Search results for: learning management systems

Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Krisztina Bohacs, Klaudia Markus

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To author’s best knowledge we are in absence of studies on cognitive program evaluation and we are certainly short of programs that prove to have high effect sizes with strong retention results. The purpose of our study was to investigate the effectiveness of a comprehensive cognitive training program, namely BrainRx. This cognitive rehabilitation program target and remediate seven core cognitive skills and related systems of sub-skills through repeated engagement in game-like mental procedures delivered one-on-one by a clinician, supplemented by digital training. A larger sample of children with learning disability were given pretest and post-test cognitive assessments. The experimental group completed a twenty-week cognitive training program in a BrainRx center. A matched control group received another twenty-week intervention with Feuerstein’s Instrumental Enrichment programs. A second matched control group did not receive training. As for pre- and post-test, we used a general intelligence test to assess IQ and a computer-based test battery for assessing cognition across the lifespan. Multiple regression analyses indicated that the experimental BrainRx treatment group had statistically significant higher outcomes in attention, working memory, processing speed, logic and reasoning, auditory processing, visual processing and long-term memory compared to the non-treatment control group with very large effect sizes. With the exception of logic and reasoning, the BrainRx treatment group realized significantly greater gains in six of the above given seven cognitive measures compared to the Feuerstein control group. Our one-year retention measures showed that all the cognitive training gains were above ninety percent with the greatest retention skills in visual processing, auditory processing, logic, and reasoning. The BrainRx program may be an effective tool to establish long-term cognitive changes in case of students with learning disabilities. Recommendations are made for treatment centers and special education institutions on the cognitive training of students with special needs. The importance of our study is that targeted, systematic, progressively loaded and intensive brain training approach may significantly change learning disabilities.

Keywords: cognitive rehabilitation training, cognitive skills, learning disability, permanent structural cognitive changes

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Authors: Prince Chukwuneme Enwereji, Annelien Van Rooyen

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In recent years, technology integration in education has transformed the learning landscape, particularly in online institutions. One technological advancement that has gained popularity is e-tutoring, which offers personalised academic support to students through online platforms. While e-tutoring has become well-known and has been adopted to promote collaborative learning, there are still students who do not use these services for various reasons. However, little attention has been given to understanding the perspectives of students who have not utilized these services. The research objectives include identifying the perceived benefits that non-e-tutoring students believe e-tutoring could offer, such as enhanced academic support, personalized learning experiences, and improved performance. Additionally, the study explored the potential drawbacks or concerns that non-e-tutoring students associate with e-tutoring, such as concerns about efficacy, a lack of face-to-face interaction, and platform accessibility. The study adopted a quantitative research approach with a descriptive design to gather and analyze data on non-e-tutoring students' perspectives. Online questionnaires were employed as the primary data collection method, allowing for the efficient collection of data from many participants. The collected data was analyzed using the Statistical Package for the Social Sciences (SPSS). Ethical concepts such as informed consent, anonymity of responses and protection of respondents against harm were maintained. Findings indicate that non-e-tutoring students perceive a sense of control over their own pace of learning, suggesting a preference for self-directed learning and the ability to tailor their educational experience to their individual needs and learning styles. They also exhibit high levels of motivation, believe in their ability to effectively participate in their studies and organize their academic work, and feel comfortable studying on their own without the help of e-tutors. However, non-e-tutoring students feel that e-tutors do not sufficiently address their academic needs and lack engagement. They also perceive a lack of clarity in the roles of e-tutors, leading to uncertainty about their responsibilities. In terms of communication, students feel overwhelmed by the volume of announcements and find repetitive information frustrating. Additionally, some students face challenges with their internet connection and associated cost, which can hinder their participation in online activities. Furthermore, non-e-tutoring students express a desire for interactions with their peers and a sense of belonging to a group or team. They value opportunities for collaboration, teamwork in their learning experience, the importance of fostering social interactions and creating a sense of community in online learning environments. This study recommended that students seek alternate support systems by reaching out to professors or academic advisors for guidance and clarification. Developing self-directed learning skills is essential, empowering students to take charge of their own learning through setting objectives, creating own study plans, and utilising resources. For HEIs, it was recommended that they should ensure that a variety of support services are available to cater to the needs of all students, including non-e-tutoring students. HEIs should also ensure easy access to online resources, promote a supportive community, and regularly evaluate and adapt their support techniques to meet students' changing requirements.

