Search results for: affective-analytical decision framework

Authors: Yasser Mohamed Abdelrahman Tarshany

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The emergence of the digital economy has transformed global business and created new opportunities for growth and development. However, as digital technologies continue to reshape the global economy, there is a growing need to ensure that these transformations are guided by ethical principles that serve the common good. In this context, Maqasid, the Islamic ethical framework that focuses on the higher objectives and values of Shariah, offers a valuable lens for examining the ethical implications of digital transformation. The research objective of this study is to explore the opportunities and challenges of integrating Maqasid into the global digital economy from a business and management perspective. Specifically, the study aims to analyze the ethical implications of digital technologies for the economy and to identify strategies for leveraging Maqasid to promote ethical and socially responsible practices in the digital age. The study adopts a qualitative research methodology, drawing on existing literature and empirical data to develop a conceptual framework for understanding the relationship between Maqasid and the global digital economy. The study also employs case studies and interviews with business leaders and policymakers to explore practical strategies for integrating Maqasid into digital business practices. The research findings reveal that Maqasid can serve as a powerful framework for promoting ethical and socially responsible practices in the digital economy. Specifically, the study identifies several key strategies for leveraging Maqasid in digital business practices, including promoting social justice, protecting privacy and personal data, and ensuring transparency and accountability in business operations. The research outcomes of this study provide a valuable contribution to the field of business and management by demonstrating the importance of integrating ethical principles into the digital economy. Furthermore, the study highlights the potential of Maqasid as a powerful framework for promoting ethical and socially responsible practices in the digital age. Finally, the study suggests several avenues for future research, including exploring the role of Maqasid in promoting digital inclusion and reducing inequality in the global economy.

Keywords: Maqasid, global digital, economy, opportunities, challenges for business, management

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Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

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Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

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Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

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Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

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Authors: Dimitrios J. Dimitriou

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It is widely recognised that the assets portfolio development is helping to enhance economic growth, productivity and competitiveness. While numerous studies and reports certify the positive effect of investments in large infrastructure investments on the local economy, still, the methodology to estimate the contribution in economic development is a challenging issue for researchers and economists. The key question is how to estimate those economic impacts in each economic system. This paper provides a compact and applicable methodological framework providing quantitative results in terms of the overall jobs and income generated into the project life cycle. According to a deterministic mathematical approach, the key variables and the modelling framework are presented. The numerical case study highlights key results for a new motorway project in Greece, which is experienced economic stress for many years, providing the opportunity for comparisons with similar cases.

Keywords: quantitative modelling, economic impact, large transport infrastructure, economic assessment

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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Authors: Lethamaga Tladi, Ray Kekwaletswe

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This study sought to conceptualise a multi-level framework for the effective use of stock ordering system in small enterprises in a rural area context. The interpretive research methodology has been used to enable the researcher to analyse, in-depth, and the subjective meanings of small enterprises’ employees in using the stock ordering system. The empirical data was collected from 13 small enterprises’ employees as participants through semi-structured interviews and observations. Interpretive Phenomenological Analysis (IPA) approach was used to analyse the small enterprises’ employee’s own account of lived experiences in relations to stock ordering system use in terms of their relatedness to, and cognitive engagement with. A case study of Kgautswane, a rural area in Limpopo Province, South Africa, served as a social context where the phenomenon manifested. Technology-Organisation-Environment Theory (TOE), Technology-to-Performance Chain Model (TPC), and Representation Theory (RT) underpinned this study. In this multi-level study, the findings revealed that; At the organisational level, the effective use of stock ordering system was found to be associated with the organisational performance gains such as efficiency, productivity, quality, competitiveness, and market share. Equally so, at the individual level, the effective use of stock ordering system minimised the end-user’s efforts and time to accomplish their tasks, which yields improved individual performance. The Multi-level framework for effective use of stock ordering system was presented.

Keywords: effective use, multi-dimensions of use, multi-level of use, multi-level research, small enterprises, stock ordering system

