bluuebunny/crossref_metadata_2025 huggingface dataset:
A prospective case-control study of disability, quality of life, and functional impairment of shoulder movements after latissimus dorsi myocutaneous flap reconstruction in breast cancer patients
Authors: Nanda Singh Gitika , Suryavanshi Parijat , Ahmad Shariq , Roy Shubhajeet
Published: March 2024

Objective: Dysfunction of shoulder movements could be a limiting factor to the use of Latissimus dorsi (LD) flap. This study aimed to assess the impact of LD flap reconstruction on shoulder dysfunction and the quality of life.

Material and Methods: This study comprised 28 early breast cancer cases who underwent breast conserving surgery (BCS) with LD flap and 40 controls. Subjective and objective assessments were done a year later.

Results: Mild and moderate disability were found in 85.71% and 14.3% cases vs. 100% and 0% controls (p= 0.316) respectively. Physical and emotional functioning were 84.29 ± 5.61 and 66.67 ± 6.05 in cases vs. 86.67 ± 8.38 and 70.0 ± 6.84 in controls (p= 0.36, 0.23) respectively. Pain score in cases was 23.8 ± 15.6 vs. 12.17 ± 8.4 in controls (p= 0.018). LD muscle strength in extension was 4.39 ± 0.35 in cases vs. 4.88 ± 0.22 in controls (p< 0.001), 4.43 ± 0.18 for adduction in cases vs. 4.65 ± 0.24 in controls (p= 0.006). ROM of shoulder in flexion was 151.61 ± 4.86° in cases and 153.88 ± 2.36° in controls (p= 0.08), 40.36 ± 3.52° in cases vs. 49.13 ± 1.86° in controls for extension (p< 0.001), in abduction it was 150.54 ± 3.69° in cases vs. 150.00 ± 0.00° in controls (p= 0.518), in adduction was 30.89 ± 4.0° in cases vs. 38.13 ± 1.11° in controls (p< 0.001), in external rotation was 73.57 ± 3.63° in cases vs. 77.63 ± 2.36° in controls (p< 0.001), and internal rotation was 69.46 ± 3.56° in cases vs. 79.00 ± 1.26° in controls (p< 0.001).

Conclusion: We conclude that functional impairment should not be a determining factor for LD flap in breast reconstruction surgery.
Predictive value of drain fluid amylase level on postoperative day one after pancreatic resection for predicting postoperative pancreatic fistula
Authors: Çağrı Büyükkasap Ahmet , Dikmen Kürşat , Yavuz Aydın , Altıner Saygın , Göbüt Hüseyin , Cihangir Emral Ahmet , Bostancı Hasan , Kerem Mustafa
Published: March 2024

Objective: The aim of this study was to evaluate the predictive value of the first postoperative day (POD1) drain fluid amylase in predicting pancreatic fistula formation following pancreaticoduodenectomy (PD).

Material and Methods: One-hundred and eighty-five prospective patients undergoing PD between April 2014 and April 2018 were studied retrospectively. Cut-off point to predict the development of POPF was determined by median values for drain fluid amylase of 1883 U/L. Patients were classified into two groups according to POD1 drain fluid amylase values: <1883 U/L (Group 1) and ≥1883 U/L (Group 2). Differences between the groups with clinically relevant POPF and without POPF were evaluated.

Results: The incidence of POPF was 17.2%. POD1 amylase level was the strongest predictor of POPF, with levels of higher than 1883 U/L demonstrating the best accuracy (87.5%), sensitivity (78.1%), specificity (89.5%), positive predictive value (60.9%), and negative predictive value (95.1%). One-hundred and forty-four patients (77.8%) had a POD1 drain amylase level of less than 1883 U/L, and POPF developed in only seven (3.7%) cases, whereas in patients with POD1 drain amylase level of 1883 U/L or higher (n= 41), the POPF rate was 31.4% [OR: 22.24, 95% CI (7.930–62.396), p<0.001].

Conclusion: The cut-off point of POD1 drain fluid amylase level (1883 U/L) might predict the clinically relevant POPF with adequate sensitivity and specificity rates in patients undergoing pancreatic resection.
Pathological complete response and associated factors in breast cancer after neoadjuvant chemotherapy: A retrospective study
Authors: Gündoğdu Adnan , Uluşahin Mehmet , Burak Çekiç Arif , Nazlı Kazaz Seher , Güner Ali
Published: March 2024

Objective: This study aimed to determine clinical and pathological factors that identify a pathological complete response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC).

Material and Methods: A retrospective, single-center study was conducted in women over the age of 18 who had been diagnosed with pathologically confirmed invasive breast cancer and who had received NAC between July 2016 and October 2021. Patient demographics, clinical, radiological, treatment, and pathological data were reviewed from the electronic hospital records. The primary outcome of interest was pCR, defined as the absence of residual invasive breast cancer in both the breast and axillary lymph nodes. Multivariable logistic regression analysis was used to identify factors associated with pCR.

