Search results for: problem solving skill

Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks

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Authors: Young Hee Geum

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In this paper, we present the iterative method and determine the control parameters to converge cubically for solving nonlinear equations. In addition, we derive the asymptotic error constant.

Keywords: asymptotic error constant, iterative method, multiple root, root-finding, order of convergent

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Authors: Helen Frialde-Dupale

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Critical thinking Index (CTI) of 150 third year college students from five State Colleges and Universities (SUCs) in Region I were determined. Only students with Grade Point Average (GPA) of at least 2.0 from four general classification of degree courses, namely: Education, Arts and Sciences, Engineering and Agriculture were included. Specific problem No.1 dealt with the profile variables, namely: age, sex, degree course, monthly family income, number of siblings, high school graduated from, grade point average, personality type, highest educational attainment of parents, and occupation of parents. Problem No. 2 determined the critical thinking index among the respondents. Problem No. 3 investigated whether or not there are significant differences in the critical thinking index among the respondents across the profile variables. While problem No.4 determined whether or not there are significant relationship between the critical thinking index and selected profile variables, namely: age, monthly family income, number of siblings, and grade point average of the respondents. Finally, on problem No. 5, the critical thinking instrument which obtained the lowest rates, were used as basis for outlining an intervention program for enhancing critical thinking index (CTI) of students. The following null hypotheses were tested at 0.05 level of significance: there are no significant differences in the critical thinking index of the third college students across the profile variables; there are no significant relationships between the critical thinking index of the respondents and selected variables, namely: age, monthly family income, number of siblings, and grade point average.

Keywords: attitude as critical thinker, critical thinking applied, critical thinking index, self-perception as critical thinker

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Authors: François Chiocchio, Mahshid Gharibpour

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Regardless of the extent to which succession management is implemented in the private sector, it is still overlooked in the public sector. Traditional succession management is evolving providing a better alignment between business strategies and HR strategies. Succession management brings sustainable effectiveness for succession programs through career path development, knowledge and skill transfer, job retention, as well as high-potential candidates’ empowerment for upcoming vacancies. By way of a systematic literature review, we bring into focus strategic succession management in public organizations and discuss best ways of implementation. 

Keywords: succession management, strategic succession management, public organization, succession management model

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Authors: Ahmad Haidar

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Modern economic systems are characterized by growing complexity, and addressing their challenges requires innovative approaches. This study examines the implications of artificial intelligence (AI) on unemployment in Europe from a macroeconomic perspective, employing data modeling techniques to understand the relationship between AI integration and labor market dynamics. To understand the AI-unemployment nexus comprehensively, this research considers factors such as sector-specific AI adoption, skill requirements, workforce demographics, and geographical disparities. The study utilizes a panel data model, incorporating data from European countries over the last two decades, to explore the potential short-term and long-term effects of AI implementation on unemployment rates. In addition to investigating the direct impact of AI on unemployment, the study also delves into the potential indirect effects and spillover consequences. It considers how AI-driven productivity improvements and cost reductions might influence economic growth and, in turn, labor market outcomes. Furthermore, it assesses the potential for AI-induced changes in industrial structures to affect job displacement and creation. The research also highlights the importance of policy responses in mitigating potential negative consequences of AI adoption on unemployment. It emphasizes the need for targeted interventions such as skill development programs, labor market regulations, and social safety nets to enable a smooth transition for workers affected by AI-related job displacement. Additionally, the study explores the potential role of AI in informing and transforming policy-making to ensure more effective and agile responses to labor market challenges. In conclusion, this study provides a comprehensive analysis of the macroeconomic implications of AI on unemployment in Europe, highlighting the importance of understanding the nuanced relationships between AI adoption, economic growth, and labor market outcomes. By shedding light on these relationships, the study contributes valuable insights for policymakers, educators, and researchers, enabling them to make informed decisions in navigating the complex landscape of AI-driven economic transformation.

