Search results for: students with learning disabilities

Authors: Ausra Turcinskaite-Balciuniene, Jonas Balciunas, Gediminas Merkys

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The problematic of gender and socioeconomic status biased differences in academic motivation patterns is discussed. Gender identity is understood according to symbolic interactionism perspective: as a result of reflected appraisals, social comparisons, self-attributions, and identifications, shaped by social environment and family context. The effects of socioeconomic status on academic motivation are conceptualized according to Bourdieu’s habitus concept, reflecting the role of unconscious and internalized cultural signals, proper to low and high socioeconomic status family contexts. Since families differ by various socioeconomic features, the hypothesis about possible impact of parents’ socioeconomic status on their children’s academic motivation interfering with gender socialization effects is held. The survey, aiming to seize gender differences in academic motivation and self-recorded improvement-oriented efforts as a result of socialization processes operating in the families of low and high socioeconomic status, was designed. The results of Lithuanian higher education students’ survey are presented and discussed.

Keywords: academic motivation, gender, socialization, socioeconomic status

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Authors: Hafiz M. Inamullah, Altaf Ullah

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Environmental degradation is a serious issue that has adverse impacts on the human population locally, regionally, and globally. There is a dire need to adopt an environmentally friendly lifestyle to minimize further environmental degradation. One of the mediums through which environmentally friendly attitudes and behavior may be inculcated is through school education. The purpose of this study was to investigate environmental activities organized in High Schools of District Peshawar. The population for this study was comprised of 77 Headmasters of the High Schools in District Peshawar. A sample of 65 Headmasters was selected randomly from the above-mentioned population. One questionnaire was developed from the relevant literature for the Headmasters and was self-administered by the researcher. The collected data was entered into Excel and was analyzed and interpreted through SPSS 20 using the frequencies and percentages, and the Chi-square test was applied. The results indicated that most high schools had never organized environmental activities for secondary-level students. It was suggested that the high schools might organize various environmental activities such as plantations, park visits, debate competitions, environmental clubs, and drawing competitions.

Keywords: proinvirmenlaism, Khyber Pakhtunkhwa, secondary level, Peshawar

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Authors: M. M. El-Awad

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This paper deals with the introduction of thermal-design optimisation to engineering students by using Microsoft's Excel as a modelling platform. Thermal-design optimisation is an iterative process which involves the evaluation of many thermo-physical properties that vary with temperature and/or pressure. Therefore, suitable modelling software, such as Engineering Equation Solver (EES) or Interactive Thermodynamics (IT), is usually used for this purpose. However, such proprietary applications may not be available to many educational institutions in developing countries. This paper presents a simple thermal-design case that demonstrates how the principles of thermo-fluids and economics can be jointly applied so as to find an optimum solution to a thermal-design problem. The paper describes the solution steps and provides all the equations needed to solve the case with Microsoft Excel. The paper also highlights the advantage of using VBA (Visual Basic for Applications) for developing user-defined functions when repetitive or complex calculations are met. VBA makes Excel a powerful, yet affordable, the computational platform for introducing various engineering principles.

Keywords: engineering education, thermal design, Excel, VBA, user-defined functions

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Authors: Siriporn Poolsuwan, Kanyarat Bussaban

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This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization.

Keywords: online database, user behavior, news clipping, library services

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Authors: Firas M. Tuaimah

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This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity. The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: short-term load forecasting, artificial neural networks, back propagation learning, hourly load demand

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Authors: Netasha Shaikh, Bryony Wood, Demitra Tsivos, Michael Knight, Risto Kauppinen, Elizabeth Coulthard