Results: A total of 119 patients were included in the analysis. The distribution of age was 54.5 ± 11.5 years. pCR was observed in 33 (27.7%) patients. pCR for breast tissue was observed in 43 (36.1%) patients. There was no statistically significant relation between the clinical stage and pCR. Age, age at first labor, extent of disease in the breast, NAC completeness, clinical tumor size (cT) stage, clinical lymph node (cN) stage, and molecular subtype were analyzed in a multivariable model. Analysis showed that molecular subtype was the only independent factor related to pCR. pCR rates across molecular subtypes were: 8.7% in luminal-A, 10.8% in luminal-B, 54.5% in human epidermal growth factor receptor 2 (HER-2)-positive, 42.4% in luminal-B (HER-2 positive) and 46.7% in triple-negative. There was no statistically significant difference between luminal-A and luminal-B subgroups (odds ratio 1.15, 95% confidence interval, 0.19-9.35, p= 0.881). Despite the limited number of patients in HER2-positive and triple-negative groups, both demonstrated statistically significant higher odds compared to reference group.

Conclusion: The presented study underscores the relevance of molecular subtypes in determining the response to neoadjuvant chemotherapy in breast cancer patients. Particularly HER2-positive and triple-negative subtypes may demonstrate more favorable response rates.
Challenges of Ta Providers in Lac Implemention: Basis for Localized Lac Framework
Authors: Irinco Daisy B. , Maravilla Jayson Seel M. , Vera Jr. Ramon R. De
Published: March 2024

Learning Action Cell (LAC) is a session conducted by group of teachers who engage in collaborative learning sessions to solve shared challenges encountered in school. Though LAC projects a promising result for teachers in improving Teaching and Learning Strategies, it is somehow, not being maximized in the school. This challenge of maximizing (LAC) brings life to Continuous Improvement CI Project BILLS, Boosting and Improving LAC Leaders and Strategies. And this, proposed research is anchored to the on going CI Project BILLS. This study in particular, tried to determine the challenges encountered by TA providers or LAC leaders in LAC implementation. This study aimed to analyze the experiences and challenges, most especially, of the TA providers, 8 Head Teachers, and 18 Master Teachers towards LAC implemantation. This action research was plainly qualitative in nature and made used of interview as the research instrument. Consequently, coding and theming were used for data analysis. This research revealed that TA providers 1. have difficulty in crafting the proposals and securing necessary attachments, 2. due to challenges encountered in LAC implementation by LAC leaders, the monitoring of teachers’ performance was taken for granted, 3. the absence of monitoring and evaluation team was found as another reason on the low success rate of LAC implementation. TA providers also observed that 4. teacher-participants demonstrated less motivation and participation in the LAC session, 5. through the TA’s initiative, they have found out that teachers’ schedule have conflict with the LAC activity and the LAC topics are no longer new to the teacher-participants. Meanwhile, the newly introduced LAC process through CI Project, was observed to have a more detailed, organized and systematic conduct of LAC. The most evident improvements are the following: 1. Presence of Monitoring and Evaluation (M&E) all throughout the process, 2. Intervention of Learning and Development (L&D) Coordinator, 3. Posting of QATAME flow chart, 4. Proper conduct of LAC, 5. Presentation of LAC outputs and outcomes.
A Study on Online Foreign Language Learning Satisfaction of Chinese College Students in Post-epidemic Period
Authors: Qiongke Huang , Yongjin Zhu
Published: March 2024

Online learning has become an important mode of foreign language learning in the post-epidemic period. Online learning satisfaction is a direct embodiment of the quality and effect of online learning of college students, and it is also an important indicator to evaluate the effectiveness of online learning of college students. In this paper, a questionnaire survey was conducted on the online foreign language learning of 420 college students in Hubei Province by random sampling. It is found that college students’ satisfaction with online foreign language learning was generally high, and there is no significant difference between males and females in terms of satisfaction. Sophomores’ online satisfaction is significantly higher than junior students, and there is no significant difference among other grades. Satisfaction is weakly correlated with students’ performance.
The Impact of Human Resource Strategies on Developing Organizational Agility An Exploratory Study in The Salah al-Din Education Directorate
Authors: احمد إبراهيم حمادي المشهدان روى , جدعان حماد احمد , محمد إبراهيم جاسم الحدي حنان
Published: March 2024

