Search results for: social media data

Authors: Bahram Soltani, Louai Ghazieh

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Following the high profile financial scandals of 2007-2008, corporate management has been faced with strong pressures resulting from more regulatory requirements, as well as the increasing expectations of various groups of stakeholders. The responsibility acquired a big importance in front of this financial crisis. This responsibility requires more transparency and communication, inside the company with the collaborators and outside of the company with the society, while companies try to improve the degree of control and to authorize managers to realize the objectives of the company. The objective of this paper is to present the concept of the responsibility generally and the various types of manager’s responsibility in private individual within the company, as well as the explanatory theories of this responsibility through the various perspectives such as: economic, political, social and behavioral. This study should have academic and practical contributions particularly for regulators seeking to improve the companies’ practices and organizational functioning within capital market economy.

Keywords: manager, accountability, corporate performance, financial crisis, behavior

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Authors: Donald Ouko

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For decades, Africa has been home to several foreign companies doing business in various sectors. In recent years, China has consistently positioned itself as a development partner powerhouse among African nations. However, this has not been felt as equally beneficial to the local communities where the partnerships bloom in extractives trading. This paper explores the impact of Chinese involvement in mining on the local communities in three African countries, the factors that enable the sector to thrive amid the impacts, and what could be done differently for the local communities to experience a different outcome. It suggests alternative terms of engagement that aim at transparency, accountability, and anti-corruption to ensure inclusive social and economic development, and sound governance both at state and corporate levels.

Keywords: law and society, social development, corporate governance, China-Africa ties, human rights, socio-economic development, accountability, transparency

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Authors: Mahdi Akbari, Ali Torabi Haghighi

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Hamun Lakes, located in the Helmand Basin, consisting of four water bodies, were the greatest (>8500 km2) freshwater bodies in Iran plateau but have almost entirely desiccated over the last 20 years. The desiccation of the lakes caused dust storm in the region which has huge economic and health consequences on the inhabitants. The flow of the Hirmand (or Helmand) River, the most important feeding river, has decreased from 4 to 1.9 km3 downstream due to anthropogenic activities. In this basin, water is mainly consumed for farming. Due to the lack of in-situ data in the basin, this research utilizes remote-sensing data to show how croplands and consequently consumed water in the agricultural sector have changed. Based on Landsat NDVI, we suggest using a threshold of around 0.35-0.4 to detect croplands in the basin. Croplands of this basin has doubled since 1990, especially in the downstream of the Kajaki Dam (the biggest dam of the basin). Using PML V2 Actual Evapotranspiration (AET) data and considering irrigation efficiency (≈0.3), we estimate that the consumed water (CW) for farming. We found that CW has increased from 2.5 to over 7.5 km3 from 2002 to 2017 in this basin. Also, the annual average Potential Evapotranspiration (PET) of the basin has had a negative trend in the recent years, although the AET over croplands has an increasing trend. In this research, using remote sensing data, we covered lack of data in the studied area and highlighted anthropogenic activities in the upstream which led to the lakes desiccation in the downstream.

Keywords: Afghanistan-Iran transboundary Basin, Iran-Afghanistan water treaty, water use, lake desiccation

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Authors: Myriam Roy

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The perspectives of the Togolese public towards mental illness were assessed, looking at religious affiliation, personal knowledge of someone with a mental illness, and education level as influencers. The goal was to observe which factors influenced most strongly the general public’s attitudes towards mental illness. The Togolese population was surveyed within the context of mental health awareness workshops and involved college and university students, rural community members, and company employees. Taylor and Dear’s Community Attitudes towards the Mentally Ill (CAMI) questionnaire was used to assess these influencers and includes four dimensions of community attitudes towards mental illness: authoritarianism, benevolence, social restrictiveness, and community mental health ideology (CMHI). Demographic questions were also included, tailored to the various realities of the Togolese population. These questions looked, among others, at religious, ethnical (region of origin within Togo), and educational background. It was found that religious affiliation and personal knowledge did not correlate significantly with changes in the four dimensions of the CAMI scale. It suggests that public perspectives towards mental illness might not be as associated with these variables as was previously thought. The dimensions, however, did correlate with themselves as was expected. Authoritarianism was associated positively with social restrictiveness, benevolence was associated negatively with social restrictiveness and positively with CMHI, and CMHI was associated negatively with social restrictiveness, indicating the CAMI did not suffer from reliability and validity issues when used with this population. Interestingly, level of education significantly impacted authoritarianism level, with higher education associated with a decrease in authoritarianism. This finding would support the notion that education is likely to provide access to a wide array of information as well as interaction with people from various backgrounds and situations. Providing increased awareness regarding mental health and illness in schools could be beneficial to favor the impact that education appears to have on public perspectives towards mental illness in Togo. Future studies could assess which mental health interventions in schools would be the most useful in Togo.