Keywords: artificial intelligence, unemployment, macroeconomic analysis, european labor market

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Authors: Mei-Ying Liao, Lee-Ching Wei, Jung-Hsiang Tseng

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The main purpose of this study was to explore the process of planning and execution of the music learning center in preschool. This study was conducted through a collaborative action research method. The research members included a university music professor, a teaching guide, a preschool director, and a preschool teacher, leading a class of 5-6-year-old children to participate in this study. Five teaching cycles were performed with a subject of bird. In the whole process that lasted three months, the research members would maintain the conversation, reflection, and revision repeatedly. A triangular validated method was used to collect data, including archives, interviews, seminars, observations, journals, and learning evaluations to improve research on the validity and reliability. It was found that a successful music learning center required comprehensive planning and execution. It is also important to develop good listening, singing, respect, and homing habits at the beginning of running the music learning center. By timely providing diverse musical instruments, learning materials, and activities according to the teaching goals, children’s desire to learning was highly stimulated. Besides, peer interactions improved their ensemble and problem-solving abilities. The collaborative action research enhanced the preschool teacher’s confidence and promoted professional growth of the research members.

Keywords: collaborative action research, case study, music learning center, music development

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Authors: Abir Derouiche, Abdesslem Layeb

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Association Rule Mining (ARM) is one of the most popular data mining tasks and it is widely used in various areas. The search for association rules is an NP-complete problem that is why metaheuristics have been widely used to solve it. The present paper presents the ARM as an optimization problem and surveys the proposed approaches in the literature based on metaheuristics.

Keywords: Optimization, Metaheuristics, Data Mining, Association rules Mining

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Authors: Zeynep Aykul Yavuz

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Misconception about design is about making a product pretty. However, the holistic approaches such as design thinking or human-centered design could take the design from making things nice to things inspired by real people and work with real-world limitations. Design thinking helps companies to understand not only problem area but also opportunities. It can be used by any people from any background which provide a space for companies where employees from different departments work together to solve the same problem. While demanding skills changing year to year into the market, previous technical skills are commons anymore. The frontier companies in the sectors look for interactive methods to solve problems. Moreover, the recruiter aims to understand the candidate’s design thinking skills (. The study includes a case study where a 21st century creative services company “ATÖLYE” offers innovation transformation with design thinking to a banking company. Both companies are located in İstanbul in Turkey. The banking company contacted with the ATÖLYE in January 2018 because they heard design thinking in different markets and how it transformed the way of working. The transformation process had 3 phases which were basic training of teams while getting coaching from ATÖLYE’s employees, coaching training with graduates of basic training, facilitator training. Employees built new skills while solving the banking company’s strategic problems. ATÖLYE offered experiential learning which helped employees’ making sense of new skills and knowledge. One day workshops were organized to create awareness about the practice of design thinking. In addition to these, a community of practice was built to create an environment to make reflections and discuss good practice. Not only graduates from the training program but also other employees from the company participated in the community gatherings. ATÖLYE did not train some employees in the company. Rather than that, its aim was to build a contemporary organization for the company. This provided a sustainable system in terms of human resources and motivation. At the beginning of 2020, employees from the first cohort in the basic training who took coaching training and facilitator training have started to design training for different groups in the company. They have considered what could be better in their training experience and designed new ones according to that, so they have been using design thinking to design the design training. This is one of the outcomes which shows the impact of all process clearly.

Keywords: design thinking, learning community, professional development, training, organizational transformation

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Authors: Yaser E. Greish, Emad F. Hindawy, Maryam S. Al Nehayan

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Introductory courses such as General Chemistry I, General Physics I and General Biology need special attention as students taking these courses are usually at their first year of the university. In addition to the language barrier for most of them, they also face other difficulties if these elementary courses are taught in the traditional way. Changing the routine method of teaching of these courses is therefore mandated. In this regard, podcasting of chemistry lectures was used as an add-on to the traditional and non-traditional methods of teaching chemistry to science and non-science students. Podcasts refer to video files that are distributed in a digital format through the Internet using personal computers or mobile devices. Pedagogical strategy is another way of identifying podcasts. Three distinct teaching approaches are evident in the current literature and include receptive viewing, problem-solving, and created video podcasts. The digital format and dispensing of video podcasts have stabilized over the past eight years, the type of podcasts vary considerably according to their purpose, degree of segmentation, pedagogical strategy, and academic focus. In this regard, the whole syllabus of 'General Chemistry I' course was developed as podcasts and were delivered to students throughout the semester. Students used the podcasted files extensively during their studies, especially as part of their preparations for exams. Feedback of students strongly supported the idea of using podcasting as it reflected its effect on the overall understanding of the subject, and a consequent improvement of their grades.