The research aims to demonstrate the impact of human resource strategies (human resource preservation strategy, cooperation strategy, restructuring strategy, outsourcing strategy) in developing organizational agility (reactive agility, proactive agility, innovative agility) in the Salah al-Din Education Directorate , this goal was translated into a hypothetical scheme that includes variables and dimensions, according to the exploratory curriculum in the Salah al-Din Education Directorate, and then the research hypotheses were formulated and tested using appropriate statistical methods and using the statistical package (SPSS) program. In general, the descriptive approach was adopted in the statement of the theoretical and analytical frameworks to test and analyze the hypotheses of the research, while the study community consisted of workers in the Salah al-Din Education Directorate at the three administrative levels, and the sample size was (78) individuals from managers, directors of departments, divisions, units, and administrative staff. The research reached several conclusions, the most important of which was the existence of a significant correlation between human resource strategies in terms of their dimensions and organizational agility in the Salah al-Din Education Directorate. In conclusion, he recommended the need to pay attention to providing an appropriate basis for human resources strategies for new operations through making structural changes, strengthening cooperation processes and using appropriate sources in order to advance and maintain survival and continuity and develop agility in the organization.
The repercussions of the Corona pandemic on the audit profession: Challenges and Prospects
Authors: عقاب سليمة , بوفنارة هاجر
Published: March 2024

This study aimed to identify the challenges faced by the auditor in the context of the coronavirus pandemic and the mechanisms adopted to confront them, by answering the problem posed by what are the implications of the coronavirus pandemic on the auditing profession. To achieve this, the analytical descriptive approach was adopted in the study, and a set of results were reached, the most important of which is that the auditor faces many challenges in the exercise of his profession due to increased risks and uncertainty, which hinders the implementation of the examinations and difficulties in obtaining sufficient and appropriate evidence, due to the lack of laws and instructions regulating the profession in such crises, despite the issuance of several publications by international and local professional organizations, which help the auditors to adopt new mechanisms in the exercise of auditing to keep up with the current conditions caused by the pandemic
THE EFFECT OF WORKPLACE INCVILITY ON TURNOVER INTENTION AMONG NURSES: THE CASE OF TURKEY
Authors: Hakan ÖZKAN Ahmet , ÖZDEMİR İsmail
Published: March 2024

The main aim of this study is surveying the relationship between workplace incivility and turnover intention among nurses. This study used a correlation and regression analysis to observe the relationship between workplace incivility and turnover intention. Semi-structured interview technique is used and 163 usable questionnaires were filled together with 163 volunteered nurses. The findings suggested that there is a positive and significant relationship between workplace incivility and turnover intention. The findings of this study will guide the future researchers and the managers who try to keep turnover intention under control in the healthcare industry
THE IMPACT OF DIGITALIZATION ON THE DEVELOPMENT AND SUCCESS OF INTERNATIONAL ECONOMIC ORGANIZATIONS
Authors: KONAK Ali , YAGUBOV Rahib
Published: March 2024

While the opportunities offered by technology to people were very limited in the period before 2000, information technology, which is used as a universal means of progress today, has become an indispensable element of the globalizing world by making it easier to access scientific information. With the increasing level of digitalization, there has been a rapid transformation in technology and it has become extremely difficult to keep up with this transformation. In the 21st century, which is accepted as the digital age, the developments in technology have made human life easier on the one hand, and on the other hand have caused the society to become dependent on technology. In the century we have been living in, international economic organizations have rapidly adapted to the developments in technology and the transformation process and have effectively used the advantages provided by technology to themselves. It is seen that international organizations, especially after the Second World War, have taken on extremely important tasks in terms of shaping international markets. Especially in meeting the funding needs of the international market, international economic organizations play an important role. Along with globalization, some international financial institutions such as the World Bank and the International Monetary Fund (IMF) have been significantly affected by recent rapid technological developments. In this context, thanks to the developments in technology, international financial institutions have had the opportunity to transfer the financial resources under their control to the countries or unions in need easily and quickly. Due to this importance, developments in technology are closely monitored by international economic organizations. With this study, it is aimed to examine the development of international economic organizations in the digitalization process and to evaluate the impact of digitalization on the success of international economic organizations by clarifying both positive and negative aspects by data analysis method
ONE OF THE MANIFESTATIONS OF SEMANTIC DEVELOPMENT IN THE PROPHET'S HADITH
Authors: SALEM ASSAD M.
Published: March 2024

Islam and the intellectual, ideological, and social advancement it brought about had profound influence on the language, changing the meanings of many terms that had not previously been employed. In addition, it dressed up existing words with new meanings that they had not before worn or indicated. The semantic level of language is distinguished by a high degree of change, development, and language transition flexibility as a result of numerous causes that are intimately connected to the lives of nations in all its facets. This study aimed to highlight some of the manifestations in which the noble Prophetic hadith Approaching the historical and descriptive method of language displayed semantic development The importance of the research lies in its purpose and nature as well as what made the language of the Prophet of God, may God bless him and grant him peace, unique in this regard; Included in this are his condemnation of lip service, praise for eloquence, and the creation of terminology to describe Muslim belief, worship, and conduct; Since language is the identity of man and it is his expression, and since man, as they say, is hidden under his tongue and his choice of words is a piece of his mind, so when he speaks he exposes his mind to others, raising it to a lofty level in society and making it a mirror of his great personality, which precedes other non-Muslims
KINDERGARTEN CHILD PSYCHOLOGICAL ATTACHMENT
Authors: Kamel MUHAMMAD Brihan
Published: March 2024

