Search results for: back propagation learning

Authors: Behdokht Mall-Amiri, Sara Farzaminejad

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The purpose of the present study was to discover which of the two writing activities, a self-assessment questioner or a critical thinking skills handout, is more effective on Iranian EFL learners’ writing ability. To fulfill the purpose of the study, a sample of 120 undergraduate students of English SAT for a standardized sample of PET. Eighty-two students whose scores fell one standard deviation above and below the sample mean were selected and randomly divided into two equal groups. One group practiced self-assessment and the other group practiced critical thinking skills while they were learning process writing. A writing posttest was finally administered to the students in both groups and the mean rank scores were compared by t-test. The result led to the rejection of the null hypothesis, indicating that practicing critical thinking skills had a significantly higher effect on the writing ability. The implications of the study for students and teachers as well as course book designers are discussed.

Keywords: writing ability, process writing, critical thinking skills, self-assessment

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Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: Angela Cristina Da F. De Oliveira, Salma E. Asmar, Norbert P. Battlori, Yaz Vera, Uriel R. Valencia, Tâmara D. Borges, Antoni D. Bueno, Leandro B. Costa

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The present study aimed to evaluate the replacement of 5% of starch per 5% of sunflower oil (SO) on meat quality and animal welfare of growing and finishing pigs (Iberic x Duroc), exposed to a heat stress environment. The experiment lasted 90 days, and it was carried out in a randomized block design, in a 2 x 2 factorial, composed of two diets (starch or sunflower oil (with or without) and two feed intake management (ad libitum and restriction). Seventy-two crossbred males (51± 6,29 kg body weight - BW) were housed in climate-controlled rooms, in collective pens and exposed to heat stress environment (32°C; 35% to 50% humidity). The treatments studies were: 1) control diet (5% starch x 0% SO) with ad libitum intake (n = 18); 2) SO diet (replacement of 5% of starch per 5% of SO) with ad libitum intake (n = 18); 3) control diet with restriction feed intake (n = 18); or 4) SO diet with restriction feed intake (n = 18). Feed were provided in two phases, 50-100 Kg BW for growing and 100-140 Kg BW for finishing, respectively. Within welfare evaluations, dirtiness score was evaluated all morning during ninety days of the experiment. The presence of manure was individually measured based on one side of the pig´s body and scored according to: 0 (less than 20% of the body surface); 1 (more than 20% but less than 50% of the body surface); 2 (over 50% of the body surface). After the experimental period, when animals reach 130-140 kg BW, they were slaughtered using carbon dioxide (CO2) stunning. Carcass weight, leanness and fat content, measured at the last rib, were recorded within 20 min post-mortem (PM). At 24h PM, pH, electrical conductivity and color measures (L, a*, b*) were recorded in the Longissimus thoracis and Semimembranosus muscles. Data shown no interaction between diet (control x SO) and management feed intake (ad libitum x restriction) on the meat quality parameters. Animals in ad libitum management presented an increase (p < 0.05) on BW, carcass weight (CW), back fat thickness (BT), and intramuscular fat content (IM) when compared with animals in restriction management. In contrast, animals in restriction management showing a higher (p < 0.05) carcass yield, percentage of lean and loin thickness. To welfare evaluations, the interaction between diet and management feed intake did not influence the degree of dirtiness. Although, the animals that received SO diet, independently of the management, were cleaner than animals in control group (p < 0,05), which, for pigs, demonstrate an important strategy to reduce body temperature. Based in our results, the diet and management feed intake had a significant influence on meat quality and animal welfare being considered efficient nutritional strategies to reduce heat stress and improved meat quality.

Keywords: dirtiness, environment, meat, pig

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Authors: Julia Wimmers Klick

