Search results for: Knowledge engineering framework

Authors: Yi Yang, Jiasong Sun

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Almost every aspect of our daily lives is now intertwined with some degree of Human-Computer Interaction (HCI). HCI courses draw on knowledge from disciplines as diverse as computer science, psychology, design principles, anthropology and more. The HCI courses in the Department of Electronics at Tsinghua University, known as the Media and Cognition course, is constantly updated to reflect the most advanced technological advances, such as virtual reality, augmented reality and artificial intelligence-based interaction. For more than a decade, this course has used an interest-based approach to teaching, in which students proactively propose some research-based questions and collaborate with teachers, using course knowledge to explore potential solutions. Semantic communication plays a key role in facilitating understanding and interaction between users and computer systems, ultimately enhancing system usability and user experience. The advancements in AI-generated technology, which has gained significant attention from both academia and industry in recent years, are exemplified by language models like GPT-3 that generate human-like dialogues from given prompts. The latest version of the HCI course practices a semantic communication platform based on AI-generated techniques. We explored a student-centered model and proposed an interest-based teaching method. Students are no longer just recipients of knowledge, but become active participants in the learning process driven by personal interests, thereby encouraging students to take responsibility for their own education. One of the latest results of this teaching approach in the course "Media and Cognition" is a student proposal to develop a semantic communication platform rooted in artificial intelligence generative technologies. The platform solves a key challenge in communications technology: the ability to preserve visual signals. The interest-based approach emphasizes personal curiosity and active participation, and the proposal of an artificial intelligence-generated semantic communication platform is an example and successful result of how students can exert greater creativity when they have the power to control their own learning.

Keywords: Human-computer interaction, media and cognition course, semantic communication, retain ability, prompts.

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Authors: Hamed Fawareh

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The recent development in learning technologies leads to emerge many learning management systems (LMS). In this study, we concentrate on the specifications and characteristics of LMSs. Furthermore, this paper emphasizes on the feature of e-learning management systems. The features take on the account main indicators to assist and evaluate the quality of e-learning systems. The proposed indicators based of ten dimensions.

Keywords: E-Learning, System Requirement, Social Requirement, Learning Management System.

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Authors: S. Khosravi, A. Afshar, F. Barazandeh

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In this study we propose a novel monitor hydraulic automatic gauge control (HAGC) system based on fuzzy feedforward controller. This is used in the development of cold rolling mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in the entry steel strip. The proposed method uses a mathematical model of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In order to improve the speed of the controller in rejecting disturbances introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.

Keywords: Fuzzy feed-forward controller, monitor HAGC system, dynamic mathematical model, entry strip thickness deviation compensation

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Authors: Mahnaz Mahmoudi Zarandi (Qazvin Islamic Azad University)

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wind catchers have been served as a cooling system, used to provide acceptable ventilation by means of renewable energy of wind. In the present study, the city of Yazd in arid climate is selected as case study. From the architecture point of view, learning about wind catchers in this study is done by means of field surveys. Research method for selection of the case is based on random form, and analytical method. Wind catcher typology and knowledge of relationship governing the wind catcher's architecture were those measures that are taken for the first time. 53 wind catchers were analyzed. The typology of the wind-catchers is done by the physical analyzing, patterns and common concepts as incorporated in them. How the architecture of wind catcher can influence their operations by analyzing thermal behavior are the archetypes of selected wind catchers. Calculating fluids dynamics science, fluent software and numerical analysis are used in this study as the most accurate analytical approach. The results obtained from these analyses show the formal specifications of wind catchers with optimum operation in Yazd. The knowledge obtained from the optimum model could be used for design and construction of wind catchers with more improved operation

Keywords: Fluent Software, Iranian architecture, wind catcher

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Authors: M. Govindarajan, R. M. Chandrasekaran

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Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.

Keywords: Back propagation, classification accuracy, textmining, time complexity.

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Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

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The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg⋅m- 3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg·m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: Biodiesel, Correlation, Density, Equation of state, Prediction.

