Search results for: stepwise development approach

Authors: Shazalina Mat Zin, Ahmad Abd. Majid, Ahmad Izani Md. Ismail, Muhammad Abbas

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The generalized wave equation models various problems in sciences and engineering. In this paper, a new three-time level implicit approach based on cubic trigonometric B-spline for the approximate solution of wave equation is developed. The usual finite difference approach is used to discretize the time derivative while cubic trigonometric B-spline is applied as an interpolating function in the space dimension. Von Neumann stability analysis is used to analyze the proposed method. Two problems are discussed to exhibit the feasibility and capability of the method. The absolute errors and maximum error are computed to assess the performance of the proposed method. The results were found to be in good agreement with known solutions and with existing schemes in literature.

Keywords: collocation method, cubic trigonometric B-spline, finite difference, wave equation

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Authors: Luciana Abednego, Cecilia Nugraheni

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There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Ephraim Daka, Maxim Kotsemir

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The National system Innovation (NSI) have recently proliferated as a vehicle for addressing poverty and national competitiveness in the developing countries. While several governments in Sub-Saharan Africa have adopted the developed countries’ models of innovation to local conditions, the Zambian case is rather unique. This study highlights conceptual and socioeconomic challenges directed to the performances of the NSI. The paper analyses science and technology strategies with the inclusion of “innovation” and its effect towards improving socioeconomic elements. The authors reviewed STI policy and national strategy documents, followed by interviews compared to economical regional and national data sets. The NSI and its related to inter-linkages and support mechanism to socioeconomic development were explored.

Keywords: national system of innovation, socioeconomics, development, Zambia

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Authors: Ruilian Zhao, Shukai Zhang, Yan Wang, Weiwei Wang

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Repairing broken test cases is an expensive and challenging task in evolving software systems. Although an automated repair technique with intent preservation has been proposed, but it does not take into account the association between test repairs and assertions, leading to a large number of irrelevant candidates and decreasing the repair capability. This paper proposes an assertion-driven test repair approach. Furthermore, an intent-oriented priority criterion is raised to guide the repair candidate generation, making the repairs closer to the intent of the test. In more detail, repair targets are determined through post-dominance relations between assertions and the methods that directly cause compilation errors. Then, test repairs are generated from the target in a bottom-up way, guided by the intent-oriented priority criteria. Finally, the generated repair candidates are prioritized to match the original test intent. The approach is implemented and evaluated on the benchmark of 4 open-source programs and 91 broken test cases. The result shows that the approach can fix 89% (81/91) of broken test cases, which is more effective than the existing intentpreserved test repair approach, and our intent-oriented priority criteria work well.

Keywords: test repair, test intent, software test, test case evolution

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Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

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In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

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Authors: Ali Mohammed Yimer, Ayalew Assen, Youssef Belmabkhout

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Environmental remediation is a pressing global concern, necessitating innovative strategies to address the challenges posed by industrial waste and pollution. This study aims to advance environmental remediation by developing cutting-edge functional porous materials from phosphorite residue tailings. Phosphorite mining activities generate vast amounts of waste, which pose significant environmental risks due to their contaminants. The proposed approach involved transforming these phosphorite residue tailings into valuable porous materials through a series of physico-chemical processes including milling, acid-base leaching, designing or templating as well as formation processes. The key components of the tailings were extracted and processed to produce porous arrays with high surface area and porosity. These materials were engineered to possess specific properties suitable for environmental remediation applications, such as enhanced adsorption capacity and selectivity for target contaminants. The synthesized porous materials were thoroughly characterized using advanced analytical techniques (XRD, SEM-EDX, N2 sorption, TGA, FTIR) to assess their structural, morphological, and chemical properties. The performance of the materials in removing various pollutants, including heavy metals and organic compounds, were evaluated through batch adsorption experiments. Additionally, the potential for material regeneration and reusability was investigated to enhance the sustainability of the proposed remediation approach. The outdoors of this research holds significant promise for addressing the environmental challenges associated with phosphorite residue tailings. By valorizing these waste materials into porous materials with exceptional remediation capabilities, this study contributes to the development of sustainable and cost-effective solutions for environmental cleanup. Furthermore, the utilization of phosphorite residue tailings in this manner offers a potential avenue for the remediation of other contaminated sites, thereby fostering a circular economy approach to waste management.