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Authors: Micael Sousa

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Board games (BGs) are thriving as new designs emerge from the hobby community to greater audiences all around the world. Although digital games are gathering most of the attention in game studies and serious games research fields, the post-digital movement helps to explain why in the world dominated by digital technologies, the analog experiences are still unique and irreplaceable to users, allowing innovation in new hybrid environments. The BG’s new designs are part of these post-digital and hybrid movements because they result from the use of powerful digital tools that enable the production and knowledge sharing about the BGs and their face-to-face unique social experiences. These new BGs, defined as modern by many authors, are providing innovative designs and unique game mechanics that are still not yet fully explored by the main serious games (SG) approaches. Even the most established frameworks settled to address SG, as fun games implemented to achieve predefined goals need more development, especially when considering modern BGs. Despite the many anecdotic perceptions, researchers are only now starting to rediscover BGs and demonstrating their potentials. They are proving that BGs are easy to adapt and to grasp by non-expert players in experimental approaches, with the possibility of easy-going adaptation to players’ profiles and serious objectives even during gameplay. Although there are many design thinking (DT) models and practices, their relations with SG frameworks are also underdeveloped, mostly because this is a new research field, lacking theoretical development and the systematization of the experimental practices. Using BG as case studies promise to help develop these frameworks. Departing from the Design, Experience, and Play (DPE) framework and considering the Common Design Think Tools (CDST), this paper proposes a new experimental framework for the adaptation and development of modern BG design for DT: the Design, Experience, and Play for Think (DPET) experimental framework. This is done through the systematization of the DPE and CDST approaches applied in two case studies, where two different sequences of adapted BG were employed to establish a DT collaborative process. These two sessions occurred with different participants and in different contexts, also using different sequences of games for the same DT approach. The first session took place at the Faculty of Economics at the University of Coimbra in a training session of serious games for project development. The second session took place in the Casa do Impacto through The Great Village Design Jam light. Both sessions had the same duration and were designed to progressively achieve DT goals, using BGs as SGs in a collaborative process. The results from the sessions show that a sequence of BGs, when properly adapted to address the DPET framework, can generate a viable and innovative process of collaborative DT that is productive, fun, and engaging. The DPET proposed framework intents to help establish how new SG solutions could be defined for new goals through flexible DT. Applications in other areas of research and development can also benefit from these findings.

Keywords: board games, design thinking, methodology, serious games

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Authors: Samira-Sadat JamaliDinan, Haidar Almohri, Mohammad-Reza Nazem-Zadeh

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Lateralization of temporal lobe epilepsy (TLE) is very important for positive surgical outcomes. We propose a machine learning framework to ultimately identify the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Unlike most studies that use classification algorithms, we propose an effective clustering approach to distinguish between normal and TLE cases. We apply the famous Minkowski weighted K-Means (MWK-Means) technique as the clustering framework. To overcome the problem of poor initialization of K-Means, we use particle swarm optimization (PSO) to effectively select the initial centroids of clusters prior to applying MWK-Means. We demonstrate that compared to K-means and MWK-means independently, this approach is able to improve the result of a benchmark data set.

Keywords: temporal lobe epilepsy, machine learning, clustering, magnetoencephalography

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Authors: Shannon Hashemi, Alireza Daneshfar

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Accounting ethical awareness has been widely promoted in recent years both in academia and in practice. However, the effectiveness of ethical awareness on accountants' judgment and choice of action is still debatable. This study investigates whether Machiavellianism and gender, as significant personality factors, influence the effect of ethical awareness on accountants' decision-making. Using an experiment, the results of ANOVA tests show that although introducing ethical awareness positively influences the accountants' judgment and choice of action, such an effect is significantly moderated by the accountants' Machiavellianism score and gender. Specifically, the test results show that the effect of introducing ethical awareness was higher on males with low Machiavellian score. The results also show that when the Machiavellian scores were high, the effect of ethical awareness was lower for both males and females. Applications of the results are discussed for accounting professionals as well as accounting ethics educators and researchers.

Keywords: ethical awareness, accounting decision making, Machiavellianism, ANOVA, ethics, accounting education

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Authors: Salam Abukhadrah

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This research advocates for the use of feminist evaluation (FE) as a tool of great potential in policy and program assessment in relation to women’s empowerment. This research explores the journey of women’s place into the evaluation and international development. Moreover, this research presents a case example of the use of FE on the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), in Ganaparthi village in rural India, in Andhra Pradesh state (AP). This evaluation is formed on the basis of women’s empowerment framework that seeks to examine empowerment as a process and an end in itself rather than as just simplified quantifiable outcomes. This framework is used to conduct in-depth semi-structured interviews that are later cross-validated by a focus group discussion. In addition, this evaluation draws on secondary data from the MGNREGA website and on extracted data from the National Family Health Survey of AP.

