Search results for: Learning supportive assessment

Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: Adaptive sampling, batch bulk methyl methacrylate polymerization, large margin nearest neighbor regression, machine learning.

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Authors: Liang Wang, Wei Zhang

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Nowadays sustainable development has increasingly become an important research topic of engineering education all over the world. Engineering Education for Sustainable Development (EESD) highlighted the importance of addressing sustainable development in engineering practice. However, whether and how the professional engineering learning and experience affect those perceptions is an interesting research topic especially in Chinese context. Our study fills this gap by investigating perceptions bias of EESD among first-grade engineering students, fourth-grade engineering students and experienced engineers using a triple-dimensional model. Our goal is to find the effect of engineering learning and experience on sustainable development and make these learning and experiences more accessible for students and engineers in school and workplace context. The data (n = 138) came from a Likert questionnaire based on the triple-dimensional model of EESD adopted from literature reviews and the data contain 48 first-grade students, 56 fourth-grade students and 34 engineers with rich working experience from Environmental Engineering, Energy Engineering, Chemical Engineering and Civil Engineering in or graduated from Zhejiang University, China. One-way ANOVA analysis was used to find the difference in different dimensions among the three groups. The statistical results show that both engineering students and engineers have a well understanding of sustainable development in ecology dimension of EESD while there are significant differences among three groups as to the socio-economy and value rationality dimensions of EESD. The findings provide empirical evidence that both engineering learning and professional engineering experience are helpful to cultivate the cognition and perception of sustainable development in engineering education. The results of this work indicate that more practical content should be added to students’ engineering education while more theoretical content should be added to engineers’ training in order to promote the engineering students’ and engineers’ perceptions of sustainable development. In addition, as to the design of engineering courses and professional practice system for sustainable development, we should not only pay attention to the ecological aspects, but also emphasize the coordination of ecological, socio-economic and human-centered sustainable development (e.g., engineer's ethical responsibility).

Keywords: Engineering education, sustainable development, experienced engineers, engineering students.

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Authors: Khondokar Farid Ahmmed, Robin Bown

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It is widely recognized that the formal financing of Small and Medium Size Enterprises (SMEs) by Private Commercial Banks (PCBs) is restricted. Due to changing financial market competition, SMEs are now important customers to PCBs in the member countries of the Asian Development Bank (ADB). Various initiatives in enhancing the efficiency of risk assessment of PCBs have failed in increasing financing accessibility in the traditional financing system where information asymmetry is a key constraint. In this circumstance, PCBs need to undertake a holistic approach. Holistic approach refers to methods that attempt to fundamentally change established traditions. To undertake holistic approach, this study intends to find the entire established financing culture between PCBs and SMEs in a new lens beyond the tradition on the basis of two basic questions: “What is the traditional lending culture between PCBs and SMEs” and “What could be potential role of PCBs to develop that culture where focusing on SME financing to PCBs". This study considered formal SME financing in Bangladesh by focusing on SMEs applying for their first loan. Bangladesh is a member country of ADB. The data collection method is semi-structured and we utilized face-to-face interviews with in-depth branch managers, higher officials and owner-managers of SME customers of PCBs and higher officials of SME Foundation and the Bangladesh central bank. Discourse analysis method was used for data analysis on the frame of thematic discussion fully based on participants’ views. The research found that branch managers and loan officers have a high level of power in assessing and financing decision-making. There is a changing attitude in PCB sector in requiring flexible collateral assets. Branch managers (Loan Officers) consider value of business prospect of owner-mangers as complementary of collateral assets. However, the study found the assessment process of business prospect is entirely unstructured and linked with socio-cultural settings that does not support PCBs’ changing manner in terms of collateral requirement. The study redefined and classified collateral assets to include all financing constructs in a structure. The degree of value of the collateral assets determines the degree of business prospects. This study suggested applying an outside classroom-learning paradigm such as “knowledge tour” to enhance the value of the kinds of collateral assets. This is the scope of PCBs in increasing SMEs’ financing eligibility in win-win basis. The findings and proposition could be effective in other ADB member countries and audiences in the field.

Keywords: CCA, financing, information asymmetry, PCA, PCB, financing.

