Search results for: collaborative problem solving

Authors: Tris Kee

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As the urban design discipline develops renewed interests in participatory design and collaborative place-making, it becomes critical to review the potential and limitations in current processes to ensure a sustainable method for future development.This paper explores how collaborative design can be a key to future sustainable urban development through two case studies from Asia.The process involves a multi-disciplinary collaboration and an innovative learning process by sharing ideas as well as careful consideration on social, economic and political circumstances among government and district stakeholders.This intrinsic proposition of innovative participatory planning implies interdisciplinary collaboration between professionals and local residents to integrate knowledge into new urban place-making thinking.Design innovation in contemporary society can manifest itself in the discourse sustainable urban development by bottom-up planning and community driven design. This paper examines the emerging design pedagogy which promotes interdisciplinary coalition of professionals and local stakeholders in community development as an innovative design rubric to create a sustainable urban approach.Through two case studies in Hong Kong, this paper reviews and critically evaluates the process of how the notion of sustainable development in contemporary urban planning theory is underpinned by the collaborative design practice.

Keywords: collaborative design, design innovation, sustainable development, urban development

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Authors: Eylem Tas

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This empirical study aims to explore the development of students' entrepreneurial skills through problem-based learning within the context of university-industry collaborations (UICs) in curriculum co-design and co-delivery (CDD). The research question guiding this study is: "How do problem-based learning and university-industry collaborations influence the development of students' entrepreneurial skills in the context of curriculum co-design and co-delivery?” To address this question, the study was conducted in a big city in Germany and involved interviews with stakeholders from various industries, including the private sector, government agencies (govt), and non-governmental organizations (NGOs). These stakeholders had established collaborative partnerships with the targeted university for projects encompassing entrepreneurial development aspects in CDD. The study sought to gain insights into the intricacies and subtleties of UIC dynamics and their impact on fostering entrepreneurial skills. Qualitative content analysis, based on Mayring's guidelines, was employed to analyze the interview transcriptions. Through an iterative process of manual coding, 442 codes were generated, resulting in two main sections: "the role of problem-based learning and UIC in fostering entrepreneurship" and "challenges and requirements of problem-based learning within UIC for systematical entrepreneurship development.” The chosen experimental approach of semi-structured interviews was justified by its capacity to provide in-depth perspectives and rich data from stakeholders with firsthand experience in UICs in CDD. By enlisting participants with diverse backgrounds, industries, and company sizes, the study ensured a comprehensive and heterogeneous sample, enhancing the credibility of the findings. The first section of the analysis delved into problem-based learning and entrepreneurial self-confidence to gain a deeper understanding of UIC dynamics from an industry standpoint. It explored factors influencing problem-based learning, alignment of students' learning styles and preferences with the experiential learning approach, specific activities and strategies, and the role of mentorship from industry professionals in fostering entrepreneurial self-confidence. The second section focused on various interactions within UICs, including communication, knowledge exchange, and collaboration. It identified key elements, patterns, and dynamics of interaction, highlighting challenges and limitations. Additionally, the section emphasized success stories and notable outcomes related to UICs' positive impact on students' entrepreneurial journeys. Overall, this research contributes valuable insights into the dynamics of UICs and their role in fostering students' entrepreneurial skills. UICs face challenges in communication and establishing a common language. Transparency, adaptability, and regular communication are vital for successful collaboration. Realistic expectation management and clearly defined frameworks are crucial. Responsible data handling requires data assurance and confidentiality agreements, emphasizing the importance of trust-based relationships when dealing with data sharing and handling issues. The identified key factors and challenges provide a foundation for universities and industrial partners to develop more effective UIC strategies for enhancing students' entrepreneurial capabilities and preparing them for success in today's digital age labor market. The study underscores the significance of collaborative learning and transparent communication in UICs for entrepreneurial development in CDD.

Keywords: collaborative learning, curriculum co-design and co-delivery, entrepreneurial skills, problem-based learning, university-industry collaborations

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Authors: Wanatchapong Kongkaew

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This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.