Keywords: feminist evaluation, MGNREGA, women’s empowerment, case example, India

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Authors: Bahadir Aydin

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Today it is difficult to reach accurate knowledge because of mass data. This huge data makes the environment more and more caotic. Data is a main piller of intelligence. There is a close tie between knowledge and intelligence. Information gathered from different sources can be modified, interpreted and classified by using knowledge development process. This process is applied in order to attain intelligence. Within this process the effect of knowledge is crucial. Knowledge is classified as explicit and tacit knowledge. Tacit knowledge can be seen as "only the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose for all organization is to be succesful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. By the help of process the decision-maker can be presented with a clear holistic understanding, as early as possible in the decision making process. Planning, execution and assessments are the key functions that connects to information to knowledge. Altering from the current traditional reactive approach to a proactive knowledge development approach would reduce extensive duplication of work in the organization. By new approach to this process, knowledge can be used more effectively.

Keywords: knowledge, intelligence cycle, tacit knowledge, KIDW

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Authors: Tim Crocker-Buque, Sandra Mounier-Jack, Natasha Howard

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Background: Due to both the increasing scale and speed of urbanisation, urban areas in low and middle-income countries (LMICs) host increasingly large populations of under-immunized children, with the additional associated risks of rapid disease transmission in high-density living environments. Multiple interdependent factors are associated with these coverage disparities in urban areas and most evidence comes from relatively few countries, e.g., predominantly India, Kenya, Nigeria, and some from Pakistan, Iran, and Brazil. This study aimed to identify, describe, and assess the main tools used to measure or improve coverage of immunisation services in poor urban areas. Methods: Authors used a qualitative review design, including academic and non-academic literature, to identify tools used to improve coverage of public health interventions in urban areas. Authors selected and extracted sources that provided good examples of specific tools, or categories of tools, used in a context relevant to urban immunization. Diagnostic (e.g., for data collection, analysis, and insight generation) and programme tools (e.g., for investigating or improving ongoing programmes) and interventions (e.g., multi-component or stand-alone with evidence) were selected for inclusion to provide a range of type and availability of relevant tools. These were then prioritised using a decision-analysis framework and a tool selection guide for programme managers developed. Results: Authors reviewed tools used in urban immunisation contexts and tools designed for (i) non-immunization and/or non-health interventions in urban areas, and (ii) immunisation in rural contexts that had relevance for urban areas (e.g., Reaching every District/Child/ Zone). Many approaches combined several tools and methods, which authors categorised as diagnostic, programme, and intervention. The most common diagnostic tools were cross-sectional surveys, key informant interviews, focus group discussions, secondary analysis of routine data, and geographical mapping of outcomes, resources, and services. Programme tools involved multiple stages of data collection, analysis, insight generation, and intervention planning and included guidance documents from WHO (World Health Organisation), UNICEF (United Nations Children's Fund), USAID (United States Agency for International Development), and governments, and articles reporting on diagnostics, interventions, and/or evaluations to improve urban immunisation. Interventions involved service improvement, education, reminder/recall, incentives, outreach, mass-media, or were multi-component. The main gaps in existing tools were an assessment of macro/policy-level factors, exploration of effective immunization communication channels, and measuring in/out-migration. The proposed framework uses a problem tree approach to suggest tools to address five common challenges (i.e. identifying populations, understanding communities, issues with service access and use, improving services, improving coverage) based on context and available data. Conclusion: This study identified many tools relevant to evaluating urban LMIC immunisation programmes, including significant crossover between tools. This was encouraging in terms of supporting the identification of common areas, but problematic as data volumes, instructions, and activities could overwhelm managers and tools are not always suitably applied to suitable contexts. Further research is needed on how best to combine tools and methods to suit local contexts. Authors’ initial framework can be tested and developed further.

Keywords: health equity, immunisation, low and middle-income countries, poverty, urban health

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Authors: P. Amarnath, Albert Thomas

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Buildings qualify to be the major consumer of energy and resources thereby urging the designers, architects and policy makers to place a great deal of effort in achieving and implementing sustainable building strategies in construction. Green building rating systems help a great deal in this by measuring the effectiveness of these strategies along with the escalation of building performance in social, environmental and economic perspective, and construct new sustainable buildings. However, for a country like India, enormous population and its rapid rate of growth impose an increasing burden on the country's limited and continuously degrading natural resource base, which also includes the land available for construction. In general, the number of sustainable rated buildings in India is very minimal primarily due to the complexity and obstinate nature of the assessment systems/regulations that restrict the stakeholders and designers in proper implementation and utilization of these rating systems. This paper aims to introduce a data driven and user-friendly framework which cross compares the present prominent green building rating systems such as LEED, BREEAM, and GRIHA and subsequently help the users to rate their proposed building design as per the regulations of these assessment frameworks. This framework is validated using the input data collected from green buildings constructed globally. The proposed system has prospects to encourage the users to test the efficiency of various sustainable construction practices and thereby promote more sustainable buildings in the country.