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s system. Naturally exchanged patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s system. The Probabilistic Risk Assessment (PRA) technique is utilized to assess the safety of an industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA-safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and rural areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is predicted for multiple factors distribution schemes of multi-criteria analysis. The input–output analysis is explored from the spillover effect, and we conducted Monte Carlo simulations for sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the composite index for biosphere with collective structure of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in an artistic/architectural perspective. The hypothesis is deployed to unify analytic and analogical spatial structure in development urban environments using optimization loads as an example of integrated industrial structure where the process is based on engineering topology of systems ecology.

Keywords: Spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology.

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Authors: Helen Zhang

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Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogenous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning.

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Authors: W. Zekri

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This paper explores Zohra Drif’s memoir, Inside the Battle of Algiers, which narrates her desires as a student to become a revolutionary activist. She exemplified, in her narrative, the different roles, she and her fellows performed as combatants in the Casbah during the Algerian Revolution 1954-1962. This book review aims to evaluate the concept of women’s agency through education and language learning, and its impact on empowering women’s desires. Close-reading method and thematic analysis are used to explore the text. The analysis identified themes that refine the meaning of agency which are social and cultural supports, education, and language proficiency. These themes aim to contribute to the representation in Inside the Battle of Algiers of a woman guerrilla who engaged herself to perform national acts of resistance.

Keywords: Agency, education, learning, women.

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Authors: A. Zeynolabedin, M. A. Olyaei, B. Ghiasi

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Drought is an inevitable part of the earth’s climate. It occurs regularly with no clear warning and without recognizing borders. In addition, its impact is cumulative and not immediately discernible. Iran is located in a semi-arid region where droughts occur periodically as natural hazard. Standardized Precipitation Index (SPI), Surface Water Supply Index (SWSI), and Palmer Drought Severity Index (PDSI) are three well-known indices which describe drought severity; each has its own advantages and disadvantages and can be used for specific types of drought. These indices take into account some factors such as precipitation, reservoir storage and discharge, temperature, and potential evapotranspiration in determining drought severity. In this paper, first all three indices are calculated in Aharchay river watershed located in northwestern part of Iran in East Azarbaijan province. Next, based on two other important parameters which are groundwater level and solar radiation, two new indices are defined. Finally, considering all five aforementioned indices, a combined drought index (CDI) is presented and calculated for the region. This combined index is based on all the meteorological, hydrological, and agricultural features of the region. The results show that the most severe drought condition in Aharchay watershed happened in Jun, 2004. The result of this study can be used for monitoring drought and prepare for the drought mitigation planning.

Keywords: Drought, index variation, regional assessment, monitoring.

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Authors: Watcharawalee Lertlum, Borworn Papasratorn

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Previous researches found that conventional WBL is effective for meaningful learner, because rote learner learn by repeating without thinking or trying to understand. It is impossible to have full benefit from conventional WBL. Understanding of rote learner-s intention and what influences it becomes important. Poorly designed user interface will discourage rote learner-s cultivation and intention to use WBL. Thus, user interface design is an important factor especially when WBL is used as comprehensive replacement of conventional teaching. This research proposes the influencing factors that can enhance learner-s intention to use the system. The enhanced TAM is used for evaluating the proposed factors. The research result points out that factors influencing rote learner-s intention are Perceived Usefulness of Homepage Content Structure, Perceived User Friendly Interface, Perceived Hedonic Component, and Perceived (homepage) Visual Attractiveness.

Keywords: Web-Based learning, Electronic learning, Intentionto use, Rote learner, Influencing

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Authors: Hassan Haghighi, Sajad Ghorbani, Maryam Mohebati, Mohammad Mahdi Javanmard

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One of the most important aspects expected from ERP systems is to integrate various operations existing in administrative, financial, commercial, human resources, and production departments of the consumer organization. Also, it is often needed to integrate the new ERP system with the organization legacy systems when implementing the ERP package in the organization. Without relying on an appropriate software architecture to realize the required integration, ERP implementation processes become error prone and time consuming; in some cases, the ERP implementation may even encounters serious risks. In this paper, we propose a new architecture that is based on the agent oriented vision and supplies the integration expected from ERP systems using several independent but cooperator agents. Besides integration which is the main issue of this paper, the presented architecture will address some aspects of intelligence and learning capabilities existing in ERP systems

Keywords: enterprise resource planning, software architecture, agent oriented architecture, integration, intelligence, learning.

