Search results for: social network ties

Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: particle swarm optimization, GIS, traffic data, outliers

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Authors: Graziela D. de Azevedo, Livia M. Pagotto, Mario P. Monzoni, Neto

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This article aims to discuss partnerships between public administration and private social investment aimed at territorial development. There has been some approximation in Brazil from private social investors with initiatives aiming at territorial development policies in highly vulnerable territories or in places where the business sector operates. This represents this paper’s major justification: on the advance of academic debate about how businesses, institutes, and foundations have been working alongside local governments, taking the territory as the reference for joint action. The research was based on the literature on governance and territorial development and adopted a mixed iterative approach (inductive and deductive) through an interpretative lens so as to develop an analysis structure that complements and expands knowledge about the contribution of public policies and private social investments for territorial development in Brazil. The analysis of 15 cases based on three distinct blocks (territorial development plans, articulation for education, and thematic approaches) has made it possible to identify common elements regarding the motivations of partnerships, the specific needs of the actors involved, and the priority drivers for stimulating development. Findings include discussion on the leading role of territories in their development paths, on the institutionalization and strengthening of capacities, and on long-term perspectives in development strategies.

Keywords: private social investment, public administration, territorial governance, territorial development

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Authors: Ailing Yang, Penghan Song, Aihua Cai

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The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.

Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention

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Authors: Kuldeep Singh

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The present paper is an attempt for tracing the changes in the welfare state in Indian democracy from the starting point till now and aims to critical analyse the social-welfare programmes in India with respect to welfare state. After getting independence from Britishers, India became a welfare state and is aiming towards the upliftment of its citizens. Indian democracy is considered to be the largest amongst democratic countries, instead of this after forty-five years of independence, Panchayati Raj Institution became one of the branches of democratic decentralization institutions in India by 73rd and 74th Constitutional Amendment in 1992. Unfortunately, desired purpose of introducing Panchayati Raj Institution is not achieved after all these delayed efforts. The basic problem regarding achievement of welfare state in India in true sense is unawareness and non-implementation of these social-welfare programmes. Presently, Indian government is only focusing on economic growth of the country but lacking from the social point. The doctrinal method of research is used in this research paper. In the concluding remarks, researcher is partly favoring the government in introducing welfare programmes as there are abundant of welfare schemes and programmes, but majority are facing implementation problem. In last, researcher has suggested regarding programmes and schemes that these should be qualitative in nature and power would be given to effective machinery for further check upon their proper implementation and aware the citizens regarding their rights so that welfare state would be achieved.

Keywords: democratic decentralization, Indian democracy, Panchayati Raj institution, social-welfare programmes, welfare state

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Authors: Maud Tixier

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Societal issues are at stake for cruises anywhere, whatever the size of the ships and their destinations are. However, the Mediterranean sea is the main region where many operate and the challenges are both social and environmental. The presentation focuses on small ships, accounting for market niches, aimed at more specific cruise passengers and calling at less visited areas. How they cope with the benefit of all stakeholders is a persistent issue of our time.

Keywords: environment, management, social, societal, safety

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Authors: Debdatta Mukherjee, Abhiman Das, Amit Garg

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In recent years, there is a growing interest about corporate social responsibility of firms in both academic literature and business world. Since business forms a part of society incorporating socio-environment concerns into its value chain, activities are vital for ensuring mutual sustainability and prosperity. But, until now most of the works have been either descriptive or normative rather than positivist in tone. Even the few ones with a positivist approach have mostly studied the link between corporate financial performance and corporate social performance. However, these studies have been severely criticized by many eminent authors on grounds that they lack a theoretical basis for their findings. They have also argued that apart from corporate financial performance, there must be certain other crucial influences that are likely to determine corporate social performance of firms. In fact, several studies have indicated that firms operating in distinct national institutions show significant variations in the corporate social responsibility practices that they undertake. This clearly suggests that the institutional context of a country in which the firms operate is a key determinant of corporate social performance of firms. Therefore, this paper uses an institutional framework to understand why corporate social performance of firms vary across countries. It examines the impact of country level institutions on corporate social performance using a sample of 3240 global publicly-held firms across 33 countries covering the period 2010-2015. The country level institutions include public institutions, private institutions, markets and capacity to innovate. Econometric Analysis has been mainly used to assess this impact. A three way panel data analysis using fixed effects has been used to test and validate appropriate hypotheses. Most of the empirical findings confirm our hypotheses and the economic significance indicates the specific impact of each variable and their importance relative to others. The results suggest that institutional determinants like ethical behavior of private institutions, goods market, labor market and innovation capacity of a country are significantly related to the corporate social performance of firms. Based on our findings, few implications for policy makers from across the world have also been suggested. The institutions in a country should promote competition. The government should use policy levers for upgrading home demands, like setting challenging yet flexible safety, quality and environment standards, and framing policies governing buyer information, providing innovative recourses to low quality goods and services and promoting early adoption of new and technologically advanced products. Moreover, the institution building in a country should be such that they facilitate and improve the capacity of firms to innovate. Therefore, the proposed study argues that country level institutions impact corporate social performance of firms, empirically validates the same, suggest policy implications and attempts to contribute to an extended understanding of corporate social responsibility and corporate social performance in a multinational context.