Keywords: functional porous materials, phosphorite residue tailings, adsorption, environmental remediation, sustainable solutions

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Authors: Omar Bouhassoun, Cristian Garrido, César Hueso

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The radiation shielding design is an optimization problem with multiple -constrained- objective functions (radiation dose, weight, price, etc.) that depend on several parameters (material, thickness, position, etc.). The classical approach for shielding design consists of a brute force trial-and-error process subject to previous designer experience. Therefore, the result is an empirical solution but not optimal, which can degrade the overall performance of the shielding. In order to automate the shielding design procedure, the IDOM Shielding Optimization Tool (ISOT) has been developed. This software combines optimization algorithms with the capabilities to read/write input files, run calculations, as well as parse output files for different radiation transport codes. In the first stage, the software was established to adjust the input files for two well-known Monte Carlo codes (MCNP and Serpent) and optimize the result (weight, volume, price, dose rate) using multi-objective genetic algorithms. Nevertheless, its modular implementation easily allows the inclusion of more radiation transport codes and optimization algorithms. The work related to the development of ISOT and its verification on a simple 3D multi-layer shielding problem using both MCNP and Serpent will be presented. ISOT looks very promising for achieving an optimal solution to complex shielding problems.

Keywords: optimization, shielding, nuclear, genetic algorithm

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Authors: Ahmed Elzainy, Abir El Sadik, Waleed Al Abdulmonem, Ahmad Alamro, Homaidan Al-Homaidan

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Problem-based learning (PBL) is an educational modality which stimulates critical and creative thinking. PBL has been practiced in the college of medicine, Qassim University, Saudi Arabia, since the 2002s with offline face to face activities. Therefore, crucial technological changes in paperless work were needed. The aim of the present study was to design and implement the digitalization of the PBL activities and to evaluate its impact on students' and tutors’ performance. This approach promoted the involvement of all stakeholders after their awareness of the techniques of using online tools. IT support, learning resources facilities, and required multimedia were prepared. Students’ and staff perception surveys reflected their satisfaction with these remarkable changes. The students were interested in the new digitalized materials and educational design, which facilitated the conduction of PBL sessions and provided sufficient time for discussion and peer sharing of knowledge. It enhanced the tutors for supervision and tracking students’ activities on the Learning Management System. It could be concluded that introducing of digitalization of the PBL activities promoted the students’ performance, engagement and enabled a better evaluation of PBL materials and getting prompt students as well as staff feedback. These positive findings encouraged the college to implement the digitalization approach in other educational activities, such as Team-Based Learning, as an additional opportunity for further development.

Keywords: multimedia in PBL, online PBL, problem-based learning, PBL digitalization

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Authors: Roger M. Wall, David G. Proverbs, Yamina Silva, Danny Scipion

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This paper critically reviews the outcomes of a 4 day workshop focused on building resilience to El Niño related Flood Events in northern Perú. The workshop was run jointly by Birmingham City University (BCU) in partnership with Instituto Geofísico del Perú (IGP) and was hosted by the Universidad de Piura (UDEP). The event took place in August 2018 and was funded by the Newton-Paulet fund administered by the British Council. The workshop was a response to the severe flooding experienced in Piura during the El Niño event of March 2017 which damaged over 100,000 homes and destroyed much local infrastructure including around 100 bridges. El Niño is a recurrent event and there is concern that its frequency and intensity may change in the future as a consequence of climate change. A group of 40 early career researchers and practitioners from the UK and Perú were challenged with working together across disciplines to identify key cross-cutting themes and make recommendations for building resilience to similar future events. Key themes identified on day 1 of the workshop were governance; communities; risk information; river management; urban planning; health; and infrastructure. A field study visit took place on day 2 so that attendees could gain first-hand experience of affected and displaced communities. Each of the themes was then investigated in depth on day 3 by small interdisciplinary teams drawing on their own expertise, local knowledge and the experiences of the previous day’s field trip. Teams were responsible for developing frameworks for analysis of their chosen theme and presenting their findings to the whole group. At this point, teams worked together to develop links between the different themes so that an integrated approach could be developed and presented on day 4. This paper describes the approaches taken by each team and the way in which these were integrated to form an holistic picture of the whole system. The findings highlighted the importance of risk-related information and the need for strong governance structures to enforce planning regulations and development. The structured facilitation approach proved to be very effective and it is recommended that the process be repeated with a broader group of stakeholders from across the region.

