Search results for: online learning/teaching

Authors: Penn P. Wu, Jeannie Jo

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Blockchain technology has rapidly gained popularity in industry. This paper attempts to assist academia to answer four questions. First, should community colleges begin offering education to nurture blockchain-literate students for the job market? Second, what are the appropriate topical areas to cover? Third, should it be an individual course? And forth, should it be a technical or management course? This paper starts with identifying the knowledge domains of blockchain technology and the topical areas each domain has, and continues with placing them in appropriate academic territories (Computer Sciences vs. Business) and subjects (programming, management, marketing, and laws), and then develops an evaluation model to determine the appropriate topical area for community colleges to teach. The evaluation is based on seven factors: maturity of technology, impacts on management, real-world applications, subject classification, knowledge prerequisites, textbook readiness, and recommended pedagogies. The evaluation results point to an interesting direction that offering an introductory course is an ideal option to guide students through the learning journey of what blockchain is and how it applies to business. Such an introductory course does not need to engage students in the discussions of mathematics and sciences that make blockchain technologies possible. While it is inevitable to brief technical topics to help students build a solid knowledge foundation of blockchain technologies, community colleges should avoid offering students a course centered on the discussion of developing blockchain applications.

Keywords: blockchain, pedagogies, blockchain technologies, blockchain course, blockchain pedagogies

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Bin Liu

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MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Daniel Gredig, Annabelle Bartelsen-Raemy

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Social work professionals should underpin their decisions with scientific knowledge and research findings. Hence, research is used as a framework for social work education and research courses have become a taken-for-granted component of study programmes. However, it has been acknowledged that social work students have negative beliefs and attitudes as well as frequently feelings of fear of research courses. Against this background, the present study aimed to establish the relationship between student’s fear of research courses, their research orientation and interest in research courses. We hypothesized that fear predicts the interest in research courses. Further, we hypothesized that research orientation (perceived importance and attributed usefulness for research for social work practice and perceived unbiased nature of research) was a mediating variable. In the years 2014, 2015 and 2016, we invited students enrolled for a bachelor programme in social work in Switzerland to participate in the study during their introduction day to the school taking place two weeks before their programme started. For data collection, we used an anonymous self-administered on-line questionnaire filled in on site. Data were analysed using descriptive statistics and structural equation modelling (generalized least squares estimates method). The sample included 708 students enrolled in a social work bachelor-programme, 501 being female, 184 male, and 5 intersexual, aged 19–56, having various entitlements to study, and registered for three different types of programme modes (full time programme; part time study with field placements in blocks; part time study involving concurrent field placement). Analysis showed that the interest in research courses was predicted by fear of research courses (β = -0.29) as well as by the perceived importance (β = 0.27), attributed usefulness of research (β = 0.15) and perceived unbiased nature of research (β = 0.08). These variables were predicted, in turn, by fear of research courses (β = -0.10, β = -0.23, and β = -0.13). Moreover, interest was predicted by age (β = 0.13). Fear of research courses was predicted by age (β = -0.10) female gender (β = 0.28) and having completed a general baccalaureate (β = -0.09). (GFI = 0.997, AGFI = 0.988, SRMR = 0.016, CMIN/df = 0.946, adj. R2 = 0.312). Findings evidence a direct as well as a mediated impact of fear on the interest in research courses in entering first-year students in a social work bachelor-programme. It highlights one of the challenges social work education in a research framework has to meet with. It seems, there have been considerable efforts to address the research orientation of students. However, these findings point out that, additionally, research anxiety in terms of fear of research courses should be considered and addressed by teachers when conceptualizing research courses.

Keywords: research anxiety, research courses, research interest, research orientation, social work students, teaching

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Authors: Shahla Ali

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In the context of promoting green infrastructure development, new opportunities are emerging to re-examine sustainable development practices. This paper presents an initial exploration of the development of community-investor dispute prevention and facilitation mechanisms in the context of the Belt and Road Initiative (BRI) spanning Asia, Africa, and Europe. Given the widescale impact of China’s multi-jurisdictional development initiative, learning how to coordinate with local communities is vital to realizing inclusive and sustainable growth. In the 20 years since the development of the first multilateral community-investor dispute resolution mechanism developed by the International Finance Centre/World Bank, much has been learned about public facilitation, community engagement, and dispute prevention during the early stages of major infrastructure development programs. This paper will explore initial findings as they relate to initiatives underway along the BRI within the Asian Infrastructure Investment Bank and the Asian Development Bank. Given the borderless nature of sustainability concerns, insights from diverse regions are critical to deepening insights into best practices. Drawing on a case-based methodology, this paper will explore the achievements, challenges, and lessons learned in community-investor dispute prevention and resolution for major infrastructure projects in the greater China region.