Keywords: podcasting, introductory course, interactivity, flipped classroom

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Authors: Charles Rutikanga

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As part of the effort to reconstruct Rwanda and foster a shared national identity after the 1994 genocide against Tutsi, the government of Rwanda has drawn on aspects of indigenous culture and traditional practices. One of these traditional practices and cultural values is Ubudehe, which has been re-introduced after it has been gradually lost since colonial times. It is a form of collective action at the village level, which is inclusive, covering men, women, and the most marginalized community members. The philosophy behind Ubudehe is to increase the level of participation and institutional problem-solving capacity at the local level by citizens and local government. Since the early 2000s, the government re-introduced Ubudehe as a neo-traditional cultural institution in order to support the implementation of the country’s poverty reduction and development programs. An empirical study on indigenous and innovative models of social work practice was conducted under the framework of the ‘Professional Social Work in East Africa’ (PROSOWO II) project. Field data were collected on traditional/indigenous approaches, including Ubudehe, from different categories of informants through focus group discussions (FGDs) and personal interviews. The research showed that professional social workers play a significant role in the whole Ubudehe process. While there have been some challenges in the administration and implementation, overall it has contributed to poverty reduction in a post-genocide Rwanda.

Keywords: development, indigenous approach, social work, Ubudehe

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Authors: Sibusiso Mnyanda

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Storytelling through motion pictures is a valuable economy. South Africa was one of the first countries in the world to see and hear sound motion pictures With Lingards Waxworks in Durban first showing them in August 1895. This article celebrates and takes a microscopic look into the developments of this industry and its economy, highlighting these fundamentals: Skill levels and talent sets that were displayed in this emergence, the quality of the products that were produced by filmmakers and actors, the level of Administration and quality assurance of production houses and the general infrastructure and resources available to the industry at the time.

Keywords: film, Africa, production economy, history

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Authors: Kwan Hee Han

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In today’s business environments, frequent change of customer requirements is a tough challenge to manufacturing company. To cope with these challenges, a production planning and scheduling (PP&S) function might be established to provide accountability for both customer service and operational efficiency. Nowadays, many manufacturing firms have utilized PP&S software solutions to generate a realistic production plan and schedule to adapt to external changes efficiently. However, companies which consider the introduction of PP&S software solution, still have difficulties for selecting adequate solution to meet their specific needs. Since the task of PP&S is the one of major building blocks of SCM (Supply Chain Management) architecture, which deals with short term decision making in the production process of SCM, it is needed that the functionalities of PP&S should be analysed within the whole SCM process. The aim of this paper is to analyse the PP&S functionalities and its system architecture from the SCM perspective by using the criteria of level of planning hierarchy, major 4 SCM processes and problem-solving approaches, and finally propose a classification framework of PP&S solutions to facilitate the comparison among various commercial software solutions. By using proposed framework, several major PP&S solutions are classified and positioned according to their functional characteristics in this paper. By using this framework, practitioners who consider the introduction of computerized PP&S solutions in manufacturing firms can prepare evaluation and benchmarking sheets for selecting the most suitable solution with ease and in less time.

Keywords: production planning, production scheduling, supply chain management, the advanced planning system

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Authors: Ming Liu, Zhihui Sun, Xiaoning Zhang

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This paper studies a deterministic container transportation problem, jointly optimizing the berth allocation, quay crane assignment and yard storage allocation at container ports. The problem is formulated as an integer program to coordinate the decisions. Because of the large scale, it is then transformed into a set partitioning formulation, and a framework of branchand- price algorithm is provided to solve it.

Keywords: branch-and-price, container terminal, joint scheduling, maritime logistics

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Authors: Harun Aydilek, Asiye Aydilek, Ali Allahverdi

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Our objective is to minimize the total tardiness in an m-machine two-stage assembly flowshop scheduling problem. The objective is an important performance measure because of the fact that the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. In the literature, the problem is considered with zero setup times which may not be realistic and appropriate for some scheduling environments. Considering separate setup times from processing times increases machine utilization by decreasing the idle time and reduces total tardiness. We propose two new algorithms and adapt four existing algorithms in the literature which are different versions of simulated annealing and genetic algorithms. Moreover, a dominance relation is developed based on the mathematical formulation of the problem. The developed dominance relation is incorporated in our proposed algorithms. Computational experiments are conducted to investigate the performance of the newly proposed algorithms. We find that one of the proposed algorithms performs significantly better than the others, i.e., the error of the best algorithm is less than those of the other algorithms by minimum 50%. The newly proposed algorithm is also efficient for the case of zero setup times and performs better than the best existing algorithm in the literature.

