Search results for: multi variable decision making

Authors: S. Haider, B. Bhushan

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Eye Gaze behaviour of individuals with and without intellectual disability are investigated in an eye tracking study in terms of sensitivity to Nonaccidental (NAPs) and Metric (MPs) shape properties. Total fixation time is used as an indirect measure of attention allocation. Studies have found Mean reaction times for non accidental properties (NAPs) to be shorter than for metric (MPs) when the MP and NAP differences were equalized. METHODS: Twenty-five individuals with intellectual disability (mild and moderate level of Mental Retardation) and twenty-seven normal individuals were compared on mean total fixation duration, accuracy level and mean reaction time for mild NAPs, extreme NAPs and metric properties of images. 2D images of cylinders were adapted and made into forced choice match-to-sample tasks. Tobii TX300 Eye Tracker was used to record total fixation duration and data obtained from the Areas of Interest (AOI). Variable trial duration (total reaction time of each participant) and fixed trail duration (data taken at each second from one to fifteen seconds) data were used for analyses. Both groups did not differ in terms of fixation times (fixed as well as variable) across any of the three image manipulations but differed in terms of reaction time and accuracy. Normal individuals had longer reaction time compared to individuals with intellectual disability across all types of images. Both the groups differed significantly on accuracy measure across all image types. Normal individuals performed better across all three types of images. Mild NAPs vs. Metric differences: There was significant difference between mild NAPs and metric properties of images in terms of reaction times. Mild NAPs images had significantly longer reaction time compared to metric for normal individuals but this difference was not found for individuals with intellectual disability. Mild NAPs images had significantly better accuracy level compared to metric for both the groups. In conclusion, type of image manipulations did not result in differences in attention allocation for individuals with and without intellectual disability. Mild Nonaccidental properties facilitate better accuracy level compared to metric in both the groups but this advantage is seen only for normal group in terms of mean reaction time.

Keywords: eye gaze fixations, eye movements, intellectual disability, stimulus properties

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Authors: Rosaline Govender, Shubnam Rambharos

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Universities are, to a certain extent, the source of under-preparedness ideologically, structurally, and pedagogically, particularly since organizational cultures often alienate students by failing to enable epistemological access. This is evident in the unsustainably low graduation rates that characterize South African higher education, which indicate that under 30% graduate in minimum time, under two-thirds graduate within 6 years, and one-third have not graduated after 10 years. Although the statistics for the Faculty of Accounting and Informatics at the Durban University of Technology (DUT) in South Africa have improved significantly from 2019 to 2021, the graduation (32%), throughput (50%), and dropout rates (16%) are still a matter for concern as the graduation rates, in particular, are quite similar to the national statistics. For our students to succeed, higher education should take a multi-pronged approach to ensure student success, and student engagement is one of the ways to support our students. Student engagement depends not only on students’ teaching and learning experiences but, more importantly, on their social and academic integration, their sense of belonging, and their emotional connections in the institution. Such experiences need to challenge students academically and engage their intellect, grow their communication skills, build self-discipline, and promote confidence. The aim of this mixed methods study is to explore the multi-pronged nature of student success within the Faculty of Accounting and Informatics at DUT and focuses on the enabling and constraining factors of student success. The sources of data were the Mid-year student experience survey (N=60), the Hambisa Student Survey (N=85), and semi structured focus group interviews with first, second, and third year students of the Faculty of Accounting and Informatics Hambisa program. The Hambisa (“Moving forward”) focus area is part of the Siyaphumelela 2.0 project at DUT and seeks to understand the multiple challenges that are impacting student success which create a large “middle” cohort of students that are stuck in transition within academic programs. Using the lens of the sociocultural influences on student engagement framework, we conducted a thematic analysis of the two surveys and focus group interviews. Preliminary findings indicate that living conditions, choice of program, access to resources, motivation, institutional support, infrastructure, and pedagogical practices impact student engagement and, thus, student success. It is envisaged that the findings from this project will assist the university in being better prepared to enable student success.

Keywords: social and academic integration, socio-cultural influences, student engagement, student success

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

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Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: forest, GIS, remote sensing, Goaso

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Authors: Nihal Kartaltepe Behram, Göksel Ataman, Dila Okçu

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With the development of foreign direct investments, the social, cultural, political and economic interactions between countries and institutions have become visible and they have become determining factors for the strategic structuring and market goals. In this context the purpose of this study is to investigate the effects of cultural distance and institutions on foreign direct investment choices in terms of location and investment model. For international establishments, the concept of culture, as well as the concept of cultural distance, is taken specifically into consideration, especially in the selection of methods for entering the market. In the researches and empirical studies conducted, a direct relationship between cultural distance and foreign direct investments is set and institutions and effective variable factors are examined at the level of defining the investment types. When the detailed calculation strategies and empirical researches and studies are taken into consideration, the most common methods for determining the direct investment model, considering the cultural distances, are full-ownership enterprises and joint ventures. Also, when all of the factors affecting the investments are taken into consideration, it was seen that the effect of institutions such as Government Intervention, Intellectual Property Rights, Corruption and Contract Enforcements is very important. Furthermore agglomeration is more intense and effective on the investment, compared to other factors. China has been selected as the target country, due to its effectiveness in world economy and its contributions to developing countries, which has commercial relationships with. Qualitative research methods are used for this study conducted, to measure the effects of determinative variable factors in the hypotheses of study, on the direct foreign investors and to evaluate the findings. In this study in-depth interview is used as a data collection method and the data analysis is made through descriptive analysis. Foreign Direct Investments are so reactive to institutions and cultural distance is identified by all interviews and analysis. On the other hand, agglomeration is the most strong determiner factor on foreign direct investors in Chinese Market. The reason of this factors, which comprise the sectorial aggregate, are not the strongest factors as agglomeration that the most important finding. We expect that this study became a beneficial guideline for developed and developing countries and local and national institutions’ strategic plans.