Keywords: CAMI questionnaire, cross-cultural psychology, stigma towards mental illness, West African psychology

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Authors: Marike Venter de Villiers, Jessica Ramoshaba

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In recent years, the fashion industry has been associated with the exploitation of both people and resources. This is largely due to the emergence of the fast fashion concept, which entails rapid and continual style changes where clothes quickly lose their appeal, become out-of-fashion, and are then disposed of. This cycle often entails appalling working conditions in sweatshops with low wages, child labor, and a significant amount of textile waste that ends up in landfills. Although the awareness of the negative implications of ‘mindless fashion production and consumption’ is growing, fast fashion remains to be a popular choice among the youth. This is especially prevalent in South Africa, a poverty-stricken country where a vast number of young adults are unemployed and living in poverty. Despite being in poverty, the celebrity conscious culture and fashion products frequently portrayed on the growing intrusive social media platforms in South Africa pressurizes the consumers to purchase fashion and luxury products. Young adults are therefore more vulnerable to the temptation to purchase fast fashion products. A possible solution to the detrimental effects that the fast fashion industry has on the environment is the revival of the secondhand clothing trend. Although the popularity of secondhand clothing has gained momentum among selected consumer segments, the adoption rate of such remains slow. The main purpose of this study was to explore consumers’ perceptions of the secondhand clothing trend and to gain insight into factors that inhibit the adoption of secondhand clothing. This study also aimed to investigate whether consumers are aware of the negative implications of the fast fashion industry and their likelihood to shift their clothing purchases to that of secondhand clothing. By means of a quantitative study, fifty young females were asked to complete a semi-structured questionnaire. The researcher approached females between the ages of 18 and 35 in a face-to-face setting. The results indicated that although they had an awareness of the negative consequences of fast fashion, they lacked detailed insight into the pertinent effects of fast fashion on the environment. Further, a number of factors inhibit their decision to buy from secondhand stores: firstly, the accessibility to the latest trends was not always available in secondhand stores; secondly, the convenience of shopping from a chain store outweighs the inconvenience of searching for and finding a secondhand store; and lastly, they perceived secondhand clothing to pose a hygiene risk. The findings of this study provide fashion marketers, and secondhand clothing stores, with insight into how they can incorporate the secondhand clothing trend into their strategies and marketing campaigns in an attempt to make the fashion industry more sustainable.

Keywords: eco-friendly fashion, fast fashion, secondhand clothing, eco-friendly fashion

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Léa Chawki, Émilie Cappe

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Context: Nowadays, supporting parents of children with autism spectrum disorder (ASD) and helping them adjust to their child’s condition represents a core clinical and scientific necessity and is encouraged by the French National Strategy for Autism (2018). In France, ASD remains a challenging condition, causing distress, segregation and social stigma to concerned family members concerned by this handicap. The literature highlights that neurodevelopmental disorders in children, such as ASD, influence parental well-being. This impact could be different according to parents’ culture and the child’s particular disorder manifestation, such as developmental coordination disorder (DCC), for instance. Objectives: This present study aims to explore parental stress, anxiety and depressive symptoms, as well as the quality of life in parents of children with ASD or DCD, as well as the explicit individual, psychosocial and cultural factors of parental well-being. Methods: Participants will be recruited through diagnostic centers, child and specialized adolescent units, and organizations representing families with ASD and DCD. Our sample will include five groups of 150 parents: four groups of parents having children with ASD – one living in France, one in the US, one in Canada and the other in Lebanon – and one group of French parents of children with DCD. Self-evaluation measures will be filled directly by parents in order to measure parental stress, anxiety and depressive symptoms, quality of life, coping and emotional regulation strategies, internalized stigma, perceived social support, the child’s problem behaviors severity, as well as motor coordination deficits in children with ASD and DCD. A sociodemographic questionnaire will help collect additional useful data regarding participants and their children. Individual and semi-structured research interviews will be conducted to complete quantitative data by further exploring participants’ distinct experiences related to parenting a child with a neurodevelopmental disorder. An interview grid, specially designed for the needs of this study, will strengthen the comparison between the experiences of parents of children with ASD with those of parents of children with DCD. It will also help investigate cultural differences regarding parent support policies in the context of raising a child with ASD. Moreover, interviews will help clarify the link between certain research variables (behavioral differences between ASD and DCD, family leisure activities, family and children’s extracurricular life, etc.) and parental well-being. Research perspectives: Results of this study will provide a more holistic understanding of the roles of individual, psychosocial and cultural variables related to parental well-being. Thus, this study will help direct the implementation of support services offered to families of children with neurodevelopmental disorders (ASD and DCD). Also, the implications of this study are essential in order to guide families through changes related to public policies assisting neurodevelopmental disorders and other disabilities. The between-group comparison (ASD and DCD) is also expected to help clarify the origins of all the different challenges encountered by those families. Hence, it will be interesting to investigate whether complications perceived by parents are more likely to arise from child-symptom severity, or from the lack of support obtained from health and educational systems.

