Search results for: clinical decision support systems

Authors: Humayun Murshed, Shibly Abdullah

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The research conducted in early seventies apparently assumed the existence of a universal decision model for union negotiators and furthermore tended to regard financial information as a ‘neutral’ input into a rational decision-making process. However, research in the eighties began to question the neutrality of financial information as an input in collective bargaining rather viewing it as a potentially effective means for controlling the labour force. Furthermore, this later research also started challenging the simplistic assumptions relating particularly to union objectives which have underpinned the earlier search for universal union decision models. Despite the above developments there seems to be a dearth of studies in developing countries concerning the use of financial information in collective bargaining. This paper seeks to begin to remedy this deficiency. Utilising a case study approach based on two enterprises, one in the public sector and the other a multinational, the universal decision model is rejected and it is argued that the decision whether or not to use financial information is a contingent one and such a contingency is largely defined by the context and environment in which both union and management negotiators work. An attempt is also made to identify the factors constraining as well as promoting the use of financial information in collective bargaining, these being regarded as unique to the organizations within which the case studies are conducted.

Keywords: collective bargaining, developing countries, disclosures, financial information

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

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Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: augmented reality, situation awareness, decision-making, problem-solving

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Authors: Julianne Macmullen

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Due to advances in technology and early detection and treatment of cancer, many cancer patients are surviving longer than five years post-diagnosis. Most cancer patients suffer from depression, anxiety, and post-traumatic stress disorder (PTSD) at some point during diagnosis, treatment, and survivorship. A subgroup of patients will continue to suffer from depression and PTSD and require early intervention. Support groups provide patients with the emotional and informational support they require while also giving survivors a sense of community, friendship, and purpose. This type of support is recognized by researchers to improve the quality of life while also decreasing depression and PTSD symptoms. The gaps in the literature include cultural diversity, minorities, and support groups involving cancer types other than breast cancer. Another gap in the literature includes the perceptions of cancer patients as well as longitudinal studies to determine the relationships between support groups and decreased depression and PTSD rates over time. Future research is required to fill the gaps in the literature mentioned previously. Future research is also needed to analyze the difference in age groups and different types of support groups such as professionally-led, peer-led, and online. Implications for practice involve providers assessing for the symptoms of depression and PTSD in order to offer prompt treatment and support services to those patients. In conclusion, social support by way of support groups improves the quality of life, gives survivors a sense of purpose to help others while also gaining the support they need, and reduces the rate of depressive episodes related to PTSD.

Keywords: cancer survivor, survivorship, post-traumatic stress disorder (PTSD), depression, support groups

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Authors: Mahdi Bastan, Ali Mohammad Ahmadvand, Fatemeh Soltani Khamsehpour

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Health organizations’ sustainable development has nowadays become highly affected by customers’ satisfaction due to significant changes made in the business environment of the healthcare system and emerging of Competitiveness paradigm. In case we look at the hospitals and other health organizations as service providers concerning profit issues, the satisfaction of employees as interior customers, and patients as exterior customers would be of significant importance in health business success. Furthermore, satisfaction rate could be considered in performance assessment of healthcare organizations as a perceived quality measure. Several researches have been carried out in identification of effective factors on patients’ satisfaction in health organizations. However, considering a systemic view, the complex causal relations among many components of healthcare system would be an issue that its acquisition and sustainability requires an understanding of the dynamic complexity, an appropriate cognition of different components, and effective relationships among them resulting ultimately in identifying the generative structure of patients’ satisfaction. Hence, the presenting paper applies system dynamics approaches coherently and methodologically to represent the systemic structure of customers’ satisfaction of a health system involving the constituent components and interactions among them. Then, the results of different policies taken on the system are simulated via developing mathematical models, identifying leverage points, and using scenario making technique and then, the best solutions are presented to improve customers’ satisfaction of the services. The presenting approach supports taking advantage of decision support systems. Additionally, relying on understanding of system behavior Dynamics, the effective policies for improving the health system would be recognized.