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Authors: A. Elbaz, K. Spang

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Infrastructure projects are often subjected to delays and cost overruns and mistakenly described as unsuccessful projects. These projects have many peculiarities such as public attention, impact on the environment, subjected to special regulations, etc. They also deal with several stakeholders with different motivations and face unique risks. With this in mind we need to reconsider our approach to manage them, define their success factors and implement these success factors. Infrastructure projects are not only lacking a unified meaning of project success or a definition of success factors, but also a clear method to implement these factors. This paper investigates this gap and introduces a concept to implement success factors in an efficient way, taking into consideration the specific characteristics of infrastructure projects. This concept consists of six enablers such as project organization, project team, project management workflow, contract management, communication and knowledge transfer and project documentations. These enablers allow other success factors to be efficiently implemented in projects. In conclusion, this paper provides project managers as well as company managers with a tool to define and implement success factors efficiently in their projects, along with upgrading their assets for the coming projects. This tool consists of processes and validated checklists to ensure the best use of company resources and knowledge. Due to the special features of infrastructure projects this tool will be tested in the German infrastructure market. However, it is meant to be adaptable to other markets and industries.

Keywords: Infrastructure projects, enablers, project success, success factors, transportation projects.

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Authors: Muritala Babatunde Hassan

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In the contemporary global political economy, foreign direct investment (FDI) is gaining currency on daily basis. Notably, the end of the Cold War has brought about the dominance of neoliberal ideology with its mantra of private-sector-led economy. As such, nation-states now see FDI attraction as an important element in their approach to national development. Governments and policy makers are preoccupying themselves with unraveling the best strategies to not only attract more FDI but also to attain the desired socio-economic development status. In Nigeria, the perceived development potentials of FDI have brought about aggressive hunt for foreign investors, most especially since transition to civilian rule in May 1999. Series of liberal and market oriented strategies are being adopted not only to attract foreign investors but largely to stimulate private sector participation in the economy. It is on this premise that this study interrogates the politics of FDI attraction for domestic development in Nigeria between 1999 and 2014, with the ultimate aim of examining the nexus between regime type and the ability of a state to attract and benefit from FDI. Building its analysis within the framework of institutional utilitarianism, the study posits that the essential FDI strategies for achieving the greatest happiness for the greatest number of Nigerians are political not economic. Both content analysis and descriptive survey methodology were employed in carrying out the study. Content analysis involves desk review of literatures that culminated in the development of the study’s conceptual and theoretical framework of analysis. The study finds no significant relationship between transition to democracy and FDI inflows in Nigeria, as most of the attracted investments during the period of the study were market and resource seeking as was the case during the military regime, thereby contributing minimally to the socio-economic development of the country. It is also found that the country placed much emphasis on liberalization and incentives for FDI attraction at the neglect of improving the domestic investment environment. Consequently, poor state of infrastructure, weak institutional capability and insecurity were identified as the major factors seriously hindering the success of Nigeria in exploiting FDI for domestic development. Given the reality of the currency of FDI as a vector of economic globalization and that Nigeria is trailing the line of private-sector-led approach to development, it is recommended that emphasis should be placed on those measures aimed at improving the infrastructural facilities, building solid institutional framework, enhancing skill and technological transfer and coordinating FDI promotion activities by different agencies and at different levels of government.

Keywords: Foreign capital, politics, socio-economic development, FDI attraction strategies, Redemocratization.

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Authors: L. A. Muhammad, M. S. Argungu

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Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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Authors: Amir Farkhonde

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The major objective of this study was to devise a method for solving mathematical problems. Three concepts including faculty of understanding, faculty of guess, and free mind or beginner's mind provided the foundation for this method. An explanatory approach along with a hermeneutic process was taken in this study to support the assumption that mathematical knowledge is constantly developing and it seems essential for students to solve math problems on their own using their faculty of understanding (interpretive dialogue) and faculty of guess. For doing so, a kind of movement from the mathematical problem to mathematical knowledge should be adopted for teaching students a new math topic. The research method of this paper is review, descriptive and conception development. This paper first reviews the research findings on the NRICH’S project (NRICH is part of the family of activities in the Millennium Mathematics Project) with the aim that these findings form the theoretical basis of the problem-solving method. Then, the curriculum, the conceptual structure of the new method, how to design the problem and an example of it are discussed. In this way, students are immersed in the story of discovering and understanding the problem formula, and interpretive dialogue with the text continues by following the questions posed by the problem and constantly reconstructing the answer to find a formula or solution to solve the problem.