Keywords: El Niño, integrated flood risk management, Perú, structured facilitation, systems approach, resilience

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Authors: Sifen Abreham

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Employees are resources in organizations; as such, they need to be trained and developed properly to achieve an organization's goals and expectations. The initial development of the human resource management concept is based on the effective utilization of people to treat them as resources, leading to the realization of business strategies and organizational objectives. The study aimed to assess the effect of training and development practices on employee performance. The researcher used an explanatory research design, which helps to explain, understand, and predict the relationship between variables. To collect the data from the respondents, the study used probability sampling. From the probability, the researcher used stratified random sampling, which can branch off the entire population into homogenous groups. The result was analyzed and presented by using the statistical package for the social science (SPSS) version 26. The major finding of the study was that the training has an impact on employees' job performance to achieve organizational objectives. The district has a policy and procedure for training and development, but it doesn’t apply actively, and it’s not suitable for district-advised reform this policy and procedure and applied actively; the district gives training for the majority of its employees, but most of the time, the training is theoretical the district advised to use practical training method to see positive change, the district gives evaluation after the employees take training and development, but the result is not encouraging the district advised to assess employees skill gap and feel that gap, the district has a budget, but it’s not adequate the district advised to strengthen its financial ground.

Keywords: training, development, employees, performance, policy

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Authors: Collins Chiemeke, Stephen Ibe, Godwin Onyedim

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This research work on high-resolution seismic tomography method was carried out with the aim of investigating how near-surface geology influences the initial distribution of infrastructural development in an area like Otuoke and its environs. To achieve this objective, seismic tomography method was employed. The result revealed that the overburden (highly-weathered layer) thickness ranges from 27 m to 50 m within the survey area, with an average value of 37 m. The 3D surface analysis for the overburden thickness distribution within the survey area showed that the thickness of the overburden is more in regions with less infrastructural development, and least in built-up areas. The range of velocity distribution from the surface to within a depth of 5 m is about 660 m/s to 1160 m/s, with an average value of 946 m/s. The 3D surface analysis of the velocity distribution also revealed that the areas with large infrastructural development are characterized with large velocity values compared with the undeveloped regions that has average low-velocity values. Hence, one can conclusively say that the initial settlement of Otuoke and its environs and the subsequent infrastructural development was influenced by the underlying near surface geology (rigid earth), among other factors.

Keywords: geology, seismic, infrastructural, near-surface

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Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach

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Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

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Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

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Authors: Donald C. Lantu, Henndy Ginting, M. Yorga Permana, Dany M. A. Ramdlany

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We constructed a training program for top-talents of a Bank with Scharmer Theory-U as the model. In this training program, we implemented the action learning perspective, as it is claimed to be the most effective one currently available. In the process, participants were encouraged to be more involved, especially compared to traditional lecturing. The goal of this study is to assess the effectiveness of this particular training. The program consists of six days non-residential workshop within two months. Between each workshop, the participants were involved in the works of action learning group. They were challenged by dealing with the real problem related to their tasks at work. The participants of the program were 30 best talents who were chosen according to their yearly performance. Using paired difference statistical test in the behavioral assessment, we found that the training was not effective to increase participants’ leadership competencies. For the future development program, we suggested to modify the goals of the program toward the next stage of development.

Keywords: action learning, behavior, leadership development, Theory-U

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Authors: Ayyoub Jamali

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At the first glance, it seems that the African Court on Human and People’s Rights has achieved a tremendous development in the protection of human rights in Africa. Since its first judgement in 2009, the court has taken a robust approach/ assertive stance, showing its strength by finding states to be in violation of the Africana Charter and other human rights treaties. This paper seeks to discuss various challenges and resistance that the Court has faced since the adoption of the Founding Protocol to the Establishment of the African Court on Human and People’s Rights. The outcome of the paper casts shadow on the legitimacy and effectiveness of the African Court as the guarantor of human rights within the African continent.

