefore, the key aim of the current study was to measure the effect of the fiscal policy along with real interest rate and literacy rate on the growth of SMEs registered in the Kingdom of Bahrain. For this purpose, the time-series data of the last 20 years from 1998 to 2018 was collected from the world bank and the official government database. ADF unit root test was applied to check the stationary of the variables and the Ordinary Least Square (OLS) method was applied to analyze for further analysis as all the variables were found stationary at level. The regression results show that the fiscal policy and literacy rate has a positive impact on SME’s growth of the country; however, the real interest rate has a negative effect on SME’s growth. Based on the current findings, the study recommended that the government should spend more to develop the basic infrastructure to support the SME’s development as well as related education and training programs especially the technical education for small businesses.
Energy-Efficient Enhanced Hierarchical Routing Chain Based Clustering for Wireless Sensor Networks
Authors: Et. al. Vidhya G,
Published: January 2024

Wireless Sensor Networks (WSN) constitute a wide range of applications. In most applications, sensor nodes are distributed in harsh environments and WSN nodes are power-limited, so once installed it will be difficult to charge those sensor nodes. In this article, combined with clusters, we propose a routing scheme that saves energy. First, the entire surface of the sensor is divided into parts, and then the sensor is divided by weighing the elements. Each section selects a Cluster Head (CH).Clustering is one of the common methods to maximize energy production. All sensor hubs are assembled into a number of groups in the clustering technique and each group is assigned a group head called the Cluster Head (CH). The CH absorbs high energy as they are responsible for data processing and data transmission compared to the remaining Sensor Nodes (SNs). The heads of the cluster are usually overwhelmed with a large number of sensing nodes, resulting in faster death. We propose an enhanced hierarchical routing chain-based clustering (EHRCC) algorithm based on the LEACH algorithm. The EHRCC algorithm uses E-LEACH, PEGASIS-E, LEACH-1R PEGASIS and P-LEACH

algorithm to investigate the creation of clusters, cluster head choice, chain creation, as well as the data transmission mechanism. Simulation results show that, EHRCC is better consumption of energy compared to HEED, E- LEACH,E- PEGASIS In addition, we evaluate the impact of various network parameters on network efficiency and further improve its performance.
Mining Of Customer Review Feedback Using Sentiment Analysis For Smart Phone Product
Authors: Et. al. Dr.P.Suresh,
Published: January 2024

With the fast growth of e-commerce, large number of products is sold online, and a lot more people are purchasing products online. People also give feedback of product purchased in form of reviews. The user generated reviews for products and services are largely available on internet. To extract the valuable understanding, classification of reviews is required from a huge set of feedback which has converted into positive and negative sentiments. The process of Sentiment Analysis (SA) has mined the attitude, opinions and emotions spontaneously from text, speech and database via Natural Language Process (NLP).It contains feedback review about product, product features or some sentiment emotional views on the product given by the customer. In this research work, feedback from the customer which associated with smart phones is taken from Amazon.com in order to predict the rating of the product given by the user feedback using SA. Feedback review of the customers has been collected fromAmazon.com and this research work had nearly 4000customer feedback reviews based on related categories namely ID of the product, name of the product, name of the brand, Rating, review of the product and vote based on review. This kind of analysis will be helpful for the customers to identify the better product with quick analysis and identify the implicit product perhaps the e-commerce business to improve the sales based on providing offers for particular implicit products.
Kriging Regressive Pseudo Randomized Lamport Certificateless Signcryption based Replication Attack Detection for Secure Routing in WSN
Authors: Et. al. D.Sudhakar,
Published: January 2024

A Wireless Sensor Network (WSN) includes small, low-cost, and resource-constrained sensor nodes to perform monitoring. Each node is free to move and susceptible to various attacks.  Therefore, WSNs have huge attention to communication security. Identifying and monitoring attack node is complex in distributed network and creates node replication attacks in WSN.  In order to improve secure routing, a novel technique called Kriging Regressive Attack Detection based Pseudo Randomized Lamport Certificateless Signcryptive Secure Routing (KRAD-PRLCSSR) is proposed. KRAD-PRLCSSR enhances the secure routing by detecting the replication attack in WSN. Initially, the neighbor discovery is performed using the Kriging Regression function. Energy of every sensor node is calculated and validates with threshold value. Based on estimated results, normal node or replica node is identified. Then the normal node is chosen as neighboring node. After that, secure transmission is performed using Pseudo Randomized Lamport one-time Generative Certificateless Signcryption. By applying the signcryption technique, Pseudo Randomized private and public keys are generated for each sensor node. After the key generation, the source node performs the encryption as well as a digital signature. The encrypted data and signature are sent to receiver. Finally, signature is verified at the receiver side to decrypt the data. This helps to increase the security of routing in WSN. The simulation analysis of KRAD-PRLCSSR technique is performed with the different metrics.
An Enhanced Framework For Automatic Voice Pathology Monitoring Based On Hidden Markov Model
Authors: Et. al. Dr. K. Mohana Prasad,
Published: January 2024