Keywords: online-tutor;, student support;, online education, educational practices, distance education

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Authors: Yingling Chen

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Most current research has been focused on whether NESTs have advantages over NNESTs in English language Teaching. The purpose of this study was to investigate English learners’ preferences toward native English speaking teachers and non-English speaking teachers in four skills of English language learning. This qualitative study consists of 12 participants. Two open-ended questions were investigated and analyzed. The findings revealed that the participants held an overall preference for NESTs over NNESTs in reading, writing, and listening English skills; nevertheless, they believed both NESTs and NNESTs offered learning experiences strengths, and weaknesses to satisfy students’ need in their English instruction.

Keywords: EFL, instruction, Student Rating of Instructions (SRI), perception

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Authors: Evgeniia Surkova, Manal Assaad, Hleb Makeyeu, Juho Makio

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The main objective of STIMEY (Science, Technology, Innovation, Mathematics, Engineering for the Young) project is the delivery of a hybrid learning environment that combines multi-level components such as social media concepts, robotic artefacts, and radio, among others. It is based on a well-researched pedagogical framework to attract European youths to STEM (science, technology, engineering, and mathematics) education and careers. To develop and integrate these various components, STIMEY is executed in iterative research cycles leading to progressive improvements. Scrum was the development methodology of choice in the project, as studies indicated its benefits as an agile methodology in global software development, especially of e-learning and integrated learning projects. This paper describes the project partners’ experience with the Scrum framework, discussing the challenges faced in its implementation and the mitigation practices employed. The authors conclude with exploring user experience tools and principles for future research, as a novel direction in supporting the Scrum development team.

Keywords: e-learning, global software development, scrum, STEM education

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Authors: Yiwei Li, Mingyu Gao

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Integrating hybrid memories with heterogeneous processors could leverage heterogeneity in both compute and memory domains for better system efficiency. To ensure performance isolation, we introduce Hydrogen, a hardware architecture to optimize the allocation of hybrid memory resources to heterogeneous CPU-GPU systems. Hydrogen supports efficient capacity and bandwidth partitioning between CPUs and GPUs in both memory tiers. We propose decoupled memory channel mapping and token-based data migration throttling to enable flexible partitioning. We also support epoch-based online search for optimized configurations and lightweight reconfiguration with reduced data movements. Hydrogen significantly outperforms existing designs by 1.21x on average and up to 1.31x.

Keywords: hybrid memory, heterogeneous systems, dram cache, graphics processing units

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Authors: Aparna Datey

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This paper explores the theoretical frameworks underpinning professional learning, professional development, and academic identity. The focus is on sessional teachers (also called tutors or adjuncts) in architectural design studios, who may be practitioners, masters or doctoral students and academics hired ‘as needed’. Drawing from Schön’s work on reflective practice, learning and developmental theories of Vygotsky (social constructionism and zones of proximal development), informal and workplace learning, this research proposes that sessional teachers not only develop their teaching skills but also shape their identities through their 'everyday' work. Continuing academic staff develop their teaching through a combination of active teaching, self-reflection on teaching, as well as learning to teach from others via formalised programs and informally in the workplace. They are provided professional development and recognised for their teaching efforts through promotion, student citations, and awards for teaching excellence. The teaching experiences of sessional staff, by comparison, may be discontinuous and they generally have fewer opportunities and incentives for teaching development. In the absence of access to formalised programs, sessional teachers develop their teaching informally in workplace settings that may be supportive or unhelpful. Their learning as teachers is embedded in everyday practice applying problem-solving skills in ambiguous and uncertain settings. Depending on their level of expertise, they understand how to teach a subject such that students are stimulated to learn. Adult learning theories posit that adults have different motivations for learning and fall into a matrix of readiness, that an adult’s ability to make sense of their learning is shaped by their values, expectations, beliefs, feelings, attitudes, and judgements, and they are self-directed. The level of expertise of sessional teachers depends on their individual attributes and motivations, as well as on their work environment, the good practices they acquire and enhance through their practice, career training and development, the clarity of their role in the delivery of teaching, and other factors. The architectural design studio is ideal for study due to the historical persistence of the vocational learning or apprenticeship model (learning under the guidance of experts) and a pedagogical format using two key approaches: project-based problem solving and collaborative learning. Hence, investigating the theoretical frameworks underlying academic roles and informal professional learning in the workplace would deepen understanding of their professional development and how they shape their academic identities. This qualitative research is ongoing at a major university in Australia, but the growing trend towards hiring sessional staff to teach core courses in many disciplines is a global one. This research will contribute to including transient sessional teachers in the discourse on institutional quality, effectiveness, and student learning.

