Search results for: learning challenges

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: Personal information, deep learning, auto fill, NLP, document analysis.

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Authors: S. Tarighat, F. Shateri

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This study explored the relationship between L2 Willingness to Communicate (WTC) of bilinguals and monolinguals in a foreign language using a snowball sampling method to collect questionnaire data from 200 bilinguals and monolinguals studying a foreign language (FL). The results indicated a higher willingness to communicate in a foreign language (WTC-FL) performed by bilinguals compared to that of the monolinguals with a weak significance. Yet a stronger significance was found in the relationship between the age of onset of bilingualism and WTC-FL. The researcher proposed that L2 WTC is indirectly influenced by knowledge of other languages, which can boost L2 confidence and reduce L2 anxiety and consequently lead to higher L2 WTC when learning a different L2. The study also found the age of onset of bilingualism to be a predictor of L2 WTC when learning a FL. The results emphasize the importance of bilingualism and early bilingualism in particular.

Keywords: Bilingualism, foreign language learning, L2 acquisition, willingness to communicate.

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Authors: A. Bey, T. Bensebaa, H. Benselem

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This paper attempts to explore a new method to improve the teaching of algorithmic for beginners. It is well known that algorithmic is a difficult field to teach for teacher and complex to assimilate for learner. These difficulties are due to intrinsic characteristics of this field and to the manner that teachers (the majority) apprehend its bases. However, in a Technology Enhanced Learning environment (TEL), assessment, which is important and indispensable, is the most delicate phase to implement, for all problems that generate (noise...). Our objective registers in the confluence of these two axes. For this purpose, EASEL focused essentially to elaborate an assessment approach of algorithmic competences in a TEL environment. This approach consists in modeling an algorithmic solution according to basic and elementary operations which let learner draw his/her own step with all autonomy and independently to any programming language. This approach assures a trilateral assessment: summative, formative and diagnostic assessment.

Keywords: Algorithmic, assessment of competences, Technology Enhanced Learning (TEL).

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Authors: Kuo Hung Huang, Chong-Ji Ke

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The purpose of this study is to explore the impacts of computer games on the mathematics instruction. First, the research designed and implemented the web-based games according to the content of existing textbook. And the researcher collected and analyzed the information related to the mathematics instruction integrating the computer games. In this study, the researcher focused on the learning motivation of mathematics, mathematics achievement, and pupil-teacher interactions in classroom. The results showed that students under instruction integrating computer games significantly improved in motivation and achievement. The teacher tended to use less direct teaching and provide more time for student-s active learning.

Keywords: computer games, mathematics instruction, pupil-teacher interaction, technology-enhanced learning

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline which ensures that data mirrors real-world settings by incorporating gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification and explainability in a single pipeline called DeClEx.

Keywords: Machine learning, healthcare, classification, explainability.

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: Drive test, LTE, machine learning, uplink throughput prediction.

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Authors: Fiona Wahr, Sitalakshmi Venkatraman

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Industry employers require new graduates to bring with them a range of knowledge, skills and abilities which mean these new employees can immediately make valuable work contributions. These will be a combination of discipline and professional knowledge, skills and abilities which give graduates the technical capabilities to solve practical problems whilst interacting with a range of stakeholders. Underpinning the development of these disciplines and professional knowledge, skills and abilities, are “enabling” knowledge, skills and abilities which assist students to engage in learning. These are academic and learning skills which are essential to common starting points for both the learning process of students entering the course as well as forming the foundation for the fully developed graduate knowledge, skills and abilities. This paper reports on a project created to introduce and strengthen these enabling skills into the first semester of a Bachelor of Information Technology degree in an Australian polytechnic. The project uses an action research approach in the context of ongoing continuous improvement for the course to enhance the overall learning experience, learning sequencing, graduate outcomes, and most importantly, in the first semester, student engagement and retention. The focus of this is implementing the new curriculum in first semester subjects of the course with the aim of developing the “enabling” learning skills, such as literacy, research and numeracy based knowledge, skills and abilities (KSAs). The approach used for the introduction and embedding of these KSAs, (as both enablers of learning and to underpin graduate attribute development), is presented. Building on previous publications which reported different aspects of this longitudinal study, this paper recaps on the rationale for the curriculum redevelopment and then presents the quantitative findings of entering students’ reading literacy and numeracy knowledge and skills degree as well as their perceived research ability. The paper presents the methodology and findings for this stage of the research. Overall, the cohort exhibits mixed KSA levels in these areas, with a relatively low aggregated score. In addition, the paper describes the considerations for adjusting the design and delivery of the new subjects with a targeted learning experience, in response to the feedback gained through continuous monitoring. Such a strategy is aimed at accommodating the changing learning needs of the students and serves to support them towards achieving the enabling learning goals starting from day one of their higher education studies.