Keywords: BREEAM, GRIHA, green building rating systems, LEED, sustainable buildings

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Authors: Mitra Ghiasi, Roghayeh Ghorbani Bousari

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Nowadays, the aim of the organizations is to gain sustainable competitive. So, developing their intellectual capital, encouraging innovation, increasing suitable performance can be done by knowledge management. Knowledge turns into science if knowledge is used to improve decision making, decision quality and make effective decisions. The current research intends to investigate the relationship between cybernetics and knowledge management from the perspective of users who are members of electronic discussion groups (ALA, ALIA). The research methodology is survey method, and it is a type of correlation research. Cybernetics and knowledge management questionnaires used for collecting data. The questionnaire that was designed in electronic format, distributed among two electronic discussion groups during 30 days and completed by 100 members of each electronic discussion groups. The finding of this research showed that although cybernetics has an impact on knowledge management, there is no significant difference between the ALA and ALIA user's view regard to effect of cybernetics on knowledge management. The results also indicated that this conceptual model is consistent with the data collected from the sample.

Keywords: ALA discussion group, ALIA discussion group, cybernetics, knowledge management

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Authors: Mohammadali Tavakoli, Atefeh Heydari, Zuriati Ismail, Naomie Salim

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With the increasing number of people reviewing products online in recent years, opinion sharing websites has become the most important source of customers’ opinions. Unfortunately, spammers generate and post fake reviews in order to promote or demote brands and mislead potential customers. These are notably destructive not only for potential customers but also for business holders and manufacturers. However, research in this area is not adequate, and many critical problems related to spam detection have not been solved to date. To provide green researchers in the domain with a great aid, in this paper, we have attempted to create a high-quality framework to make a clear vision on review spam-detection methods. In addition, this report contains a comprehensive collection of detection metrics used in proposed spam-detection approaches. These metrics are extremely applicable for developing novel detection methods.

Keywords: fake reviews, feature collection, opinion spam, spam detection

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: Bi Xiao Fang, Tan Bao Zhen

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Soft skills, core competencies, and generic competencies are exchangeable terminologies often used to represent a similar concept. In the Singapore context, such skills are currently being referred to as Critical Core Skills (CCS). In 2019, SkillsFuture Singapore (SSG) reviewed the Generic Skills and Competencies (GSC) framework that was first introduced in 2016, culminating in the development of the Critical Core Skills (CCS) framework comprising 16 soft skills classified into three clusters. The CCS framework is part of the Skills Framework, and whose stated purpose is to create a common skills language for individuals, employers and training providers. It is also developed with the objectives of building deep skills for a lean workforce, enhance business competitiveness and support employment and employability. This further helps to facilitate skills recognition and support the design of training programs for skills and career development. According to SSG, every job role requires a set of technical skills and a set of Critical Core Skills to perform well at work, whereby technical skills refer to skills required to perform key tasks of the job. There has been an increasing emphasis on soft skills for the future of work. A recent study involving approximately 80 organizations across 28 sectors in Singapore revealed that more enterprises are beginning to recognize that soft skills support their employees’ performance and business competitiveness. Though CCS is of high importance for the development of the workforce’s employability, there is little attention paid to the CCS use and profiling across occupations. A better understanding of how CCS is distributed across the economy will thus significantly enhance SSG’s career guidance services as well as training providers’ services to graduates and workers and guide organizations in their hiring for soft skills. This CCS profiling study sought to understand how CCS is demanded in different occupations. To achieve its research objectives, this study adopted a quantitative method to measure CCS use across different occupations in the Singaporean workforce. Based on the CCS framework developed by SSG, the research team adopted a formative approach to developing the CCS profiling tool to measure the importance of and self-efficacy in the use of CCS among the Singaporean workforce. Drawing on the survey results from 2500 participants, this study managed to profile them into seven occupation groups based on the different patterns of importance and confidence levels of the use of CCS. Each occupation group is labeled according to the most salient and demanded CCS. In the meantime, the CCS in each occupation group, which may need some further strengthening, were also identified. The profiling of CCS use has significant implications for different stakeholders, e.g., employers could leverage the profiling results to hire the staff with the soft skills demanded by the job.