Keywords: academic identity, architectural design learning, pedagogy, teaching and learning, sessional teachers

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Authors: Shamatha Shetty, Sakshi Dhabadi, Prerana M., Indushree B.

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About 66% of firms claim that insider attacks are more likely to happen. The frequency of insider incidents has increased by 47% in the last two years. The goal of this work is to prevent dangerous employee behavior by using keyloggers and the Machine Learning (ML) model. Every keystroke that the user enters is recorded by the keylogging program, also known as keystroke logging. Keyloggers are used to stop improper use of the system. This enables us to collect all textual data, save it in a CSV file, and analyze it using an ML algorithm and the VirusTotal API. Many large companies use it to methodically monitor how their employees use computers, the internet, and email. We are utilizing the SVM algorithm and the VirusTotal API to improve overall efficiency and accuracy in identifying specific patterns and words to automate and offer the report for improved monitoring.

Keywords: cyber security, machine learning, cyclic process, email notification

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Authors: Valliyil Govindankutty

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Human civilizations across the globe stand testimony to water being one of the major interaction points with nature. The interactions with nature especially in drier areas revolve around water, be it harnessing, transporting, usage and management. Many ingenious ideas were born, nurtured and developed for harnessing, transporting, storing and distributing water through the areas in the drier parts of the world. Many methods of water extraction, collection and management could be found throughout the world, some of which are associated with efficient, sustained use of surface water, ground water and rain water. Karez is one such ingenious method of collection, transportation, storage and distribution of ground water. Most of the Karez systems in India were developed during reign of Muslim dynasties with ruling class descending from Persia or having influential connections and inviting expert engineers from there. Karez have strongly influenced the village socio-economic organisations due to multitude of uses they were brought into. These are masterpiece engineering structures to collect groundwater and direct it, through a subsurface gallery with a gradual slope, to surface canals that provide water to settlements and agricultural fields. This ingenious technology, karez was result of need for harnessing groundwater in arid areas like that of Bidar. The study views this traditional technology in historical perspective linked to sustainable utilization and management of groundwater and above all the immediate environment. The karez system is one of the best available demonstration of human ingenuity and adaptability to situations and locations of water scarcity. Bidar, capital of erstwhile Bahmani sultanate with a history of more than 700 years or more is one of the heritage cities of present Karnataka State. The unique water systems of Bidar along with other historic entities have been listed under World Heritage Watch List by World Monument Fund. The Historical or cultural landscape in Bidar is very closely associated to the natural resources of the region, Karez systems being one of the best examples. The Karez systems were the lifeline of Bidar’s historical period providing potable water, fulfilling domestic and irrigation needs, both within and outside the fort enclosures. These systems are still functional, but under great pressure and threat of rapid and unplanned urbanisation. The change in land use and fragmentation of land are already paving way for irreversible modification of the karez cultural and geographic landscape. The Paper discusses the significance of character defining elements of Naubad Karez Landscape, highlights the importance of conserving cultural heritage and presents a geographical approach to its revival.

Keywords: Karez, groundwater, traditional water harvesting, cultural heritage landscape, urban planning

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Authors: Ouahab Kadri, Leila Hayet Mouss

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In this paper, we present three diagnostic modules for complex and dynamic systems. These modules are based on three ant colony algorithms, which are AntTreeStoch, Lumer & Faieta and Binary ant colony. We chose these algorithms for their simplicity and their wide application range. However, we cannot use these algorithms in their basement forms as they have several limitations. To use these algorithms in a diagnostic system, we have proposed three variants. We have tested these algorithms on datasets issued from two industrial systems, which are clinkering system and pasteurization system.