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Interprofessional Education (IPE) is widely recognized as a valuable approach in healthcare education, despite the challenges it presents. This study explores IP surface anatomy lab sessions, with a focus on fostering trust and collaboration among healthcare students. The research is conducted within the context of rural healthcare settings in British Columbia (BC), where a medical school and a physical therapy (PT) program operate under the Faculty of Medicine at the University of British Columbia (UBC). While IPE sessions addressing soft skills have been implemented, the integration of hard skills, such as Anatomy, remains limited. To address this gap, a pilot feasibility study was conducted with a positive outcome, a follow-up study involved these IPE sessions aimed at exploring the influence of bonding and trust between medical and PT students. Data were collected through focus groups comprising participating students and faculty members, and a structured SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis was conducted. The IPE sessions, 3 in total, consisted of a 2.5-hour lab on surface anatomy, where PT students took on the teaching role, and medical students were newly exposed to surface anatomy. The focus of the study was on the relationship-building process and trust development between the two student groups, rather than assessing the acquisition of surface anatomy skills. Results indicated that the surface anatomy lab served as a suitable tool for the application and learning of soft skills. Faculty members observed positive outcomes, including productive interaction between students, reversed hierarchy with PT students teaching medical students, practicing active listening skills, and using a mutual language of anatomy. Notably, there was no grade assessment or external pressure to perform. The students also reported an overall positive experience; however, the specific impact on the development of soft skill competencies could not be definitively determined. Participants expressed a sense of feeling respected, welcomed, and included, all of which contributed to feeling safe. Within the small group environment, students experienced becoming a part of a community of healthcare providers that bonded over a shared interest in health professions education. They enjoyed sharing diverse experiences related to learning across their varied contexts, without fear of judgment and reprisal that were often intimidating in single professional contexts. During a joint Christmas party for both cohorts, faculty members observed students mingling, laughing, and forming bonds. This emphasized the importance of early bonding and trust development among healthcare colleagues, particularly in rural settings. In conclusion, the findings emphasize the potential of IPE sessions to enhance trust and collaboration among healthcare students, with implications for their future professional lives in rural settings. Early bonding and trust development are crucial in rural settings, where healthcare professionals often rely on each other. Future research should continue to explore the impact of content-concentrated IPE on the development of soft skill competencies.

Keywords: interprofessional education, rural healthcare settings, trust, surface anatomy

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Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

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In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Piotr Wisniewski, Sławomir Dykas

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Condensation has a negative impact on turbomachinery efficiency in many energy processes.In technical applications, it is often impossible to dry the working fluid at the nozzle inlet. One of the most popular working fluid is atmospheric air that always contains water in form of steam, liquid, or ice crystals. Moreover, it always contains some amount of suspended particles which influence the phase change process. It is known that the phenomena of evaporation or condensation are connected with release or absorption of latent heat, what influence the fluid physical properties and might affect the machinery efficiency therefore, the phase transition has to be taken under account. This researchpresents an attempt to evaluate the impact of solid and liquid particles suspended in the air on the expansion of moist air in a low expansion rate, i.e., with expansion rate, P≈1000s⁻¹. The numerical study supported by analytical and experimental research is presented in this work. The experimental study was carried out using an in-house experimental test rig, where nozzle was examined for different inlet air relative humidity values included in the range of 25 to 51%. The nozzle was tested for a supersonic flow as well as for flow with shock waves induced by elevated back pressure. The Schlieren photography technique and measurement of static pressure on the nozzle wall were used for qualitative identification of both condensation and shock waves. A numerical model validated against experimental data available in the literature was used for analysis of occurring flow phenomena. The analysis of the suspended particles number, diameter, and character (solid or liquid) revealed their connection with heterogeneous condensation importance. If the expansion of fluid without suspended particlesis considered, the condensation triggers so called condensation wave that appears downstream the nozzle throat. If the solid particles are considered, with increasing number of them, the condensation triggers upwind the nozzle throat, decreasing the condensation wave strength. Due to the release of latent heat during condensation, the fluid temperature and pressure increase, leading to the shift of normal shock upstream the flow. Owing relatively large diameters of the droplets created during heterogeneous condensation, they evaporate partially on the shock and continues to evaporate downstream the nozzle. If the liquid water particles are considered, due to their larger radius, their do not affect the expanding flow significantly, however might be in major importance while considering the compression phenomena as they will tend to evaporate on the shock wave. This research proves the need of further study of phase change phenomena in supersonic flow especially considering the interaction of droplets with the aerodynamic waves in the flow.

Keywords: aerodynamics, computational fluid dynamics, condensation, moist air, multi-phase flows

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Authors: Dominika Collett

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AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology.