Keywords: Gaussian process regression, iterated local search, simulated annealing, single machine total weighted tardiness

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Authors: Chung To Kong, Siu Ming Yiu

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Rubik's cube was invented in 1974. Since then, speedcubers all over the world try their best to break the world record again and again. The newest record is 3.47 seconds. There are many factors that affect the timing, including turns per second (tps), algorithm, finger trick, hardware of the cube. In this paper, the lower bound of the cube solving time will be discussed using convex optimization. Extended analysis of the world records will be used to understand how to improve the timing. With the understanding of each part of the solving step, the paper suggests a list of speed improvement techniques. Based on the analysis of the world record, there is a high possibility that the 3 seconds mark will be broken soon.

Keywords: Rubik's Cube, speed, finger trick, optimization

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Authors: Sung Ryong Kim, Hyung Sup Han, Jae-Yup Kim

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Many engineering students feel uncomfortable in solving the industry related problems. There are many ways to strengthen the engineering student’s ability to solve the assigned problem when they get a job. Korea National University of Transportation has developed an industry-oriented undergraduate research program (URP). An URP program is designed for engineering students to provide an experience of solving a company’s research problem. The URP project is carried out for 6 months. Each URP team consisted of 1 company mentor, 1 professor, and 3-4 engineering students. A team of different majors is strongly encouraged to integrate different perspectives of multidisciplinary background. The corporate research projects proposed by companies are chosen by the major-related student teams. A company mentor gives the detailed technical background of the project to the students, and he/she also provides a basic data, raw materials and so forth. The company allows students to use the company's research equipment. An assigned professor has adjusted the project scope and level to the student’s ability after discussing with a company mentor. Monthly meeting is used to check the progress, to exchange ideas, and to help the students. It is proven as an effective engineering education program not only to provide an experience of company research but also to motivate the students in their course work. This program provides a premier interdisciplinary platform for undergraduate students to perform the practical challenges encountered in their major-related companies and it is especially helpful for students who want to get a job from a company that proposed the project.

Keywords: company mentor, industry oriented, interdisciplinary platform, undergraduate research program

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Authors: M. G. N. A. S. Fernando

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This study uses a researchable framework to improve the quality of ICT education and the Teaching Learning Assessment/ Evaluation (TLA/TLE) process. It utilizes existing resources while improving the methodologies along with pedagogical techniques and e-Learning approaches used in the secondary schools of Sri Lanka. The study was carried out in two phases. Phase I focused on investigating the factors which affect the quality of ICT education. Based on the key factors of phase I, the Phase II focused on the design of an Experimental Application Model with 6 activity levels. Each Level in the Activity Model covers one or more levels in the Revised Bloom’s Taxonomy. Towards further enhancement of activity levels, other pedagogical techniques (activity based learning, e-learning techniques, problem solving activities and peer discussions etc.) were incorporated to each level in the activity model as appropriate. The application model was validated by a panel of teachers including a domain expert and was tested in the school environment too. The validity of performance was proved using 6 hypotheses testing and other methodologies. The analysis shows that student performance with problem solving activities increased by 19.5% due to the different treatment levels used. Compared to existing process it was also proved that the embedded techniques (mixture of traditional and modern pedagogical methods and their applications) are more effective with skills development of teachers and students.

Keywords: activity models, Bloom’s taxonomy, ICT education, pedagogies

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Authors: S. Zenhari, M. R. Hematiyan, A. Khosravifard, M. R. Feizi

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The boundary element method (BEM) and the method of fundamental solutions (MFS) are well-known fundamental solution-based methods for solving a variety of problems. Both methods are boundary-type techniques and can provide accurate results. In comparison to the finite element method (FEM), which is a domain-type method, the BEM and the MFS need less manual effort to solve a problem. The aim of this study is to compare the accuracy and reliability of the BEM and the MFS. This comparison is made for 2D potential and elasticity problems with different boundary and loading conditions. In the comparisons, both convex and concave domains are considered. Both linear and quadratic elements are employed for boundary element analysis of the examples. The discretization of the problem domain in the BEM, i.e., converting the boundary of the problem into boundary elements, is relatively simple; however, in the MFS, obtaining appropriate locations of collocation and source points needs more attention to obtain reliable solutions. The results obtained from the presented examples show that both methods lead to accurate solutions for convex domains, whereas the BEM is more suitable than the MFS for concave domains.