Clinical analysis of voice issue and assessment of treatment result vigorously depend on exact measurement of voice quality, which is intently attached to the physiology and capacity of the laryngeal instrument. Considering the assessment strategy of the voice, two principle classes of sound-related perceptual appraisal and acoustic examination can be recognized. This work exhibits another methodology for acoustic examination of voice quality, which carries a few focal points to the field. The proposed approach is nonparametric as in it doesn't require the estimation of the principal recurrence or unearthly reaction of the vocal tract. This lessens the computational multifaceted nature of the estimation and decreases the potential blunders because of wrong estimation of those parameters. Also, the technique doesn't make any presumption about the phonetic setting and subsequently can possibly be applied to associated discourse. This work focuses on building up an exact and hearty component extraction for recognizing and grouping voice pathologies by researching diverse recurrence groups utilizing autocorrelation and entropy. We extricated greatest pinnacle esteems and their relating slack qualities from each casing of a voiced sign by utilizing autocorrelation as highlights to identify and group neurotic examples. These highlights were researched in particular recurrence groups to survey the commitment of each band to the identification and arrangement forms.
Improved Results on Delay dependent Stability Criteria of Neural Networks with Interval Time Varying Delay
Authors: Et. al. R. Jeetendra,
Published: January 2024

This paper examines the stability issue of continuous Neural Networks with a time varying delay. A Lyapunov Krasovskii functional consisting of some simple augmented terms and delay dependent terms is constructed. While calculating the derivative of Lyapunov functional, various integral inequalities such as Auxiliary Function Based Integral Inequality, Wirtinger-based integral inequality and an extended Jensen double integral inequality are jointly adopted and hence in terms of linear matrix inequality a new delay dependent stability criterion is obtained. Two numerical examples are taken to show that the derived result is less conservative than some existing ones.
“A Comprehensive Reveal: Early Detection Of Glaucoma using SVM”
Authors: Et. al. Senthi Vadivu M,
Published: January 2024

Eyes are our body's most importantly developed sensory organ. A far large part of the brain is dedicated to vision, other sensory activities such as hearing, taste, touch, or smell combined. This precious organs affected by various reasons. Glaucoma is a category of eye disease that causes damages to the optic nerves, the protection of which is critical for proper vision. This collision is often triggered by unusually high pressure in your eye. Glaucoma also known as the “Silent Thief of Sight,” is one of the leading cause of blindness in the world for people above the age of 60.The cost of detecting glaucoma using optical coherence tomography (OCT) and Heidelberg Retinal Tomography (HRT) technique is prohibitively high. The aim of this study is to uncover and explore the early detection of glaucoma using the Support Vector Machine (SVM) classifier process, which are a type of Supervised learning method. Furthermore, the SVM classification process is straightforward, with high precision and first-rate performance.
The Effectiveness of Financial Management Strategies in Public Primary Schools in the South Africa
Authors: Et. al. L S Mandlazi,
Published: January 2024

This paper reports a sequential mixed methods study on the effectiveness of financial management strategies in achieving organisational success and stability in public primary schools in Dwarsloop Circuit, Mpumalanga Province, South Africa. The study involved six schools and a sample of 78 participants, comprising 72 School Governing Body (SGB) members and six primary school managers. The study shows that the South African Schools Act, 1996 and the Public Finance Management Act, 1999, are key legislation used to govern and administer the finances of  public schools in South Africa. It was ascertained that SGB members with a background in teaching, had a better understanding of the South African Schools Act, compared to SGB members who were parents without teaching experience. The research further shows that most schools in the Dwarsloop Circuit do not use strict internal controls nor is there clear and consistent segregation of duties as key aspects of financial management. It is recommended that all SGB members undergo mandatory training required to execute their duties effectively. The Department of Education in conjunction with the relevant agencies, should ensure an annual financial audit is conducted of all schools in the Dwarsloop Circuit of Mpumalanga Province.
Economic Value Added (EVA) And Market Value Added (MVA) Towards Value Creation
Authors: Et. al. Yap Voon Choong,
Published: January 2024