Keywords: African Court on Human and People’s Rights, African Union, African regional human rights system, compliance

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we propose an approach of detecting the behavior of the viewers of a TV program in a non-controlled environment. The experiment we propose is based on the use of three types of connected objects (smartphone, smart watch, and a connected remote control). 23 participants were observed while watching their TV programs during three phases: before, during and after watching a TV program. Their behaviors were detected using an approach based on The Dempster Shafer Theory (DST) in two phases. The first phase is to approximate dynamically the mass functions using an approach based on the correlation coefficient. The second phase is to calculate the approximate mass functions. To approximate the mass functions, two approaches have been tested: the first approach was to divide each features data space into cells; each one has a specific probability distribution over the behaviors. The probability distributions were computed statistically (estimated by empirical distribution). The second approach was to predict the TV-viewing behaviors through the use of classifiers algorithms and add uncertainty to the prediction based on the uncertainty of the model. Results showed that mixing the fusion rule with the computation of the initial approximate mass functions using a classifier led to an overall of 96%, 95% and 96% success rate for the first, second and third TV-viewing phase respectively. The results were also compared to those found in the literature. This study aims to anticipate certain actions in order to maintain the attention of TV viewers towards the proposed TV programs with usual connected objects, taking into account the various uncertainties that can be generated.

Keywords: Iot, TV-viewing behaviors identification, automatic classification, unconstrained environment

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Authors: Oluwatosin S. Adeoye

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The power quality issues in the world today are critical to the development of different nations. Prosperity of each nation depends on availability of constant power supply. Constant power supply is a major challenge in Africa particularly in Nigeria where the generated power is than thirty percent of the required power. The metrics of power quality are voltage dip, flickers, spikes, harmonics and interruptions. The level of interruptions in Ekiti State was examined through the investigation of the causes of power interruptions in the State. The method used was the collection of data from the Distribution Company, assessment through simple programming as a command for plotting the graphs through the use of MATLAB 2015 depicting the behavioural pattern of the interruption for a period of six months in 2016. The result shows that the interrelationship between the interruptions and development. Recommendations were suggested with the objective of solving the problems being set up by interruptions in the State and these include installation of reactors, automatic voltage regulators and effective tap changing system on the lines, busses and transformer substation respectively.

Keywords: development, frequency, interruption, power, quality

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Authors: Seyed Habib Shojaei, Reza Eivazi, Mir Sajad Shojaei, Alireza Akbari, Pooria Mazloom, Seyede Mitra Sadati, Mir Zeinalabedin Shojaei, Farnaz Farbakhsh

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To study the genetic diversity in rapeseeds and agronomic traits, an experiment was conducted using multivariate statistical methods at Agricultural Research Station of Kashmar in 2012-2013.In this experiment, ten genotypes of rapeseed in a Randomized Complete Block designs with three replications were evaluated. The following traits were studied: seed yield, number of days to the fifty percent of flowering, plant height, number of pods on main stem, length of the pod, seed yield per plant, number of seed in pod, harvest index, weight of 100 seeds, number of pods on lateral branch, number of lateral branches. In analyzing the variance, differences between cultivars were significant. The average comparative revealed that the most valuable variety was Licord regarding to the traits while the least valuable variety was Opera. In stepwise regression, harvest index, grain yield per plant and number of pods per lateral branches were entering to model. Correlation analysis showed that the grain yield with the number of pods per lateral branches and seed yield per plant have positive and significant correlation. In the factor analysis, the first five components explained more than 83% of the variance in the data. In the first factor, seed yield and the number of pods per lateral branches were of the highest importance. The traits, seed yield per plant, and pod per main stem were of a great significance in the second factor. Moreover, in the third factor, plant height and the number of lateral branches were more important. In the fourth factor, plant height and one hundred seeds weight were of the highest variance. Finally, days to fifty percent of flowering and one hundred seeds weight were more important in fifth factor.