Keywords: law and development, dispute prevention, sustainable development, mitigation

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: Zhang Shuqi, Liu Dan

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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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Authors: Elizabeth M. Seabrook, Nikki S. Rickard

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Examining time-dependent measures of emotion such as variability, instability, and inertia, provide critical and complementary insights into mental health status. Observing changes in the pattern of emotional expression over time could act as a tool to identify meaningful shifts between psychological well- and ill-being. From a practical standpoint, however, examining emotion dynamics day-to-day is likely to be burdensome and invasive. Utilizing social media data as a facet of lived experience can provide real-world, temporally specific access to emotional expression. Emotional language on social media may provide accurate and sensitive insights into individual and community mental health and well-being, particularly with focus placed on the within-person dynamics of online emotion expression. The objective of the current study was to examine the dynamics of emotional expression on the social network platform Facebook for active users and their relationship with psychological well- and ill-being. It was expected that greater positive and negative emotion variability, instability, and inertia would be associated with poorer psychological well-being and greater depression symptoms. Data were collected using a smartphone app, MoodPrism, which delivered demographic questionnaires, psychological inventories assessing depression symptoms and psychological well-being, and collected the Status Updates of consenting participants. MoodPrism also delivered an experience sampling methodology where participants completed items assessing positive affect, negative affect, and arousal, daily for a 30-day period. The number of positive and negative words in posts was extracted and automatically collated by MoodPrism. The relative proportion of positive and negative words from the total words written in posts was then calculated. Preliminary analyses have been conducted with the data of 9 participants. While these analyses are underpowered due to sample size, they have revealed trends that greater variability in the emotion valence expressed in posts is positively associated with greater depression symptoms (r(9) = .56, p = .12), as is greater instability in emotion valence (r(9) = .58, p = .099). Full data analysis utilizing time-series techniques to explore the Facebook data set will be presented at the conference. Identifying the features of emotion dynamics (variability, instability, inertia) that are relevant to mental health in social media emotional expression is a fundamental step in creating automated screening tools for mental health that are temporally sensitive, unobtrusive, and accurate. The current findings show how monitoring basic social network characteristics over time can provide greater depth in predicting risk and changes in depression and positive well-being.

Keywords: emotion, experience sampling methods, mental health, social media

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Authors: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

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Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

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Authors: Huicong Jia, Donghua Pan

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As a key component of disaster reduction management, disaster emergency relief and reconstruction is an important process. Based on disaster system theory, this study analyzed the Jiangsu tornado from the formation mechanism of disasters, through to the economic losses, loss of life, and social infrastructure losses along the tornado disaster chain. The study then assessed the emergency relief and reconstruction efforts, based on an analytic hierarchy process method. The results were as follows: (1) An unstable weather system was the root cause of the tornado. The potentially hazardous local environment, acting in concert with the terrain and the river network, was able to gather energy from the unstable atmosphere. The wind belt passed through a densely populated district, with vulnerable infrastructure and other hazard-prone elements, which led to an accumulative disaster situation and the triggering of a catastrophe. (2) The tornado was accompanied by a hailstorm, which is an important triggering factor for a tornado catastrophe chain reaction. (3) The evaluation index (EI) of the emergency relief and reconstruction effect for the ‘‘6.23’’ tornado disaster in Yancheng was 91.5. Compared to other relief work in areas affected by disasters of the same magnitude, there was a more successful response than has previously been experienced. The results provide new insights for studies of disaster systems and the recovery measures in response to tornado catastrophe in China.