Keywords: algorithm, assembly flowshop, scheduling, simulation, total tardiness

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Authors: Ehsan Yadegari

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While there are several metaheuristics and exact approaches to solving the Supply Chain Network Design (SCND) problem, there still remains an unfilled gap in using the Teaching-Learning-Based Optimization (TLBO) algorithm. The algorithm has demonstrated desirable results with problems with complicated combinational optimization. The present study introduces a Discrete Self-Study TLBO (DSS-TLBO) with priority-based solution representation that can solve a supply chain network configuration model to lower the total expenses of establishing facilities and the flow of materials. The network features four layers, namely suppliers, plants, distribution centers (DCs), and customer zones. It is designed to meet the customer’s demand through transporting the material between layers of network and providing facilities in the best economic Potential locations. To have a higher quality of the solution and increase the speed of TLBO, a distinct operator was introduced that ensures self-adaptation (self-study) in the algorithm based on the four types of local search. In addition, while TLBO is used in continuous solution representation and priority-based solution representation is discrete, a few modifications were added to the algorithm to remove the solutions that are infeasible. As shown by the results of experiments, the superiority of DSS-TLBO compared to pure TLBO, genetic algorithm (GA) and firefly Algorithm (FA) was established.

Keywords: supply chain network design, teaching–learning-based optimization, improved metaheuristics, discrete solution representation

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Authors: M. F. F. Ab Rashid, A. N. Mohd Rose, N. M. Z. Nik Mohamed, W. S. Wan Harun, S. A. Che Ghani

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Traveling salesman problem with precedence constraint (TSPPC) is one of the most complex problems in combinatorial optimization. The existing algorithms to solve TSPPC cost large computational time to find the optimal solution. The purpose of this paper is to present an efficient genetic algorithm that guarantees optimal solution with less number of generations and iterations time. Unlike the existing algorithm that generates priority factor as chromosome, the proposed algorithm directly generates sequence of solution as chromosome. As a result, the proposed algorithm is capable of generating optimal solution with smaller number of generations and iteration time compare to existing algorithm.

Keywords: traveling salesman problem, sequencing, genetic algorithm, precedence constraint

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Authors: Y. Wang

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The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CN_maxn²) where C is the iterations, N_max is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.

Keywords: frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: C. Park, H. Lee, Y-J. Lee

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Aim: This study aims to present the Sustainability Innovation Capacity Building Framework (SICBF) to enable the wider public to achieve UN Sustainable Development Goals (UN SDGs) for a sustainable future. The intrinsically interwoven nature of sustainability requires systematic approaches to attain. However, there is a lack of an effective framework for capacity building that enables a systematic implementation approach for UN SDGs. The SICBF illustrates the six core components and their dynamics: 1. Momentum creation; 2. Exposure to diverse worldviews; 3. Serendipity/Eureka moment; 4. Creative problem solving; 5. Individual empowerment; 6. Systems thinking. Method: First, a structured literature review was used to synthesise existing sustainability competencies studies and generic innovation competencies. Secondly, the conceptual framework based on literature findings was tested with the participants' survey and interview data collected from four sets of MAKEathon events. The interview analysis and event observation data were used to further refine and validate the conceptual framework. Contributions: The scientific contribution of this study is to pave the way for SDGs specific capacity building framework that caters to the need for systematic approaches to allow the wider public aspiring to tackle the seemingly intractable sustainable development goals. The framework will aid sustainable development academics, educators, and practitioners in understanding the dynamics of how capacity building can be facilitated.

Keywords: capacity building, sustainability innovation, sustainable development, systems thinking, UN SDGs

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Authors: Mohammed Makki, Milad Showkatbakhsh, Aiman Tabony

