Search results for: capability maturity model integration

Authors: Viet-Hung Truong, Seung-Eock Kim

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Rain–wind induced vibration of inclined cable is a special aerodynamic phenomenon because it is easily influenced by many factors, especially the distribution of rivulet and wind velocity. This paper proposes a new 3D model of inclined cable, based on single degree-of-freedom model. Aerodynamic forces are firstly established and verified with the existing results from a 2D model. The 3D model of inclined cable is developed. The 3D model is then applied to assess the effects of wind velocity distribution and the continuity of rivulets on the cable. Finally, an inclined cable model with small sag is investigated.

Keywords: 3D model, rain - wind induced vibration, rivulet, analytical model

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Authors: Zhidong Zhang, Amanda Resendez

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This study is to examine how teachers’ perspective on education technology use in their class influence their students’ achievement. The authors hypothesized that teachers’ perspective can directly or indirectly influence students’ learning, performance, and achievements. In this study, a questionnaire entitled, Teacher’s Perspective on Educational Technology, was delivered to 63 teachers and 1268 students’ mathematics and reading achievement records were collected. The questionnaire consists of four parts: a) demographic variables, b) attitudes on technology integration, c) outside factor affecting technology integration, and d) technology use in the classroom. Kruskal-Wallis and hierarchical regression analysis techniques were used to examine: 1) the relationship between the demographic variables and teachers’ perspectives on educational technology, and 2) how the demographic variables were causally related to students’ mathematics and reading achievements. The study found that teacher demographics were significantly related to the teachers’ perspective on educational technology with p < 0.05 and p < 0.01 separately. These teacher demographical variables included the school district, age, gender, the grade currently teach, teaching experience, and proficiency using new technology. Further, these variables significantly predicted students’ mathematics and reading achievements with p < 0.05 and p < 0.01 separately. The variations of R² are between 0.176 and 0.467. That means 46.7% of the variance of a given analysis can be explained by the model.

Keywords: teacher's perception of technology use, mathematics achievement, reading achievement, Kruskal-Wallis test, hierarchical regression analysis

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Authors: Christian Lavault

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In this paper, the generalized fractional integral operators of two generalized Mittag-Leffler type functions are investigated. The special cases of interest involve the generalized M-series and K-function, both introduced by Sharma. The two pairs of theorems established herein generalize recent results about left- and right-sided generalized fractional integration operators applied here to the M-series and the K-function. The note also results in important applications in physics and mathematical engineering.

Keywords: Fox–Wright Psi function, generalized hypergeometric function, generalized Riemann– Liouville and Erdélyi–Kober fractional integral operators, Saigo's generalized fractional calculus, Sharma's M-series and K-function

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Authors: Azzeddine Atibi, Lamalif latifa, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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This study analyzes the integration of Information and Communication Technologies (ICT) in modern education, where these tools have become essential. Due to the rapid emergence of new technologies and their increasing adoption in education, it is important to understand how teachers use and perceive these tools. The study pursues three objectives : examining current teacher practices regarding ICT, evaluating their impact on student skills and engagement, and making recommendations for better integration of ICT in education. The study's methodology is based on a quantitative approach, using a questionnaire administered to a sample of 104 teachers. This questionnaire, rigorously validated to ensure its reliability, gathers representative data on perceptions and challenges related to the use of ICT. The results show widespread adoption of ICT by teachers, with the majority reporting an improvement in student skills due to these technologies. However, opinions diverge on their impact on student engagement : some teachers note an increase in engagement, while others remain skeptical. Persistent challenges include insufficient technological infrastructure and the need for ongoing training. The recommendations highlight the importance of improving infrastructures and supporting the professional development of teachers to optimize the integration of ICT.

Keywords: ICT, education, teaching practices, teacher perceptions, continuing education

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Authors: Gisele Mah, Paul Saah

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The rising rates of inflation are hindering economic growth in developing nations. Hence, this study investigated the effects of inflation rates on the economic growth of South Africa using the secondary time series data from 1987 to 2022. The main objectives of this study were to investigate the long run relationship between inflation and economic growth, and also to determine the causality direction between these two variables. The study utilized the Autoregressive Distributed Lag (ARDL) bounds test of co-integration to investigate whether there is a long-run relationship between inflation and economic growth. The Pairwise Granger causality approach was employed to determine the second objective, which is the direction of causality. The study discovered only one co-integration relationship between our variables and it was between inflation and economic growth. The results showed that there is a negative and significant relationship between inflation and economic growth. There appeared to be a positive and significant relationship between economic growth and exchange rate. The interest rates have shown to be negative and insignificant in explaining economic growth. The study also established that inflation does Granger cause economic growth which is given as GDP. Similarly, the study discovered that inflation Granger causes exchange rates. Therefore, the study recommends that inflation should be decreased in South Africa, in order for economic growth to increase. Contrary, this study recommends that South Africa should increase its exchange rates, in order for economic growth to also increase.