Keywords: copyright, artificial intelligence, legal use, infringement, Czech law, EU law, text and data mining

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Authors: Syhalath Xaphakdy, Toshio Nagata, Saykham Phommathat, Pavy Souwannavong, Vilayvanh Srithilat, Phoxay Sengdala, Bounaom Phetarnousone, Boualay Siharath, Xaya Chemcheng

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The National University of Laos (NUOL) invited a group of volunteers from the Japan International Cooperation Agency (JICA) to revise the physics experiments to utilize the materials that were already available to students. The intension was to review and revise the materials regularly utilized in physics class. The project had access to limited materials and a small budget for the class in the unit; however, by developing experimental textbooks related to mechanics, electricity, and wave and vibration, the group found a way to apply them in the classroom and enhance the students teaching activities. The aim was to introduce a way to incorporate the materials and practices in the classroom to enhance the students learning and teaching skills, particularly when they graduate and begin working as high school teachers.

Keywords: NUOL, JICA, physics experiment materials, small budget, mechanics, electricity

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Authors: Samuel Olugbenga King

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This review article, which is a synthesis of the relevant research literature, focuses on the capabilities of digital video to support, facilitate and enhance faculty development. Based on the literature review, faculty development (i.e., academic or educational development) requires the continued adoption of cohesive, theoretical frameworks to guide research and practice; incorporation of relevant tools from analogous fields, such as teacher professional development; systematic program evaluations; and detailed descriptions of practice to further practice and creative development. A cohesive, five-heuristic framework is subsequently outlined to inform the design and evaluation of the use of digital video, so as to address the barriers to advancing faculty development, as identified through the literature review. Alternative impact evaluation approaches are also described, while the limitations of using digital video for faculty development are highlighted. This paper is therefore conceived as one way to meaningfully leverage the educational affordances of digital video to address some lingering gaps in faculty development.

Keywords: digital video, faculty/educational development, evaluation, scholarship of teaching and learning (SoTL)

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Authors: Angeliki Gkiouzeli, Christine Rotonda, Elise Eby, Claire Touchet, Marie-Jo Brennstuhl, Cyril Tarquinio

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Resilience is a psychological concept of possible relevance to the development and maintenance of chronic pain (CP). It refers to the ability of individuals to maintain reasonably healthy levels of physical and psychological functioning when exposed to an isolated and potentially highly disruptive event. Extensive research in recent years has supported the importance of this concept in the CP literature. Increased levels of resilience were associated with lower levels of perceived pain intensity and better mental health outcomes in adults with persistent pain. The ongoing project seeks to include the concept of pain-specific resilience in the French literature in order to provide more appropriate measures for assessing and understanding the complexities of CP in the near future. To the best of our knowledge, there is currently no validated version of the pain-specific resilience measure, the Pain Resilience scale (PRS), for French-speaking populations. Therefore, the present work aims to address this gap, firstly by performing a linguistic and cultural translation of the scale into French and secondly by studying the internal validity and reliability of the PRS for French CP populations. The forward-translation-back translation methodology was used to achieve as perfect a cultural and linguistic translation as possible according to the recommendations of the COSMIN (Consensus-based Standards for the selection of health Measurement Instruments) group, and an online survey is currently conducted among a representative sample of the French population suffering from CP. To date, the survey has involved one hundred respondents, with a total target of around three hundred participants at its completion. We further seek to study the metric properties of the French version of the PRS, ''L’Echelle de Résilience à la Douleur spécifique pour les Douleurs Chroniques'' (ERD-DC), in French patients suffering from CP, assessing the level of pain resilience in the context of CP. Finally, we will explore the relationship between the level of pain resilience in the context of CP and other variables of interest commonly assessed in pain research and treatment (i.e., general resilience, self-efficacy, pain catastrophising, and quality of life). This study will provide an overview of the methodology used to address our research objectives. We will also present for the first time the main findings and further discuss the validity of the scale in the field of CP research and pain management. We hope that this tool will provide a better understanding of how CP-specific resilience processes can influence the development and maintenance of this disease. This could ultimately result in better treatment strategies specifically tailored to individual needs, thus leading to reduced healthcare costs and improved patient well-being.

Keywords: chronic pain, pain measure, pain resilience, questionnaire adaptation

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Authors: B. Chandra

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In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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Authors: Orisakwe Chimuanya Favour Israel

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In a world filled with the products of scientific inquiry, scientific literacy has become a necessity for everyone because it is indispensable to achieving technological development of any nation. Everyone needs to use scientific information to make choices that arise every day. Everyone needs to be able to engage intelligently in public discourse and debate about important issues that involves science and technology. And everyone deserves to share in the excitement and personal fulfillment that can come from -understanding and learning about the natural world. No doubt that industrialized countries have, through their control of science and technology education, developed the potential to increase production, and to improve the standard of living of their people. The main thrust of this paper therefore, is to present an overview of science education, strategies for achieving application of science in national development, such as teaching science with the right spirit of inquiry. Also, the paper discussed three research models that can help in national development and suggests the best out of the three which is more realistic for a developing country like ours (Nigeria) to follow for a sustainable national development and finally suggests some key ways of solving problems of development.

