bluuebunny/crossref_metadata_2025_split huggingface dataset:
MANET Hidden and Exposed Terminal - Challenges and Survey
Authors: Hemalatha S. , Patel Nileshkumar , Kumar Ajay , Jain Neelesh Kumar , Narayanan G. Venkat , Manwali Manka , Pallathadka Harikumar , Chinhewadi Rajesh P. 
Published: October 2023

Mobile Adhoc Network (MANET)is a self organized wireless Network which was created to communicate among the nodes without support of the any Infrastructure. While transmission of the packets between the nodes, many challenges the every nodes faces. One of the Major challenges is Hidden and Exposed nodes issues in the MANET. This causes the packet drop or packet failure while the transmitting the packets. Also which reflects in degrades the throughput of the MANET and performance of the MANET nodes when the heavy traffic ,retransmission of the dropped packets delayed the communication. This article discussed about hidden and Exposed terminal problem and challenges in MANET and also dissimilar survey in MANET.
A Review on Software Quality Forensics: Techniques, Challenges, and Limitations
Authors: Sharma Sandeep Kumar , Khaliq Mazhar , Khaliq Mazhar 
Published: October 2023

Software quality forensics plays a vibrant role related to software quality, security, and integrity. The paper aims to derive a software quality forensics model through existing software quality models and their factors. The papers explore quality models, factors, approaches, tools, techniques, and standards regarding software quality investigation and confine the research area for software quality integrity breach forensics. The explore the deviations of quality attributes, standards, factors, and artifacts, it leads to further investigation of root-cause followed by digital evidence procedure for alleged software quality issues. Therefore, there is a need for a software quality forensics model and dedicated standards to fulfill the digital evidence procedure validation, satisfiable, and prosecution in the court of law in the context of alleged or illegal activity investigation quality of software. The paper has derived the techniques, challenges, and limitations of software quality forensics based on the review of research questions.
Recognition and Evaluation of Heart Arrhythmias via a General Sparse Neural Network
Authors: Sanamdikar Sanjay , Waghmare Surendra , Patil Satis , Patil Dipak , Borawake Madhuri , Suryatal Baban 
Published: October 2023

In clinical use, an electrocardiogram (ECG) is an essential medical tool for assessing heart arrhythmias. Thousands of human beings worldwide are affected by different cardiac problems nowadays. As a consequence, studying the features of the ECG pattern is critical for detecting a wide range of cardiac diseases. The ECG is a test which assesses the intensity of the electrical impulses in the circulatory system. In the present investigation, detection and examination of arrhythmias in the heart on the system using GSNNs (General sparsed neural network classifier) can be carried out[1]. In this paper, the methodologies of support vector regression(SVR), neural mode decomposition(NMD), Artificial Neural Network (ANN), Support Vector Machine(SVM) and are examined. To assess the suggested structure, three distinct ECG waveform situations are chosen from the MIT-BIH arrhythmia collection. The main objective of this assignment is to create a simple, accurate, and simply adaptable approach for classifying the three distinct heart diseases chosen. The wavelet transform Db4 is used in the present paper to obtain several features from an ECG signal. The suggested setup was created using the MATLAB programme. The algorithms suggested are 98% accurate for forecasting cardiac arrhythmias, which is greater than prior techniques.
Robust Brain Tissue Segmentation in AD Using Comparative Linear Transformation and Deep Learning
Authors: Latha Vunnam Asha , Namburu Anupama 
Published: October 2023

As a progressive neurological disease, Alzheimer's disease (AD), if no preventative measures are taken, can result in dementia and a severe decline in brain function, making it difficult to perform basic tasks. Over 1 in 9 people suffer from dementia caused by Alzheimer's disease and require uncompensated care. The hippocampus is extracted from MRI scans of the brain via image segmentation have been useful for diagnosing Alzheimer's disease (AD).The segmentation of the CSF region in brain MRI is critical for analyzing the stages of AD. The extraction of Hippocampus from an MRI of the brain is greatly influenced by the contrast of the images. Using comparative linear transformation in the horizontal and vertical dimensions as well as statistical edge-based features, this article proposes a robust method for segmentation technique for the extraction of Hippocampus from brain MRI. These transformations aid in balancing the brain image's thin and dense fluid extractions. Through use of the ADNI dataset, the proposed approach had a 99% success rate in segmentation.
Deep Learning Frameworks for Cardiovascular Arrhythmia Classification
Authors: Malleswari Pinjala N. , Padala Srinivas , Pullarao Matta Venkata , Sankar M. Ravi , Mounika Y. 
Published: October 2023