Keywords: boundary element method, method of fundamental solutions, elasticity, potential problem, convex domain, concave domain

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems does not scale well on multi-CPU/multi-GPUs clusters. For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration instead of two for standard CG. The standard and pipelined CG methods need the vector entries generated by the current GPU and other GPUs for matrix-vector products. So the communication between GPUs becomes a major performance bottleneck on multi GPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using the pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP, and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: conjugate gradient, GPU, parallel programming, pipelined algorithm

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Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: frame, grey wolf optimization algorithm, modal residual force, structural damage detection

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Authors: Jason Digalakis, John Cotronis

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Memetic algorithms (MAs) are useful for solving optimization problems. It is quite difficult to search the search space of the optimization problem with large dimensions. There is a challenge to use all the cores of the system. In this study, a sequential implementation of the memetic algorithm is converted into a concurrent version, which is executed on the cores of both CPU and GPU. For this reason, CUDA and OpenMP libraries are operated on the parallel algorithm to make a concurrent execution on CPU and GPU, respectively. The aim of this study is to compare CPU and GPU implementation of the memetic algorithm. For this purpose, fourteen benchmark functions are selected as test problems. The obtained results indicate that our approach leads to speedups up to five thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have the potential to acceleration of MAs and allow them to solve much more complex tasks.

Keywords: memetic algorithm, CUDA, GPU-based memetic algorithm, open multi processing, multimodal functions, unimodal functions, non-linear optimization problems

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Authors: Mitat Uysal

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A new met heuristic optimization algorithm called as Migrating Birds Optimization is used for curve fitting by rational cubic Bezier Curves. This requires solving a complicated multivariate optimization problem. In this study, the solution of this optimization problem is achieved by Migrating Birds Optimization algorithm that is a powerful met heuristic nature-inspired algorithm well appropriate for optimization. The results of this study show that the proposed method performs very well and being able to fit the data points to cubic Bezier Curves with a high degree of accuracy.

Keywords: algorithms, Bezier curves, heuristic optimization, migrating birds optimization

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Authors: Simone Balin, Cecilia M. Bolognesi, Paolo Borin

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In the construction industry, there is a large amount of data and interconnected information. To manage this information effectively, a transition to the immersive digitization of information processes is required. This transition is important to improve knowledge circulation, product quality, production sustainability and user satisfaction. However, there is currently a lack of a common definition of immersion in the construction industry, leading to misunderstandings and limiting the use of advanced immersive technologies. Furthermore, the lack of guidelines and a common vocabulary causes interested actors to abandon the virtual world after the first collaborative steps. This research aims to define the optimal use of immersive technologies in the AEC sector, particularly for collaborative processes based on the BIM methodology. Additionally, the research focuses on creating classes and levels to structure and define guidelines and a vocabulary for the use of the " Immersive Need Level." This concept, matured by recent technological advancements, aims to enable a broader application of state-of-the-art immersive technologies, avoiding misunderstandings, redundancies, or paradoxes. While the concept of "Informational Need Level" has been well clarified with the recent UNI EN 17412-1:2021 standard, when it comes to immersion, current regulations and literature only provide some hints about the technology and related equipment, leaving the procedural approach and the user's free interpretation completely unexplored. Therefore, once the necessary knowledge and information are acquired (Informational Need Level), it is possible to transition to an Immersive Need Level that involves the practical application of the acquired knowledge, exploring scenarios and solutions in a more thorough and detailed manner, with user involvement, via different immersion scales, in the design, construction or management process of a building or infrastructure. The need for information constitutes the basis for acquiring relevant knowledge and information, while the immersive need can manifest itself later, once a solid information base has been solidified, using the senses and developing immersive awareness. This new approach could solve the problem of inertia among AEC industry players in adopting and experimenting with new immersive technologies, expanding collaborative iterations and the range of available options.