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Computational applications of natural evolutionary processes as problem-solving tools have been well established since the mid-20th century. However, their application within architecture and design has only gained ground in recent years, with an increasing number of academics and professionals in the field electing to utilize evolutionary computation to address problems comprised from multiple conflicting objectives with no clear optimal solution. Recent advances in computer science and its consequent constructive influence on the architectural discourse has led to the emergence of multiple algorithmic processes capable of simulating the evolutionary process in nature within an efficient timescale. Many of the developed processes of generating a population of candidate solutions to a design problem through an evolutionary based stochastic search process are often driven through the application of both environmental and architectural parameters. These methods allow for conflicting objectives to be simultaneously, independently, and objectively optimized. This is an essential approach in design problems with a final product that must address the demand of a multitude of individuals with various requirements. However, one of the main challenges encountered through the application of an evolutionary process as a design tool is the ability for the simulation to maintain variation amongst design solutions in the population while simultaneously increasing in fitness. This is most commonly known as the ‘golden rule’ of balancing exploration and exploitation over time; the difficulty of achieving this balance in the simulation is due to the tendency of either variation or optimization being favored as the simulation progresses. In such cases, the generated population of candidate solutions has either optimized very early in the simulation, or has continued to maintain high levels of variation to which an optimal set could not be discerned; thus, providing the user with a solution set that has not evolved efficiently to the objectives outlined in the problem at hand. As such, the experiments presented in this paper seek to achieve the ‘golden rule’ by incorporating a mathematical fitness criterion for the development of an urban tissue comprised from the superblock as its primary architectural element. The mathematical value investigated in the experiments is the standard deviation factor. Traditionally, the standard deviation factor has been used as an analytical value rather than a generative one, conventionally used to measure the distribution of variation within a population by calculating the degree by which the majority of the population deviates from the mean. A higher standard deviation value delineates a higher number of the population is clustered around the mean and thus limited variation within the population, while a lower standard deviation value is due to greater variation within the population and a lack of convergence towards an optimal solution. The results presented will aim to clarify the extent to which the utilization of the standard deviation factor as a fitness criterion can be advantageous to generating fitter individuals in a more efficient timeframe when compared to conventional simulations that only incorporate architectural and environmental parameters.

Keywords: architecture, computation, evolution, standard deviation, urban

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Authors: Sanchai Ratthanakwan

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This research aims to study situations and characteristics of the problems facing the urban poor. The data and information are collected by focus group and in-depth interview leader and members of Four Regions Slum Network, community representatives and the social welfare officer. The research can be concluded that the problems of the urban poor faced with three major problems: Firstly, the shortage of housing and stability issues in housing; secondly, the problem of substandard quality of life; and thirdly, the debt problem. The study found that a solution will be found in two ways: First way is the creation of housing for the urban poor in slums or community intrusion by the state. Second way is the stability in the housing and subsistence provided by the community center called “housing stability”.

Keywords: urban poor, social welfare, Bangkok metropolis, housing stability

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Authors: Wajahat Ali, Shakeel Javaid

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In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

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Authors: Radah Yousuf, Ashraf Shebl

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Suicide is a tragic event with strong emotional repercussions for its survivors and for families of its victims. There were thousands of cases all over the world. There are many risk factors include mental disorders such as depression, and substance abuse, including alcoholism and use of benzodiazepines. Other suicides are impulsive acts due to stress such as from financial difficulties, troubles with relationships, or from bullying. The aim of work in this study is making a survey from archives of the suicidal cases, which had a medicolegal examination, in forensic medicine center in Al Madinah Almunawarah-KSA, for ten years in the period between 1428-1438h. In each case, some data are collected such as age, sex, time and place of an act, method of suicide, the presence of the witness, medical history. This study demonstrates that suicide is more common in male than female, and the 4th decade was the most period of age. The most common method of suicide was hanging followed by falling from the height. These results indicated that cultural and religious beliefs that discourage suicide and support self-preservation instinct, and suicide education programs provide information to students in high school, builds awareness, one of the most important issues in solving that problem. From the forensic view, circumstantial evidence of every forensic case must take and record, full history about the social, medical and psychological problems, attend the scene of death is a very important, complete medicolegal investigation for every case, and full autopsy with very skilled techniques and facilities can help in diagnosing what type of crimes.

Keywords: suicide, age, sex, hanging

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Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

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Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: identification, Hammerstein-Wiener, optimization, quantization

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Authors: Serhat Tüzün, Tufan Demirel

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The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

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Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

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The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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Authors: Hamad Alhamad, Catriona Khamisha, Emma Green, Yvonne Robb