Keywords: China, cultural distance, Foreign Direct Investments, institutions

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Authors: Magdy Al Shourbagi

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Diabetes mellitus is the commonest cause of neuropathy. The common pattern is a distal symmetrical sensory polyneuropathy, associated with autonomic disturbances. Less often, Diabetes mellitus is responsible for a focal or multifocal neuropathy. Common causes for non-healing of diabetic foot are the infection and ischemia. Diabetes mellitus is associated with a defective cellular and humoral immunity. Particularly, decreased phagocytosis, decreased chemotaxis, impaired bacterial killing and abnormal lymphocytic function resulting in a reduced inflammatory reaction and defective wound healing. Hyperbaric oxygen therapy is defined by the Undersea and Hyperbaric Medical Society as a treatment in which a patient intermittently breathes 100% oxygen and the treatment chamber is pressurized to a pressure greater than sea level (1 atmosphere absolute). The pressure increase may be applied in mono-place (single person) or multi-place chambers. Multi-place chambers are pressurized with air, with oxygen given via face mask or endotracheal tube; while mono-place chambers are pressurized with oxygen. Oxygen gas plays an important role in the physiology of wound healing. Hyperbaric oxygen therapy can raise tissue oxygen tensions to levels where wound healing can be expected. HBOT increases the killing ability of leucocytes also it is lethal for certain anaerobic bacteria and inhibits toxin formation in many other anaerobes. Multiple anecdotal reports and studies in HBO therapy in diabetic patients report that HBO can be an effective adjunct therapy in the management of diabetic foot wounds and is associated with better functional outcomes.

Keywords: hyperbari oxygen therapy, diabetic foot, neuropathy, multiplace chambers

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Authors: Seyed Mohammad Hashemi, Shahrokh Barati

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The problem of fault-tolerant control (FTC) by accommodation method has been studied in this paper. The fault occurs in any system components such as actuators, sensors or internal structure of the system and leads to loss of performance and instability of the system. When a fault occurs, the purpose of the fault-tolerant control is designate strategy that can keep the control loop stable and system performance as much as possible perform it without shutting down the system. Here, the section of fault detection and isolation (FDI) system has been evaluated with regard to actuator's fault. Designing a fault detection and isolation system for a multi input-multi output (MIMO) is done by an unknown input observer, so the system is divided to several subsystems as the effect of other inputs such as disturbing given system state equations. In this observer design method, the effect of these disturbances will weaken and the only fault is detected on specific input. The results of this approach simulation can confirm the ability of the fault detection and isolation system design. After fault detection and isolation, it is necessary to redesign controller based on a suitable modification. In this regard after the use of unknown input observer theory and obtain residual signal and evaluate it, PID controller parameters redesigned for iterative. Stability of the closed loop system has proved in the presence of this method. Also, In order to soften the volatility caused by Annie variations of the PID controller parameters, modifying Sigma as a way acceptable solution used. Finally, the simulation results of three tank popular example confirm the accuracy of performance.

Keywords: fault tolerant control, fault detection and isolation, actuator fault, unknown input observer

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Authors: Teodorica G. Ani

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Economic activity requires an encouraging regulatory environment and effective rules that are transparent and accessible to all. The World Bank has been publishing the annual Doing Business reports since 2004 to investigate the scope and manner of regulations that enhance business activity and those that constrain it. A streamlined business environment supporting the development of competitive small and medium enterprises (SMEs) may expand employment opportunities and improve the living conditions of low income households. Asia has emerged as one of the most attractive markets in the world. Economies in East Asia and the Pacific were among the most active in making it easier for local firms to do business. The study aimed to describe the ease of doing business and its effect to economic growth among selected economies in Asia for the year 2014. The study covered 29 economies in East Asia, Southeast Asia, South Asia and Middle Asia. Ease of doing business is measured by the Doing Business indicators (DBI) of the World Bank. The indicators cover ten aspects of the ease of doing business such as starting a business, dealing with construction permits, getting electricity, registering property, getting credit, protecting investors, paying taxes, trading across borders, enforcing contracts and resolving insolvency. In the study, Gross Domestic Product (GDP) was used as the proxy variable for economic growth. Descriptive research was the research design used. Graphical analysis was used to describe the income and doing business among selected economies. In addition, multiple regression was used to determine the effect of doing business to economic growth. The study presented the income among selected economies. The graph showed China has the highest income while Maldives produces the lowest and that observation were supported by gathered literatures. The study also presented the status of the ten indicators of doing business among selected economies. The graphs showed varying trends on how easy to start a business, deal with construction permits and to register property. Starting a business is easiest in Singapore followed by Hong Kong. The study found out that the variations in ease of doing business is explained by starting a business, dealing with construction permits and registering property. Moreover, an explanation of the regression result implies that a day increase in the average number of days it takes to complete a procedure will decrease the value of GDP in general. The research proposed inputs to policy which may increase the awareness of local government units of different economies on the simplification of the policies of the different components used in measuring doing business.