Keywords: rapeseed, variance analysis, regression, factor analysis

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Authors: Yi-De Liu

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Cultural tourism is one of the largest and fastest growing global tourism markets and the cultures are increasingly being used to promote cities and to increase their competitiveness and attractiveness. One of the major forms of cultural tourism development undertaken throughout Europe has been the staging of a growing number of cultural events. The event of European Capitals of Culture (ECOC) is probably the best example of the new trends of cultural tourism in Europe, which is therefore used in this article to demonstrate some of the key issues surrounding the event-led strategy for cultural tourism development. Based on the experience of the 2008 ECOC Liverpool, UK, the study’s findings point to a number of ways in which the ECOC constitutes a boost for the development of cultural tourism in terms of realising experience economy, enhancing city image, facilitating urban regeneration, promoting cultural production and consumption, as well as establishing partnerships. This study is concluded by drawing some critical factors that event and tourism organisers should consider.

Keywords: cultural tourism, event tourism, cultural event, European capital of culture, Liverpool

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Authors: Houda Abadlia, Nadia Smairi, Khaled Ghedira

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Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Keywords: particle swarm optimization, migration, variable neighborhood search, multiobjective optimization

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Authors: Xukai Fu

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The concept of circular economy is interdisciplinary, intersecting environmental engineering, information technology, business, and social science domains. Over the course of its 15-year tenure in the sanitation industry, Jinkai has concentrated its efforts in the past five years on integrating artificial intelligence (AI) technology with street sanitation apparatus and systems. This endeavor has led to the development of various innovations, including the Intelligent Identification Sweeper Truck (Intelligent Waste Recognition and Energy-saving Control System), the Intelligent Identification Water Truck (Intelligent Flushing Control System), the intelligent food waste treatment machine, and the Intelligent City Road Sanitation Surveillance Platform. This study will commence with an examination of prevalent global challenges, elucidating how Jinkai effectively addresses each within the framework of circular economy principles. Utilizing a review and analysis of pertinent environmental management data, we will elucidate Jinkai's strategic approach. Following this, we will investigate how Jinkai utilizes the advantages of circular economy principles to guide the design of street sanitation machinery, with a focus on digitalization integration. Moreover, we will scrutinize Jinkai's sustainable practices throughout the invention and operation phases of street sanitation machinery, aligning with the triple bottom line theory. Finally, we will delve into the significance and enduring impact of corporate social responsibility (CSR) and environmental, social, and governance (ESG) initiatives. Special emphasis will be placed on Jinkai's contributions to community stakeholders, with a particular emphasis on human rights. Despite the widespread adoption of circular economy principles across various industries, achieving a harmonious equilibrium between environmental justice and social justice remains a formidable task. Jinkai acknowledges that the mere development of energy-saving technologies is insufficient for authentic circular economy implementation; rather, they serve as instrumental tools. To earnestly promote and embody circular economy principles, companies must consistently prioritize the UN Sustainable Development Goals and adapt their technologies to address the evolving exigencies of our world.

Keywords: circular economy, core principles, benefits, the tripple bottom line, CSR, ESG, social justice, human rights, Jinkai

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Authors: Jennifer K. Bowerman, Rhonda L. Reich

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The purpose of this paper is to explore the concepts ACDC (Amore, Consciousness, Discipline, and Commitment) which the authors first discovered as a philosophy and framework for recruitment and organizational development in a successful start-up tech company in Brazil. This paper represents an exploration of these concepts as a potential pedagogical foundation for undergraduate business education in the classroom. It explores whether their application has potential to build emotional and practical resilience in the face of constant organizational and societal change. Derived from Holonomy this paper explains the concepts and develops a narrative around how change influences the operation of organizations. Using examples from leading edge organizational theorists, it explains why a different educational approach grounded in ACDC concepts may not only have relevance for the working world, but also for undergraduates about to enter that world. The authors propose that in the global context of constant change, it makes sense to develop an approach to education, particularly business education, beyond cognitive knowledge, models and tools, in such a way that emotional and practical resilience and creative thinking may be developed. Using the classroom as an opportunity to explore these concepts, and aligning personal passion with the necessary discipline and commitment, may provide students with a greater sense of their own worth and potential as they venture into their ever-changing futures.

