Search results for: minimal social networks

Authors: Suvankar Chakraborty

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Introduction: Corporate Social Responsibility means the obligations of business to act in a manner which will serve the best interests of the Society. The Companies Act , 2013 for the first time has emphasized on the fact that every company having net worth of rupees five hundred crore or more, or turnover of rupees one thousand crore or more or a net profit of rupees five crore or more during any financial year shall constitute a Corporate Social Responsibility Committee of the Board consisting of three or more directors, out of which at least one director shall be an independent director. In the previous Companies Act, 1956 there was no such compulsion for constituting a Corporate Social Responsibility Committee. Objective: This study examines the changes in the perception of corporate sectors so far as social responsibility is concerned. Methodology: The study is based on secondary data obtained from various websites of different corporate sectors and the Gazette of India related to Companies Act, 1956 and the new Companies Act, 2013. For capturing the perception of the corporate world regarding the provisions of CSR in the new Companies Act, 2013, primary data has been collected through structured questionnaire. Findings: Corporate Social Responsibility can put a company on a strong base of sustainable development and in facing the business risk of foreclosure or winding up. Shouldering social responsibility on a long-term basis can help a company not only in increasing its reputation in the business world but also helps in minimizing Government intervention. . But, there can hardly be any universal rule that the area of social responsibility being wholly and solely dependent on the ethical aspect of the corporate sectors. But having said that it may be asserted that business ethics may be a key driver of CSR activities rather than rule based CSR activities in the years to come.

Keywords: business ethics, corporate social responsibility, companies act, 2013, CSR committee

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Lorenzo Maiorino, Fabio Fortuna, Giovanni Panebianco, Marco Sanzari, Gabriella Arcese, Valerio Maria Paolozzi

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It is well known that sport is a factor of social cohesion and the breaking down of barriers between people. From this point of view, the aim is to demonstrate how, through the (re)generation of sustainable structures, it is possible to give life to a new social, cultural, and economic pathway, where possible, in peripheral areas with problems of abandonment and degradation. The aim of this paper is, therefore, to study realities such as European programs and funds and to highlight the ways in which planning can be used to respond to critical issues such as urban decay, abandonment, and the mitigation of social differences. For this reason, the analysis will be carried out through the Multiannual Financial Framework (MFF) package, the Next Generation EU, the Recovery and Resilience Facility (RRF), the Cohesion Fund, the European Social Fund, and other managed funds. The procedure will rely on sources and data of unquestionable origin, and the relation to the object of study in question will be highlighted. The project lends itself to be ambitious and exploring a further aspect of the sports theme, which, as we know, is one of the foundations for a healthy society.

Keywords: sport, social inclusion, urban regeneration, sports facilities, European funds

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Authors: Rana S. Alghamdi

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Play in early childhood education has been stifled across the world due to an overemphasis on academic achievement and a reduced focus on physical play and motor development. In Saudi Arabia, teachers reticent to allocate more time to play for fear of retribution from parents and administrators that children are losing academic seat time. This practice has proven to be detrimental to the social, emotional, physical, and cognitive development of children. Teachers are pressured to prioritize Arabic, math, and science while providing minimal time for physical activities. Administrators tend to push for an ever-increasing emphasis on academia in order to achieve higher test scores. However, young children often find it difficult to concentrate if they are not able to get out energy through physical play. Furthermore, many youth educators are not qualified to oversee physical activities, and many facilities are unprepared for safe, outdoor play. This results in children getting little to no outdoor activity. They are stuck in a strict academic regimen that may dampen the creativity and imagination easily fostered through cooperative play. For a stronger educational system and more well-rounded students, Saudi schools should enact policies that extend the number of required hours dedicated to outdoor and physical play. They should also offer training for unqualified teachers. This training should focus on the benefits of physical play and instruct them on how to facilitate these activities safely and effectively. School administrators must focus on providing adequate equipment and safe environments for the purpose of outdoor play and education. In doing so, they will be setting their students up for a successful future and improving their abilities in all aspects of education.