Keywords: AECindustry, immersive technology (IMT), virtual reality, augmented reality, building information modeling (BIM), decision making, collaborative process, information need level, immersive level of need

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Authors: José de Jesús Rivero Oliva, Jesús Salomón Llanes, Manuel Perdomo Ojeda, Antonio Torres Valle

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Combinatorial explosion is a common problem to both predominant methods for solving fault trees: Minimal Cut Set (MCS) approach and Binary Decision Diagram (BDD). High memory consumption impedes the complete solution of very complex fault trees. Only approximated non-conservative solutions are possible in these cases using truncation or other simplification techniques. The paper proposes a method (CSolv+) for solving complex fault trees, without any possibility of combinatorial explosion. Each individual MCS is immediately discarded after its contribution to the basic events importance measures and the Top gate Upper Bound Probability (TUBP) has been accounted. An estimation of the Top gate Exact Probability (TEP) is also provided. Therefore, running in a computer cluster, CSolv+ will guarantee the complete solution of complex fault trees. It was successfully applied to 40 fault trees from the Aralia fault trees database, performing the evaluation of the top gate probability, the 1000 Significant MCSs (SMCS), and the Fussell-Vesely, RRW and RAW importance measures for all basic events. The high complexity fault tree nus9601 was solved with truncation probabilities from 10-²¹ to 10-²⁷ just to limit the execution time. The solution corresponding to 10-²⁷ evaluated 3.530.592.796 MCSs in 3 hours and 15 minutes.

Keywords: system reliability analysis, probabilistic risk assessment, fault tree analysis, basic events importance measures

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Authors: Bello Theodora O., Animola Odunayo V., Owoade Johnson T.

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With the advent of Covid-19, online classroom instruction became a very important mode of instruction delivery during which learners were engaged in both collaborative and online interactive learning process, but along with it are challenges as well as its deliverables. This study therefore investigated the various online platform used by the students for learning among fresh undergraduate students of Obafemi Awolowo University, Ile-Ife, Osun Sate. It also assessed the student’s perception towards online learning in the university and examined the influence of collaborative learning among the students. Lastly, it examined the problems that are associated with collaborative online learning instruction in the university. These were with a view to providing empirical information on problems and prospects of online classroom instruction among fresh undergraduate physical science students of Obafemi Awolowo University, Ile-Ife. The study employed a descriptive survey research technique. The population comprised all the fresh undergraduates in physical science departments of Obafemi Awolowo University, Ile-Ife. The sample consisted two hundred freshmen in physical science departments of Obafemi Awolowo University, Ile-Ife, who were selected using simple random techniques. During the selection, a questionnaire was used to collect data from the respondents. The data were analyzed using appropriate descriptive of frequency, simple percentage, and mean. Results showed that Google Meet 149(74.5%), Telegram 120(60.0%), and Google Classroom 143(71.5%), are the prominent online classroom instruction used by the students in Obafemi Awolowo University, Ile-Ife. The results also showed that the freshmen’s perception towards online classroom instruction in Obafemi Awolowo University, Ile-Ife is low with cluster mean of 2.97. It further revealed that collaborative learning enhances the learning ability of below average learners more than that of the above average and average students (73.6%). Finally, the result showed that they are affirmative of the problems associated with online classroom instruction in Obafemi Awolowo University, Ile-Ife with cluster mean of 3.01. The result concluded that most Online platform used by the fresher’s students in Obafemi Awolowo University, Ile-Ife are Google Meet, Telegram and Google Classroom. The students have negatives perception towards online classroom instruction and the students are affirmative of the problems associated with online classroom instruction among physical science freshmen in Obafemi Awolowo University, Ile-Ife.

