bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Factors Influencing Students Interaction During COVID 19 in the Faculty of Language Studies at Sohar University: A Qualitative Case Study
Authors: AL-Maktoumi, Halima Ali Sulaiman 
Published: December 2023

This study aimed at investigating the factors influencing interaction in the Faculty of Language Studies at Sohar University. The sample of this study was selective. It included all students who study translation in level two in the Faculty of Language Studies in the academic year 2021/2022. The researcher applied instruments which were focus group interviews via interviewing students and recording videos, individual interviews. In addition, the researcher measured all types of validity, descriptive, interpretative, theoretical and evaluation.
Furthermore, the reliability of the study was confirmed by repeating interviews several times and the reseracher used ATLAS to analyse collected data. The results revealed that there are different factors influencing interaction which are class size, teaching experiences, skills, methods and various psychological issues. Regarding the factors which are influencing students’ interaction, the results support the presumed Constructivism Theory so, it recommends improving online teaching and providing students with all their needs as this will lead to better class interaction during Covid 19. The study recommends providing the lecturers with training; for example, providing the lecturers at Sohar University with adequate professional trainings and professional development sessions that consolidate and improve their online teaching skillsto expand their experiences during this crisis and for future sudden changes in learning. In addition, the study recommended to cover all students’ needs by conducting intensive advising sessions that support the students’ interaction, psychology and perspectives of realizing things that are surrounding them in the classrooms’ atmosphere.
 The Challenging Facing City Council, as a Democratic Institution, in Iran towards Sustainability: a Case Study of Mahmoodabad, Mazandaran
Authors: Farzaneh Hamideh 
Published: December 2023

Introduction: This study focuses on city councils as public, democratic, and participatory institutions to identify the key challenges and barriers faced by democratic organizations towards full democracy. It also discusses the role of democratic institutions in fostering societal movement toward democracy and building a more sustainable society and city.
Methods: It is a qualitative study with semi-structured interviews with council members from different cities in Iran, focusing on council challenges, local management, participation, the role of citizens; and exploring selected documents from Mahmoodabad City Council.
Results and Conclusions: The results highlight the serious and complex problems that city councils in Iran face, particularly concerning the application of democratic principles and values. Iran has a long path ahead to establish democratic institutions and internalize democratic principles among citizens. It appears that Iran, like other developing societies, require non-political mechanisms and a committed atmosphere to guide society toward a democratic direction. Society must focus on guidelines to introduce strategies for individual and collective citizen actions to embrace democratic values and build a more sustainable society.
Awareness about Physiotherapy in Rural Population that it can be Primary Mode of Practice without Needing a Referral: - A Survey Study
Authors: Mandar Malawade K. Arundhati Shivaprasad, 
Published: December 2023

Background- A physiotherapist is a primary contact practician and patients can have direct access to their treatment. Direct access signifies that an individual can refer themselves to a physiotherapist without any consultation from another health professional. In India, physiotherapy is majorly a secondary contact profession that is because of lack of awareness regarding health education and physiotherapy profession. However, the condition is improving in recent years.
Methodology- A sample size of sixty patients were taken for this study. Self-made questionnaire was made and this was completed by participants who were willingly participating in this.
Result- According to the survey conducted based on the sample size it was found out that most of participants consulted a Physiotherapist on the advice of a Physician and they are not aware that physiotherapy consultation can be taken directly.
Conclusion- Physiotherapy can be your go-to option for treatment without needing a referral. You can directly access the services and take control of your health journey. It’s all about empowering yourself and getting the care you need. Rural population are not aware about this.
Gaussian Harris Hawks Optimizer (GHHO) Based Cluster Head Selection (CHS) And Enhanced Energy Harvesting Clustering (EEHC) Protocol for WSN
Authors: L. Lakshmaiah, Dr. K Raja, Dr. B. Rama Subba Reddy  
Published: December 2023

Designing routing protocols for Energy Harvesting- Wireless Sensor Network (EH-WSN) has two key challenges like improving harvested energy utilization and examination harvested energy utilization. However, the clustering and routing phases of the clustering-based routing protocols employed in EH-WSN need a lot of message overhead. Cluster Head Selection (CHS) is a crucial component of clustering that improves energy efficiency. An Enhanced Energy Harvesting Clustering (EEHC) protocol with two phases for cluster setup and data transmission is presented in this research. Sensor nodes are grouped into clusters during cluster construction, and CHS using the Gaussian Harris Hawks Optimizer (GHHO) algorithm is used for data transmission. Hawks chasing behaviours serve as the search agent in the GHHO algorithm, while prey serves as the ideal CH position. Data from each cluster node is collected by CHS, which then sends the aggregated data to the base station. Following CHS, connecting Cluster Member (CM) to a suitable CH is done using a variety of factors like energy, distance to neighbours, distance to the Base Station (BS), node density, and Signal-to-Noise Ratio (SNR). Each CM awakens during its designated working time slot during the DT stage, and transfers the data it has gathered towards the CH of the same cluster. A mobile sink is employed to enhance network performance and relay transmission distance is changed to match the amount of gathered energy. Residual Energy (RE), Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), Network Lifetime, and average delay are metrics used to measure the results of clustering methods.
A Study on Assessment of Noise Levels in Various Construction Activities
Authors: Damaraju Lakshmi Lavanya, T. Usha Madhuri  
Published: December 2023