The research aims to identify: The current research aims to identify 1- Psychological attachment among children of Riyadh. 2- There are no statistically significant differences in psychological attachment among kindergarten children according to the gender variable (males and females). 3- There are no statistically significant differences in the attachment of security among kindergarten children according to the variable (kindergarten, pre-school). Based on the findings of the research, the researcher concluded the following: 1 Psychological attachment is the common characteristics of children, and this result indicates that children need tenderness and affection from parents, especially (mother), and this was confirmed by Koverj’s study (1982) and the importance of dealing with children on a moral basis, because dealing with children makes The personality of its members is more stable and balanced, and it implants in the psyche of the child the conscience and morals. 2 There are no differences between the sexes in the behavior of psychological attachment, because children of both sexes need attention and psychological care, especially in Iraqi society. 3- There are no differences between (kindergarten and preschool) in the behavior of psychological attachment, because children of both sexes need to modify behaviors and psychological care.
Comparative analysis of a supercapacitor and Li-ion battery based electric vehicle
Authors: Gupta Nidhi , Mishra Sarvagya , Kumar Samarth , Kamra Rakhi , Gupta Sunil , Gandhar Abhishek , Gupta Saket
Published: March 2024

This paper has simulated an Electric Vehicle (EV) in MATLAB/Simulink environment where Supercapacitors (SC) are compared with Li-ion batteries. Simulated EV is tested under both above discussed scenarios for evaluating its performance under certain speed and torque load conditions. The critical aim of the government or any manufacturing company is to reduce the carbon footprint and provide better living conditions for their people. The major step to achieve this aim is to maximize EV usage. Therefore, it can be attained through the implementation of battery energy storage system. This paper has paved the way towards the goal by showing supercapacitors or Li-ion as energy sorage interms of there performances and recharging time. The inhibition of supercapacitors instead of the currently used Li-ion can turn out to be a game changer as it can be reused which decreases the chances of E-wastage but it has certain limitation. Moreover, supercapacitors are known for having high speed of charge (1000 times faster than Li-ion) that increases the efficiency of the EV.
Estimation of missing data in intuitionistic fuzzy soft matrix (IFSM) with application in MCDM
Authors: Singh Seema , Hooda D. S. , Malik S. C.
Published: March 2024

The theory of fuzzy soft as well as intuitionistic soft set generally depends on complete information. But there are situations in which the complete information is not available due to various different reasons like data erroneous, in sufficiency of data, lacking of evidence and illegibility of data. Missing data restrict fuzzy soft matrix and intuitionistic fuzzy soft matrix and that causes more ambiguous uncertainty in the process of decision making. Thus, estimation of incomplete information data plays an important role in multi criteria decision making process which has been developed recently. Here, a novel method of missing data estimation in intuitionistic fuzzy soft matrix is described. Firstly, we estimate the missing values using the information given in data. After estimation the missing values in IFSM thus obtained is applied in a multi-criteria decision-making problem with illustration by an example.
Opinion mining and machine learning analysis : What emotions twitter data tell us about telemedicine?
Authors: Saylan Busr , Cinaroglu Songul
Published: March 2024

The Covid-19 pandemic has made telemedicine one of the most relevant topics in recent years, so data mining about telemedicine obtained from Twitter offers a unique opportunity. The motivation of this study is to identify the emotional groupings of Twitter data users’ opinions for telemedicine using opinion mining techniques such as Sentiment Analysis combined with high-dimensional data classification and prediction methods. Data was collected from Twitter in August and September of 2021 related to telemedicine and official World Health Organization and World Bank documents for the years 2018 and 2021, respectively. Sentiment Analysis showed that 56.2% (n = 5351 tweets) of the sample had predominantly positive emotions toward telemedicine. Telemedicine, telehealth, and ivermectin are the most frequent words in the word cloud. Twitter data users’ opinions consist of nine mood classes (SIL index = 0.80) and the differences between these classes are statistically significant in terms of positive (p < 0.05), negative (p < 0.05), and neutral (p < 0.05) emotions. Neural Network (AUC = 0.842, F1 = 0.492) and Random Forest (AUC = 0.841, F1 = 0.494) are the best predictors of Twitter users’ mood classes compared with other machine learning techniques. The pythagorean tree generated by Random Forest showed that retweet is the best predictor of Twitter users’ opinions and emotional classes towards telemedicine. Future studies will create big social media datasets for a deep understanding of the emotional classes of individuals towards telemedicine technologies.
Joint determination of quality investment and tolerance under the sampling inspection plan with quality protection
Authors: Chen Chung-Ho , Lee Tzu-Hsien
Published: March 2024

In this study, we present the joint design for process mean, standard deviation, and tolerance. In the first phase, Taguchi’s quality loss and process adjustment cost are used. In the second phase, the quality investment and sampling inspection are addressed with quality protection under the specified capability value and consumer’s risk.
Restricted estimators of repeated measurements model for unbalanced data
Authors: Abdel-Zahra Sarah Abbas , AL-Mouel Abdul Hussein Saber
Published: March 2024