Keywords: early childhood education, play, outdoor, Saudi Arabia

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Authors: Kay Thi Yar, Khin Mar Lar Tun

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Nowadays, social networks are so popular and widely used in all over the world. In addition, searching personal information of each person and searching connection between them (peoples’ relation in real world) becomes interesting issue in our society. In this paper, we propose a framework with three portions for exploring peoples’ relations from their connected information. The first portion focuses on the Graph database structure to store the connected data of peoples’ information. The second one proposes the graph database searching algorithm, the Modified-SoS-ACO (Sense of Smell-Ant Colony Optimization). The last portion proposes the Deductive Reasoning Algorithm to define two persons’ relationship. This study reveals the proper storage structure for connected information, graph searching algorithm and deductive reasoning algorithm to predict and analyze the personnel relationship from peoples’ relation in their connected information.

Keywords: personnel information, graph storage structure, graph searching algorithm, deductive reasoning algorithm

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Authors: Swati Tyagi, Syed Abbas

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Fractional-order Hopfield neural networks are generally used to model the information processing among the interacting neurons. To show the constancy of the processed information, it is required to analyze the stability of these systems. In this work, we perform Mittag-Leffler stability for the corresponding Caputo fractional-order bidirectional associative memory (BAM) neural networks with various time-delays. We derive sufficient conditions to ensure the existence and uniqueness of the equilibrium point by using the theory of topological degree theory. By applying the fractional Lyapunov method and Mittag-Leffler functions, we derive sufficient conditions for the global Mittag-Leffler stability, which further imply the global asymptotic stability of the network equilibrium. Finally, we present two suitable examples to show the effectiveness of the obtained results.

Keywords: bidirectional associative memory neural network, existence and uniqueness, fractional-order, Lyapunov function, Mittag-Leffler stability

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Authors: R. M. López-Gutiérrez, J. A. Michel-Macarty, H. Cervantes-De Avila, J. I. Nieto-Hipólito, C. Cruz-Hernández, L. Cardoza-Avendaño, S. Cortiant-Velez

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It is well know that mankind benefits from the application of robot control by virtual handlers in industrial environments. In recent years, great interest has emerged in the control of multiple robots in order to carry out collective tasks. One main trend is to copy the natural organization that some organisms have, such as, ants, bees, school of fish, birds’ migration, etc. Surely, this collaborative work, results in better outcomes than those obtain in an isolated or individual effort. This topic has a great drive because collaboration between several robots has the potential capability of carrying out more complicated tasks, doing so, with better efficiency, resiliency and fault tolerance, in cases such as: coordinate navigation towards a target, terrain exploration, and search-rescue operations. In this work, synchronization of multiple autonomous robots is shown over a variety of coupling topologies: star, ring, chain, and global. In all cases, collective synchronous behavior is achieved, in the complex networks formed with mobile robots. Nodes of these networks are modeled by a mass using Matlab to simulate them.

Keywords: robots, synchronization, bidirectional, coordinate navigation

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Authors: Georgina Cherry, Taranpreet Rai, Luke Boyden, Sitira Williams, Andrea Wright, Richard Brown, Viva Chu, Alasdair Cook, Kevin Wells