Keywords: Enabling skills, student retention, embedded learning support, continuous improvement.

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Authors: Ashly Joseph, Jithu Paulose

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Large language models (LLMs) have revolutionized natural language processing capabilities, enabling applications such as chatbots, dialogue agents, image, and video generators. Nevertheless, their trainings on extensive datasets comprising personal information poses notable privacy and safety hazards. This study examines methods for addressing these challenges, specifically focusing on approaches to enhance the security of LLM outputs, safeguard user privacy, and adhere to data protection rules. We explore several methods including post-processing detection algorithms, content filtering, reinforcement learning from human and AI inputs, and the difficulties in maintaining a balance between model safety and performance. The study also emphasizes the dangers of unintentional data leakage, privacy issues related to user prompts, and the possibility of data breaches. We highlight the significance of corporate data governance rules and optimal methods for engaging with chatbots. In addition, we analyze the development of data protection frameworks, evaluate the adherence of LLMs to General Data Protection Regulation (GDPR), and examine privacy legislation in academic and business policies. We demonstrate the difficulties and remedies involved in preserving data privacy and security in the age of sophisticated artificial intelligence by employing case studies and real-life instances. This article seeks to educate stakeholders on practical strategies for improving the security and privacy of LLMs, while also assuring their responsible and ethical implementation.

Keywords: Data privacy, large language models, artificial intelligence, machine learning, cybersecurity, general data protection regulation, data safety.

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD.

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Authors: A. M. Sultana, Norhirdawati. M. Zahir, Norzalan. H. Yaacob

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Recently in Malaysia, women's participation in teaching profession has increased. The increasing trend of women’s participation in the teaching profession poses challenges in families, especially in the developing countries like Malaysia. One of these challenges, concerns in balancing their role between family and job responsibility that faced by many women teachers. The purpose of this study is to discover how women teachers' impact on family happiness and the challenges faced by them in balancing their role between family and job responsibility. The findings presented in this study are based on survey research in a secondary school Dato’ Bijaya Setia in the district of Gugusan Manjoi which is located in Kedah, Malaysia. The study found that employment of women in economic activity has several beneficial impacts of improving the economic condition of the family. The results also revealed that in low income earning families, both husbands and wives’ employment contribute to the family income that less likely to experience of family poverty. The study also showed despite women's teachers’ significant role towards the overall development of the family, the majority of women teachers encountered a number of difficulties in balancing their role between family and job responsibility especially when they need to work more than the normal working time. Therefore, it is common for the majority of women suffering from psychological stress when they are unable to complete the task at a fixed time. The present study also suggests implication of family friendly policy and its appropriate practice to support the women teachers who are significantly contributing to family, community and the country.

Keywords: Emotional exhaustion, Family friendly policy, Work family conflict, Women Teacher.

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Authors: Tamara Djurickovic MSc

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Internet today has a huge impact on all aspects of life, and also in the area of the broader context of democracy, politics and politicians. If democracy is freedom of choice, there are a number of conditions that can ensure in practice the freedom to be achieved and realized. These preconditions must be achieved regardless of the manner of voting. The key contribution of ICT to achieve freedom of choice is that technology enables the correlation of the citizens and elected representatives on the better way than it was possible without the Internet. In this sense, we can say that the Internet and ICT are changing significantly, and potentially improving the environment in which democratic processes are taking place. This paper aims to describe trends in use of ICT in democratic processes, and analyzes the challenges for implementation of e-Democracy in Montenegro

Keywords: About four key words or phrases in alphabetical order, separated by commas.