Keywords: online, instruction, freshmen, physical science, collaborative

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Authors: Leizhang Wang, Baocang Wang

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General Sieve Kernel (G6K) is considered as currently the fastest algorithm for the shortest vector problem (SVP) and record holder of open SVP challenge. We study the lattice basis quality improvement effects of the Workout proposed in G6K, which is composed of a series of pumps to solve SVP. Firstly, we use a low-dimensional pump output basis to propose a predictor to predict the quality of high-dimensional Pumps output basis. Both theoretical analysis and experimental tests are performed to illustrate that it is more computationally expensive to solve the LWE problems by using a G6K default SVP solving strategy (Workout) than these lattice reduction algorithms (e.g. BKZ 2.0, Progressive BKZ, Pump, and Jump BKZ) with sieving as their SVP oracle. Secondly, the default Workout in G6K is optimized to achieve a stronger reduction and lower computational cost. Thirdly, we combine the optimized Workout and the Pump output basis quality predictor to further reduce the computational cost by optimizing LWE instances selection strategy. In fact, we can solve the TU LWE challenge (n = 65, q = 4225, = 0:005) 13.6 times faster than the G6K default Workout. Fourthly, we consider a combined two-stage (Preprocessing by BKZ- and a big Pump) LWE solving strategy. Both stages use dimension for free technology to give new theoretical security estimations of several LWE-based cryptographic schemes. The security estimations show that the securities of these schemes with the conservative Newhope’s core-SVP model are somewhat overestimated. In addition, in the case of LAC scheme, LWE instances selection strategy can be optimized to further improve the LWE-solving efficiency even by 15% and 57%. Finally, some experiments are implemented to examine the effects of our strategies on the Normal Form LWE problems, and the results demonstrate that the combined strategy is four times faster than that of Newhope.

Keywords: LWE, G6K, pump estimator, LWE instances selection strategy, dimension for free

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Authors: Chonlawit Yuwajitaa, Suttipong Pruangkab

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Existing situation on labour use, health management and problems, and ancillary work done along with buffalo farming in Thailand was studied, There were 52 farms had been interviewed during August to September 2014. The study revealed that 100 percent of labor use was family labors themselves and all of farmers reared their buffaloes and grew rice simultaneously. The farmers valued veterinary service and advice as the most important problem (40.40%) and buffalo farming health problems was found 7.69% of dystocia, retain placenta and abortion. The major problem that should be taken into account was officials involved and buffalo farming should be continually promoted by government sectors to help solving economic problems as a whole.

Keywords: buffalo, labor use, health management, Thailand

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Authors: Salami Akeem Olanrewaju

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The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: Maria Consuelo Doble

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For decades, basic public education in the Philippines has been beleaguered by a governance scenario of multi-layered decision-making and the lack of collaboration between sectors in addressing issues on poor access to schools, high dropout rates, low survival rates, and poor student performance. These chronic problems persisted despite multiple efforts making it appear that the education system is incapable of reforming itself. In the mountainous rural towns of La Trinidad and Tuba, in the province of Benguet in Northern Philippines, collaborative education governance was catalyzed by the intervention of Synergeia Foundation, a coalition made up of individuals, institutions and organizations that aim to improve the quality of education in the Philippines. Its major thrust is to empower the major stakeholders at the community level to make education work by building the capacities of School Governing Councils (SGCs). Although mandated by the Department of Education in 2006, the SGCs in Philippine public elementary schools remained dysfunctional. After one year of capacity-building by Synergeia Foundation, some SGCs are already exhibiting active community-based multi-sectoral collaboration, while there are many that are not. With the myriad of factors hindering collaboration, Synergeia Foundation is now confronted with the pressing question: What are the factors that promote collaborative governance in the SGCs so that they can address the education-related issues that they are facing? Using Emerson’s (2011) framework on collaborative governance, this study analyzes the application of collaborative governance by highly-functioning SGCs in the public elementary schools of Tuba and La Trinidad. Findings of this action research indicate how the dynamics of collaboration composed of three interactive and iterative components – principled engagement, shared motivation and capacity for joint action – have resulted in meaningful short-term impact such as stakeholder engagement and decreased a number of dropouts. The change in the behavior of stakeholders is indicative of adaptation to a more collaborative approach in governing education in Benguet highland settings such as Tuba and La Trinidad.