Keywords: Interpretive dialogue, NRICH, inventing, a method of problem solving.

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Authors: N. Hammid, F. Bouarab-Dahmani, T. Berkane

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Since its appearance, the MOOC (massive open online course) is gaining more and more intention of the educational communities over the world. Apart from the current MOOCs design and purposes, the creators of MOOC focused on the importance of the connection and knowledge exchange between individuals in learning. In this paper, we present a conceptual model for massive open online blended courses where teachers over the world can collaborate and exchange their experience to get a common efficient content designed as a MOOC opened to their students to live a better learning experience. This model is based on disciplines’ concepts capitalization and the detection of the obstacles met by their students when faced with problem situations (exercises, projects, case studies, etc.). This detection is possible by analyzing the frequently of semantic errors committed by the students. The participation of teachers in the design of the course and the attendance by their students can guarantee an efficient and extensive participation (an important number of participants) in the course, the learners’ motivation and the evaluation issues, in the way that the teachers designing the course assess their students. Thus, the teachers review, together with their knowledge, offer a better assessment and efficient connections to their students.

Keywords: MOOC, Massive Open Online Courses, Online learning, E-learning, Blended learning.

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Authors: K. Durairaj, I. N. Umar

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Lately, asynchronous discussion forum is integrated in higher educational institutions as it may increase learning process, learners’ understanding, achievement and knowledge construction. The asynchronous discussion forum is used to complement the traditional, face-to-face learning session in hybrid learning courses. However, studies have proven that students’ engagement in online forums is still unconvincing. Thus, the aim of this study is to investigate the motivating factors and obstacles that affect the learners’ engagement in asynchronous discussion forum. This study is carried out in one of the public higher educational institutions in Malaysia with 18 postgraduate students as samples. The authors have developed a 40-items questionnaire based on literature review. The results indicate several factors that have encouraged or limited students’ engagement in asynchronous discussion forum: (a) the practices or behaviors of peers, or instructors, (b) the needs for the discussions, (c) the learners’ personalities, (d) constraints in continuing the discussion forum, (e) lack of ideas, (f) the level of thoughts, (g) the level of knowledge construction, (h) technical problems, (i) time constraints and (j) misunderstanding. This study suggests some recommendations to increase the students’ engagement in online forums. Finally, based upon the findings, some implications are proposed for further research.

Keywords: Asynchronous Discussion Forum, Engagement, Factors, Motivating, Limiting.

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Javier Araluce, Joshué Pérez

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, this paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for in-depth gesture classification. This tandem of MediaPipe’s extraction prowess and MPL’s analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System 2 (ROS2), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real-vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: Gesture detection, MediaPipe, MultiLayer Perceptron Layer, Robot Operating System.

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Authors: K. Shimola, M. Krishnaveni

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This paper examines vulnerability assessment of water resources in a semi-arid basin using the 4-step approach. The vulnerability assessment framework is developed to study the water resources vulnerability which includes the creation of GIS-based vulnerability maps. These maps represent the spatial variability of the vulnerability index. This paper introduces the 4-step approach to assess vulnerability that incorporates a new set of indicators. The approach is demonstrated using a framework composed of a precipitation data for (1975–2010) period, temperature data for (1965–2010) period, hydrological model outputs and the water resources GIS data base. The vulnerability assessment is a function of three components such as exposure, sensitivity and adaptive capacity. The current water resources vulnerability is assessed using GIS based spatio-temporal information. Rainfall Coefficient of Variation, monsoon onset and end date, rainy days, seasonality indices, temperature are selected for the criterion ‘exposure’. Water yield, ground water recharge, evapotranspiration (ET) are selected for the criterion ‘sensitivity’. Type of irrigation and storage structures are selected for the criterion ‘Adaptive capacity’. These indicators were mapped and integrated in GIS environment using overlay analysis. The five sub-basins, namely Arjunanadhi, Kousiganadhi, Sindapalli-Uppodai and Vallampatti Odai, fall under medium vulnerability profile, which indicates that the basin is under moderate stress of water resources. The paper also explores prioritization of sub-basinwise adaptation strategies to climate change based on the vulnerability indices.