Keywords: China, disaster system, emergency relief, tornado catastrophe

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: Sharon Milberger, Jane Turner, Denise White-Perkins

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Michigan shares the overall U.S. national need for more highly qualified professionals who have knowledge and experience in the use of evidence-based practices to meet the special health care needs of children, adolescents, and adults with neurodevelopmental disabilities including autism spectrum disorder (DD/ASD). The Michigan Leadership Education in Neurodevelopmental Disabilities (MI-LEND) program is a consortium of six universities that spans the state of Michigan and serves more than 181,800 undergraduate, graduate, and professional students. The purpose of the MI LEND program is to improve the health of infants, children and adolescents with disabilities in Michigan by training individuals from different disciplines to assume leadership roles in their respective fields and work across disciplines. The MI-LEND program integrates “L.I.F.E.” perspectives into all training components. L.I.F.E. is an acronym for Leadership, Interdisciplinary, Family-Centered and Equity perspectives. This paper will describe how L.I.F.E. perspectives are embedded into all aspects of the MI-LEND training program including the application process, didactic training, community and clinical experiences, discussions, journaling and projects. Specific curriculum components will be described including content from a training module dedicated to Equity. Upon completion of the Equity module, trainees are expected to be able to: 1) Use a population health framework to identify key social determinants impacting families and children; 2) Explain how addressing bias and providing culturally appropriate linguistic care/services can influence patient/client health and wellbeing; and 3) Describe the impact of policy and structural/institutional factors influencing care and services for children with DD/ASD and their families. Each trainee completes two self-assessments: the Cultural and Linguistic Competence Health Practitioner Assessment and the other assessing social attitudes/implicit bias. Trainees also conduct interviews with a family with a child with DD/ASD. In addition, interdisciplinary Equity-related group activities are incorporated into face-to-face training sessions. Each MI-LEND trainee has multiple ongoing opportunities for self-reflection through discussion and journaling and completion of a L.I.F.E. project as a culminating component of the program. The poster will also discuss the challenges related to teaching and measuring successful outcomes related to diversity/equity perspectives.

Keywords: disability, diversity, equity, training

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Authors: N. H. D. P. Fonseka, I. H. Rajapakse, A. S. Dissanayake

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Background: Problem drinking, namely alcohol dependence (AD) and alcohol abuse (AA) are associated with major medical, social and economic adverse consequences. Problem drinking behavior is noted among those admitted to hospitals due to alcohol-related medical/surgical complaints as well as those with unrelated complaints. Literature shows an association between alcohol consumption and depression. Aims of this study were to determine the frequency of problem drinking and depression among males with a history of alcohol consumption tertiary care setting in Southern Sri Lanka. Method: Two-hundred male patients who consumed alcohol, receiving care in medical and surgical wards in Teaching Hospital Galle, were assessed. A validated J12 questionnaire of the Mini International Neuropsychiatric Interview was administered to determine frequency AA and AD. A validated PHQ 9 questionnaire to determine the prevalence and severity of depression. Results: Sixty-three participants (31%) had problem drinking. Of them, 61% had AD, and 39% had AA. Depression was noted in 39 (19%) subjects. In those who reported alcohol consumption not amounting to problem drinking, depression was noted in 23 (16%) participants. Mild depression was seen in 17, moderate in five and moderately severe in one. Among those who had problem drinking, 16 (25%) had depression. Mild depression was seen in four, moderate in seven, moderately severe in three and severe in two. Conclusions: A high proportion alcohol users had problem drinking. Adverse consequences associated with problem drinking places a major strain on the health system especially in a low resource setting where healthcare spending is limited and alcohol cessation support services are not well organised. Thus alcohol consumption and problem drinking behaviour need to be inquired into all medical consultations. Community prevalence of depression in Sri Lanka is approximately 10%. Depression among those consuming alcohol was two times higher compared to the general population. The rates of depression among those with problem drinking were especially high being 2.5 times more common than in the general population. A substantial proportion of these patients with depression had moderately severe or severe depression. When depression coexists with problem drinking, it may increase the tendency to consume alcohol as well as act as a barrier to the success of alcohol cessation interventions. Thus screening all patients who consume alcohol for depression, especially those who are problem drinkers becomes an important step in their clinical evaluation. In addition, in view of the high prevalence of problem drinking and coexistent depression, the need to organize a structured alcohol cessation support service in Sri Lanka as well as the need for increasing access to psychological evaluation and treatment of those with problem drinking are highlighted.