Keywords: customer satisfaction, healthcare, scenario, simulation, system dynamics

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Authors: Erfan Izadpanah

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The present study was conducted to investigate the effect of the Trans-Cranial Direct Current Stimulation (tDCS) on cognitive flexibility and social decision-making in skilled, semi-skilled and novice football players. The present quasi-experimental pretest-posttest study was conducted on 60 randomly-selected subjects divided into trial and placebo groups (n=30 per group). The trial group received three 20-minute sessions of anodic stimulation at the intensity of 2 mA. The placebo group also received three sessions of sham anodic stimulation. Data were collected using the Wisconsin, Grant and Berg Card-Sorting Test (1948) and the ultimatum game and were then analyzed using the ANCOVA. The results showed significant differences between the skilled, semi-skilled and novice football players in the trial and placebo groups in terms of cognitive flexibility and social decision-making (P<0.01). TDCS appears to be able to improve cognitive flexibility and consequently social decision-making in football players and is recommended to sport psychologists and coaches as a useful intervention to increase cognitive flexibility and improve social decision-making in players.

Keywords: TDCS, cognitive flexibility, social decision-making, skilled, semi-skilled and novice football players

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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Authors: M. Hirani, M. Devine, O. Obisesan, C. Bryant

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Introduction: The use of four or more implants to support a fixed prosthesis in the edentulous mandible is well documented, with high levels of clinical outcomes recorded. Despite this, the use of three implant-supported fixed prostheses offers the potential to deliver a more cost-effective method of oral rehabilitation in the lower arch, an important consideration given that edentulism is most prevalent in low-income subpopulations. The purpose of this study aimed to evaluate the implant and prosthetic survival rate, changes in marginal bone level, and patient satisfaction associated with a three-implant-supported fixed prosthesis for rehabilitation of the edentulous mandible over a follow-up period of at least one year. Methods: A comprehensive literature search was performed to evaluate studies that met the selection criteria. The information extracted included the study design and population, participant demographics, observation period, loading protocol, and the number of implants placed together with the required outcome measures. Mean values and standard deviations (SD) were calculated using SPSS® (IBM Corporation, New York, USA), and the level of statistical significance across all comparative studies described was set at P < 0.05. Results: The eligible studies included a total of 1968 implants that were placed in 652 patients. The subjects ranged in age from 33-89 years, with a mean of 63.2 years. The mean cumulative implant and prosthetic survival rates were 95.5% and 96.2%, respectively, over a mean follow-up period of 3.25 years. The mean marginal bone loss recorded was 1.04 mm, and high patient satisfaction rates were reported across the studies. Conclusion: Current evidence suggests that a three implant-supported fixed prosthesis for the edentulous mandible is a successful treatment strategy presenting high implant and prosthetic survival rates over the short-to-medium term. Further well-designed controlled clinical trials are required to evaluate longer-term outcomes, with supplemental data correlating implant dimensions and prosthetic design.

Keywords: implants, mandible, fixed, prosthesis

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Authors: Sakul Jariyachamsit

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The objectives of this research were to study the behaviour of inbound tourist who visited Ratanakosin Island and to study their needs concerning support facilities. The independent variables included gender, age, levels of education, occupation, and income while the dependent variables were classified into two groups: tourists’ behaviour variables and tourists’ need of supporting facilities. A simple random sampling method was utilized to get 225 respondents. The majority of respondents were both male and female in the same proportion but most were between 21-30 years old. Most were married with a graduated degree. The average income of the respondents was between $20,000-30,000. The findings revealed that the majority of respondents came to Thailand for the first time and spent about 8 days in Thailand and preferred to travel in small groups. Their decision to come to Thailand was influenced by word of mouth. When they first thought of Thailand, they thought of Thai food. In terms of the needs for tourists around the Ratanakosin Island, and ranked in importance, are as follows: a tourist centre, somebody who can speak English, a trustable agency, police patrol, and the availability of maps and brochures.