Keywords: Adaptive capacity, exposure, overlay analysis, sensitivity, vulnerability.

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Authors: Mona Soliman Habib

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This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: Sawarni Hasibuan, Juliza Hidayati

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Competitiveness and sustainability issues not only put pressure on big companies, but also small and medium enterprises (SMEs). SMEs Batik Bogor is one of the local culture-based creative industries in Bogor city which is also dealing with the issue of sustainability. The purpose of this research is to develop framework of sustainability at SMEs Batik Indonesia case of SMEs Batik Bogor by integrating innovation of cleaner production in its supply chain. The approach used is desk study, field survey, in-depth interviews, and benchmarking best practices of SMEs sustainability. In-depth interviews involve stakeholders to identify the needs and standards of sustainability of SMEs Batik. Data analysis was done by benchmarking method, Multi Dimension Scaling (MDS) method, and Strength, Weakness, Opportunity, Threat (SWOT) analysis. The results recommend the framework of sustainability for SMEs Batik in Indonesia. The sustainability status of SMEs Batik Bogor is classified as Moderate Sustainable. Factors that support the sustainability of SMEs Batik Bogor such is a strong commitment of top management in adopting cleaner production innovation and creativity approach. Successful cleaner production innovations are implemented primarily in the substitution of dye materials from toxic to non-toxic, reducing the intensity of non-renewable energy use, as well as the reuse and recycle of solid waste. “Mosaic Batik” is one of the innovations of solid waste utilization of batik waste produced by company R&D center that gives benefit to three pillars of sustainability, that is financial benefit, environmental benefit, and social benefit. The sustainability of SMEs Batik Bogor cannot be separated from the support of Bogor City Government which proactively facilitates the promotion of sustainable innovation produced by SMEs Batik Bogor.

Keywords: Cleaner production innovation, creativity, SMEs Batik, sustainability supply chain.

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Authors: Hui Fang Huang Su, Jia Borror

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This study compared two different interventions for math instruction among preschoolers with autism spectrum disorder (ASD). The first intervention, a combination of discrete trial teaching and Strategies for Teaching Based on Autism Research (STAR), was the regular math curriculum utilized at the preschool. The second activity-based, naturalistic intervention was Project Mind, also known as Math is Not Difficult. The curricular interventions were randomly assigned to four preschool classrooms with ASD students and implemented over three months for Project MIND. Measurements gained during the same three months for the STAR intervention were used. A quasi-experimental, pre-test/post-test design was selected to compare which intervention was the most effective in increasing mathematical knowledge and skills among preschoolers with ASD. Standardized pre and post-test instruments included the Bracken Basic Concept Scale-3 Receptive, the Applied Problems and Calculation subtests of the Woodcock-Johnson IV Tests of Achievement, and the TEMA 3: Test of Early Mathematics Ability – Third Edition. The STAR assessment is typically administered to all preschoolers at the study site three times per year, and those results were used in this study. We anticipated that the implementation of these two approaches would lead to improvement in the mathematical knowledge and skills of children with ASD. Still, it is essential to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: Autism, mathematics, preschool, special education.

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Authors: A. Habibizad Navin, A. Sadighi, M. Naghian Fesharaki, M. Mirnia, M. Teshnelab, R. Keshmiri

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This paper presents a new data oriented model of image. Then a representation of it, ADBT, is introduced. The ability of ADBT is clustering, segmentation, measuring similarity of images etc, with desired precision and corresponding speed.

Keywords: Data oriented modelling, image, clustering, segmentation, classification, ADBT and image processing.

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Authors: L. Dixon, D. Gavani

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Objective: Sharing devastating news with patients is often considered the most difficult task of doctors. This study aimed to explore patients’ perceptions of receiving bad news including which features improve the experience and which areas need refining. Methods: A questionnaire was written based on the steps of the SPIKES model for breaking bad new. 20 patients receiving treatment for a hematological malignancy completed the questionnaire. Results: Overall, the results are promising as most patients praised their consultation. ‘Poor’ was more commonly rated by women and participants aged 45-64. The main differences between the ‘excellent’ and ‘poor’ consultations include the doctor’s sensitivity and checking the patients’ understanding. Only 35% of patients were asked their existing knowledge and 85% of consultations failed to discuss the impact of the diagnosis on daily life. Conclusion: This study agreed with the consensus of existing literature. The commended aspects include consultation set-up and information given. Areas patients felt needed improvement include doctors determining the patient’s existing knowledge and checking new information has been understood. Doctors should also explore how the diagnosis will affect the patient’s life. With a poorer prognosis, doctors should work on conveying appropriate hope. The study was limited by a small sample size and potential recall bias.