Keywords: inflation rate, economic growth, South Africa, autoregressive distributed lag model

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Authors: Somdech Rungsrisawas

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The objectives of this study are to examine the relationship between the competitive advantage of small and medium enterprises (SMEs) and their overall performance. A mixed method has been applied to identify the effect of determinants toward competitive advantage. The sample is composed of SMEs in product and service businesses. The study has been tested at an organizational level with samples of SME entrepreneurs, business successors, and board of directors or management team. Quantitative analysis has been conducted through multiple regression analysis with 400 samples. The findings illustrate that each aspect of competitive advantage needs a different set of driving factors to explain either the direct or the indirect effect on firm performance. Interestingly, technological capability is a perfect mediator and interorganizational cooperation toward competitive advantage. In addition, differentiation is difficult to be perceived by customers, as well as difficult to manage; however, it is considered important to develop an SMEs product or service for firm sustainably.

Keywords: competitive advantage, firm performance, technological capability, Small and Medium Enterprise (SMEs)

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Authors: Brian Connett, Bryan O'Halloran

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Systems assets within critical infrastructures were seemingly safe from the exploitation or attack by nefarious cyberspace actors. Now, critical infrastructure is a target and the resources to exploit the cyber physical systems exist. These resources are characterized in terms of patience, stealth, replication-ability and extraordinary robustness. System owners are obligated to maintain a high level of protection measures. The difficulty lies in knowing when to fortify a critical infrastructure against an impending attack. Models currently exist that demonstrate the value of knowing the attacker’s capabilities in the cyber realm and the strength of the target. The shortcomings of these models are that they are not designed to respond to the inherent fast timing of an attack, an impetus that can be derived based on open-source reporting, common knowledge of exploits of and the physical architecture of the infrastructure. A useful model will inform systems owners how to align infrastructure architecture in a manner that is responsive to the capability, willingness and timing of the attacker. This research group has used an existing theoretical model for estimating parameters, and through analysis, to develop a decision tool for would-be target owners. The continuation of the research develops further this model by estimating the variable parameters. Understanding these parameter estimations will uniquely position the decision maker to posture having revealed the vulnerabilities of an attacker’s, persistence and stealth. This research explores different approaches to improve on current attacker-defender models that focus on cyber threats. An existing foundational model takes the point of view of an attacker who must decide what cyber resource to use and when to use it to exploit a system vulnerability. It is valuable for estimating parameters for the model, and through analysis, develop a decision tool for would-be target owners.

Keywords: critical infrastructure, cyber physical systems, modeling, exploitation

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Authors: Vytautas Galvanauskas, Rimvydas Simutis, Donatas Levisauskas, Vykantas Grincas, Renaldas Urniezius

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The paper deals with model-based development and implementation of efficient control strategies for recombinant protein synthesis in fed-batch E.coli cultivation processes. Based on experimental data, a kinetic dynamic model for cultivation process was developed. This model was used to determine substrate feeding strategies during the cultivation. The proposed feeding strategy consists of two phases – biomass growth phase and recombinant protein production phase. In the first process phase, substrate-limited process is recommended when the specific growth rate of biomass is about 90-95% of its maximum value. This ensures reduction of glucose concentration in the medium, improves process repeatability, reduces the development of secondary metabolites and other unwanted by-products. The substrate limitation can be enhanced to satisfy restriction on maximum oxygen transfer rate in the bioreactor and to guarantee necessary dissolved carbon dioxide concentration in culture media. In the recombinant protein production phase, the level of substrate limitation and specific growth rate are selected within the range to enable optimal target protein synthesis rate. To account for complex process dynamics, to efficiently exploit the oxygen transfer capability of the bioreactor, and to maintain the required dissolved oxygen concentration, adaptive control algorithms for dissolved oxygen control have been proposed. The developed model-based control strategies are useful in scale-up of cultivation processes and accelerate implementation of innovative biotechnological processes for industrial applications.