The well-known value-based performance measures are Economic Value Added (EVA) and Market Value Added (MVA). EVA and MVA can help managers and shareholders to measure company’s performance in order to create wealth. The main objective of this study is to examine the relationship between EVA and MVA in creating shareholders ‘value. This study has analyzed the performance of 476 public listed companies in Bursa Malaysia. The companies represent 8 sectors and covers data for 10 years period (2007-2016). The findings seem to show a significant relationship between EVA and MVA for Malaysian firms. However, Malaysian firms indeed need some reliable measures that could evaluate their performance thoughtfully and assist investors to make right investment decisions and capital allocation.
Study and Analysis of Various Automatic Brain Tumour Segmentation andClassification: A Challenging Overview
Authors: Et. al. K.V. Shiny,
Published: January 2024

Early prediction of Brain Tumour (BT) plays a vital function for providing treatment plan and patient care at initial stage. The manual identification and classification of brain tumour is difficult to realize and time consuming due to the same structures, and also the scarcity of available radiology expertise. Generally, the BT classification is performed in two ways, such as:realize whether the image as either normal or abnormal (ii) Classification of abnormal region based on the various kinds of tumours. Thus, the manual classification of brain tumour from MR images are time consuming, nonreproducible and impractical due to the vast quantity of MRI dataset. To overcome these issues, automatic classification is a proper solution to classify the tumour from Magnetic Resonance (MR) images with less intervention of radiologists. The key challenge in classification of MR image is the semantic gap among low level visual data gathered through MRI machine and high level information perceived through human evaluator. The conventional machine learning-based classification techniques focused only in either low level or high level or handcrafted features for diminishing this gap and achieving better feature extraction and classification methods. Thus, this survey analyzes several techniques intended to BT segmentation and classification through images from various sources. This study utilized25 research papers concentrated on various techniques, and the review of various researches technique-wiseis also to be provided.Finally, the analysis discussed in this survey based on the publication year, research technique, implementation tools, performance measures and achievement of the research methodologies towards BT segmentation and classification using different datasets. At the end, the research gaps, issues of the techniques and then, the motivation for developing an effective method for brain tumour segmentation and classification is also to be revealed.
Responses to Fatwas of Islamic Religious Leaders and Institutions during the Coronavirus Disease (COVID-19) in the Philippines: Looking at How Guidance Was Provided to Muslim Communities in the Philippines.
Authors: Et. al. Sheryl R. Morales,
Published: January 2024

The Philippine constitution guarantees the free exercise of religion and religious worship. The law forbids public officials from interrupting religious activities. However, with the sharp rise of Coronavirus (COVID-2019) infection all over the world, the Inter-Agency Task Force (AITF) on Emerging Infections Disease created resolutions to assess, monitor, contain and prevent the spread of the pandemic. Religious leaders and Islamic institutions are no exceptions and they must abide to these resolutions including mass gatherings, safety procedures on burials, and strict observance of social distancing.

Muslims strictly perform five times a day prayer, Friday Jamaah prayer, and bury the dead in accordance to Islamic practices mentioned in the Quran. Therefore, the study focus on how Islamic leaders and institutions responded to AITF resolutions to prevent the spread of the pandemic.

The data were collected from mixed sources: from official announcements, social media accounts, and by phone interviews.  Meaningful central themes were derived from the data.

Findings noted responses of Muslim communities focused on (1) suspension of collective religious activities and programs until the pandemic is over; (2) abide by government directives on how to be safe from the threat of COVID-19; (3) institutionalization of positive sanitation practices of their facilities personnel and families; (4) cancellation of classes and their religious learning institutions; and (5) public interest and dharurah (possibility of harm or injury).