Keywords: doing business, economic growth, gross domestic product, Asia

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Charles Koduru, Parth Patel, M. Hassan Tanveer

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In this paper, the communication between a team of robots is used to sanitize an environment with germs is proposed. We introduce capabilities from a team of robots (most likely heterogeneous), a wheeled robot named ROSbot 2.0 that consists of a mounted LiDAR and Kinect sensor, and a modified prototype design of a unicycle-drive Roomba robot called the UV robot. The UV robot consists of ultrasonic sensors to avoid obstacles and is equipped with an ultraviolet light system to disinfect and kill germs, such as bacteria and viruses. In addition, the UV robot is equipped with disinfectant spray to target hidden objects that ultraviolet light is unable to reach. Using the sensors from the ROSbot 2.0, the robot will create a 3-D model of the environment which will be used to factor how the ultraviolet robot will disinfect the environment. Together this proposed system is known as the RME assistive robot device or RME system, which communicates between a navigation robot and a germ disinfecting robot operated by a user. The RME system includes a human-machine interface that allows the user to control certain features of each robot in the RME assistive robot device. This method allows the cleaning process to be done at a more rapid and efficient pace as the UV robot disinfects areas just by moving around in the environment while using the ultraviolet light system to kills germs. The RME system can be used in many applications including, public offices, stores, airports, hospitals, and schools. The RME system will be beneficial even after the COVID-19 pandemic. The Kennesaw State University will continue the research in the field of robotics, engineering, and technology and play its role to serve humanity.

Keywords: multi robot system, assistive robots, COVID-19 pandemic, ultraviolent technology

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Authors: Andreas Lind, Aitor Iriondo Pascual, Dan Hogberg, Lars Hanson

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Factory setup lifecycles are most often described and prepared in CAD environments; the preparation is based on experience and inputs from several cross-disciplinary processes. Early in the factory setup preparation, a so-called block layout is created. The intention is to describe a high-level view of the intended factory setup and to claim area reservations and allocations. Factory areas are then blocked, i.e., targeted to be used for specific intended resources and processes, later redefined with detailed factory setup layouts. Each detailed layout is based on the block layout and inputs from cross-disciplinary preparation processes, such as manufacturing sequence, productivity, workers’ workplace requirements, and resource setup preparation. However, this activity is often not carried out with all variables considered simultaneously, which might entail a risk of sub-optimizing the detailed layout based on manual decisions. Therefore, this work aims to realize a digital method for assembly manufacturing layout planning where productivity, area utilization, and ergonomics can be considered simultaneously in a cross-disciplinary manner. The purpose of the digital method is to support engineers in finding optimized designs of detailed layouts for assembly manufacturing factories, thereby facilitating better decisions regarding setups of future factories. Input datasets are company-specific descriptions of required dimensions for specific area reservations, such as defined dimensions of a worker’s workplace, material façades, aisles, and the sequence to realize the product assembly manufacturing process. To test and iteratively develop the digital method, a demonstrator has been developed with an adaptation of existing software that simulates and proposes optimized designs of detailed layouts. Since the method is to consider productivity, ergonomics, area utilization, and constraints from the automatically generated block layout, a multi-objective optimization approach is utilized. In the demonstrator, the input data are sent to the simulation software industrial path solutions (IPS). Based on the input and Lua scripts, the IPS software generates a block layout in compliance with the company’s defined dimensions of area reservations. Communication is then established between the IPS and the software EPP (Ergonomics in Productivity Platform), including intended resource descriptions, assembly manufacturing process, and manikin (digital human) resources. Using multi-objective optimization approaches, the EPP software then calculates layout proposals that are sent iteratively and simulated and rendered in IPS, following the rules and regulations defined in the block layout as well as productivity and ergonomics constraints and objectives. The software demonstrator is promising. The software can handle several parameters to optimize the detailed layout simultaneously and can put forward several proposals. It can optimize multiple parameters or weight the parameters to fine-tune the optimal result of the detailed layout. The intention of the demonstrator is to make the preparation between cross-disciplinary silos transparent and achieve a common preparation of the assembly manufacturing factory setup, thereby facilitating better decisions.

Keywords: factory setup, multi-objective, optimization, simulation

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Santosh Kumar Ketham

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Climate change creating most dramatic and destructive consequences, the result is global warming and sea-level rise, flooding coastal cities around the world forming vulnerable situations affecting in multiple ways: environment, economy, social and political. The aim and goal of the research is to develop cities on water. Taking the problem as an opportunity to bring science, engineering, policies and design together to make a resilient and sustainable floating community on water considering existing/new technologies of floating. The quest is to make sustainable habitat on water to live, work, learn and play.  To make sustainable energy generation and storage alongside maintaining balance of land and marine to conserve Ecosystem. The research would serve as a model for sustainable neighbourhoods designed in a modular way and thus can easily extend or re-arranged, to adapt for future socioeconomic realities.  This research paper studies primarily on climate change problems, effects, risks and opportunities. It does so, through analysing existing case studies, books and writings published on coastal cities and understanding its various aspects for making sustainable habitat.