Keywords: Autism spectrum disorder, cross-cultural, cross-disorder, developmental coordination delay, well-being

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Authors: Azzaya Enkhjargal

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Context: The mining industry has a long history of human rights abuses, including forced labor, environmental pollution, and displacement of communities. In recent years, there has been growing international pressure to hold mining companies accountable for these abuses. Research Aim: This study explores the legal liabilities of mining companies for human rights abuses. The study specifically examines the case of Erdenet Mining Corporation (EMC), a large mining company in Mongolia that has been accused of human rights abuses. Methodology: The study used a mixed-methods approach, which included a review of legal literature, interviews with community members and NGOs, and a case study of EMC. Findings: The study found that mining companies can be held liable for human rights abuses under a variety of regulatory frameworks, including soft law and self-regulatory instruments in the mining industry, international law, national law, and corporate law. The study also found that there are a number of challenges to holding mining companies accountable for human rights abuses, including the lack of effective enforcement mechanisms and the difficulty of proving causation. Theoretical Importance: The study contributes to the growing body of literature on the legal liabilities of mining companies for human rights abuses. The study also provides insights into the challenges of holding mining companies accountable for human rights abuses. Data Collection: The data for the study was collected through a variety of methods, including a review of legal literature, interviews with community members and NGOs, and a case study of EMC. Analysis Procedures: The data was analyzed using a variety of methods, including content analysis, thematic analysis, and case study analysis. Conclusion: The study concludes that mining companies can be held liable for human rights abuses under a variety of legal and regulatory frameworks. There are positive developments in ensuring greater accountability and protection of affected communities and the environment in countries with a strong economy. Regrettably, access to avenues of redress is reasonably low in less developed countries, where the governments have not implemented a robust mechanism to enforce liability requirements in the mining industry. The study recommends that governments and mining companies take more ambitious steps to enhance corporate accountability.

Keywords: human rights, human rights abuses, ESG, litigation, Erdenet Mining Corporation, corporate social responsibility, soft law, self-regulation, mining industry, parent company liability, sustainability, environment, UN

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Authors: G. H. B. Dilhari, A. A. D. T. Saparamadu

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The coir is one of the by-products of the coconut and the coir industry can be identified as one of the traditional industries in Sri Lanka. Sri Lanka is one of the prominent countries for the coir production. Due to the labour insensitiveness, the labourers are the significant factor in the coir production process. The study has analyzed the determinants and its impact on income of the household level coir yarn labourers. The study was conducted in the Kumarakanda Grama Niladhari division, Galle, Sri Lanka. Simple random sampling was used to generate the sample of 100 household level coir yarn labourers and structured questionnaire, personal interviews and discussion were performed to gather the required data. The obtained data were statistically analyzed by using Statistical Package for Social Science (SPSS) software. Mann-Whitney U and Kruskal-Wallis test were carried out. The findings revealed that the household level coir yarn industry is dominated by the female workers and fewer amounts of workers have engaged this industry as the main occupation. In addition to that, elderly participation of the industry is greater than younger participation and most of them engaged as an extra income source. Level of education, the methods of engagement, satisfaction, labour’s children employment in the coir industry, support from the government, method of government support, working hours per day, employed as a main job, no of completed units per day, suffering any job related diseases and type of the diseases were related with income level of household level coir yarn labourers. The recommendations were formulated in respect to these problems including technological transformation for coir yarn production, strengthening of the raw material base and regulating the raw material supply, introduction of new technologies, markets and training programs, the establishment of the labourers association, the initiation of micro credit schemes, better consideration about the job oriented diseases.

