Search results for: selection of support tenants

Authors: Hanna Zietara

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Gastronomy is one of the oldest forms of commercial activity. It is currently one of the most popular and still dynamically developing branches of business. Socio-economic changes, its widespread occurrence, new techniques, or culinary styles affect the almost unlimited possibilities of its development. Importantly, regardless of the form of business adopted, food service is strongly related to logistics processes, and areas of food service that are closely linked to logistics are of strategic importance. Any inefficiency in logistics processes results in reduced chances for success and achieving competitive advantage by companies belonging to the catering industry. The aim of the paper is to identify the areas of logistic support occurring in the catering business, affecting the scope of the logistic processes implemented. The aim of the paper is realized through a plural homogeneous approach, based on: direct observation, text analysis of current documents, in-depth free targeted interviews.

Keywords: gastronomy, competitive advantage, logistics, logistics support

Procedia PDF Downloads 163

Authors: Evrim Genc Kumtepe, Elif Toprak, Aylin Ozturk, Gamze Tuna, Hakan Kilinc, Irem Aydin Menderis

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Support services are very significant elements for all educational institutions in general; however, for distance learners, these services are more essential than traditional (face-to-face) counterparts. One of the most important reasons for this is that learners and instructors do not share the same physical environment and that distance learning settings generally require intrapersonal interactions rather than interpersonal ones. Some learners in distance learning programs feel isolated. Furthermore, some fail to feel a sense of belonging to the institution because of lack of self-management skills, lack of motivation levels, and the need of being socialized, so that they are more likely to fail or drop out of an online class. In order to overcome all these problems, support services have emerged as a critical element for an effective and sustainable distance education system. Within the context of distance education support services, it is natural to include technology-based and web-based services and also the related materials. Moreover, institutions in education sector are expected to use information and communication technologies effectively in order to be successful in educational activities and programs. In terms of the sustainability of the system, an institution should provide distance education services through ICT enabled processes to support all stakeholders in the system, particularly distance learners. In this study, it is envisaged to develop a model based on the current support services literature in the field of open and distance learning and the applications of the distance higher education institutions. Specifically, content analysis technique is used to evaluate the existing literature in the distance education support services, the information published on websites, and applications of distance higher education institutions across the world. A total of 60 institutions met the inclusion criteria which are language option (English) and availability of materials in the websites. The six field experts contributed to brainstorming process to develop and extract codes for the coding scheme. During the coding process, these preset and emergent codes are used to conduct analyses. Two coders independently reviewed and coded each assigned website to ensure that all coders are interpreting the data the same way and to establish inter-coder reliability. Once each web page is included in descriptive and relational analysis, a model of support services is developed by examining the generated codes and themes. It is believed that such a model would serve as a quality guide for future institutions, as well as the current ones.

Keywords: support services, open education, distance learning, support model

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Authors: Woosik Jang, Seung H. Han

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The optimal partner selection is one of the most important factors to pursue the project’s success. However, in practice, there is a gaps in perception of success depending on the role of the enterprises for the projects. This frequently makes a relations between the partner evaluation results and the project’s final performances, insufficiently. To meet this challenges, this study proposes a strategic partner evaluation model considering the perception gaps between enterprises. A total 3 times of survey was performed; factor selection, perception gap analysis, and case application. After then total 8 factors are extracted from independent sample t-test and Borich model to set-up the evaluation model. Finally, through the case applications, only 16 enterprises are re-evaluated to “Good” grade among the 22 “Good” grade from existing model. On the contrary, 12 enterprises are re-evaluated to “Good” grade among the 19 “Bad” grade from existing model. Consequently, the perception gaps based evaluation model is expected to improve the decision making quality and also enhance the probability of project’s success.

Keywords: partner evaluation model, project based enterprise, decision making, perception gap, project performance

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Authors: Supattra Kanchanopast

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This article presents the process of change for innovation in the Thai public sector in order to create higher client satisfaction. Change management should concern the potentiality of the change agent or leader, the long-term vision or policy (political side) of the organization, the communication within the organization, suitable organizational culture and structure, preparedness of the personnel, and the fitness of the reward system. Sustaining innovation creation is not sophisticated, as traditionally believed. A basic management principle of identifying clarified and motivating goals needs to be followed by creating support systems after implementation and by ensuring the stakeholders’ benefit, derived from the innovation projects. Finally, creating an amiable atmosphere among the practitioners, including effective evaluation and reward schemes, will support the innovation. However, none of these will ever take place unless support is gained from the leaders of those organizations, and from the staff and clients involved also as well.