Keywords: ACDC, holonomic thinking, organizational learning, organizational change, business pedagogy

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Authors: Mikhail Bouniaev

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The paper reviews design and implementation of a Calculus Course required for the Biomedical Competency Based Program developed as a joint project between The University of Texas Rio Grande Valley, and the University of Texas’ Institute for Transformational Learning, from the theoretical perspective as presented in scholarly work on active learning, formative assessment, and on-line teaching. Following a four stage curriculum development process (objective, content, delivery, and assessment), and theoretical recommendations that guarantee effectiveness and efficiency of assessment in active learning, we discuss the practical recommendations on how to incorporate a strong formative assessment component to address disciplines’ needs, and students’ major needs. In design and implementation of this project, we used Constructivism and Stage-by-Stage Development of Mental Actions Theory recommendations.

Keywords: active learning, assessment, calculus, cognitive demand, mathematics, stage-by-stage development of mental action theory

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Authors: Rotem Mashkov, Noam Shoval

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In an age when a tourist’s gaze is more focused on the daily lives of locals, it is evident that local food markets are being rediscovered. Traditional urban markets succeed in reinventing themselves as a space for consumption, recreation, and culture, enabling authentic experiences and interpersonal interactions with the local culture. Alongside this, the pressure of tourism development may result in commercialization and retail gentrification to the point of losing the sense of local identity. The issue of finding a balance between tourism development and the preservation of unique local features is at the heart of this study and is being tested using the case of the Mahane Yehuda market in Jerusalem. The research question—how merchants respond to tourism development in the Mahane Yehuda food market— focuses on local traders, a group of players who are usually absent from the research arenas, although they influence tourism development as well as influenced by it. Three main research methods were integrated into this study. The first two methods, a survey of articles survey and comparative mapping of the business mix, were used to characterize the changes in the Mahane Yehuda market both consciously and physically. The third research method, involving in-depth interviews with merchants, was used to examine the traders' attitudes and responses to tourism development. The findings indicate that there has been a turnaround in the market image over the past decade and a half. Additionally, there has been a significant physical change in the business mix, reflected by a decline of 15% in the number of stalls selling food products and delicacies. The data from the interviews on the traders’ attitudes towards tourism development were inconclusive; there were disagreements among the traders about the economic contribution of tourism development in relation to their dependence on the tourism industry. However, there was a consensus on the need for authentic elements in the marketplace. The findings of the study also indicate a strong link between the merchants’ response to tourism development and their stall ownership status as the merchant could exercise their position in various ways depending on the possession type.

Keywords: business mix, Jerusalem, local food markets, Mahane Yehuda market, merchants’ attitude, ownership status, retail gentrification, tourism development, traditional urban markets

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Authors: Genziana Lay

Abstract:

A wide majority of older children and adolescents who enter the juvenile court system present with an array of problematic symptoms and behaviors including anxiety, depression, aggressive acting out, detachment, and substance abuse. Attachment theory offers a framework for understanding normative and pathological functioning, which during development is influenced by emotional, social and cognitive elements. There is clear evidence that children and adolescents with the highest risk of developing adaptation problems present an insecure attachment profile. Most offending minors have experienced dysfunctional family relationships as well as social and/or economic deprivation. Their maladaptive attachment develops not only through their relationship with caregivers but with the environment at large. Activation of their faulty attachment system leads them to feel emotionally overwhelmed and engage in destructive behaviors and decision-making. A psycho-social intervention with this population conceptualized as attachment therapy is a multi-faceted, practical approach that has shown excellent results in terms of increased psychological well-being and drastically reduced rates of re-offense/ destructive behavior. Through several; components including psychotherapy, monitoring, volunteering, meditation and socialization, the program focuses on seven dimensions: self-efficacy, responsibility, empathy/reparation, autonomy/security, containment/structure, insight building, and relational health. This paper presents the program and illustrates how the framework of attachment theory practically applied to psycho-social intervention has great therapeutic and social reparation potential. Preliminary evidence drawn from the Sassari Juvenile Court is very promising; this paper will illustrate these results and propose an even more comprehensive, applicable approach to psycho-social reparative intervention that leads to greater psychological health and reduced recidivism in the child and adolescent population.