Keywords: ant colony algorithms, complex and dynamic systems, diagnosis, classification, optimization

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Authors: Andrea Ghermandi

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Constructed wetlands have long been recognized as sources of ancillary benefits such as support for recreational activities. To date, there is a lack of quantitative understanding of the extent and welfare impact of such benefits. Here, it is shown how geotagged, passively crowdsourced data from online social networks (e.g., Flickr and Panoramio) and Geographic Information Systems (GIS) techniques can: (1) be used to infer annual recreational visits to 273 engineered wetlands worldwide; and (2) be integrated with non-market economic valuation techniques (e.g., travel cost method) to infer the monetary value of recreation in these systems. Counts of social media photo-user-days are highly correlated with the number of observed visits in 62 engineered wetlands worldwide (Pearson’s r = 0.811; p-value < 0.001). The estimated, mean willingness to pay for access to 115 wetlands ranges between $5.3 and $374. In 50% of the investigated wetlands providing polishing treatment to advanced municipal wastewater, the present value of such benefits exceeds that of the capital, operation and maintenance costs (lifetime = 45 years; discount rate = 6%), indicating that such systems are sources of net societal benefits even before factoring in benefits derived from water quality improvement and storage. Based on the above results, it is argued that recreational benefits should be taken into account in the design and management of constructed wetlands, as well as when such green infrastructure systems are compared with conventional wastewater treatment solutions.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, social media

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Authors: Tshegofatso Rambau, Tonderai Muchenje

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Zero-day attacks (ZDA) are increasing day by day; there are many vulnerabilities in systems and software that date back decades. Companies keep discovering vulnerabilities in their systems and software and work to release patches and updates. A zero-day vulnerability is a software fault that is not widely known and is unknown to the vendor; attackers work very quickly to exploit these vulnerabilities. These are major security threats with a high success rate because businesses lack the essential safeguards to detect and prevent them. This study focuses on the factors and techniques that can help us detect zero-day attacks. There are various methods and techniques for detecting vulnerabilities. Various companies like edges can offer penetration testing and smart vulnerability management solutions. We will undertake literature studies on zero-day attacks and detection methods, as well as modeling approaches and simulations, as part of the study process.

Keywords: zero-day attacks, exploitation, vulnerabilities

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Authors: Carin Chuang, Kuan-Chou Chen

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An Enterprise Resource Planning (ERP) system is an integrated information system that supports the seamless integration of all the business processes of a company. Implementing an ERP system can increase efficiencies and decrease the costs while helping improve productivity. Many organizations including large, medium and small-sized companies have already adopted an ERP system for decades. Although ERP system can bring competitive advantages to organizations, the lack of proper training approach in ERP implementation is still a major concern. Organizations understand the importance of ERP training to adequately prepare managers and users. The low return on investment, however, for the ERP training makes the training difficult for knowledgeable workers to transfer what is learned in training to the jobs at workplace. Inadequate and inefficient ERP training limits the value realization and success of an ERP system. That is the need to call for a profound change and innovation for ERP training in both workplace at industry and the Information Systems (IS) education in academia. The innovated ERP training approach can improve the users’ knowledge in business processes and hands-on skills in mastering ERP system. It also can be instructed as educational material for IS students in universities. The purpose of the study is to examine the use of ERP simulation games via the ERPsim system to train the IS students in learning ERP implementation. The ERPsim is the business simulation game developed by ERPsim Lab at HEC Montréal, and the game is a real-life SAP (Systems Applications and Products) ERP system. The training uses the ERPsim system as the tool for the Internet-based simulation games and is designed as online student competitions during the class. The competitions involve student teams with the facilitation of instructor and put the students’ business skills to the test via intensive simulation games on a real-world SAP ERP system. The teams run the full business cycle of a manufacturing company while interacting with suppliers, vendors, and customers through sending and receiving orders, delivering products and completing the entire cash-to-cash cycle. To learn a range of business skills, student needs to adopt individual business role and make business decisions around the products and business processes. Based on the training experiences learned from rounds of business simulations, the findings show that learners have reduced risk in making mistakes that help learners build self-confidence in problem-solving. In addition, the learners’ reflections from their mistakes can speculate the root causes of the problems and further improve the efficiency of the training. ERP instructors teaching with the innovative approach report significant improvements in student evaluation, learner motivation, attendance, engagement as well as increased learner technology competency. The findings of the study can provide ERP instructors with guidelines to create an effective learning environment and can be transferred to a variety of other educational fields in which trainers are migrating towards a more active learning approach.