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Estimating population-level burden, abilities of pet-parents to identify disease and demand for veterinary services worldwide is challenging. The purpose of this study is to compare a feline pruritus survey with social media listening (SML) data discussing this condition. Surveys are expensive and labour intensive to analyse, but SML data is freeform and requires careful filtering for relevancy. This study considers data from a survey of owner-observed symptoms of 156 pruritic cats conducted using Pet Parade® and SML posts collected through web-scraping to gain insights into the characterisation and management of feline pruritus. SML posts meeting a feline body area, behaviour and symptom were captured and reviewed for relevance representing 1299 public posts collected from 2021 to 2023. The survey involved 1067 pet-parents who reported on pruritic symptoms in their cats. Among the observed cats, approximately 18.37% (n=196) exhibited at least one symptom. The most frequently reported symptoms were hair loss (9.2%), bald spots (7.3%) and infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin (8.2%). Notably, bald spots were the primary symptom reported for short-haired cats, while other symptoms were more prevalent in medium and long-haired cats. Affected body areas, according to pet-parents, were primarily the head, face, chin, neck (27%), and the top of the body, along the spine (22%). 35% of all cats displayed excessive behaviours consistent with pruritic skin disease. Interestingly, 27% of these cats were perceived as non-symptomatic by their owners, suggesting an under-identification of itch-related signs. Furthermore, a significant proportion of symptomatic cats did not receive any skin disease medication, whether prescribed or over the counter (n=41). These findings indicate a higher incidence of pruritic skin disease in cats than recognized by pet owners, potentially leading to a lack of medical intervention for clinically symptomatic cases. The comparison between the survey and social media listening data revealed bald spots were reported in similar proportions in both datasets (25% in the survey and 28% in SML). Infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin accounted for 31% of symptoms in the survey, whereas it represented 53% of relevant SML posts (excluding bumpy skin). Abnormal licking or chewing behaviours were mentioned by pet-parents in 40% of SML posts compared to 38% in the survey. The consistency in the findings of these two disparate data sources, including a complete overlap in affected body areas for the top 80% of social media listening posts, indicates minimal biases in each method, as significant biases would likely yield divergent results. Therefore, the strong agreement across pruritic symptoms, affected body areas, and reported behaviours enhances our confidence in the reliability of the findings. Moreover, the small differences identified between the datasets underscore the valuable insights that arise from utilising multiple data sources. These variations provide additional depth in characterising and managing feline pruritus, allowing for more comprehensive understanding of the condition. By combining survey data and social media listening, researchers can obtain a nuanced perspective and capture a wider range of experiences and perspectives, supporting informed decision-making in veterinary practice.

Keywords: social media listening, feline pruritus, surveys, felines, cats, pet owners

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Authors: Yosra Benchaabene, Noureddine Boujnah, Faouzi Zarai

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To meet the growing demand of users, the fifth generation (5G) will continue to provide services to higher data rates with higher carrier frequencies and wider bandwidths. As part of the 5G communication paradigm, Ultra Reliable Communication (URC) is envisaged as an important technology pillar for providing anywhere and anytime services to end users. Ultra Reliable Communication (URC) is considered an important technology that why it has become an active research topic. In this work, we analyze the availability of a service in the space domain. We characterize spatially available areas consisting of all locations that meet a performance requirement with confidence, and we define cell availability and system availability, individual user availability, and user-oriented system availability. Poisson point process (PPP) and Voronoi tessellation are adopted to model the spatial characteristics of a cell deployment in heterogeneous networks. Numerical results are presented, also highlighting the effect of different system parameters on the achievable link availability.

Keywords: URC, dependability and availability, space domain analysis, Poisson point process, Voronoi Tessellation

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Shuai Yang, Bin Li, Sixing Chen

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Engaging and co-creating value with buyers (i.e., the buying organizations) have rapidly become a rising trend for sellers (i.e., the selling organizations) within Business-to-Business (B2B) environments, through which buyers can interact more with sellers and be better informed about products. One important way to achieve this is through engaging with buyers on social media, termed as brand engagement on social media, which provides a platform for sellers to interact with customers. This study addresses the research gap by answering the following questions: (1) Are B2B firms’ brand engagement on social media related to their firm value? (2) To what extent do analyst stock recommendations channel B2B firms’ brand engagement on social media’s possible impact on firm value? To answer the research questions, this study collected data merged from multiple sources. The results show that there is a positive association between seller-initiated engagement and B2B sellers’ firm value. Besides, analyst stock recommendations mediate the positive relationships between seller-initiated engagement and firm value. However, this study reveals buyer-initiated engagement has a counterintuitive and negative relationship with firm value, which shows a dark side of buyer-initiated engagement on social media for B2B sellers.