Keywords: Communication, diagnosis, hematology, patients.

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Authors: E. Cenderelli, E. Bruno, G. Iacoviello, A. Lazzini

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The financial sector is exposed to the risk of cyber-attacks like any other industrial sector. Furthermore, the topic of CybeRisk (cyber risk) has become particularly relevant given that Information Technology (IT) attacks have increased drastically in recent years, and cannot be stopped by single organizations requiring a response at international and national level. IT risk is never a matter purely for the IT manager, although he clearly plays a key role. A bank's risk management function requires a thorough understanding of the evolving risks as well as the tools and practical techniques available to address them. Upon the request of European and national legislation regarding CybeRisk in the financial system, banks are therefore called upon to strengthen the operational model for CybeRisk management. This will require an important change with a more intense collaboration with the structures that deal with information security for the development of an ad hoc system for the evaluation and control of this type of risk. The aim of the work is to propose a framework for the management and control of CybeRisk that will bridge the gap in the literature regarding the understanding and consideration of CybeRisk as an integral part of business management. The IT function has a strong relevance in the management of CybeRisk, which is perceived mainly as operational risk, but with a positive tendency on the part of risk management to the identification of CybeRisk assessment methods that are increasingly complete, quantitative and able to better describe the possible impacts on the business. The paper provides answers to the research questions: Is it possible to define a CybeRisk governance structure able to support the comparison between risk and security? How can the relationships between IT assets be integrated into a cyberisk assessment framework to guarantee a system of protection and risks control? From a methodological point of view, this research uses a case study approach. The choice of “Monte dei Paschi di Siena” was determined by the specific features of one of Italy’s biggest lenders. It is chosen to use an intensive research strategy: an in-depth study of reality. The case study methodology is an empirical approach to explore a complex and current phenomenon that develops over time. The use of cases has also the advantage of allowing the deepening of aspects concerning the "how" and "why" of contemporary events, on which the scholar has little control. The research bases on quantitative data and qualitative information obtained through semi-structured interviews of an open-ended nature and questionnaires to directors, members of the audit committee, risk, IT and compliance managers, and those responsible for internal audit function and anti-money laundering. The added value of the paper can be seen in the development of a framework based on a mapping of IT assets from which it is possible to identify their relationships for purposes of a more effective management and control of cyber risk.

Keywords: Bank, CybeRisk, information technology, risk management.

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Authors: M. Pushparani, A. Sagaya

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Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: Embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems.

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Authors: Yusuf Garba Baba

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The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: Risk identification, risk assessment, analytical hierarchical process, multi-criteria decision.

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Authors: Ke Zhao, Ballarat Colin Richardson, Jerry Courvisanos, John Crawford

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Climate change has profound consequences for the agriculture of south-eastern Australia and its climate-induced water shortage in the Murray-Darling Basin. Post Keynesian Economics (PKE) macro-dynamics, along with Kaleckian investment and growth theory, are used to develop an ecological-economic system dynamics model of this complex nonlinear river basin system. The Murray- Darling Basin Simulation Model (MDB-SM) uses the principles of PKE to incorporate the fundamental uncertainty of economic behaviors of farmers regarding the investments they make and the climate change they face, particularly as regards water ecosystem services. MDB-SM provides a framework for macroeconomic policies, especially for long-term fiscal policy and for policy directed at the sustainability of agricultural water, as measured by socio-economic well-being considerations, which include sustainable consumption and investment in the river basin. The model can also reproduce other ecological and economic aspects and, for certain parameters and initial values, exhibit endogenous business cycles and ecological sustainability with realistic characteristics. Most importantly, MDBSM provides a platform for the analysis of alternative economic policy scenarios. These results reveal the importance of understanding water ecosystem adaptation under climate change by integrating a PKE macroeconomic analytical framework with the system dynamics modelling approach. Once parameterised and supplied with historical initial values, MDB-SM should prove to be a practical tool to provide alternative long-term policy simulations of agricultural water and socio-economic well-being.