Keywords: business simulations, ERP implementation training, ERPsim, game-based learning, instructional strategy, training innovation

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Authors: Masimuddin Mohd Khaled

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From the past couple of years, focus has been done on the quality management theories and has been pertained to various firms. The core quality management theories are Total Quality Management (TQM) and Six Sigma where a number of documents have already been presented regarding these theories. The purpose of this paper is to study in detail about these theories and how the theories are applied in the aerospace industry. A methodical literature review, comparison of TQM and Six Sigma as well as a case study of each has been carried out in this paper thus providing a clear understanding of the theories.

Keywords: total quality management, six sigma, aerospace, research, innovation

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Ozge Gurcanli

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Recent studies in active-learning focus on how student experience varies based on the content (e.g. STEM versus Humanities) and the medium (e.g. in-class exercises versus off-campus activities) of experiential learning. However, little is known whether the variation in classroom time and space within the same active learning context affects student experience. This study manipulated the use of classroom time for the active learning component of a developmental psychology course that is offered at a four-year university in the South-West Region of United States. The course uses a blended model: traditional and active learning. In the traditional learning component of the course, students do weekly readings, listen to lectures, and take midterms. In the active learning component, students make a documentary on a developmental topic as a final project. Students used the classroom time and space for the documentary in two ways: regular classroom time slots that were dedicated to the making of the documentary outside without the supervision of the professor (Classroom-time Outside) and lectures that offered basic instructions about how to make a documentary (Documentary Lectures). The study used the public teaching evaluations that are administered by the Office of Registrar’s. A total of two hundred and seven student evaluations were available across six semesters. Because the Office of Registrar’s presented the data separately without personal identifiers, One-Way ANOVA with four groups (Traditional, Experiential-Heavy: 19% Classroom-time Outside, 12% for Documentary Lectures, Experiential-Moderate: 5-7% for Classroom-time Outside, 16-19% for Documentary Lectures, Experiential Light: 4-7% for Classroom-time Outside, 7% for Documentary Lectures) was conducted on five key features (Organization, Quality, Assignments Contribution, Intellectual Curiosity, Teaching Effectiveness). Each measure used a five-point reverse-coded scale (1-Outstanding, 5-Poor). For all experiential conditions, the documentary counted towards 30% of the final grade. Organization (‘The instructors preparation for class was’), Quality (’Overall, I would rate the quality of this course as’) and Assignment Contribution (’The contribution of the graded work that made to the learning experience was’) did not yield any significant differences across four course types (F (3, 202)=1.72, p > .05, F(3, 200)=.32, p > .05, F(3, 203)=.43, p > .05, respectively). Intellectual Curiosity (’The instructor’s ability to stimulate intellectual curiosity was’) yielded a marginal effect (F (3, 201)=2.61, p = .053). Tukey’s HSD (p < .05) indicated that the Experiential-Heavy (M = 1.94, SD = .82) condition was significantly different than all other three conditions (M =1.57, 1.51, 1.58; SD = .68, .66, .77, respectively) showing that heavily active class-time did not elicit intellectual curiosity as much as others. Finally, Teaching Effectiveness (’Overall, I feel that the instructor’s effectiveness as a teacher was’) was significant (F (3, 198)=3.32, p <.05). Tukey’s HSD (p <.05) showed that students found the courses with moderate (M=1.49, SD=.62) to light (M=1.52, SD=.70) active class-time more effective than heavily active class-time (M=1.93, SD=.69). Overall, the findings of this study suggest that within the same active learning context, the time and the space dedicated to active learning results in different outcomes in intellectual curiosity and teaching effectiveness.