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Background: Effective treatment of dementia will require early diagnosis, before significant brain damage has accumulated. Memory loss is an early symptom of Alzheimer’s disease (AD). The hippocampus, a brain area critical for memory, degenerates early in the course of AD. The hippocampus comprises several subfields. In contrast to healthy aging where CA3 and dentate gyrus are the hippocampal subfields with most prominent atrophy, in AD the CA1 and subiculum are thought to be affected early. Conventional clinical structural neuroimaging is not sufficiently sensitive to identify preferential atrophy in individual subfields. Here, we will explore the sensitivity of new magnetic resonance imaging (MRI) sequences designed to interrogate medial temporal regions as an early marker of Alzheimer’s. As it is likely a combination of tests may predict early Alzheimer’s disease (AD) better than any single test, we look at the potential efficacy of such imaging alone and in combination with standard and novel cognitive tasks of hippocampal dependent memory. Methods: 20 patients with mild cognitive impairment (MCI), 20 with mild-moderate AD and 20 age-matched healthy elderly controls (HC) are being recruited to undergo 3T MRI (with sequences designed to allow volumetric analysis of hippocampal subfields) and a battery of cognitive tasks (including Paired Associative Learning from CANTAB, Hopkins Verbal Learning Test and a novel hippocampal-dependent abstract word memory task). AD participants and healthy controls are being tested just once whereas patients with MCI will be tested twice a year apart. We will compare subfield size between groups and correlate subfield size with cognitive performance on our tasks. In the MCI group, we will explore the relationship between subfield volume, cognitive test performance and deterioration in clinical condition over a year. Results: Preliminary data (currently on 16 participants: 2 AD; 4 MCI; 9 HC) have revealed subfield size differences between subject groups. Patients with AD perform with less accuracy on tasks of hippocampal-dependent memory, and MCI patient performance and reaction times also differ from healthy controls. With further testing, we hope to delineate how subfield-specific atrophy corresponds with changes in cognitive function, and characterise how this progresses over the time course of the disease. Conclusion: Novel sequences on a MRI scanner such as those in route in clinical use can be used to delineate hippocampal subfields in patients with and without dementia. Preliminary data suggest that such subfield analysis, perhaps in combination with cognitive tasks, may be an early marker of AD.

Keywords: Alzheimer's disease, dementia, memory, cognition, hippocampus

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Authors: Murtaza Hassan Sheikh, Ahmed A. A. AlSaleh, Naser H. N. Jasem

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Kuwait has not yet made its mark in the world of technology and research. Therefore, advancements have been made to fill in this gap. Since Robotics covers a wide variety of fields and helps innovation, efforts have been made to promote its education. Despite of the efforts made in Kuwait, robotics education is still on hold. The paper discusses the issues and obstacles in the implementation of robotics education in Kuwait and how a robotics kit “E-Robot” is making an impact in the Kuwait’s future education and innovation. Problems such as robotics competitions rather than education, complexity of robot programming and lack of organized open source platform are being addressed by the introduction of the E-Robot Kit in Kuwait. Due to its success since 2012 a total of 15 schools have accepted the Kit as a core subject, with 200 teaching it as an extracurricular activity.

Keywords: robotics education, Kuwait's education, e-robot kit, research and development, innovation and creativity

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Authors: Dmitry Fedoseyev

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The ultimate success of unmanned aerial vehicles (UAVs) depends largely on the effective control of their flight, especially in variable wind conditions. This paper investigates different approaches to selecting the optimal flight level to maximize the range of UAVs. We propose to consider methods based on mathematical models of atmospheric conditions, as well as the use of sensor data and machine learning algorithms to automatically optimize the flight level in real-time. The proposed approaches promise to improve the efficiency and range of UAVs in various wind conditions, which may have significant implications for the application of these systems in various fields, including geodesy, environmental surveillance, and search and rescue operations.

Keywords: drone, UAV, flight trajectory, wind-searching, efficiency

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

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Authors: Norfiza Ibrahim, Norshuhada Shiratuddin, Siti Mahfuzah Sarif

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Decision-making system is used to facilitate people in making the right choice for their important daily activities. For the youth, proper guidance in making important decisions is needed. Their skills in decision-making aid decisions will indirectly affect their future. For that reason, this study focuses on the intelligent aspects in the development of intelligent decision support application. The aid apparently integrates Personality Traits (PT) and Multiple Intelligence (MI) data in development of a computerized personal decision aid for youth named as Youth Personal Decision Aid (Youth PDA). This study is concerned with the aid’s helpfulness based on the hybrid intelligent process. There are four main items involved which are reliability, decision making effort, confidence, as well as decision process awareness. Survey method was applied to the actual user of this system, namely the school and the Institute of Higher Education (IPT)’s students. An establish instrument was used to evaluate the study. The results of the analysis and findings in the assessment indicates a high mean value of the four dimensions in helping Youth PDA to be accepted as a useful tool for the youth in decision-making.