Keywords: change management, client satisfaction, innovation management, Thai public sector

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Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

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Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

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The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

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Authors: Manverpreet Kaur, Amarpreet Singh

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The demand of Vehicular ad hoc networks is increasing day by day, due to offering the various applications and marvelous benefits to VANET users. Clustering in VANETs is most important to overcome the connectivity problems of VANETs. In this paper, we proposed a new clustering technique Enhanced cluster based connectivity maintenance in vehicular ad hoc network. Our objective is to form long living clusters. The proposed approach is grouping the vehicles, on the basis of the longest list of neighbors to form clusters. The cluster formation and cluster head selection process done by the RSU that may results it reduces the chances of overhead on to the network. The cluster head selection procedure is the vehicle which has closest speed to average speed will elect as a cluster Head by the RSU and if two vehicles have same speed which is closest to average speed then they will be calculate by one of the new parameter i.e. distance to their respective destination. The vehicle which has largest distance to their destination will be choosing as a cluster Head by the RSU. Our simulation outcomes show that our technique performs better than the existing technique.

Keywords: VANETs, clustering, connectivity, cluster head, intelligent transportation system (ITS)

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Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

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Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

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Authors: Guilhermina Torrao

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An extensive number of studies have been conducted to determine the factors which influence crash injury risk (CIR); however, uncertainties inherent to selected variables have been neglected. A review of existing literature is required to not only obtain an overview of the variables and measures but also ascertain the implications when comparing studies without a systematic view of variable taxonomy. Therefore, the aim of this literature review is to examine and report on peer-reviewed studies in the field of crash analysis and to understand the implications of broad variations in variable selection in CIR analysis. The objective of this study is to demonstrate the variance in variable selection and classification when modeling injury risk involving occupants of light vehicles by presenting an analytical review of the literature. Based on data collected from 64 journal publications reported over the past 21 years, the analytical review discusses the variables selected by each study across an organized list of predictors for CIR analysis and provides a better understanding of the contribution of accident and vehicle factors to injuries acquired by occupants of light vehicles. A cross-comparison analysis demonstrates that almost half the studies (48%) did not consider vehicle design specifications (e.g., vehicle weight), whereas, for those that did, the vehicle age/model year was the most selected explanatory variable used by 41% of the literature studies. For those studies that included speed risk factor in their analyses, the majority (64%) used the legal speed limit data as a ‘proxy’ of vehicle speed at the moment of a crash, imposing limitations for CIR analysis and modeling. Despite the proven efficiency of airbags in minimizing injury impact following a crash, only 22% of studies included airbag deployment data. A major contribution of this study is to highlight the uncertainty linked to explanatory variable selection and identify opportunities for improvements when performing future studies in the field of road injuries.

Keywords: crash, exploratory, injury, risk, variables, vehicle

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Authors: M. Johnson, R. Faggian, V. Sposito

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A participatory and engaged approach is key in connecting agricultural managers to sustainable agricultural systems to support and optimize production in Victoria’s food bowl. A sustainable intensification (SI) approach is well documented globally, but participation rates amongst Victorian farmers is fragmentary, and key outcomes and implementation strategies are poorly understood. Improvement in decision-support management tools and a greater understanding of the productivity gains available upon implementation of SI is necessary. This paper reviews the current understanding and uptake of SI practices amongst farmers in one of Victoria’s premier food producing regions, the Goulburn Broken; and it spatially analyses the potential for this region to adapt to climate change and optimize food production. A Geographical Information Systems (GIS) approach is taken to develop an interactive decision-support tool that can be accessible to on-ground agricultural managers. The tool encompasses multiple criteria analysis (MCA) that identifies factors during the construction phase of the tool, using expert witnesses and regional knowledge, framed within an Analytical Hierarchy Process. Given the complexities of the interrelations between each of the key outcomes, this participatory approach, in which local realities and factors inform the key outcomes and help to strategies for a particular region, results in a robust strategy for sustainably intensifying production in key food producing regions. The creation of an interactive, locally embedded, decision-support management and education tool can help to close the gap between farmer knowledge and production, increase on-farm adoption of sustainable farming strategies and techniques, and optimize farm productivity.