Keywords: Agricultural water, Macroeconomic dynamics, Modeling, Investment dynamics, Sustainability, Unemployment, Economics, Keynesian, Kaleckian.

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Authors: F. Farzin

Abstract:

Research has shown that techno-entrepreneurship is economically significant. Therefore, it is suggested that teaching techno-entrepreneurship may be important because such programmes would prepare current and future generations of learners to recognise and act on high-technology opportunities. Education in technoentrepreneurship may increase the knowledge of how to start one’s own enterprise and recognise the technological opportunities for commercialisation to improve decision-making about starting a new venture; also it influence decisions about capturing the business opportunities and turning them into successful ventures. Universities can play a main role in connecting and networking technoentrepreneurship students towards a cooperative attitude with real business practice and industry knowledge. To investigate and answer whether education for techno-entrepreneurs really helps, this paper choses a comparison of literature reviews as its method of research. After reviewing literature related to the impact of technoentrepreneurship education on self-employment 6 studies which had similar aim and objective to this paper were. These particular papers were selected based on a keywords search and as their aim, objectives, and gaps were close to the current research. In addition, they were all based on the influence of techno-entrepreneurship education in self-employment and intention of students to start new ventures. The findings showed that teaching techno-entrepreneurship education may have an influence on students’ intention and their future self-employment, but which courses should be covered and the duration of programmes, needs further investigation.

Keywords: Techno-entrepreneurship education, training, higher education, intention, self-employment.

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Authors: Sareh Rajabi, Taha Anjamrooz, Salwa Bheiry

Abstract:

Sustainability of construction projects is an important issue to be addressed since the sector will continue to be developed in the coming years, especially in developing countries. Thus, it is significant to discover approaches and solutions for improving sustainability. Currently, the construction industry is the largest consumer of natural resources. This is the same in other countries in the Gulf region, and the United Arab Emirates (UAE) has limited natural resources such as water, electricity, etc. Recently, the UAE has taken several actions in order to implement sustainable initiatives within its construction industry. Within the industry, the contractors’ role is significant in promoting sustainable development by taking the responsibility to minimize their negative impacts on the environment and society, and maximize their economic distribution. In this research, sustainability will be studied as an important key to bring competitive advantages to contracting organizations. The contractors should understand the need to improve their sustainable performance in order to expand their business competitiveness. Competitiveness at the construction project level refers to a contractor’s ability to compete for a project. There is less focus on how to improve contractors’ competitiveness by implementing sustainable construction practices. Based on an inclusive literature review on the relationship between sustainability performance and business competitiveness, this research will conduct a study of sustainable practice in the construction industry and the relationship between sustainability performance and business competitiveness in order to develop a framework for evaluating how contractors can improve their competitiveness in terms of more efficient processes, enhancements in productivity, and lower costs of compliance in order to reduce the initial project cost and obtain market opportunities in the UAE. The research findings will provide a framework that can be a useful guideline for contractors to develop their sustainability policy, strategy and practice for meeting the increased requirements for sustainable development in construction.

Keywords: Sustainable construction practice, sustainability, competitiveness, construction industry, contractors.

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Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

Abstract:

Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: Decision support system, event sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine.

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Authors: Ena Bhattacharyya, Zullina H. Shaari

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Till date, English as a Second Language (ESL) educators involved in teaching language and communication to engineering students face an uphill task in developing graduate communicative competency. This challenge is accentuated by the apparent lack of English for Specific Purposes (ESP) materials for engineering students in the engineering curriculum. As such, most ESL educators are forced to play multiple roles. They don tasks such as curriculum designers, material writers and teachers with limited knowledge of the disciplinary content. Previous research indicates that prospective professional engineers should possess some sub-sets of competency: technical, linguistic oral immediacy, meta-cognitive and rhetorical explanatory competence. Another study revealed that engineering students need to be equipped with technical and linguistic oral immediacy competence. However, little is known whether these competency needs are in line with the educators- perceptions of communicative competence. This paper examines the best mix of communicative competence subsets that create the magic for engineering students in technical oral presentations. For the purpose of this study, two groups of educators were interviewed. These educators were language and communication lecturers involved in teaching a speaking course and content experts who assess students- technical oral presentations at tertiary level. The findings indicate that these two groups differ in their perceptions

Keywords: Communicative competence, Content experts, Educators, Technical Oral Presentations

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Authors: Maumita Bhattacharya

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Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiency

Keywords: Meta model, Evolutionary algorithm, Stochastictechnique, Fitness function, Optimization, Support vector machine.