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Authors: Bing Lu, Shuang Li, Hongyuan Zhou

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The steel-concrete hybrid structure has been extensively employed in high-rise buildings and super high-rise buildings. The light gauge steel-concrete hybrid structure, including light gauge steel structure and concrete hybrid structure, is a type of steel-concrete hybrid structure, which possesses some advantages of light gauge steel structure and concrete hybrid structure. The seismic behavior and loss assessment of three high-rise buildings with three different concrete hybrid structures were investigated through finite element software. The three concrete hybrid structures are reinforced concrete column-steel beam (RC-S) hybrid structure, concrete-filled steel tube column-steel beam (CFST-S) hybrid structure, and tubed concrete column-steel beam (TC-S) hybrid structure. The nonlinear time-history analysis of three high-rise buildings under 80 earthquakes was carried out. After simulation, it indicated that the seismic performances of three high-rise buildings were superior. Under extremely rare earthquakes, the maximum inter-story drifts of three high-rise buildings are significantly lower than 1/50. The inter-story drift and floor acceleration of high-rise building with CFST-S hybrid structure were bigger than those of high-rise buildings with RC-S hybrid structure, and smaller than those of high-rise building with TC-S hybrid structure. Then, based on the time-history analysis results, the post-earthquake repair cost ratio and repair time of three high-rise buildings were predicted through an economic performance analysis method proposed in FEMA-P58 report. Under frequent earthquakes, basic earthquakes and rare earthquakes, the repair cost ratio and repair time of three high-rise buildings were less than 5% and 15 days, respectively. Under extremely rare earthquakes, the repair cost ratio and repair time of high-rise buildings with TC-S hybrid structure were the most among three high rise buildings. Due to the advantages of CFST-S hybrid structure, it could be extensively employed in high-rise buildings subjected to earthquake excitations.

Keywords: seismic behavior, loss assessment, light gauge steel, concrete hybrid structure, high-rise building, time-history analysis

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Authors: C. Barreto Carvalho, C. da Motta, M. Sousa, J. Cabral, A. L. Carvalho, E. B. Peixoto

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The aim of the current study was to develop and validate a Response to Stressful Situations Scale (RSSS) for the Portuguese population. This scale assesses the degree of stress experienced in scenarios that can constitute positive, negative and more neutral stressors, and also describes the physiological, emotional and behavioral reactions to those events according to their intensity. These scenarios include typical stressor scenarios relevant to patients with schizophrenia, which are currently absent from most scales, assessing specific risks that these stressors may bring on subjects, which may prove useful in non-clinical and clinical populations (i.e. Patients with mood or anxiety disorders, schizophrenia). Results from Principal Components Analysis and Confirmatory Factor Analysis of two adult samples from general population allowed to confirm a three-factor model with good fit indices: χ2 (144)= 370.211, p = 0.000; GFI = 0.928; CFI = 0.927; TLI = 0.914, RMSEA = 0.055, P(rmsea ≤0.005) = .096; PCFI = .781. Further data analysis of the scale revealed that RSSS is an adequate assessment tool of stress response in adults to be used in further research and clinical settings, with good psychometric characteristics, adequate divergent and convergent validity, good temporal stability and high internal consistency.

Keywords: Assessment, stress events, stress response, stress vulnerability.

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Authors: Roberto Iglesias, Theocharis Kyriacou, Ulrich Nehmzow, Steve Billings

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Fundamental sensor-motor couplings form the backbone of most mobile robot control tasks, and often need to be implemented fast, efficiently and nevertheless reliably. Machine learning techniques are therefore often used to obtain the desired sensor-motor competences. In this paper we present an alternative to established machine learning methods such as artificial neural networks, that is very fast, easy to implement, and has the distinct advantage that it generates transparent, analysable sensor-motor couplings: system identification through nonlinear polynomial mapping. This work, which is part of the RobotMODIC project at the universities of Essex and Sheffield, aims to develop a theoretical understanding of the interaction between the robot and its environment. One of the purposes of this research is to enable the principled design of robot control programs. As a first step towards this aim we model the behaviour of the robot, as this emerges from its interaction with the environment, with the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving Average models with eXogenous inputs). This method produces explicit polynomial functions that can be subsequently analysed using established mathematical methods. In this paper we demonstrate the fidelity of the obtained NARMAX models in the challenging task of robot route learning; we present a set of experiments in which a Magellan Pro mobile robot was taught to follow four different routes, always using the same mechanism to obtain the required control law.

Keywords: Mobile robotics, system identification, non-linear modelling, NARMAX.