Construction industry is one of the occupational hazardous workplaces. Most of the construction activities are involved with various risks, prone to occupational hazards. Noise is a physical hazard, resulting from simple headache to permanent hearing loss. Noise is not only confined to work involved but also involves surrounding activities like traffic, commercial activities of the construction sites. Each construction activity is associated with various tools, machinery, producing moderate to severe noise. Workers are exposed to repeated noise levels during worktime. The present study is to identify the machinery and tools producing high noise levels, calculating the average noise exposure levels, the dose levels pertaining to time weighted average levels during high work time. The survey, interview, observation based method adopted in collection and analysing the data .A collective number of noise levels were measured using Noise meter during the study . Ms excel sheet was used to analyse the dose levels and Time weighted average (TWA) . Construction activities exceeding the OSHA standards 85 dB, identified as noise hazard. Analysis concluded that concrete pouring activity produces a noise of 90 dB, exceeded the OSHA limit and carpentry activity just exceeds the limit. Based on survey 44.4% of the construction workers are responded as construction noise is not tolerable and 61.1% are not showing interest towards wearing of PPE.
Evaluation of Responsive With Big Data Technologies
Authors: Ashif Ali, Dr. Nisarg Gandhewar  
Published: December 2023

The volume of produced digital data & everyday usage is increasing as a result of rising man-machine interaction, process automation, and falling hardware and software costs.
The vast amount of digital information produced per second worldwide in unstructured, structured, and semi-structured formats is referred to as big data in this context.
Big data analytics is a new topic that has inspired researchers all over the world to create, develop, and implement a variety of mechanisms, technologies, architectures, and areas for evaluating the enormous amount of data created every day. Traditional database management systems struggle to make sense of the massive amounts of data that make up "big data." The paper describes a few analyses, including word count, sentiment analysis, and responsive analysis.
Responsiveness is crucial for improving the system, identifying vulnerabilities, and ensuring that tasks are distributed fairly. Responsive is important data that can be used for making wise decisions.
Responsive is significant for both strengths and weaknesses, not just when it identifies flaws. If the responsive analysis is performed incorrectly, the analysis's conclusion will likewise be incorrect. As a result, the system as a whole will be inaccurate because the pattern that was discovered will also be incorrect. We will utilize the Map-Reduce framework to create this suggested system for responsive analysis, and Hadoop will be used for storage.
Crime Classification Using GRU and 1CNN Techniques
Authors: S. Jeya Selvakumari, V. Joseph Peter  
Published: December 2023

Criminal activity is a widespread social problem that affects a nation's standard of living, rate of economic development, and international standing. Numerous crimes have proliferated worldwide in recent years. It has a variety of effects on people of all types. Classification of crime is necessary to create a safe society. Many researchers classify the crimes using machine learning techniques with a common dataset, which presents numerous computational opportunities and challenges. Using the learning capabilities of several deep learning architectures, we are trying to classify the criminal activity from the real-time dataset of particular city. In the proposed work, Gated Recurrent Unit (GRU) and Convolutional Neural Network (1CNN) deep learning architecture are used for crime classification. We have conducted performance comparison for classifying the crime with real-time dataset. The effectiveness of the aforementioned deep learning models was assessed by Training and Validation Loss curve. It was discovered that 1CNN models achieve better result compared to GRU. 1CNN produced 97% accuracy.
Direct Marketing Of Banks And Its Effects In Corporate Clients
Authors: Harsan Thambi. N.J., Dr. G. Jones Green  
Published: December 2023

Banks use direct marketing as a tactic to attract and retain profitable business relationships with its customers. Direct marketing in this sense comprises a broad variety of customized communication tactics, such as one-on-one interactions, specific offers, and a wide range of monetary goods and services. The importance of direct marketing by banks to corporate customers is highlighted in this study as it is investigated over a wide spectrum.
This abstract presents a summary of the most important components of direct marketing in corporate banking based on a survey of the relevant literature. It highlights the importance of direct marketing in attracting new business and maintaining relationships with current customers. It also discusses the benefits and drawbacks of digital transformation, with special emphasis on data protection, ethical issues, and the evaluation of campaigns' success.
Dense Convolution Neural Network for Automated Diabetic Retinopathy Detection
Authors: K. Geethalakshmi, Dr. V. S. Meenakshi  
Published: December 2023