Keywords: coir, coir yarn labourers, income, Galle

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Authors: Estelle Abrahams, Tania Pretorius

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A joint media statement by the South African Reserve Bank, the Banking Association of South Africa, the Financial Sector Conduct Authority, and the Payments Association of South Africa was recently published, stating that the receipt or acceptance of cheques will terminate effectively on 31 December 2020. All stakeholders are urged to cease accepting or issuing cheques as a payment method. The purpose of the study is to examine the effect that the discontinuation of the usage of cheques has on bank reconciliations for the subject: economic and management sciences. A literature study was performed to gain insight into the bank reconciliation process to be able to draw conclusions on the outcome of the discontinuation of cheques on the bank reconciliation. The study found that the teaching of the bank reconciliation process will change to introduce new replacement source documents for digital payments, and this impacts the teaching of reconciling differences.

Keywords: bank reconciliation, internal control, accounting education, source documents

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Authors: Hasan Vural

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Turkey is a favorable country to produce a great variety of agricultural products because of her different geographic and climatic conditions which have been used to divide the country into four main and seven sub regions. This classification into seven regions traditionally has been used in order to data collection and publication especially related with agricultural production. Afterwards, nine agricultural regions were considered. Recently, the governmental body which is responsible of data collection and dissemination (Turkish Institute of Statistics-TIS) has used 12 classes which include 11 sub regions and Istanbul province. This study aims to evaluate these classification efforts based on the acreage of ten main crops in a ten years time period (1996-2005). The panel data grouped in 11 subregions has been evaluated by cluster and multivariate statistical methods. It was concluded that from the agricultural production point of view, it will be rather meaningful to consider three main and eight sub-agricultural regions throughout the country.

Keywords: agricultural region, factorial analysis, cluster analysis,

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Authors: Ibtisam Mohammed Al-Quraini

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This paper examines how introducing Omani literature in foreign language classrooms can influence the students' motivation in learning the language. The data was collected through the questionnaire which was administered to two samples (A and B) of the participants. Sample A was comprised of 30 female students from English department who are specialist in English literature in college of Arts and Social Science. Sample B in contrast was comprised of 10 female students who their major is English from college of Education. Results show that each genre in literature has different influence on the students' motivation in learning the language which proves that literacy texts are powerful. Generally, Omani English teachers tend to avoid teaching literature because they think that it is a difficult method to use in teaching field. However, the advantages and the influences of teaching poetries, short stories, and plays are discussed. Recommendations for current research and further research are also discussed at the end.

Keywords: education, foreign language, English, Omani literature, poetry, story, play

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Authors: Salina Budin, Shaira Ismail

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Students learn effectively in a learning environment with a suitable teaching approach that matches their learning preferences. The main objective of the study is to examine the learning preferences amongst the students in the Science and Technology (S&T), and Social Science (SS) fields of study at the Universiti Teknologi Mara (UiTM), Pulau Pinang. The measurement instrument is based on the Dunn and Dunn Learning Styles which measure five elements of learning styles; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering and Faculty of Business Management. The respondents comprise of 131 diploma students of the Faculty of Mechanical Engineering and 111 degree students of the Faculty of Business Management. The results indicate that, both S&T and SS students share a similar learning preferences on the environmental aspect, emotional preferences, motivational level, learning responsibility, persistent level in learning and learning structure. Most of the S&T students are concluded as analytical learners and the majority of SS students are global learners. Both S&T and SS students are concluded as visual learners, preferred to be in an active mobility in a relaxing and enjoying mode with some light of refreshments during the learning process and exhibited reflective characteristics in learning. Obviously, the S&T students are considered as left brain dominant, whereas the SS students are right brain dominant. The findings highlighted that both categories of students exhibited similar learning preferences except on psychological preferences.