Keywords: Rattanakosin Island, tourist, travelling behaviour, media engineering

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Authors: Sree Sanyal

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Research in ageing often highlights the age-related health dimension more than the psycho-social characteristics of the elderly, which also influences and challenges the health outcomes. Multimorbidity is defined as the person having more than one chronic non-communicable diseases and their prevalence increases with ageing. The study aims to evaluate the influence of social ties on self-reported prevalence of multimorbidity (selected chronic non-communicable diseases) among the selected states of elderly population in India. The data is accessed from Building Knowledge Base on Population Ageing in India (BKPAI), collected in 2011 covering the self-reported chronic non-communicable diseases like arthritis, heart disease, diabetes, lung disease with asthma, hypertension, cataract, depression, dementia, Alzheimer’s disease, and cancer. The data of the above diseases were taken together and categorized as: ‘no disease’, ‘one disease’ and ‘multimorbidity’. The predicted variables were demographic, socio-economic, residential types, and the variable of social ties includes social support, social engagement, perceived support, connectedness, and importance of the elderly. Predicted probability for multiple logistic regression was used to determine the background characteristics of the old in association with chronic morbidities showing multimorbidity. The finding suggests that 24.35% of the elderly are suffering from multimorbidity. Research shows that with reference to ‘no disease’, according to the socio-economic characteristics of the old, the female oldest old (80+) from others in caste and religion, widowed, never had any formal education, ever worked in their life, coming from the second wealth quintile standard, from rural Maharashtra are more prone with ‘one disease’. From the social ties background, the elderly who perceives they are important to the family, after getting older their decision-making status has been changed, prefer to stay with son and spouse only, satisfied with the communication from their children are more likely to have less single morbidity and the results are significant. Again, with respect to ‘no disease’, the female oldest old (80+), who are others in caste, Christian in religion, widowed, having less than 5 years of education completed, ever worked, from highest wealth quintile, residing in urban Kerala are more associated with multimorbidity. The elderly population who are more socially connected through family visits, public gatherings, gets support in decision making, who prefers to spend their later years with son and spouse only but stays alone shows lesser prevalence of multimorbidity. In conclusion, received and perceived social integration and support from associated neighborhood in the older days, knowing about their own needs in life facilitates better health and wellbeing of the elderly population in selected states of India.

Keywords: morbidity, multi-morbidity, prevalence, social ties

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Authors: Haikal Achmad Thaha, Pujo Laksono, Dhamma Nibbana Putra

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Customer service is one of the core interest in a service sector of a company, whether as the core business or as service part of the operation. Most of the time, the people and the previous research in service industry is focused on finding the best business model solution for the service sector, usually to decide between total in house customer service, outsourcing, or something in between. Conventionally, to take this decision is some important part of the management job, and this is a process that usually takes some time and staff effort, meanwhile market condition and overall company needs may change and cause loss of income and temporary disturbance in the companies operation . However, in this paper we have offer a new concept model to assist decision making process in service industry. This model will featured information platform as central tool to integrate service industry operation. The result is service information model which would ideally increase response time and effectivity of the decision making. it will also help service industry in switching the service solution system quickly through machine learning when the companies growth and the service solution needed are changing.

Keywords: service industry, customer service, machine learning, decision making, information platform

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Authors: Eun Jeong Yu, Inn Soo Kang, Tae Ki Yoon, Mi Kyoung Koong

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Advanced female age is associated with higher cycle cancelation rates, lower clinical pregnancy rate, increased miscarriage and aneuploidy rates in IVF (In Vitro Fertilization) cycles. This retrospective cohort study was conducted at a Cha Fertility Center, Seoul Station. All fresh non-donor IVF cycles performed in women aged 40 years and above from January 2016 to December 2016 were reviewed. Donor/recipient treatment, PGD/PGS (Preimplantation Genetic Diagnosis/ Preimplantation Genetic Screening) were excluded from analysis. Of the 1,166 cycles from 753 women who completed ovulation induction, 1,047 were appropriate for the evaluation according to inclusion and exclusion criterion. IVF cycles were categorized according to age and grouped into the following 1-year age groups: 40, 41, 42, 43, 44, 45 and > 46. The mean age of patients was 42.4 ± 1.8 years. The median AMH (Anti-Mullerian Hormone) level was 1.2 ± 1.5 ng/mL. The mean number of retrieved oocytes was 4.9 ± 4.3. The clinical pregnancy rate and live birth rate in women > 40 years significantly decreased with each year of advancing age (p < 0.001). The clinical pregnancy rate decreased from 21% at the age of 40 years to 0% at ages above 45 years. Live birth rate decreased from 12.3% to 0%, respectively. There were no clinical pregnancy outcomes among 95 patients aged above 45 years of age. The overall miscarriage rate was 40.7% (range, 36.7%-70%). The transfer of at least one good quality embryo was associated with about 4-9% increased chance of a clinical pregnancy rate. Therefore, IVF in old age women less than 46 had a reasonable chance for successful pregnancy outcomes especially when good quality embryo is transferred.