The model of one-way repeated measurements for imbalanced data, as the number of explanations are not the same at some levels, is the subject of this research. We used two methods to estimate the model parameters: the restricted maximum likelihood method and maximum likelihood approach, and we considered some of their characteristics. The Experiment’s practical research goal is to determine how the experimental elements and their interactions affect date palm productivity. The Experiment included the factor of irrigation method with three treatments: drip irrigation, basin irrigation, and the regular tidal method, while the irrigation interval factor included three treatments: 3, 6 and 9 days.
Economic manufacturing quantity model with quality investment
Authors: Chen Chung-Ho , Lee Tzu-Hsien
Published: March 2024

In this article, we propose the modified economic production problem by considering acceptance inspection for obtaining production quantity, mean, and quality investment. One considers unknown mean and known variability under the normal quality. The quality investment function is the declining exponential function of variability. One adopts Taguchi’s loss cost for evaluating quality.
Retailer’s optimal pricing and replenishment policy for new product and buy back policy for used product with price and time dependent demand and shortages
Authors: Katariya Dharmesh K. , Shukla Kunal T
Published: March 2024

The new age consumer, manufacturers and government is aware about the hazardous impact of manufacturing on the environment and limited assets are factors which are considered while buying a product. As an outcome, consumers have demonstrated their enthusiasm to purchase utilized or restored items. We looked at a scenario in this article where a retailer collects and resells old products to customers in addition to selling new products. Detailed formulation and discussion are given to the optimum price and ordering strategies for new products as well as the optimum buyback strategy for used products. The demand of the products is the time and price sensitive. Additionally, Shortages are permitted and there is a partial backlog. Maximizing a retailer’s total profit per time unit while determining the best selling price and quantity to place an order for new products and the best amount to buy back for used products is the objective. The numerical example demonstrates the framework and sensitivity evaluations are carried out on the significant parameters.
Diabetes prediction using feature engineering and machine learning algorithms with security
Authors: Arora Jyoti , Rathee Sonia , Gahlan Mamta , Yadav Amita , Shalu Shalu
Published: March 2024

The prevalence of diabetes has been steadily increasing, necessitating accurate prediction models to assist in early diagnosis and proactive management. In this paper, a hybrid machine learning-based diabetes prediction model has been proposed. To evaluate the model, the dataset was subsequently divided into training and testing subsets. We used the Random Forest Classifier, Light Gradient Boosting Mechanism Classifier, Gradient Boosting Classifier, Logistic Regression, K-Nearest Neighbours (KNN) Classifier, Naive Bayes Gaussian, Decision Tree Classifier, XGBoost Classifier, and Support Vector Classifier as nine different classifiers. Several metrics were used to evaluate the models, including testing accuracy, recall score, F1 score, and precision score. We have evaluated our model on the “Pima Indian Diabetes Database”[1], which served as the main dataset, for diabetes prediction. The proposed model serves as a practical framework for researchers and practitioners interested in leveraging machine learning techniques for diabetes prediction.
A secured image based three factor user authentication system
Authors: Golar Priti , Sharma Rika
Published: March 2024

Graphical User Authentication (GUA) is an image-based password system that leverages the human tendency to remember visuals more effectively. This methodology enables users to effortlessly generate and recall passwords. The three important parameters for any graphical based password system are Usability, Randomness and Security. Usability deals with the system adaptability, memorability, flexibility, User satisfaction etc. On the other side randomness is about Hotspot Coverage, Click Point Clustering, Spatial Patterns, J-statistics etc. This paper is an attempt to initially develop an image-based authentication system that is usable, venerable in terms of randomness. In addition, it is necessary to build a strong security authentication process where the attackers are unable to access the system. The past research study claims the diversity between the usability and security aspect. The focus of this research study is to analyze the impact of various security attacks on the proposed system and the possible solution to avoid them.
MXRFCS : Development of an enhanced multidomain X-ray feature representation model for the detection and classification of COVID severity levels
Authors: Thombre Supriya S. , Malik Latesh , Kumar Sanjay
Published: March 2024

Global healthcare has been under stress due to the COVID-19 pandemic, necessitating effective methods to determine COVID-19 patient severity and distribute resources accordingly. Current COVID-19 X-ray models are either too complicated or too ineffective to employ in real time. This paper introduces a novel method for assessing COVID-19 severity using an enhanced multimodal X-ray model. A strong patient representation is produced by combining demographics, clinical information, and X-ray results. Multidomain features, including frequency, Gabor, Wavelet, and entropy components, are produced from this data. Using this model, a customized neural network is trained to predict COVID-19 severity levels. A dataset of X-ray pictures and clinical information from COVID-19 patients were used to evaluate the model. The suggested model achieves 98.5% accuracy on several datasets, outperforming existing approaches in the identification of COVID-19 severity levels, according to the results. Performance shows promise in terms of accuracy, memory, and latency, supporting early and efficient management of severe COVID-19 cases and thwarting the pandemic without clinical usage.
Natural language processing for drug information extraction : Advancing knowledge discovery in biomedical literature
Authors: Koparde A. A. , Jadhav Pradnya A. , Annie G. Jisha , Goyal Dinesh , Hardas Bhalchandra M. , Mange Purva
Published: March 2024