In conclusion, the concept of collective duty (farḍ kifāya) as a basic of principle of Islam was practiced by Islamic religious leaders and institutions. Hence, maintaining social
A survey of the identification strategies of brain tumors for MR images
Authors: Et. al. Ayushi Sharma,
Published: January 2024

A substantial rise in medical cases associated with brain tumor has been seen in recent years, making it the 10th most common type of tumor Impacting both children and adults. Due to the rising refining of medical picture technologies, Brain Tumor [BT] and their study are of considerable concern Medical image processing concepts have been used successfully in diagnosis of Tumor. For its non-invasive imaging properties, science is more oriented toward MR. Diagnosis or identification mechanisms assisted by computers have become problematic and are still an Open concern due to heterogeneity in tumor shapes, locations, and sizes. Many experts in medical field have carried out notable study work on automated detection of tumor strategies based on segmentation, grouping and variations of automatic brain tumor detection. Different brain tumor identification methods for MR images are analysed in the manuscript, including the assets and challenges found with all techniques to detect different forms of BT. The survey presented here is aimed at supporting the researchers identify the important features of types of brain tumor and identify different segmentation/classification approaches that are effective in identifying a variety of tumor types of disorders of the brain. The manuscript covers the most important approaches, procedures and operating practices. Brain tumor identification rules, priorities, restrictions, and their potential snags on MR picture.
Regression Tree Based Correlation Technique in Spatial Data Classification
Authors: Et. al. P.D.Sheena Smart,
Published: January 2024

Data mining is the process of discovering useful patterns from large geo-spatial datasets with the help of machine learning methods. . The machine learning methods plays an important role for data analytics modeling and visualization. Geo-spatial data is a significant task in many application domains, such as environmental science, geographic information science, and social networks.  However, the existing spatial pattern discovery and prediction techniques failed to predict the event accurately with minimum error and time consumption. . In this paper, a novel Pearson Correlated Regression Tree-based Affine Projective spatial data Classification (PCRT-APSDC) technique is proposed to improve the spatial data classification and minimize error based on the Affine Projective classification technique. The proposed algorithm employs a fuzzy rule procedure that constructs the regression tree. The fuzzy rule is applied for linking the inputs (i.e. spatial data) with the outputs (i.e. classification results). Our goal is to classify the data into two subsets such as fired region and non-fired region.  Experimental evaluation is carried out using a forest fire dataset with different factors such as classification accuracy, false-positive rate, and classification time. The results confirm that the proposed technique predicts the fired region with increased spatial data classification accuracy and minimized time as well as false-positive rate than the state-of-the-art methods.
Energy-Aware Ch Selection And Optimized Routing Algorithm In Wireless Sensor Networks Using Wmba And Qoga
Authors: Et. al. Subhash Chandra Gupta,
Published: January 2024

WSN is widely used in different applications, such as smart grid, water municipals, and health care, for monitoring the health condition of a patient, etc. But, the major challenge of WSN is energy efficiency. Energy Efficient-based WSN has always been a research focus to improve its performance. Aiming at optimal energy utilization to improve life expectancy with guaranteed QoS, an optimal CH selection and optimal routing algorithm in WSN is proposed. The work has carried out the selection of the CH based on various factors, such as residual energy of the nodes, proximity, distance to the base station, cost, node degree, and node centrality or coverage, using the proposed WMBA. After that, an optimal path selection using QOGA is done between CH and BS based on various factors, such as distance, residual energy, and node degree, under the MKMA clustering process. The experiment shows that the proposed methodology achieves better life expectancy for the WSN by achieving an energy consumption of 975J for the entire round of 2000 and a PDR of 93.56%, and remains to be energy efficient compared to the existing state-of-art methods.
The Effectiveness of using Electronic Commerce Mobile Applications During Covid-19 Pandemic
Authors: Et. al. Yousef A. Baker El-Ebiary,
Published: January 2024

E-Commerce has been one of the human needs all around the world. Not only to a customer but also to industry players. The food delivery service industry is one of the E-commerce services. Food delivery is growing up and has a good potential rate in Malaysia and globally now. At first many of Malaysians were still not exposed to food delivery has many advantages, with social distancing the new norm, consumers are demanding to have takeout food delivered in parallel with government standard procedure in the Covid-19 pandemic. To reach people with online business, e-commerce makes an application as initiative to do business via the Internet. E-commerce has many system applications which are product or service system and food system. Product or service system will do business related with product or service meanwhile food system will do business related with food. While running a business via online, there is advantages and disadvantages that will give many impacts in customers, sellers and an application itself. So, the method or strategy to improve the online business which is sample size, measurement and data analysis developed so that online business can run smoothly according to planning.
Vector Control of Induction Motor Using Neural Networks Based Lookup Table for Reduced CMV
Authors: Et. al. Aladalli Sharanabasappa,
Published: January 2024