Keywords: adaptive algorithms, model-based control, recombinant E. coli, scale-up of bioprocesses

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Authors: D. Naresh Yadav, K. Anand Kishore, Bhaskar Bethi, Shirish H. Sonawane, D. Bhagawan

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The untreated industrial wastewater discharged into the environment causes the contamination of soil, water and air. Advanced treatment methods for enhanced wastewater treatment are attracting substantial interest among the currently employed unit processes in wastewater treatment. The textile industry is one of the predominant in wastewater production at current industrialized situation. The refused dyes at textile industry need to be treated in proper manner before its discharge into water bodies. In the present investigation, hybrid treatment process has been developed for the treatment of synthetic mixed dye wastewater. Photocatalysis and ceramic nanoporous membrane are mainly used for process integration to minimize the fouling and increase the flux. Commercial semiconducting powders (TiO2 and ZnO) has used as a nano photocatalyst for the degradation of mixed dye in the hybrid system. Commercial ceramic nanoporous tubular membranes have been used for the rejection of dye and suspended catalysts. Photocatalysis with catalyst has shown the average of 34% of decolorization (RB-32%, BG-34% and CR-36%), whereas ceramic nanofiltration has shown the 56% (RB-54%, BG-56% and CR-58%) of decolorization. Integration of photocatalysis and ceramic nanofiltration has shown 96% (RB-94%, BG-96% and CR-98%) of dye decolorization over 90 min of operation.

Keywords: photocatalysis, ceramic nanoporous membrane, wastewater treatment, advanced oxidation process, process integration

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Authors: Vephkhvia Grigalashvili

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This paper provides an overview of criteria for good governance in Georgian defense sector and scientific outcomes of comparative research. A respect for good governance and its realization into Georgian national defense sector represents a fundamental institutional necessity as well as country`s politico-legal obligation within the framework of the existing collaboration mechanisms with NATO (especially Building Integrity (BI) Programme) and the Association Agreement between the EU and Georgia. Furthermore good governance is considered as a democracy measuring criterion in country`s Euro-Atlantic integration process. Accordingly, integration and further development of the contemporary approaches of good governance into Georgian defense management model represents a burning issue of the country. The assessment of an existing model of the country, identification of defects and determination of course of institutional reforms in a mutual comparison format of good governance mechanisms of NATO or/and the EU member Eastern European or Baltic countries positively assessed by the international organizations is considered as a precondition for its effective realization. Scientific aims of this study are: (a) to conduct comparative analysis of Georgian national principles and generalized standards of NATO or/and the EU member Eastern European and Baltic countries in following segments of good governance: open governance; anticorruption policy; conflict of interests; integrity; internal and external control bodies; (b) to formulate theoretical and practical recommendations on reforms to be implemented in the country`s national defence sector. As research reveals, although, institutional / legal pillars of good governance in Georgian defense sector generally are in compliance with international principles, the quality of implementation of good government norms still remains as an area that needs further development by raising awareness of public servants and community.

Keywords: anti-corruption policy within Georgian defense governance, conflict of interests within Georgian defense governance, good governance in Georgian defense sector, principles of integrity in Georgian defense management

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Authors: R. B. Ogunrinde, C. C. Jibunoh

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In this paper, a spectral decomposition method is developed for the direct integration of stiff and nonstiff homogeneous linear (ODE) systems with linear, constant, or zero right hand sides (RHSs). The method does not require iteration but obtains solutions at any random points of t, by direct evaluation, in the interval of integration. All the numerical solutions obtained for the class of systems coincide with the exact theoretical solutions. In particular, solutions of homogeneous linear systems, i.e. with zero RHS, conform to the exact analytical solutions of the systems in terms of t.

Keywords: spectral decomposition, linear RHS, homogeneous linear systems, eigenvalues of the Jacobian

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Authors: Ejoke U. P., Smitha Dev., Madwuke Ann, DuPlessis E. D.