Keywords: agriculture, decision-support management tool, Geographic Information System, GIS, sustainable intensification

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Authors: A. Yongsheng Guo, B. Obedat. Abdulazeez, C. Xiaoxian Zhu

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This study aimed to identify the barriers to the development of small and medium-sized enterprises (SMEs) in China and build a theoretical framework to evaluate the support provided by the authorities and institutions. A grounded theory approach was adopted to collect and analyze data. 32 interviews were conducted with SME managers, and open, axial and selective coding was utilized to develop themes. Based on institutional theory, grounded theory models were used to present findings. The findings showed that the main barriers in the business environment were defaulting on contracts, bureaucracy in procedures, lack of financial and legal support, limited intermediaries and channels, and poor quality of products and services. This study found that many programs were provided to support SMEs. A theoretical framework was developed to evaluate the performance of the programs from the managers’ perspective. The concepts of economy, efficiency and effectiveness were used to evaluate the perceived value of the programs. This study suggests that specialized programs are needed to suit sector-specific requirements, and creative packages are helpful in supporting SMEs' growth.

Keywords: business support, public economics, public programme, SME

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Authors: Byungchae Kim, Jiwoo Nam

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Aging of weapon systems can cause the failure and degeneration of components which results in increase of operating and support costs. However, whether this aging effect is significantly strong and it influences a lot on national defense spending due to the rapid increase in operating and support (O&S) costs is questionable. To figure out this, we conduct a literature review analyzing the aging effect of US weapon systems. We also conduct an empirical research using a maintenance database of Korean weapon systems, Defense Logistics Integrated Information System (DAIIS). We run regression of various types of O&S cost on weapon system age to investigate the statistical significance of aging effect and use generalized linear model to find relations between the failure of different priced components and the age. Our major finding is although aging effect exists, its impacts on weapon system cost seem to be not too large considering several characteristics of O&S cost elements not relying on the age.

Keywords: O&S cost, aging effect, weapon system, GLM

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Authors: Aseela Alhinaai, Suliman Abdullah, Adil Albusaidi

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Knowledge has been considered an important asset in private and public organizations. It is utilized in the libraries sector to run different operations of technical services and administrative works. As a result, the International Federation of Library Association (IFLA) established a department “Knowledge Management” in December 2003 to provide a deep understanding of the KM concept for professionals. These are implemented through different programs, workshops, and activities. This study aims to identify the impact of the knowledge-sharing factors (technology, collaboration, management support) to improve decision-making at Sultan Qaboos University Libraries. This study conducted a quantitative method using a questionnaire instrument to measure the impact of technology, collaboration, and management support on knowledge sharing that lead to improved decision-making. The study population is the (SQU) libraries (Main Library, Medical Library, College of Economic and political science library, and Art Library). The results showed that management support, collaboration, and technology use have a positive impact on the knowledge-sharing process, and knowledge-sharing positively affects the decision making process.

Keywords: knowledge sharing, decision-making, information technology, management support, corroboration, Sultan Qaboos University

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Authors: Gaafar Omer BaOmer, Abdulmohsin A. Al-Sofyani, Hassan A. Ramadan

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Drupella is found on coral reefs throughout the tropical and subtropical shallow waters of the Indo-Pacific region. Drupella is muricid gastropod, obligate corallivorous and their population outbreak can cause significant coral mortality. Belt transect surveys were conducted at two sites (Bohairat and Baydah) in Jeddah coast, Saudi Arabia to assess prey preferences for D. cornus with respect to prey availability through resource selection ratios. Results revealed that there are different levels of prey preferences at the different age stages and at the different sites. Acropora species with a caespitose, corymbose and digitate growth forms were preferred prey for recruits and juveniles of Drupella cornus, whereas Acropora variolosa was avoided by D. cornus because of its arborescent colony growth form. Pocillopora, Stylophora, and Millipora were occupied by Drupella cornus less than expected, whereas massive corals genus Porites were avoided. High densities of D. cornus were observed on two fragments of Pocillopora damicornis which may because of the absence of coral guard crabs genus Trapezia. Mean densities of D. cornus per colony for each species showed significant differentiation between the two study sites. Low availability of Acropora colonies in Bayadah patch reef caused high mean density of D. cornus per colony to compare to that in Bohairat, whereas higher mean density of D. cornus per colony of Pocillopora in Bohairat than that in Bayadah may because of most of occupied Pocillopora colonies by D. cornus were physical broken by anchoring compare to those colonies in Bayadah. The results indicated that prey preferences seem to depend on both coral genus and colony shape, while mean densities of D. cornus depend on availability and status of coral colonies.