Keywords: alcohol abuse, alcohol, depression, problem drinking

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Authors: Ruwan Gunawardane

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This paper attempts to emphasize the benefits of conducting an intensive course in English for university entrants. In the Sri Lankan university context, an intensive course in English is usually conducted amidst various obstacles. In the 1970s and 1980s, undergraduates had intensive programmes in English for two to three months. Towards the end of the 1990s, a programme called General English Language Training (GELT) was conducted for the new students, and it was done outside universities before they entered their respective universities. Later it was not conducted, and that also resulted in students’ poor performance in English at university. However, having understood its importance, an eight week long intensive course in English was conducted for the new intake of the Faculty of Science, University of Ruhuna. As the findings show, the students heavily benefited from the programme. More importantly, they had the opportunity to refresh their knowledge of English gained at school and private institutions while gaining new knowledge. Another advantage was that they had plenty of time to enjoy learning English since the learners had adequate opportunities to carry out communicative tasks and the course was not exam-oriented, which reduced their fear of making mistakes in English considerably. The data was collected through an open-ended questionnaire given to 60 students, and their oral feedback was also taken into consideration. In addition, a focus group interview with 6 teachers was also conducted to get an idea about their experience and perception. The data were qualitatively analyzed. The findings suggest that an intensive programme in English undoubtedly lays a good foundation for the students’ academic career at university.

Keywords: intensive course, English, teachers, undergraduates, experience, perception

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Authors: Jeewantha Ranawaka, Gunawardane Kapila, Wijethunaga Mudiyanselage B. G. Jayathilake

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Introduction: Sweeping of the membranes is a fairly simple technique that may positively influence the shift from maintenance of pregnancy to the beginning of labor. Objective: To assess the effectiveness and acceptability of twice versus once-only membrane sweeping in uncomplicated primi gravid at 40 weeks of gestational age in a tertiary care hospital in Sri Lanka. Methods: A randomized controlled clinical trial was done in Ward 05 of Teaching Hospital, Kandy. The participants were primi-gravida with a singleton live fetus who was at 40 weeks of gestation with intact fetal membranes and with a Modified Bishop’s score <5. After randomization both groups received membrane sweeping at 40 weeks of gestation and the experimental group received membrane sweeping after 48 hours (40+2 days). The modified Bishop Score was assessed at 40+5 days. In two groups who did not go into natural labor at 40+5 days were managed according to the ward policy of cervical ripening and with labor induction at 40+5 days. Two different methods were used to assess discomfort and pain. Patient acceptability was assessed using recommendation to another patient and acceptance during next pregnancy. Perinatal, maternal and labour outcomes were assessed. Results: A change of the Bishops score was 67.3% (n= 31 of 46) in experimental group whereas in control group it was 57.5% (n= 38 of 66). (p = 0.21, OR-1.52, CI = 0.6 -3.34). Mean (SD) of Modified Bishop score was 6.36 (1.94) in experimental group and 6.03 (.84) in control group (p = 0.354). The probability of having the spontaneous onset of labour in experimental group was 61.6% (n=74 of 120) whereas in control group it was 45% (n= 54 of 120) (p=0.01, OR-1.966, CI = 1.17 – 3.28 NNT = 5.99). Recommending the method to another among experimental group was 75% (n= 90 of 120) whereas in control group it was 79.2% (n= 95 of 120) (p= 0.443). Accepting membrane Sweeping for subsequent pregnancy among experimental was 72.5% (n=87 of 120) whereas in control group was 72.5% (n=87 of 120) (p= 1.00) Need of formal induction of labour at 40+ 5 days in experimental group was 38.4% (n=46 of 120) whereas in control group was 61.6% (n=66 of 120) (p=0.01, OR=0.5, CI= 0.3 – 0.8, NNT=6). Neonatal outcome, labour outcome such as Cesarean -section rate, need for augmentation and maternal complications such as fever, Premature rupture of membrane, bleeding were comparable in two groups. Conclusions and Recommendations: It can be concluded that twice sweeping of membrane was effective to reduce the need of formal induction of labour and increase the chances of having spontaneous onset of labour (SOL) at 40+5 days without increasing maternal or fetal morbidity. Acceptability of twice sweeping is not different from sweeping once. Hence we recommend consideration of multiple membranes sweeping as first line for women at 40 weeks of gestation.