Keywords: corporate social performance, corporate social responsibility, institutions, markets

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Authors: Şeyda Kaya

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The aim of this study is to examine the relationship between corporate social responsibility perception and organizational commitment among Turkish cabin crew. At the same time, the social responsibility perception and organizational commitment scores of the participants were compared according to their gender, age, education level, title, and work experience. In the globalizing world, businesses have developed some innovative marketing methods in order to survive and strengthen their place in the market. Nowadays, consumers who are connected to the brand with an emotional bond rather than being just consumers. Corporate Social Responsibility Projects, on the one hand, provide social benefit, on the other hand, increase the brand awareness of businesses by providing credibility in the eyes of consumers. The rapid increase of competition, requires businesses to use their human resources, which is the most important resource to sustain their existence, in the most effective and efficient way. For this reason, the concept of ‘Organizational Commitment’ has become an important research topic for business and academics. Although there are studies in the literature to determine the effect of the perception of corporate social Responsibility on Organizational Commitment in Banking and Finance and Tourism sectors, there are no studies conducted specifically for the Turkish aviation sector to our best knowledge. Personal information form, CSR scale, Importance of CSR scale, Organizational commitment scale were used as data collection tools in the research. CSR Scale created by Türker (2006). was used to find out how employees felt about CSR. Importance of CSR Scale through a subscale of the Perceived Role of Ethics and Social Responsibility (PRESOR) that Etheredge (1999) converted into a two-factor framework, the significance of social responsibility for employees was assessed. Organizational Commitment Scale, Mowday, Steers, and Porter (1979) created the OCQ, which uses 15 measures to evaluate global commitment to the organization. As a result of the study, there is a significant positive relationship between the participants' CSR scale sub-dimensions, CSR to Employees, CSR to Customers, CSR to Society, CSR to Government, CSR to Natural Environment, CSR to Next Generation, CSR to Governmental Organizations, Importance of CSR, and Organizational Commitment scores. As a result; as the participants' Corporate Social Responsibility scores increase, their organizational commitment increases. To summarize the findings of our study, the scores obtained from the CSR scale and the scores obtained from the Organizational Commitment scale were found to have a positive and significant relationship. In other words, if the participants value the corporate social responsibility projects of the institution they work for and think that they spare time and effort, the importance they attach to the corporate social responsibility projects and their organizational commitment to the institution they work for, increase. Similarly, the scores obtained from the Importance of CSR and the scores obtained from the Organizational Commitment scale also have a positive and significant relationship. As the importance given to corporate social responsibility projects by the participants increases, their organizational commitment to the institution they work for also increases.

Keywords: corporate social responsibility, organizational commitment, Turkish cabin crew, aviation

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Authors: O. Abdelkhalek, A. Naimi, M. Rami, M. N. Tandjaoui, A. Kechich

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This paper deals with the active and reactive power flow analysis inside the unified power quality conditioner (UPQC) during several cases. The UPQC is a combination of shunt and series active power filter (APF). It is one of the best solutions towards the mitigation of voltage sags and swells problems on distribution network. This analysis can provide the helpful information to well understanding the interaction between the series filter, the shunt filter, the DC bus link and electrical network. The mathematical analysis is based on active and reactive power flow through the shunt and series active power filter. Wherein series APF can absorb or deliver the active power to mitigate a swell or sage voltage where in the both cases it absorbs a small reactive power quantity whereas the shunt active power absorbs or releases the active power for stabilizing the storage capacitor’s voltage as well as the power factor correction. The voltage sag and voltage swell are usually interpreted through the DC bus voltage curves. These two phenomena are introduced in this paper with a new interpretation based on the active and reactive power flow analysis inside the UPQC. For simplifying this study, a linear load is supposed in this digital simulation. The simulation results are carried out to confirm the analysis done.