Keywords: advanced maternal age, in vitro fertilization, pregnancy rate, live birth rate

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Authors: Jeena R. S., Sukesh Kumar A.

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Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.

Keywords: prediction, retinal imaging, risk factors, stroke

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Authors: Mahshid Hatamzad, Geanette Polanco

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Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

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Authors: Dennis Infante

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This paper examined the reflections of teachers on curriculum reforms, the implementation of the K-12 Basic Education Program in the Philippines. The results revealed that problems and concerns raised by teachers could be classified into curriculum materials and design; competence, readiness and motivation of the teachers; the learning environment, and support systems; readiness, competence and motivation of students; and other relevant factors. The best features of the K-12 curriculum reforms included (1) the components, curriculum materials; (2) the design, structure and delivery of the lessons; (3) the framework and theoretical approach; (3) the qualities of the teaching-learning activities; (4) and other relevant features. With the demanding task of implementing the new curriculum, the teachers expressed their needs which included (1) making the curriculum materials available to achieve the goals of the curriculum reforms; (2) enrichment of the learning environments; (3) motivating and encouraging the teachers to embrace change; (4) providing appropriate support systems; (5) re-tooling, and empowering teachers to implement the curriculum reforms; and (6) other relevant factors. The research concluded with a synthesis that provided a paradigm for implementing curriculum reforms which recognizes the needs of the teachers and the features of the new curriculum.

Keywords: curriculum reforms, K-12, teachers' reflections, implementing curriculum change

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Authors: Giuseppe Timperio, Robert De Souza

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The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

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Authors: Bhawat Chiamjinnawat

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The agri-food market transformation has implied market growth for the fruit industry in Thailand. This article focuses on analysis of farmer competence and farm resources which affect market strategies used by fruit farmers in Chanthaburi province of Thailand. The survey data were collected through the use of face-to-face interviews with structured questionnaires. This study identified 14 drivers related to farmer competence and farm resources of which some had significant effect on the decision to use either high-value markets or traditional markets. The results suggest that farmers who used high-value markets were better educated and they had longer experience and larger sized business. Identifying the important factors that match with the market transformation provides policy with opportunities to support the fruit farmers to increase their market power. Policies that promote business expansion of agricultural cooperatives and knowledge sharing among farmers are recommended to reduce limitations due to limited knowledge, low experience, and small business sizes.

Keywords: farmer competence, farm resources, fruit industry, high-value markets, Thailand

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Authors: Leila Asadollahi

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Dry powder inhalers (DPIs) have come a long way since their creation, starting with the Spinhaler Fisons in 1967. For optimal performance, it is important to consider the interplay between formulation, device, and patient. DPIs have shown great potential in treating systemic disorders, as evidenced by their success in clinical practices. Ongoing clinical trials and market availability of DPI products for systemic disease treatment are also examined. Furthermore, the current COVID-19 pandemic has sparked increased interest in dry powder inhalation as a potential avenue for vaccines and antiviral drugs, prompting further exploration of its applications. To achieve optimal treatment outcomes for respiratory diseases, a thorough understanding of the various types of DPIs currently available is crucial. These include single-dose, multiple-unit dose, and multi-dose DPIs. This informative article delves into the administration of drugs via inhalation, examining its diverse routes of administration. Additionally, it illuminates the exciting advancements in inhalation delivery systems and investigates the latest therapeutic approaches for the treatment of respiratory ailments. Additionally, the article discusses the historical development of DPIs and the need for improved designs to enhance efficacy and patient adherence. The potential of DPIs in treating systemic diseases is also examined. Overall, this review provides valuable insights into the advancements, challenges, and future prospects of inhalation drug delivery systems, highlighting the potential they hold for respiratory and systemic disorders. The review aims to provide valuable insights into the advancements, challenges, and future prospects of inhalation drug delivery systems, highlighting the potential they hold for respiratory and systemic disorders.