Arrhythmia classification is a prominent research problem due to the computational complexities of learning the morphology of various ECG patterns and its wide prevalence in the medical field, particularly during the COVID-19 pandemic. In this article, we used Empirical Mode Decomposition and Discrete Wavelet Transform for preprocessing and then the modified signal is classified using various classifiers such as Decision Tree, Logistic Regression, Gaussian Naïve Bayes, Random Forest, Linear SVM, Polynomial SVM, RBF SVM, Sigmoid SVM and Convolutional Neural Networks. The proposed method classify the data into five classes N (Normal), S (Supraventricular premature) beat, (V) Premature ventricular contraction, F (Fusion of ventricular and normal), and Q, (Unclassifiable Beat) using softmax regressor at the end of the network. The proposed approach performs well in terms of classification accuracy when tested using ECG signals acquired from the MIT-BIH database. In comparison to existing classifiers, the Accuracy, Precision, Recall, and F1 score values of the proposed technique are 98.5%, 96.9%, 94.3%, and 91.32%, respectively.
An Open-Source Platform for Real-Time Preliminary Diagnosis amongst Adults using Data Analytics
Authors: Sharma Kalpana , Sharma Sital , Dhimal Sunil , Sen Biswaraj , Pradhan Ashis , Singh Vikash Kumar 
Published: October 2023

Depression can be defined as a mental health disorder characterized by persistently depressed mood, loss of interest in activities, causing significant impairment in daily life. Technical intervention to screen depression in non-clinical population which records, classify depression on the basis of severity and provide features or predictors that discriminate the classification of depression among non-clinical population comprising of college students is the main area of the study. Beck Depression Inventory – II (BDI-II), as per Diagnostic and Statistical manual of Mental disorder (DSM IV) is used to screen depression and its severity. Indicators are determined on the basis of how well the features or predictors can discriminate the classes of depression severity. Providing quality indicators which help in supporting the process can be considered as symptoms for screening depression. Descriptive analytics is used in order to find the underlying pattern of the responses captured, factor analysis groups variables on the basis of correlation between patterns of the responses to reduce dimension. The approach for supervised descriptive analysis method that takes BDI-II questions as features and refine the features using information gain and linear discriminant analysis as feature selection algorithm. The classification of severity of depression is done using Support vector machine (SVM)..
Arabic Text Summarization Challenges using Deep Learning Techniques: A Review
Authors: Souri Adnan , Achhab Mohammed Al , Mohajir Badr Eddine El , Naoum Mohamed , Hichami Outman El , Zbakh Abdelali 
Published: October 2023

Text summarization is a challenging field in Natural Language Processing due to language modelisation and used techniques to give concise summaries. Dealing with Arabic language does increase the challenge while taking into consideration the many features of the Arabic language, the lack of tools and resources for Arabic, and the Algorithms adaptation and modelisation. In this paper, we present several researches dealing with Arabic Text summarization applying different Algorithms on several Datasets. We then compare all these researches and we give a conclusion to guide researchers on their further work.
Survey of Deep Fake Creation Technologies and Deep Fake Detection using LSTM
Authors: Pant Shilpa , Gosavi Chhaya 
Published: October 2023

Artificial intelligence known as Deep Fake is one of many techniques that have been successfully developed in recent years for altering faces in images and videos. It can produce convincingly faked images, audio, and video. Deep Fake can create problem, especially when there is a media component involved. Even if it is helpful, when it is used maliciously, such as for disseminating fake news or cyber bullying, it can pose a threat to society. It is necessary to develop a complete fake detection method to handle such issues. Too far, numerous methods have been developed to distinguish between authentic and fraudulent videos.
The objective of this work is to give a summary of different approaches for Deep Fake creation and to provide an overview of LSTM algorithms for deep fake video detection.
Cross-Layer Optimization on Different Data Rates for Efficient Performance in Wireless Sensor Network
Authors: Anju Anju , Bindal Amit Kumar , Bhatia Sukhwinder Kaur , Narang Pravin , Kumar Ajay , Saini Mehak 
Published: October 2023