Keywords: employability, skills profiling, skills measurement, soft skills

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Authors: Tarun Chand, Michael Jurczyk

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With the increasing need and popularity of IoT devices and how integrated they are becoming in our daily lives and industries, these devices make for a very lucrative target for malicious actors. And since these devices have such limited resources, the implementation of robust security features is a tradeoff to be made for the actual functionality the device was intended for. This makes them an easy target with high returns. Several frameworks for the secure firmware update of these devices have been recently proposed in the literature. They focus on methods such as blockchains and distributed file systems to secure firmware updates, but do not go into the details of the actual implementation of these frameworks and the lower-level interactions among these methods used. This work integrates some of these security measures into one overall framework and details the actual lower-level implementation of this framework in a virtual dockerized testbed running on AWS.

Keywords: blockchain, Ethereum, Geth, IPFS, secure IoT-firmware update, virtual testbed development

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: U. S. Putro, L. Mayangsari, M. Siallagan, N. P. Tjahyani

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National Collective Management Institute (LKMN) in Indonesia stated that legal music products were about 77.552.008 unit while illegal music products were about 22.0688.225 unit in 1996 and this number keeps getting worse every year. Consequently, Indonesia named as one of the countries with high piracy levels in 2005. This study models people decision toward unlawful behavior, music content piracy in particular, using agent-based modeling and simulation (ABMS). The classification of actors in the model constructed in this study are legal consumer, illegal consumer, and neutral consumer. The decision toward piracy among the actors is a manifestation of the social norm which attributes are social pressure, peer pressure, social approval, and perceived prevalence of piracy. The influencing attributes fluctuate depending on the majority of surrounding behavior called social network. There are two main interventions undertaken in the model, campaign and peer influence, which leads to scenarios in the simulation: positively-framed descriptive norm message, negatively-framed descriptive norm message, positively-framed injunctive norm with benefits message, and negatively-framed injunctive norm with costs message. Using NetLogo, the model is simulated in 30 runs with 10.000 iteration for each run. The initial number of agent was set 100 proportion of 95:5 for illegal consumption. The assumption of proportion is based on the data stated that 95% sales of music industry are pirated. The finding of this study is that negatively-framed descriptive norm message has a worse reversed effect toward music piracy. The study discovers that selecting the context-based campaign is the key process to reduce the level of intention toward music piracy as unlawful behavior by increasing the compliance awareness. The context of Indonesia reveals that that majority of people has actively engaged in music piracy as unlawful behavior, so that people think that this illegal act is common behavior. Therefore, providing the information about how widespread and big this problem is could make people do the illegal consumption behavior instead. The positively-framed descriptive norm message scenario works best to reduce music piracy numbers as it focuses on supporting positive behavior and subject to the right perception on this phenomenon. Music piracy is not merely economical, but rather social phenomenon due to the underlying motivation of the actors which has shifted toward community sharing. The indication of misconception of value co-creation in the context of music piracy in Indonesia is also discussed. This study contributes theoretically that understanding how social norm configures the behavior of decision-making process is essential to breakdown the phenomenon of unlawful behavior in music industry. In practice, this study proposes that reward-based and context-based strategy is the most relevant strategy for stakeholders in music industry. Furthermore, this study provides an opportunity that findings may generalize well beyond music piracy context. As an emerging body of work that systematically constructs the backstage of law and social affect decision-making process, it is interesting to see how the model is implemented in other decision-behavior related situation.

Keywords: music piracy, social norm, behavioral decision-making, agent-based model, value co-creation

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Authors: Mokgadi Julia Ngoepe-Ntsoane

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The article aims to make a case for a legislative framework for the fire sector in South Africa. Robust legislative framework is essential for empowering those with obligatory mandate within the sector. This article contributes to the body of knowledge in the field of policy reviews particularly with regards to the legal framework. It has been observed overtime that the scholarly contributions in this field are limited. Document analysis was the methodology selected for the investigation of the various legal frameworks existing in the country. It has been established that indeed the national legislation on the fire industry does not exist in South Africa. From the documents analysed, it was revealed that the sector is dominated by cartels who are exploiting the new entrants to the market particularly SMEs. It is evident that these cartels are monopolising the system as they have long been operating in the system turning it into self- owned entities. Commitment to addressing the challenges faced by fire services and creating a framework for the evolving role that fire brigade services are expected to execute in building safer and sustainable communities is vital. Legislation for the fire sector ought to be concluded with immediate effect. The outdated national fire legislation has necessitated the monopolisation and manipulation of the system by dominating organisations which cause a painful discrimination and exploitation of smaller service providers to enter the market for trading in that occupation. The barrier to entry bears long term negative effects on national priority areas such as employment creation, poverty, and others. This monopolisation and marginalisation practices by cartels in the sector calls for urgent attention by government because if left attended, it will leave a lot of people particularly women and youth being disadvantaged and frustrated. The downcast syndrome exercised within the fire sector has wreaked havoc and is devastating. This is caused by cartels that have been within the sector for some time, who know the strengths and weaknesses of processes, shortcuts, advantages and consequences of various actions. These people take advantage of new entrants to the sector who in turn find it difficult to manoeuvre, find the market dissonant and end up giving up their good ideas and intentions. There are many pieces of legislation which are industry specific such as housing, forestry, agriculture, health, security, environmental which are used to regulate systems within the institutions involved. Other regulations exist as bi-laws for guiding the management within the municipalities.

