Search results for: modeling strategy

Authors: Nadia Allouache, Omar Rahli

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Many promising technologies have been developed to harness the sun's energy. These technologies help in economizing energy and environmental protection. The solar refrigerating systems are one of these important technologies. In addition to environmental benefits and energy saving, adsorption refrigerating systems have many advantages such as lack of moving parts, simplicity of construction and low operating costs. The work aimed to establish the main factors that affect the performances of an adsorption refrigerating system using different geometries of adsorbers and different adsorbent-adsorbate pairs. The numerical modeling of the heat and mass transfer in the system, using various working pairs, such as: activated carbon-ammonia, calcium chlorid-ammonia, activated carbon fiber- methanol and activated carbon AC35-methanol, show that the adsorber design can influence the system performances; The thermal performances of system are better in the annular configuration case. An optimal value of generating temperature is observed in annular adsorber case for which the thermal performance of the cooling system is maximal. While in the plate adsorber, above a certain value of generating temperature, the performance of the system remains almost constant. The environmental conditions such as solar radiation and pressure have a great influence in the system efficiency, and the choice of the working pair depends on the environmental conditions and the geometry of the adsorber.

Keywords: adsorber geometry, numerical modeling, optimal environmental conditions, working pairs.

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Authors: Bolatbek Rysbaiuly, Nazerke Rysbayeva, Aigerim Rysbayeva

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Relevance: Energy saving elevated to public policy in almost all developed countries. One of the areas for energy efficiency is improving and tightening design standards. In the tie with the state standards, make high demands for thermal protection of buildings. Constructive arrangement of layers should ensure normal operation in which the humidity of materials of construction should not exceed a certain level. Elevated levels of moisture in the walls can be attributed to a defective condition, as moisture significantly reduces the physical, mechanical and thermal properties of materials. Absence at the design stage of modeling the processes occurring in the construction and predict the behavior of structures during their work in the real world leads to an increase in heat loss and premature aging structures. Method: To solve this problem, widely used method of mathematical modeling of heat and mass transfer in materials. The mathematical modeling of heat and mass transfer are taken into the equation interconnected layer [1]. In winter, the thermal and hydraulic conductivity characteristics of the materials are nonlinear and depends on the temperature and moisture in the material. In this case, the experimental method of determining the coefficient of the freezing or thawing of the material becomes much more difficult. Therefore, in this paper we propose an approximate method for calculating the thermal conductivity and moisture permeability characteristics of freezing or thawing material. Questions. Following the development of methods for solving the inverse problem of mathematical modeling allows us to answer questions that are closely related to the rational design of fences: Where the zone of condensation in the body of the multi-layer fencing; How and where to apply insulation rationally his place; Any constructive activities necessary to provide for the removal of moisture from the structure; What should be the temperature and humidity conditions for the normal operation of the premises enclosing structure; What is the longevity of the structure in terms of its components frost materials. Tasks: The proposed mathematical model to solve the following problems: To assess the condition of the thermo-physical designed structures at different operating conditions and select appropriate material layers; Calculate the temperature field in a structurally complex multilayer structures; When measuring temperature and moisture in the characteristic points to determine the thermal characteristics of the materials constituting the surveyed construction; Laboratory testing to significantly reduce test time, and eliminates the climatic chamber and expensive instrumentation experiments and research; Allows you to simulate real-life situations that arise in multilayer enclosing structures associated with freezing, thawing, drying and cooling of any layer of the building material.

Keywords: energy saving, inverse problem, heat transfer, multilayer walling

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Authors: Olusola Akintunde Adediran

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This study examined differential effect of Gender difference in social interaction skill of pupils with autism using token economy and video modeling as intervention strategies. A pretest, posttest, control group, quasi-experimental research design was adopted in the study. 17 participants (11 males and 6 females) were selected purposively from 5 centres in Ibadan and randomized into three groups (token economy, video modeling and control groups). Two instruments were used in the study; Autism Spectrum Rating Scale (ASRS) for 299.00 Autistic Disorder (r = 0.82) and Children’s Self-report Social Skill Scale (CS4) (r= 0.93). A descriptive statistics was used to analyse the participants social interaction data based on intervention and gender, while inferential statistics of analysis of covariance (ANCOVA) and scheffe post-hoc measure was used to anlayse three null hypotheses tested at 0.05 level of significance. The results obtained indicated that there was a significant main effect of treatment on social interaction of participants, but there was no significant of main effect of gender on the social interaction of participants, hence, (F(2,14) = .741; p > .05, eta = .050). Lastly, there was no significant interaction effect of treatment and gender of the participants, hence (F(2,10) = 2.177; p > .05, eta 2 = 202). The study has contributed to the frontiers of knowledge by establishing that social interaction of autism is attainable when token economy and video modelling are used as treatment intervention, hence, they should be adopted by the teachers, curriculum planners and other stakeholders.