Keywords: attachment, child, adolescent, crime, juvenile, psychosocial

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Authors: Ahmed Abbou

Abstract:

This paper present a sensorless controller designed by the backstepping approach for the speed control of induction motor. In this strategy of control, we also combined the method Fuzzy MRAS to estimate the rotor speed and the observer type Luenburger to observe Rotor flux. The control model involves a division by the flux variable that may lead to unbounded solutions. Such a risk is avoided by basing the controller design on Lyapunov function that accounts for the model singularity. On the other hand, this mixed method gives better results in Sensorless operation and especially at low speed. The response time at 5% of the flux is 20ms while the error between the speed with sensor and the estimated speed remains in the range of ±0.8 rad/s for the rated functioning and ±1.5 rad/s for low speed.

Keywords: backstepping approach, fuzzy logic, induction motor, luenburger observer, sensorless MRAS

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Authors: Ezekiel Mwangi, Stephen Kimani, Agnes Mindila

Abstract:

Usability is one of the key factors that determine the success or failure of any WebGIS (technology normally applied on the internet to analyze and present spatial data on the Internet). However, not all the usability attributes have the same impact on usability. It is, therefore, necessary to prioritize WebGIS usability elements and determine the ones that are more crucial to the success of the WebGIS. This research aims to identify the main elements of WebGIS usability, investigate the order of importance and priority of the usability elements of WebGIS, and propose a WebGIS development framework that incorporates the prioritization of the usability elements. This will be achieved through a literature review. The outcome of this research will help usability specialists and WebGIS developers in determining specific usability elements that should be accorded more emphasis during the design and development of WebGIS.

Keywords: framework, prioritization, usability, WebGIS

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Authors: Jianhua Zhou, Yuwen Zhang

Abstract:

A two-step multigrid approach is proposed to solve the inverse heat conduction problem in a 3-D object under laser irradiation. In the first step, the location of the laser center is estimated using a coarse and uniform grid system. In the second step, the front-surface temperature is recovered in good accuracy using a multiple grid system in which fine mesh is used at laser spot center to capture the drastic temperature rise in this region but coarse mesh is employed in the peripheral region to reduce the total number of sensors required. The effectiveness of the two-step approach and the multiple grid system are demonstrated by the illustrative inverse solutions. If the measurement data for the temperature and heat flux on the back surface do not contain random error, the proposed multigrid approach can yield more accurate inverse solutions. When the back-surface measurement data contain random noise, accurate inverse solutions cannot be obtained if both temperature and heat flux are measured on the back surface.

Keywords: conduction, inverse problems, conjugated gradient method, laser

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Authors: Hanadi Mubarak AL-Mubaraki, Michael Busler

Abstract:

Innovation is the process of making changes, differences, and novelties in the products and services, adding values and business practices to create economic and social benefit. The purpose of this paper is to identify the strengths and weaknesses of innovation programs in developed and developing countries. We used a mixed-methods approach, quantitative as survey and qualitative as a multi-case study to examine innovation best practices in developed and developing countries. In addition, four case studies of innovation organisations based on the best practices and successful implementation in the developed and developing countries are selected for examination. The research findings provide guidance, suggestions, and recommendations for future implementation in developed and developing countries for practitioners such as policy makers, governments, funded organizations, and strategic institutions. In conclusion, innovation programs are vital tools for economic growth, knowledge, and technology transfer based on the several indicators such as creativity, entrepreneurship, role of government, role of university, strategic focus, new products, survival rate, job creation, start-up companies, and number of patents. The authors aim to conduct future research which will include a comparative study of innovation case studies between developed and developing countries for policy implications worldwide. The originality of this study makes a contribution to the current literature about the innovation best practice in developed and developing countries.

Keywords: economic development, entrepreneurship, innovation program, developed countries

Procedia PDF Downloads 363