Keywords: basic public education, Benguet highlands, collaborative governance, School Governing Council

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Authors: Chattrarat Hotrawaisaya

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This research aims to formulate the logistics collaborative model which is the management tool for orchid flower exporter. The researchers study logistics activities in orchid supply chain that stakeholders can collaborate and develop, including demand forecasting, inventory management, warehouse and storage, order-processing, and transportation management. The research also explores logistics collaboration implementation into orchid’s stakeholders. The researcher collected data before implementation and after model implementation. Consequently, the costs and efficiency were calculated and compared between pre and post period of implementation. The research found that the results of applying the logistics collaborative model to orchid exporter reduces inventory cost and transport cost. The model also improves forecasting accuracy, and synchronizes supply chain of exporter. This research paper contributes the uniqueness logistics collaborative model which value to orchid industry in Thailand. The orchid exporters may use this model as their management tool which aims in competitive advantage.

Keywords: logistics, orchid, supply chain, collaboration

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Authors: Irina Maria Artinescu, Costin Radu Boldea, Eduard-Ionut Matei

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The paper is a comparative study of two classical variants of parallel projection methods for solving the convex feasibility problem with their equivalents that involve variable weights in the construction of the solutions. We used a graphical representation of these methods for inpainting a convex area of an image in order to investigate their effectiveness in image reconstruction applications. We also presented a numerical analysis of the convergence of these four algorithms in terms of the average number of steps and execution time in classical CPU and, alternatively, in parallel GPU implementation.

Keywords: convex feasibility problem, convergence analysis, inpainting, parallel projection methods

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Authors: C. W. F. Che Wan Putra, M. Alshawi, M. S. Al Ahbabi, M. Jabakhanji

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Much of the waste that is generated throughout the life-cycle of a building is mainly related to project stakeholders not having access to information that others have created. This results in waste and high costs. Over the past decade, however, the industry reacted to these challenges by adopting effective procurement approaches, such as partnering and design and build, to improve collaboration and communication among projects’ stakeholders. Most recently, there is a focus on creating and reusing digital project information of stakeholders throughout the life-cycle to facilitate the exchange of information among partners. This shift is based around BIM (Building Information Modelling) and collaborative environment (IPD). The power of collaborative BIM goes beyond improving efficiency. Sustainability, perhaps the most important challenge for the design and construction community, is at the intersection of BIM and collaborative project delivery, drawing strength from both. Due to these benefits, a research study has been carried out to investigate the need of BIM and IPD, on a large scale construction project which is procured on a traditional approach, i.e. design-bid-build. A qualitative research work including a semi-structured interview with project partners was conducted on a typical project in the UAE, whereby the selected project suffered from severe delays and cost overrun. This paper aims to bring about clear evidence to what most likely to happen to a typical construction project in spite of employing very good consultants, project manager and contractors and how these problems could have been avoided if BIM and IPD were deployed.

Keywords: building information modelling (BIM), integrated project delivery (IPD), collaborative environment, case study

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Authors: Alexander P. Smirnov, Sergey A. Matveev, Dmitry A. Zheltkov, Eugene E. Tyrtyshnikov

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We propose a new computational technique for multidimensional (multicomponent) Smoluchowski coagulation equation. Using low-rank approximations in Tensor Train format of both the solution and the coagulation kernel, we accelerate the classical finite-difference Runge-Kutta scheme keeping its level of accuracy. The complexity of the taken finite-difference scheme is reduced from O(N^2d) to O(d^2 N log N ), where N is the number of grid nodes and d is a dimensionality of the problem. The efficiency and the accuracy of the new method are demonstrated on concrete problem with known analytical solution.

