Search results for: teaching and learning effectiveness

Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Amani Abdallah, Isam Shahrour

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The quality of drinking water is a major concern of public health. The control of this quality is generally performed in the laboratory, which requires a long time. This type of control is not adapted for accidental pollution from sudden events, which can have serious consequences on population health. Therefore, it is of major interest to develop real-time innovative solutions for the detection of accidental contamination in drinking water systems This paper presents researches conducted within the SunRise Demonstrator for ‘Smart and Sustainable Cities’ with a particular focus on the supervision of the water quality. This work aims at (i) implementing a smart water system in a large water network (Campus of the University Lille1) including innovative equipment for real-time detection of abnormal events, such as those related to the contamination of drinking water and (ii) develop a numerical modeling of the contamination diffusion in the water distribution system. The first step included verification of the water quality sensors and their effectiveness on a network prototype of 50m length. This part included the evaluation of the efficiency of these sensors in the detection both bacterial and chemical contamination events in drinking water distribution systems. An on-line optical sensor integral with a laboratory-scale distribution system (LDS) was shown to respond rapidly to changes in refractive index induced by injected loads of chemical (cadmium, mercury) and biological contaminations (Escherichia coli). All injected substances were detected by the sensor; the magnitude of the response depends on the type of contaminant introduced and it is proportional to the injected substance concentration.

Keywords: distribution system, drinking water, refraction index, sensor, real-time

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Authors: Nikoletta G. Karytsioti

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The European Union’s function and effectiveness are still an issue that minds, bringing about division even in the member-states interior. Recently, more serious issues have been added in the Union’s malfunction, which affects not only the Union’s function but also their residents’ safety. One of these issues is the migration crisis, which frustrates the European Union’s balances and the stability. The present paper’s aim to frame and interpret the Greek public opinion in basic migration matters, throughout the political philosophy and specifically via John Rawls ‘Theory of Justice’. The theory is deployed to examine if it may be used in a practical way, on a tangible issue and in a specific area. In order to obtain a real frame of the public opinion about the matter of migration, a questionnaire was addressed to Greek people. The sample was chosen for three main reasons: a) Greeks are experienced in the migration as they had migrated in the past, b) many young people migrated the recent years after the debt crisis, c) Greece is a reception state. Being based in the Theory of Justice and specifically in the ‘veil of ignorance’, is tried to overcome the obstacles of human nature’s subjectivity, while examining the variations in the responses per social group. The questionnaire will have demographic questions and special interest questions, related with the crisis, before and after ‘the veil of ignorance’. The paper’s originality comes from the fact that it is the first time that a philosophical theory is used to examine the migration issue in a practical manner. The main goals of the paper are three: - To examine the differences/similarities in the responses before and after the veil of ignorance, - to reveal opinions on migration crisis from E.U. citizens and - to confirm or not the practical usefulness of the Political Philosophy as a highlighting tool

Keywords: European Union, immigrants, migration crisis, political philosophy, theory of justice, veil of ignorance

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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: Hafiz Arbab Sakandar

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Time-restricted intermittent fasting (TRIF) impacts host’s physiology and health. Plenty of health benefits have been reported for TRIF in animal models. However, limited studies have been conducted on humans especially in underdeveloped economies. Here, we designed a study to investigate the impact of TRIF/Ramadan fasting (16:8) on the modulation of gut-microbiome structure, metabolic pathways, and predicted metabolites and explored the correlation among them at different time points (during and after the month of Ramadan) in Pakistani Expats living in China. We observed different trends of Shannon-Wiener index in different subjects; however, all subjects showed substantial change in bacterial diversity with the progression of TRIF. Moreover, the changes in gut microbial structure by the end of TRIF were higher vis-a-vis in the beginning, significant difference was observed among individuals. Additionally, metabolic pathways analysis revealed that amino acid, carbohydrate and energy metabolism, glycan biosynthesis metabolism of cofactors and vitamins were significantly affected by TRIF. Pyridoxamine, glutamate, citrulline, arachidonic acid, and short chain fatty acid showed substantial difference at different time points based on the predicted metabolism. In conclusion, these results contribute to further our understanding about the key relationship among, dietary intervention (TRIF), gut microbiome structure and function. The preliminary results from study demonstrate significant potential for elucidating the mechanisms underlying gut microbiome stability and enhancing the effectiveness of microbiome-tailored interventions among the Pakistani populace. Nonetheless, extensive, and rigorous large-scale research on the Pakistani population is necessary to expound on the association between diet, gut microbiome, and overall health.