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include the cost of infrastructure, personnel, and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion, and various indirect costs in terms of air transport. This research aims to predict the probabilistic crash prediction of vehicles using Machine Learning due to natural and structural reasons by excluding spontaneous reasons, like overspeeding, etc., in the United States. These factors range from meteorological elements such as weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity, to human-made structures, like road structure components such as Bumps, Roundabouts, No Exit, Turning Loops, Give Away, etc. The probabilities are categorized into ten distinct classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes in all states collected by the US government. The probability of the crash was determined by employing Multinomial Expected Value, and a classification label was assigned accordingly. We applied three classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-depth insights through exploratory data analysis.

Keywords: Road safety, crash prediction, exploratory analysis, machine learning.

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Authors: Inam Shamsher, Zaheer Ahmad, Jehanzeb Khan Orakzai, Awais Adnan

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This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.

Keywords: Algorithm, Feed Forward Neural Networks, Supervised learning, Pattern Matching.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI) is a hybrid e-framework for the development of a web-based instruction (WBI), which contributes towards instructional design and language development. WeCWI divides its contribution in instructional design into macro and micro perspectives. In macro perspective, being a 21st century educator by disseminating knowledge and sharing ideas with the in-class and global learners is initiated. By leveraging the virtue of technology, WeCWI aims to transform an educator into an aggregator, curator, publisher, social networker and ultimately, a web-based instructor. Since the most notable contribution of integrating technology is being a tool of teaching as well as a stimulus for learning, WeCWI focuses on the use of contemporary web tools based on the multiple roles played by the 21st century educator. The micro perspective in instructional design draws attention to the pedagogical approaches focusing on three main aspects: reading, discussion, and writing. With the effective use of pedagogical approaches through free reading and enterprises, technology adds new dimensions and expands the boundaries of learning capacity. Lastly, WeCWI also imparts the fundamental theories and models for web-based instructors’ awareness such as interactionist theory, cognitive information processing (CIP) theory, computer-mediated communication (CMC), e-learning interactionalbased model, inquiry models, sensory mind model, and leaning styles model.

Keywords: WeCWI, instructional discovery, technological discovery, pedagogical discovery, theoretical discovery.

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Authors: Ali Osman Güney, Bahattin Kanber

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In this work, the effect of material type, diameter, orientation and closeness of fibers on the general performance of reinforced vulcanized rubbers are investigated using finite element method with experimental verification. Various fiber materials such as hemp, nylon, polyester are used for different fiber diameters, orientations and closeness. 3D finite element models are developed by considering bonded contact elements between fiber and rubber sheet interfaces. The fibers are assumed as linear elastic, while vulcanized rubber is considered as hyper-elastic. After an experimental verification of finite element results, the developed models are analyzed under prescribed displacement that causes tension. The normal stresses in fibers and shear stresses between fibers and rubber sheet are investigated in all models. Large deformation of reinforced rubber sheet also represented with various fiber conditions under incremental loading. A general assessment is achieved about best fiber properties of reinforced rubber sheets for tension-load conditions.

Keywords: Fiber properties, finite element method, tension-load condition, reinforced vulcanized rubbers.

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Authors: Elizabeth D. Ramos

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Peace education supports a holistic appreciation for the value of life and the interdependence of all living systems. Peace education aims to build a culture of peace. One way of building a culture of peace is through environmental stewardship. This study sought to find out the environmental stewardship practices in selected Higher Education Institutions (HEIs) in the Philippines and how these environmental stewardship practices lead to building a culture of peace. The findings revealed that there is still room for improvement in implementing environmental stewardship in schools through academic service learning. In addition, the following manifestations are implemented very satisfactorily in schools: 1) waste reduction, reuse, and recycling, 2) community service, and 3) clean and green surroundings. Administrators of schools in the study lead their staff and students in implementing environmental stewardship. It could be concluded that those involved in environmental stewardship display an acceptable culture of peace, particularly solidarity, respect for persons, and inner peace.

Keywords: Academic service learning, environmental stewardship, leadership support, peace, solidarity.