Keywords: brand engagement, B2B firms, firm value, social media, stock recommendations

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Authors: Amanda Maitland

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This preliminary study has examined ways in which social media may help cause stalker murder by individuals with personality disorders and a strong sense of sexual propriety. A public display on social media by the intended victim was felt to be a trigger that instigated interpersonal violence. To identify behavioural paradigms, case studies of intimate partner murders were explored using news media sources and documentaries. In all of the case studies, social media interaction and social media postings occurred shortly before the murder. The evidence suggested a preponderance of correlations between the social media postings, stalking behaviours, personality disorders, and the murder of an intimate partner. In addition to this, a profile for of Facebook/social media murder was gleaned from the paradigms of behavior found in the case studies. The evidence showed a complex relationship between severe violence, stalking, borderline personality, and intimate partner violence was identified through the study. The struggle clients have in dealing with the: public, ambiguous and unrelenting nature of social media postings was also observed. The murderers anguish and rage appeared to be further intensified by attitudes of sexual propriety and entitlement. These attitudes were evident in all the case studies. The study concluded with further research on how the public can protect themselves from entering situations where social media postings might trigger a violent response. Further to this, psychological approaches were identified that might support client’s with personality disorders to cope with perceived provocative and distressing data on the internet. Thus, the findings of this study will be of interest to: therapists, psychologists, nurses, criminologists and social workers.

Keywords: social media, borderline personality, murder, cyberstalking, intimate partner violence, sexual propriety, Facebook

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Authors: Joseph Kwame Sarfo-Adu

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Social protection programs have been rolled out by successive governments in the quest of bridging the inequality gap in Ghana. Despite notable positive impacts of these programs across the country, there still remains worrying experience of the exclusion of the poor and vulnerable especially in rural Ghana Notwithstanding the rhetoric of participation within the discussion of social protection programs, less attention has been given to the design of these programs. In view of this, the study seeks to address how social protection programs are designed to address the needs of the poor. This study focused on five selected social protection programs in Ghana because they are programs with nationwide coverage. Qualitative thematic analysis was applied to analyze our data with the use of the Nvivo 12 version. We found out that there is a strong link between policy design and poverty alleviation. Our findings revealed that a well-designed program can significantly alleviate poverty, a poorly designed program can create more damage.

Keywords: social protection, poverty alleviation, policy design, effective outcome

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Authors: Avinash Malladhi

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Forensic accounting is a specialized field that involves the application of accounting principles, investigative skills, and legal knowledge to detect and prevent fraud. With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting.

Keywords: AI, machine learning, forensic accounting & fraud detection, anti money laundering, Benford's law, fraud triangle theory

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Authors: Saurabh Rawat, Anushree Sah

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K Maps are generally and ideally, thought to be simplest form for obtaining solution of Boolean equations. Cubical Representation of Boolean equations is an alternate pick to incur a solution, otherwise to be meted out with Truth Tables, Boolean Laws, and different traits of Karnaugh Maps. Largest possible k- cubes that exist for a given function are equivalent to its prime implicants. A technique of minimization of Logic functions is tried to be achieved through cubical methods. The main purpose is to make aware and utilise the advantages of cubical techniques in minimization of Logic functions. All this is done with an aim to achieve minimal cost solution.r

Keywords: K-maps, don’t care conditions, Boolean equations, cubes

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Authors: Hamna Hamid, Kashmala Zaman

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The aim of this study was to evaluate the relationship between self-efficacy, resilience, and social support among clinical psychologists, counselors, and teachers of special schools. The study also assesses the gender differences in self-efficacy, resilience, social support, and vicarious trauma and also vicarious trauma differences among three professions, i.e., clinical psychologists, counselors, and teachers of special schools. A sample of 150 women and 97 men were handed out a set questionnaire to complete: a General Self-Efficacy Scale, Brief Resilience Scale, Multidimensional Scale of Perceived Social Support, and Vicarious Trauma Scale. Results showed that there is a significant negative correlation between self-efficacy, resilience, and vicarious trauma. Women experience higher levels of vicarious trauma as compared to men. At the same time, clinical psychologists and counselors experience higher levels of vicarious trauma as compared to teachers of special schools. The moderation effect of social support is not significant towards resilience and vicarious trauma.