Keywords: social interaction, token economy, video modelling, autism, gender

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Authors: Shinta Ardiana Sari, Dini Puti Angelia

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A high number of urban population in Jakarta has been a substantial issue for mobility strategy. Transit Oriented Development (TOD) becomes one of the strategies to improve community livability based on the design of transit place and the system of its context. TOD principle is trying to win over pedestrian motorization habit, makes people would rather transit and travel more than using private vehicle. Train station takes the main role as the catalyst to emerge TOD, in Jakarta this role will be taken by Commuter line and the future MRT. For advancing its development, architectural design perspective is needed to perform evaluation while seeking for the strategies between accessibility transportation modes with convenience and safety for increasing human behavioral intention. This paper discovers design strategy for transit place that appropriates with Jakarta condition use the basic theories of liminal space and transit-oriented development goal. This paper use evidence-based approach with typology method to analyze the present condition of Commuter Line station in Jakarta and precedent of Asian Cities, Tokyo and Seoul, as the secondary sources, and also with numbers of valid questionnaires. Furthermore, the result of this paper aims to the emerging of a transit-oriented community by giving design requirements and suggestion transportation policies preparing for the operational of MRT in the future Jakarta and other similar cities.

Keywords: station design, transit place, transit-oriented development, urban

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Authors: Amal G. Kurian

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The use of mathematical modeling has seen a considerable boost in recent times with the development of many advanced algorithms and mathematical modeling capabilities. The advantages this method has over other methods are that they are much closer to standard physics theories and thus represent a better theoretical model. They take lesser solving time and have the ability to change various parameters for optimization, which is a big advantage, especially in automotive industry. This thesis work focuses on a thorough investigation of the effects of vehicle speed and road roughness on a heavy commercial vehicle ride and structural dynamic responses. Since commercial vehicles are kept in operation continuously for longer periods of time, it is important to study effects of various physical conditions on the vehicle and its user. For this purpose, various experimental as well as simulation methodologies, are adopted ranging from experimental transfer path analysis to various road scenario simulations. To effectively investigate and eliminate several causes of unwanted responses, an efficient and robust technique is needed. Carrying forward this motivation, the present work focuses on the development of a mathematical model of a 4-axle configuration heavy commercial vehicle (HCV) capable of calculating responses of the vehicle on different road PSD inputs and vehicle speeds. Outputs from the model will include response transfer functions and PSDs and wheel forces experienced. A MATLAB code will be developed to implement the objectives in a robust and flexible manner which can be exploited further in a study of responses due to various suspension parameters, loading conditions as well as vehicle dimensions. The thesis work resulted in quantifying the effect of various physical conditions on ride comfort of the vehicle. An increase in discomfort is seen with velocity increase; also the effect of road profiles has a considerable effect on comfort of the driver. Details of dominant modes at each frequency are analysed and mentioned in work. The reduction in ride height or deflection of tire and suspension with loading along with load on each axle is analysed and it is seen that the front axle supports a greater portion of vehicle weight while more of payload weight comes on fourth and third axles. The deflection of the vehicle is seen to be well inside acceptable limits.

Keywords: mathematical modeling, HCV, suspension, ride analysis

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Authors: Mia Françoise

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This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization.

Keywords: financial stocks, optimized asset allocation, prediction modelling, South Africa