Keywords: floating cities, flexible modular typologies, rising sea levels, sustainable architecture and urbanism

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Authors: Taiwo Frances Gbadegesin

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Children’s capacity to contribute to social and economic status of a nation has been given more recognition than ever. Global policy priority aimed at ensuring sustainable development has been extended to the developing nations of the world. However, many developing countries have continued to puzzle out the extent and possibilities of exploring sustainability within their socio-economic environment. This paper considers ways in which the theoretical framework of Dahlberg, Moss and Pence (1999; 2007) and Moss (2007; 2012) that embraces meaning-making, social construction of childhood experiences and democratic perspectives can be used to understand children’s capacity for building a sustainable future. This paper presents data collected through interviews and observations from ECCE teachers and children in Lagos, Nigeria. A distinct finding is that children’s participation in building sustainable future is a consequence of the knowledge of the workings of their social, economic and cultural nuances and not a matter of economic wealth per se. It further argues that sustainability is situated within a complex network of local and global contexts. It thus challenges the present neo-liberal approach and advocates a democratic approach to preparing children for a sustainable society. It concludes that sustainability cannot be built on what may be seen as decontextualized responses by relevant stakeholders to the needs and experiences of the “whole child”.

Keywords: children, ECCE, sustainable development, Nigeria

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Authors: P. Vindin, R. Cordier, N. J. Wilson, H. Lee

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Engagement in community-based activities such as education, employment, and social relationships can improve the quality of life for individuals with Autism Spectrum Disorder (ASD). Community mobility is vital to attaining independence for individuals with ASD. Learning to drive and gaining a driver’s license is a critical link to community mobility; however, for individuals with ASD acquiring safe driving skills can be a challenging process. Issues related to anxiety, executive function, and social communication may affect driving behaviours. Driving training and education aimed at addressing barriers faced by learner drivers with ASD can help them improve their driving performance. A multi-site randomized controlled trial (RCT) was conducted to evaluate the effectiveness of an autism-specific driving training intervention for improving the on-road driving performance of learner drivers with ASD. The intervention was delivered via a training manual and interactive website consisting of five modules covering varying driving environments starting with a focus on off-road preparations and progressing through basic to complex driving skill mastery. Seventy-two learner drivers with ASD aged 16 to 35 were randomized using a blinded group allocation procedure into either the intervention or control group. The intervention group received 10 driving lessons with the instructors trained in the use of an autism-specific driving training protocol, whereas the control group received 10 driving lessons as usual. Learner drivers completed a pre- and post-observation drive using a standardized driving route to measure driving performance using the Driving Performance Checklist (DPC). They also completed anxiety, executive function, and social responsiveness measures. The findings showed that there were significant improvements in driving performance for both the intervention (d = 1.02) and the control group (d = 1.15). However, the differences were not significant between groups (p = 0.614) or study sites (p = 0.842). None of the potential moderator variables (anxiety, cognition, social responsiveness, and driving instructor experience) influenced driving performance. This study is an important step toward improving community mobility for individuals with ASD showing that an autism-specific driving training intervention can improve the driving performance of leaner drivers with ASD. It also highlighted the complexity of conducting a multi-site design even when sites were matched according to geography and traffic conditions. Driving instructors also need more and clearer information on how to communicate with learner drivers with restricted verbal expression.

Keywords: autism spectrum disorder, community mobility, driving training, transportation

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Authors: Nirit Raichel, Dorit Alt

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Although university teaching is claimed to have a special task to support students in adopting ways of thinking and producing new knowledge anchored in scientific inquiry practices, it is argued that students' habits of learning are still overwhelmingly skewed toward passive acquisition of knowledge from authority sources rather than from collaborative inquiry activities. In order to overcome this critical inadequacy between current educational goals and instructional methods, the LLAF consortium is aimed at developing updated instructional practices that put a premium on adaptability to the emerging requirements of present society. LLAF has created a practical guide for teachers containing updated pedagogical strategies based on the constructivist approach for learning, arranged along Delors’ four theoretical ‘pillars’ of education: Learning to know, learning to do, learning to live together, and learning to be. This presentation will be limited to problem-based learning (PBL), as a strategy introduced in the second pillar. PBL leads not only to the acquisition of technical skills, but also allows the development of skills like problem analysis and solving, critical thinking, cooperation and teamwork, decision- making and self-regulation that can be transferred to other contexts. This educational strategy will be exemplified by a case study conducted in the pre-piloting stage of the project. The case describes a three-fold process implemented in a postgraduate course for in-service teachers, including: (1) learning about PBL (2) implementing PBL in the participants' classes, and (3) qualitatively assessing the contributions of PBL to students' outcomes. An example will be given regarding the ways by which PBL was applied and assessed in civic education for high-school students. Two 9th-grade classes have participated the study; both included several students with learning disability. PBL was applied only in one class whereas traditional instruction was used in the other. Results showed a robust contribution of PBL to students' affective and cognitive outcomes as reflected in their motivation to engage in learning activities, and to further explore the subject. However, students with learning disability were less favorable with this "active" and "annoying" environment. Implications of these findings for the LLAF project will be discussed.

Keywords: problem-based learning, higher education, pedagogical strategies

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Authors: Christopher Meyer, Laima Gerlitz

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European ports are facing high political pressure through the implementation of initiatives such as the European Green Deal or IMO's 2030 targets (Fit for 55). However, small and medium-sized ports face even higher challenges compared to bigger ones due to lower capacities in various fields such as investments, infra-structure, Human Resources, and funding opportunities. Small and Medium-Sized Ports (SMPs) roles in economic systems are various depending on their specific functionality in maritime ecosystems. Depending on their different situations, being an actor in multiport gateways, aligned to core ports, regional nodes in peripheries for the hinterland, specialized cluster members, or logistical nodes, different strategic business models may be applied to increase SMPs' competitiveness among other bigger ports. Additionally, SMPs are facing more challenges for future development in terms of digital and green transition of their operations. Thus, it is necessary to evaluate the own strategical position and apply management strategies alongside the regional growth and innovation strategies for diversification or specialisation of own port businesses. The research uses inductive perspectives to set up a transferable framework based on case studies to be analysed. In line with particular research and document analysis, qualitative approaches were considered. The research is based on a deep literature review on SMPs as well as theories on diversification and specialisation. Existing theories from different fields are evaluated on their application for the port sector and these specific maritime actors, paying respect to enabling innovation incorporation to enhance digital and environmental transition with fu-ture perspectives for SMPs. The paper aims to provide a decision-making matrix for the strategic positioning of SMPs in Europe, including opportunities to get access to particular EU funds for future development alongside the Regional In-novation Strategies on Smart Specialisation.