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Introduction: Practice education is a key component of occupational therapy education. This critical review aimed to explore students’ and clinical supervisors’ experiences of practice education, and to make recommendations for research. Method: The literature was systematically searched using five databases. Qualitative, quantitative and mixed methods studies were included. Critical Appraisal Skills Programme checklist for qualitative studies and Mixed Methods Assessment Tool for quantitative and mixed methods studies were used to assess study quality. Findings: Twenty-two studies with high quality scores were included: 16 qualitative, 3 quantitative and 3 mixed methods. Studies were conducted in Australia, Canada, USA and UK. During practice education, students learned professional skills, practical skills, clinical skills and problem-solving skills, and improved confidence and creativity. Supervisors had an opportunity to reflect on their practice and get experience of supervising students. However, clear objectives and expectations for students, and sufficient theoretical knowledge, preparation and resources for supervisors were required. Conclusion: Practice education provides different skills and experiences, necessary to become competent professionals; but some areas of practice education need to improve. Studies in non-western countries are needed to explore the perspectives of students and clinical supervisors in different cultures, to ensure the practice education models adopted are relevant.

Keywords: occupational therapy, practice education, fieldwork, students, clinical supervisors

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Authors: Doris Lacej, Eni Bushi

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Cleaning and disinfection procedures are essential for maintaining the cleanliness status of the pharmaceutical manufacturing environment particularly of the cleanrooms and sterile unit area. The Good Manufacturing Practice (GMP) Annex 1 recommendation highly requires the implementation of the standard and validated cleaning and disinfection protocols. However, environmental monitoring has shown that even a validated cleaning method with certified agents may result in the presence of atypical microorganisms’ colony that exceeds GMP limits for a specific cleanroom area. In response to this issue, this case study aims to arrive at the root cause of the microbial contamination observed in the sterile production environment in Profarma pharmaceutical industry in Albania through applying a problem-solving practical approach that ensures the appropriate sterility grade. The guidelines and literature emphasize the importance of several factors in the prevention of possible microbial contamination occurring in cleanrooms, grade A and C. These factors are integrated into a practical framework, to identify the root cause of the presence of Aspergillus Niger colony in the sterile production environment in Profarma pharmaceutical industry in Albania. In addition, the application of a semi-automatic disinfecting system such as H2O2 FOG into sterile grade A and grade C cleanrooms has been an effective solution in eliminating the atypical colony of Aspergillus Niger. Selecting the appropriate detergents and disinfectants at the right concentration, frequency, and combination; the presence of updated and standardized guidelines for cleaning and disinfection as well as continuous training of operators on these practices in accordance with the updated GMP guidelines are some of the identified factors that influence the success of achieving sterility grade. However, to ensure environmental sustainability it is important to be prepared for identifying the source of contamination and making the appropriate decision. The proposed case-based practical approach may help pharmaceutical companies to achieve sterile production and cleanliness environmental sustainability in challenging situations. Apart from the integration of valid agents and standardized cleaning and disinfection protocols according to GMP Annex 1, pharmaceutical companies must be careful and investigate the source and all the steps that can influence the results of an abnormal situation. Subsequently apart from identifying the root cause it is important to solve the problem with a successful alternative approach.

Keywords: cleanrooms, disinfectants, environmental monitoring, GMP Annex 1

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Authors: Reza Mohammadzadeh

Abstract:

The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Blair D. Macdonald

Abstract:

After nearly one hundred years of its origin, foundational quantum mechanics remains one of the greatest unexplained mysteries in physicists today. Within this time, chaos theory and its geometry, the fractal, has developed. In this paper, the propagation behaviour with an iteration of a simple fractal, the Koch Snowflake, was described and analysed. From an arbitrary observation point within the fractal set, the fractal propagates forward by oscillation—the focus of this study and retrospectively behind by exponential growth from a point beginning. It propagates a potentially infinite exponential oscillating sinusoidal wave of discrete triangle bits sharing many characteristics of light and quantum entities. The model's wave speed is potentially constant, offering insights into the perception and a direction of time where, to an observer, when travelling at the frontier of propagation, time may slow to a stop. In isolation, the fractal is a superposition of component bits where position and scale present a problem of location. In reality, this problem is experienced within fractal landscapes or fields where 'position' is only 'known' by the addition of information or markers. The quantum' measurement problem', 'uncertainty principle,' 'entanglement,' and the classical-quantum interface are addressed; these are a problem of scale invariance associated with isolated fractality. Dual forward and retrospective perspectives of the fractal model offer the opportunity for unification between quantum mechanics and cosmological mathematics, observations, and conjectures. Quantum and cosmological problems may be different aspects of the one fractal geometry.

Keywords: measurement problem, observer, entanglement, unification

Procedia PDF Downloads 90