Search results for: integrated learning

Authors: P. Cavlan, B. Kırmızıgil

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Introduction: Each exercise in suspension exercises offer the use of gravity and body weight; and is thought to develop the equilibrium, flexibility and body stability necessary for daily life activities and sports, in addition to creating the correct functional force. Suspension exercises based on body weight focus the human body as an integrated system. Total Resistance Exercises (TRX) suspension training that physiotherapists, athletic health clinics, exercise centers of hospitals and chiropractic clinics now use for rehabilitation purposes. The purpose of this study is to investigate and compare the effects of TRX suspension exercises on physical performance in healthy individuals. Method: Healthy subjects divided into two groups; the study group and the control group with 40 individuals for each, between ages 20 to 45 with similar gender distributions. Study group had 2 sessions of suspension exercises per week for 8 weeks and control group had no exercises during this period. All the participants were given explosive strength, flexibility, strength and endurance tests before and after the 8 week period. The tests used for evaluation were respectively; standing long jump test and single leg (left and right) long jump tests, sit and reach test, sit up and back extension tests. Results: In the study group a statistically significant difference was found between prior- and final-tests in all evaluations, including explosive strength, flexibility, core strength and endurance of the group performing TRX exercises. These values were higher than the control groups’ values. The final test results were found to be statistically different between the study and control groups. Study group showed development in all values. Conclusions: In this study, which was conducted with the aim of investigating and comparing the effects of TRX suspension exercises on physical performance, the results of the prior-tests of both groups were similar. There was no significant difference between the prior and the final values in the control group. It was observed that in the study group, explosive strength, flexibility, strength, and endurance development was achieved after 8 weeks. According to these results, it was shown that TRX suspension exercise program improved explosive strength, flexibility, especially core strength and endurance; therefore the physical performance. Based on the results of our study, it was determined that the physical performance, an indispensable requirement of our life, was developed by the TRX suspension system. We concluded that TRX suspension exercises can be used to improve the explosive strength and flexibility in healthy individuals, as well as developing the muscle strength and endurance of the core region. The specific investigations could be done in this area so that programs that emphasize the TRX's physical performance features could be created.

Keywords: core strength, endurance, explosive strength, flexibility, physical performance, suspension exercises

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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

Procedia PDF Downloads 102

Authors: Pooria Norouzi, Nicholas Tsang, Adam van der Goes, Joseph Yu, Douglas Zheng, Sirine Maleej

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In this study, virtual meters will be designed and used for energy balance measurements of an air handling unit (AHU). The method aims to replace traditional physical sensors in heating, ventilation, and air conditioning (HVAC) systems with simulated virtual meters. Due to the inability to manage and monitor these systems, many HVAC systems have a high level of inefficiency and energy wastage. Virtual meters are implemented and applied in an actual HVAC system, and the result confirms the practicality of mathematical sensors for alternative energy measurement. While most residential buildings and offices are commonly not equipped with advanced sensors, adding, exploiting, and monitoring sensors and measurement devices in the existing systems can cost thousands of dollars. The first purpose of this study is to provide an energy consumption rate based on available sensors and without any physical energy meters. It proves the performance of virtual meters in HVAC systems as reliable measurement devices. To demonstrate this concept, mathematical models are created for AHU-07, located in building NE01 of the British Columbia Institute of Technology (BCIT) Burnaby campus. The models will be created and integrated with the system’s historical data and physical spot measurements. The actual measurements will be investigated to prove the models' accuracy. Based on preliminary analysis, the resulting mathematical models are successful in plotting energy consumption patterns, and it is concluded confidently that the results of the virtual meter will be close to the results that physical meters could achieve. In the second part of this study, the use of virtual meters is further assisted by artificial intelligence (AI) in the HVAC systems of building to improve energy management and efficiency. By the data mining approach, virtual meters’ data is recorded as historical data, and HVAC system energy consumption prediction is also implemented in order to harness great energy savings and manage the demand and supply chain effectively. Energy prediction can lead to energy-saving strategies and considerations that can open a window in predictive control in order to reach lower energy consumption. To solve these challenges, the energy prediction could optimize the HVAC system and automates energy consumption to capture savings. This study also investigates AI solutions possibility for autonomous HVAC efficiency that will allow quick and efficient response to energy consumption and cost spikes in the energy market.