Keywords: gut microbiome, health, fasting, functionality

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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: Kalsoom Rani

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Tobacco contains nicotine, which causes addiction to many toxic chemicals. In the world, people consume it in the form of smoke, chew, and sniffing, smoke of it is composed of almost 7000 active chemicals, which are very harmful to human health as well as for eye health, inhalation of tobacco smoke and fumes can accelerate and cause many blinding eye diseases. Dry eye and smoking have not been covered extensively in researches; more studies are required to unveil the relationship between smoking and dry eye. This study was conducted to determine the quantity and quality of tears in smokers. 60 subjects participated in the study, which was divided into two groups on the basis of consumption of cigarettes per day with age matched non smokers of 15-50 years. All participants have gone through a study based questioner, eye examination, and diagnostic 'Dry Eye Tests' for evaporative tears evaluation and measurement of basal tear secretion. Subjects were included in the criteria of 10 cigarettes per day with a minimum duration of 1 year; passive smokers for control groups were excluded. The study was carried out in a Medina Teaching Hospital, Faisalabad, Pakistan, ophthalmology department for the duration of 8 months. Mean values for tear break up time (TBUT), was reported 10sec with SD of +3.74 in controlled group, 5sec with SD + 2.32 in smokers and 4sec SD +3.77 heavy smokers in right eye (RE) and left eye (LE) 10.35sec with SD of +3.88 in controlled 5sec with SD + 2.3 in smokers and much reduced TBUT in heavy smokers was 3.85sec SD+2.20. Smoking has a very strong association with TRUT with a significance of P=.00 both eyes. Mean Schirmer-I value of the subjects was reported 12.6mm with SD + 8.37 in RE and 12.59mm with SD + 8.96 LE. The mean Schirmer-II test value was reported in the right, and left eye with a mean value for control was 20.23mm with SD + 8.93, 20.75mm with SD + 8.84 respectively, and in Smokers 9.90mm with SD + 5.74, and 10.07mm with SD + 6.98, and in heavy smokers 7.7mm, SD + 3.22 and 6.9, SD + 3.50 mm, association with smoking showed p=.001 in RE and .003 in LE. Smoking has deteriorated effect on both evaporative tear and aqueous tear secretion and causing symptoms of dry eye burning, itching, redness, and watering with epithelial cell damage.

Keywords: tear break-up time, basal tear secretion, smokers, dry eye

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Authors: Gulnaz Erkomaishvili

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Introduction: The pandemic and the current economic crisis have created problems for entrepreneurship and, therefore for start-up entrepreneurs. The paper presents the challenges of start-up entrepreneurs in Georgia in the time of pandemic and the analysis of the state economic policy measures. Despite many problems, the study found that in 54.2% of start-ups surveyed under the pandemic, innovation opportunities were growing. It can be stated that the pandemic was a good opportunity to increase the innovative capacity of the enterprise. 52% of the surveyed start-up entrepreneurs managed to adapt to the current situation and increase the sale of their products/services through remote channels. As for the assessment of state support measures by start-up entrepreneurs, a large number of Georgian start-ups do not assess the measures implemented by the state positively. Methodology: The research process uses methods of analysis and synthesis, quantitative and qualitative, interview/survey, grouping, relative and average values, graphing, comparison, data analysis, and others. Main Findings: Studies have shown that for the start-up entrepreneurs, the main problem remains: inaccessible funding, workers' qualifications gap, inflation, taxes, regulation, political instability, inadequate provision of infrastructure, amount of taxes, and other factors. Conclusions: The state should take the following measures to support business start-ups: create an attractive environment for investment, availability of soft loans, creation of an insurance system, infrastructure development, increase the effectiveness of tax policy (simplicity of the tax system, clarity, optimal tax level ); promote export growth (develop strategy for opening up international markets, build up a broad marketing network, etc.).