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Robert H. Bradley

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Many minority adolescents in the United States live in adverse circumstances that pose long-term threats to their well-being. A strong sense of personal control and self-efficacy can help youth mitigate some of those risks and may help protect youth from influences connected with deviant peer groups. Accordingly, it is important to identify conditions that help foster feelings of efficacy in areas that seem critical for the accomplishment of developmental tasks during adolescence. The purpose of this study is to examine two aspects of the home environment (modeling and encouragement of maturity, family companionship and investment) and their relation to three components of self efficacy (self efficacy in enlisting social resources, self efficacy for engaging in independent learning, and self-efficacy for self-regulatory behavior) in three groups of minority adolescents (Native American, African American, Latino). The sample for this study included 54 Native American, 131 African American, and 159 Latino families, each with a child between 16 and 20 years old. The families were recruited from four states: Arizona, Arkansas, California, and Oklahoma. Each family was administered the Late Adolescence version of the Home Observation for Measurement of the Environment (HOME) Inventory and each adolescent completed a 30-item measure of perceived self-efficacy. Three areas of self-efficacy beliefs were examined for this study: enlisting social resources, independent learning, and self-regulation. Each of the three areas of self-efficacy was regressed on the two aspects of the home environment plus overall household risk. For Native Americans, modeling and encouragement were significant for self-efficacy pertaining to enlisting social resources and independent learning. For African Americans, companionship and investment was significant in all three models. For Latinos, modeling and encouragement was significant for self-efficacy pertaining to enlisting social resources and companionship and investment were significant for the other two areas of self-efficacy. The findings show that even as minority adolescents are becoming more individuated from their parents, the quality of experiences at home continues to be associated with their feelings of self-efficacy in areas important for adaptive functioning in adult life. Specifically, individuals can develop a sense that they are efficacious in performing key tasks relevant to work, social relationships, and management of their own behavior if they are guided in how to deal with key challenges and they have been exposed and supported by others who are competent in dealing with such challenges. The findings presented in this study would seem useful given that there is so little current research on home environmental factors connected to self-efficacy beliefs among adolescents in the three groups examined. It would seem worthwhile that personnel from health, human service and juvenile justice agencies give attention to supporting parents in communicating with adolescents, offering expectations to adolescents in mutually supportive ways, and in engaging with adolescents in productive activities. In comparison to programs for parents of young children, there are few specifically designed for parents of children in middle childhood and adolescence.

Keywords: family companionship, home environment, household income, modeling, self-efficacy

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Authors: Chaitanya R. Mali, V. Vinod, Ashwin W. Patwardhan

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Design of long vertical steam generator (SG) tubes in nuclear power plant involves an understanding of different aspects of flow boiling phenomenon such as flow instabilities, flow regimes, dry out, critical heat flux, pressure drop, etc. The knowledge of the prediction of local thermal hydraulic characteristics is necessary to understand these aspects. For this purpose, the methodology has been developed which covers all the flow boiling regimes to model full range flow boiling phenomenon. In this methodology, the vertical tube is divided into four sections based on vapor fraction value at the end of each section. Different modeling strategies have been applied to the different sections of the vertical tube. Computational fluid dynamics simulations have been performed on a vertical SG tube of 0.0126 m inner diameter and 23 m length. The thermal hydraulic parameters such as vapor fraction, liquid temperature, heat transfer coefficient, pressure drop, heat flux distribution have been analyzed for different designed heat duties (1.1 MW (20%) to 3.3 MW (60%)) and flow conditions (10 % to 80 %). The sensitivity of different boiling parameters such as bubble departure diameter, nucleation site density, bubble departure frequency on the thermal hydraulic parameters was also studied. Flow instability has been observed at 20 % designed heat duty and 20 % flow conditions.

Keywords: thermal hydraulics, boiling, vapor fraction, sensitivity

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Authors: Samuele Abagnato, Lucia Rigamonti

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Life-Cycle-Assessment (LCA) is an effective tool to quantify the environmental impacts of reuse models and recycling technologies for textiles. In this work, publications in the last ten years about LCA on textile waste are classified according to location, goal and scope, functional unit, waste composition, impact assessment method, impact categories, and sensitivity analysis. Twenty papers have been selected: 50% are focused only on recycling, 30% only on reuse, the 15% on both, while only one paper considers only the final disposal of the waste. It is found that reuse is generally the best way to decrease the environmental impacts of textiles waste management because of the avoided impacts of manufacturing a new item. In the comparison between a product made with recycled yarns and a product from virgin materials, in general, the first option is less impact, especially for the categories of climate change, water depletion, and land occupation, while for other categories, such as eutrophication or ecotoxicity, under certain conditions the impacts of the recycled fibres can be higher. Cultivation seems to have quite high impacts when natural fibres are involved, especially in the land use and water depletion categories, while manufacturing requires a remarkable amount of electricity, with its associated impact on climate change. In the analysis of the reuse processes, relevant importance is covered by the laundry phase, with water consumption and impacts related to the use of detergents. About the sensitivity analysis, it can be stated that one of the main variables that influence the LCA results and that needs to be further investigated in the modeling of the LCA system about this topic is the substitution rate between recycled and virgin fibres, that is the amount of recycled material that can be used in place of virgin one. Related to this, also the yield of the recycling processes has a strong influence on the results of the impact. The substitution rate is also important in the modeling of the reuse processes because it represents the number of avoided new items bought in place of the reused ones. Another aspect that appears to have a large influence on the impacts is consumer behaviour during the use phase (for example, the number of uses between two laundry cycles). In conclusion, to have a deeper knowledge of the impacts of a life-cycle approach of textile waste, further data and research are needed in the modeling of the substitution rate and of the use phase habits of the consumers.