Keywords: decision support, multiple intelligent, personality traits, youth personal decision aid

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Authors: Fariea Bakul, Chhanda Karmaker

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The present study was designed to investigate the effects of parental bonding on adult’s cognitive emotion regulation and also to investigate gender differences in parental bonding and cognitive emotion regulation. Data were collected by using convenience sampling technique from 100 adult students (50 males and 50 females) of different universities of Dhaka city, ages between 20 to 25 years, using Bengali version of Parental Bonding Inventory and Bengali version of Cognitive Emotion Regulation Questionnaire. The obtained data were analyzed by using multiple regression analysis and independent samples t-test. The results revealed that fathers care (β =0.317, p < 0.05) was only significantly positively associated with adult’s cognitive emotion regulation. Adjusted R² indicated that the model explained 30% of the variance in adult’s adaptive cognitive emotion regulation. No significant association was found between parental bonding and less adaptive cognitive emotion regulations. Results from independent samples t-test also revealed that there was no significant gender difference in both parental bonding and cognitive emotion regulations.

Keywords: cognitive emotion regulation, parental bonding, parental care, parental over-protection

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Authors: L. Matthewman, J. Nowlan

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Background: Holistic or Integrative Psychology emphasizes the interdependence of physiological, spiritual and psychological dynamics. Studying “wholeness and well-being” from a systems perspective combines innovative psychological science interventions with Eastern orientated healing wisdoms and therapies. The literature surrounding holistic/integrative psychology focuses on multi-stage interventions in attempts to enhance the mind-body experiences of well-being for participants. This study proposes a new single stage model as an intervention for UG/PG students, time-constrained workplace employees and managers/leaders for improved well-being and life enhancement. The main research objective was to investigate participants’ experiences of holistic and mindfulness interventions for impact on emotional well-being. The main research question asked was if single stage holistic interventions could impact on psychological well-being. This is of consequence because many people report that a reason for not taking part in mind-body or wellness programmes is that they believe that they do not have sufficient time to engage in such pursuits. Experimental Approach: The study employed a mixed methods pre-test/post-test research design. Data was analyzed using descriptive statistics and interpretative phenomenological analysis. Purposive sampling methods were employed. An adapted mindfulness measurement questionnaire (MAAS) was administered to 20 volunteer final year UG student participants prior to the single stage intervention and following the intervention. A further post-test longitudinal follow-up took place one week later. Intervention: The single stage model intervention consisted of a half hour session of mindfulness, yoga stretches and head and neck massage in the following sequence: Mindful awareness of the breath, yoga stretches 1, mindfulness of the body, head and neck massage, mindfulness of sounds, yoga stretches 2 and finished with pure awareness mindfulness. Results: The findings on the pre-test indicated key themes concerning: “being largely unaware of feelings”, “overwhelmed with final year exams”, “juggling other priorities” , “not feeling in control”, “stress” and “negative emotional display episodes”. Themes indicated on the post-test included: ‘more aware of self’, ‘in more control’, ‘immediately more alive’ and ‘just happier’ compared to the pre-test. Themes from post-test 2 indicated similar findings to post-test 1 in terms of themes. but on a lesser scale when scored for intensity. Interestingly, the majority of participants reported that they would now seek other similar interventions in the future and would be likely to engage with a multi-stage intervention type on a longer-term basis. Overall, participants reported increased psychological well-being after the single stage intervention. Conclusion: A single stage one-off intervention model can be effective to help towards the wellbeing of final year UG students. There is little indication to suggest that this would not be generalizable to others in different areas of life and business. However this study must be taken with caution due to low participant numbers. Implications: Single stage one-off interventions can be used to enhance peoples’ lives who might not otherwise sign up for a longer multi-stage intervention. In addition, single stage interventions can be utilized to help participants progress onto longer multiple stage interventions. Finally, further research into one stage well-being interventions is encouraged.