Natural language processing (NLP) has emerged as an important tool in the biomedical industry for bettering medication information extraction and other knowledge gathering. In this study, we explore the use of natural language processing (NLP) techniques to glean useful insights from massive volumes of biological literature, with the goal of better comprehending data pertaining to drugs. We want to automate the extraction of crucial aspects such drug interactions, side effects, and efficacy by utilizing sophisticated language models and semantic analysis. Effective and comprehensive drug information retrieval will be encouraged. Our innovation improves the drug development process by facilitating the rapid exploration of big databases for previously unknown connections and patterns. By facilitating the synthesis of data from several sources, NLP in biomedical research speeds up information extraction, which in turn accelerates drug development and improves patient care by allowing for evidence-based decision making. This research demonstrates the promising potential of natural language processing (NLP) for unraveling the complexities of drug-related data, ushering in a new era of learning in the biomedical field.
An experiment-based investigation into machine learning for predicting coronary heart disease
Authors: Akoosh Lamiaa Mohammed Salem , Siddiqui Farheen , Zafar Sherin , Naaz Sameena , Alam M. Afshar
Published: March 2024

Extensive inquiry has been conducted to explore potential applications of machine learning methodologies in the realm of cardiovascular disease management. To facilitate a more comprehensive investigation This study explores machine learning algorithms, specifically Support Vector Machines (SVM) and Artificial Neural Networks (ANN), for disease identification, focusing on cardiovascular diseases. Utilizing a Kaggle dataset of around seventy thousand medical records, the research aims to refine methodology and assess performance variations. SVM and ANN techniques are applied to the Kaggle dataset, revealing SVM accuracies of 0.9997 (default), 0.9998 (RBF kernel, C=100.0), and 1.000 (linear kernel, C=1000.0). The Feedforward neural network, using Adam optimization across 50 batches and 10 epochs, achieved perfect accuracy of 1.000.
A review on unveiling the impact of government policies on Rajasthan’s startup ecosystem
Authors: Sharma Devika , Goyal Ruchi
Published: March 2024

This study examines the critical influence of state-led policies on the development and nurturing of the startup ecosystem in Rajasthan, India, underscoring a strategic deployment of initiatives such as the 2015 Rajasthan Startup Policy, the iStart Rajasthan platform, the Bhamashah Techno Fund, and the Digital Rajasthan projects. Aimed at bolstering entrepreneurial ventures through financial backing, regulatory streamlining, incubation support, and digital infrastructure enhancement, these government interventions collectively foster a conducive atmosphere for startups. This investigation reveals the effectiveness of these comprehensive efforts in cultivating an environment that not only stimulates innovation but also ensures startups’ access to crucial resources and generates employment opportunities across a spectrum of sectors. The findings of this review paper highlight the indispensable role of policy frameworks in fostering vibrant startup ecosystems and provide deep insights into the interplay between governmental policy initiatives and the growth of entrepreneurial ventures.
Modified exponential ratio estimator for ranked set sampling in the presence of tie information and application on COVID-19 real data
Authors: Koçyiğit Eda Gizem , Kadilar Cem
Published: March 2024

In this article, we develop the isotonic ratio mean estimator proposed by Kocyigit and Kadilar (2020) within the case of tie information in the Ranked Set Sampling (RSS). In addition, we take into consideration the population size being large and small. We offer a generalized exponential ratio estimator using the modified isotonic estimator for this situation. Simulation results show that the proposed estimator is more efficient than the estimators in the literature. In the real data study, the 34 regions of China since China is the country where the pandemic started are taken as a small population, and the data of 212 countries on a world scale is taken as a large population, then the estimators are calculated. In the real data study, the proposed estimator gives better results than the existing estimators thus the results in the simulation study are similar to the real data study.
The Profit-Sharing System in Financing Islamic Banking
Authors: Syah Danial , Rahmadani Gema
Published: March 2024

Sharia Banking is a business entity that carries out the function of collecting funds from parties with a surplus of funds and then channeling them to parties with a deficit of funds and providing other financial services based on Islamic sharia principles. This article analyzes. This type of research uses normative legal research, using a conceptual approach and a statutory approach as well as the Koran and hadith, primary and secondary.  Legal materials obtained and analyzed qualitatively and then presented descriptively. The article aims to explain in general, the principles of sharia financing business activities include justice ('adl), balance (tawazun), kemashlahatan (maslahah), universalism (alamiyah), and do not contain gharar, maisir, usury, zhulm, risywah, and other haram objects. Financing or financing is funding provided by one party to another to support planned investments, both carried out by themselves and institutions. In other words, financing is funding issued to support planned investments. Law Number 10 of 1998 states that financing based on sharia principles is the provision of money or bills that are equated with it based on an agreement or agreement between a bank and another party that requires the financed party to return the money or bill after a certain period of time in return or profit sharing.
Bridging Communication Gaps: A Literature Survey on Assistive Technologies for Individuals with Disabilities in India
Authors: Aishwarya  , Akshata Chou  , Shruti J. Ingaleswar  , Vaishnavi G. Pattar  , Prof. S. C. Hiremath
Published: March 2024