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The study examines the relationship between psychological capital (PsyCap) and social well-being among international faculty members in the United Arab Emirates (UAE). The UAE has become a significant destination for global academic talent, yet challenges related to social integration, acceptance, and overall well-being persist among its international faculty. The study focuses on the predictive role of PsyCap, encompassing hope, efficacy, resilience, and optimism, in determining various dimensions of social well-being, including social integration, acceptance, contribution, actualization, and coherence. Additionally, the research investigates the potential moderating or mediating effects of institutional support and Faculty Job-Status position on the relationship between PsyCap and social well-being. Through structural equation modeling, we found that institutional support mediated the positive relationship between PsyCap and SWB and the permanent Faculty job-status position type strengthens the relationship between PsyCap and SWB. Our findings uncover the pathways through which PsyCap influences the social well-being outcomes of international faculty in the UAE. The findings will contribute to the development of tailored interventions and support systems aimed at enhancing the integration experiences and overall well-being of international faculty within the UAE academic community. Thus, fostering a more inclusive and thriving academic environment in the UAE.

Keywords: faculty job-status, institutional-faculty, psychological capital, social well-being, UAE

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Authors: Supakij Saisopon

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The process of economic development incurs spatial transformation. This spatial alternation also causes environmental impacts, leading to higher pollution. In the case of Thailand, there is still a lack of price-endogenous quantitative analysis incorporating relationships among economic growth, land-use change, and environmental impact. Therefore, this paper aimed at developing the Computable General Equilibrium (CGE) model with the capability of stimulating such mutual effects. The developed CGE model has also incorporated the nested constant elasticity of transformation (CET) structure that describes the spatial redistribution mechanism between agricultural land and urban area. The simulation results showed that the 1% decrease in the availability of agricultural land lowers the value-added of agricultural by 0.036%. Similarly, the 1% reduction of availability of urban areas can decrease the value-added of manufacturing and service sectors by 0.05% and 0.047%, respectively. Moreover, the outcomes indicate that the increasing farming and urban areas induce higher volumes of solid waste, wastewater, and air pollution. Specifically, the 1% increase in the urban area can increase pollution as follows: (1) the solid waste increase by 0.049%, (2) water pollution ̶ indicated by biochemical oxygen demand (BOD) value ̶ increase by 0.051% and (3) air pollution ̶ indicated by the volumes of CO₂, N₂O, NOₓ, CH₄, and SO₂ ̶ increase within the range of 0.045%–0.051%. With the simulation for exploring the sustainable development path, a 1% increase in agricultural land use efficiency leads to the shrinking demand for agricultural land. But this is not happening in urban, a 1% scale increase in urban utilization results in still increasing demand for land. Therefore, advanced clean production technology is necessary to align the increasing land-use efficiency with the lowered pollution density.

Keywords: CGE model, CET structure, environmental impact, land use

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Authors: K. N. Umesh

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Wood Polymer Composites (WPC) were synthesized artificially by combining polypropylene, wood and resin. It is difficult to obtain a good surface finish by conventional machining on WPC because of material degradation due to excessive heat generated during the process. In order to preserve the material property and deliver a better surface finish and accuracy, a proper solution is devised for the machining of wood composites at low temperature. This research focuses on studying the effects of parameters of cryogenic machining on sawdust incorporated polypropylene composite material, in view of evolving the most suitable composition and an appropriate combination of process parameters. The machining characteristics of the six different compositions of WPC were evaluated by analyzing the trend. An attempt is made to determine proper combinations material composition and process control parameters, through process capability studies. A WPC of 80%-wood (saw dust particles), 20%-polypropylene and 0%-resin was found to be the best alternative for obtaining the best surface finish under cryogenic machining conditions.

Keywords: Cryogenic Machining, Process Capability, Surface Finish, Wood Polymer Composites

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Authors: Naci Kalkan, Ihsan Dagtekin

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Passive design responds to improve indoor thermal comfort and minimize the energy consumption. The present research analyzed the how efficiently passive solar technologies generate heating and cooling and provide the system integration for domestic applications. In addition to this, the aim of this study is to increase the efficiency of solar systems system with integration some innovation and optimization. As a result, outputs of the project might start a new sector to provide environmentally friendly and cheap cooling for domestic use.