Keywords: environmental impacts, life-cycle-assessment, textiles recycling, textiles reuse, textiles waste management

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Authors: Tapas Acharya, Monalisa Mitra

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Overlay modeling is the most widely used conventional analysis for spatial decision support system. Overlay modeling requires a set of themes with different weightage computed in varied manners, which gives a resultant input for further integrated analysis. In spite of the popularity and most widely used technique; it gives inconsistent and erroneous results for similar inputs while processed in various GIS overlay techniques. This study is an attempt to compare and analyse the differences in the outputs of different overlay methods using GIS platform with same set of themes of the Precambrian metamorphic to obtain groundwater prospecting in Precambrian metamorphic rocks. The objective of the study is to emphasize the most suitable overlay method for groundwater prospecting in older Precambrian metamorphics. Seven input thematic layers like slope, Digital Elevation Model (DEM), soil thickness, lineament intersection density, average groundwater table fluctuation, stream density and lithology have been used in the spatial overlay models of fuzzy overlay, weighted overlay and weighted sum overlay methods to yield the suitable groundwater prospective zones. Spatial concurrence analysis with high yielding wells of the study area and the statistical comparative studies among the outputs of various overlay models using RStudio reveal that the Weighted Overlay model is the most efficient GIS overlay model to delineate the groundwater prospecting zones in the Precambrian metamorphic rocks.

Keywords: fuzzy overlay, GIS overlay model, groundwater prospecting, Precambrian metamorphics, weighted overlay, weighted sum overlay

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Authors: V. Radulescu, S. Dumitru

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Introduction: Determination of the temperature field inside a fluid in motion has many practical issues, especially in the case of turbulent flow. The phenomenon is greater when the solid walls have a different temperature than the fluid. The turbulent heat and mass transfer have an essential role in case of the thermal pollution, as it was the recorded during the damage of the Thermoelectric Power-plant Oradea (closed even today). Basic Methods: Solving the theoretical turbulent thermal pollution represents a particularly difficult problem. By using the semi-empirical theories or by simplifying the made assumptions, based on the experimental measurements may be assured the elaboration of the mathematical model for further numerical simulations. The three zones of flow are analyzed separately: the vicinity of the solid wall, the turbulent transition zone, and the turbulent core. For each area are determined the distribution law of temperature. It is determined the dependence of between the Stanton and Prandtl numbers with correction factors, based on measurements experimental. Major Findings/Results: The limitation of the laminar thermal substrate was determined based on the theory of Landau and Levice, using the assumption that the longitudinal component of the velocity pulsation and the pulsation’s frequency varies proportionally with the distance to the wall. For the calculation of the average temperature, the formula is used a similar solution as for the velocity, by an analogous mediation. On these assumptions, the numerical modeling was performed with a gradient of temperature for the turbulent flow in pipes (intact or damaged, with cracks) having 4 different diameters, between 200-500 mm, as there were in the Thermoelectric Power-plant Oradea. Conclusions: It was made a superposition between the molecular viscosity and the turbulent one, followed by addition between the molecular and the turbulent transfer coefficients, necessary to elaborate the theoretical and the numerical modeling. The concept of laminar boundary layer has a different thickness when it is compared the flow with heat transfer and that one without a temperature gradient. The obtained results are within the margin of error of 5%, between the semi-empirical classical theories and the developed model, based on the experimental data. Finally, it is obtained a general correlation between the Stanton number and the Prandtl number, for a specific flow (with associated Reynolds number).

Keywords: experimental measurements, numerical correlations, thermal pollution through pipelines, turbulent thermal flow

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Authors: Yake Zhang, Peng Xu

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The development of building energy models (BEM) required for architectural design and analysis is a time-consuming and complex process, demanding a deep understanding and proficient use of simulation software. To streamline the generation of complex building energy models, this study proposes an automated method for generating building energy models using a large language model and the BEM library aimed at improving the efficiency of model generation. This method leverages a large language model to parse user-specified requirements for target building models, extracting key features such as building location, window-to-wall ratio, and thermal performance of the building envelope. The BEM library is utilized to retrieve energy models that match the target building’s characteristics, serving as reference information for the large language model to enhance the accuracy and relevance of the generated model, allowing for the creation of a building energy model that adapts to the user’s modeling requirements. This study enables the automatic creation of building energy models based on natural language inputs, reducing the professional expertise required for model development while significantly decreasing the time and complexity of manual configuration. In summary, this study provides an efficient and intelligent solution for building energy analysis and simulation, demonstrating the potential of a large language model in the field of building simulation and performance modeling.