Keywords: start-up entrepreneurs, startups, start-up entrepreneurs support programs, start-up entrepreneurs support economic policy

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Authors: Paul Saah, Charles Mbohwa, Nelson Sizwe Madonsela

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The capacity to deliver projects on schedule, within budget, and to the pleasure of the client depends on effective communication, which is the lifeblood of project-based businesses. In order to pinpoint areas for development and shed light on the crucial role that communication plays in project success, the aim of this study is to evaluate the efficacy of communication practises and processes inside project-based organisations. In order to analyse concepts and get a greater grasp of their theoretical basis, this study's methodology combines a careful review of the relevant literature with a conceptual analysis of the subject. Data from a varied sample of project-based businesses spanning all industries and sizes were collected via document analysis. The relationship between communication practises, and processes were investigated in connection to key performance measures such as project outcomes, client satisfaction, and team dynamics. According to the study's findings, project-based businesses that adopt effective communication practises, and procedures experience a reduction in unfavourable experiences, stronger integration, and coordination, clarity of purpose, and practises that can hasten problem resolution. However, failing to adopt effective communication practises and procedures in project-based company result in counter issues, including project derailment from the schedule, failure to meet goals, inefficient use of existing resources, and failure to meet organisational goals. Therefore, optimising their communication practises, and procedures are crucial for sustainable growth and competitive advantage as project-based enterprises continue to play a crucial part in today's dynamic business scene.

Keywords: effective communication, project-based firms, communication practices, project success, communication strategies

Procedia PDF Downloads 53

Authors: S. Hussain, N. Ahmad, S. Alam, M. Bezabhi, W. H. Hendriks, P. Yu, J. W. Cone

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The high content of lignin in cell walls is the major limiting factor in the digestion and utilisation of cereal crop residues by ruminants. The aim of this study was to evaluate the effectiveness of the white rot fungus, Pleurotus ostreatus (P. ostreatus), to degrade lignin and to enhance the rumen degradability of maize stover, rice straw, wheat straw and their mixture in equal proportion on a dry-matter (DM) basis. Four samples of each substrate were incubated aerobically in triplicate with P. ostreatus for 0 (Control), 21, 28 and 35 days under solid-state conditions (temperature, 24 ͦ C; humidity, 70± 5%). The changes in chemical composition, DM and nutrient losses, and rumen fermentation characteristics using in vitro DM digestibility (DMD) and the in vitro gas production (GP) technique were measured. The results showed that incubation with P. ostreatus decreased (P < 0.001) the contents of neutral detergent fibre and lignin with a concomitant increase (P < 0.001) in the contents of ash and crude protein. The losses of nutrients differed (P < 0.001) among the straw types, with rice straw and maize stover showing the largest (P < 0.05) lignin degradation compared to wheat and mixed straws. The DMD and 72-h cumulative GP increased (P < 0.001) consistently with increasing fungal incubation period and for all substrates the highest values of DMD and GP were measured after 35 days of incubation with P. ostreatus. The lignin degradation was strongly associated with hemicellulose degradation (r = 0.71) across the various straws. Results of the present study demonstrated that incubation of low-quality crop residues with P. ostreatus under solid-state conditions upgrades their feeding value by reducing the content of lignin and increasing the content of crude protein and ruminal degradation.

Keywords: crop residues, lignin degradation, maize stovers, wheat straws, white rot fungi

Procedia PDF Downloads 51

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: 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: Philippa Hunter

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How might history education support teachers and students to see the past as a provocation, be open to possible futures, and act differently? As teacher educators in an age of diversity and uncertainty, we need to question history’s curriculum nature, pedagogy, and policy intent. The cultural politics of history’s identity in the senior secondary curriculum influences educational socialization (disciplinary, professional, research) and engagement with curriculum decision-making. This paper reflects on curriculum disturbance that shaped a critical pedagogy stance to problematize school history’s certainties. The context is situated in an Aotearoa New Zealand university-based initial teacher education programme. A pedagogic innovation was activated whereby problematized history pedagogy [PHP] was conceptualized as the phenomenon and method of inquiry and storied in doctoral work. The PHP was a reciprocal research process involving history class’ participants and the teacher as researcher, in fashioning teaching identities, identifying with, and thinking critically about history pedagogy. PHP findings revealed evocative discourses of embodiment, nostalgia, and connectedness about living ‘inside the past’. Participants expressed certainty about their abilities as teachers living ‘outside the past’ to interpret historical perspectives. However, discomfort was evident in relation to ‘difficult knowledge’ or unfamiliar contexts of the past that exposed exclusion, powerlessness, or silenced voices. Participants identified history programmes as strongly masculine and conflict-focused. A normalized inquiry-transmission approach to history pedagogy was identified and critiqued. Individuals’ reflexive accounts of PHP implemented whilst on practicum indicate possibilities of history pedagogy as; inclusive and democratic, social and ethical reconstruction, and as a critical project. The PHP sought to reimagine history curriculum and identify spaces of possibility in secondary postgraduate teacher education.