Keywords: self-efficacy, resilience, vicarious-trauma social-support, social support

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Authors: Atmaja Patel

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Since the development of lasers in 1951, the first medical application was reported by Goldman in 1962. In 1960, T.H. Maiman produced the first Ruby laser and was used in cardiovascular surgery by McGuff in 1963. After a long time of investigations and new developments in laser technology first clinical applications were performed by Choy and Ginsburg in 1983. Introduction of the first true dental laser was in 1989. This paper is to highlight the various treatments and prevention of periodontal diseases. Lasers have become more predictable and effective form of treatment for periodontal diseases. The advantages of lasers include reduced use of anaesthesia, coagulation that yields a dry surgical field and hence better visibility, reduced need of sutures, minimal swelling and scarring, less pain and medication, faster healing and increased patient acceptance.

Keywords: lasers, periodontal surgery, diode laser, healing

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Authors: Bassem Boshra Thabet, Mohammed Ibrahim Elsabagh, Mohammad Adly Talaat

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The number of cellular mobile phone users has increased enormously worldwide over the last two decades. Consequently, the monitoring of the performance of the Mobile Network Operators (MNOs) in terms of network coverage and broadband signal strength has become vital for both of the MNOs and regulators. This monitoring helps telecommunications operators and regulators keeping the market playing fair and most beneficial for users. However, the adopted methodologies to facilitate this continuous monitoring process are still problematic regarding cost, effort, and reliability. This paper introduces My Operator Coverage (MOC) system that is using Internet of Things (IoT) concepts and tools to monitor the MNOs performance using a crowd-sourced real-time methodology. MOC produces robust and reliable geographical maps for the user-perceived quality of the MNOs performance. MOC is also meant to enrich the telecommunications regulators with concrete, and up-to-date information that allows for adequate mobile market management strategies as well as appropriate decision making.

Keywords: mobile performance monitoring, crowd-sourced applications, mobile broadband performance, cellular networks monitoring

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Ilham S. M. Elsayed

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The purpose of this study is to investigate Alahsa Governorate status and its vulnerability to generate urban heat islands. Alahsa Governorate is a famous oasis in the Arabic Peninsula including several oil centers. Extensive literature review was done to collect previous relative data on the urban heat island of Alahsa Governorate. Data used for the purpose of this research were collected from authorized bodies who control weather station networks over Alahsa Governorate, Eastern Province, Saudi Arabia. Although, the number of weather station networks within the region is very limited and the analysis using GIS software and its techniques is difficult and limited, the data analyzed confirm an increase in temperature for more than 2 °C from 2004 to 2014. Such increase is considerable whenever human health and comfort are the concern. The increase of temperature within one decade confirms the availability of urban heat islands. The study concludes that, Alahsa Governorate is vulnerable to create urban heat islands and more attention should be drawn to strategic planning of the governorate that is developing with a high pace and considerable increasing levels of urbanization.

Keywords: Alahsa Governorate, population density, Urban Heat Island, weather station

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Authors: Emma Groenewald

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In 1994, numerous policies of a democratic dispensation envisage social justice and the transformation of the South Africa society. The drive for transformation and social justice resulted in an increasing number of university students from diverse backgrounds, which in turn, lead to the establishment of Sol Plaatje University (SPU) in 2014. A re-curriculated B. Ed. programme at SPU aims to equip students with knowledge and skills to realise the aim of social justice and to enhance the transformation of the South African society. The aim of this study is to explore the experiences and perceptions of students at a diverse university campus on a curriculum that aims to promote social justice. Four education modules, with the assumption that it reflects social justice content, were selected. Four students, representative of different ethnic and language groupings found at the SPU, were chosen as participants. Data were generated by the participants through four reflective exercises on each of the modules, spread over a period of four years. The module aims, linked with the narratives of the participants' perceptions and experiences of each module, provided an overview of the enacted curriculum. A qualitative research design with an interpretivist approach informed by Vygotsky's theory of learning was used. The participants' experiences of the four modules were analysed, and their views were interpreted. The students' narratives shed light on the strengths and weaknesses of how the B.Ed. Curriculum works towards social justice and revealed student's perceptions of otherness. From the narratives it became apparent that module did promote a social justice orientation in prospective teachers trained at a university.