Keywords: scientific inquiry, scientific literacy, strategies, sustainable national development

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Authors: Tom Elias, Kiran G. Shirlal

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Coastal erosion is one of the major issue faced by maritime countries, globally. More than 1200 km stretch of Indian coastline is marked eroding. There have been numerous attempts to impede the erosion rate and to attain equilibrium beach profiles. High cost and unavailability of natural rocks forced coastal engineers to find alternatives for conventional hard options like seawalls and groynes. Geosynthetic containment systems, emerged in the mid 20th century proved promising in catering coastal protection in countries like Australia, Germany and United States. The present study aims at reviewing Indian timeline of protection works that uses geosynthetic containment systems. Indian exploration regarding geosynthetic containment system dates back to early 2000s. Generally, protection structures use geosynthetics in the form of Geotubes, Geocontainers, and Geobags with Geotubes being most widely used in the form of submerged reefs, seawalls, groynes and breakwaters. Sand and dredged waste are used to fill these containment systems with calculated sand fill ratio. Reviewing the prominent protection works constructed in the east and west coast of India provides an insight into benefits and the difficulties faced by the practical installation. Initially, geosynthetic structures were considered as a temporary protection method prior to the construction of some other hard structure. Later Dahanu, Hamala and Pentha experiences helped in establishing geotubes as an alternative to conventional structures. Nearshore geotubes reefs aimed to attain equilibrium beach served its purpose in Hamala and Dahanu, Maharashtra, while reef constructed at Candolim, Goa underwent serious damage due to Toe Scour. In situ filling by pumping of sand slurry as in case of Shankarpur Seawall, West Bengal remains as a major concern. Geosynthetic systems supplemented by gabions and rock armours improves the wave dissipation, stability and reflection characteristics as implied in Pentha Coast, Odisha, Hazira, Gujarat and Uppada, Andhra Pradesh. Keeping improper design and deliberate destruction by vandals apart, geosynthetic containment systems offer a cost-effective alternative to conventional coastal protection methods in India. Additionally, geosynthetics supports marine growth in its surface which enhances its demand as an eco-friendly material and encourages usage.

Keywords: coastal protection, geotubes, geobags, geocontainers

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Authors: Amanda Abbott-Jones

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Adult students with dyslexia in higher education can receive support for their cognitive needs but may also experience negative emotion such as anxiety due to their dyslexia in connection with their studies. This paper aims to test the hypothesis that adult dyslexic learners have a higher prevalence of academic and social anxiety than their non-dyslexic peers. A quantitative approach was used to measure differences in academic and social anxiety between 102 students with a formal diagnosis of dyslexia compared to 72 students with no history of learning difficulties. Academic and social anxiety was measured in a questionnaire based on the State-Trait Anxiety Inventory. Findings showed that dyslexic students showed statistically significant higher levels of academic, but not social anxiety in comparison to the non-dyslexic sample. Dyslexic students in higher education show academic anxiety levels that are well above what is shown by students without dyslexia. The implications of this for the dyslexia practitioner is that delivery of strategies to deal with anxiety should be seen equally as important, if not more so, than interventions to deal with cognitive difficulties.

Keywords: Academic, Anxiety, Dyslexia, Quantitative

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Authors: Hao Zhang, Hongyang Yu

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Scale uncertainty is a well-known challenging problem in visual SLAM. Because RGB-D sensor provides depth information, RGB-D SLAM improves this scale uncertainty problem. However, due to the limitation of physical hardware, the depth map output by RGB-D sensor usually contains a large area of missing depth values. These missing depth information affect the accuracy and robustness of RGB-D SLAM. In order to reduce these effects, this paper completes the missing area of the depth map output by RGB-D sensor and then fuses the completed dense depth map into ORB SLAM2. By adding the process of obtaining pixel-level dense depth maps, a better RGB-D visual SLAM algorithm is finally obtained. In the process of obtaining dense depth maps, a deep learning model of indoor scenes is adopted. Experiments are conducted on public datasets and real-world environments of indoor scenes. Experimental results show that the proposed SLAM algorithm has better robustness than ORB SLAM2.