Keywords: holistic/integrative psychology, mindfulness, well-being, yoga

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Authors: Seyed Ahmad Hosseini, Makan Cheraghpour, Saeed Shirali, Roya Rafie, Matin Ghanavati, Arezoo Amjadi, Meysam Alipour

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Background: There is a mutual relationship between sleep duration and obesity. We studied the relationship between sleep duration with obesity and dietary Intake. Methods: This cross-sectional study was conducted on 444 male students in Ahvaz Jundishapur University of Medical Science. Dietary intake was analyzed by food frequency questionnaire (FFQ). Anthropometric indices were analyzed. Participants were being asked about their sleep duration and they were categorized into three groups according to their responses (less than six hours, between six and eight hours, and more than eight hours). Results: Macronutrient, micronutrient, and antioxidant intake did not show significant difference between three groups. Moreover, we did not observe any significant difference between anthropometric indices (weight, body mass index, waist circumference, and percentage body fat). Conclusions: Our study results show no significant relationship between sleep duration, nutrition pattern, and obesity. Further study is recommended.

Keywords: sleep duration, obesity, dietary intake, cross-sectional

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Authors: Maria R. A. R. Moreira, Francisco R. O. Da Silva, André O. A. Fontenele, Érick A. Ribeiro

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This article deals with the influence of technology in education showing educational robotics as pedagogical method of solution for knowledge building. We are proposing the development and implementation of four robot models that can be used for teaching purposes involving the areas of mechatronics, mechanics, electronics and computing, making it efficient for learning other sciences and theories. One of the main reasons for application of the developed educational kits is its low cost, allowing its applicability to a greater number of educational institutions. The technology will add to education dissemination of knowledge by means of experiments in such a way that the pedagogical robotics promotes understanding, practice, solution and criticism about classroom challenges. We also present the relationship between education, science, technology and society through educational robotics, treated as an incentive to technological careers.

Keywords: education, mecatronics, robotics, technology

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Authors: Santoshi Halder, Ranjini Ghosh

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Research on educational stratification suggests that inequality in education between different social strata continues and sometimes even widens in spite of educational growth. The backward classes are the most suppressed classes in society. In India, the Scheduled Castes are found as one of the backward classes. After independence there a lot of provisions were made for their uplift. Still they are facing a lot of problems in perusing education, getting jobs, choosing life style independently etc. The present study was conducted to explore the educational disparities in education with respect to caste. Sample consisted of 1020 students (540 scheduled caste and 540 general caste) from three different universities of West Bengal. Tools selected were General Information Schedule (GIS), socioeconomic status (SES), Achievement motivation scale. Findings indicated significant differences for the selected variables under the study with respect to caste. Findings have significant implication for the advocates, policy makers and educationists and sociologists for appropriate intervention.

Keywords: scheduled caste, educational barriers, achievement motivation, socioeconomic status

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Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

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This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: control, fuzzy logic, sensitive system, technological proves

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Somayyeh Naeemi, Ezhar Tamam

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In most of the countries, Facebook allocated high rank of usage among other social network sites. Several studies have examined the effect of Facebook intensity on individuals’ psychological well-being. However, few studies have investigated its effect on eudaimonic well-being. The current study explored how emotional dependency to Facebook relates to psychological well-being in terms of eudaimonic well-being. The number of 402 adolescents 13-16 years old who studied in upper secondary school in Malaysia participated in this study. It was expected to find out a negative association between emotional dependency to Facebook and time spent on Facebook and psychological well-being. It also was examined the moderation effects of self-efficacy on psychological well-being. The results by Structural Equation Modeling revealed that emotional dependency to Facebook has a negative effect on adolescents’ psychological well-being. Surprisingly self-efficacy did not have moderation effect on the relationship between emotional dependency to Facebook and psychological well-being. Lastly, the emotional dependency to Facebook and not the time spent on Facebook lessen adolescents’ psychological well-being, suggesting the value of investigating Facebook usage among college students in future studies.

Keywords: emotional dependency to facebook, psychological well-being, eudaimonic well-being, self-efficacy, adolescent

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Authors: Gholam Reza Parvizi, Ali Reza Kargar, Amir Arani

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In the present days, learning and teaching researchers have emphasized the role which teachers, tutors, and trainers’ constraint knowledge treat in resizing and trimming what they perform in educational atmosphere. Regarding English language as subject to teaching, although the prominence of instructor’s knowledge about grammar has also been stressed, but the lack of empirical insights into the relationship between teacher’ self-monitoring and self-response of grammar knowledge have been observed. With particular attention to the grammar this article indicates and discusses information obtained self- feedback and conversing teachers of a kind who backwash the issue. The result of the study indicates that enabling teachers to progress and maintain a logical and realistic awareness of their knowledge about grammar have to be prominent goal for teachers’ education and development programs.