Keywords: UPQC, Power flow analysis, shunt filter, series filter.

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Authors: Vethathirri Ramanujam Srinivasan, S. M. Shiva Nagendra

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Air quality management in urban areas is a serious concern in both developed and developing countries. In this regard, more number of air quality monitoring stations are planned to mitigate air pollution in urban areas. In India, Central Pollution Control Board has set up 574 air quality monitoring stations across the country and proposed to set up another 500 stations in the next few years. The number of monitoring stations for each city has been decided based on population data. The setting up of ambient air quality monitoring stations and their operation and maintenance are highly expensive. Therefore, there is a need to optimize monitoring networks for air quality management. The present paper discusses the various methods such as Indian Standards (IS) method, US EPA method and European Union (EU) method to arrive at the minimum number of air quality monitoring stations. In addition, optimization of rain-gauge method and Inverse Distance Weighted (IDW) method using Geographical Information System (GIS) are also explored in the present work for the design of air quality network in Chennai city. In summary, additionally 18 stations are required for Chennai city, and the potential monitoring locations with their corresponding land use patterns are ranked and identified from the 1km x 1km sized grids.

Keywords: air quality monitoring network, inverse distance weighted method, population based method, spatial variation

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Authors: Parisa Toloue Hayat Azar

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Businesses have been playing an important role in the economic growth and social welfare of cities; however, they generally have negative reputations regarding their impact on environmental issues regarding sustainability. However, some believe that by incorporating strategic Corporate Social Responsibility (CSR) activities, businesses will be able to solve problems in society, including environmental ones. Besides economic, social and environmental aspects, governance is another essential pillar for creating sustainable communities and cities. Governance plays a key role in the success of sustainable projects or creating long lasting legacies; an example of this can be creating circular supply chain with collaboration between different businesses, which in the end results in positive economic, social and environmental outcomes for everyone. Governance is a very important parameter in creating the legacy of low carbon and environmentally friendly city due to the fact that, besides building energy efficient buildings and infrastructure, citizens who are also part of the success of this system should know about how to behave and collaborate with others to make the system work. By deploying the philosophy of cultural historical activity theory, this paper explains how influential businesses have been and can be still used as a mediating tool for governance purposes, and succeed in creating shared value and lasting legacy within society.

Keywords: business, governance, CSR, sustainability

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Authors: Lu Zhao, Nadir Farhi, Zoi Christoforou, Nadia Haddadou

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The safety test of deploying intelligent connected vehicles (ICVs) on the road network is a critical challenge. Road traffic network simulation can be used to test the functionality of ICVs, which is not only time-saving and less energy-consuming but also can create scenarios with car collisions. However, the relationship between different human driver behaviors and the car-collision occurrences has been not understood clearly; meanwhile, the procedure of car-collisions generation in the traffic numerical simulators is not fully integrated. In this paper, we propose an approach to identify specific driver profiles from real driven data; then, we replicate them in numerical traffic simulations with the purpose of generating inter-vehicular collisions. We proposed three profiles: (i) 'aggressive': short time-headway, (ii) 'inattentive': long reaction time, and (iii) 'normal' with intermediate values of reaction time and time-headway. These three driver profiles are extracted from the NGSIM dataset and simulated using the intelligent driver model (IDM), with an extension of reaction time. At last, the generation of inter-vehicular collisions is performed by varying the percentages of different profiles.

Keywords: vehicular collisions, human driving behavior, traffic modeling, car-following models, microscopic traffic simulation

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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Authors: Rania S. Hussein