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Authors: G. Ghodrati Amiri, M. Khorasani, Razavian Ameri, M.Mohamadi Dehcheshmeh, S.Fathi

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Many studies have been conducted for derivation of attenuation relationships worldwide, however few relationships have been developed to use for the seismic region of Iranian plateau and only few of these studies have been conducted for derivation of attenuation relationships for parameters such as uniform duration. Uniform duration is the total time during which the acceleration is larger than a given threshold value (default is 5% of PGA). In this study, the database was same as that used previously by Ghodrati Amiri et al. (2007) with same correction methods for earthquake records in Iran. However in this study, records from earthquakes with MS< 4.0 were excluded from this database, each record has individually filtered afterward, and therefore the dataset has been expanded. These new set of attenuation relationships for Iran are derived based on tectonic conditions with soil classification into rock and soil. Earthquake parameters were chosen to be hypocentral distance and magnitude in order to make it easier to use the relationships for seismic hazard analysis. Tehran is the capital city of Iran wit ha large number of important structures. In this study, a probabilistic approach has been utilized for seismic hazard assessment of this city. The resulting uniform duration against return period diagrams are suggested to be used in any projects in the area.

Keywords: Attenuation Relationships, Iran, Probabilistic Seismic Hazard Analysis, Tehran, Uniform Duration

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Authors: Päivi Aarreniemi-Jokipelto, Merja Alanko-Turunen

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The possibilities of mobile technology generate new demands for vocational teacher trainers to transform their approach to work and to incorporate its usage into their ordinary educational practice. This paper presents findings of a focus discussion group (FDG) session on the usage of iPads within a school of vocational teacher education (SoVTE). It aims to clarify how the teacher trainers are using iPads and what has changed in their work during the usage of iPads. The analytical framework bases on content analysis and expansive learning cycle. It was not only found what kind of a role iPads played in their daily practices but it brought also into attention how a cultural change regarding the usage of social media and mobile technology was desperately needed in the whole work community. Thus, the FGD was abducted for developing the knowledge practices of the community of the SoVTE.

Keywords: iPad, mobile learning, vocational teacher education.

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: Hassan Haleh, Amin Ghaffari, Parisa Farahpour

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Need for an appropriate system of evaluating students- educational developments is a key problem to achieve the predefined educational goals. Intensity of the related papers in the last years; that tries to proof or disproof the necessity and adequacy of the students assessment; is the corroborator of this matter. Some of these studies tried to increase the precision of determining question weights in scientific examinations. But in all of them there has been an attempt to adjust the initial question weights while the accuracy and precision of those initial question weights are still under question. Thus In order to increase the precision of the assessment process of students- educational development, the present study tries to propose a new method for determining the initial question weights by considering the factors of questions like: difficulty, importance and complexity; and implementing a combined method of PROMETHEE and fuzzy analytic network process using a data mining approach to improve the model-s inputs. The result of the implemented case study proves the development of performance and precision of the proposed model.

Keywords: Assessing students, Analytic network process, Clustering, Data mining, Fuzzy sets, Multi-criteria decision making, and Preference function.

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: Facial expression recognition, image pre-processing, deep learning, CNN.

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Authors: Kholoud H. Al-Zedjali, Abir S. Al-Harrasi, Ali H. Al-Badi

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Recently there has been a dramatic proliferation in the number of social networking sites (SNSs) users; however, little is published about what motivates college students to use SNSs in education. The main goal of this research is to explore the college students’ motives for using SNSs in education. A conceptual framework has therefore been developed to identify the main factors that influence/motivate students to use social networking sites for learning purposes. To achieve the research objectives a quantitative method was used to collect data. A questionnaire has been distributed amongst college students. The results reveal that social influence, perceived enjoyment, institute regulation, perceived usefulness, ranking up-lift, attractiveness, communication tools, free of charge, sharing material and course nature all play an important role in the motivation of college students to use SNSs for learning purposes.

Keywords: Social networking sites (SNSs), education, college students.

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Authors: Juris Burlakovs, Maris Klavins, Raimonds Ernsteins, Armands Ruskulis

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Environmental contamination is a common problem in ex-industrial and industrial sites. This article gives a brief description of general applied environmental investigation methodologies and possible remediation applications in Latvia. Most of contaminated areas are situated in former and active industrial, military areas and ports. Industrial and logistic activities very often have been with great impact for more than hundred years thus the contamination level with heavy metals, hydrocarbons, pesticides, persistent organic pollutants is high and is threatening health and environment in general. 242 territories now are numbered as contaminated and fixed in the National Register of contaminated territories in Latvia. Research and remediation of contamination in densely populated areas are of important environmental policy domain. Four different investigation case studies of contaminated areas are given describing the history of use, environmental quality assessment as well as planned environmental management actions. All four case study locations are situated in Riga - the capital of the Republic of Latvia. The aim of this paper is to analyze the situation and problems with management of contaminated areas in Latvia, give description of field research methods and recommendations for remediation industry based on scientific data and innovations.