Keywords: curriculum, pedagogy, problematise, reciprocal

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Authors: Adina Dudau, Georgios Kominis, Melinda Szocs

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This paper links distinct bodies of literature around innovation and public services by examining a case of perceived innovation failure. Through a mixed methodology investigating student attitudes to, and behaviour around, technological innovation in higher education, the paper makes a contribution to the public service innovation literature by focusing on the duality of innovation outcomes, suggestive of an innovation typology in public services. The study was conducted in a UK Russell Group university and it focused on a technological process innovation. The innovation consisted of the provision of feedback to students in the form of a digital video (mp4), tailored to each individual submission, with extended voice-over commentary from the course coordinator and visual cues intended to help students see the relevance of comments to their submissions. The sample of the study consisted of a class of 79 undergraduate students. To investigate student attainment, we designed a field (also known as quasi or natural) experiment, essentially a manipulation of a social setting (in this case, the form of feedback given to students), but as part of a naturally occurring social arrangement (a real course which students attend and in which they are assessed). A two group control group design (see figure 3) was utilised to examine the effectiveness of the feedback innovation (video feedback). Two outcome variables of the service innovation were measured: student satisfaction and student attainment. In other words, the study examined not only students’ perceptions of whether VF was deemed to be beneficial towards their subsequent assignments; but also evidence of actual incremental benefits in students’ performance from one assignment to the next after VF was provided. The results were baffling and indicating competing agendas in higher education.

Keywords: higher education, audio-video, feedback, innovation

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Authors: Jaber Shurrab, Matloub Hussain

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The rapid pace of changes in the construction industry, technological advancements, and rising costs present tremendous challenges for project managers. Project managers are under severe pressure to minimize the waste, improve the efficiency of the entire operations and the philosophy of ‘lean thinking’ so that ‘more could be achieved with less’ is becoming very popular. Though, lean management has strong roots in manufacturing industry and over the last decade lean philosophy has started gaining attention in the service industry as well. However, little has been known in the context of waste minimization and lean implementation in the construction industry and this paper deals with this important issue. The primary objective of this paper is to propose a conceptual framework for the exploration of appropriate lean techniques applicable to medium and large construction companies and measure their impact on the competitiveness and economic performance of construction companies of United Arab Emirates (UAE). To this end, a comprehensive literature review and interviews with eight project managers of medium and large construction companies of UAE have been conducted. It has been found that competitive, reduce waste and costs are critical to the construction industry. This is an ongoing research in lean management, giving project managers a practical framework for improving the efficiency of their project through various lean techniques. Originality/value: Research significance emphasizes increasing the effectiveness of the construction industry, influences the development of lean construction framework which improves lean construction practices using the lean techniques. This contributes to the effort of applying lean techniques in the construction industry. Limited publications were done in the construction industry mainly in United Arab Emirates (UAE) compared to the lean manufacturing. This research will recommend a systematic approach for the implementing of the anticipated framework within a cyclical look-ahead period and emphasizes the practical implications of the proposed approach.

Keywords: construction, lean, lean manufacturing, waste

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Authors: Yun-Tsuen Chen, Shih-Ting Huang, Pi-Fen Cheng, Heng-Hua Wang, Hui-Zhu Chen

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This paper discusses the experience of caring for a patient diagnosed with breast cancer and later received total mastectomy during a 2nd trimester pregnancy. She was hospitalized from January 31 to February 4, 2018. Using 'Gordon’s 11 Functional Health Patterns' through physical exams and interviews, the researcher assessed the patient’s physical and mental health and determined the patient to have anxiety, acute pain, and body image disturbance. After establishing a strong relationship with the patient, the researcher helped the patient express her anxiety and personal feelings. A multi-specialist team was formed to evaluate both the patient and her unborn child, before, during, and after surgery. This individualized care allowed the patient and her child to optimize the post-operative results. Aside from medication, the patient also received non-medicinal treatment, including improvement of sleep quality with body positioning, diaphragmatic breathing exercises for pain and stress relief after surgery. Throughout hospitalization, the patient’s physical and emotional needs were addressed daily with listening sessions and empathy. The patient’s husband was also incorporated in the patient’s recovery by teaching both he and the patient how to change the sterile wound dressing, which may have the added benefit of improving marital relationships through shared activities of nurturing. The patient was also given advice about how to improve self-confidence through clothing. Lastly, the patient was encouraged to join a support group for breast cancer patients. Through the sharing of experience in groups and within the family, the patient was helped to adapt to the change of her appearance and re-establish her self-confidence. This level of care expedited the patient’s return to her family life and role of being a mother.