Keywords: passive solar systems, heating, cooling, thermal comfort, ventilation systems

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Authors: Ebrahim Alamatian, Seyed Mehdi Afzalnia

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One of the most vital hydraulic structures is the dam. Regarding the unrecoverable damages which may occur after a dam break phenomenon, analyzing dams’ break is absolutely essential. GOLESTAN dam is located in the western South of Mashhad city in Iran. GOLESTAN dam break might lead to severe problems due to adjacent tourist and entertainment areas. In this paper, a numerical code based on the finite volume method was applied for assessing the risk of GOLESTAN dam break. As to this issue, first, a canal with a triangular barrier was modeled so as to verify the capability of the concerned code. Comparing analytical, experimental and numerical results showed that water level in the model results is in a good agreement with the similar water level in the analytical solutions and experimental data. The results of dam break modeling are revealed that two of the bridges, that are PARTOIE and NAMAYESHGAH, located downstream in the flow direction, are at risk following the potential GOLESTAN dam break. Therefore, the required times to conduct the precautionary measures at bridges were calculated at about 12 and 21 minutes, respectively. Thus, it is crucial to announce people about the possible risks of the dam break in order to decrease likely losses.

Keywords: numerical model, shallow water equations, GOLESTAN dam break, dry and wet beds modeling

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Authors: Theertha Chandroth

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This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

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Authors: F. Fakheri Raof, F. Zobeidizadeh

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The present study examined the potential capability of Spirogyra algae remove heavy metals Zn, Pb, Cu, and Cr from the water. For this purpose, the water treatment No. 3 of Ahvaz County in Khuzestan Province of Iran was selected as a case study. From 8 sampling stations, 4 stations were dedicated to the water samples and 4 stations to the algae samples. According to the obtained results, the concentration of the heavy metals Cr, Cu, Pb, and Zn in water samples were within the ranges of 1.98-19.53, 0.67-13.45, 1-23.18, and 2.12-83.04 µg/L. Besides, the concentration of heavy metal Cr, Pb, Cu, and Zn in spirogyra algae samples varied between the ranges 2.30-3.61, 2.06-3.43, 2.29-2.56, and 9.88-10.84 µg/L. The highest amount of metal absorption in spirogyra algae samples was related to the zinc. The obtained results also indicated that the last spirogyra algae sample which was at the inlet of Tank 4 absorbed the lowest concentration of metals. This would be due to the treatment process along the course of ponds resulted in completely pure water at the outlet without the existence of algae on the sides. The paper also provides some useful recommendations on this issue.

Keywords: absorption, Ahvaz, heavy metal, spirogyra algae, water treatment plants

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Authors: Lucero Luciano, Cesar Celis, Jose Ramos

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Polygeneration improves energy efficiency and reduce both energy consumption and pollutant emissions compared to conventional generation technologies. A polygeneration system is a variation of a cogeneration one, in which more than two outputs, i.e., heat, power, cooling, water, energy or fuels, are accounted for. In particular, polygeneration systems integrating solar energy and water desalination represent promising technologies for energy production and water supply. They are therefore interesting options for coastal regions with a high solar potential, such as those located in southern Peru and northern Chile. Notice that most of the Peruvian and Chilean mining industry operations intensive in electricity and water consumption are located in these particular regions. Accordingly, this work focus on the design and integration of a polygeneration system producing industrial heating, cooling, electrical power and water for an industrial plant. The design procedure followed in this work involves integer linear programming modeling (MILP), operational planning and dynamic operating conditions. The technical and economic feasibility of integrating renewable energy technologies (photovoltaic and solar thermal, PV+CPS), thermal energy store, power and thermal exchange, absorption chillers, cogeneration heat engines and desalination technologies is particularly assessed. The polygeneration system integration carried out seek to minimize the system total annual cost subject to CO2 emissions restrictions. Particular economic aspects accounted for include investment, maintenance and operating costs.

Keywords: desalination, design and integration, polygeneration systems, renewable energy

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Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

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In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

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Authors: Buse A. Ataç, Doğan K. Cenan, Arda Çetinkaya, Naz D. Şahin, Köksal Sanlı, Zeynep Koç, Akın Kısa

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With its spatial data reliability, interpretation and questioning capabilities, Geographical Information Systems make significant contributions to scientists, planners and practitioners. Geographic information systems have received great attention in today's digital world, growing rapidly, and increasing the efficiency of use. Access to and use of current and accurate geographical data, which are the most important components of the Geographical Information System, has become a necessity rather than a need for sustainable and economic development. This project aims to enable sharing of data collected by public institutions and organizations on a web-based platform. Within the scope of the project, INSPIRE (Infrastructure for Spatial Information in the European Community) data specifications are considered as a road-map. In this context, Turkey's National Geographic Information System (TUCBS) Integration Project supports sharing spatial data within 61 pilot public institutions as complied with defined national standards. In this paper, which is prepared by the project team members in the TUCBS Integration Project, the technical process with a detailed methodology is explained. In this context, the main technical processes of the Project consist of Geographic Data Analysis, Geographic Data Harmonization (Standardization), Web Service Creation (WMS, WFS) and Metadata Creation-Publication. In this paper, the integration process carried out to provide the data produced by 61 institutions to be shared from the National Geographic Data Portal (GEOPORTAL), have been trying to be conveyed with a detailed methodology.