Keywords: sustainable job creation, growth and development, transformation, risk management

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Authors: Khaled Selatnia

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Nowadays, the traffic congestion becomes increasingly a chronic problem. Sometimes, the cause is attributed to the recurrent road works that create barriers to the efficient movement. But congestion, which usually occurs in cities, can take diverse forms and magnitudes. The case study of Biskra city in Algeria and the diagnosis of its road network show that throughout all the micro regional system, the road network seems at first quite dense. However, this density although it is important, does not cover all areas. A major flow is concentrated in the axis Sidi Okba – Biskra – Tolga. The largest movement of people in the Wilaya (prefecture) revolves around these three centers and their areas of influence. Centers farthest from the trio are very poorly served. This fact leads us to ask questions about the extent of congestion in Biskra city and its relationship to the imbalance of the urban framework. The objective of this paper is to highlight the impact of the urban fact on the traffic congestion.

Keywords: congestion, urban framework, regional, urban and regional studies

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Authors: Beatrice Arthur

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The rapid development of artificial intelligence (AI) has transformed various industries, enabling faster and more accurate decision-making processes. However, with these advancements come increased risks, including data privacy issues, systemic biases, and challenges related to transparency and accountability. As AI technologies become more integrated into business processes, there is a growing need for comprehensive auditing and assurance frameworks to manage these risks and ensure ethical use. This paper provides a literature review on AI auditing and assurance programs, highlighting the importance of adapting traditional audit methodologies to the complexities of AI-driven systems. Objective: The objective of this review is to explore current AI audit practices and their role in mitigating risks, ensuring accountability, and fostering trust in AI systems. The study aims to provide a structured framework for developing audit programs tailored to AI technologies while also investigating how AI impacts governance, risk management, and regulatory compliance in various sectors. Methodology: This research synthesizes findings from academic publications and industry reports from 2014 to 2024, focusing on the intersection of AI technologies and IT assurance practices. The study employs a qualitative review of existing audit methodologies and frameworks, particularly the COBIT 2019 framework, to understand how audit processes can be aligned with AI governance and compliance standards. The review also considers real-time auditing as an emerging necessity for influencing AI system design during early development stages. Outcomes: Preliminary findings indicate that while AI auditing is still in its infancy, it is rapidly gaining traction as both a risk management strategy and a potential driver of business innovation. Auditors are increasingly being called upon to develop controls that address the ethical and operational risks posed by AI systems. The study highlights the need for continuous monitoring and adaptable audit techniques to handle the dynamic nature of AI technologies. Future Directions: Future research will explore the development of AI-specific audit tools and real-time auditing capabilities that can keep pace with evolving technologies. There is also a need for cross-industry collaboration to establish universal standards for AI auditing, particularly in high-risk sectors like healthcare and finance. Further work will involve engaging with industry practitioners and policymakers to refine the proposed governance and audit frameworks. Funding/Support Acknowledgements: This research is supported by the Information Systems Assurance Management Program at Concordia University of Edmonton.

Keywords: AI auditing, assurance, risk management, governance, COBIT 2019, transparency, accountability, machine learning, compliance

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Authors: Maria M. Calheiros, Carla Silva, Eunice Magalhães