Diabetic Retinopathy is a diabetes complication due to uncontrolled levels of glucose in the body which leads to abnormality in the eyes which owing to distortion in the retina and leading to permanent damage of the eye or vision losses. Hence identification and classification of diabetic retinopathy through manual observation is a challenging process due to composite boundaries and features with a high degree of intraclass variation and a low degree of interclass variation.
Unsupervised machine learning algorithms have been used to classify diseases automatically based on the appearance of lesions and their characteristics. These models require more processing time and less reliability. It has been proposed that deep learning architecture can overcome these limitations as it is more efficient and accurate at detecting the lesion’s features.
The novel dense convolution neural network has been proposed with preprocessing, segmentation, feature extraction and classification steps. Laplacian filter and CLAHE techniques have been used in a preprocessing step. The region growing algorithm, Principal Component Analysis and Dense CNN have been used for segmentation, Feature extraction and classification of DR lesions. Furthermore, the proposed model was compared with conventional classifiers in terms of Accuracy parameters. The proposed model achieves 97.88 % of Accuracy. It improves computing efficiency and minimizes network complexity. Hence the proposed model can accurately detect the lesions in the retinal fundus images.
Reputation-Based Opportunistic Routing Protocol Using Q-Learning For Manet Attacked By Malicious Nodes: A Survey
Authors: P. Saranya, Dr. A. Nithya  
Published: December 2023

Mobile Ad-hoc Networks (MANETs) have emerged as a viable paradigm for creating dynamic communication between mobile nodes in the absence of a permanent infrastructure. However, since MANETs are inherently decentralized and self-organizing, they are vulnerable to a variety of security concerns, especially when hostile nodes seek to interrupt communication and undermine network operations. As a consequence, developing efficient and robust routing protocols is critical to ensuring dependable and secure data transmission in MANETs. This review study gives an in-depth look into Reputation-Based Opportunistic Routing Protocols (RORPs), which use Q-Learning methods to improve MANET resistance against malicious node assaults. We provide a thorough study of current RORPs, delving into their core design ideas, underlying processes, and comparative performance evaluations. We begin with a comprehensive introduction to the fundamental concepts, issues, and security risks associated with MANETs. Following that, we explore the concepts of reputation-based routing, emphasizing the need of reputation management in discriminating between malicious and genuine nodes. The review then goes into further detail on the incorporation of Q-Learning methods into RORPs, emphasizing on how reinforcement learning mechanisms may adaptively change routing choices depending on the developing network state and the dynamic reputations of participating nodes. This article reviews 38 research papers of opportunistic routing protocol and explores the potential of computer-assisted methods for MANET. We next divide the studied RORPs into categories depending on their approach to reputation computation, learning algorithms, and cooperative enforcement methods. Furthermore, we analyze their strengths and weaknesses in terms of resilience to different sorts of attacks, as well as their influence on network performance measures including packet delivery ratio, end-to-end latency, and throughput.
Nonlinear Static Analysis of Building with Different Aspect Ratio
Authors: Sumit Tak, Dakshata Garg  
Published: December 2023

The earthquake resistant design of structures requires that systems ought to maintain, adequately, any ground motions of an depth that would arise for the duration of their construction or in their regular use. However floor motions are unique inside the consequences they have got on structural responses. The most accurate evaluation method for structures subjected to strong ground motions is the time history analysis . This evaluation entails the integration of the equations of motion of a multi-degree-of-freedom system, MDOF, within the time domain the usage of a stepwise answer which will constitute the real reaction of a structure. This technique is time-eating even though for application in all sensible functions. The necessity for faster techniques that could make certain a dependable structural assessment or design of structures subjected to seismic loading brought about the pushover analysis.
Pushover analysis is based totally on the belief that systems oscillate predominantly inside the first mode or inside the decrease modes of vibration at some stage in a seismic occasion. This ends in a reduction of the multi-degree-of-freedom, MDOF machine, to an equivalent single-degree- of-freedom, ESDOF gadget, with properties expected by a nonlinear static evaluation of the MDOF system. The ESDOF device is then eventually subjected to a nonlinear time- history analysis or to a response spectrum analysis with consistent- ductility spectra, or damped spectra. The seismic demands calculated for the ESDOF device are converted through modal relationships to the seismic demands of the MDOF machine.
The objective of this thesis record is to emphasise the use of non-linear static procedure i.e pushover analysis a seismic overall performance assessment of R.C frames .
Effect of yoga on stress, hyperactivity and inattention of government school students in Andhra Pradesh
Authors: Dr. R. Rajeswari, B. Uma Maheswari  
Published: December 2023