Keywords: dry powder inhalers (DPIs), respiratory diseases, systemic disorders, pulmonary drug delivery

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Authors: Sheraz Gul

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The requirements for progressing a compound to clinical trials is well established and relies on the results from in-vitro and in-vivo animal tests to indicate that it is likely to be safe and efficacious when testing in humans. The typical data package required will include demonstrating compound safety, toxicity, bioavailability, pharmacodynamics (potential effects of the compound on body systems) and pharmacokinetics (how the compound is potentially absorbed, distributed, metabolised and eliminated after dosing in humans). If the desired criteria are met and the compound meets the clinical Candidate criteria and is deemed worthy of further development, a submission to regulatory bodies such as the US Food & Drug Administration for an exploratory Investigational New Drug Study can be made. The purpose of this study is to collect data to establish that the compound will not expose humans to unreasonable risks when used in limited, early-stage clinical studies in patients or normal volunteer subjects (Phase I). These studies are also designed to determine the metabolism and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on their effectiveness. In order to reach the above goals, we have developed a pre-clinical high throughput Absorption, Distribution, Metabolism and Excretion–Toxicity (ADME–Toxicity) panel of assays to identify compounds that are likely to meet the Lead and Candidate compound acceptance criteria. This panel includes solubility studies in a range of biological fluids, cell viability studies in cancer and primary cell-lines, mitochondrial toxicity, off-target effects (across the kinase, protease, histone deacetylase, phosphodiesterase and GPCR protein families), CYP450 inhibition (5 different CYP450 enzymes), CYP450 induction, cardio-toxicity (hERG) and gene-toxicity. This panel of assays has been applied to multiple compound series developed in a number of projects delivering Lead and clinical Candidates and examples from these will be presented.

Keywords: absorption, distribution, metabolism and excretion–toxicity , drug discovery, food and drug administration , pharmacodynamics

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Authors: Mohit Kumar, Mayur Betharia

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Healthcare domain, with the emergence of Electronic Medical Record (EMR), collects a lot of data which have been attracting Data Mining expert’s interest. In the past, doctors have relied on their intuition while making critical clinical decisions. This paper presents the means to analyze the Medical workflows to get business insights out of huge dumped medical databases. Market Basket Analysis (MBA) which is a special data mining technique, has been widely used in marketing and e-commerce field to discover the association between products bought together by customers. It helps businesses in increasing their sales by analyzing the purchasing behavior of customers and pitching the right customer with the right product. This paper is an attempt to demonstrate Market Basket Analysis applications in healthcare. In particular, it discusses the Market Basket Analysis Algorithm ‘Apriori’ applications within healthcare in major areas such as analyzing the workflow of diagnostic procedures, Up-selling and Cross-selling of Healthcare Systems, designing healthcare systems more user-friendly. In the paper, we have demonstrated the MBA applications using Angiography Systems, but can be extrapolated to other modalities as well.

Keywords: data mining, market basket analysis, healthcare applications, knowledge discovery in healthcare databases, customer relationship management, healthcare systems

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Authors: Cristian Matti, Valerie Fowles, Eva Enyedi, Piotr Pogorzelski

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The system mapping process can be defined as a knowledge service where a team of facilitators, experts and practitioners facilitate a guided conversation, enable the exchange of information and support an iterative curation process. System mapping processes rely on science-based tools to introduce and simplify a variety of components and concepts of socio-technical systems through metaphors while facilitating an interactive dialogue process to enable the design of co-created maps. System maps work then as “artifacts” to provide information and focus the conversation into specific areas around the defined challenge and related decision-making process. Knowledge management facilitates the curation of that data gathered during the system mapping sessions through practices of documentation and subsequent knowledge co-production for which common practices from data science are applied to identify new patterns, hidden insights, recurrent loops and unexpected elements. This study presents empirical evidence on the application of these techniques to explore mechanisms by which visual tools provide guiding principles to portray system components, key variables and types of data through the lens of climate change. In addition, data science facilitates the structuring of elements that allow the analysis of layers of information through affinity and clustering analysis and, therefore, develop simple indicators for supporting the decision-making process. This paper addresses methodological and empirical elements on the horizontal learning process that integrate system mapping through visual tools, interpretation, cognitive transformation and analysis. The process is designed to introduce practitioners to simple iterative and inclusive processes that create actionable knowledge and enable a shared understanding of the system in which they are embedded.