The traditional protocols used in wireless sensor networks adhere to stringent layering approaches, which decreases the performance of the quality of service (Quality of Service) metrics. As per specifications 802.15.4, wireless sensor networks are inexpensive and energy efficient. It is essential for evaluating the performance of WSNs. Researchers have looked into the fundamental aspects of a single physical layer and the medium access control (MAC) layer protocol using methodologies calculated using several mathematical models or experimental approaches, respectively. In this research, we offer an improved cross-layer analytical model that utilises a thorough combining and interacting of a Markov chain model of the MAC layer's propagation with a model of the PHY layer's propagation. This combination and interaction are described in detail. Various Quality of Service (quality of service) statistics are presented and evaluated, and a cross-layer effectiveness degradation study is conducted under different inputs of multi-parameter vectors. Other parameters, such as Average Wait Time, Reliability, Failure Probability, and Throughput, have been estimated from the simulation results and contrasted with standardised models. The cross-layer model provides a more thorough performance study with various cross-layer parameter sets, some of which comprise distance, power transmission, and offered loads, among other things.
Phytochemicals & Pharmacological activity of Xanthium strumarium: An Updated Review
Authors: Trivedi Swati , Gupta Vishal , Tiwari Gaurav , Manigaunha Ashish 
Published: October 2023

Therapeutic plants are of extraordinary worth in the field of treatment and fix of infections. Throughout the long term, logical examination has extended our insight into the compound constituents of the therapeutic plants, which decide the restorative properties. The purpose of this paper is to summarize the progress of modern research, and provide a systematic review on the traditional usages, phytochemistry, pharmacology of the X. strumarium. Plant parts like leaves, organic product, bark and seed have been accounted for having antidiabetic, antiulcer, calming, invulnerable modulator and pain- relieving movement. This survey tends to the tentatively validated realities and furthermore proposes the requirement for research on substance and pharmacological properties of Xanthium strumarium.
Eco-Friendly Stability Indicating HPLC Method for Estimation of Elbasvir and Grazoprevir by Quality by Design Approach
Authors: Bhangale Charushila , Somwanshi Sachin , Kotade Kiran , Gaikar Mayur 
Published: October 2023

Introduction: The pharmaceutical industry faces a significant problem as a result of the worldwide requirement to modify processes in order to comply with the green analytical chemistry (GAC) requirements. An enormous amount of organic hazardous waste is produced by high-performance liquid chromatography (HPLC), one of the methods employed the most frequently at different stages in the pharmaceutical sector. Aim: To develop analytical quality by design-aided stability indicating green high-performance liquid chromatography (HPLC) method for estimation of Elbasvir and Grazoprevir in a dosage form. Material and Methods: The critical chromatographic factors were the % of ethanol in the mobile phase, flow rate, and their overall effect on the responses like asymmetry, theoretical plates, and resolution were studied to optimize the method. Green analytical chemistry (GAC) has mainly focused on developing analytical methods that are safe for the environment. Therefore, it is imperative that the GAC principles be applied in pharmacological analysis. A rotatable central composite design was employed, and the optimized conditions for chromatographic separation were made with a run time of 5 minutes using Zorbax C18 column (4.6× 150 mm, 5 µm) with 0.1% Trifluoroacetic acid and ethanol (40:60 v/v) as components of a mobile phase, flowing at a rate of 1.0 ml/minute. Photodiode array detection was carried out at 253 nm. Results: The retention time was 1.8 min for EBS and 2.84 min for GZP. According to the ICH guidelines, the proposed method was validated and stress studies revealed that Elbasvir and Grazoprevir are prone to acidic, basic, and oxidation stress conditions. An analytical eco-scale score evaluated the greenness profile and a software-based evaluation. Conclusion: The developed HPLC method is eco-friendly and shall be adopted in the routine quality control of Elbasvir and Grazoprevir in a tablet dosage form.
A schwannoma of superficial radial nerve in hand mimicking a masquerading subcutaneous lipoma-a very rare case report
Authors: Bhat Tanveer Ahmad , Alokaili Hisham , Alkadi Renad O. , Altamimi Abdulla S. , Mirza Mohammed Y. 
Published: October 2023