Keywords: artificial intelligence, building energy modelling, building simulation, large language model

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Authors: El Miloudi Djelloul

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The computer network play an important position for practical implementations of the differently system. To implement a system into network above all is needed to know all the configurations, which is responsible to be a part of the system, and to give adequate information and solution in realtime. So if want to implement this system for example in the school or relevant institutions, the first step is to analyze the types of model which is needed to be configured and another important step is to organize the works in the context of devices, as a part of the general system. Often before configuration, as important point is descriptions and documentations from all the works into the respective process, and then to organize in the aspect of problem-solving. The computer network as critic infrastructure is very specific so the paper present the effectiveness solutions in the structured aspect viewed from one side, and another side is, than the paper reflect the positive aspect in the context of modeling and block schema presentations as an better alternative to solve the specific problem because of continually distortions of the system from the line of devices, programs and signals or packed collisions, which are in movement from one computer node to another nodes.

Keywords: local area networks, LANs, block schema presentations, computer network system, computer node, critical infrastructure packed collisions, structural control system representations, computer network, implementations, modeling structural representations, companies, computers, context, control systems, internet, software

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Milica Karadžić

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The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina.

Keywords: anti-prion activity, chemometrics, molecular modeling, QSAR

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Authors: Milena Lakicevic

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The paper deals with the problem of optimizing management options for urban parks within different scenarios of nature protection and tourism importance. The procedure is demonstrated on a case study example of urban parks in Novi Sad (Serbia). Six management strategies for the selected area have been processed by the decision support method PROMETHEE. Two criteria used for the evaluation were nature protection and tourism and each of them has been divided into a set of indicators: for nature protection those were biodiversity and preservation of original landscape, while for tourism those were recreation potential, aesthetic values, accessibility and culture features. It was pre-assumed that each indicator in a set is equally important to a corresponding criterion. This way, the research was focused on a sensitivity analysis of criteria weights. In other words, weights of indicators were fixed and weights of criteria altered along the entire scale (from the value of 0 to the value of 1), and the assessment has been performed in two-dimensional surrounding. As a result, one could conclude which management strategy would be the most appropriate along with changing of criteria importance. The final ranking of management alternatives was followed up by investigating the mean PROMETHEE Φ values for all options considered and when altering the importance of nature protection/tourism. This type of analysis enabled detecting an alternative with a solid performance along the entire scale, i.e., regardlessly of criteria importance. That management strategy can be seen as a compromise solution when the weight of criteria is not defined. As a conclusion, it can be said that, in some cases, instead of having criteria importance fixed it is important to test the outputs depending on the different schemes of criteria weighting. The research demonstrates the state of the final decision when the decision maker can estimate criteria importance, but also in cases when the importance of criteria is not established or known.

Keywords: criteria weights, PROMETHEE, sensitivity analysis, urban parks

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Authors: Irina-Emily Hansen, Ola Jon Mork

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The European economic growth strategy and supporting it framework for research and innovation highlight the importance of nurturing new open innovation in order to strengthen Europe’s competitiveness. One of the main approaches to enhance innovation in European society is the Triple Helix model that centres on science- industry collaboration where the universities are assigned the managerial role. In spite of the defined collaboration strategy, the collaboration between academics and in-dustry in Europe has still many challenges. Many of them are explained by culture difference: academic culture aims towards scientific knowledge, while businesses are oriented towards pro-duction and profitable results; also execution of collaborative projects is seen differently by part-ners involved. That proves that traditional management strategies applied to collaboration between researchers and businesses are not effective. There is a need for dynamic strategies that can support the interaction between researchers and industry intensifying knowledge co-creation and contributing to development of national innovation system (NIS) by incorporating individual, organizational and inter-organizational learning. In order to find a good subject to follow, the researchers of a given paper have investigated one of the most rapidly developing knowledge-based, innovation society, Singapore. Singapore does not dispose much land- or sea- resources that normally provide income for any country. Therefore, Singapore was forced to think differently and build society on resources that are available: talented people and knowledge. Singapore has during the last twenty years developed attracting high rated university camps, research institutions and leading industrial companies from all over the world. This article elucidates and elaborates Singapore’s national innovation strategies from Knowledge Management perspective. The research is done on the variety of organizations that enable and support knowledge development in this state: governmental research and development (R&D) centers in universities, private talent incubators for entrepreneurs, and industrial companies with own R&D departments. The research methods are based on presentations, documents, and visits at a number of universities, research institutes, innovation parks, governmental institutions, industrial companies and innovation exhibitions in Singapore. In addition, a literature review of science articles is made regarding the topic. The first finding is that objectives of collaboration between researchers, entrepreneurs and industry in Singapore correspond primary goals of the state: knowledge- and economy growth. There are common objectives for all stakeholders on all national levels. The second finding is that Singapore has enabled system on a national level that supports innovation the entire way from fostering or capturing the new knowledge, providing knowledge exchange and co-creation to application of it in real-life. The conclusion is that innovation means not only new idea, but also the enabling mechanism for its execution and the marked-oriented approach in order that new knowledge can be absorbed in society. The future research can be done with regards to application of Singapore knowledge management strategy in innovation to European countries.