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Professionals working in child protection services (CPS) need to have common and clear criteria to identify cases of maltreatment and to differentiate levels of severity in order to determine when CPS intervention is required, its nature and urgency, and, in most countries, the service that will be in charge of the case (community or specialized CPS). Actually, decision-making process is complex in CPS, and, for that reason, such criteria are particularly important for who significantly contribute to that decision-making in child maltreatment cases. The main objective of this presentation is to describe the Maltreatment Severity Assessment Questionnaire (MSQ), specifically designed to be used by professionals in the CPS, which adopts a multidimensional approach and uses a scale of severity within subtypes. Specifically, we aim to provide evidence of validity and reliability of this tool, in order to improve the quality and validity of assessment processes and, consequently, the decision making in CPS. The total sample was composed of 1000 children and/or adolescents (51.1% boys), aged between 0 and 18 years old (M = 9.47; DP = 4.51). All the participants were referred to official institutions of the children and youth protective system. Children and adolescents maltreatment (abuse, neglect experiences and sexual abuse) were assessed with 21 items of the Maltreatment Severity Questionnaire (MSQ), by professionals of CPS. Each item (sub-type) was composed of four descriptors of increasing severity. Professionals rated the level of severity, using a 4-point scale (1= minimally severe; 2= moderately severe; 3= highly severe; 4= extremely severe). The construct validity of the Maltreatment Severity Questionnaire was assessed with a holdout method, performing an Exploratory Factor Analysis (EFA) followed by a Confirmatory Factor Analysis (CFA). The final solution comprised 18 items organized in three factors 47.3% of variance explained. ‘Physical neglect’ (eight items) was defined by parental omissions concerning the insurance and monitoring of the child’s physical well-being and health, namely in terms of clothing, hygiene, housing conditions and contextual environmental security. ‘Physical and Psychological Abuse’ (four items) described abusive physical and psychological actions, namely, coercive/punitive disciplinary methods, physically violent methods or verbal interactions that offend and denigrate the child, with the potential to disrupt psychological attributes (e.g., self-esteem). ‘Psychological neglect’ (six items) involved omissions related to children emotional development, mental health monitoring, school attendance, development needs, as well as inappropriate relationship patterns with attachment figures. Results indicated a good reliability of all the factors. The assessment of child maltreatment cases with MSQ could have a set of practical and research implications: a) It is a valid and reliable multidimensional instrument to measure child maltreatment, b) It is an instrument integrating the co-occurrence of various types of maltreatment and a within-subtypes scale of severity; c) Specifically designed for professionals, it may assist them in decision-making processes; d) More than using case file reports to evaluate maltreatment experiences, researchers could guide more appropriately their research about determinants and consequences of maltreatment.

Keywords: assessment, maltreatment, children and youth, decision-making

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Authors: Seokyoon Moon, Yun-Ho Ahn, Heejoong Kim, Sujin Hong, Yunseok Lee, Youngjune Park

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Gas hydrate is a non-stoichiometric crystalline compound consisting of host water-framework and low molecular weight guest molecules. Small gaseous molecules such as CH₄, CO₂, and N₂ can be captured in the host water framework lattices of the gas hydrate with specific temperature and pressure conditions. The three well-known crystal structures of structure I (sI), structure II (sII), and structure H (sH) are determined by the size and shape of guest molecules. In this study, we measured the phase equilibria of binary (2,2-dimethyl-1-propanol + CO₂, CH₄, N₂) hydrates to explore their fundamental thermodynamic characteristics. We identified the structure of the binary gas hydrate by employing synchrotron high-resolution powder diffraction (HRPD), and the guest distributions in the lattice of gas hydrate were investigated via dispersive Raman and ¹³C solid-state nuclear magnetic resonance (NMR) spectroscopies. The end-to-end distance of 2,2-dimethyl-1-propanol was calculated to be 7.76 Å, which seems difficult to be enclathrated in large cages of sI or sII. However, due to the flexibility of the host water framework, binary hydrates of sI or sII types can be formed with the help of small gas molecule. Also, the synchrotron HRPD patterns revealed that the binary hydrate structure highly depends on the type of help gases; a cubic Fd3m sII hydrate was formed with CH₄ or N₂, and a cubic Pm3n sI hydrate was formed with CO₂. Interestingly, dispersive Raman and ¹³C NMR spectra showed that the unique tuning phenomenon occurred in binary (2,2-dimethyl-1-propanol + CO₂) hydrate. By optimizing the composition of NPA, we can achieve both thermodynamic stability and high CO₂ storage capacity for the practical application to CO₂ capture.

Keywords: clathrate, gas hydrate, neopentyl alcohol, CO₂, tuning phenomenon

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Authors: Ali Zaimi

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Citizen participation in local government is an opportunity given to citizens and government to increase communication between them, create public support for local government plans and most important grow public trust in government. Also, the citizens’ involvement in the political process is an important part of democracy. This study aims to define the strategies for increasing citizen participation in local governance and concentrated in two important mechanisms such as participatory budget and public policy councils. Three strategies that promote more effective citizen involvement in local governance are understanding and using formal institutions of power, collaboration of citizens’ groups and governments officials to jointly formulate programs plans, electing and appointing local officials. A unique aspect of citizen participation to operate effectively is the transparency of government and the inclusion of actors into decision-making. The citizen engagement in local governance enhances accountability and problem solving, promote more inclusive and cohesive communities and enlarge the quality and quantity of initiatives made by communities.