Keywords: grammar knowledge, self-monitoring, self-response, teaching grammar, language teaching program

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Authors: Ennios Eros Giogos, Nefeli Katsarou, Giota Mantziorou, Elena Panou, Nikolaos Kourniatis, Socratis Giannoudis

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In the context of the postgraduate course Productive Design, Department of Interior Architecture of the University of West Attica in Athens, under the guidance of Professors Nikolaos Koyrniatis and Socratis Giannoudis, kinetic mechanisms with parametric models were examined for their further application in the design of objects. In the first phase, the students studied a motion mechanism that they chose from daily experience and then analyzed its geometric structure in relation to the geometric transformations that exist. In the second phase, the students tried to design it through a parametric model in Grasshopper3d for Rhino algorithmic processor and plan the design of its application in an everyday object. For the project presented, our team began by studying the movement of living beings, specifically the snake. By studying the snake and the role that the environment has in its movement, four basic typologies were recognized: serpentine, concertina, sidewinding and rectilinear locomotion, as well as its ability to perform spiral formations. Most typologies are characterized by ripples, a series of sinusoidal curves. For the application of the snake movement in a polymorphic space divider, the use of a coil-type joint was studied. In the Grasshopper program, the simulation of the desired motion for the polymorphic surface was tested by applying a coil on a sinusoidal curve and a spiral curve. It was important throughout the process that the points corresponding to the nodes of the real object remain constant in number, as well as the distances between them and the elasticity of the construction had to be achieved through a modular movement of the coil and not some elastic element (material) at the nodes. Using mesh (repeating coil), the whole construction is transformed into a supporting body and combines functionality with aesthetics. The set of elements functions as a vertical spatial network, where each element participates in its coherence and stability. Depending on the positions of the elements in terms of the level of support, different perspectives are created in terms of the visual perception of the adjacent space. For the implementation of the model on the scale (1:3), (0.50m.x2.00m.), the load-bearing structure that was studied has aluminum rods for the basic pillars Φ6mm and Φ 2.50 mm, for the secondary columns. Filling elements and nodes are of similar material and were made of MDF surfaces. During the design process, four trapezoidal patterns were picketed, which function as filling elements, while in order to support their assembly, a different engraving facet was done. The nodes have holes that can be pierced by the rods, while their connection point with the patterns has a half-carved recess. The patterns have a corresponding recess. The nodes are of two different types depending on the column that passes through them. The patterns and knots were designed to be cut and engraved using a Laser Cutter and attached to the knots using glue. The parameters participate in the design as mechanisms that generate complex forms and structures through the repetition of constantly changing versions of the parts that compose the object.

Keywords: polymorphic, locomotion, sinusoidal curves, parametric

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Authors: Lenell D. Walton

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African American families have consistently contended that their child’s special education team does not provide the services necessary to meet their child’s academic goals. Special education teams must guide and mentor African American students and their families through the special education process. This qualitative study examined African American female caregivers' perceptions, experiences, and expectations regarding the special education process. Data collection methods utilized in the study included a survey, semi-structured interviews, and three focus groups. Data were analyzed and compared to identify themes. Three themes emerged from the survey: education and training, participation, and challenges. Six major themes emerged: (a) differences in treatment and cultural disconnect, (b) lack of support and resources, (c) participants’ experiences of the special education process, (d) parent participation, (e) barriers and concerns, and (f) expectations. Implications for policy and practice to improve the special education process are discussed.

Keywords: African American, caregivers, critical race theory, special education

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Authors: Sherry Robinson, Hans Anton Stubberud

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Entrepreneurship can take many forms. Traditional entrepreneurs seek profits and growth for the businesses they start themselves. Intrapreneurs act entrepreneurially within a business they do not own. Social entrepreneurs have goals other than (but not excluding) profit and growth as they seek to solve social problems or protect the environment. This type of entrepreneur often focuses on the triple bottom line, which includes a concern for people and the planet as well as profit. Ecopreneurs in particular are driven by their desire to create and promote environmentally sustainable products and processes. All of these entrepreneurs need an entrepreneurial orientation in order to survive and thrive. The three most common elements of an entrepreneurial orientation are (1) creativity and innovation, (2) the willingness to take risks and (3) the proactiveness to put ideas into action. This study describes an interdisciplinary entrepreneurship course integrating topics regarding the triple bottom line with those relevant to an entrepreneurial orientation. The results show that students significantly increased their skill levels in many areas, including soft skills such as communicating and working in teams, as well as designing innovative products and taking calculated risk.