Keywords: learning preferences, Dunn and Dunn learning style, teaching approach, science and technology, social science

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Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

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Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: building system, time series, diagnosis, outliers, delay, data gap

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Authors: Brian Yulianto, Syachrial, Saeful Aziz, Anggita Clara Shinta

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Indonesia, with a population of about two hundred and fifty million people in quantity, indicates the outstanding wealth of human resources. Hundreds of millions of the population scattered in various communities in various regions in Indonesia with the different characteristics of economic, social and unique culture. Broadly speaking, the community in Indonesia is divided into two classes, namely urban communities and rural communities. The rural communities characterized by low potential and management of natural and human resources, limited access of development, and lack of social and economic infrastructure, and scattered and isolated population. West Java is one of the provinces with the largest population in Indonesia. Based on data from the Central Bureau of Statistics in 2015 the number of population in West Java reached 46.7096 million souls spread over 18 districts and 9 cities. The big difference in geographical and social conditions of people in West Java from one region to another, especially the south to the north causing the gap is high. It is closely related to the flow of investment to promote the area. Poverty and underdevelopment are the classic problems that occur on a massive scale in the region as the effects of inequity in development. South Cianjur and Tasikmalaya area South became one of the portraits area where the existing potential has not been capable of prospering society. Tri Dharma College not only define the College as a pioneer implementation of education and research to improve the quality of human resources but also demanded to be a pioneer in the development through the concept of public service. Bandung Institute of Technology as one of the institutions of higher education to implement community service system through collaborative community work program "one of the university community" as one approach to developing villages. The program is based Community Service, where students are not only required to be able to take part in community service, but also able to develop a community development strategy that is comprehensive and integrity in cooperation with government agencies and non-government related as a real form of effort alignment potential, position and role from various parties. Areas of western Java in particular have high poverty rates and disparity. On the other hand, there are three fundamental pillars in the development of rural communities, namely economic development, community development, and the integrated infrastructure development. These pillars require the commitment of all components of community, including the students and colleges for upholding success. College’s community program is one of the approaches in the development of rural communities. ITB is committed to implement as one form of student community service as community-college programs that integrate all elements of the community which is called Kuliah Kerja Nyata-Thematic.

Keywords: development in rural area, collaborative, student community service, Kuliah Kerja Nyata-Thematic ITB

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Authors: Eman I. Raslan, Haitham S. Hamza, Reda A. El-Khoribi

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Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.

Keywords: fiber-wireless (FiWi), dynamic bandwidth allocation (DBA), passive optical networks (PON), media access control (MAC)

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Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Kanyapat U. Tapao

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The purpose of this study is to analyze the operation strategy strategies and public relations trend for public relations strategies development in public television station in Thailand. This study is a qualitative approach by indent interview from the 6 key informants that are managers of Voice TV and Thairath TV Channel. The results showed that both TV stations have to do research before making a release on the operation strategy policy such as a slogan, segmentation, integrated marketing communication and PR activity and also in term of Public Relations trend are including online media, online content and online training before opening the station and start promoting. By the way, we found the PR strategy for both TV station should be including application on mobile, online content, CRM activity, online banner, special event, and brand ambassador in order to bring a very reliable way.

Keywords: online banner, operation strategy, public relations trend, public relations strategies development

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Authors: Omojokun Gabriel Aju

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Communication network is a process of exchanging data between two or more devices via some forms of transmission medium using communication protocols. The data could be in form of text, images, audio, video or numbers which can be grouped into FTP, Email, HTTP, VOIP or Video applications. The effectiveness of such data exchange will be proved if they are accurately delivered within specified time. While some senders will not really mind when the data is actually received by the receiving device, inasmuch as it is acknowledged to have been received by the receiver. The time a data takes to get to a receiver could be very important to another sender, as any delay could cause serious problem or even in some cases rendered the data useless. The validity or invalidity of a data after delay will therefore definitely depend on the type of data (information). It is therefore imperative for the network device (such as router) to be able to differentiate among the packets which are time sensitive and those that are not, when they are passing through the same network. So, here is where the queuing disciplines comes to play, to handle network resources when such network is designed to service widely varying types of traffics and manage the available resources according to the configured policies. Therefore, as part of the resources allocation mechanisms, a router within the network must implement some queuing discipline that governs how packets (data) are buffered while waiting to be transmitted. The implementation of the queuing discipline will regulate how the packets are buffered while waiting to be transmitted. In achieving this, various queuing disciplines are being used to control the transmission of these packets, by determining which of the packets get the highest priority, less priority and which packets are dropped. The queuing discipline will therefore control the packets latency by determining how long a packet can wait to be transmitted or dropped. The common queuing disciplines are first-in-first-out queuing, Priority queuing and Weighted-fair queuing (FIFO, PQ and WFQ). This paper critically evaluates and analyse through the use of Optimized Network Evaluation Tool (OPNET) Modeller, Version 14.5 the effects of three queuing disciplines (FIFO, PQ and WFQ) on the performance of 5 different applications (FTP, HTTP, E-Mail, Voice and Video) within specified parameters using packets sent, packets received and transmission delay as performance metrics. The paper finally suggests some ways in which networks can be designed to provide better transmission performance while using these queuing disciplines.