Keywords: acceptability, induction, labour, membrane sweeping

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Authors: Mahfoodh Saleh Al Sabbagh, Venkoba Rao

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There is plenty of research, both in academic and consultancy circles, about the importance and benefits of employee engagement and customer engagement and how it gives organization an opportunity to reduce variability and improve performance. Customer engagement is directly related to the engagement level of the organization's employees. It is therefore important to measure both. This research drawing from the work of Human Sigma by Fleming and Asplund, attempts to assess engagement level of customer and employees - the human systems of business - in an educational setup. Student is important to an educational institute and is a customer to be served efficiently and effectively. Considering student as customer and faculty as employees serving them, in–depth interviews were conducted to analyze the relationship between faculty and student engagement in two leading colleges in Oman, one from private sector and another from public sector. The study relied mainly on secondary data sources to understand the concept of engagement. However, the search of secondary sources was extensive to compensate the limited primary data. The results indicate that high faculty engagement is likely to lead to high student engagement. Engaged students were excited about learning, loved the feeling of they being cared as a person by their faculty and advocated the organization to other. The interaction truly represents an opportunity to build emotional connection to the organization. This study could be of interest to organizations interest in building and maintaining engagement with employees and customers.

Keywords: customer engagement, consumer psychology, strategy, educational institutes

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Authors: Abhijeet Ostawal, Parmjit Lall

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The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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Authors: Andrea Hernandez Hurtado

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Research on social networks (SNs) -- the interactions individuals share with others has shed important light in helping to explain differential use of variable linguistic forms, both in L1s and L2s. Nevertheless, the acquisition of nonstandard L2 Spanish in the Region of Murcia, Spain, and how learners interact with other speakers while sojourning there have received little attention. Murcian Spanish (MuSp) was widely influenced by Panocho, a divergent evolution of Hispanic Latin, and differs from the more standard Peninsular Spanish (StSp) in phonology, morphology, and lexicon. For instance, speakers from this area will most likely palatalize diminutive endings, producing animalico [̩a.ni.ma.ˈli.ko] instead of animalito [̩a.ni.ma.ˈli.to] ‘little animal’. Because L1 speakers of the area produce and prefer salient regional lexicon and morphology (particularly the palatalized diminutive -ico) in their speech, the current research focuses on how international residents in the Region of Murcia use Spanish: (1) whether or not they acquire (perceptively and/or productively) any of the salient regional features of MuSp, and (2) how their SNs explain such acquisition. This study triangulates across three tasks -recognition, production, and preference- addressing both lexicon and morphology, with each task specifically created for the investigation of MuSp features. Among other variables, the effects of L1, residence, and identity are considered. As an ongoing dissertation research, data are currently being gathered through an online questionnaire. So far, 7 participants from multiple nationalities have completed the survey, although a minimum of 25 are expected to be included in the coming months. Preliminary results revealed that MuSp lexicon and morphology were successfully recognized by participants (p<.001). In terms of regional lexicon production (10.0%) and preference (47.5%), although participants showed higher percentages of StSp, results showed that international residents become aware of stigmatized lexicon and may incorporate it into their language use. Similarly, palatalized diminutives (production 14.2%, preference 19.0%) were present in their responses. The Social Network Analysis provided information about participants’ relationships with their interactants, as well as among them. Results indicated that, generally, when residents were more immersed in the culture (i.e., had more Murcian alters) they produced and preferred more regional features. This project contributes to the knowledge of language variation acquisition in L2 speakers, focusing on a stigmatized Spanish dialect and exploring how stigmatized varieties may affect L2 development. Results will show how L2 Spanish speakers’ language is affected by their stay in Murcia. This, in turn, will shed light on the role of SNs in language acquisition, the acquisition of understudied and marginalized varieties, and the role of immersion on language acquisition. As the first systematic account on the acquisition of L2 Spanish lexicon and morphology in the Region of Murcia, it lays important groundwork for further research on the connection between SNs and the acquisition of regional variants, applicable to Murcia and beyond.