Keywords: RGB-D, SLAM, dense depth, depth map

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Authors: Ali Asheibi

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The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

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Authors: Dilek Turan Eroğlu

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Educators have been searching the more effective and appalling methods of teaching for ages. It has always been an issue among the teachers and scientists to improve the quality of education and to ensure that all students have equal opportunities to learn. However, when it comes to the effective ways of learning,the learners are exposed to the ways which are chosen and approved to be effective by their teachers not by the learners themselves. This is the main problem of this study as the learners are not always happy to be in their classes being treated with their teachers’ favourite styles. This paper is telling the results of a study which has been conducted with the university students in Turkey. The students have been interviewed and asked to respond some questions related to best practices to find out their favourite styles, medium, techniques and strategies. The study has been conducted using qualitative research methods i.e one to one interviews and group discussions. The results show that the learners have significantly different views than the educators when it comes to modern teaching styles. Their definition of the term “modern teaching styles” is different than the general understanding. The university students expect their teachers to be “early adopter”. of ICT tools and or the other electronic devices, but a modern teacher must have many other characteristics for them.

Keywords: effective, innovation, teaching, modern teaching styles

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

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Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

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Authors: Ana Maghfiroh

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Learning a foreign language needs a big effort from the learner itself to make their language ability grows better day by day. Among those, they also need a support from all around them including teacher, friends, as well as activities which support them to speak the language. When those activities developed well as a habit which are done regularly, it will help improving the students’ language competence. It was a qualitative research which aimed to find out and describe some activities implemented in Pesantren Al Mawaddah, Ponorogo, in order to teach the students a foreign language. In collecting the data, the researcher used interview, questionnaire, and documentation. From the study, it was found that Pesantren Al Mawaddah had successfully built the language habit on the students to speak the target language. More than 15 hours a day students were compelled to speak foreign language, Arabic or English, in turn. It aimed to habituate the students to keep in touch with the target language. The habit was developed through daily language activities, such as dawn vocabs giving, dictionary handling, daily language use, speech training and language intensive course, daily language input, and night vocabs memorizing. That habit then developed the students awareness towards the language learned as well as promoted their language mastery.

Keywords: habit, communicative competence, daily language activities, Pesantren

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Authors: Shaden S. Attia

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This study investigated foreign language anxiety (FLA) and teachers’ awareness of its presence in the Egyptian ESL classrooms and how FLA correlates with different variables such as four language skills, students' sex, and activities used in class. A combination of quantitative and qualitative instruments was used in order to investigate the previously mentioned variables, which included five interviews with teachers, six classroom observations, a survey for teachers, and a questionnaire for students. The findings of the study revealed that some teachers were aware of the presence of FLA, with some of them believing that other teachers, however, are not aware of this phenomenon, and even when they notice anxiety, they do not always relate it to learning a foreign language. The results also showed that FLA was affected by students’ sex, different language skills, and affective anxieties; however, teachers were unaware of the effect of these variables. The results demonstrated that both teachers and students preferred group and pair work to individual activities as they were more relaxing and less anxiety-provoking. These findings contribute to raising teachers' awareness of FLA in ESL classrooms and how it is affected by different variables.

Keywords: foreign language anxiety, situation specific anxiety, skill-specific anxiety, teachers’ perceptions