Keywords: virtual meters, HVAC, artificial intelligence, energy consumption prediction

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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

Procedia PDF Downloads 189

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: Siddharth Sarma, Ayush Majumdar, Nidhi Sabu, Mufaddal Jiruwaala, Shilpa Paygude

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Digital Elevation Models (DEMs) are digital representations of the Earth’s topography, which include information about the elevation, slope, aspect, and other terrain attributes. DEMs play a crucial role in various applications, including terrain analysis, urban planning, and environmental modeling. In this paper, TerraEnhance is proposed, a distinct approach for high-resolution DEM generation using Generative Adversarial Networks (GANs) combined with Real-ESRGANs. By learning from a dataset of low-resolution DEMs, the GANs are trained to upscale the data by 10 times, resulting in significantly enhanced DEMs with improved resolution and finer details. The integration of Real-ESRGANs further enhances visual quality, leading to more accurate representations of the terrain. A post-processing layer is introduced, employing high-pass filtering to refine the generated DEMs, preserving important details while reducing noise and artifacts. The results demonstrate that TerraEnhance outperforms existing methods, producing high-fidelity DEMs with intricate terrain features and exceptional accuracy. These advancements make TerraEnhance suitable for various applications, such as terrain analysis and precise environmental modeling.

Keywords: DEM, ESRGAN, image upscaling, super resolution, computer vision

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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: Abdul Rahman Hamdan

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The Fourth Industrial Revolution (4IR) has brought unprecedented technological advancements that have disrupted many industries worldwide. In keeping up with the technological advances and rapid disruption by the introduction of many technological advancements brought forth by the 4IR, the use of technology road mapping has emerged as one of the critical tools for organizations to leverage. Technology road mapping can be used by many companies to guide them to become more adaptable and anticipate future transformation and innovation, and avoid being redundant or irrelevant due to the rapid changes in technological advancement. This research paper provides a comprehensive analysis of technology road mapping within the context of the 4IR. The objectives of the paper are to provide companies with practical insights and a strategic framework of technology road mapping for them to navigate the fast-changing nature of the 4IR. This study also contributes to the understanding and practice of technology road mapping in the 4IR and, at the same time, provides organizations with the necessary tools and critical insight to navigate the 4IR transformation by leveraging technology road mapping. Based on the literature review and case studies, the study analyses key principles, methodologies, and best practices in technology road mapping and integrates them with the unique characteristics and challenges of the 4IR. The research paper gives the background of the fourth industrial revolution. It explores the disruptive potential of technologies in the 4IR and the critical need for technology road mapping that consists of strategic planning and foresight to remain competitive and relevant in the 4IR era. It also highlights the importance of technology road mapping as an organisation’s proactive approach to align the organisation’s objectives and resources to their technology and product development in meeting the fast-evolving technological 4IR landscape. The paper also includes the theoretical foundations of technology road mapping and examines various methodological approaches, and identifies external stakeholders in the process, such as external experts, stakeholders, collaborative platforms, and cross-functional teams to ensure an integrated and robust technological roadmap for the organisation. Moreover, this study presents a comprehensive framework for technology road mapping in the 4IR by incorporating key elements and processes such as technology assessment, competitive intelligence, risk analysis, and resource allocation. It provides a framework for implementing technology road mapping from strategic planning, goal setting, and technology scanning to road mapping visualisation, implementation planning, monitoring, and evaluation. In addition, the study also addresses the challenges and limitations related to technology roadmapping in 4IR, including the gap analysis. In conclusion of the study, the study will propose a set of practical recommendations for organizations that intend to leverage technology road mapping as a strategic tool in the 4IR in driving innovation and becoming competitive in the current and future ecosystem.