Keywords: active learning, learning outcomes, student experience, learning context

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Bander Mohayya Alotaibi

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The valuable partnerships between parents and teachers may develop positive and effective interactions between home and school. This will help these stakeholders share information and resources regarding student academics during ongoing interactions. Thus, partnerships will build a solid foundation for both families and schools to help children succeed in school. Parental involvement can be seen as an effective tool that can change homes and communities and not just schools’ systems. Seeking parents and stakeholders’ attitudes toward learning and learners can help schools design a curriculum. Subsequently, this information can be used to find ways to help improve the academic performance of students, especially in low performing schools. There may be some conflicts when designing curriculum. In addition, designing curriculum might bring more educational expectations to all the sides. There is a lack of research that targets the specific attitude of parents toward specific concepts on curriculum contents. More research is needed to study the perspective that parents of children with learning disabilities (LD) have regarding early reading curriculum. Parents and stakeholders’ perspectives on early reading intervention implemented as a curriculum for children with LD was studied through an advanced quantitative research. The purpose of this study seeks to understand stakeholders and parents’ perspectives of key concepts and essential early reading skills that impact the design of curriculum that will serve as an intervention for early struggler readers who have LD. Those concepts or stages include phonics, phonological awareness, and reading fluency as well as strategies used in house by parents. A survey instrument was used to gather the data. Participants were recruited through 29 schools and districts of the metropolitan area of the northern part of Saudi Arabia. Participants were stakeholders including parents of children with learning disability. Data were collected using distribution of paper and pen survey to schools. Psychometric properties of the instrument were evaluated for the validity and reliability of the survey; face validity, content validity, and construct validity including an Exploratory Factor Analysis were used to shape and reevaluate the structure of the instrument. Multivariate analysis of variance (MANOVA) used to find differences between the variables. The study reported the results of the perspectives of stakeholders toward reading strategies, phonics, phonological awareness, and reading fluency. Also, suggestions and limitations are discussed.

Keywords: stakeholders, learning disability, early reading, perspectives, parents, intervention, curriculum

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Authors: Yihao Kuang, Bowen Ding

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With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graphs and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improved strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain a better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference

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Authors: Parth Shah

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The author examines the recent trend where business organizations are significantly reducing their developmental cycle times to stay competitive in today’s global marketspace. The author proposes a rapid systems engineering framework to address late design changes and allow for flexibility (i.e. to react to unexpected or late changes and its impacts) during the product development cycle using a Systems Engineering approach. A System Engineering approach is crucial in today’s product development to deliver complex products into the marketplace. Design changes can occur due to shortened timelines and also based on initial consumer feedback once a product or service is in the marketplace. The ability to react to change and address customer expectations in a responsive and cost-efficient manner is crucial for any organization to succeed. Past literature, research, and methods such as concurrent development, simultaneous engineering, knowledge management, component sharing, rapid product integration, tailored systems engineering processes, and studies on reducing product development cycles all suggest a research gap exist in specifically addressing late design changes due to the shortening of life cycle environments in increasingly competitive markets. The author’s research suggests that 1) product development cycles time scales are now measured in months instead of years, 2) more and more products have interdepended systems and environments that are fast-paced and resource critical, 3) product obsolesce is higher and more organizations are releasing products and services frequently, and 4) increasingly competitive markets are leading to customization based on consumer feedback. The author will quantify effectiveness with respect to success factors such as time-to-market, return-of-investment, life cycle time and flexibility in late design changes by complexity of product or service, number of late changes and ability to react and reduce late design changes.

Keywords: product development, rapid systems engineering, scalability, systems engineering, systems integration, systems life cycle

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Authors: Anilkumar L. Rathod

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This paper examines event tourism as a field of study and area of professional practice updating the previous review article published in 2015. In this substantially extended review, a deeper analysis of the field's evolution and development is presented, charting the growth of the literature, focusing both chronologically and thematically. A framework for understanding and creating knowledge about events and tourism is presented, forming the basis which signposts established research themes and concepts and outlines future directions for research. In addition, the review article focuses on constraining and propelling forces, ontological advances, contributions from key journals, and emerging themes and issues. It also presents a roadmap for research activity in event tourism. Published scholarly studies within this period are examined through content analysis, using such keywords as knowledge management, organizational learning, hospitality, tourism, tourist destinations, travel industry, hotels, lodging, motels, hotel industry, gaming, casino hotel and convention to search scholarly research journals. All contributions found are then screened for a hospitality and tourism theme. Researchers mostly discuss knowledge management approach in improving information technology, marketing and strategic planning in order to gain competitive advantage. Overall, knowledge management research is still limited. Planned events in tourism are created for a purpose, and what was once the realm of individual and community initiatives has largely become the realm of professionals and entrepreneurs provides a typology of the four main categories of planned events within an event-tourism context, including the main venues associated with each. It also assesses whether differences exist between socio-demographic groupings. An analysis using primarily descriptive statistics indicated both sub-samples had similar viewpoints although Maharashtra residents tended to have higher scores pertaining to the consequences of gambling. It is suggested that the differences arise due to the greater exposure of Maharashtra residents to the influences of casino development.