Keywords: data specification, geoportal, GIS, INSPIRE, Turkish National Geographic Information System, TUCBS, Turkey's national geographic information system

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Authors: Xuan Zhou, Litian Zhang, Shuixiang Li

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Mesh deformation using radial basis function interpolation method has been demonstrated to produce quality meshes with relatively little computational cost using a concise algorithm. However, it still suffers from the limited deformation ability, especially in large deformation. In this paper, a pre-displacement improvement is proposed to improve the problem that illegal meshes always appear near the moving inner boundaries owing to the large relative displacement of the nodes near inner boundaries. In this improvement, nodes near the inner boundaries are first associated to the near boundary nodes, and a pre-displacement based on the displacements of associated boundary nodes is added to the nodes near boundaries in order to make the displacement closer to the boundary deformation and improve the deformation capability. Several 2D and 3D numerical simulation cases have shown that the pre-displacement improvement for radial basis function (RBF) method significantly improves the mesh quality near inner boundaries and deformation capability, with little computational burden increasement.

Keywords: mesh deformation, mesh quality, background mesh, radial basis function

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Authors: Felix Golla

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In an era where technology increasingly intersects with education, the potential of chatbots and ChatGPT agents in enhancing student learning experiences in higher education is both significant and timely. This study explores the integration of these AI-driven tools in educational settings, emphasizing their design and functionality to meet the specific needs of students. Recognizing the gap in literature concerning student-centered AI applications in education, this research offers valuable insights into the role and efficacy of chatbots and ChatGPT agents as educational tools. Employing qualitative research methodologies, the study involved conducting semi-structured interviews with university students. These interviews were designed to gather in-depth insights into the students' experiences and expectations regarding the use of AI in learning environments. The High-Performance Cycle Model, renowned for its focus on goal setting and motivation, served as the theoretical framework guiding the analysis. This model helped in systematically categorizing and interpreting the data, revealing the nuanced perceptions and preferences of students regarding AI tools in education. The major findings of the study indicate a strong preference among students for chatbots and ChatGPT agents that offer personalized interaction, adaptive learning support, and regular, constructive feedback. These features were deemed essential for enhancing student engagement, motivation, and overall learning outcomes. Furthermore, the study revealed that students perceive these AI tools not just as passive sources of information but as active facilitators in the learning process, capable of adapting to individual learning styles and needs. In conclusion, this study underscores the transformative potential of chatbots and ChatGPT agents in higher education. It highlights the need for these AI tools to be designed with a student-centered approach, ensuring their alignment with educational objectives and student preferences. The findings contribute to the evolving discourse on AI in education, suggesting a paradigm shift towards more interactive, responsive, and personalized learning experiences. This research not only informs educators and technologists about the desirable features of educational chatbots but also opens avenues for future studies to explore the long-term impact of AI integration in academic curricula.

Keywords: chatbot design in education, high-performance cycle model application, qualitative research in AI, student-centered learning technologies

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Authors: Dušica Kovačević

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This study explores the influence of destructive groups on the mental health and social integration of high school students in Loznica, Serbia. Despite increasing concerns, there is a significant lack of research on the impact of these groups on adolescents in this region. This qualitative study aims to fill this gap by examining the prevalence of destructive groups, their psychological effects on students, and their broader social implications. Data were collected through surveys and in-depth interviews with high school students, educators, and mental health professionals. The study focuses on key mental health indicators, such as anxiety, depression, and identity formation, alongside social factors, including peer relationships and community engagement. Additionally, it defines coping mechanisms and supporting strategies employed by students affected by these groups. The findings reveal substantial psychological and social challenges faced by students exposed to destructive groups, including increased levels of anxiety and depression, disrupted identity development, and impaired social integration. Insights into the personal experiences of these students provide a detailed understanding of the groups’ impact, underscoring the need for targeted interventions. This research offers evidence-based recommendations for educators, mental health practitioners, and policymakers. It emphasizes the importance of developing effective educational programs and support services to enhance the well-being of high school advocates for proactive measures to protect adolescent mental health and promote healthy social values within educational and community settings.