Keywords: applications, first-in-first-out queuing (FIFO), optimised network evaluation tool (OPNET), packets, priority queuing (PQ), queuing discipline, weighted-fair queuing (WFQ)

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Authors: N. Nalini, Bhanu Prakash Gopularam

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The term data security refers to the degree of resistance or protection given to information from unintended or unauthorized access. The core principles of information security are the confidentiality, integrity and availability, also referred as CIA triad. Cloud computing services are classified as SaaS, IaaS and PaaS services. With cloud adoption the confidential enterprise data are moved from organization premises to untrusted public network and due to this the attack surface has increased manifold. Several cloud computing platforms like OpenStack, Eucalyptus, Amazon EC2 offer users to build and configure public, hybrid and private clouds. While the traditional encryption based on PKI infrastructure still works in cloud scenario, the management of public-private keys and trust certificates is difficult. The Identity based Public Key Cryptography (also referred as ID-PKC) overcomes this problem by using publicly identifiable information for generating the keys and works well with decentralized systems. The users can exchange information securely without having to manage any trust information. Another advantage is that access control (role based access control policy) information can be embedded into data unlike in PKI where it is handled by separate component or system. In OpenStack cloud platform the keystone service acts as identity service for authentication and authorization and has support for public key infrastructure for auto services. In this paper, we explain OpenStack security architecture and evaluate the PKI infrastructure piece for data confidentiality. We provide method to integrate ID-PKC schemes for securing data while in transit and stored and explain the key measures for safe guarding data against security attacks. The proposed approach uses JPBC crypto library for key-pair generation based on IEEE P1636.3 standard and secure communication to other cloud services.

Keywords: data confidentiality, identity based cryptography, secure communication, open stack key stone, token scoping

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Authors: Ahmad Haidar

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This research paper investigates the concept of modern management, concentrating on the development of managerial practices and the adoption of innovative strategies in response to the fast-changing business landscape caused by Artificial Intelligence (AI). The study begins by examining the historical context of management theories, tracing the progression from classical to contemporary models, and identifying key drivers of change. Through a comprehensive review of existing literature and case studies, this paper provides valuable insights into the principles and practices of modern management, offering a roadmap for organizations aiming to navigate the complexities of the contemporary business world. The paper examines the growing role of digital technology in modern management, focusing on incorporating AI, machine learning, and data analytics to streamline operations and facilitate informed decision-making. Moreover, the research highlights the emergence of new principles, such as adaptability, flexibility, public participation, trust, transparency, and digital mindset, as crucial components of modern management. Also, the role of business leaders is investigated by studying contemporary leadership styles, such as transformational, situational, and servant leadership, emphasizing the significance of emotional intelligence, empathy, and collaboration in fostering a healthy organizational culture. Furthermore, the research delves into the crucial role of environmental sustainability, corporate social responsibility (CSR), and corporate digital responsibility (CDR). Organizations strive to balance economic growth with ethical considerations and long-term viability. The primary research question for this study is: "What are the key principles, practices, and innovations that define modern management, and how can organizations effectively implement these strategies to thrive in the rapidly changing business landscape?." The research contributes to a comprehensive understanding of modern management by examining its historical context, the impact of digital technologies, the importance of contemporary leadership styles, and the role of CSR and CDR in today's business landscape.

Keywords: modern management, digital technology, leadership styles, adaptability, innovation, corporate social responsibility, organizational success, corporate digital responsibility

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Authors: Alexander K. Edwards