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This research mainly focuses on examining engagement in social media brand communities. Engagement in social media has become a main focus in literature affirming that the role of social media in our daily lives is growing. (Akman and Mishra, 2017;Prado-Gascó et al., 2017). Social media has also become a key medium for brand communication and brand building relationships(Frimpong and McLean,2018;Dimitriu and Guesalaga, 2017). Engagement on social media has become a main focus of many researchers who tried to understand this concept further and draw a link between engagement and various social media activities (Cvijikj and Michahelles;2013), Andre,2015; Wang et al., 2015). According to Felix et al. (2017), the internet and social media have provided better digital resources to improve brand loyalty and customer interactions, thus leading to social media engagement within brand communities. The aim of this research is to highlight the importance of social media and why it is important to maintain engagement within social media. While the term ‘engagement’ is widely used in scholarly literature, there isn’t a common consensus about what the term exactly entails, according to Kidd, (2011). On one hand, it was seen as something that includes factors such as participation, activation, empowerment, devotion, trust, and productivity (Zhang et al, andBenyoucef, M. (2016), ). Other scholars held different viewpoints. For example, Lim et al. (2015) has chosen to break down engagement into three types: operational engagement, emotional engagement, and relational engagement. Chandler and Lusch (2015) further studied engagement as a means to measure commitment to a brand. Fernandes&Remelhe (2016) had a more technical view, measuring engagement through comments, following, subscribing, sharing, enjoying, writing, etc., in the social media context. ustomer engagement has become a research focus for understanding how consumer relationships are developed, retained, and improved within a digital context. Based on previous literature, it is evident that many customer engagement related studies are limited to the interaction between firms and consumers on social media. There is a clear gap in the literature regarding consumer-to-consumer interaction and user-generated content and its significance. While some researchers, such as Alversia et al. (2016), touched upon the importance of customer-based engagement, a gap still remains: there is no consistent and well-tested method for defining the factors that affect consumer interaction. Moreover, few scholarly research papers such as (Case, 2019; Riley, 2020;Habibi, 2014) provided to assist businesses understand their customers' interaction habits as well as the best ways to develop customer loyalty. Additionally, the majority of research on brand pages concentrated on the drivers of Consumer engagement, with just a few studies example, Lamberton, Cc(2016), Poorrezaei, (2016). (Jayasingh, 2019), looking into the implications. This study focuses on understanding the concept of engagement and its importance, specifically engagement within social media brand communities. It examines drivers as well as consequences of engagement, including brand knowledge, brand trust, entertainment, and brand page interactivity. Brand engagement is also expected to affect brand loyalty and word of the mouth.

Keywords: engagement, social media, brand communities, drivers

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Authors: Ibraheem Alzahrani

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This paper seeks to discover the relationship between both the social constructivist learning theory and the collaborative learning environment. This relationship can be identified through given an example of the learning environment. Due to wiki characteristics, wiki can be used to understand the relationship between constructivist learning theory and collaborative learning environment. However, several evidences will come in this paper to support the idea of why wiki is the suitable method to explore the relationship between social constructivist theory and the collaborative learning and their role in learning. Moreover, learning activities in wiki classroom will be discussed in this paper to find out the result of the learners' interaction in the classroom groups, which will be through two types of communication; synchronous and asynchronous.

Keywords: social constructivist, collaborative, environment, wiki, activities

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Authors: Yoga Maulana Putra, Herry Hudrasyah

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The Internet has now become an important part of human life; it can be accessed through a computer or even a smartphone almost anywhere and anytime. The Internet has created many social media such as Facebook, Twitter, and Instagram. Instagram has been acquired by Facebook in 2012. Since then, Instagram is growing fast. And now, Instagram is transforming from photo-sharing social media into business tools. As the result, some new behavior has been discovered. Some of Instagram user is becoming popular. These people also being called minor celebrity and they are also being used as marketing tools by many companies to influencing or promoting their product or service. This minor celebrity is existing because of their behavior in using Instagram. The company is using the personal influence of the minor celebrity to promoting and influencing their product or service, and the minor celebrity gets paid as much as their rate card. And their rate card based on their followers and insight. This research is using a qualitative method. An interview is being done to 6 minor celebrities from many different categories such as photographer, travel blogger, lifestyle, food blogger, fashion, and healthcare. Theory of reasoned behavior is being used as the grounded theory to discover the reason for their behavior and personal influence to describe their way to influencing people. The result of the interview is most of the minor celebrities is influenced by their friend’s circle in the process of using Instagram. They also had a different way to use their personal influence to affect their followers when the company employs them.