Keywords: technology management, technology road mapping, technology transfer, technology planning

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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: Mala Tankam Carine, Kekeunou Sévilor, Nukenine Elias

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Storage and preservation of agricultural products remain the only conditions ensuring the almost permanent availability of foodstuffs. However, infestations due to insects and microorganisms often occur. Callosobruchus maculatus is a pest that causes a lot of damage to cowpea stocks in the tropics. Several methods are adopted to limit their damage, but the use of synthetic chemical insecticides is the most widespread. Biopesticides in sustainable agriculture respond to several environmental, economic and social concerns while offering innovative opportunities that are ecologically and economically viable for producers, workers, consumers and ecosystems. Our main objective is to evaluate the insecticidal efficacy of binary combinations of Fossilshield with root-bark powder of Securidaca longepedunculata against Callosobruchus maculatus in stored cowpea Vigna unguiculata. Laboratory bioassays were conducted in stored grains to evaluate the toxicity of root-bark powder of Securidaca longepedunculata alone or combined with diatomaceous earth Fossil-Shield ® against C. maculatus. Twenty-hour-old adults of C. maculatus were exposed to 50g of cowpea seeds treated with four doses (10, 20, 30, and 40g/kg) of root-bark powder of S. longepedunculata, on the one hand, and (0.5, 1, 1.5, and 2 g/kg) on DE and binary combinations on the other hand. 0g/kg corresponded to untreated control. Adult mortality was recorded up to 7 days (d) post-treatment, whereas the number of F1 progeny was assessed after 30 d. Weight loss and germinative ability were conducted after 120 d. All treatments were arranged according to a completely randomized block with four replicates. The combined mixture of S. longepedunculata and DE controlled the beetle faster compared to the root-bark powder of S. longepedunculata alone. According to the Co-toxicity coefficient, additive effect of binary combinations was recorded at 3-day post-exposure time with the mixture 25% FossilShield + 75% S. longepedunculata. A synergistic action was observed after 3-d post-exposure at mixture 50% FossilShield + 50% S. longepedunculata and at 1-d and 3-d post-exposure periods at mixture 75% FossilShield + 25% S. longepedunculata. The mixture 25% FossilShield + 75% S. longepedunculata induced a decreased progeny of 6 times fewer individuals for 4.5 times less weight loss and 2, 9 times more sprouted grains than with root-bark powder of S. longepedunculata. The combination of FossilShield + S. longepedunculata was more potent than root-bark powder of S. longepedunculata alone, although the root-bark powder of S. longepedunculata caused significant reduction of F1 adults compared to the control. Combined action of botanical insecticides with FossilShield as a grain protectant in an integrated pest management approach is discussed.

Keywords: diatomaceous earth, cowpea, callosobruchus maculatus, securidaca longepedunculata, combined action, co-toxicity coefficient

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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

Procedia PDF Downloads 132

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: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris

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An aero-derivative marine Gas Turbine engine model is simulated to be installed as the main propulsion prime mover to power a cruise ship which is designed and routed to transport intending Muslim pilgrims for the annual hajj pilgrimage from Nigeria to the Islamic port city of Jeddah in Saudi Arabia. A performance assessment of the Gas Turbine engine has been conducted by examining the effect of varying aerodynamic and hydrodynamic conditions encountered at various geographical locations along the scheduled transit route during the voyage. The investigation focuses on the overall behavior of the Gas Turbine engine employed to power and propel the ship as it operates under ideal and adverse conditions to be encountered during calm and rough weather according to the different seasons of the year under which the voyage may be undertaken. The variation of engine performance under varying operating conditions has been considered as a very important economic issue by determining the time the speed by which the journey is completed as well as the quantity of fuel required for undertaking the voyage. The assessment also focuses on the increased resistance caused by the fouling of the submerged portion of the ship hull surface with its resultant effect on the power output of the engine as well as the overall performance of the propulsion system. Daily ambient temperature levels were obtained by accessing data from the UK Meteorological Office while the varying degree of turbulence along the transit route and according to the Beaufort scale were also obtained as major input variables of the investigation. By assuming the ship to be navigating the Atlantic Ocean and the Mediterranean Sea during winter, spring and summer seasons, the performance modeling and simulation was accomplished through the use of an integrated Gas Turbine performance simulation code known as ‘Turbomach’ along with a Matlab generated code named ‘Poseidon’, all of which have been developed at the Power and Propulsion Department of Cranfield University. As a case study, the results of the various assumptions have further revealed that the marine Gas Turbine is a reliable and available alternative to the conventional marine propulsion prime movers that have dominated the maritime industry before now. The techno-economic and environmental assessment of this type of propulsion prime mover has enabled the determination of the effect of changes in weather and sea conditions on the ship speed as well as trip time and the quantity of fuel required to be burned throughout the voyage.