Keywords: student diversity, social justice, transformation, teacher education

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Authors: Akila Murali, Prithika Manivel

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Disasters are defined as a serious disruption of the functioning of a community or a society, which involves widespread human, material, economic or environmental impacts. The number of people suffering food crisis as a result of natural disasters has tripled in the last thirty years. The economic losses due to natural disasters have shown an increase with a factor of eight over the past four decades, caused by the increased vulnerability of the global society, and also due to an increase in the number of weather-related disasters. Efficient disaster detection and alerting systems could reduce the loss of life and properties. In the event of a disaster, another important issue is a good search and rescue system with high levels of precision, timeliness and safety for both the victims and the rescuers. Wireless Sensor Networks technology has the capability of quick capturing, processing, and transmission of critical data in real-time with high resolution. This paper studies the capacity of sensors and a Wireless Sensor Network to collect, collate and analyze valuable and worthwhile data, in an ordered manner to help with disaster management.

Keywords: alerting systems, disaster detection, Ad Hoc network, WSN technology

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Authors: A. Uludağ, F. G. Tufekci, N. Ceviz

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Aim: The research has been carried out in order to evaluate caregiver burden, life satisfaction and received social support level of the parents whose children have congenital heart disease; to examine the relationship between the social supports received by them and caregiver burden and life satisfaction. Material and Method: The research which is descriptive and which is searching a relationship has been carried out between the dates June 7, 2012- June 30, 2014, in Erzurum Ataturk University Research and Application Hospital, Department of Pediatrics and Children Cardiology Polyclinic. In the research, it was collaborated with the parents (N = 157) who accepted to participate in, of children who were between the ages of 3 months- 12 years. While gathering the data, a questionnaire, Zarit Caregiver Burden, Life Satisfaction and Social Support Scales have been used. The statistics of the data acquired has been produced by using percentage distribution, mean, and variance and correlation analysis. Ethical principles are followed in the research. Results: In the research, caregiver burden, life satisfaction and social support level received from family (p < 0.05), have been determined higher in the parents whose children have serious congenital heart disease than that of parents whose children have slight disease and social support received from friends has been found lower. It has been determined that there is a strong relation (p < 0.001) through negative direction between both social support levels and caregiver burden of parents; and that there is a strong relation (p < 0.001) through positive direction between both support levels and life satisfaction. Conclusion: That Social Support is in a strong relation with Caregiver Burden through a negative direction and a strong relation with Life Satisfaction through positive direction in parents of all the children who have congenital heart disease requires social support systems to be reinforced. Parents can be led or guided so as to prompt social support systems more.

Keywords: congenital heart disease, child, parents, caregiver burden, life satisfaction, social support

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Authors: Ashish Shrivastava, C. Pandu Rangan

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In this paper, we consider The Hospitals Residents problem with Social Stability (HRSS), where hospitals and residents can communicate only through the underlying social network. Those residents and hospitals which don not have any social connection between them can not communicate and hence they cannot be a social blocking pair with respect to a socially stable matching in an instance of hospitals residents problem with social stability. In large scale matching like NRMP or Scottish medical matching scheme etc. where set of agents, as well as length of preference lists, are very large, social stability is a useful notion in which members of a blocking pair could block a matching if and only if they know the existence of each other. Thus the notion of social stability in hospitals residents problem allows us to increase the cardinality of the matching without taking care of those blocking pairs which are not socially connected to each other. We know that finding a maximum cardinality socially stable matching, in an instance, of HRSS is NP-hard. This motivates us to solve this problem with bounded length preference lists on one side. In this paper, we have presented a polynomial time algorithm to compute maximum cardinality socially stable matching in a HRSS instance where residents can give at most two length and hospitals can give unbounded length preference list. Preference lists of residents and hospitals will be strict in nature.