Keywords: organizational learning, hospitality, tourism, tourist destinations, travel industry, hotels, lodging, motels, hotel industry, gaming, casino hotel and convention to search scholarly research journals

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

Procedia PDF Downloads 114

Authors: Marcel Randermann, Roland Jochem

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Research activities are mostly conducted in form of projects. In fact, research projects take the highest share of all project forms combined. However, project management is very rarely applied purposefully by researchers and scientists. More specifically no project management frameworks, methods or tools are not being used to plan, execute or control research project to ensure research success or improve project quality. In this qualitative study, several interviews were conducted with scientists and research managers from German institutions to gain insights into project management activities, to determine challenges and barriers, and to evaluate premises for successful project management. The analyses show that conventional project management is not easily applicable in scientific environments and researchers’ mindsets prevent a reasonable application.

Keywords: academics, project management methods, research and science projects, scientist's mindset

Procedia PDF Downloads 177

Authors: Shan Jiang, Xinyu Tang

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Game-based learning is an emerging pedagogy to make the learning experience more effective, enjoyable, and fun. However, most games used in classroom settings have been overly simplistic. This paper presents a case study on a Python-based online game designed to improve the effectiveness in both teaching and research in higher education. The proposed game system not only creates a fun and enjoyable experience for students to learn various topics in programming but also improves the effectiveness of teaching in several aspects, including material presentation, helping students to recognize the importance of the subjects, and linking theoretical concepts to practice. The proposed game system also serves as an information cyber-infrastructure that automatically collects and stores data from players. The data could be useful in research areas including human-computer interaction, decision making, opinion mining, and artificial intelligence. They further provide other possibilities beyond these areas due to the customizable nature of the game.

Keywords: game-based learning, programming, research-teaching integration, Hearthstone

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Authors: Misbah Javaid, Vladimir Estivill-Castro, Rene Hexel

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The field of robotics is advancing rapidly to the point where robots have become an integral part of the modern society. These robots collaborate and contribute productively with humans and compensate some shortcomings from human abilities and complement them with their skills. Effective teamwork of humans and robots demands to investigate the critical issue of trust. The field of human-computer interaction (HCI) has already examined trust humans place in technical systems mostly on issues like reliability and accuracy of performance. Early work in the area of expert systems suggested that automatic generation of explanations improved trust and acceptability of these systems. In this work, we augmented a robot with the user-invoked explanation generation proficiency. To measure explanations effect on human’s level of trust, we collected subjective survey measures and behavioral data in a human-robot team task into an interactive, adversarial and partial information environment. The results showed that with the explanation capability humans not only understand and recognize robot as an expert team partner. But, it was also observed that human's learning and human-robot team performance also significantly improved because of the meaningful interaction with the robot in the human-robot team. Moreover, by observing distinctive outcomes, we expect our research outcomes will also provide insights into further improvement of human-robot trustworthy relationships.

Keywords: explanation interface, adversaries, partial observability, trust building