Communication barriers faced by individuals with disabilities, particularly in India, pose significant challenges to social inclusion and interaction. This paper presents a comprehensive literature survey on existing research and developments in assistive technologies aimed at overcoming these barriers. Focusing on communication aids for the blind, deaf, and mute populations, this survey explores innovative solutions, evaluates their effectiveness, and identifies areas for future research
Computational Model for Regional Languages Interpretation like ChatGPT
Authors: Miss. Pallavi Parma  , Dr. Neeraj Sahu
Published: March 2024

ChatGPT is a language model developed by OpenAI, based on the GPT-3.5 architecture. It is designed for natural language understanding and generation, enabling it to engage in coherent and contextually relevant conversations. With a vast training dataset, ChatGPT can comprehend and respond to a wide range of topics, making it a versatile tool for various applications such as customer support, content creation, and general-purpose chat interactions. Despite its capabilities, ChatGPT may exhibit limitations, including occasional inaccuracies and sensitivity to input phrasing. As of my knowledge cutoff in January 2022, continuous improvements may have been made to enhance its performance., ChatGPT raises numerous ethical and privacy concerns that are meticulously explored in this paper. Acknowledging the current limitations of ChatGPT is crucial in understanding its potential for growth. We also ask ChatGPT to provide its point of view and present its responses to several questions we attempt to answer
Enabling Simultaneous PDF File Access on Android Mobile Device
Authors: Aliza I. Shaikh  , Taiba G. Shaikh  , Madiya R. Kazi
Published: March 2024

Pdf (portable record format) files use is growing each day for college kids, instructors, and for all of us because it's far person pleasant clean to examine, open and proportion.
purpose: This assignment goals to beautify the user experience by means of growing a cell application for Android devices that allows users to open and manipulate a couple of PDF files simultaneously or simultaneously. Our answer leverages Android's sturdy multitasking talents to allow the simultaneous establishing of multiple PDF files within a unmarried app, presenting a unbroken and effective workflow. Key capabilities encompass:
Tabbed Interface: The application presents PDF files in a tabbed interface, allowing users to replace between documents results easily. every tab represents a different PDF document, making navigation intuitive.
report management: The app affords gear for organizing and handling PDF documents efficaciously. users can create folders, rename documents, and perform actions like reproduction, move, and delete. Customization: users can customize the viewing revel in through adjusting settings like zoom degree, page layout, and coloration schemes, making sure a relaxed analyzing revel in. Our assignment addresses the growing need for green PDF record control on Android devices, catering to experts, college students, and anybody who relies on PDFs for his or her daily obligations. by means of imparting a unbroken and function-wealthy answer, we aim to enhance mobile productiveness and convenience in coping with PDF documents. This assignment represents a full-size leap forward in cell PDF file management, imparting Android customers with a versatile and user-friendly device for handling multiple PDF documents simultaneously. whether or not for paintings, have a look at, or entertainment, our application empowers customers to make the most of their Android devices for PDF-related responsibilities
Fusion-Fits: Augmented Reality Based Immersive Platform
Authors: Abhishek Lawhale  , Mehul Shah  , Raghavendra Puranik  , Shubhankar Sonawane  , Prof. Vrushali Paithankar
Published: March 2024

In response to the evolving demands of consumers in the clothing industry, businesses are increasingly focusing on enhancing the online shopping experience through innovative marketing strategies like virtual fitting rooms. These platforms allow users to try on clothes virtually, eliminating the need for physical fitting rooms and streamlining the purchasing process. To optimize this experience, our approach involves extracting the user's social model from a video stream using a coordinate function for precise alignment. This not only ensures an accurate representation of the clothing on the user but also mitigates common ecommerce challenges such as compliance, environmental impact, and return costs. By leveraging advanced technologies, we aim to revolutionize online shopping, providing a seamless and satisfying experience for consumers while addressing industry challenges
Fake Social Media Profile Detection and Reporting Using Machine Learning
Authors: Aniket Agravat  , Umang Makwana  , Sahil Mehta  , Devashish Mondal  , Sushant Gawade
Published: March 2024