Keywords: accountability, citizen participation, democracy, government

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Authors: Mohammed Ali Ahmed, Vaughan Coffey, Bo Xia

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Quality management systems (QMSs) in the construction industry are often implemented to ensure that sufficient effort is made by companies to achieve the required levels of quality for clients. Attainment of these quality levels can result in greater customer satisfaction, which is fundamental to ensure long-term competitiveness for construction companies. However, the construction sector is still lagging behind other industries in terms of its successful adoption of QMSs, due to the relative lack of acceptance of the benefits of these systems among industry stakeholders, as well as from other barriers related to implementing them. Thus, there is a critical need to undertake a detailed and comprehensive exploration of adoption of QMSs in the construction sector. This paper comprehensively investigates in the construction sector setting, the impacts of all the salient factors surrounding successful implementation of QMSs in building organizations, especially those of external factors. This study is part of an ongoing PhD project, which aims to develop a new framework that integrates both internal and external factors affecting QMS implementation. To achieve the paper aim and objectives, interviews will be conducted to define the external factors influencing the adoption of QMSs, and to obtain holistic critical success factors (CSFs) for implementing these systems. In the next stage of data collection, a questionnaire survey will be developed to investigate the prime barriers facing the adoption of QMSs, the CSFs for their implementation, and the external factors affecting the adoption of these systems. Following the survey, case studies will be undertaken to validate and explain in greater detail the real effects of these factors on QMSs adoption. Specifically, this paper evaluates the effects of the external factors in terms of their impact on implementation success within the selected case studies. Using findings drawn from analyzing the data obtained from these various approaches, specific recommendations for the successful implementation of QMSs will be presented, and an operational framework will be developed. Finally, through a focus group, the findings of the study and the new developed framework will be validated. Ultimately, this framework will be made available to the construction industry to facilitate the greater adoption and implementation of QMSs. In addition, deployment of the applicable recommendations suggested by the study will be shared with the construction industry to more effectively help construction companies to implement QMSs, and overcome the barriers experienced by businesses, thus promoting the achievement of higher levels of quality and customer satisfaction.

Keywords: barriers, critical success factors, external factors, internal factors, quality management systems

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Authors: Roopa Singh, Anurag Singh, Ajay

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Agriculture contributes a major share in the national economy of India. A major portion of Indian economy (about 70%) depends upon agriculture as it forms the main source of income. About 43% of India’s geographical area is used for agricultural activity which involves 65-75% of total population of India. The given work deals with the Fast moving Consumer Goods (FMCG) industries and their inventories which use agricultural produce as their raw material or input for their final product. Since the beginning of inventory practices, many developments took place which can be categorised into three phases, based on the review of various works. The first phase is related with development and utilization of Economic Order Quantity (EOQ) model and methods for optimizing costs and profits. Second phase deals with inventory optimization method, with the purpose of balancing capital investment constraints and service level goals. The third and recent phase has merged inventory control with electrical control theory. Maintenance of inventory is considered negative, as a large amount of capital is blocked especially in mechanical and electrical industries. But the case is different in food processing and agro-based industries and their inventories due to cyclic variation in the cost of raw materials of such industries which is the reason for selection of these industries in the mentioned work. The application of electrical control theory in inventory control makes the decision-making highly instantaneous for FMCG industries without loss in their proposed profits, which happened earlier during first and second phases, mainly due to late implementation of decision. The work also replaces various inventories and work-in-progress (WIP) related errors with their monetary values, so that the decision-making is fully target-oriented.

Keywords: control theory, inventory control, manufacturing sector, EOQ, feedback, FMCG sector

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Authors: Shaikh Farhad Hossain, Liakot Ali

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Technology advances accelerate the quality and type of services provided for health care and especially for monitoring health conditions. Sensors have turned out to be more effective to detect diverse physiological signs and can be worn on the human body utilizing remote correspondence modules. An assortment of programming devices have been created to help in preparing a difference rundown of essential signs by examining and envisioning information produced by different sensors. In this proposition, we presented a Health signs and Activity acknowledgment monitoring system. Utilizing off-the-rack sensors, we executed a movement location system for identifying five sorts of action: falling, lying down, sitting, standing, and walking. The framework collects and analyzes sensory data in real-time, and provides different feedback to the users. In addition, it can generate alerts based on the detected events and store the data collected to a medical server.

Keywords: ADL, SVM, TRIL , MEMS

Procedia PDF Downloads 398