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Introduction: The moral dimension of teacher education globally has assumed a new paradigm of thinking based on the public gain (return-on-investments), value-creation (quality), professionalism (practice), and business strategies (innovations). Abundant literature reveals an interesting revolutionary trend in complimenting the raising of teachers and academic performances. Because of the global competition in the knowledge-creation and service areas, the C21st teacher at all levels is expected to be resourceful, strategic thinker, socially intelligent, relationship aptitude, and entrepreneur astute. This study is a significant contribution to practice and innovations to raise exemplary or primal teachers. In this study, the qualities needed were considered as ‘Quadrant Intelligence (Q-i)’ model for a primal teacher leadership beyond the classroom. The researcher started by examining the issue of the majority of teachers in Ghana Education Services (GES) in need of this Q-i to be effective and efficient. The conceptual framing became determinants of such Q-i. This is significant for global employability and versatility in teacher education to create premium and primal teacher leadership, which are again gaining high attention in scholarship due to failing schools. The moral aspect of teachers failing learners is a highly important discussion. In GES, some schools score zero percent at the basic education certificate examination (BECE). The question is what will make any professional teacher highly productive, marketable, and an entrepreneur? What will give teachers the moral consciousness of doing the best to succeed? Method: This study set out to develop a model for primal teachers in GES as an innovative way to highlight a premium development for the C21st business-education acumen through desk reviews. The study is conceptually framed by examining certain skill sets such as strategic thinking, social intelligence, relational and emotional intelligence and entrepreneurship to answer three main burning questions and other hypotheses. Then the study applied the causal comparative methodology with a purposive sampling technique (N=500) from CoE, GES, NTVI, and other teachers associations. Participants responded to a 30-items, researcher-developed questionnaire. Data is analyzed on the quadrant constructs and reported as ex post facto analyses of multi-variances and regressions. Multiple associations were established for statistical significance (p=0.05). Causes and effects are postulated for scientific discussions. Findings: It was found out that these quadrants are very significant in teacher development. There were significant variations in the demographic groups. However, most teachers lack considerable skills in entrepreneurship, leadership in teaching and learning, and business thinking strategies. These have significant effect on practices and outcomes. Conclusion and Recommendations: It is quite conclusive therefore that in GES teachers may need further instructions in innovations and creativity to transform knowledge-creation into business venture. In service training (INSET) has to be comprehensive. Teacher education curricula at Colleges may have to be re-visited. Teachers have the potential to raise their social capital, to be entrepreneur, and to exhibit professionalism beyond their community services. Their primal leadership focus will benefit many clienteles including students and social circles. Recommendations examined the policy implications for curriculum design, practice, innovations and educational leadership.

Keywords: emotional intelligence, entrepreneurship, leadership, quadrant intelligence (q-i), primal teacher leadership, strategic thinking, social intelligence

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Authors: Lemu Abebe Geleta

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In this study, it compare the performance of banks and financial services (operational, financial, and market) across four major regions including Asia, Europe, Africa, and North with the extent of sustainability reporting. We examine how the Environment, Social, and Governance score (ESG) and the three pillars such as Return on Assets, Return on Equity, and Tobin's (Q) affect the performance of banks using data collected from 3450 observations across 40 different nations over ten years of (2011-2020). it also consider implications for governance, macroeconomics, and specific bank attributes. The results indicate a negative correlation between ESG and operational performance (ROA), financial performance (ROE), and market performance (TQ). The inclusion of diverse political and economic contexts lends distinctiveness to this paper. the findings hold significant theoretical implications for global scholars and policymakers. The limited correlation between ESG, its pillars, and the performance of banks and financial services underscores managerial shortcomings within these sectors.

Keywords: bank specialization, financial crisis, credit risk, difference-in-differences, herfindahl hirschman index

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Authors: Amira Mabrouk

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This paper deals with the acceptability of urban toll in Tunisia. The price-based regulation, i.e. urban toll, is the outcome of a political process hampered by three-fold objectives: effectiveness, equity and social acceptability. This produces both economic interest groups and functions that are of incongruent preferences. The plausibility of this speculation goes hand in hand with the fact that these economic interest groups are also taxpayers who undeniably perceive urban toll as an additional charge. This wariness is coupled with an inquiry about the conditions of usage, the redistribution of the collected tax revenue and the idea of the leviathan state completes the picture. In a nutshell, if researches related to road congestion proliferate, no de facto legitimacy can be pleaded. Nonetheless, the theory on urban tolls engenders economists’ questioning of ways to reduce negative external effects linked to it. Only then does the urban toll appear to bear an answer to these issues. Undeniably, the urban toll suggests inherent conflicts due to the apparent no-payment principal of a public asset as well as to the social perception of the new measure as a mere additional charge. However, when the main concern is effectiveness is its broad sense and the social well-being, the main factors that determine the acceptability of such a tariff measure along with the type of incentives should be the object of a thorough, in-depth analysis. Before adopting this economic role, one has to recognize the factors that intervene in the acceptability of a congestion toll which brought about a copious number of articles and reports that lacked mostly solid theoretical content. It is noticeable that nowadays uncertainties float over the exact nature of the acceptability process. Accepting a congestion tariff could differ from one era to another, from one region to another and from one population to another, etc. Notably, this article, within a convenient time frame, attempts at bringing into focus a link between the social acceptability of the urban congestion toll and the value of time through a survey method barely employed in Tunisia, that of stated preference method. How can the urban toll, as a tax, be defined, justified and made acceptable? How can an equitable and effective tariff of congestion toll be reached? How can the costs of this urban toll be covered? In what way can we make the redistribution of the urban toll revenue visible and economically equitable? How can the redistribution of the revenue of urban toll compensate the disadvantaged while introducing such a tariff measure? This paper will offer answers to these research questions and it follows the line of contribution of JULES DUPUIT in 1844.