Keywords: international residents, L2 Spanish, lexicon, morphology, nonstandard language acquisition, social networks

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Authors: Waleed Alanzi

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The purpose of this qualitative study was to add to the existing literature and provide a more detailed understanding of the individual experiences and perceptions of 15 Deans at the University of Kuwait regarding their first year of planning, developing, and implementing crisis distance education (CDE) in response to the COVID-19 epidemic. An interpretative phenomenological approach was applied, using the thematic analysis of interview transcripts to describe the challenging journeys taken by each of the Deans from the first-person point of view. There was objective evidence, manifested by four primary themes (“Obstacles to the implementation of CDE”; “Planning for CDE”; “Training for CDE,” and “Future Directions”) to conclude that the faculty members, technical staff, administrative staff, and students generally helped each other to overcome the obstacles associated with planning and implementing CDE. The idea that CDE may turn homes into schools and parents into teachers was supported. The planning and implementation of CDE were inevitably associated with a certain amount of confusion, as well as disruptions in the daily routines of staff and students, as well as significant changes in their responsibilities. There were contradictory ideas about the future directions of distance education after the pandemic. Previous qualitative research on the implementation of CDE at higher education institutions in the Arab world has focused mainly on the experiences and perceptions of students; however, little is known about the experiences and perceptions of the students at the University of Kuwait during the COVID19 pandemic, providing a rationale and direction for future research.

Keywords: distance learning, qualitative research, COVID-19 epidemic, Kuwait university

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Christopher Leung, Tony Kim, Rebecca Lendzion, Scott Mackenzie

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Retroperitoneal abscesses are a rare but serious condition with often delayed diagnosis, non-specific symptoms, multiple causes and high morbidity/mortality. With the advent of more readily available cross-sectional imaging, retroperitoneal abscesses are treated earlier and better outcomes are achieved. Occasionally, a retroperitoneal abscess is present as a huge retroperitoneal abscess, as evident in this 53-year-old male. With a background of chronic renal disease and left partial nephrectomy, this gentleman presented with a one-month history of left flank pain without any other symptoms, including fevers or abdominal pain. CT abdomen and pelvis demonstrated a huge retroperitoneal abscess spanning from the diaphragm, abutting the spleen, down to the iliopsoas muscle and abutting the iliac vessels at the pelvic brim. This large retroperitoneal abscess required open drainage as well as drainage by interventional radiology. A long course of intravenous antibiotics and multiple drainages was required to drain the abscess. His blood culture and fluid culture grew Proteus species suggesting a urinary source, likely from his non-functioning kidney, which had a partial nephrectomy. Such a huge retroperitoneal abscess has rarely been described in the literature. The learning point here is that the basic principle of source control and antibiotics is paramount in treating retroperitoneal abscesses regardless of the size of the abscess.

Keywords: retroperitoneal abscess, retroperitoneal mass, sepsis, genitourinary infection

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: Linda Richter

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Background and Significance: The influence of parents on their children’s attitudes and behaviors is immense, even as children grow out of what one might assume to be their most impressionable years and into teenagers. This study specifically examines the potential that parents have to prevent or reduce the risk of adolescent substance use, even in the face of considerable environmental influences to use nicotine, alcohol, or drugs. Methodology: The findings presented are based on a nationally representative survey of 1,014 teens aged 12-17 living in the United States. Data were collected using an online platform in early 2018. About half the sample was female (51%), 49% was aged 12-14, and 51% was aged 15-17. The margin of error was +/- 3.5%. Demographic data on the teens and their families were available through the survey platform. Survey items explored adolescent respondents’ exposure to addictive substances; the extent to which their sources of information about these substances are reliable or credible; friends’ and peers’ substance use; their own intentions to try substances in the future; and their relationship with their parents. Key Findings: Exposure to nicotine, alcohol, or other drugs and misinformation about these substances were associated with a greater likelihood that adolescents have friends who use drugs and that they have intentions to try substances in the future, which are known to directly predict actual teen substance use. In addition, teens who reported a positive relationship with their parents and having parents who are involved in their lives had a lower likelihood of having friends who use drugs and of having intentions to try substances in the future. This relationship appears to be mediated by parents’ ability to reduce the extent to which their children are exposed to substances in their environment and to misinformation about them. Indeed, the findings indicated that teens who reported a good relationship with their parents and those who reported higher levels of parental monitoring had significantly higher odds of reporting a lower number of risk factors than teens with a less positive relationship with parents or less monitoring. There also were significantly greater risk factors associated with substance use among older teens relative to younger teens. This shift appears to coincide directly with the tendency of parents to pull back in their monitoring and their involvement in their adolescent children’s lives. Conclusion: The survey findings underscore the importance of resisting the urge to completely pull back as teens age and demand more independence since that is exactly when the risks for teen substance use spike and young people need their parents and other trusted adults to be involved more than ever. Particularly through the cultivation of a healthy, positive, and open relationship, parents can help teens receive accurate and credible information about substance use and also monitor their whereabouts and exposure to addictive substances. These findings, which come directly from teens themselves, demonstrate the importance of continued parental engagement throughout children’s lives, regardless of their age and the disincentives to remaining involved and connected.