Keywords: Remediation technology, environmental quality assessment, heavy metals, hydrocarbon contamination, environmental management.

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Authors: Jenny Hall, Alison Jaquet

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Universities’ push toward the production of high quality research is not limited to academic staff and experienced researchers. In this environment of research rich agendas, Higher Degree Research (HDR) students are increasingly expected to engage in the publishing of good quality papers in high impact journals. IFN001: Advanced Information Research Skills (AIRS) is a credit bearing mandatory coursework requirement for Queensland University of Technology (QUT) doctorates. Since its inception in 1989, this unique blended learning program has provided the foundations for new researchers to produce original and innovative research. AIRS was redeveloped in 2012, and has now been evaluated with reference to the university’s strategic research priorities. Our research is the first comprehensive evaluation of the program from the learner perspective. We measured whether the program develops essential transferrable skills and graduate capabilities to ensure best practice in the areas of publishing and data management. In particular, we explored whether AIRS prepares students to be agile researchers with the skills to adapt to different research contexts both within and outside academia. The target group for our study consisted of HDR students and supervisors at QUT. Both quantitative and qualitative research methods were used for data collection. Gathering data was by survey and focus groups with qualitative responses analyzed using NVivo. The results of the survey show that 82% of students surveyed believe that AIRS assisted their research process and helped them learn skills they need as a researcher. The 18% of respondents who expressed reservation about the benefits of AIRS were also examined to determine the key areas of concern. These included trends related to the timing of the program early in the candidature and a belief among some students that their previous research experience was sufficient for postgraduate study. New insights have been gained into how to better support HDR learners in partnership with supervisors and how to enhance learning experiences of specific cohorts, including international students and mature learners.

Keywords: Data management, enhancing learning experience, publishing, research higher degree students.

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: Customer relationship management, churn prediction, telecom industry, deep learning, Artificial Neural Networks, ANN.

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Authors: Jeff A. Tysinger, Dawn P. Tysinger

Abstract:

There has been considerable growth in online learning. Researchers continue to explore the impact various methods of delivery. Podcasting is a popular method for sharing information. The purpose of this study was to examine the impact of student motivation and the perception of the acquisition of knowledge in an online environment of a skill-based class. 25 students in a school psychology graduate class completed a pretest and posttest examining podcast use and familiarity. In addition, at the completion of the course they were administered a modified version of the Instructional Materials Motivation Survey. The four subscales were examined (attention, relevance, confidence, and satisfaction). Results indicated that students are motivated, they perceive podcasts as positive instructional tools, and students are successful in acquiring the needed information. Additional benefits of using podcasts and recommendations in school psychology training are discussed.

Keywords: Motivation, online learning, pedagogy, podcast.

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Authors: M. Armenteros, A. Domínguez, M. Fernández, A. J. Benítez

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The following paper describes the video database tool used by the Fédération Internationale de Football Association (FIFA) as part of the research project developed in collaboration with the Carlos III University of Madrid. The database project began in 2012, with the aim of creating an educational tool for the training of instructors, referees and assistant referees, and it has been used in all FUTURO III courses since 2013. The platform now contains 3,135 video clips of different match situations from FIFA competitions. It has 1,835 users (FIFA instructors, referees and assistant referees). In this work, the main features of the database are described, such as the use of a search tool and the creation of multimedia presentations and video quizzes. The database has been developed in MySQL, ActionScript, Ruby on Rails and HTML. This tool has been rated by users as "very good" in all courses, which prompt us to introduce it as an ideal tool for any other sport that requires the use of video analysis.

Keywords: Video database, FIFA, refereeing, e-learning.

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Authors: Vladimir Rastunkov, Jae-Eun Park, Abhijit Mitra, Brian Quanz, Steve Wood, Christopher Codella, Heather Higgins, Joseph Broz

Abstract:

Quantum Support Vector Machines (QSVM) have become an important tool in research and applications of quantum kernel methods. In this work we propose a boosting approach for building ensembles of QSVM models and assess performance improvement across multiple datasets. This approach is derived from the best ensemble building practices that worked well in traditional machine learning and thus should push the limits of quantum model performance even further. We find that in some cases, a single QSVM model with tuned hyperparameters is sufficient to simulate the data, while in others - an ensemble of QSVMs that are forced to do exploration of the feature space via proposed method is beneficial.

Keywords: QSVM, Quantum Support Vector Machines, quantum kernel, boosting, ensemble.

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