Keywords: adolescents, mental health, destructive groups, social integration, qualitative study, high school students, Serbia

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Authors: J. Satya Eswari, Ch. Venkateswarlu

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The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation.

Keywords: pharmaceutical formulation, multiple regression model, response surface method, radial basis function network, differential evolution, multiobjective optimization

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Authors: Yadgar Tayfur, Antony Darby, Tim Ibell, Mark Evernden, John Orr

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Fabric form-work is a technique to cast concrete structures with a great advantage of saving concrete material of up to 40%. This technique is particularly associated with the optimized concrete structures that usually have smaller cross-section dimensions than equivalent prismatic members. However, this can make the structural system produced from these members prone to smaller serviceability safety margins. Therefore, it is very important to understand the serviceability issue of non-prismatic concrete structures. In this paper, an analytical computer-based model to optimize concrete beams and to predict load-deflection behaviour of both prismatic and non-prismatic concrete beams is presented. The model was developed based on the method of sectional analysis and integration of curvatures. Results from the analytical model were compared to load-deflection behaviour of a number of beams with different geometric and material properties from other researchers. The results of the comparison show that the analytical program can accurately predict the load-deflection response of concrete beams with medium reinforcement ratios. However, it over-estimates deflection values for lightly reinforced specimens. Finally, the analytical program acceptably predicted load-deflection behaviour of on-prismatic concrete beams.

Keywords: fabric-formed concrete, continuous beams, optimisation, serviceability

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Authors: Morteza Malek Yarand, Hadi Saebi Monfared

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This study aimed at designing and developing a mechanical force gauge for the square watermelon mold for the first time. It also tried to introduce the square watermelon characteristics and its production limitations. The mechanical force gauge performance and the product itself were also described. There are three main designable gauge models: a. hydraulic gauge, b. strain gauge, and c. mechanical gauge. The advantage of the hydraulic model is that it instantly displays the pressure and thus the force exerted by the melon. However, considering the inability to measure forces at all directions, complicated development, high cost, possible hydraulic fluid leak into the fruit chamber and the possible influence of increased ambient temperature on the fluid pressure, the development of this gauge was overruled. The second choice was to calculate pressure using the direct force a strain gauge. The main advantage of these strain gauges over spring types is their high precision in measurements; but with regard to the lack of conformity of strain gauge working range with water melon growth, calculations were faced with problems. Finally the mechanical pressure gauge has advantages, including the ability to measured forces and pressures on the mold surface during melon growth; the ability to display the peak forces; the ability to produce melon growth graph thanks to its continuous force measurements; the conformity of its manufacturing materials with the required physical conditions of melon growth; high air conditioning capability; the ability to permit sunlight reaches the melon rind (no yellowish skin and quality loss); fast and straightforward calibration; no damages to the product during assembling and disassembling; visual check capability of the product within the mold; applicable to all growth environments (field, greenhouses, etc.); simple process; low costs and so forth.

Keywords: mechanical force gauge, mold, reshaped fruit, square watermelon

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Jing-Gang Xie

Abstract:

The research, in this case, considers the integration of the Quantum Field Theory and the General Relativity Theory. As two successful models in explaining behaviors of particles, they are incompatible since they work at different masses and scales of energy, with the evidence that regards the description of black holes and universe formation. It is so considering previous efforts in merging the two theories, including the likes of the String Theory, Quantum Gravity models, and others. In a bid to prove an actionable experiment, the paper’s approach starts with the derivations of the existing theories at present. It goes on to test the derivations by applying the same initial assumptions, coupled with several deviations. The resulting equations get similar results to those of classical Newton model, quantum mechanics, and general relativity as long as conditions are normal. However, outcomes are different when conditions are extreme, specifically with no breakdowns even for less than Schwarzschild radius, or at Planck length cases. Even so, it proves the possibilities of integrating the two theories.

Keywords: general relativity theory, particles, photons, Quantum Gravity Model, gravitational frequency shift

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

Abstract:

The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

Procedia PDF Downloads 46