Keywords: indicators, knowledge management, system mapping, visual tools

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Authors: Ciwang Teyra, A. H. Y. Lai

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Introduction: Indigenous LGBTQ individuals face with significant life stress such as racial and gender discrimination and microaggressions, which may lead to negative impacts of their mental health. Although studies relevant to Taiwanese indigenous LGBTQpeople gradually increase, most of them are primarily conceptual or qualitative in nature. This research aims to fulfill the gap by offering empirical quantitative evidence, especially investigating the impact of racial and gender microaggressions on mental health among Taiwanese indigenous LGBTQindividuals with an intersectional perspective, as well as examine whether social support can help them to cope with microaggressions. Methods: Participants were (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Standardised measurements was used, including Racial Microaggression Scale (10 items), Gender Microaggression Scale (9 items), Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender, and perceived economic hardships. Structural equation modelling (SEM) was employed using Mplus 8.0 with the latent variables of depression and anxiety as outcomes. A main effect SEM model was first established (Model1).To test the moderation effects of perceived social support, an interaction effect model (Model 2) was created with interaction terms entered into Model1. Numerical integration was used with maximum likelihood estimation to estimate the interaction model. Results: Model fit statistics of the Model 1:X2(df)=1308.1 (795), p<.05; CFI/TLI=0.92/0.91; RMSEA=0.06; SRMR=0.06. For Model, the AIC and BIC values of Model 2 improved slightly compared to Model 1(AIC =15631 (Model1) vs. 15629 (Model2); BIC=16098 (Model1) vs. 16103 (Model2)). Model 2 was adopted as the final model. In main effect model 1, racialmicroaggressionand perceived social support were associated with depression and anxiety, but not sexual orientation microaggression(Indigenous microaggression: b = 0.27 for depression; b=0.38 for anxiety; Social support: b=-0.37 for depression; b=-0.34 for anxiety). Thus, an interaction term between social support and indigenous microaggression was added in Model 2. In the final Model 2, indigenous microaggression and perceived social support continues to be statistically significant predictors of both depression and anxiety. Social support moderated the effect of indigenous microaggression of depression (b=-0.22), but not anxiety. All covariates were not statistically significant. Implications: Results indicated that racial microaggressions have a significant impact on indigenous LGBTQ people’s mental health. Social support plays as a crucial role to buffer the negative impact of racial microaggression. To promote indigenous LGBTQ people’s wellbeing, it is important to consider how to support them to develop social support network systems.

Keywords: microaggressions, intersectionality, indigenous population, mental health, social support

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Authors: Ahmed M. El-Araby, Ibrahim Sabry, Ahmed El-Assal

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The relationships between the industrial facilities, the capacity available for these facilities, and the costs involved are the main factors in deciding the correct selection of a facility layout. In general, an issue of facility layout is considered to be an unstructured problem of decision-making. The objective of this work is to provide a survey that describes the techniques by which a facility planning problem can be solved and also the effect of these techniques on the efficiency of the layout. The multi-criteria decision making (MCDM) techniques can be classified according to the previous researches into three categories which are the use of single MCDM, combining two or more MCDM, and the integration of MCDM with another technique such as genetic algorithms (GA). This paper presents a review of different multi-criteria decision making (MCDM) techniques that have been proposed in the literature to pick the most suitable layout design. These methods are particularly suitable to deal with complex situations, including various criteria and conflicting goals which need to be optimized simultaneously.

Keywords: facility layout, MCDM, GA, literature review

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Chitra Rajagopal, Indra Deo Kumar, Ila Chauhan, Ruchi Joshi, Binoy Bhargavan

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Reliability and safety are essential for the success of mission-critical and safety-critical defense systems. Humans are part of the entire life cycle of defense systems development and deployment. The majority of industrial accidents or disasters are attributed to human errors. Therefore, considerations of human performance and human reliability are critical in all complex systems, including defense systems. Defense systems are operating from the ground, naval and aerial platforms in diverse conditions impose unique physical and psychological challenges to the human operators. Some of the safety and mission-critical defense systems with human-machine interactions are fighter planes, submarines, warships, combat vehicles, aerial and naval platforms based missiles, etc. Human roles and responsibilities are also going through a transition due to the infusion of artificial intelligence and cyber technologies. Human operators, not accustomed to such challenges, are more likely to commit errors, which may lead to accidents or loss events. In such a scenario, it is imperative to understand the human factors in defense systems for better systems performance, safety, and cost-effectiveness. A case study using Task Analysis (TA) based methodology for assessment and reduction of human errors in the Air and Missile Defense System in the context of emerging technologies were presented. Action-oriented task analysis techniques such as Hierarchical Task Analysis (HTA) and Operator Action Event Tree (OAET) along with Critical Action and Decision Event Tree (CADET) for cognitive task analysis was used. Human factors assessment based on the task analysis helps in realizing safe and reliable defense systems. These techniques helped in the identification of human errors during different phases of Air and Missile Defence operations, leading to meet the requirement of a safe, reliable and cost-effective mission.