Procedia PDF Downloads 189

Authors: Samuel Olajide Babawale, Jonathan Bridge

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Natural Flood Management (NFM) is promoted as part of sustainable flood management (SFM) in response to climate change adaptation. Stakeholder engagement is central to this approach, and current trends are progressively moving towards a collaborative learning approach where stakeholder participation is perceived as one of the indicators of sustainable development. Within this methodology, participation embraces a diversity of knowledge and values underpinned by a philosophy of empowerment, equity, trust, and learning. To identify barriers to NFM uptake, there is a need for a new understanding of how stakeholder participation could be enhanced to benefit individual and community resilience within SFM. This is crucial in light of climate change threats and scientific reliability concerns. In contributing to this new understanding, this research evaluated the proposed interventions on six (6) UK NFM in a catchment known as the Sheffield Lakeland Partnership Area with reference to the Environment Agency Working with Natural Processes (WWNP) Potentials/Opportunities. Three of the opportunities, namely Run-off Attenuation Potential of 1%, Run-off Attenuation Potential of 3.3% and Riparian Woodland Potential, were modeled. In all the models, the interventions, though they have been proposed or already in place, are not in agreement with the data presented by EA WWNP. Findings show some institutional weaknesses, which are seen to inhibit the development of adequate flood management solutions locally with damaging implications for vulnerable communities. The gap in communication from practitioners poses a challenge to the implementation of real flood mitigating measures that align with the lead agency’s nationally accepted measures which are identified as not feasible by the farm management officers within this context. Findings highlight a dominant top-bottom approach to management with very minimal indication of local interactions. Current WWNP opportunities have been termed as not realistic by the people directly involved in the daily management of the farms, with less emphasis on prevention and mitigation. The targeted approach suggested by the EA WWNP is set against adaptive flood management and community development. The study explores dimensions of participation using the self-reliance and self-help approach to develop a methodology that facilitates reflections of currently institutionalized practices and the need to reshape spaces of interactions to enable empowered and meaningful participation. Stakeholder engagement and resilience planning underpin this research. The findings of the study suggest different agencies have different perspectives on “community participation”. It also shows communities in the case study area appear to be least influential, denied a real chance of discussing their situations and influencing the decisions. This is against the background that the communities are in the most productive regions, contributing massively to national food supplies. The results are discussed concerning practical implications for addressing interagency partnerships and conducting grassroots collaborations that empower local communities and seek solutions to sustainable development challenges. This study takes a critical look into the challenges and progress made locally in sustainable flood risk management and adaptation to climate change by the United Kingdom towards achieving the global 2030 agenda for sustainable development.

Keywords: natural flood management, sustainable flood management, sustainable development, working with natural processes, environment agency, run-off attenuation potential, climate change

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Authors: Noran Adel Emara, Elham Ghazi Mohammad

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Qatar University is engaged in a systemic education reform that includes integrating the latest and most effective technologies for teaching and learning. ICube is high-immersive virtual reality technology is used to teach educational scenarios that are difficult to teach in real situations. The trends toward delivering science education via virtual reality applications have accelerated in recent years. However, research on students perceptions of integrating virtual reality especially ICube technology is somehow limited. Students often have difficulties focusing attention on learning science topics that require imagination and easily lose attention and interest during the lesson. The aim of this study was to examine students’ perception of integrating ICube technology in the solar system lesson. Moreover, to explore how ICube could engage students in learning scientific concept of the solar system. The research framework included the following quantitative research design with data collection and analysis from questionnaire results. The solar system lesson was conducted by teacher candidates (Diploma students) who taught in the ICube virtual lab in Qatar University. A group of 30 students from eighth grade were randomly selected to participate in the study. Results showed that the students were extremely engaged in learning the solar system and responded positively to integrating ICube in teaching. Moreover, the students showed interest in learning more lessons through ICube as it provided them with valuable learning experience about complex situations.

Keywords: ICube, integrating technology, science education, virtual reality

Procedia PDF Downloads 283

Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Golnaz Moghimi, Alireza Afsharghotli, Alireza Rezaei

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Construction waste has been gradually increased as a result of upsizing construction projects which are occurred within the lifecycle of buildings. Since waste management is a major priority and has profound impacts on the volume of waste generated in construction stage, the majority of efforts have been attempted to reuse, recycle and reduce waste. However, there is still room to study on lack of sufficient knowledge about waste management in construction industry. This paper intends to provide an insight into the effect of project management knowledge areas on waste management solely on construction stage. To this end, a survey among Iranian building construction industry contractors was conducted to identify the effectiveness of project management knowledge areas on three jobsite key factors including ‘Site activity’, ‘Training’, and ‘Awareness’. As a result, four management disciplines were identified as most influential ones on amount of construction waste. These disciplines were Project Cost Management, Quality Management, Human Resource Management, and Integration Management. Based on the research findings, a new model was presented to develop effective construction waste strategies.

Keywords: awareness, PMBOK, site activity, training, waste management

Procedia PDF Downloads 322