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Authors: Shilpy Sharma

Abstract:

As the web continues to grow exponentially, the idea of crawling the entire web on a regular basis becomes less and less feasible, so the need to include information on specific domain, domain-specific search engines was proposed. As more information becomes available on the World Wide Web, it becomes more difficult to provide effective search tools for information access. Today, people access web information through two main kinds of search interfaces: Browsers (clicking and following hyperlinks) and Query Engines (queries in the form of a set of keywords showing the topic of interest) [2]. Better support is needed for expressing one's information need and returning high quality search results by web search tools. There appears to be a need for systems that do reasoning under uncertainty and are flexible enough to recover from the contradictions, inconsistencies, and irregularities that such reasoning involves. In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view algorithms, which reduce the amount of labeled data required for learning, rely on the assumptions that the views are compatible and uncorrelated. This paper describes the use of semi-structured machine learning approach with Active learning for the “Domain Specific Search Engines". A domain-specific search engine is “An information access system that allows access to all the information on the web that is relevant to a particular domain. The proposed work shows that with the help of this approach relevant data can be extracted with the minimum queries fired by the user. It requires small number of labeled data and pool of unlabelled data on which the learning algorithm is applied to extract the required data.

Keywords: Search engines; machine learning, Informationretrieval, Active logic.

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Authors: F. Havas Beigi, E. Mohammadi, M.Vafaee Yeganeh

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Curriculum is one of the most important inputs in higher education system and for knowing the strong and weak spots of it we need evaluation. The main purpose of this study was to survey of the curriculum quality of Insurance Management field. Case: University of Allameh Taba Tabaee(according to view point of students,alumni,employer and faculty members).Descriptive statistics (mean, tables, percentages, frequency distribution) and inferential statistics (CHI SQUARE) were used to analyze the data. Six criterions considered for the Quality of curriculum: objectives, content, teaching and learning methods, space and facilities, Time, assessment of learning. objectives, teaching and learning methods criterions was desirable level, content criteria was undesirable level, space and facilities, time and assessment of learning were rather desirable level. The quality of curriculum of insurance management field was relatively desirable level.

Keywords: Quality, curriculum, insurance management, higher education.

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Authors: Tim Klemke, Peter Nyhuis

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In today-s turbulent environment, companies are faced with two principal challenges. On the one hand, it is necessary to produce ever more cost-effectively to remain competitive. On the other hand, factories need to be transformable in order to manage unpredictable changes in the corporate environment. To deal with these different challenges, companies use the philosophy of lean production in the first case, in the second case the philosophy of transformability. To a certain extent these two approaches follow different directions. This can cause conflicts when designing factories. Therefore, the Institute of Production Systems and Logistics (IFA) of the Leibniz University of Hanover has developed a procedure to allow companies to evaluate and design their factories with respect to the requirements of both philosophies.

Keywords: Factory planning, lean production, transformability

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Authors: Robin Lok-Wang

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The purpose of this paper is to investigate how engineering students’ motivation and interests are maintained through a project-based course in their lifelong learning journeys. In recent years, different pedagogies of teaching including entrepreneurship, experiential and lifelong learnings as well as dream builder, etc., have been widely used for education purpose. University advocates hands-on practice, learning by experiencing and experimenting throughout different courses. Students are not limited to gain knowledge via traditional lectures, laboratory demonstration, tutorial and so on. The capabilities to identify both complex problems and its corresponding solutions in daily lives are one of the criteria/skill sets required for graduates to obtain their careers at professional organizations and companies. A project-based course, namely Mechatronic Design and Prototyping, was developed for students to design and build a physical prototype for solving existing problems in their daily lives, thereby encouraging them as an entrepreneur to explore further possibilities to commercialize their designed prototypes and launch it to the market. Feedbacks from students show that they are keen to propose their own ideas freely with guidance from instructor instead of using either suggested or assigned topics. Proposed ideas of the prototypes reflect that if students’ interests are maintained, they acquire the knowledges and skills they need, including essential communication, logical thinking and more importantly problem solving for their lifelong learning journey.

Keywords: Problem solving, lifelong learning, entrepreneurship, mechanical engineering.