Keywords: humanities and social sciences, Instagram, minor celebrity, social media

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Authors: Guanhao Tong, Li Li, Ben David

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This study aims to provide an explanatory account of how the leisure tourist experience emerges from tourists and their surroundings through a critical realist lens. This was achieved by applying Archer’s realist social theory as the underlying theoretical ground to unpack the interplays between the external (tourism system or structure) and the internal (tourists or agency). This theory argues that social phenomena can be analyzed in three domains - structure, agency, and culture (SAC), and along three phases – structure conditioning, sociocultural interactions, and structure elaboration. From the realist perspective, the world is an open system; events and discourses are irreducible to present individuals and collectivities. Therefore, identifying the processes or mechanisms is key to help researchers understand how social reality is brought about. Based on the contextual nature of the tourist experience, the research focuses on Chinese tourists (from mainland China) to London as a destination and British culture conveyed through the concept of the destination image. This study uses an intensive approach based on Archer’s M/M approach to discover the mechanisms/processes of the emergence of the tourist experience. Individual interviews were conducted to reveal the underlying causes of lived experiences of the tourists. Secondary data was also collected to understand how British destinations are portrayed to Chinese tourists.

Keywords: Chinese tourists, destination image, M/M approach, realist social theory, social mechanisms, tourist experience

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Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: Heather Fulford, Melanie Liddell

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The recruitment and retention of high quality employees can prove to be challenging for social enterprises, particularly in some of the core business support functions such as marketing, communications, IT and finance. This holds true for social enterprises in urban contexts, where roles with more attractive remuneration in these business functions can often be found quite readily in the private sector. For social enterprises situated in rural locations, the challenges of staff recruitment and retention are even more acute. Such challenges can lead to a skills deficit in rural social enterprises, which can, at best, hinder their growth potential, and worse, jeopardise their chances of survival. This in turn, can have a negative impact on the sustainability and resilience of the surrounding rural community in which the social enterprise is located. The purpose of this paper is to report on aspects of a collaborative initiative established to stimulate innovation and business growth in remote rural businesses in Scotland. Launched in 2010, this initiative was designed to attract young students and graduates from the region to stay in the region upon completion of their studies, and to attract others from outside the region to re-locate there post-university. To facilitate this, SMEs in the region were offered wage subsidies to encourage them to recruit a student or graduate on a work placement for up to one year to participate in an innovation or business growth-oriented project. A number of the employers offering work placements were social enterprises. Through analysis of the placement project and role specifications devised by the participating social enterprises, an overview is provided of their business development needs and the skills they require to stimulate innovation and growth. Scrutiny of the reflective accounts compiled by the students and graduates at the close of their work placements highlights the benefits they derived from being able to put their academic knowledge and skills into action within a social enterprise. Examination of interviews conducted with a sample of placement employers reveals the contribution the students and graduates made during the business development projects with the social enterprises. The challenges of hosting such placements are also discussed. The paper concludes with indications of the lessons learned and an outline of the wider implications for other remote rural locations in which social enterprises play an important role in the local economy and life of the community.

Keywords: resilience, rural development, regeneration, regional development, recruitment, resource management, retention, remuneration

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Authors: Karla Hrbackova, Irena Balaban Cakirpaloglu

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This paper is a report on self-regulation in socially rejected pupils. A certain form of social rejection can be found in almost every class within the school environment. Research shows that due to social rejection mechanisms supporting the individual´s effort of reintegration into the group are not triggered. Paradoxically the opposite tendency arises, i.e., an increase in selfish and defeating behaviour. The link between peer exposure and self-regulation is likely to vary as a function of a type and quality of peer interaction (e.g., rejection or acceptance). The paper aims to clarify the level of self-regulation related to interpersonal cognitive problem-solving within the process of social rejection in a school class. The research was done on a sample of 1,133 upper-primary school pupils using the Means-Ends Problem Solving technique (MEPS) and peer sociometric nomination. The results showed that the level of self-regulated skills is related to the status of social rejection. Socially rejected pupils achieve lower levels of self-regulation than other classmates. We found deficiency in the regulation of behaviour, emotions and the regulation of will in the peer rejected pupils with the exception of cognitive regulation in which no differences were detected between socially rejected pupils and other classmates. The results have implications for early prevention and intervention efforts to foster adaptive self-regulation and reduce the risk of later social rejection.