Keywords: strategic planning, sustainability transition, competitiveness portfolio, EU green deal

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Authors: Hendri Purwadi, Christine McCloud

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Triage is a complex decision-making process that aims to categorize a victim’s level of acuity and the need for medical assistance. Two common triage systems have been widely used in Mass Casualty Incidents (MCIs) and disaster situation are START (Simple triage algorithm and rapid treatment) and SALT (sort, asses, lifesaving, intervention, and treatment/transport). There is currently controversy regarding the effectiveness of SALT over START triage system. This systematic review aims to investigate and compare the effectiveness between SALT and START triage system in disaster and MCIs setting. Literatures were searched via systematic search strategy from 2009 until 2019 in PubMed, Cochrane Library, CINAHL, Scopus, Science direct, Medlib, ProQuest. This review included simulated-based and medical record -based studies investigating the accuracy and applicability of SALT and START triage systems of adult and children population during MCIs and disaster. All type of studies were included. Joana Briggs institute critical appraisal tools were used to assess the quality of reviewed studies. As a result, 1450 articles identified in the search, 10 articles were included. Four themes were identified by review, they were accuracy, under-triage, over-triage and time to triage per individual victim. The START triage system has a wide range and inconsistent level of accuracy compared to SALT triage system (44% to 94. 2% of START compared to 70% to 83% of SALT). The under-triage error of START triage system ranged from 2.73% to 20%, slightly lower than SALT triage system (7.6 to 23.3%). The over-triage error of START triage system was slightly greater than SALT triage system (START ranged from 2% to 53% compared to 2% to 22% of SALT). The time for applying START triage system was faster than SALT triage system (START was 70-72.18 seconds compared to 78 second of SALT). Consequently; The START triage system has lower level of under-triage error and faster than SALT triage system in classifying victims of MCIs and disaster whereas SALT triage system is known slightly more accurate and lower level of over-triage. However, the magnitude of these differences is relatively small, and therefore the effect on the patient outcomes is not significance. Hence, regardless of the triage error, either START or SALT triage system is equally effective to triage victims of disaster and MCIs.

Keywords: disaster, effectiveness, mass casualty incidents, START triage system, SALT triage system

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Authors: R. Ueda

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Today global society is seeking resilient partnership in local organizations and individuals, which realizes multi-stakeholders relationship. Although it is proposed by modern global framework of sustainable development, it is conceivable that such affiliation can be found out in the traditional local community in Japan, and that traditional spirit is tacitly sustaining in modern context of disaster mitigation in society and economy. Then this research is aiming to clarify and analyze implication for the global world by actual case studies. Regional and urban resilience is the ability of multi-stakeholders to cooperate flexibly and to adapt in response to changes in the circumstances caused by disasters, but there are various conflicts affecting coordination of disaster relief measures. These conflicts arise not only from a lack of communication and an insufficient network, but also from the difficulty to jointly draw common context from fragmented information. This is because of the weakness of our modern engineering which focuses on maintenance and restoration of individual systems. Here local ‘circles’ holistically includes local community and interacts periodically. Focusing on examples of resilient organizations and wisdom created in communities, what can be seen throughout history is a virtuous cycle where the information and the knowledge are structured, the context to be adapted becomes clear, and an adaptation at a higher level is made possible, by which the collaboration between organizations is deepened and expanded. And the wisdom of a solid and autonomous disaster prevention formed by the historical community called’ Waju’ – an area surrounded by circle embankment to protect the settlement from flood – lives on in government efforts of the coastal industrial island of today. Industrial company there collaborates to create a circle including common evacuation space, road access improvement and infrastructure recovery. These days, people here adopts new interface technology. Large-scale AR- Augmented Reality for more than hundred people is expressing detailed hazard by tsunami and liquefaction. Common experiences of the major disaster space and circle of mutual discussion are enforcing resilience. Collaboration spirit lies in the center of circle. A consistent key point is a virtuous cycle where the information and the knowledge are structured, the context to be adapted becomes clear, and an adaptation at a higher level is made possible, by which the collaboration between organizations is deepened and expanded. This writer believes that both self-governing human organizations and the societal implementation of technical systems are necessary. Infrastructure should be autonomously instituted by associations of companies and other entities in industrial areas for working closely with local governments. To develop advanced disaster prevention and multi-stakeholder collaboration, partnerships among industry, government, academia and citizens are important.