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Authors: Eli Hustad, Aurilla A. Bechina

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The purpose of this research is to increase our knowledge as regards how Small-and-Medium-Sized Enterprises (SMEs) tackle ERP implementation projects to achieve successful adoption and use of these systems within the organization. SMEs have scare resources to handle these kinds of projects which have proved to be risky and costly. There are several studies focusing on ERP implementation in larger companies, however, few studies report on challenges experienced by SMEs. Our research seeks to bridge this gap. Through a multiple case study of four companies, we identified challenges and critical elements within the different phases (pre-implementation, implementation and post-implementation) of the ERP life cycle. To interpret our findings, we utilize a well-know ERP life cycle model and critical success factors developed for larger companies which are reported in former research literature. We discuss if these models are relevant for SMEs and suggest additional critical elements identified in this study to make a framework more adapted to the SME context.

Keywords: ERP implementation challenges, ERP implementation framework, ERP life cycle model, Small-and- Medium-Sized Enterprises, ERP critical success factors

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Authors: W. S. Barber, S. L. King

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This paper is a qualitative case study analysis of the development of a fully online learning community of graduate students through arts-based community building activities. With increasing numbers and types of online learning spaces, it is incumbent upon educators to continue to push the edge of what best practices look like in digital learning environments. In digital learning spaces, instructors can no longer be seen as purveyors of content knowledge to be examined at the end of a set course by a final test or exam. The rapid and fluid dissemination of information via Web 3.0 demands that we reshape our approach to teaching and learning, from one that is content-focused to one that is process-driven. Rather than having instructors as formal leaders, today’s digital learning environments require us to share expertise, as it is the collective experiences and knowledge of all students together with the instructors that help to create a very different kind of learning community. This paper focuses on innovations pursued in a 36 hour 12 week graduate course in higher education entitled “Critical and Reflective Practice”. The authors chronicle their journey to developing a fully online learning community (FOLC) by emphasizing the elements of social, cognitive, emotional and digital spaces that form a moving interplay through the community. In this way, students embrace anywhere anytime learning and often take the learning, as well as the relationships they build and skills they acquire, beyond the digital class into real world situations. We argue that in order to increase student online engagement, pedagogical approaches need to stem from two primary elements, both creativity and critical reflection, that are essential pillars upon which instructors can co-design learning environments with students. The theoretical framework for the paper is based on the interaction and interdependence of Creativity, Intuition, Critical Reflection, Social Constructivism and FOLCs. By leveraging students’ embedded familiarity with a wide variety of technologies, this case study of a graduate level course on critical reflection in education, examines how relationships, quality of work produced, and student engagement can improve by using creative and imaginative pedagogical strategies. The authors examine their professional pedagogical strategies through the lens that the teacher acts as facilitator, guide and co-designer. In a world where students can easily search for and organize information as self-directed processes, creativity and connection can at times be lost in the digitized course environment. The paper concludes by posing further questions as to how institutions of higher education may be challenged to restructure their credit granting courses into more flexible modules, and how students need to be considered an important part of assessment and evaluation strategies. By introducing creativity and critical reflection as central features of the digital learning spaces, notions of best practices in digital teaching and learning emerge.

Keywords: Online, pedagogy, learning, communities.

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Authors: R. Tirado, G. Habert, A. Mailhac, S. Laurenceau

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The rapid development of cities implies significant material inflows and outflows. The construction sector is one of the main consumers of raw materials and producers of waste. The waste from the building sector, for its quantity and potential for recovery, constitutes significant deposits requiring major efforts, by combining different actors, to achieve the circular economy's objectives. It is necessary to understand and know the current construction actors' knowledge of stocks, urban metabolism, deposits, and recovery practices in this context. This article aims to explore the role of local governments in planning strategies by facilitating a circular economy. In particular, the principal opportunities and challenges of communities for applying the principles of the circular economy in the building sector will be identified. The approach used for the study was to conduct semi-structured interviews with those responsible for circular economy projects within local administrations of some communities in France. The results show territories' involvement in the inclusion and application of the principles of the circular economy in the building sector. The main challenges encountered are numerous, hence the importance of having identified and described them so that the different actors can work to meet them.

Keywords: Building stock, circular economy, interview, local authorities.