Keywords: interpersonal cognitive problem-solving, self-regulation, socially rejected pupils, upper-primary school pupils

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Authors: Farzad Jalilian, Mehdi Mirzaei Alavijeh, Fazel Zinat Motlagh

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Social support is an important benchmark of health for people in avoidance conditions. The main goal of this study was to determine the three kinds of social support (family, friend and other significant) to drug cessation among male addicts, in Kermanshah, the west of Iran. This cross-sectional study was conducted among 132 addicts, randomly selected to participate voluntarily in the study. Data were collected from conduct interviews based on standard questionnaire and analyzed by using SPSS-18 at 95% significance level. The majority of addicts were young (Mean: 30.4 years), and with little education. Opium (36.4%), Crack (21.2%), and Methamphetamine (12.9%) were the predominant drugs. Inabilities to reject the offer and having addict friends are the most often reasons for drug usage. Almost, 18.9% reported history of drug injection. 43.2% of the participants already did drug cessation at least once. Logistic regression showed the family support (OR = 1.110), age (OR = 1.106) and drug use initiation age (OR = 0.918) was predicting drug cessation. Our result showed; family support is a more important effect among types of social support in drug cessation. It seems that providing educational program to addict’s families for more support of patients at drug cessation can be beneficial.

Keywords: drug cessation, family support, drug use, initiation age

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Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Libo Jiang, Huan Li, Rongling Wu

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Ordinary differentiation equations (ODE) have proven to be powerful for reconstructing precise and informative gene regulatory networks (GRNs) from dynamic gene expression data. However, joint modeling and analysis of all genes, essential for the systematical characterization of genetic interactions, are challenging due to high dimensionality and a complex pattern of genetic regulation including activation, repression, and antitermination. Here, we address these challenges by unifying variable selection and game theory through ODE. Each gene within a GRN is co-expressed with its partner genes in a way like a game of multiple players, each of which tends to choose an optimal strategy to maximize its “fitness” across the whole network. Based on this unifying theory, we designed and conducted a real experiment to infer salt tolerance-related GRNs for Euphrates poplar, a hero tree that can grow in the saline desert. The pattern and magnitude of interactions between several hub genes within these GRNs were found to determine the capacity of Euphrates poplar to resist to saline stress.

Keywords: gene regulatory network, ordinary differential equation, game theory, LASSO, saline resistance

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Danna Jia, Bin Li

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Background: Atopic dermatitis (AD) is a chronic and refractory inflammatory skin disease characterized by relapsing eczematous and pruritic skin lesions. The global prevalence of AD ranges from 1~ 20%, and its incidence rates are increasing. It affects individuals from infancy to adulthood, significantly impacting their daily lives and social activities. Despite its major health burden, the precise mechanisms underlying AD remain unknown. Understanding the genetic differences associated with AD is crucial for advancing diagnosis and targeted treatment development. This study aims to identify candidate genes of AD by using bioinformatics analysis. Methods: We conducted a comprehensive analysis of four pooled transcriptomic datasets (GSE16161, GSE32924, GSE130588, and GSE120721) obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was performed using the R statistical language. The differentially expressed genes (DEGs) between AD patients and normal individuals were functionally analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, a protein-protein interaction (PPI) network was constructed to identify candidate genes. Results: Among the patient-level gene expression datasets, we identified 114 shared DEGs, consisting of 53 upregulated genes and 61 downregulated genes. Functional analysis using GO and KEGG revealed that the DEGs were mainly associated with the negative regulation of transcription from RNA polymerase II promoter, membrane-related functions, protein binding, and the Human papillomavirus infection pathway. Through the PPI network analysis, we identified eight core genes: CD44, STAT1, HMMR, AURKA, MKI67, and SMARCA4. Conclusion: This study elucidates key genes associated with AD, providing potential targets for diagnosis and treatment. The identified genes have the potential to contribute to the understanding and management of AD. The bioinformatics analysis conducted in this study offers new insights and directions for further research on AD. Future studies can focus on validating the functional roles of these genes and exploring their therapeutic potential in AD. While these findings will require further verification as achieved with experiments involving in vivo and in vitro models, these results provided some initial insights into dysfunctional inflammatory and immune responses associated with AD. Such information offers the potential to develop novel therapeutic targets for use in preventing and treating AD.

Keywords: atopic dermatitis, bioinformatics, biomarkers, genes

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Authors: Rakesh Namdeti

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Toxic dyes found in industrial effluent must be treated before being disposed of due to their harmful impact on human health and aquatic life. Thus, Musa acuminata (Banana Leaves) was employed in the role of a biosorbent in this work to get rid of methylene blue derived from a synthetic solution. The effects of five process parameters, such as temperature, pH, biosorbent dosage, and initial methylene blue concentration, using a central composite design (CCD), and the percentage of dye clearance were investigated. The response was modelled using a quadratic model based on the CCD. The analysis of variance revealed the most influential element on experimental design response (ANOVA). The temperature of 44.30C, pH of 7.1, biosorbent dose of 0.3 g, starting methylene blue concentration of 48.4 mg/L, and 84.26 percent dye removal were the best conditions for Musa acuminata (Banana leave powder). At these ideal conditions, the experimental percentage of biosorption was 76.93. The link between the estimated results of the developed ANN model and the experimental results defined the success of ANN modeling. As a result, the study's experimental results were found to be quite close to the model's predicted outcomes.