Keywords: adolescent, parental monitoring, prevention, substance use

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Authors: Katie Dolaghan, Christina Tran, Kim Hamilton, Amanda Beresford, Vicky Adams, Jamie Toole, John Marley

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During the Covid 19 pandemic routine outpatient appointments were not possible face to face. That resulted in many branches of healthcare starting virtual clinics. These clinics have continued following the return to face to face patient appointments. With these new types of clinic it is important to ensure that a high standard of patient care is maintained. In order to improve patient and clinician experience of the telephone clinics a quality improvement project was carried out to ensure the patient and clinician experience of these clinics was enhanced whilst remaining a safe, effective and an efficient use of resources. The project began by developing a process map for the consultation process and agreed on the design of a driver diagram and tests of change. In plan do study act (PDSA) cycle1 a single consultant completed an online survey after every patient encounter over a 5 week period. Baseline patient responses were collected using a follow-up telephone survey for each patient. Piloting led to several iterations of both survey designs. Salient results of PDSA1 included; patients not receiving appointment letters, patients feeling more anxious about a virtual appointment and many would prefer a face to face appointment. The initial clinician data showed a positive response with a provisional diagnosis being reached in 96.4% of encounters. PDSA cycle 2 included provision of a patient information sheet and information leaflets relevant to the patients’ conditions were developed and sent following new patient telephone clinics with follow-up survey analysis as before to monitor for signals of change. We also introduced the ability for patients to send an images of their lesion prior to the consultation. Following the changes implemented we noted an improvement in patient satisfaction and, in fact, many patients preferring virtual clinics as it lead to less disruption of their working lives. The extra reading material both before and after the appointments eased patients’ anxiety around virtual clinics and helped them to prepare for their appointment. Following the patient feedback virtual clinics are now used for review patients as well, with all four consultants within the department continuing to utilise virtual clinics. During this presentation the progression of these clinics and the reasons that these clinics are still operating following the return to face to face appointments will be explored. The lessons that have been gained using a QI approach have helped to deliver an optimal service that is valid and reliable as well as being safe, effective and efficient for the patient along with helping reduce the pressures from ever increasing waiting lists. In summary our work in improving the quality of virtual clinics has resulted in improved patient satisfaction along with reduced pressures on the facilities of the health trust.

Keywords: clinic, satisfaction, telephone, virtual

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Authors: Qiao Mao

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There is a growing number of studies concerning STEM (Science, Technology, Engineering, and Mathematics) and STEAM (Science, Technology, Engineering, Arts, and Mathematics). However, the research is little on STEAM competitions from Arts' perspective. This study takes the annual PowerTech STEAM competition in Taiwan as an example. In this activity, students are asked to make wooden bionic mechanical beasts on the spot and participate in a model and speed competition. This study aims to explore how Arts influences STEM after it involves in the making of mechanical beasts. A case study method is adopted. Through expert sampling, five prize winners in the PowerTech Youth Science and Technology Creation Competition and their supervisors are taken as the research subjects. Relevant data which are collected, sorted out, analyzed and interpreted afterwards, derive from observations, interview and document analyses, etc. The results of the study show that in the PowerTech Youth Science and Technology Creation Competition, when Arts involves in STEM, (1) it has an impact on the athletic performance, balance, stability and symmetry of mechanical beasts; (2) students become more interested and more creative in making STEAM mechanical beasts, which can promote students' learning of STEM; (3) students encounter more difficulties and problems when making STEAM mechanical beasts, and need to have more systematic thinking and design thinking to solve problems.

Keywords: PowerTech, STEAM contest, mechanical beast, arts' role

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