This paper confers a vector control (VC) perspective for induction motor drives by combining the principles of vector and direct torque control (DTC) methods. In classical vector control, the switching states will be chosen dependent on current hysteresis regulators. Based on the instantaneous current waves, the hysteresis controllers generate the switching specimen. But, the classical DTC selects the pertinent voltage vector from lookup table extracted from the flux and torque error signals and sector information. The proposed perspective combines both VC and DTC techniques. In this paper  d and q-axis current errors and sector information, the lookup table chooses an appropriate voltage vector. Moreover, to select the befitting voltage vector Neural Network (NN) based approach is presented in this paper. Also, to reduce the common mode voltage (CMV) variations, NN based lookup tables are proposed. To substantiate the proposed NN based vector control, simulation studies have been conveyed and results are collated.
English Learning Platform Student Behavior Analysis in Buying Courses by Using Data Mining Techniques
Authors: Et. al. Yohanssen Pratama,
Published: January 2024

English Learning Platform is an online English learning platform which utilizes subtitled YouTube video as learning platform. This learning platform is said to be personalized, by recommending next material based on how well one performs for each exam given per video. If students are able to learn successfully, they may have a tendency to buy more courses. Our goal is to use data mining techniques to research on the relationship about number of courses that students purchase with their learning behavior. After comparing 5 methods by using 4 machine learning algorithm we found that student score attributes has stronger impact to determine the number of packages that bought by students and the login frequency doesn’t affect the number of purchased courses. The neural network algorithm gives the best accuracy which around 90% compare to another algorithm there are decision tree, random forest, and k-means.
Transport Accessibility as a Factor of Regional Development
Authors: Et. al. Liliya V. Erygina,
Published: January 2024

The spatial distribution of industrial enterprises is closely related to the development of transport systems that unite them into a single regional complex. Sustainable operation of transport systems is a guarantee of a single space, free movement of goods and services, improvement of conditions and living standards of the region's population.

The transport system ensures the territorial integrity of the region and the unity of the economic space based on the movement of passengers and goods, linking the region's enterprises into a single complex and ensuring the continuity of the processes of development of productive forces. The existing approaches to assessing this indicator are of a complex nature, but they do not take into account the influence of a number of factors associated with the peculiarities of the spatial distribution of the population of certain, for example, northern territories. The lack of objective statistical data does not allow researchers to conduct a comprehensive assessment of transport accessibility. Despite this, many authors are considering the possibility of measuring transport accessibility based on taking into account the costs of movement. The authors of the article propose to use this approach, improving it by refining the formula for the cost of travel time, which makes it possible to objectively compare the transport accessibility of various settlements to the regional center. Thus, this study is devoted to the study of transport accessibility as a leading factor in the development of the regional economy
A Comparative Performance Study on Smart Home Automation and Security System Using Blockchain Technology
Authors: Et. al. Priyajot,
Published: January 2024

Smart-home researchers' opinions and experiences suggest that privacy and choice are their main ethical concern. The researchers consider the private life of a person as a major problem when conducting research, though tending to see privacy in terms of information privacy, seldom see privacy as a personal privacy. In addition, we urge smart house-researchers to focus upon this. These are two major ethical issues. Is it necessary to concentrate on privacy? While some sort of privacy respect is a global social norm, it is fundamentally debated whether and when privacy is considered to be a moral principle coherently, as respect for privacy specifically limits the application of other moral requirements. Maybe due to the disputed moral significance, privacy-based moral arguments are at the forefront of many polarised bioethic discussions. Philosophical debates on privacy concentrate whether privacy is in the interests of one's own right (and therefore vulnerable to harm) or a cluster of other more fundamental interests, such as ownership and freedom interests.
Subsequently Direct Right Maximum Minimum Financial plan Eventual Procedure for Sheltered and Fanatical Rectangular Arrangement
Authors: Et. al. K. Thiagarajan,
Published: January 2024

In this research, the proposed algorithm is Next Immediate Right Maximum Minimum Allotment method. This algorithm is to calculate the optimal value of cost for the Travelling agent to reduce the transportation cost. The expressed algorithm is very useful to derive the allotment in every sector of the rectangular matrix without any disturbance in degeneracy condition.
Using Big Data, An Extensible System for Forecasting and Analyzing Relations Among Crimes
Authors: Et. al. Subashka Ramesh S.S,
Published: January 2024