Keywords: industrial recovery, multi-sakeholders, traditional culture, user experience, Waju

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Authors: Shrutisingh Tomar, Madhu Sharan

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It has been an undisputed fact that the culture of a nation has always been reflected in its practice, visual content and in forms of its oral traditions. Regional and communal costumes in India since ancient times have worked as a strong repository for its people to comprehend not only the locality but also the community of the wearer. Such a strong visual language apparently was ordained to communicate basic details about the person such as age, marital status, and socio-cultural status. Most of the fragments of this visual vocabulary have been intensively investigated, recorded, diversified and revived, while a limited range of these has died a slow death. Some of the rare existent kinds of such threads have survived as a mainstream article of clothing: simpler, apparent and a product for daily life yet unique in their own kind. The paper intends to consider and elaborate the investigated repository pertinent to the Pacchedi weaving tradition of Gujarat. The research involved field surveys across seven districts of the two states of India namely Gujarat and Rajasthan. Ethnographic interviews, observations, recording of oral histories and archival research was conducted through multi-timed and multi-cited studies between from the year 2012 to 2015. The results include varied forms of Pacchedi based on the sartorial expressions in the male costume. The characteristic features of these textiles were accorded by the sumptuous use of brocaded cross borders and weft heavy ends along with the details on the languishing fabrication procedure.

Keywords: handloom weaving, material culture, sartorial expressions and vernacular textile craft

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Authors: Veronika Lesáková, Silvia Slezáková, František Štěpánek

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Drug dosage forms consisting of multi-unit particle systems (MUPS) for modified drug release provide a promising route for overcoming the limitation of conventional tablets. Despite the conventional use of pellets as units for MUP systems, 3D printed polymers loaded with a drug seem like an interesting candidate due to the control over dosing that 3D printing mechanisms offer. Further, 3D printing offers high flexibility and control over the spatial structuring of a printed object. The final MUPS tablets include PVP and HPC as granulate with other excipients, enabling the compaction process of this mixture with 3D printed inclusions, also termed minitablets. In this study, we have developed the multi-step production process for MUPS tablets, including the 3D printing technology. The MUPS tablets with incorporated 3D printed minitablets are a complex system for drug delivery, providing modified drug release. Such structured tablets promise to reduce drug fluctuations in blood, risk of local toxicity, and increase bioavailability, resulting in an improved therapeutic effect due to the fast transfer into the small intestine, where particles are evenly distributed. Drug loaded 3D printed minitablets were compacted into the excipient mixture, influencing drug release through varying parameters, such as minitablets size, matrix composition, and compaction parameters. Further, the mechanical properties and morphology of the final MUPS tablets were analyzed as many properties, such as plasticity and elasticity, can significantly influence the dissolution profile of the drug.

Keywords: 3D printing, dissolution kinetics, drug delivery, hot-melt extrusion

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Authors: Berker Bayazit, Gulgun Kayakutlu

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The World Energy Outlook shows that energy markets will substantially change within a few forthcoming decades. First, determined action plans according to COP21 and aim of CO₂ emission reduction have already impact on policies of countries. Secondly, swiftly changed technological developments in the field of renewable energy will be influential upon medium and long-term energy generation and consumption behaviors of countries. Furthermore, share of electricity on global energy consumption is to be expected as high as 40 percent in 2040. Electrical vehicles, heat pumps, new electronical devices and digital improvements will be outstanding technologies and innovations will be the testimony of the market modifications. In order to meet highly increasing electricity demand caused by technologies, countries have to make new investments in the field of electricity production, transmission and distribution. Specifically, electricity generation mix becomes vital for both prevention of CO₂ emission and reduction of power prices. Majority of the research and development investments are made in the field of electricity generation. Hence, the prime source diversity and source planning of electricity generation are crucial for improving the wealth of citizen life. Approaches considering the CO₂ emission and total cost of generation, are necessary but not sufficient to evaluate and construct the product mix. On the other hand, employment and positive contribution to macroeconomic values are important factors that have to be taken into consideration. This study aims to constitute new investments in renewable energies (solar, wind, geothermal, biogas and hydropower) between 2018-2023 under 4 different goals. Therefore, a multi-objective programming model is proposed to optimize the goals of minimizing the CO₂ emission, investment amount and electricity sales price while maximizing the total employment and positive contribution to current deficit. In order to avoid the user preference among the goals, Dinkelbach’s algorithm and Guzel’s approach have been combined. The achievements are discussed with comparison to the current policies. Our study shows that new policies like huge capacity allotment might be discussible although obligation for local production is positive. The improvements in grid infrastructure and re-design support for the biogas and geothermal can be recommended.

Keywords: energy generation policies, multi-objective linear programming, portfolio planning, renewable energy

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Authors: Rajendra Kumar Dubey

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Einstein’s field equations with variable cosmological term Λ are considered in the presence of viscous fluid for Bianchi type I space time. Exact solutions of Einstein’s field equations are obtained by assuming cosmological term Λ Proportional to (R is a scale factor and m is constant). We observed that the shear viscosity is found to be responsible for faster removal of initial anisotropy in the universe. The physical significance of the cosmological models has also been discussed.

Keywords: bianchi type, I cosmological model, viscous fluid, cosmological constant Λ

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Authors: Ali Mahmoud, Shadi Najjar, Mounir Mabsout, Kassim Tarhini

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Empirical expressions for estimating the wheel load distribution and live-load bending moment are typically specified in highway bridge codes such as the AASHTO procedures. The purpose of this paper is to analyze the reliability levels that are inherent in reinforced concrete slab bridges that are designed based on the simplified empirical live load equations in the AASHTO LRFD procedures. To achieve this objective, bridges with multi-lanes (three and four lanes) and different spans are modeled using finite-element analysis (FEA) subjected to HS20 truck loading, tandem loading, and standard lane loading per AASHTO LRFD procedures. The FEA results are compared with the AASHTO LRFD moments in order to quantify the biases that might result from the simplifying assumptions adopted in AASHTO. A reliability analysis is conducted to quantify the reliability index for bridges designed using AASHTO procedures. To reach a consistent level of safety for three- and four-lane bridges, following a previous study restricted to one- and two-lane bridges, the live load factor in the design equation proposed by AASHTO LRFD will be assessed and revised if needed by alternating the live load factor for these lanes. The results will provide structural engineers with more consistent provisions to design concrete slab bridges or evaluate the load-carrying capacity of existing bridges.