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Authors: Tajinder Pal Singh

Abstract:

Teaching of mathematics to engineering students is an open ended problem in education. The main goal of mathematics learning for engineering students is the ability of applying a wide range of mathematical techniques and skills in their engineering classes and later in their professional work. Most of the undergraduate engineering students and faculties feels that no efforts and attempts are made to demonstrate the applicability of various topics of mathematics that are taught thus making mathematics unavoidable for some engineering faculty and their students. The lack of understanding of concepts in engineering mathematics may hinder the understanding of other concepts or even subjects. However, for most undergraduate engineering students, mathematics is one of the most difficult courses in their field of study. Most of the engineering students never understood mathematics or they never liked it because it was too abstract for them and they could never relate to it. A right balance of application and concept based teaching can only fulfill the objectives of teaching mathematics to engineering students. It will surely improve and enhance their problem solving and creative thinking skills. In this paper, some practical (informal) ways of making mathematics-teaching application based for the engineering students is discussed. An attempt is made to understand the present state of teaching mathematics in engineering colleges. The weaknesses and strengths of the current teaching approach are elaborated. Some of the causes of unpopularity of mathematics subject are analyzed and a few pragmatic suggestions have been made. Faculty in mathematics courses should spend more time discussing the applications as well as the conceptual underpinnings rather than focus solely on strategies and techniques to solve problems. They should also introduce more ‘word’ problems as these problems are commonly encountered in engineering courses. Overspecialization in engineering education should not occur at the expense of (or by diluting) mathematics and basic sciences. The role of engineering education is to provide the fundamental (basic) knowledge and to teach the students simple methodology of self-learning and self-development. All these issues would be better addressed if mathematics and engineering faculty join hands together to plan and design the learning experiences for the students who take their classes. When faculties stop competing against each other and start competing against the situation, they will perform better. Without creating any administrative hassles these suggestions can be used by any young inexperienced faculty of mathematics to inspire engineering students to learn engineering mathematics effectively.

Keywords: Application based learning, conceptual learning, engineering mathematics, word problem.

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Authors: Faris Elghaish, Sepehr Abrishami, Mark Gaterell, Richard Wise

Abstract:

The collaboration and integration between all building information management (BIM) processes and tasks are necessary to ensure that all project objectives can be delivered. The literature review has been used to explore the state of the art BIM technologies to manage construction materials as well as the challenges which have faced the construction process using traditional methods. Thus, this paper aims to articulate a framework to integrate traditional material planning methods such as ABC analysis theory (Pareto principle) to analyse and categorise the project materials, as well as using independent material planning methods such as Economic Order Quantity (EOQ) and Fixed Order Point (FOP) into the BIM 4D, and 5D capabilities in order to articulate a dependent material planning cycle into BIM, which relies on the constructability method. Moreover, we build a model to connect between the material planning outputs and the BIM 4D and 5D data to ensure that all project information will be accurately presented throughout integrated and complementary BIM reporting formats. Furthermore, this paper will present a method to integrate between the risk management output and the material management process to ensure that all critical materials are monitored and managed under the all project stages. The paper includes browsers which are proposed to be embedded in any 4D BIM platform in order to predict the EOQ as well as FOP and alarm the user during the construction stage. This enables the planner to check the status of the materials on the site as well as to get alarm when the new order will be requested. Therefore, this will lead to manage all the project information in a single context and avoid missing any information at early design stage. Subsequently, the planner will be capable of building a more reliable 4D schedule by allocating the categorised material with the required EOQ to check the optimum locations for inventory and the temporary construction facilitates.

Keywords: Building information management, BIM, economic order quantity, fixed order point, BIM 4D, BIM 5D.

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