Keywords: prey availability, resource selection, Drupella cornus, Jeddah, Saudi Arabia

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

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The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence numerous studies have come up with technologies for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. Since the demisability of spacecraft depends on evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. Therefore, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: demisability, emissivity, lightweight, re-entry, survivability

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Authors: Maryam Khalilzadeh Poshtegal, Seyed Ahmad Mirbagheri, Mojtaba Noury

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In this paper, by application of the input yearly data of rainfall, temperature and flow to the Urmia Lake, the simulation of water level fluctuation were applied by means of three models. According to the climate change investigation the fluctuation of lakes water level are of high interest. This study investigate data-driven models, support vector machines (SVM), SVM method which is a new regression procedure in water resources are applied to the yearly level data of Lake Urmia that is the biggest and the hyper saline lake in Iran. The evaluated lake levels are found to be in good correlation with the observed values. The results of SVM simulation show better accuracy and implementation. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria.

Keywords: simulation, water level fluctuation, urmia lake, support vector machine

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Authors: Naz Najma, Grace T. M. Dal Sasso, Maria de Lourdes de Souza

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The development of information and communication technologies and the accessibility of mobile devices has increased the possibilities of the teaching and learning process anywhere and anytime. Mobile and web application allows the production of constructive teaching and learning models in various educational settings, showing the potential for active learning in nursing. The objective of this study was to present the development of an educational technology (Savinglife®, an app) for learning cardiopulmonary resuscitation and advanced cardiovascular life support training. Savinglife® is a technological production, based on the concept of virtual learning and problem-based learning approach. The study was developed from January 2016 to November 2016, using five phases (analyze, design, develop, implement, evaluate) of the instructional systems development process. The technology presented 10 scenarios and 12 simulations, covering different aspects of basic and advanced cardiac life support. The contents can be accessed in a non-linear way leaving the students free to build their knowledge based on their previous experience. Each scenario is presented through interactive tools such as scenario description, assessment, diagnose, intervention and reevaluation. Animated ECG rhythms, text documents, images and videos are provided to support procedural and active learning considering real life situation. Accessible equally on small to large devices with or without an internet connection, Savinglife® offers a dynamic, interactive and flexible tool, placing students at the center of the learning process. Savinglife® can contribute to the student’s learning in the assessment and management of basic and advanced cardiac life support in a safe and ethical way.

Keywords: problem-based learning, cardiopulmonary resuscitation, nursing education, advanced cardiac life support, educational technology

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Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

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The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Evridiki Zachopoulou, Vasilis Grammatikopoulos, Michail Vitoulis, Athanasios Gregoriadis

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In the last ten years, the recent economic crisis in Greece has decreased the financial ability and strength of several families when it comes to supporting their children’s studies. As a result, the number of students who are significantly delaying or even dropping out of their university studies is constantly increasing. The students who are at greater risk for academic failure are those who are facing various problems and social disadvantages, like health problems, special needs, family poverty or unemployment, single-parent students, immigrant students, etc. The ‘Umbrella’ project is a volunteer-based initiative to tackle this problem at International Hellenic University. The main purpose of the project is to provide support to disadvantaged students at a socio-emotional, academic, and practical level in order to help them complete their undergraduate studies. More specifically, the ‘Umbrella’ project has the following goals: (a) to develop a consulting-supporting network based on volunteering senior students, called ‘i-mentors’. (b) to train the volunteering i-mentors and create a systematic and consistent support procedure for students at-risk, (c), to develop a service that, parallel to the i-mentor network will be ensuring opportunities for at-risk students to find a job, (d) to support students who are coping with accessibility difficulties, (e) to secure the sustainability of the ‘Umbrella’ project after the completion of the funding of the project. The innovation of the Umbrella project is in its holistic-person-centered approach that will be providing individualized support -via the i-mentors network- to any disadvantaged student that will come ‘under the Umbrella.’