Keywords: ambient temperature, hull fouling, marine gas turbine, performance, propulsion, voyage

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Authors: Camilla Marini, Deborah Agostino

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Cultural institutions provide more than service-based offers; indeed, they are experience-based contexts. A cultural experience is a special event that encompasses a wide range of values which, for visitors, are primarily cultural rather than economic and financial. Cultural institutions have always been characterized by inclusivity and participatory practices, but the upcoming of digital technologies has put forward their interest in collaborative practices and the relationship with their audience. Indeed, digital technologies highly affected the cultural experience as it was conceived. Especially, museums, as traditional and authoritative cultural institutions, have been highly challenged by digital technologies. They shifted by a collection-oriented toward a visitor-centered approach, and digital technologies generated a highly interactive ecosystem in which visitors have an active role, shaping their own cultural experience. Most of the studies that investigate value co-creation in museums adopt a single perspective which is separately one of the museums or one of the users, but the analysis of the convergence/divergence of these perspectives is still emphasized. Additionally, many contributions focus on digital value co-creation as an outcome rather than as a process. The study aims to provide a joint perspective on digital value co-creation which include both museum and visitors. Also, it deepens the contribution of digital technologies in the value co-creation process, addressing the following research questions: (i) what are the convergence/divergence drivers on digital value co-creation and (ii) how digital technologies can be means of value co-creation? The study adopts an action research methodology that is based on the case of WORTHY, an educational project which involves cultural institutions and schools all around Europe, creating a virtual collaborative museum. It represents a valuable case for the aim of the study since it has digital technologies at its core, and the interaction through digital technologies is fundamental, all along with the experience. Action research has been identified as the most appropriate methodology for researchers to have direct contact with the field. Data have been collected through primary and secondary sources. Cultural mediators such as museums, teachers and students’ families have been interviewed, while a focus group has been designed to interact with students, investigating all the aspects of the cultural experience. Secondary sources encompassed project reports and website contents in order to deepen the perspective of cultural institutions. Preliminary findings highlight the dimensions of digital value co-creation in cultural institutions from a museum-visitor integrated perspective and the contribution of digital technologies in the value co-creation process. The study outlines a two-folded contribution that encompasses both an academic and a practitioner level. Indeed, it contributes to fulfilling the gap in cultural management literature about the convergence/divergence of service provider-user perspectives but it also provides cultural professionals with guidelines on how to evaluate the digital value co-creation process.

Keywords: co-creation, digital technologies, museum, value

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Authors: Dosun Shin, Assegid Kidane, Pavan Turaga

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According to the National Institute of Health, living a sedentary lifestyle leads to a number of health issues, including increased risk of cardiovascular dis-ease, type 2 diabetes, obesity, and certain types of cancers. This project brings together experts in multiple disciplines to bring product design, sensor design, algorithms, and health intervention studies to develop a product and system that helps reduce the amount of time sitting at the workplace. This paper illustrates ongoing improvements to prototypes the research team developed in initial research; including working prototypes with a software application, which were developed and demonstrated for users. Additional modifications were made to improve functionality, aesthetics, and ease of use, which will be discussed in this paper. Extending on the foundations created in the initial phase, our approach sought to further improve the product by conducting additional human factor research, studying deficiencies in competitive products, testing various materials/forms, developing working prototypes, and obtaining feedback from additional potential users. The solution consisted of an aesthetically pleasing seat cover cushion that easily attaches to common office chairs found in most workplaces, ensuring a wide variety of people can use the product. The product discreetly contains sensors that track when the user sits on their chair, sending information to a phone app that triggers reminders for users to stand up and move around after sitting for a set amount of time. This paper also presents the analyzed typical office aesthetics and selected materials, colors, and forms that complimented the working environment. Comfort and ease of use remained a high priority as the design team sought to provide a product and system that integrated into the workplace. As the research team continues to test, improve, and implement this solution for the sedentary workplace, the team seeks to create a viable product that acts as an impetus for a more active workday and lifestyle, further decreasing the proliferation of chronic disease and health issues for sedentary working people. This paper illustrates in detail the processes of engineering, product design, methodology, and testing results.