While Big Data presents a dilemma for criminal activity analysis, it's even possible to assist them in locating and detecting patterns that can help them crime prevention and investigation. This system intends to draw consideration to current problems in Cyber Crime Investigations – particularly those involving Big Data – as well as potential approaches to combating cybercrime. The proposed system's outcome would help law enforcement and police department agencies a higher comprehension criminal issues and provide insights that will allow them to track operations, forecast the chance of incidents, arrange resources effectively, and optimise policymaking processes. Crime prediction makes use of historical data and, after analysing it, forecasts future crimes based on place and time.

Outdated methods become fewer effective as their ability to deliver needed outcomes in an appropriate and supply-constrained manner deteriorates. To prevent and combat crime, one promising choice for Criminal Inquiries is to use tools for computing based on cutting-edge data analytics. As a result, machine learning and computer modelling should be included in the investigations. One of the solutions is computational, which provides quick and effective data analysis to find small sign in big, unstructured data sets.
Investors Satisfaction Towards Stock Market In Thoothukudi City
Authors: Et. al. Dr. G. Paulraj,
Published: January 2024

The globalization of economic markets has been raise the size of the society of retail investors’ in excess of the past two decades by providing a wide range of market and investment options. Therefore, it makes their investment decisions development more multifaceted. The factors influence investor’s awareness are return on investment, market trend or risk, short term profitability, price of the share, dividend policy, past financial presentation, company character, standing of the board, current earnings of the company and specialist judgment. This study focuses investor satisfaction towards stock market in Thoothukudi city
The Day in Shadow: A Voyage of Self Discovery
Authors: Et. al. Bhargavi Jha,
Published: January 2024

The theories regarding self, being and identity formation has always been at the locus of all philosophies. Plethora of philosophical dialogues and discourses has been intertwined to understand the rubrics of self and being since time immemorial. Postmodern era encompasses the fractured and hybrid self which is to be understood by understanding the process of formation. In postcolonial era formation of self subsumes class, cast and gender as paramount factors. The paper analyze those factors in detail which provides development of a postcolonial protagonist in Indian context. The postcolonial/Dissensual model of the genre does not surrenders to the traditional conventions of the genre but the failure itself becomes a new perspective of development.
Prototype Model for High Speed Railway Power Supply System Suitable for Indian Traction Sub Stations using Multi Modular Converter
Authors: Et. al. Venkatasupura Vemulapati ,
Published: January 2024

As on 2020, India does not have any globally proven railway lines running with high-speed standards as above 250 km/h. Indian Railways looking at the prospect of high speed rail networks also known as bullet rail network in India. With the present Indian traction supply system which is based on the phase splitting or phase shifting method is not suitable for the high speed railway network unless we eliminate neutral sections as well as mitigating the power quality issues such as voltage unbalance, harmonics and high reactive power drawn from the utility grid. In this paper, Co-phase traction power supply system with zero neutral sections is proposed. Modular multilevel converter based three phase to single phase catenary system through a DC Link has been designed, simulated and laboratory prototype is made. A MATLAB simulation of the suggested method and droop characteristics based on load sharing between the two single phase parallel inverters had executed. The obtained results were satisfactory and shows that the proposed system is very much suitable for high speed railway.
Impact Of Internet Bankingin Usage Of Consumer Satisfaction In Indian Banking Sector
Authors: Et. al. Mr.G. Dhayanidhi,
Published: January 2024

Internet Banking is set the use of the infrastructure for virtual age to create possibilities, each in local & worldwide market. IT allows the giant reducing of transaction price and the advent of recent kinds of banking possibilities that cope with the boundaries of time and distance. Banking possibilities are local, worldwide and on the spot in net banking. Internet banking is a web charge machine that allows clients of a financial institution or different economic establishments to behavior a number economic transactions via web sites of economic establishments. Internet banking has many benefits over different conventional banking shipping methods. Internet banking gives banks with an accelerated patron base, price savings, mass customization, product innovations, progressed marketing, and communication, the capacity to broaden non-center businesses, and the capacity to provide offerings no matter geography and time constraints, viewing account balances, latest transactions, ordering cheque books and lots of more. With the improvement of recent technology, Internet banking is anticipated to grow to be a main banking technique for clients. Internet banking reduces expenses via way of means of presenting clients with every other manner of having access to their bills with-out bodily touring a financial institution. The essential reason of this examine is to investigate numerous on line centers supplied via way of means of fundamental public and personal banks in India and to degree their effect on clients in phrases of patron satisfaction.
Impact of Peer Assisted Learning Strategy (PALS) for Learning Enhancement of Students at Secondary Level
Authors: Et. al. Mrs.P.C. Santhanalakshmi,
Published: January 2024