Keywords: peer mentoring, student support, socially disadvantaged students, volunteerism in higher education

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Authors: Muhammad Shahid Shah, Akram Maqbool, Samina Ashraf

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Since start of this century, world has adopted inclusion as a trend in special education. To meet the challenges of inclusion response, the Punjab government has developed a progressive policy to implement inclusive education. The objectives of this research were to analyze the administration and implementation process by consideration on the management, student’s admission process, screening and assessment, adaptations in curriculum and instruction along with an evaluation, government and nonprofit organizations support. The sample consisted of 50 schools both public and private with a total of 3000 students, 9 percent of which (270) were students with disabilities. Among all the students with disabilities, 63 percent (170) were male and 37 percent (100) were female. The concluded remarks regarding management revealed that a large number of inclusive schools was lacking in terms of developing a certain model for inclusion, including the managerial breakup of staff, the involvement of stakeholders, and conducted frequent meetings. Many of schools are not able to restructure their school organizations due to lack of financial resources, consultations, and backup. As for as student’s admission/identification/assessment was concerned, only 12 percent schools applied a selection process regarding student admission, half of which used different procedures for disable candidates. Approximately 5 percent of inclusive schools had modified their curriculum, including a variety of standards. In terms of instruction, 25 percent of inclusive schools reported that they modified their instructional process. Only a few schools, however, provided special equipment for students with visual impairment, physical impairment, speech and hearing problems, students with mild intellectual disabilities, and autism. In a student evaluation, more than 45 percent reported that test items, administration, time allocations, and students’ reports were modified. For the primary board examination conducted by the Education Department of Government of Punjab, this number decreased dramatically. Finally, government and nonprofit organizations support in the forms of funding, coaching, and facilities were mostly provided by provincial governments and by Ghazali Education Trust.

Keywords: inclusion, identification, assessment, funding, facilities, evaluation

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Authors: Justyna Mroczkowska

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Social worker's ability to provide culturally sensitive assistance in child protection is taken for granted; given limited training opportunities and lack of clear guidance, practitioners report working with migrant families more demanding in comparison to working with native families. In this study, the author developed and factor analyzed the Norwegian Cultural Self-Efficacy Scale to describe the level of cultural capability among Norwegian child protection professionals. The study aimed to determine the main influencing factors to cultural efficacy and examine the relationship between self-efficacy and perceived difficulty in working with migrant families. The scale was administered to child protection workers in Norway (N=251), and the reliability of the scale measured by Cronbach's alpha coefficient was .904. The confirmatory factor analysis of social work cultural self-efficacy found support for four separate but correlated subscales: Assessment, Communication, Support Request, and Teamwork. Regression analyses found the experience in working with migrant families, training and support from external agencies, and colleague support to be significant predictors of cultural self-efficacy. Self-efficacy in assessment skills and self-efficacy in communication skills were moderately related to the perceived difficulty to work with migrant families. The findings conclude with previous research and highlight the need for both professional development programs and institutional resources to be provided to support the practitioner's preparation for multicultural practice in child protection.

Keywords: child protection, cultural self-efficacy, cultural competency, migration, resources

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Authors: M. Novak, E. Munoz, A. Jana, M. Nelemans

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Cities and local governments the world over are interested to employ circular strategies as a means to bring about food security, create employment and increase resilience. The selection and implementation of circular strategies is facilitated by modeling the effects of strategies locally and understanding the impacts such strategies have had in other (comparable) cities and how that would translate locally. Urban areas are heterogeneous because of their geographic, economic, social characteristics, governance, and culture. In order to better understand the effect of circular strategies on urban systems, we create a dataset for over 300 cities around the world designed to facilitate circular strategy scenario modeling. This new dataset integrates data from over 20 prominent global national and urban data sources, such as the Global Human Settlements layer and International Labour Organisation, as well as incorporating employment data from over 150 cities collected bottom up from local departments and data providers. The dataset is made to be reproducible. Various clustering techniques are explored in the paper. The result is sets of clusters of cities, which can be used for further research, analysis, and support comparative, regional, and national policy making on circular cities.