Our research focuses on utilizing machine learning techniques, encompassing natural language processing and computer vision, to create an automated system for the detection and reporting of fake social media profiles across various platforms. Our approach involves feature extraction from both textual and visual content, followed by the application of machine learning models to classify profiles as fake or genuine. This system operates in real-time, monitoring user activity and promptly flagging suspicious profiles for user- initiated reporting. By combining the power of machine learning with cross-platform compatibility and user feedback, our solution aims to enhance online safety by swiftly identifying and addressing fraudulent social media profiles, thus fostering more secure and trustworthy online communities.
An Approach Towards Activity Recognition using AI and ML
Authors: Soniya Rajendra Binnod  , Dr. Amit K Gaikwad
Published: March 2024

The study of correctly identifying human actions that are put to various tests is known as "human activity recognition."Human activity is the constant flow of one or more discrete actions that are necessary for advancement. A series of activities in which an individual enters a room, moves ahead, sits down, stands up, etc. is a specimen of human activity. Human activity recognition can be carried out at many abstract levels and has broad applications in the actual world, such as activity-based search, monitoring of critical sites, patient monitoring, etc. the years, researchers, engineers, and students from all across the world have explored the identification of human action.YoloV4 and DarkNet are two computer vision algorithms used in machine learning-based activity recognition that identify the actions that are performed
Redefining Intelligence: The Deep Learning Revolution in AI
Authors: Aman  , Nitin Yadav
Published: March 2024

In the ever-evolving realm of artificial intelligence (AI), deep learning stands as a beacon of innovation, transforming the essence and trajectory of AI systems. This paper ventures into the heart of deep learning’s transformative power, charting its journey from the early neural network concepts to the advanced architectures that propel today’s technological breakthroughs. We delve into the harmonious interplay between deep learning and the surge in computational prowess, amplified by the vast seas of big data, which have jointly propelled AI to unprecedented levels of functionality and societal integration.
Through a tapestry of case studies, we illuminate the tangible applications of deep learning across diverse sectors such as healthcare, finance, and autonomous navigation, showcasing how these intelligent algorithms have not only sharpened efficiency and accuracy but also brought forth pressing ethical dilemmas. The conversation on AI’s ethical landscape, with a spotlight on transparency, accountability, and privacy, emerges as an indispensable facet of conscientious AI evolution.
Peering into the horizon, we ponder the onward march of deep learning, recognizing the promise it holds for awe-inspiring innovation as well as the hurdles that await. The paper underscores the imperative for ongoing inquiry into algorithmic refinement, data morality, and the ecological footprint of AI technologies.
In our closing reflections, this paper celebrates the profound sway of deep learning over AI, with a nod to the indomitable human spirit that fuels technological advancement. It is this fusion of human ingenuity, moral vision, and technical mastery that will chart the course for AI’s future, steering it towards our shared ideals and dreams for a brighter tomorrow
IMPROVING STUDENTS’ SPEAKING FLUENCY THROUGH THE IMPLEMENTATION OF TRIVIA-BASED ACTIVITY ON UNIVERSITY STUDENTS
Authors: M. Afrizal  , Chalil As’ari
Published: March 2024

This article describes a classroom action research held in speaking class through  the implementation of trivia-based activity to improve the University students’ speaking fluency and improve the classroom situation as well. The method used in the reasearch is  collaborative classroom action research which was conducted in two cycles. Each cycle included four stages namely planning, implementing, observing and reflecting. The data that were obtained qualitatively and quantitatively showed that through trivia-based activity could improve: (1) students’ speaking fluency; (2) speaking classroom situation.
INCREASING STUDENTS’ ABILITY IN READING COMPREHENSION THROUGH PQRST STRATEGY (LESSON STUDY BASED FOR THE FIRST YEAR AT SMA N 1 PEUSANGAN)
Authors: Harmita Zaini  , Silvi Listia Dewi
Published: March 2024

The title of this research is increasing students’ ability in reading comprehension through pqrst strategy in lesson study. The objective of this research is: To describe the students’ achievement in reading comprehension by using PQRST strategy at SMAN Peusangan and to know the students’ respond through prediction strategy to the reading comprehension in recount text of grade ten students of SMA N 1 Peusangan. The data collected through the observation sheet, text, and test. This research uses lesson study in the teaching process and this research was done in two meeting. The research subject was the first year students of SMA N 1 Peusangan. The sample of this resarch was were 21 students. The data was collected through the observation sheet, text, and test.The data was analyzed through Quantitative Recount Text in conducting the research. The procedure of lesston study of lesson study: Plan, Do, See. After the researcher was done all the the steps of action the result of students’ means score for the first meeting was 66,90 it does not meets the criteria, then the researcher decide to continue for the second meeting the students’ score was 85 and it meets the criteria of SMA N 1 Peusangan. The finding of the researcher also showed that PQRST Strategy in Lesson Study model can icreas the students’ reading comprehension, it was showed from the result of students mastery recoun text. The result of this study indicate that reading can add insight and new vocabulary, because by reading students would get a lot of new words that were not yet know, therefore reading be able to increase students’ vocabulary and the steps of the PQRST strategy can help students understand the text more easly bisides that students also mindset broad and sharp.