Peer Assisted Learning Strategies (PALS) is a Peer tutoring technique in which it supplements the core curriculum through intervention. This is an evidence based approach and fits with many instructional methods and help the teachers to address all kind of students in the classroom. Moreover, PALS would be beneficial to teachers for teaching science and can target students who need more support.This study attempted to study the effect of PALS on learning Science subject. The result of this experimental study showed improvement in reading and overall learning the concept of science subject.
Optimal Parameter Selection for DWT based PCG Denoising
Authors: Et. al. Ravindra Manohar Potdar,
Published: January 2024

Analysis of PCG signals helps in diagnosis of cardio vascular disorder non-invasively. PCG signals are non-stationery in nature and hence time-frequency analysis of PCG is the most suitable means for analysis to determine the basic features of it. However, the PCG signals need to be denoised before feature extraction process and DWT proves to be most suitable for this purpose. During acquisition of HSS technically known as PCG various types of noises and artifacts contaminate the signal of interest. Hence denoising of the signal is inevitable before proceeding for diagnosis. DWT has been proved to be a powerful and handy tool along with thresholding for this purpose. However, the main challenge lies in the fact of selection of the suitable MWT with required number of DL and the type of thresholding function. The present work deals with the optimization of the selection process using varieties of MWT with varying DL and thresholding functions. Rigorous experiments have been conducted using codes in MATLAB environment to select the suitable MWT, DL and thresholding function. After optimization, the selected MWT, DL and Thresholding function have been applied on 22 PCG signals obtained from open data source and the performance of the process has been measured in terms of SNR and RMSE. It has been observed from the extensive experiments using different combination that sym20 wavelet with 10 decomposition level along with Bayesian Soft thresholding function provide the best result in denoising the applied PCG signals. The database used is that of MHSDB available at www.med.umich.edu/Irc/psb/heartsounds/index.htm provided by the University of Michigan Health System.
Effectiveness Of Rural Healthcare Centres: An Empirical Study In Sonitpur District Of Assam, India.
Authors: Et. al. Rimakhi Borah,
Published: January 2024

It is essential for a nation to have provision for proper healthcare facility in urban as well as in rural areas of the country as health and socio-economic development work simultaneously. With the distressing effect of COVID-19, it becomes more important to understand how our health care system works and what it has more to provide. India is heavily covered with more rural populations than urban where Community Healthcare Centres (CHCs) being the uppermost tier of rural public health infrastructure in India is formed to provide proper healthcare service to its community. In the present study, an attempt has been made to understand the effectiveness of the health centers in the studied area so as to find out the areas which requires more attention and efforts can be put on those areas so as to improve the quality of service and provide proper healthcare facilities to the community. The result showed distressing figure and despite the well-structured healthcare system in the country, the health care infrastructure and the basic health care facilities even in the CHCs and Model hospital lagged far behind and required proper attention towards it.
A Smart Hoodie- Assistive Technology for Blind People Using IoT
Authors: Et. al. Kathiravan M,
Published: January 2024

Assistive technology for the blind is a field of research that is gaining more and more importance due to the eruption of new interest from different fields. These research findings have had a huge social impact among elderly and blind population. In this paper, we introduced a novel Smart Hoodie which can sense the objects around them and can prevent the blind people from getting hurt accidentally or banging on heavy objects. The technology used here is IoT, where a Raspberry Pi kit is used along with ultrasonic sensors which can sense objects. A micro camera can be fixed on top of the Hoodie, which is triggered once the sensor detects the object and then object recognition is performed; a voice notification is generated either with the speaker or earphones. We can also track the location of a blind person in case they are lost, using a GPS module. A GSM module is used by a blind person to send messages in case of any emergency. Although, there were a lot of discoveries related to the above-mentioned issue, it has inflamed that our invention is much better than other state of the art approaches.