Keywords: defence systems, reliability, risk, safety

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Authors: Emmanuel Okechukwu Nwafor, Folake Olubunmi Akintayo, Denis Alcides Rezende

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Decision tree models are versatile and interpretable machine learning algorithms widely used for both classification and regression tasks, which can be related to cities, whether physical or digital. The aim of this research is to assess how well decision tree algorithms can predict trip purposes in Makurdi, Nigeria, while also exploring their connection to the strategic digital city initiative. The research methodology involves formalizing household demographic and trips information datasets obtained from extensive survey process. Modelling and Prediction were achieved using Python Programming Language and the evaluation metrics like R-squared and mean absolute error were used to assess the decision tree algorithm's performance. The results indicate that the model performed well, with accuracies of 84% and 68%, and low MAE values of 0.188 and 0.314, on training and validation data, respectively. This suggests the model can be relied upon for future prediction. The conclusion reiterates that This model will assist decision-makers, including urban planners, transportation engineers, government officials, and commuters, in making informed decisions on transportation planning and management within the framework of a strategic digital city. Its application will enhance the efficiency, sustainability, and overall quality of transportation services in Makurdi, Nigeria.

Keywords: decision tree algorithm, trip purpose, intelligent transport, strategic digital city, travel pattern, sustainable transport

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Authors: Laura Saraf, Katarina Alagić, Karmen Znaor

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Background: One of the most important public health problems affecting the health of the mother and child is postpartum depression. This study aimed to determine the frequency and risk factors that contribute to postpartum depression (PPD). Methods: The research was conducted from November 2022 to April 2023 on a convenient sample of mothers (N=195) who have children up to 6 months of age during home visits by visiting nurses in the Zagreb area or during the breastfeeding support group ‘Vita’. The Edinburgh Postpartum Depression Questionnaire and the Multidimensional Scale of Perceived Social Support were used. Results: Symptoms of PPD of varying intensity were present in 43 (22.05%) participants. It was found that mothers with previous mental disorders and those who are less satisfied with their husband's support have more depressive symptoms than mothers who do not have previous mental disorders and are satisfied with their husband's support. Also, it was found that mothers with depressive symptoms had a lower level of support from significant others, family and friends than mothers without depressive symptoms. Conclusion: The prevalence of postpartum depression (PPD) in the sample was high, and it was shown that the following risk factors influence its occurrence: previous mental disorders, dissatisfaction with emotional support from the husband, and a lower level of social support from significant others, family and friends. It is important to raise awareness of the problem and recognize the symptoms in time to provide adequate psychosocial support to women in labor.

Keywords: postpartum depression (PPD), prevalence, emotional support, social support

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Authors: Teimuraz Manjapharashvili, Ketevani Manjaparashvili