Schwannoma also called neurilemmoma are benign tumours arising from Schwann cells. Schwannoma of superficial radial nerve is very rare. We report a 22 years old female who presented with a painless swelling on the dorsum of the hand simulating clinically a lipoma. Excision of the swelling was performed and on histopathological examination it proved to be Schwannoma. So, while dealing with any lump over dorsum of the hand in the distribution of superficial radial nerve Schwannoma should be kept in mind as one of the differential diagnoses and proper radiological evaluation before excision of swelling should be routinely done followed by histopathological confirmation and immunochemistry.
Beyond conventions, medication-induced organ damage: exploring a case of gangrenous cholecystitis in a healthy young adult male on fluoxetine and amphetamines
Authors: Sneed Christina C. , Louis Martine A. , Gratsinsky Denis , Cervellione Kelly 
Published: October 2023

Acute cholecystitis occurs in 1 to 2% of patients with gallstones, with 2 to 20% progressing to gangrenous cholecystitis (GC). Within the realm of acute cholecystitis, GC presents itself as a formidable challenge, with a higher mortality rate (15 to 50%) compared to uncomplicated cholecystitis (3%) and elusive preoperative diagnosis. Traditionally observed among the elderly population burdened by comorbidities, GC's emergence in younger patients with no apparent risk factors sets the stage for intriguing exploration. Our case report involves a healthy young adult male on fluoxetine and amphetamines, introducing the potential of medication-induced ischemia leading to the development of GC.
ALTERNATİF BİR YÖNTEM OLARAK KATILIMCI ÖĞRENME: ÇOCUKLARLA KENTSEL MEKÂN ÜZERİNE GERÇEKLEŞTİRİLEN YARATICI UYGULAMALAR
Authors: YILMAZ Ayşe , DEMİRAL Seran 
Published: October 2023

Bu makale, çocukluk sosyolojisi alanından yola çıkarak çocukların toplumdaki sosyal aktörler olduğu düşüncesi çerçevesinde katılımcı öğrenmenin olanaklarını çocuklarla gerçekleştirilen yaratıcı yöntemler aracılığıyla araştırmaktadır. Kentsel mekân deneyimlerine odaklanan çalışma, çocukların öğrenme süreçlerini okul mekânının dışına taşıyarak geleneksel öğrenme yöntemlerine bir alternatif sunma amacı taşır. İstanbul’da bir ortaokulda farklı sınıflarda eğitimlerini sürdüren gönüllü öğrencilerle gerçekleştirilen araştırma kapsamında çocukların kent mirası, kültürel miras, kamusal alan ve çevresel konulardaki görüşlerini ortaya çıkarmak hedeflenmektedir. Kültür mirası kavramını, kuşaktan kuşağa aktarılan bütün etnografik bileşenleriyle ele alan bir anlayış çerçevesinde, araştırmacılar bir sivil toplum kuruluşuyla iş birliği içerisinde çocuklarla haftalık periyotlarla bir araya gelerek yaratıcı metodolojiler aracılığıyla alternatif bir yöntem olarak katılımcı öğrenme süreci deneyimlemişlerdir.
Araştırma boyunca, yaşları 10 ile 14 arasında değişen 35 çocukla kent yürüyüşleri, müze ve park ziyaretleri; kentsel ve ekolojik mirasın çeşitli boyutlarını tartışma amacıyla görsel üretimler ile drama süreçleri; çocukların liderliğinde video-performanslar ve bütün bunlar odağında eleştirel düşünmeye dayalı “çocuklar ile felsefe” tartışmaları gerçekleştirilmiştir. Çocukların bireysel ve sosyal gelişimlerini desteklemeyi hedefleyen araştırma kapsamında İstanbul’un çeşitli mekânlarında, sanat odaklı aktiviteler ve dijital uygulamaların araçsallaştırılmasıyla kültürel miras konusu çocuklarla farklı yönleriyle tartışılmış, katılımcılar bireysel ve kolektif olarak eleştirel düşünme ve yaratıcı üretime teşvik edilmiştir. Bu çalışma, kentsel mekânda çocuklarla katılımcı öğrenme örneği teşkil etmesinin yanı sıra sosyoloji alanında çocuklarla birlikte araştırma gerçekleştirmenin olanaklarını ortaya koymaktadır.
Transfer pricing in Indonesia: Do managers still utilize it as an effective strategy?
Authors: Larasati Nadifa Vicri , Arieftiara Dianwicaksih 
Published: October 2023