Keywords: matching under preference, socially stable matching, the hospital residents problem, the stable marriage problem

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Authors: Elizabeth Radian

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In a challenging era of neoliberalism and managerialism in social services, the status of Canadian social work education at the Bachelor of Social Work level (BSW) was examined to determine how prepared students were to practice in a time of resource cutbacks and insecurity. Curricula in BSW programs was the focus as this generalist degree results in the greatest number of social work graduates in Canada, most of whom work at the front lines in service delivery. The study reviewed the practice frameworks that students in BSW programs were exposed to. Traditionally, schools of social work have embraced two major practice frameworks. The person in environment framework is a well-established practice framework taught in most schools. The framework offers some focus on smaller scale social change, tweaking existing arrangements and is more accepting of the status quo. An alternate practice framework taught in fewer schools has been described as a structural, progressive or anti oppressive framework. This latter framework challenges the status quo, is focused on social justice and social transformation, often incorporating social action strategies to ensure marginalized voices are heard. Using a content analysis methodology of keywords and phrases to delineate framework orientation, practice frameworks articulated in the curricula were determined by reviewing the mission/mandate of schools offering a BSW degree, their core course outlines and core course textbooks. Social action, as one strategy for initiating social change and transformation was considered. Initial research for 28 schools was completed in 2000, with follow up replications of the initial study in 2005 and 2014. These earlier studies displayed that the dominant practice framework taught in BSW programs was the person in environment framework. A lesser number of schools were categorized as primarily offering a structural, progressive or anti oppressive framework. The findings from the current study of 39 Canadian schools of social work are considered to determine how prominent structural, progressive and anti oppressive frameworks exist in current BSW curricula. This study can assist in contemplating the question – are we educating future practitioners for acceptance or action.

Keywords: social work education and pedagogy, social change, social justice, social services

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Authors: Elisa Bertagna

Abstract:

The aim of the research is to study diversity issues and gender equality in the Finnish and Italian oil and gas companies. Particular attention is given to the effects on the organization’s and employees’ interactions resulting from intersecting social categories. The study is aimed to be settled in companies where social inequalities and diversity management problematics are present. Consequently, ten semi-structured interviews with key managers from the companies and four focus groups composed of culturally diverse employees aim to depict and analyze the situation from both points of view. Social discourse and intersectionality are employed as the analysis methods. Trainings, workshops, and suggestions are to be offered in the required situations.

Keywords: diversity, gender, intersectionality, oil and gas companies, social constructionism

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Authors: Mohanad Alhabo, Naveed Nawaz, Mahmoud Al-Faris

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The dense deployment of small cells is a promising solution to enhance the coverage and capacity of the heterogeneous networks (HetNets). However, the unplanned deployment could bring new challenges to the network ranging from interference, unnecessary handovers and handover failures. This will cause a degradation in the quality of service (QoS) delivered to the end user. In this paper, we propose an integrated Grey Rational Analysis Standard Deviation based handover method (GRA-SD) for HetNet. The proposed method integrates the Standard Deviation (SD) technique to acquire the weight of the handover metrics and the GRA method to select the best handover base station. The performance of the GRA-SD method is evaluated and compared with the traditional Multiple Attribute Decision Making (MADM) methods including Simple Additive Weighting (SAW) and VIKOR methods. Results reveal that the proposed method has outperformed the other methods in terms of minimizing the number of frequent unnecessary handovers and handover failures, in addition to improving the energy efficiency.