Keywords: tensor train decomposition, multicomponent Smoluchowski equation, runge-kutta scheme, convolution

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Thendo Mafame

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There is a need for academic research to focus on solving or contributing to solving real-world societal problems. Transdisciplinary research (TDR) provides a way to produce functional and applicable research findings, which can be used to advance developmental causes. This TDR study explores ways in which South Africa’s spatial divide, entrenched through decades of discriminatory planning policies, can be restructured to bring about equitable access to places of employment, business, leisure, and service for previously marginalised South Africans. It does by exploring the potential of the transit-orientated development (TOD) model to restructure and revitalise urban spaces in a collaborative model. The study focuses, through a case study, on the Du Toit station precinct in the town of Stellenbosch, on the peri-urban edge of the city of Cape Town, South Africa. The TOD model is increasingly viewed as an effective strategy for creating sustainable urban redevelopment initiatives, and it has been deployed successfully in other parts of the world. The model, which emphasises development density, diversity of land-use and infrastructure and transformative design, is customisable to a variety of country contexts. This study made use of case study approach with mixed methods to collect and analyse data. Various research methods used include the above-mentioned focus group discussions and interviews, as well as observation, transect walks This research contributes to the professional development of TDR studies that are focused on urbanisation issues.

Keywords: case study, integrated urban development, land-use, stakeholder collaboration, transit-oriented development, transdisciplinary research

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Authors: Juanita Morris

Abstract:

The purpose of this study will examine the mediating relationships between the theories of intelligence, mathematics anxiety, gender stereotype threat, meta-cognition and math performance through the use of eye tracking technology, affecting student perception and problem-solving abilities. The participants will consist of (N=80) female graduate students. Test administered were the Abbreviated Math Anxiety Scale, Tobii Eye Tracking software, gender stereotype threat through Google images, and they will be asked to describe their problem-solving approach allowed to measure metacognition. Participants will be administered mathematics problems while having gender stereotype threat shown to them through online images while being directed to look at the eye tracking software Tobii. We will explore this by asking ‘Is mathematics anxiety associated with the theories of intelligence and gender stereotype threat and how does metacognition and math performance place a role in mediating those perspectives?’. It is hypothesized that math-anxious students are more likely affected by the gender stereotype threat and that may play a role in their performance? Furthermore, we also want to explore whether math anxious students are more likely to be an entity theorist than incremental theorist and whether those who are math anxious will be more likely to be fixated on variables associated with coefficients? Path analysis and independent samples t-test will be used to generate results for this study. We hope to conclude that both the theories of intelligence and metacognition mediate the relationship between mathematics anxiety and gender stereotype threat.

Keywords: math anxiety, emotions, affective domains fo learning, cognitive underlinings

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Authors: Hamioud Saida, Khalfallah Salah

Abstract:

In this study, a spectral element method is employed to predict the free vibration of a Euler-Bernoulli beam resting on a Winkler foundation with elastically restrained ends. The formulation of the dynamic stiffness matrix has been established by solving the differential equation of motion, which was transformed to frequency domain. Non-dimensional natural frequencies and shape modes are obtained by solving the partial differential equations, numerically. Numerical comparisons and examples are performed to show the effectiveness of the SEM and to investigate the effects of various parameters, such as the springs at the boundaries and the elastic foundation parameter on the vibration frequencies. The obtained results demonstrate that the present method can also be applied to solve the more general problem of the dynamic analysis of structures with higher order precision.

Keywords: elastically supported Euler-Bernoulli beam, free-vibration, spectral element method, Winkler foundation

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Authors: Eva Nolan, Timothy Mcnichols

Abstract:

Gamers spend over 3 billion hours collectively playing video games a week, which is arguably not nearly enough time to indulge in the many benefits gaming has to offer. Much of the previous research on video gaming is centered on the effects of playing violent video games and the negative impacts they have on the individual. However, there is a dearth of research in the area of non-violent video games, specifically the emotional and cognitive benefits playing non-violent games can offer individuals. Current research in the area of video game play suggests there are many benefits to playing for an individual, such as decreasing symptoms of depression, decreasing stress, increasing positive emotions, inducing relaxation, decreasing anxiety, and particularly improving mood. One suggestion as to why video games may offer such benefits is that they possess ideal characteristics to create and maintain flow experiences, which in turn, is the subjective experience where an individual obtains a heightened and improved state of mind while they are engaged in a task where a balance of challenge and skill is found. Many video games offer a platform for collaborative gameplay, which can enhance the emotional experience of gaming through the feeling of social support and social inclusion. The present study was designed to examine the effects of collaborative gameplay and flow experience on participants’ perceived mood. To investigate this phenomenon, an in-between subjects design involving forty participants were randomly divided into two groups where they engaged in solo or collaborative gameplay. Each group represented an even number of frequent gamers and non-frequent gamers. Each participant played ‘The Lego Movie Videogame’ on the Playstation 4 console. The participant’s levels of flow experience and perceived mood were measured by the Flow State Scale (FSS) and the Positive and Negative Affect Schedule (PANAS). The following research hypotheses were investigated: (i.) participants in the collaborative gameplay condition will experience higher levels of flow experience and higher levels of mood than those in the solo gameplay condition; (ii.) participants who are frequent gamers will experience higher levels of flow experience and higher levels of mood than non-frequent gamers; and (iii.) there will be a significant positive relationship between flow experience and mood. If the estimated findings are supported, this suggests that engaging in collaborative gameplay can be beneficial for an individual’s mood and that experiencing a state of flow can also enhance an individual’s mood. Hence, collaborative gaming can be beneficial to promote positive emotions (higher levels of mood) through engaging an individual’s flow state.

Keywords: collaborative gameplay, flow experience, mood, games, positive emotions

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Authors: Majid Khalili

Abstract:

This paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective variable neighborhood algorithm (MOVNS). A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The algorithm is carefully evaluated for its performance against available algorithm by means of multi-objective performance measures and statistical tools. The related results show that a variant of our proposed MOVNS provides sound performance comparing with other algorithms.

Keywords: no-wait hybrid flowshop scheduling; multi-objective variable neighborhood algorithm; makespan; total weighted tardiness

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Authors: Craig A. Kaplan

Abstract:

If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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Authors: Bagireanu Astrid, Bros-Williamson Julio, Duncheva Mila, Currie John

Abstract:

The Architecture, Engineering, and Construction (AEC) sector plays a critical role in the global transition toward sustainable and net-zero built environments. However, the industry faces unique challenges in planning for net-zero while struggling with low productivity, cost overruns and overall resistance to change. Traditional practices fall short due to their inability to meet the requirements for systemic change, especially as governments increasingly demand transformative approaches. Working in silos and rigid hierarchies and a short-term, client-centric approach prioritising immediate gains over long-term benefit stands in stark contrast to the fundamental requirements for the realisation of net-zero objectives. These practices have limited capacity to effectively integrate AEC stakeholders and promote the essential knowledge sharing required to address the multifaceted challenges of achieving net-zero. In the context of built environment, procurement may be described as the method by which a project proceeds from inception to completion. Collaborative procurement methods under the Integrated Practices (IP) umbrella have the potential to align more closely with net-zero objectives. This paper explores the synergies between collaborative procurement principles and the pursuit of net zero in the AEC sector, drawing upon the shared values of cross-disciplinary collaboration, Early Supply Chain involvement (ESI), use of standards and frameworks, digital information management, strategic performance measurement, integrated decision-making principles and contractual alliancing. To investigate the role of collaborative procurement in advancing net-zero objectives, a structured research methodology was employed. First, the study focuses on a systematic review on the application of collaborative procurement principles in the AEC sphere. Next, a comprehensive analysis is conducted to identify common clusters of these principles across multiple procurement methods. An evaluative comparison between traditional procurement methods and collaborative procurement for achieving net-zero objectives is presented. Then, the study identifies the intersection between collaborative procurement principles and the net-zero requirements. Lastly, an exploration of key insights for AEC stakeholders focusing on the implications and practical applications of these findings is made. Directions for future development of this research are recommended. Adopting collaborative procurement principles can serve as a strategic framework for guiding the AEC sector towards realising net-zero. Synergising these approaches overcomes fragmentation, fosters knowledge sharing, and establishes a net-zero-centered ecosystem. In the context of the ongoing efforts to amplify project efficiency within the built environment, a critical realisation of their central role becomes imperative for AEC stakeholders. When effectively leveraged, collaborative procurement emerges as a powerful tool to surmount existing challenges in attaining net-zero objectives.

Keywords: collaborative procurement, net-zero, knowledge sharing, architecture, built environment

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