Keywords: anti-sedentary work behavior, new product development, sensor design, health intervention studies

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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: Sudikshya Bhandari, Jonathan K. London

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Barpak in northern Nepal represents a unique identity expressed through the local rituals, values, lifeways and the styles of vernacular architecture. The traditional residential buildings and construction practices adopted by the dominant ethnic groups: Ghales and Gurungs, reflect environmental, social, cultural and economic concerns. However, most of these buildings did not survive the Gorkha earthquake in 2015 that made many residents skeptical about their strength to resist future disasters. This led Barpak residents to prefer modern housing designs primarily for the strength but additionally for convenience and access to earthquake relief funds. Post-earthquake reconstruction has transformed the cohesive community, developed over hundreds of years into a haphazard settlement with the imposition of externally-driven building models. Housing guidelines provided for the community reconstruction and earthquake resilience have been used as a singular template, similar to other communities on different geographical locations. The design and construction of these buildings do not take into account the local, historical, environmental, social, cultural and economic context of Barpak. In addition to the physical transformation of houses and the settlement, the consequences continue to develop challenges to sustainability. This paper identifies the major challenges for environmental sustainability with the construction of new houses in post-earthquake Barpak. Mixed methods such as interviews, focus groups, site observation, and documentation, and analysis of housing and neighborhood design have been used for data collection. The discernible changing situation of this settlement due to the new housing has included reduced climatic adaptation and thermal comfort, increased consumption of agricultural land and water, minimized use of local building materials, and an increase in energy demand. The research has identified that reconstruction housing practices happening in Barpak, while responding to crucial needs for disaster recovery and resilience, are also leading this community towards an unsustainable future. This study has also integrated environmental, social, cultural and economic parameters into an assessment framework that could be used to develop place-based design guidelines in the context of other post-earthquake reconstruction efforts. This framework seeks to minimize the unintended repercussions of unsustainable reconstruction interventions, support the vitality of vernacular architecture and traditional lifeways and respond to context-based needs in coordination with residents.

Keywords: earthquake, environment, reconstruction, sustainability

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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: Soofia Malik

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The purpose of this study is to develop an instrument to measure undergraduate students’ attitudes toward mathematics (MAT) and to assess the data collected from the instrument for validity and reliability. The instrument is developed using five subscales: anxiety, enjoyment, self-confidence, value, and technology. The technology dimension is added as the fifth subscale of attitude toward mathematics because of the recent trend of incorporating online homework in mathematics courses as well as due to heavy reliance of higher education on using online learning management systems, such as Blackboard and Moodle. The sample consists of 163 (M = 82, F = 81) undergraduates enrolled in College Algebra course in the summer 2017 semester at a university in the USA. The data is analyzed to answer the research question: if and how do undergraduate students’ attitudes toward mathematics load using Principal Components Analysis (PCA)? As a result of PCA, three subscales emerged namely: anxiety/self-confidence scale, enjoyment, and value scale. After deleting the last five items or the last two subscales from the initial MAT scale, the Cronbach’s alpha was recalculated using the scores from 20 items and was found to be α = .95. It is important to note that the reliability of the initial MAT form was α = .93. This means that employing the final MAT survey form would yield consistent results in repeated uses. The final MAT form is, therefore, more reliable as compared to the initial MAT form.

Keywords: college algebra, Cronbach's alpha reliability coefficient, Principal Components Analysis, PCA, technology in mathematics

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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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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, Samut Songkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: 1. The identity of Amphur (District) Mueang, Samut Songkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. 2. The communication of the identity of Amphur Mueang, Samut Songkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of Amphur Mueang, Samut Songkram province 2) Wat Phet Samut Worrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep Amphur Mueang, Samut Songkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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Authors: Kamal Kumar Gupta, Sunil Kayesth