Introduction: School days are memorable one, where young people will be prepared to face the adult world with education of morals and attitudes. So many students put their wellness to achieve good marks, ranks and degree, hence stressed. Yoga is an exercise that can be performed by balancing the elements of the body. In this study we examined the impact of yoga and meditation on stress, hyperactivity and inattention of engineering college students.
Method: A total of 100 students are randomly selected whosr age limit is between 13-15 years. These subjects were divided into two groups, yoga group and control group. The data is collected with the questionnaires and analysed.
Results: There were no significant differences in pre test of perceived stress, hyperactivity and inattention between the two groups. The interaction of group and time was not significant in predicting the slope of change in perceived distress. Pairwise t-tests did not show a significant reduction in perceived distress for either group. There was no significant interaction in hyperactivity and significant interaction in inattention of group and time. Pairwise t-tests demonstrated a significant reduction in hyperactivity and inattention for the yoga group but not the control group.
Conclusion: Yoga may improve attention and hyperactivity for the students of government school.
Characterization of Al 5052 Based Metal Matrix Composites Reinforced with SiC and Al2O3
Authors: Mallaradhya H. M., Shridhar Deshpande Mohan V., N. B. Doddapattar, 
Published: December 2023

When compared to traditional aluminium alloys, composites made of aluminium display several material characteristics, including enhanced stiffness, wear resistance, specific strength, vibration dampening, and a lower coefficient of thermal expansion. Non-metallic reinforcement aluminium matrix composites, which have advantages over the base material typically include and preferred SiC& Al2O3 as reinforcements to enhance the desired mechanical qualities. Vertex stir processing (VSP) is a novel technique used to produce hybrid composite to improve mechanical properties and microstructure refinement. In this investigation work the fabrication of all Al5052 aluminium hybrid composite was done by VSP method. An effort has been made to look at the impact of SiC& Al2O3 reinforcing elements in an Al5052 matrix. Three combinations of composites had been prepared with different % wt of reinforcements. The microstructural alterations were examined using scanning electron microscopy (SEM).Using a Brinell hardness tester, the microhardness of samples was evaluated. A composite with the following reinforcementsAl5052/ 6%wtSiC/ 6%wt Al2O3was found to exhibit superior mechanical properties.
A Comprehensive Review of Ferromagnetic Liquid Dynamics and Nonlinear Thermal Buoyancy Effects
Authors: Dr T K Sreelakshmi  
Published: December 2023

Ferromagnetic liquid is a unique class of fluids that exhibits strong magnetic properties when subjected to a magnetic field. This liquid has been extensively studied in various industrial and scientific applications due to its unique properties such as high thermal conductivity, heat capacity, and electrical conductivity. One of the key phenomena associated with this type of liquid is its nonlinear thermal buoyancy effect, which refers to the motion of the liquid due to variation in temperature caused by a non-uniform magnetic field. In recent years, there has been a growing interest in studying the nonlinear thermal buoyancy effect in ferromagnetic liquids, specifically in the context of heat transport processes.
Non-Fourier heat flux is another crucial aspect of ferromagnetic liquids that has gained considerable attention among researchers. Non-Fourier heat flux is characterized by the deviation from the linear Fourier's law of heat conduction, where the rate of heat transfer is not proportional to the temperature gradient. In ferromagnetic liquids, this phenomenon is mainly attributed to the presence of magnetic fields, which influence the heat transfer processes within the liquid. This nonlinear heat flux behavior has significant implications in a wide range of applications, including heat dissipation, cooling, and thermal insulation.
Radiated elastic surfaces are another key feature of ferromagnetic liquids that has recently emerged as a promising area of research. These surfaces are formed when a magnetic field is applied to a ferromagnetic liquid, resulting in the formation of elastic waves on the surface. These waves are created due to the interaction between the magnetic field and the elastic properties of the liquid. The formation of these surfaces has been observed to have a considerable impact on the heat transfer behavior of the liquid, where they act as efficient heat dissipators and significantly enhance the rate of heat exchange between the liquid and its surroundings.
In summary, the interplay of nonlinear thermal buoyancy, non-Fourier heat flux, and radiated elastic surfaces in ferromagnetic liquids has attracted significant attention in recent years due to its potential for a wide range of practical applications. The understanding of these phenomena has the potential to significantly improve the design and efficiency of various heat transfer processes, making ferromagnetic liquids an important area of study in materials science and engineering. Future research in this field is expected to focus on developing more comprehensive models and experimental techniques to further explore the complex thermal and magnetic interactions in ferromagnetic liquids.