Keywords: knowledge management strategy, national innovation system, research industry and business collaboration, knowledge enabling

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Authors: Suci Lestari Yuana, Shofi Fatihatun Sholihah, Derarika Ensta Jesse

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Textile is one of buyer-driven industry which rely on label trust from the consumers. Most of textile manufacturers produce textile and textile products based on consumer demands. The company’s policy is highly depend on the dynamic evolution of consumers behavior. Recently, ecofriendly has become one of the most important factor of western consumers to purchase the textile and textile product (TPT) from the company. In that sense, companies from developing countries are encouraged to follow western consumers values. Some examples of ecolabel certificate are ISO (International Standard Organisation), Lembaga Ekolabel Indonesia (Indonesian Ecolabel Instution) and Global Ecolabel Network (GEN). The submission of national company to international standard raised a critical question whether this is a reflection towards the legitimation of global norms into national policy or it is actually a practical strategy of the company to gain global consumer. By observing one of the prominent textile company in Indonesia, this research is aimed to discuss what kind of impetus factors that cause a company to use ecolabel and what is the meaning behind it. Whether it comes from normative power or the strategy of the company. This is a qualitative research that choose a company in Sukoharjo, Central Java, Indonesia as a case study in explaining the pratice of ecolabelling by textitle company. Some deep interview is conducted with the company in order to get to know the ecolabelling process. In addition, this research also collected some document which related to company’s ecolabelling process and its impact to company’s value. The finding of the project reflected issues that concerned several issues: (1) role of media as consumer information (2) role of government and non-government actors as normative agency (3) role of company in social responsibility (4) the ecofriendly consciousness as a value of the company. As we know that environmental norms that has been admitted internationally has changed the global industrial process. This environmental norms also pushed the companies around the world, especially the company in Sukoharjo, Central Java, Indonesia to follow the norm. The neglection toward the global norms will remained the company in isolated and unsustained market that will harm the continuity of the company. So, in buyer-driven industry, the characteristic of company-consumer relations has brought a fast dynamic evolution of norms and values. The creation of global norms and values is circulated by passing national territories or identities.

Keywords: ecolabeling, waste management, CSR, normative power

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Authors: Nien-Ming Hong, Kuei-Fang Huang

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Climate change is an important issue in future, which seriously affects water resources for a long term planning and management. Flood assessment is highly related with climate and land use. Increasing rainfall and urbanization will induce the inundated area in future. For adapting the impacts of climate change, a land use planning is a good strategy for reducing flood damage. The study is to build a trade-off process with different land use types. The Ta-Liao watershed is the study area with three types of land uses that are build-up, farm and forest. The build-up area is concentrated in the downstream of the watershed. Different rainfall amounts are applied for assessing the land use in 1996, 2005 and 2013. The adapted strategies are based on retarding the development of urban and a trade-off process. When a land changes from farm area to built-up area in downstream, this study is to search for a farm area and change it to forest/grass area or building a retention area in the upstream. For assessing the effects of the strategy, the inundation area is simulated by the Flo-2D model with different rainfall conditions and land uses. The results show inundation maps of several cases with land use change planning. The results also show the trade-off strategies and retention areas can decrease the inundated area and divide the inundated area, which are better than retarding urban development. The land use change is usually non-reverse and the planning should be constructed before the climate change.