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Authors: Nives Mikelic Preradovic, Damir Boras, Tomislava Lauc

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The paper presents the service learning project titled DicDucFac (idea-leadership-product), that was planned and conducted by the team of information sciences students. It was planned as a workshop dealing with the application of modern social media (Facebook, YouTube, Gmail) for the purposes of selfpromotion, free advertising via social networks and marketing own ideas and/or products in the virtual world. The workshop was organized for highly-skilled computer literate unemployed youth. These youth, as final beneficiaries, will be able to apply what they learned in this workshop to “the real world“, increasing their chances for employment and self-employment. The results of the project reveal that the basic, active-learning principles embodied in our teaching approach allow students to learn more effectively and gain essential life skills (from computer applications to teamwork) that can only be learned by doing. It also shows that our students received the essentials of professional ethics and citizenship through direct, personal engagement in professional activities and the life of the community.

Keywords: Service Learning, Innovation, Engaged Citizenship, Leadership, Social Networks, Marketing.

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Authors: M. Tahmasebi, R.A. Rahman, M. Mailah, M. Gohari

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The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.

Keywords: Active force control, sprayer boom, active suspension, iterative learning.

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Authors: Petr Teply

Abstract:

Liquidity risk management ranks to key concepts applied in finance. Liquidity is defined as a capacity to obtain funding when needed, while liquidity risk means as a threat to this capacity to generate cash at fair costs. In the paper we present challenges of liquidity risk management resulting from the 2007- 2009 global financial upheaval. We see five main regulatory liquidity risk management issues requiring revision in coming years: liquidity measurement, intra-day and intra-group liquidity management, contingency planning and liquidity buffers, liquidity systems, controls and governance, and finally models testing the viability of business liquidity models.

Keywords: liquidity, risk management, regulation, global crisis

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Authors: Sandra Baßler, Peter Dünow, Mathias Marquardt

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A Fourier series based learning control (FSBLC) algorithm for tracking trajectories of mechanical systems with unknown nonlinearities is presented. Two processes are introduced to which the FSBLC with PD controller is applied. One is a simplified service robot capable of climbing stairs due to special wheels and the other is a propeller driven pendulum with nearly the same requirements on control. Additionally to the investigation of learning the feed forward for the desired trajectories some considerations on the implementation of such an algorithm on low cost microcontroller hardware are made. Simulations of the service robot as well as practical experiments on the pendulum show the capability of the used FSBLC algorithm to perform the task of improving control behavior for repetitive task of such mechanical systems.

Keywords: Climbing stairs, FSBLC, ILC, Service robot.

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Authors: B. Montero, M. Rico, A. Ares, R. Bouza

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The development of competences and practical capacities of students is getting an important incidence into the guidelines of the European Higher Education Area (EHEA). The methodology applied in this work is based on the education through directed resolution of practical cases. All cases are related to professional tasks that the students will have to develop in their future career. The method is intended to form the necessary competences of students of the Marine Engineering and Maritime Transport Degree in the matter of “Physics". The experience was applied in the course of 2011/2012. Students were grouped, and a practical task was assigned to them, that should be developed and solved within the team. The aim was to realize students learning by three ways: their own knowledge, the contribution of their teammates and the teacher's direction. The results of the evaluation were compared with those obtained previously by the traditional teaching method.

Keywords: Cooperation, Marine Engineering, Self-learning skills.

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Authors: R. Bawazir, P. Jones

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Social Stories are widely used to teach social and communication skills or concepts to individuals on the autistic spectrum. This paper presents a theoretical framework for using Social Stories in conjunction with the creative arts. The paper argues that Bandura’s social learning theory can be used to explain the mechanisms behind Social Stories and the way they influence changes in response, while Gardner’s multiple intelligences theory can be used simultaneously to demonstrate the role of the creative arts in learning. By using Social Stories with the creative arts for individuals on the autistic spectrum, the aim is to meet individual needs and help individuals with autism to develop in different areas of learning and communication.

Keywords: Individuals on the autistic spectrum, social stories, creative arts, theoretical framework.

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Authors: W. Hou, X. Shan, X. Ye

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Bidding is a very important business function to find latent contractors of construction projects. Moreover, bid markup is one of the most important decisions for a bidder to gain a reasonable profit. Since the bidding system is a complex adaptive system, bidding agent need a learning process to get more valuable knowledge for a bid, especially from past public bidding information. In this paper, we proposed an iterative agent leaning model for bidders to make markup decisions. A classifier for public bidding information named PIBS is developed to make full use of history data for classifying new bidding information. The simulation and experimental study is performed to show the validity of the proposed classifier. Some factors that affect the validity of PIBS are also analyzed at the end of this work.