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Fuzzy logic is a modeling method for complex or ill-defined systems and is a relatively new mathematical approach. Its basis is to consider overlapping cases of parameter values and define operations to manipulate these cases. Fuzzy logic can successfully create operative automatic management or appropriate advisory systems. Fuzzy logic techniques in various operational control technologies have grown rapidly in the last few years. Fuzzy logic is used in many areas of human technological activity. In recent years, Fuzzy logic has proven its great potential, especially in the automation of industrial process control, where it allows the form of a control design based on the experience of experts and the results of experiments. The engineering of chemical technological processes uses fuzzy logic in optimal management, and it is also used in process control, including the operational control of continuous cycle chemical industrial, technological processes, where special features appear due to the continuous cycle and correct management acquires special importance. This paper discusses how intelligent systems can be developed, in particular, how Fuzzy logic can be used to build knowledge-based expert systems in chemical process engineering. The implemented projects reveal that the use of Fuzzy logic in technological process control has already given us better solutions than standard control techniques. Fuzzy logic makes it possible to develop an advisory system for decision-making based on the historical experience of the managing operator and experienced experts. The present paper deals with operational control and management systems of continuous cycle chemical technological processes, including advisory systems. Because of the continuous cycle, many features are introduced in them compared to the operational control of other chemical technological processes. Among them, there is a greater risk of transitioning to emergency mode; the return from emergency mode to normal mode must be done very quickly due to the impossibility of stopping the technological process due to the release of defective products during this period (i.e., receiving a loss), accordingly, due to the need for high qualification of the operator managing the process, etc. For these reasons, operational control systems of continuous cycle chemical technological processes have been specifically discussed, as they are different systems. Special features of such systems in control and management were brought out, which determine the characteristics of the construction of control and management systems. To verify the findings, the development of an advisory decision-making information system for operational control of a lime kiln using Fuzzy logic, based on the creation of a relevant expert-targeted knowledge base, was discussed. The control system has been implemented in a real lime production plant with a lime burn kiln, which has shown that suitable and intelligent automation improves operational management, reduces the risks of releasing defective products, and, therefore, reduces costs. The special advisory system was successfully used in the said plant both for the improvement of operational management and, if necessary, for the training of new operators due to the lack of an appropriate training institution.

Keywords: chemical process control systems, continuous cycle industrial technological processes, fuzzy logic, lime kiln

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Authors: Joseph Ignagni, Rebecca Deen

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In this study, the decision making of the Justices of the United States Supreme Court will be considered in terms of constrained maximization and cognitive-cybernetic theory. This paper will integrate research in such fields as law, psychology, political science, economics and decision-making theory. It will be argued that due to its heavy workload, the Supreme Court may be forced to make decisions in a boundedly rational manner. The ideas and theory put forward here will be considered in the area of the Court’s decisions involving religion. Therefore, the cases involving the U.S. Constitution’s Free Exercise Clause and Establishment Clause will be analyzed.

Keywords: bounded rationality, cognitive-cybernetic, US supreme court, religion

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Authors: Fatemeh Nikpay, Rodina Binti Ahmad, Babak Darvish Rouhani

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Enterprise Architecture (EA) is employed by enterprises for providing integrated Information Systems (ISs) in order to support alignment of their business and Information Technology (IT). Evaluation of EA implementation can support enterprise to reach intended goals. There are some problems in current evaluation methods of EA implementation that lead to ineffectiveness implementation of EA. This paper represents current issues on evaluation of EA implementation. In this regard, we set the framework in order to represent evaluation’s issues based on their functionality and structure. The results of this research not only increase the knowledge of evaluation, but also could be useful for both academics and practitioners in order to realize the current situation of evaluations.

Keywords: current issues on EA implementation evaluation, evaluation, enterprise architecture, evaluation of enterprise architecture implementation

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Authors: Nikolay P. Brayanov, Anna V. Stoynova

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Model-based development approach is gaining more support and acceptance. Its higher abstraction level brings simplification of systems’ description that allows domain experts to do their best without particular knowledge in programming. The different levels of simulation support the rapid prototyping, verifying and validating the product even before it exists physically. Nowadays model-based approach is beneficial for modelling of complex embedded systems as well as a generation of code for many different hardware platforms. Moreover, it is possible to be applied in safety-relevant industries like automotive, which brings extra automation of the expensive device certification process and especially in the software qualification. Using it, some companies report about cost savings and quality improvements, but there are others claiming no major changes or even about cost increases. This publication demonstrates the level of maturity and autonomy of model-based approach for code generation. It is based on a real live automotive seat heater (ASH) module, developed using The Mathworks, Inc. tools. The model, created with Simulink, Stateflow and Matlab is used for automatic generation of C code with Embedded Coder. To prove the maturity of the process, Code generation advisor is used for automatic configuration. All additional configuration parameters are set to auto, when applicable, leaving the generation process to function autonomously. As a result of the investigation, the publication compares the quality of generated embedded code and a manually developed one. The measurements show that generally, the code generated by automatic approach is not worse than the manual one. A deeper analysis of the technical parameters enumerates the disadvantages, part of them identified as topics for our future work.

Keywords: embedded code generation, embedded C code quality, embedded systems, model-based development

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