Keywords: climate change, land use change, flood risk assessment, land use planning

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Authors: Muhammad L. A. Dwiyoga

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The condition of a spatial land in the industrial park needs special attention to be studied more deeply. Geoplanology modeling can help arrange area according to his ability. This research method is to perform the analysis of remote sensing, Geographic Information System, and more comprehensive analysis to determine geological characteristics and the ability to land on the area of research and its relation to the geological disaster. Cilegon is part of Banten province located in western Java, and the direction of the north is the Strait of Borneo. While the southern part is bordering the Indian Ocean. Morphology study area is located in the highlands to low. In the highlands of identified potential landslide prone, whereas in low-lying areas of potential flooding. Moreover, in the study area has the potential prone to earthquakes, this is due to the proximity of enough research to Mount Krakatau and Subdcution Zone. From the results of this study show that the study area has a susceptibility to landslides located around the District Waringinkurung. While the region as a potential flood areas in the District of Cilegon and surrounding areas. Based on the seismic data, this area includes zones with a range of magnitude 1.5 to 5.5 magnitude at a depth of 1 to 60 Km. As for the ability of its territory, based on the analyzes and studies carried out the need for renewal of the map Spatial Plan that has been made, considering the development of a fairly rapid Cilegon area.

Keywords: geoplanology, spatial plan, geological hazard, cilegon, Indonesia

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Authors: Carlson Murray, Ali Lazrak

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Robust experimental evidence of systematic violations of expected utility (EU) establishes that individuals facing risk overweight utility from low probability gains and losses when making choices. These findings motivated development of models of preferences with probability weighting functions, such as rank dependent utility (RDU). We solve for the optimal investing strategy of an RDU investor in a dynamic binomial setting from which we derive implications for investing behavior. We show that relative to EU investors with constant relative risk aversion, commonly measured probability weighting functions produce optimal RDU terminal wealth with significant downside protection and upside exposure. We additionally find that in contrast to EU investors, RDU investors optimally choose a portfolio that contains fair bets that provide payo↵s that can be interpreted as lottery outcomes or exposure to idiosyncratic returns. In a calibrated version of the model, we calculate that RDU investors would be willing to pay 5% of their initial wealth for the freedom to trade away from an optimal EU wealth allocation. The dynamic trading strategy that supports the optimal wealth allocation implies portfolio weights that are independent of initial wealth but requires higher risky share after good stock return histories. Optimal trading also implies the possibility of non-participation when historical returns are poor. Our model fills a gap in the literature by providing new quantitative and qualitative predictions that can be tested experimentally or using data on household wealth and portfolio choice.

Keywords: behavioral finance, probability weighting, portfolio choice

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Authors: Neda Azimi, Masoud Rahimi, Faezeh Mohammadi

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Computational fluid dynamics (CFD) simulation was performed to investigate the effect of ferrofluid stimulation on hydrodynamic and mass transfer characteristics of two immiscible liquid phases in a Y-micromixer. The main purpose of this work was to develop a numerical model that is able to simulate hydrodynamic of the ferrofluid flow under magnetic field and determine its effect on mass transfer characteristics. A uniform external magnetic field was applied perpendicular to the flow direction. The volume of fluid (VOF) approach was used for simulating the multiphase flow of ferrofluid and two-immiscible liquid flows. The geometric reconstruction scheme (Geo-Reconstruct) based on piecewise linear interpolation (PLIC) was used for reconstruction of the interface in the VOF approach. The mass transfer rate was defined via an equation as a function of mass concentration gradient of the transported species and added into the phase interaction panel using the user-defined function (UDF). The magnetic field was solved numerically by Fluent MHD module based on solving the magnetic induction equation method. CFD results were validated by experimental data and good agreements have been achieved, which maximum relative error for extraction efficiency was about 7.52 %. It was showed that ferrofluid actuation by a magnetic field can be considered as an efficient mixing agent for liquid-liquid two-phase mass transfer in microdevices.

Keywords: CFD modeling, hydrodynamic, micromixer, ferrofluid, mixing

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Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

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This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

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The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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Authors: Tan Swee Liang

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This paper studies the two-way relationship between fintech credit and banking efficiency using the Generalized panel Method of Moment (GMM) estimation in structural equation modeling (SEM). Banking system efficiency, defined as its ability to produce the existing level of outputs with minimal inputs, is measured using input-oriented data envelopment analysis (DEA), where the whole banking system of an economy is treated as a single DMU. Banks are considered an intermediary between depositors and borrowers, utilizing inputs (deposits and overhead costs) to provide outputs (increase credits to the private sector and its earnings). Analysis of the interrelationship between fintech credit and bank efficiency is conducted to determine the impact in different country groupings (ASEAN, Asia and OECD), in particular the banking system response to fintech credit platforms. Our preliminary results show that banks do respond to the greater pressure caused by fintech platforms to enhance their efficiency, but differently across the different groups. The author’s earlier research on ASEAN-5 high bank overhead costs (as a share of total assets) as the determinant of economic growth suggests that expenses may not have been channeled efficiently to income-generating activities. One practical implication of the findings is that policymakers should enable alternative financing, such as fintech credit, as a warning or encouragement for banks to improve their efficiency.