Keywords: Musa acuminata, central composite design, methylene blue, artificial neural network

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Authors: Jaballah Jamil

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KLD (Peter Kinder, Steve Lydenberg and Amy Domini) research & analytics is an independent intermediary of social performance information that adopts an investor-pay model. KLD rating agency does not have an explicit monitoring on the rated firm which suggests that KLD ratings may not include private informations. Moreover, the incapacity of KLD to predict accurately the extra-financial rating of Enron casts doubt on the reliability of KLD ratings. Therefore, we first investigate whether KLD ratings affect investors' perception by studying the effect of KLD rating changes on firms' financial performances. Second, we study the impact of the Enron scandal on investors' perception of KLD rating changes by comparing the effect of KLD rating changes on firms' financial performances before and after the failure of Enron. We propose an empirical study that relates a number of equally-weighted portfolios returns, excess stock returns and book-to-market ratio to different dimensions of KLD social responsibility ratings. We first find that over the last two decades KLD rating changes influence significantly and negatively stock returns and book-to-market ratio of rated firms. This finding suggests that a raise in corporate social responsibility rating lowers the firm's risk. Second, to assess the Enron scandal's effect on the perception of KLD ratings, we compare the effect of KLD rating changes before and after the Enron scandal. We find that after the Enron scandal this significant effect disappears. This finding supports the view that the Enron scandal annihilates the KLD's effect on Socially Responsible Investors. Therefore, our findings may question results of recent studies that use KLD ratings as a proxy for Corporate Social Responsibility behavior.

Keywords: KLD social rating agency, investors' perception, investment decision, financial performance

Procedia PDF Downloads 439

Authors: David Gottlieb, Jason Yoder

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The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

Procedia PDF Downloads 97

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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Authors: Titus Amodu Umoru

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The global economy today is full of sophistication. All over the world, business and marketing practices are undergoing an unprecedented transformation. In realization of this fact, the federal government of Nigeria has put in place a robust transformation agenda in order to put Nigeria in a better position to be a competitive player and in the process transform all sectors of its economy. New technologies, especially the internet, are the driving force behind this transformation. However, technology has inadvertently affected the way businesses are done thus necessitating the acquisition of new skills. In developing countries like Nigeria, citizens are still battling with effective application of those technologies. Obviously, students of business education need to acquire relevant business knowledge to be able to transit into the world of work on graduation from school and compete favourably in the labour market. Therefore, effective utilization of social media by both teachers and students can help extensively in empowering students with the needed skills. Social media which is described as a group of internet-based applications that build on the ideological foundations of Web 2.0, and which allow the creation and exchange of user-generated content, if incorporated into the classroom experience may be the needed answer to unemployment and poverty in Nigeria as beneficiaries can easily connect with existing and potential enterprises and customers, engage with them and reinforce mutual business benefits. Challenges and benefits of social media use in education in Nigeria universities were revealed in this study.

Keywords: business education, challenges, opportunities, utilization, social media

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Authors: A. Moualdia, D. J. Boudana, O. Bouchhida, A. Medjber

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, the cost of this energy is still too high to compete with traditional fossil fuels, especially on sites less windy. The performance of a wind turbine depends on three parameters: the power of wind, the power curve of the turbine and the generator's ability to respond to wind fluctuations. This paper presents a control chain conversion based on a double-fed asynchronous machine and flow-oriented. The supply system comprises of two identical converters, one connected to the rotor and the other one connected to the network via a filter. The architecture of the device is up by three commands are necessary for the operation of the turbine control extraction of maximum power of the wind to control itself (MPPT) control of the rotor side converter controlling the electromagnetic torque and stator reactive power and control of the grid side converter by controlling the DC bus voltage and active power and reactive power exchanged with the network. The proposed control has been validated in both modes of operation of the three-bladed wind 7.5 kW, using Matlab/Simulink. The results of simulation control technology study provide good dynamic performance and static.

Keywords: D.F.I.G, variable wind speed, hypersynchrone, energy quality, hyposynchrone

Procedia PDF Downloads 367