Keywords: reliability analysis of concrete bridges, finite element modeling, reliability analysis, reinforced concrete bridge design, load carrying capacity

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Authors: Marwa Ahmed Abd El Hamied

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In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Haileyesus Tessema Alemneh, Abiyu Enyew Molla, Oluwole Daniel Makinde

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Introduction: Faba bean is one of the most important grown plants worldwide for humans and animals. Several biotic and abiotic elements have limited the output of faba beans, irrespective of their diverse significance. Many faba bean pathogens have been reported so far, of which the most important yield-limiting disease is chocolate spot disease (Botrytis fabae). The dynamics of disease transmission and decision-making processes for intervention programs for disease control are now better understood through the use of mathematical modeling. Currently, a lot of mathematical modeling researchers are interested in plant disease modeling. Objective: In this paper, a deterministic mathematical model for chocolate spot disease (CSD) on faba bean plant with an optimal control model was developed and analyzed to examine the best strategy for controlling CSD. Methodology: Three control interventions, quarantine (u2), chemical control (u3), and prevention (u1), are employed that would establish the optimal control model. The optimality system, characterization of controls, the adjoint variables, and the Hamiltonian are all generated employing Pontryagin’s maximum principle. A cost-effective approach is chosen from a set of possible integrated strategies using the incremental cost-effectiveness ratio (ICER). The forward-backward sweep iterative approach is used to run numerical simulations. Results: The Hamiltonian, the optimality system, the characterization of the controls, and the adjoint variables were established. The numerical results demonstrate that each integrated strategy can reduce the diseases within the specified period. However, due to limited resources, an integrated strategy of prevention and uprooting was found to be the best cost-effective strategy to combat CSD. Conclusion: Therefore, attention should be given to the integrated cost-effective and environmentally eco-friendly strategy by stakeholders and policymakers to control CSD and disseminate the integrated intervention to the farmers in order to fight the spread of CSD in the Faba bean population and produce the expected yield from the field.

Keywords: CSD, optimal control theory, Pontryagin’s maximum principle, numerical simulation, cost-effectiveness analysis

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Authors: Mandeep Saini

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The rapid advancement of Artificial Intelligence (AI) is transforming various fields, including intellectual property law. This paper explores the emerging role of AI in interpreting patent claims, a critical and highly specialized area within intellectual property rights. Patent claims define the scope of legal protection granted to an invention, and their precise interpretation is crucial in determining the boundaries of the patent holder's rights. Traditionally, this interpretation has relied heavily on the expertise of patent examiners, legal professionals, and judges. However, the increasing complexity of modern inventions, especially in fields like biotechnology, software, and electronics, poses significant challenges to human interpretation. Introducing AI into patent claim interpretation raises several legal and ethical concerns. This paper addresses critical issues such as the reliability of AI-driven interpretations, the potential for algorithmic bias, and the lack of transparency in AI decision-making processes. It considers the legal implications of relying on AI, particularly regarding accountability for errors and the potential challenges to AI interpretations in court. The paper includes a comparative study of AI-driven patent claim interpretations versus human interpretations across different jurisdictions to provide a comprehensive analysis. This comparison highlights the variations in legal standards and practices, offering insights into how AI could impact the harmonization of international patent laws. The paper proposes policy recommendations for the responsible use of AI in patent law. It suggests legal frameworks that ensure AI tools complement, rather than replace, human expertise in patent claim interpretation. These recommendations aim to balance the benefits of AI with the need for maintaining trust, transparency, and fairness in the legal process. By addressing these critical issues, this research contributes to the ongoing discourse on integrating AI into the legal field, specifically within intellectual property rights. It provides a forward-looking perspective on how AI could reshape patent law, offering both opportunities for innovation and challenges that must be carefully managed to protect the integrity of the legal system.

Keywords: artificial intelligence (ai), patent claim interpretation, intellectual property rights, algorithmic bias, natural language processing, patent law harmonization, legal ethics

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Authors: Keshari Shrestha, Philip Vatterott