Keywords: fintech lending, banking efficiency, data envelopment analysis, structural equation modeling

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Authors: Yogesh Mahor, Subhash Nigam, Abhai Khare

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Road safety education is a composite subject which should be viewed holistically if taken into accoubehavior change communication, safe road infrastructure and low enforcement. Specific and customized road safety education is crucial for each type of road user and learners in the formal and informal teaching and various kind of training programs directly sponsored by state and center government, as they are active contributors to shaping a community and responsible citizens. The aim of this discussion article is to explore a strategy to integrate road safety education into the formal curriculum of schools, higher education institutions, driving schools, skill development centers, various government funded urban and rural development training institutions and their work plans as standing agenda. By applying the desktop research method, the article conceptualizes what the possible focus of road safety education and training should be. The article then explores international common practices in road safety education and training, and considers the necessary synergy between education, road engineering and low enforcement. The article uses secondary data collected from documents which are then analysed in a sectoral way. A well-designed road safety strategy for mainstreaming education and government-sponsored training is urgently needed, facilitating partnerships in various sectors to implement such education in the students and learners in multidisciplinary ways.

Keywords: road safety education, curriculum-based road safety education, behavior change communication, low enforcement, road engineering, safe system approach, infrastructure development consultants

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Authors: S. Abera, T. Gidey, W. Terefe

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Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

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Authors: Francesca Marsili

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The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

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Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

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This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

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Authors: Alexandra Papagianni, George Filis, Panagiotis Papadopoulos

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The liberalization of the energy market and the increasing penetration of fluctuating renewables (e.g., wind and solar power) have heightened the importance of the spot market for ensuring efficient electricity supply. This is further emphasized by the EU’s goal of achieving net-zero emissions by 2050. The day-ahead market (DAM) plays a key role in European energy trading, accounting for 80-90% of spot transactions and providing critical insights for next-day pricing. Therefore, short-term electricity price forecasting (EPF) within the DAM is crucial for market participants to make informed decisions and improve their market positioning. Existing literature highlights out-of-sample performance as a key factor in assessing EPF accuracy, with influencing factors such as predictors, forecast horizon, model selection, and strategy. Several studies indicate that electricity demand is a primary price determinant, while renewable energy sources (RES) like wind and solar significantly impact price dynamics, often lowering prices. Additionally, incorporating data from neighboring countries, due to market coupling, further improves forecast accuracy. Most studies predict up to 24 steps ahead using hourly data, while some extend forecasts using higher-frequency data (e.g., half-hourly or quarter-hourly). Short-term EPF methods fall into two main categories: statistical and computational intelligence (CI) methods, with hybrid models combining both. While many studies use advanced statistical methods, particularly through different versions of traditional AR-type models, others apply computational techniques such as artificial neural networks (ANNs) and support vector machines (SVMs). Recent research combines multiple methods to enhance forecasting performance. Despite extensive research on EPF accuracy, a gap remains in understanding how forecasting strategy affects prediction outcomes. While iterated strategies are commonly used, they are often chosen without justification. This paper contributes by examining whether the choice of forecasting strategy impacts the quality of day-ahead price predictions, especially for multi-step forecasts. We evaluate both iterated and direct methods, exploring alternative ways of conducting iterated forecasts on benchmark and state-of-the-art forecasting frameworks. The goal is to assess whether these factors should be considered by end-users to improve forecast quality. We focus on the Greek DAM using data from July 1, 2021, to March 31, 2022. This period is chosen due to significant price volatility in Greece, driven by its dependence on natural gas and limited interconnection capacity with larger European grids. The analysis covers two phases: pre-conflict (January 1, 2022, to February 23, 2022) and post-conflict (February 24, 2022, to March 31, 2022), following the Russian-Ukraine conflict that initiated an energy crisis. We use the mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (sMAPE) for evaluation, as well as the Direction of Change (DoC) measure to assess the accuracy of price movement predictions. Our findings suggest that forecasters need to apply all strategies across different horizons and models. Different strategies may be required for different horizons to optimize both accuracy and directional predictions, ensuring more reliable forecasts.

Keywords: short-term electricity price forecast, forecast strategies, forecast horizons, recursive strategy, direct strategy

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