Keywords: bidding markup, decision making, agent learning, information similarity.

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Authors: C. W. Kan, H. F. Cheung, Y. S. Lee

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This study examines the results of colour fading of cotton fabric by plasma-induced ozone treatment, with an aim to provide learning materials for fashion designers when designing colour fading effects in fashion products. Cotton knitted fabrics were dyed with red reactive dye with a colour depth of 1.5% and were subjected to ozone generated by a commercially available plasma machine for colour fading. The plasma-induced ozone treatment was conducted with different parameters: (i) air concentration = 10%, 30%, 50% and 70%; (ii) water content in fabric = 35% and 45%, and (iii) treatment time = 10 minutes, 20 minutes and 30 minutes. Finally, the colour properties of the plasma–induced ozone treated fabric were measured by spectrophotometer under illuminant D₆₅ to obtain the CIE L*, CIE a* and CIE b* values.

Keywords: Learning materials, colour fading, colour properties, fashion products.

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Authors: Eiko Takaoka, Yuji Osawa

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We have designed and implemented e-Learning materials for a JAVA programming course since 2004 and have found that “normal” students, meaning motivated and capable students, can successfully learn the course material taught in a fully online manner. However, for “weaker” students, meaning those lacking motivation, experience, and/or aptitude, the results have been unsatisfactory, and such students thus fall into the supplementary category. From 2007 to 2008, we offered a face-to-face class with small-group instruction for the weaker students, while we provided the fully online course for the normal students. Consequently, we succeeded in helping the weaker students to overcome their programming phobia and develop the ability to create basic programs.

Keywords: e-learning, JAVA Programming Course, Small-Group Instruction, Supplementary.

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Authors: Kien Tsong Chau, Zarina Samsudin, Wan Ahmad Jaafar Wan Yahaya

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The paper examined the capability of a prototype of a tangible multimedia system that was augmented with tangible objects in motivating young preschoolers in learning. Preschoolers’ learning behaviour is highly captivated and motivated by external physical stimuli. Hence, conventional multimedia which solely dependent on digital visual and auditory formats for knowledge delivery could potentially place them in inappropriate state of circumstances that are frustrating, boring, or worse, impede overall learning motivations. This paper begins by discussion with the objectives of the research, followed by research questions, hypotheses, ARCS model of motivation adopted in the process of macro-design, and the research instrumentation, Persuasive Multimedia Motivational Scale was deployed for measuring the level of motivation of subjects towards the experimental tangible multimedia. At the close, a succinct description of the findings of a relevant research is provided. In the research, a total of 248 preschoolers recruited from seven Malaysian kindergartens were examined. Analyses revealed that the tangible multimedia system improved preschoolers’ learning motivation significantly more than conventional multimedia. Overall, the findings led to the conclusion that the tangible multimedia system is a motivation conducive multimedia for preschoolers.

Keywords: Tangible multimedia, preschooler, motivation, multimedia.

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Authors: H. Bouhamed, A. Rebai, T. Lecroq, M. Jaoua

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The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.

Keywords: Data-organization, data-optimization, automatic knowledge discovery, Multi-Entities Bayesian networks, score merging.

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Authors: Wafa Labib

Abstract:

Teaching methods include lectures, workshops and tutorials for the presentation and discussion of ideas have become out of date; were developed outside the discipline of architecture from the college of engineering and do not satisfy the architectural students’ needs and causes them many difficulties in integrating structure into their design. In an attempt to improve structure teaching methods, this paper focused upon proposing a supportive teaching/learning tool using multi-media applications which seeks to better meet the architecture student’s needs and capabilities and improve the understanding and application of basic and intermediate structural engineering and technology principles. Before introducing the use of multi-media as a supportive teaching tool, a questionnaire was distributed to third year students of a structural design course who were selected as a sample to be surveyed forming a sample of 90 cases. The primary aim of the questionnaire was to identify the students’ learning style and to investigate whether the selected method of teaching could make the teaching and learning process more efficient. Students’ reaction on the use of this method was measured using three key elements indicating that this method is an appropriate teaching method for the nature of the students and the course as well.

Keywords: Teaching Method, Architecture, Learning style, Multi-Media.

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