Keywords: data integration, urban innovation, cluster analysis, circular economy, city profiles, scenario modelling

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Authors: Vincenzo Piemonte

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The liver is a complex, large-scale biochemical reactor which plays a unique role in the human physiology. When liver ceases to perform its physiological activity, a functional replacement is required. Actually, liver transplantation is the only clinically effective method of treating severe liver disease. Anyway, the aforementioned therapeutic approach is hampered by the disparity between organ availability and the number of patients on the waiting list. In order to overcome this critical issue, research activities focused on liver support device systems (LSDs) designed to bridging patients to transplantation or to keep them alive until the recovery of native liver function. In recirculating albumin dialysis devices, such as MARS (Molecular Adsorbed Recirculating System), adsorption is one of the fundamental steps in albumin-dialysate regeneration. Among the albumin-bound toxins that must be removed from blood during liver-failure therapy, bilirubin and tryptophan can be considered as representative of two different toxin classes. The first one, not water soluble at physiological blood pH and strongly bounded to albumin, the second one, loosely albumin bound and partially water soluble at pH 7.4. Fixed bed units are normally used for this task, and the design of such units requires information both on toxin adsorption equilibrium and kinetics. The most common adsorptive media used in LSDs are activated carbon, non-ionic polymeric resins and anionic resins. In this paper, bilirubin adsorption isotherms on different adsorptive media, such as polymeric resin, albumin-coated resin, anionic resin, activated carbon and alginate beads with entrapped albumin are presented. By comparing all the results, it can be stated that the adsorption capacity for bilirubin of the five different media increases in the following order: Alginate beads < Polymeric resin < Albumin-coated resin < Activated carbon < Anionic resin. The main focus of this paper is to provide useful guidelines for the optimization of liver support devices which implement adsorption columns to remove albumin-bound toxins from albumin dialysate solutions.

Keywords: adsorptive media, adsorption equilibrium, artificial liver devices, bilirubin, mathematical modelling

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Authors: Wan Jiun Tin

Abstract:

Neighborhood regeneration has gained its popularity despite market-led urban redevelopment is still the main strategy in most of the countries in Asia. Area-based approach of neighborhood regeneration with the focus on people, place and system which covers the main sustainable aspects shall be studied as part of the solution. Project implementation in small scale without fully depending on the financial support from the government and main stakeholders is the advantage of neighborhood regeneration. This enables the improving and upgrading of living conditions to be ongoing even during the economy downturn. In addition to that, there will be no specific selection on the development areas as the entire nation share the similar opportunity to upgrade and to improve their neighborhood. This is important to narrow the income disparities in urban. The objective of this paper is to review and to summarize the urban regeneration in developed countries with the focus on Korea, Singapore and Hong Kong. The aim is to determine the direction of sustainable urban regeneration in Malaysia for post-Vision 2020 through the introduction of neighborhood regeneration. This paper is conducted via literature review and observations in those selected countries. In conclusion, neighborhood regeneration shall be one of the approach of sustainable urban regeneration in Malaysia. A few criteria have been identified and to be recommended for the adaptation in Malaysia.

Keywords: area-based regeneration, public participation, sustainable urban regeneration, urban redevelopment

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

Abstract:

In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Stefan Kurbatfinski, Aliyah Dosani, Andrew F. Hayes, Deborah Dewey, Nicole Letourneau

Abstract:

Background: Maternal adverse childhood experiences (ACEs) have been associated with internalizing and externalizing behavioral problems in preschool children. However, little is known about the influence of maternal adult attachment patterns on this association. Further, potential moderation by maternal mental health, maternal social support, or child sex is poorly understood. Therefore, this study examined associations between 1) maternal ACEs and preschool children’s behavioural problems, with mediation through maternal attachment patterns and moderation by maternal mental health, maternal social support, and child sex; and 2) maternal attachment patterns and children’s behavioural problems, with mediation through maternal mental health and social support and moderation by child sex. Methods: This secondary analysis used data (n=625) from a high socioeconomic, longitudinally prospective cohort (Alberta Pregnancy Outcomes and Nutrition). Child behaviour (BASC-2) and maternal adult attachment (ECR-Q) were measured at five years of child age, maternal ACEs (ACEs Questionnaire) at around 12 months, and maternal mental health (CESD and SCL-90-R) and social support (SSQ) across various prenatal and postnatal time points. All moderation and mediation analyses occurred through RStudio using PROCESS, interpreting significant interactions through Johnson-Neyman plots. Findings: Maternal ACEs interacted with maternal anxiety symptoms to predict both behavioural problems (pexternalizing=0.007; pinternalizing=0.0159). An indirect pathway via dismissive attachment was moderated by maternal social support ([0.0058, 0.0596]). Attachment patterns predicted all behavioural problems (p<0.05) and interacted with maternal anxiety symptoms to predict internalizing behaviours among male children ([0.0321, 0.1307]; [0.0321, 0.1291]). Interpretation: Maternal attachment patterns may predict children’s behavioural problems more than ACEs. Social support interventions may not always be beneficial for highly dismissively attached mothers. Implications for policy and child health include mandatory sex and gender education for teachers; assessing attachment patterns prior to recommending social support as an intervention; and anxiety-focused interventions for mothers in higher socioeconomic populations.

Keywords: maternal adverse childhood experiences, internalizing behaviours, externalizing behaviours, mediators and moderators, attachment patterns, child health

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Authors: Eng. M. Ahmed, A. Ibrahim, M. Ashour

Abstract:

One of the major concerns facing dam is the repair of their structures to prevent the seepage under them. In previous years, many existing dams have been treated by grouting, but with varying degrees of success. One of the major reasons for this erratic performance is the unsuitable selection of the grouting materials to reduce the seepage. Grouting is an effective way to improve the engineering properties of the soil and strengthen of the permeability of the soil to reduce the seepage. The purpose of this paper is to focus on the efficiency of current available grouting materials and techniques from construction, environmental and economical point of view. The seepage reduction usually accomplished by either chemical grouting or cementious grouting using ultrafine cement. In addition, the study shows a comparison between grouting materials according to their degree of permeability reduction and cost. The application of seepage reduction is based on the permeation grouting using grout curtain installation. The computer program (SEEP/W) is employed to model a dam rested on sandy soil, using grout curtain to reduce seepage quantity and hydraulic gradient by different grouting materials. This study presents a relationship that takes into account the permeability of the soil, grout curtain spacing and a new performance parameter that can be used to predict the best selection of grouting materials for seepage reduction.

Keywords: seepage, sandy soil, grouting, permeability

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Authors: Bintou Jobe

Abstract:

The construction sector, both in the United Kingdom (UK) and developing Anglophone West African countries, specifically The Gambia, is facing significant health and safety challenges. While the UK has established legislation and regulations to support Occupational Health and Safety (OHS) in the industry, the same level of support is lacking in developing countries. The significance of this review is to assess the extent and effectiveness of OHS legislation and regulatory reform in the construction industry, with a focus on understanding the challenges faced by both the UK and developing Anglophone West African countries. It aims to highlight the benefits of implementing an OHS management system, specifically ISO 45001. This study uses a literature review approach, synthesizing publications from the past decade and identifying common themes and best practices related to Occupational Health and Safety in the construction industry. Findings were analysed, compared, and conclusions and recommendations were drawn after developing research questions and addressing them. This comprehensive review of the literature allows for a detailed understanding of the challenges faced by the industry in both contexts. The findings of the study indicate that while the UK has established robust health and safety legislation, many UK construction companies have not fully met the standards outlined in ISO 45001. These challenges faced by the UK include poor data management, inadequate communication of best practices, insufficient training, and a lack of safety culture mirroring those observed in the developing Anglophone countries. Therefore, compliance with OHS management systems has been shown to yield benefits, including injury prevention and centralized health and safety documentation. In conclusion, the effectiveness of OHS legislation for developing Anglophone West African countries should consider the positive impact experienced by the UK. The implementation of ISO 45001 can serve as a benchmark standard and potentially inform recommendations for developing countries. The selection criteria for literature include search keywords and phrases, such as occupational health and safety challenges, The Gambia, developing countries management systems, ISO 45001, and impact and effectiveness of OHS legislation. The literature was sourced from Google Scholar, the UK Health and Safety Executive websites, and Google Advanced Search.

Keywords: ISO 45001, developing countries, occupational health and safety, UK

Procedia PDF Downloads 101