This research aims to find out and analyze the effect of the bonus mechanism, tunneling incentive, and exchange rate on company decisions to perform transfer pricing practices in 35 manufacturing and mining sector companies listed on the Indonesia Stock Exchange for the 2018–2020 period. The population of this research is used in the manufacturing and mining sectors listed on the Indonesia Stock Exchange (IDX). This research is a type of quantitative research using secondary data in the form of the company’s annual report and financial statement. The Random Effect Model (REM) with panel data regression was used in this study using STATA version 16. Based on the test results and analysis, it can be concluded that the bonus mechanism has a significant positive effect on transfer pricing, the exchange rate has a significant negative effect on transfer pricing, and the tunneling incentive has no effect on transfer pricing.
Bidirectional and cross-lag relationship between social media use and psychological wellbeing: Evidence from an Indian adolescent cohort study
Authors: Maurya Chanda , Dhillon Preeti , Sharma Himani , Kumar Pradeep 
Published: October 2023

Abstract
Introduction: In an online era like today, the relationship between social media and depression among adolescents and young adults is erratic and still continues to be a debatable subject. The study aims to examine the association and bi-directional relationship between social media usage and depressive symptoms among the adolescent boys and girls in India.
Methods: The study uses data from two waves of Understanding the Lives of Adolescents and Young Adults (UDAYA) project survey conducted in two Indian states of Uttar Pradesh and Bihar. Depression was measured by a Patient Health Questionnaire. Logistic regression has been used for analyzing the data comprising the same time period, whereas the bidirectional relationship between two time periods has been evaluated by Cross-Lagged Path Model.
Result: Findings suggest that the percentage of moderate depressive symptoms increased from 1.7% to 3.0% from Wave 1 to Wave 2. Depression among adolescent girls increased slightly from wave 1 to wave 2 whereas a slight decrement was noticed in the moderate form of depressive symptom among adolescent girls using social media for the two waves. Socioeconomic factors like education, age, gender played an important role in affecting depression among adolescents in both the Wave of the survey. The path relationship reveals that social media users in Wave 1 [β=0.22, p<0.001] were positively associated with social media users in Wave 2. Similar patterns were observed for depressive symptoms at both the waves of the survey. However, cross lagged relations between social media use and depression could not be established between the survey periods.
Conclusion: A significant degree of association was found between social media use and depression among adolescent boys and girls in the study. The present study concludes that factors like age, gender and education showed significant relationships with social media use and depression.
Effect of ultrasonic-assisted organic acid washing on heavy metals and nutrients in tannery sludge
Authors: Li Ziran , Wu Yonggui , Lu Hongpei , Luo Youfa , Wang Ziqi , Qiang Yibin , Liu Zhongjuan , Yang Hao 
Published: October 2023

Abstract
The rapid growth of the tannery industry has led to an increasingly serious problem of how to treat tannery sludge. Washing, which is an effective method for remediating polluted sludge, requires suitable washing reagents. In this study, the removal of heavy metals by washing tannery sludge with three organic acid reagents, namely citric acid (CA), oxalic acid (OA) and tartaric acid (TA), was investigated. The influences of washing reagent concentration, pH, solid‒liquid ratio, and ultrasound assistance on the removal of heavy metals were also analysed. When the optimal single-factor test was satisfied, the removal rates of Cr, Zn and Pb reached 49.11%, 63.74% and 31.88% for CA, 66.25%, 56.72% and 10.44% for OA and 32.79%, 67.53% and 18.34% for TA, respectively. The use of ultrasound-assisted organic acid treatment for heavy metal removal significantly improved the washing efficiency and shortened the reaction time. Moreover, tannery sludge washed by CA, OA and TA, in which the residual heavy metals are less likely to mobile and less harmful to the environment. In addition, the pH and ammonium nitrogen (AN) and rapidly available potassium (AK) contents of the washed tannery sludge decreased, while the organic matter (OM) and available phosphorus (AP) contents increased. The results showed that CA, OA and TA are effective washing reagents and that the washed sludge has the potential for resource utilization.