Keywords: creativity, entrepreneurship education, sustainability, triple bottom line

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Authors: Francis E. Idachaba, Sarah Uyimeh Tommy

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This paper describes the design of an RFID laptop monitoring and management system. Laptops embedded with RFID chips are monitored and tracked to provide a monitoring system for the purpose of tracking as well as monitoring movement of the laptops in and out of a building. The proposed system is implemented with both hardware and software components. The hardware architecture consists of RFID passive tag, RFID module (reader), and a server hosting the application and database. The RFID readers are distributed at major exits of a building or premises. The tags are programmed with owner laptop details are concealed in the laptops. The software architecture consists of application software that has the APIs (Applications Programming Interface) necessary to interface the RFID system with the PC, to achieve automated laptop monitoring system. A friendly graphic user interface (GUI) and a database that saves all readings and owners details. The system is capable of reducing laptop theft especially in students’ hostels as laptops can be monitored as they are taken either in or out of the building.

Keywords: asset tracking, GUI, laptop monitoring, radio frequency identification, passive tags

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Authors: Indhumathi Gopal, Ashley Johnson

Abstract:

Social media use for communication among college student-athletes is growing. There is little research on student-athletes use of Blogs, one of the online communication tool outlets. Twenty-seven student-athletes, aged 18-24 years completed a student perception questionnaire which assessed demographics, the effect of blogging on college student-athletes self-concept, the correlation of age, GPA and blogging as well as the training students received in the use of social media. Descriptive statistics and Pearson correlations were analyzed examined. Results indicated a significant correlation between use of Blogs and student age (p < .01) and student GPA earned (p < .01). With respect to self-concept, results suggest that blogging could be a useful tool for communication but can present challenges, could affect student self-esteem either, positively or negatively. The training student-athletes received in the use of social media was not adequate. College athletes’ can more easily divulge information about their personal lives and opinions on social media and challenge the athletic programs and their own future. The findings of the study suggest implications for student-athletes to be better prepared for the current media climate.

Keywords: college student-athletes, self-concept, use of social media training, social networking

Procedia PDF Downloads 598

Authors: Marilyn U. Balagtas, Maria Ruth M. Regalado, Carmelina E. Barrera, Ramer V. Oxiño, Rosarito T. Suatengco, Josephine E. Tondo

Abstract:

This study presents the perceptions of the students and teachers from kindergarten to tertiary level of the image of the 21st century teacher to provide basis in designing teacher development programs in Teacher Education Institutions (TEIs) in the Philippines. The highlights of the report are the personal, psychosocial, and professional images of the 21st century teacher in basic education and the teacher educators based on a survey done to 612 internal stakeholders of nine member institutions of the National Network of Normal Schools (3NS). Data were obtained through the use of a validated researcher-made instrument which allowed generation of both quantitative and qualitative descriptions of the teacher image. Through the use of descriptive statistics, the common images of the teacher were drawn, which were validated and enriched by the information drawn from the qualitative data. The study recommends a repertoire of teacher development programs to create the good image of the 21st century teachers for a better Philippines.

Keywords: teacher image, 21st century teacher, teacher education, development program

Procedia PDF Downloads 372

Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

Procedia PDF Downloads 230

Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

Abstract:

Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

Procedia PDF Downloads 209

Authors: Boulis M. Ibrahim, Iordanis A. Kalaitzoglou

Abstract:

A micro structural pricing model is proposed in which price components account for learning by incorporating changing expectations of the trading intensity and the risk level of incoming trades. An analysis of European carbon futures transactions finds expected trading intensity to increase the information component and decrease the liquidity component of price changes, but at different rates. Among the results, the expected persistence in trading intensity explains the majority of the auto correlations in the level and the conditional volatility of price changes, helps predict hourly patterns in the bid–ask spread and differentiates between the impact of buy versus sell and continuing versus reversing trades.

Keywords: CO2 emission allowances, market microstructure, duration, price discovery

Procedia PDF Downloads 410