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Introduction: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare and potentially fatal drug-related syndrome. DRESS classically presents with a diffuse maculopapular rash, fevers, and eosinophilia more than three weeks after drug exposure. DRESS can present with multi-organ involvement, with liver damage being the most common and severe. Pulmonary involvement is a less common manifestation and is associated with poor clinical outcomes. Chest imaging is often nonspecific, and symptoms can range from mild cough to acute respiratory distress syndrome (ARDS) . This is a case of a 49-year-old female with a history of recent clostridium difficile colitis status post treatment with oral vancomycin who presented with rash, acute liver and kidney failure, as well as diffuse nodular alveolar lung opacities concerning for DRESS syndrome with multi-organ involvement. Clinical Course: This patient initially presented to an outside hospital with clostridium difficile colitis, acute liver injury, and acute kidney injury. She developed a desquamating maculopapular rash in the setting of recent oral vancomycin, meloxicam, and furosemide initiation. She was hospitalized on two additional occasions with worsening altered mental status, liver injury, and acute kidney injury and was initiated on intermittent hemodialysis. Notably, she was found to have systemic eosinophilia (4100 cells/microliter) several weeks prior. She was transferred to this institution for further management where she was found to have encephalopathy, jaundice, lower extremity edema, and diffuse bilateral rhonchorous breath sounds on pulmonary examination. The patient was started on methylprednisolone for suspected DRESS syndrome. She underwent an evaluation for alternative causes of her organ failure. Her workup included a negative infectious, autoimmune, metabolic, toxic, and malignant work-up. Abdominal computed tomography (CT) and ultrasound were remarkable for evidence of hepatic steatosis and possible cirrhotic morphology. Additionally, a chest CT demonstrated diffuse and symmetric nodular alveolar lung opacities with peripheral sparing not consistent with acute respiratory distress syndrome or edema. Ultimately, her condition continued to decline, and she required intubation on several occasions. On hospital day 25 she succumbed to distributive shock in the setting of probable sepsis and multi-organ failure. Discussion: DRESS syndrome occurs in 1 in 1,000 to 10,000 patients with a mortality rate of around 10%. Anti-convulsant, anti-bacterial, anti-viral, and sulfonamide drugs are the most common drugs implicated in the development of DRESS syndrome; however, the list of offending agents is extensive . The diagnosis of DRESS syndrome is made after excluding other causes of disease such as infectious and autoimmune etiologies. The RegiSCAR scoring system is used to diagnose DRESS syndrome with 2-3 points indicating possible disease, 4-5 probable disease, and >5 definite disease. This patient scored a 7 on the RegiSCAR scale for eosinophilia, rash, organ involvement, and exclusion of other causes (infectious and autoimmune). While the pharmacologic trigger in this case is unknown, it is speculated to be caused by vancomycin, meloxicam, or furosemide due to the favorable timeline of initiation. Despite aggressive treatment, DRESS syndrome can often be fatal. Because of this, early diagnosis and treatment of patients with suspected DRESS syndrome is imperative.

Keywords: drug reaction with eosinophilia and systemic symptoms, multi-organ failure, pulmonary involvement, renal failure

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Authors: Eric A. Morris, Xia Liu, Yee Ka Wong, Greg J. Evans, Jeff R. Brook

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Air quality monitoring stations tend to be widely distributed and are often located far from major roadways, thus, determining where, when, and which traffic-related air pollutants (TRAPs) have the greatest impact on public health becomes a matter of extrapolation. Compact, multipollutant sensor systems are an effective solution as they enable several TRAPs to be monitored in a geospatially dense network, thus filling in the gaps between conventional monitoring stations. This work describes two applications of one such system named AirSENCE for gathering actionable air quality data relevant to smart city infrastructures. In the first application, four AirSENCE devices were co-located with traffic monitors around the perimeter of a city block in Oshawa, Ontario. This study, which coincided with the COVID-19 outbreak of 2020 and subsequent lockdown measures, demonstrated a direct relationship between decreased traffic volumes and TRAP concentrations. Conversely, road construction was observed to cause elevated TRAP levels while reducing traffic volumes, illustrating that conventional smart city sensors such as traffic counters provide inadequate data for inferring air quality conditions. The second application used two AirSENCE sensors on opposite sides of a major 2-way commuter road in Toronto. Clear correlations of TRAP concentrations with wind direction were observed, which shows that impacted areas are not necessarily static and may exhibit high day-to-day variability in air quality conditions despite consistent traffic volumes. Both of these applications provide compelling evidence favouring the inclusion of air quality sensors in current and future smart city infrastructure planning. Such sensors provide direct measurements that are useful for public health alerting as well as decision-making for projects involving traffic mitigation, heavy construction, and urban renewal efforts.

Keywords: distributed sensor network, continuous ambient air quality monitoring, Smart city sensors, Internet of Things, traffic-related air pollutants

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Authors: Sandra T. Matarneh, Mark Danso-Amoako, Salam Al-Bizri, Mark Gaterell

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Today’s facilities are ever more sophisticated and the need for available and reliable information for operation and maintenance activities is vital. The key challenge for facilities managers is to have real-time accurate and complete information to perform their day-to-day activities and to provide their senior management with accurate information for decision-making process. Currently, there are various technology platforms, data repositories, or database systems such as Computer-Aided Facility Management (CAFM) that are used for these purposes in different facilities. In most current practices, the data is extracted from paper construction documents and is re-entered manually in one of these computerized information systems. Construction Operations Building information exchange (COBie), is a non-proprietary data format that contains the asset non-geometric data which was captured and collected during the design and construction phases for owners and facility managers use. Recently software vendors developed add-in applications to generate COBie spreadsheet automatically. However, most of these add-in applications are capable of generating a limited amount of COBie data, in which considerable time is still required to enter the remaining data manually to complete the COBie spreadsheet. Some of the data which cannot be generated by these COBie add-ins is essential for facilities manager’s day-to-day activities such as job sheet which includes preventive maintenance schedules. To facilitate a seamless data transfer between BIM models and facilities management systems, we developed a framework that enables automated data generation using the data extracted directly from BIM models to external web database, and then enabling different stakeholders to access to the external web database to enter the required asset data directly to generate a rich COBie spreadsheet that contains most of the required asset data for efficient facilities management operations. The proposed framework is a part of ongoing research and will be demonstrated and validated on a typical university building. Moreover, the proposed framework supplements the existing body of knowledge in facilities management domain by providing a novel framework that facilitates seamless data transfer between BIM models and facilities management systems.

Keywords: building information modeling, BIM, facilities management systems, interoperability, information management

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