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Authors: V. Esteves

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As products of participatory culture, internet memes represent a global form of interaction with online culture. These digital objects draw upon a rich historical engagement with remix practices that dates back decades: from the copy and paste practices of Dadaism and punk to the re-appropriation techniques of the Situationist International; memes echo a long established form of cultural creativity that pivots on the art of the remix. Online culture has eagerly embraced the changes that the Web 2.0 afforded in terms of making use of remixing as an accessible form of societal expression, bridging these remix practices of the past into a more widely available and accessible platform. Memes embody the idea of 'intercreativity', allowing global creative collaboration to take place through networked digital media; they reflect the core values of participation and interaction that are present throughout much internet discourse whilst also existing in a historical remix continuum. Memes hold the power of cultural symbolism manipulated by global audiences through which societies make meaning, as these remixed digital objects have an elasticity and low literacy level that allows for a democratic form of cultural engagement and meaning-making by and for users around the world. However, because memes are so elastic, their ability to be re-appropriated by other powers for reasons beyond their original intention has become evident. Recently, corporations have made use of internet memes for advertising purposes, engaging in the circulation and re-appropriation of internet memes in commercial spaces – which has, in turn, complicated this relation between online users and memes' democratic possibilities further. By engaging in a widespread online ethnography supplemented by in-depth interviews with meme makers, this research was able to not only track different online meme use through commercial contexts, but it also allowed the possibility to engage in qualitative discussions with meme makers and users regarding their perception and experience of these varying commercial uses of memes. These can be broadly put within two categories: internet memes that are turned into physical merchandise and the use of memes in advertising to sell other (non-meme related) products. Whilst there has been considerable acceptance of the former type of commercial meme use, the use of memes in adverts in order to sell unrelated products has been met with resistance. The changes in reception regarding commercial meme use is dependent on ideas of cultural ownership and perceptions of authorship, ultimately uncovering underlying socio-cultural ideologies that come to the fore within these overlapping contexts. Additionally, this adoption of memes by corporate powers echoes the recuperation process that the Situationist International endured, creating a further link with older remix cultures and their lifecycles.

Keywords: commodification, internet culture, memes, recuperation, remix

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Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

Abstract:

This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

Procedia PDF Downloads 374

Authors: Zeynep Turhan

Abstract:

Digital tools can improve knowledge and awareness of strategies and skills for healthy and respectful intimate relationships. The website of the Healthy and Respectful Relationship Program has been developed and included five key videos about how to build healthy intimate relationships. This study examined the perspectives about informative videos by focusing on how individuals learn new information or challenge their preconceptions or attitudes regarding male privilege and women's oppression. Five individuals who received no-contact orders and attended group intervention were the sample of this study. The observation notes were the major methodology examining how participants responded to video tools. The data analysis method was the interpretative phenomenological analysis. The results showed that many participants found the tools useful in learning the types of violence and communication strategies. Nevertheless, obstacles to implementing some techniques were found in their relationships. These digital tools might enhance healthy and respectful relationships despite some limitations.

Keywords: healthy relationship, digital tools, intimate partner violence, perpetrators, video interventions

Procedia PDF Downloads 95

Authors: Aiswarya Gopal, Kamal Bijlani, Vinoth Rengaraj, R. Jayakrishnan

Abstract:

In the business world, the term “startup” is frequently ringing the bell with the high frequency of young ventures. The main dilemma of startups is the unsuccessful management of the unique risks that have to be confronted in the present world of competition and technology. This research work tried to bring out a game based methodology to improve enough real-world experience among entrepreneurs as well as management students to handle risks and challenges in the field. The game will provide experience to the player to overcome challenges like market problems, running out of cash, poor management, and product problems which can be resolved by a proper strategic approach in the entrepreneurship world. The proposed serious game works on the life cycle of a new software enterprise where the entrepreneur moves from the planning stage to secured financial stage, laying down the basic business structure, and initiates the operations ensuring the increment in confidence level of the player.

Keywords: business model, game based learning, poor management, start up

Procedia PDF Downloads 475

Authors: Claudia Norambuena, Myissa Weiss, Maria Ruiz Maya, Matthew Straley, Elijah Hammond, Benjamin Chesebrough, David Grow

Abstract:

The purpose of this project is to develop a low-cost, portable sensor device that can be used at home for long-term analysis of gait and balance abnormalities. One area of particular concern involves the asymmetries in movement and balance that can accompany certain types of injuries and/or the associated devices used in the repair and rehabilitation process (e.g. the use of splints and casts) which can often increase chances of falls and additional injuries. This device has the capacity to monitor a patient during the rehabilitation process after injury or operation, increasing the patient’s access to healthcare while decreasing the number of visits to the patient’s clinician. The sensor device may thereby improve the quality of the patient’s care, particularly in rural areas where access to the clinician could be limited, while simultaneously decreasing the overall cost associated with the patient’s care. The device consists of nine interconnected accelerometer/ gyroscope/compass chips (9-DOF IMU, Adafruit, New York, NY). The sensors attach to and are used to determine the orientation and acceleration of the patient’s lower abdomen, C7 vertebra (lower neck), L1 vertebra (middle back), anterior side of each thigh and tibia, and dorsal side of each foot. In addition, pressure sensors are embedded in shoe inserts with one sensor (ESS301, Tekscan, Boston, MA) beneath the heel and three sensors (Interlink 402, Interlink Electronics, Westlake Village, CA) beneath the metatarsal bones of each foot. These sensors measure the distribution of the weight applied to each foot as well as stride duration. A small microntroller (Arduino Mega, Arduino, Ivrea, Italy) is used to collect data from these sensors in a CSV file. MATLAB is then used to analyze the data and output the hip, knee, ankle, and trunk angles projected on the sagittal plane. An open-source program Processing is then used to generate an animation of the patient’s gait. The accuracy of the sensors was validated through comparison to goniometric measurements (±2° error). The sensor device was also shown to have sufficient sensitivity to observe various gait abnormalities. Several patients used the sensor device, and the data collected from each represented the patient’s movements. Further, the sensors were found to have the ability to observe gait abnormalities caused by the addition of a small amount of weight (4.5 - 9.1 kg) to one side of the patient. The user-friendly interface and portability of the sensor device will help to construct a bridge between patients and their clinicians with fewer necessary inpatient visits.

Keywords: biomedical sensing, gait analysis, outpatient, rehabilitation

Procedia PDF Downloads 289

Authors: Yuqing Sun

Abstract:

Nowadays, English has been taught in many countries as a second language. One of the major ways to learn this language is through the class teaching. As in the field of second language acquisition, there are many factors to affect its acquisition processes, such as the target language itself, a learner’s personality, cognitive factor, language transfer, and the outward factors (teaching method, classroom, environmental factor, teaching policy, social environment and so on). Flipped Classroom as a newly developed classroom model has been widely used in language teaching classroom, which was, to some extent, accepted by teachers and students for its effect. It distinguishes itself from the traditional classroom for its focus on the learner and its great importance attaching to the personal learning process and the application of technology. The class becomes discussion-targeted, and the class order is somewhat inverted since the teaching process is carried out outside the class, while the class is only for knowledge-internalization. This paper will concentrate on the influences of the flipped classroom, as a classroom affecting factor, on the the process of English acquisition by the way of case studies (English teaching class in China), and the analysis of the mechanism of the flipped classroom itself to propose some feasible advice of promoting the the effectiveness of English acquisition.

Keywords: second language acquisition, English, flipped classroom, case

Procedia PDF Downloads 400

Authors: Georges Bou Ghantous

Abstract:

This research delves into the transformative impact of Artificial Intelligence (AI) on Infrastructure as Code (IaaC) practices, specifically focusing on the redefinition of infrastructure orchestration. By harnessing AI technologies such as machine learning algorithms and predictive analytics, organizations can achieve unprecedented levels of efficiency and optimization in managing their infrastructure resources. AI-driven IaaC introduces proactive decision-making through predictive insights, enabling organizations to anticipate and address potential issues before they arise. Dynamic resource scaling, facilitated by AI, ensures that infrastructure resources can seamlessly adapt to fluctuating workloads and changing business requirements. Through case studies and best practices, this paper sheds light on the tangible benefits and challenges associated with AI-driven IaaC transformation, providing valuable insights for organizations navigating the evolving landscape of digital infrastructure management.

Keywords: artificial intelligence, infrastructure as code, efficiency optimization, predictive insights, dynamic resource scaling, proactive decision-making

Procedia PDF Downloads 34

Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

Abstract:

Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

Procedia PDF Downloads 696

Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

Abstract:

For security purposes, it is important to detect passwords entered by unauthorized users. With traditional alphanumeric passwords, if the content of a password is acquired and correctly entered by an intruder, it is impossible to differentiate the password entered by the intruder from those entered by the authorized user because the password entries contain precisely the same character set. However, no two entries for the gesture-based passwords, even those entered by the person who created the password, will be identical. There are always variations between entries, such as the shape and length of each stroke, the location of each stroke, and the speed of drawing. It is possible that passwords entered by the unauthorized user contain higher levels of variations when compared with those entered by the authorized user (the creator). The difference in the levels of variations may provide cues to detect unauthorized entries. To test this hypothesis, we designed an empirical study, collected and analyzed the data with the help of machine-learning algorithms. The results of the study are significant.

Keywords: authentication, gesture-based passwords, shoulder-surfing attacks, usability

Procedia PDF Downloads 139