Keywords: anxiety, body image disturbance, breast cancer during pregnancy, multi-specialist team

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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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: Akinbuluma Ayodeji Theophilus, Adewale Olutaiwo

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When building roads and paved surfaces, a strong foundation is always essential. A durable material that can withstand years of traffic while staying trustworthy must be used to build the foundation. A frequent problem in the construction of roads and pavements is the lack of high-quality, long-lasting materials for the pavement structure (base, subbase, and subgrade). Hence, this study examined the stabilization of lateritic soil samples from Ijoko with cement kiln dust and lime. The study adopted the experimental design. Laboratory tests were conducted on classification, swelling potential, compaction, California bearing ratio (CBR), and unconfined compressive tests, among others, were conducted on the laterite sample treated with cement kiln dust (CKD) and lime in incremental order of 2% up to 10% of dry weight soft soil sample. The results of the test showed that the studied soil could be classified as an A-7-6 and CL soil using the American Association of State Highway and transport officials (AASHTO) and the unified soil classification system (USCS), respectively. The plasticity (PI) of the studied soil reduced from 30.5% to 29.9% at the application of CKD. The maximum dry density on the application of CKD reduced from 1.9.7 mg/m3 to 1.86mg/m3, and lime application yielded a reduction from 1.97mg/m3 to 1.88.mg/m3. The swell potential on CKD application was reduced from 0.05 to 0.039%. The study concluded that soil stabilizations are effective and economic way of improving road pavement for engineering benefit. The degree of effectiveness of stabilization in pavement construction was found to depend on the type of soil to be stabilized. The study therefore recommended that stabilized soil mixtures should be used to subbase material for flexible pavement since is a suitable.

Keywords: lateritic soils, sand, cement, stabilization, road pavement

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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: Mohammed Saleh Rezk, Reza Kashani

Abstract:

Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

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Authors: Ali Asheibi

Abstract:

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: G. Baranski, A. Majczak, M. Wendeker

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Currently, the most commonly used solution to provide fuel to the diesel engines is the Common Rail system. Compared to previous designs, as a due to relatively simple construction and electronic control systems, these systems allow achieving favourable engine operation parameters with particular emphasis on low emission of toxic compounds into the atmosphere. In this system, the amount of injected fuel dose is strictly dependent on the course of parameters of the electrical impulse sent by the power amplifier power supply system injector from the engine controller. The article presents the construction of a laboratory test bench to examine the course of the injection process and the expense in storage injection systems. The test bench enables testing of injection systems with electromagnetically controlled injectors with the use of scientific engineering tools. The developed system is based on LabView software and CompactRIO family controller using FPGA systems and a real time microcontroller. The results of experimental research on electromagnetic injectors of common rail system, controlled by a dedicated National Instruments card, confirm the effectiveness of the presented approach. The results of the research described in the article present the influence of basic parameters of the electric impulse opening the electromagnetic injector on the value of the injected fuel dose. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A.’ and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: fuel injector, combustion engine, fuel pressure, compression ignition engine, power supply system, controller, LabVIEW

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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

Procedia PDF Downloads 133

Authors: Tirtha Raj Dhakal, Brian Davidson, Bob Farquharson

Abstract:

Irrigation management transfer has been taken as the important policy instrument for effective irrigation resource management in many developing countries. The change in governance of the irrigation schemes for its day-to-day operation and maintenance has been centered in recent Nepalese irrigation policies also. However, both farmer- and agency-managed irrigation schemes in Nepal are performing well below than expected. This study tries to link the present concerns of poor performance of both forms of schemes with the institutions for its operation and management. Two types of surveys, management and farm surveys; were conducted as a case study in the command area of Narayani Lift Irrigation Project (agency-managed) and Khageri Irrigation System (farmer-managed) of Chitwan District. The farm survey from head, middle and tail regions of both schemes revealed that unequal water distribution exists in these regions in both schemes with greater percentage of farmers experiencing this situation in agency managed scheme. In both schemes, the cost recovery rate was very low, even below five percent in Lift System indicating poor operation and maintenance of the schemes. Also, the institution on practice in both schemes is unable to create any incentives for farmers’ willingness to pay as well as for its economical use in the farm. Thus, outcomes from the study showed that only the management transfer programs may not achieve the goal of efficient irrigation resource management. This may suggest water professionals to rethink about the irrigation policies for refining institutional framework irrespective of the governance of schemes for improved cost recovery and better water distribution throughout the irrigation schemes.

Keywords: cost recovery, governance, institution, irrigation management transfer, willingness to pay

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Authors: Ana Maghfiroh

Abstract:

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: Clare Victoria Martin

Abstract:

With reports of increased mental health problems and a lack of proactive, consistent well-being initiatives, well-being is a topical issue in the workplace, as well as a wider public health concern. Additionally, workplace well-being is closely linked to performance, both from a business perspective and in psychological research. Businesses are therefore becoming increasingly motivated to promote well-being, yet there are still barriers, including a lack of evidence-based workplace interventions, issues with measuring effectiveness and problems creating lasting cultural change. This review aimed to collate workplace well-being research to propose a comprehensive new model for delivering evidence-based workplace well-being training with a real potential for lasting impact. Method: A narrative review was conducted to meta-synthesise relevant research. Thematic analysis was then adopted as a systematic method of identifying key themes from the review to lead to practical recommendations. Interventions focusing on strengths, psychological capital, mindfulness and positivity (SPMP) dominated the research in this area, suggesting benefits of incorporating all four into training. However, to avoid a ‘quick fix’ mentality, the concept of training ‘well-being ambassadors’ as a preventative counterpart to mental health ‘first aiders’ was proposed alongside a new ‘REST and RISE’ model: well-being interventions should be ‘relatable’, ‘enjoyable’, ‘sociable’ and ‘trackable’ (REST) in order to increase ‘resilience’, ‘innovation’, ‘strengths’ and ‘engagement’ (RISE). If the REST principles are applied to interventions focusing on SPMP, research suggests individuals will RISE. Future research should empirically test this new well-being ambassador programme and REST/RISE model in an applied setting.

Keywords: performance, positive psychology, thriving, workplace well-being

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Authors: Dwi Endarti, Susi a Kristina, Rizki Noorizzati, Akbar E Nugraha, Fera Maharani, Kika a Putri, Asninda H Azizah, Sausanzahra Angganisaputri, Yunisa Yustikarini

Abstract:

Cost utility analysis is the most recommended pharmacoeconomic method since it allows widely comparison of cost-effectiveness results from different interventions. The method uses outcome of quality-adjusted life year (QALY) or disability-adjusted life year (DALY). Measurement of QALY requires the data of utility dan life years gained. Utility is measured with the instrument for quality of life measurement such as EQ-5D. Recently, the EQ-5D is available in two versions which are EQ-5D-3L and EQ-5D-5L. This study aimed to compare the EQ-5D-3L and EQ-5D-5L to examine the most suitable version for Indonesian population. This study was an observational study employing cross sectional approach. Data of quality of life measured with EQ-5D-3L and EQ-5D-5L were collected from several groups of population which were respondent with chronic diseases, respondent with acute diseases, and respondent from general population (without illness) in Yogyakarta Municipality, Indonesia. Convenience samples of hypertension patients (83), diabetes mellitus patients (80), and osteoarthritis patients (47), acute respiratory tract infection (81), cephalgia (43), dyspepsia (42), and respondent from general population (293) were recruited in this study. Responses on the 3L and 5L versions of EQ-5D were compared by examining the psychometric properties including agreement, internal consistency, ceiling effect, and convergent validity. Based on psychometric properties tests of EQ-5D-3L dan EQ-5D-5L, EQ-5D-5L tended to have better psychometric properties compared to EQ-5D-3L. Future studies for health related quality of life (HRQOL) measurements for pharmacoeconomic studies in Indonesia should apply EQ-5D-5L.

Keywords: EQ-5D, Health Related Quality of Life, Indonesian Population, Psychometric Properties

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