Keywords: congestion charge, social perception, acceptability, stated preferences

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Authors: Shuchi Bharti

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This article intends to analyse the transforming nature of state and corporate sector relationship in the light of evolving regulatory and institutional aspects pertaining to Corporate Social Responsibility (CSR) in India. The focus is on evaluating the accounts of law and decentred discourses, relevant within the changing regulatory and institutional paradigm that substantially goes ahead of formal legal control of state towards corporate actors. At this vantage point, it is important to understand the state’s posture towards a changing scenario particularly as the tone is set by regulatory parameters pertaining to CSR to drive process of engagement with the stakeholders. The tripartite framework of the article intends to focus on finding on the vital interconnected aspects of the CSR provisions (Section 135) of The Companies Act 2013 (The Act), rise of new institutions and the emergence of the decentred regulatory space. Thus is earmarked in a neo-liberal paradigm; state is witnessed to perform a responsive function in engendering enhanced public role for the corporate sector. In this overarching framework the aim is to undertake a causal, exploratory and relational analysis of aspects pertaining law, regulation and institutional transformations. Firstly, focus is drawn on to investigate the relational facets of the advent of law and regulatory framework of CSR. Secondly, in the light of the historical evolution, a causal connection is attempted between globalization, emergence of international soft law framework and the Indian case of CSR. Finally, I look into how the new Companies Act mandates CSR expenditure vis- a -vis multiple parameters and guidelines.

Keywords: corporate social responsibility, stakeholders, soft law, decentred regulation

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have played an indispensable role in controlling illness and death associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global healthcare problem. Many antibiotics had lost their effectiveness since the beginning of the antibiotic era because many bacteria have adapted defenses against these antibiotics. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing require the isolation of the pathogen from a clinical specimen by culturing on the appropriate media (this culturing stage lasts 24 h-first culturing). Then, chosen colonies are grown on media containing antibiotic(s), using micro-diffusion discs (second culturing time is also 24 h) in order to determine its bacterial susceptibility. Other methods, genotyping methods, E-test and automated methods were also developed for testing antimicrobial susceptibility. Most of these methods are expensive and time-consuming. Fourier transform infrared (FTIR) microscopy is rapid, safe, effective and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria; nonetheless, its true potential in routine clinical diagnosis has not yet been established. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The UTI E.coli bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 700 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 90% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E.coli, FTIR, multivariate analysis, susceptibility, UTI

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Authors: Iva Trako, Maris Micaela Sviatschi, Guadalupe Kavanaugh

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Domestic violence is a major concern in developing countries, with important social, economic and health consequences. However, institutions do not usually address the problems facing women or ethnic and religious minorities. For example, the police do very little to stop domestic violence in rural areas of developing countries. This paper exploits the introduction of women’s justice centers (WJCs) in Peru to provide causal estimates on the effects of improving access to justice for women and children. These centers offer a new integrated public service model for women by including medical, psychological and legal support in cases of violence against women. Our empirical approach uses a difference in difference estimation exploiting variation over time and space in the opening of WJC together with province-by-year fixed effects. Exploiting administrative data from health providers and district attorney offices, we find that after the opening of these centers, there are important improvements on women's welfare: a large reduction in femicides and female hospitalizations for assault. Moreover, using geo-coded household surveys we find evidence that the existence of these services reduces domestic violence, improves women's health, increases women's threat points and, therefore, lead to household decisions that are more aligned with their interests. Using administrative data on the universe of schools, we find large gains on human capital for their children: affected children are more likely to enroll, attend school and have better grades in national exams, instead of working for the family. In sum, the evidence in this paper shows that providing access to justice for women can be a powerful tool to reduce domestic violence and increase education of children, suggesting a positive inter-generational benefit.

Keywords: access to justice, domestic violence, education, household bargaining

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Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

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Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

Procedia PDF Downloads 470