Keywords: energy efficiency, handover, HetNets, MADM, small cells

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Authors: Beatriz Martinez-Pastor, Maria Nogal, Alan O'Connor

Abstract:

During the last years, the number of extreme weather events has increased. A variety of extreme weather events, including river floods, rain-induced landslides, droughts, winter storms, wildfire, and hurricanes, have threatened and damaged many different regions worldwide. These events have a devastating impact on critical infrastructure systems resulting in high social, economical and environmental costs. These events have a huge impact in transport systems. Since, transport networks are completely exposed to every kind of climatological perturbations, and its performance is closely related with these events. When a traffic network is affected by a climatological hazard, the quality of its service is threatened, and the level of the traffic conditions usually decreases. With the aim of understanding this process, the concept of resilience has become most popular in the area of transport. Transport resilience analyses the behavior of a traffic network when a perturbation takes place. This holistic concept studies the complete process, from the beginning of the perturbation until the total recovery of the system, when the perturbation has finished. Many concepts are included in the definition of resilience, such as vulnerability, redundancy, adaptability, and safety. Once the resilience of a transport network can be evaluated, in this case, the methodology used is a dynamic equilibrium-restricted assignment model that allows the quantification of the concept, the next step is its improvement. Through the improvement of this concept, it will be possible to create transport networks that are able to withstand and have a better performance under the presence of climatological hazards. Analyzing the impact of a perturbation in a traffic network, it is observed that the response of the different links, which are part of the network, can be completely different from one to another. Consequently and due to this effect, many questions arise, as what makes a link more critical before an extreme weather event? or how is it possible to identify these critical links? With this aim, and knowing that most of the times the owners or managers of the transport systems have limited resources, the identification of the critical links of a transport network before extreme weather events, becomes a crucial objective. For that reason, using the available resources in the areas that will generate a higher improvement of the resilience, will contribute to the global development of the network. Therefore, this paper wants to analyze what kind of characteristic makes a link a critical one when an extreme weather event damages a transport network and finally identify them.

Keywords: critical links, extreme weather events, hazard, resilience, transport network

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Authors: F. A. Adesoji, A. A. Ayandele

Abstract:

There has been a concern over non-responsiveness of educational programme in Nigeria’s higher institutions to adequately meet social needs. The study, therefore, investigated the effectiveness of basic elements of the Social Studies Curriculum, the contributions of the Teacher–Related Variables (TRV) such as qualification, area of specialization, teaching experience, teaching methods, gender and teaching facilities to the implementation of the curriculum (IOC) in the Colleges of Education (COEs). The study adopted the descriptive survey design. Four COEs in Oyo, Osun, Ondo and Lagos States were purposively selected. Stratified sampling technique was used to select 455 Social Studies students and 47 Social Studies lecturers. Stakeholders’ Perception of Social Studies Curriculum (r = 0.86), Social Studies Curriculum Resources scale (r = 0.78) and Social Studies Basic Concepts Test (r = 0.78) were used for data collection. Data were analysed using descriptive statistics, multiple regression, and t-test at 0.05 level of significance. COEs teachers and students rated the elements of the curriculum to be effective with mean scores x̄ =3.02 and x̄ =2.80 respectively; x̄ =5.00 and x̄ = 2.50 being the maximum and minimum mean scores. The finding showed average level of availability (x̄ =1.60), adequacy (x̄ =1.55) and utilization (x̄ =1.64) of teaching materials, x̄ =3.00 and x̄ =1.50 being maximum and minimum mean scores respectively. Academic performance of the students is on average with the mean score of x̄ =51.4775 out of maximum mean score of x̄ =100. The TRV and teaching facilities had significant composite contribution to IOC (F (6,45) = 3.92:R² = 0.26) with 39% contributions to the variance of IOC. Area of specialization (β= 29, t = 2.05) and teaching facilities (β = -25, t = 1.181) contributed significantly. The implementation of bachelor degree in Social Studies curriculum was effective in the colleges of education. There is the need to beef-up the provision of facilities to improve the implementation of the curriculum.

Keywords: bachelor degree in social studies, colleges of education in southwestern Nigeria, curriculum implementation, social studies curriculum

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