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Dysdercus koenigii is serious pest of cotton and other malvaceous crop. Present research work aimed at ecofriendly approach for management of pest by plant extracts. The impact of Ocimum sanctum was studied on reproductive performance of Dysdercus koenigii. The hexane extract of Ocimum leaves was prepared by ‘cold extraction method’. The newly emerged fifth instar nymphs were exposed to the extract of concentrations ranging from 0.1% to 0.00625% by ‘thin film residual method’ for a period of 24h. Reproductive fitness of the adults emerged from the treated nymphs was evaluated by assessing their courtship behaviour, oviposition behaviour, and fertility. The studies indicated that treatment of Dysdercus with the hexane extract of Ocimum altered their courtship behaviour. Consequently, the treated males exhibited less sexual activity, performed fewer mounting attempts, increased time to mate and showed decreased percent successful mating. The females often rejected courting treated male by shaking the abdomen. Similarly, the treated females in many cases remained non-receptive to the courting male. Premature termination of mating in the mating pairs prior to insemination further decreased the mating success of the treated adults. Maximum abbreviation of courtship behaviour was observed in the experimental set up where both the males and the females were treated. Only females which mate successfully were observed for study of oviposition behaviour. The treated females laid lesser number of egg batches and eggs in their life span. The eggs laid by these females were fertile indicating insemination of the female. However, percent hatchability was lesser than control. The effects of hexane extract were dose dependent. Treatment with 0.1% and 0.05% extract altered courtship behaviour. Doses of concentrations less than 0.05% did not affect courtship behaviour but altered the oviposition behaviour and fertility. Significant reduction in the fecundity and fertility was observed in the treatments at concentration as low as 0.00625%. The GCMS analysis of the extract revealed a plethora of phytochemicals including juvenile hormone mimics, and the intermediates of juvenile hormone biosynthesis. Therefore, some of these compounds individually or synergistically impair reproductive behaviour of Dysdercus. Alteration of courtship behaviour and suppression of fecundity and fertility with the help of plant extracts has wide potentials in suppression of pest population and ‘integrated pest management’.

Keywords: courtship behaviour, Dysdercus koenigii, Ocimum sanctum, oviposition behaviour

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Authors: Shaine Mehta, Neelam Parmar, Patrick White, Mark Ashworth

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Patients with a history of substance have a high prevalence of comorbidities, including asthma and chronic obstructive pulmonary disease (COPD). Mortality rates are higher than that of the general population and the link to respiratory disease is reported. Randomised controlled trials (RCTs) support opioid substitution therapy as an effective means for harm reduction. However, whilst a high proportion of patients receiving opioid substitution therapy are smokers, to the author’s best knowledge there have been no studies of respiratory disease and smoking intensity in these patients. A cross sectional prevalence study was conducted using an anonymised patient-level database in primary care, Lambeth DataNet (LDN). We included patients aged 18 years and over who had records of ever having been prescribed methadone in primary care. Patients under 18 years old or prescribed buprenorphine (because of uncertainty about the prescribing indication) were excluded. Demographic, smoking, alcohol and asthma and COPD coding data were extracted. Differences between methadone and non-methadone users were explored with multivariable analysis. LDN contained data on 321, 395 patients ≥ 18 years; 676 (0.16%) had a record of methadone prescription. Patients prescribed methadone were more likely to be male (70.7% vs. 50.4%), older (48.9yrs vs. 41.5yrs) and less likely to be from an ethnic minority group (South Asian 2.1% vs. 7.8%; Black African 8.9% vs. 21.4%). Almost all those prescribed methadone were smokers or ex-smokers (97.3% vs. 40.9%); more were non-alcohol drinkers (41.3% vs. 24.3%). We found a high prevalence of COPD (12.4% vs 1.4%) and asthma (14.2% vs 4.4%). Smoking intensity data shows a high prevalence of ≥ 20 cigarettes per day (21.5% vs. 13.1%). Risk of COPD, adjusted for age, gender, ethnicity and deprivation, was raised in smokers: odds ratio 14.81 (95%CI 11.26, 19.47), and in the methadone group: OR 7.51 (95%CI: 5.78, 9.77). Furthermore, after adjustment for smoking intensity (number of cigarettes/day), the risk was raised in methadone group: OR 4.77 (95%CI: 3.13, 7.28). High burden of respiratory disease compounded by the high rates of smoking is a public health concern. This supports an integrated approach to health in patients treated for opiate dependence, with access to smoking cessation support. Further work may evaluate the current structure and commissioning of substance misuse services, including smoking cessation. Regression modelling highlights that methadone as a ‘risk factor’ was independently associated with COPD prevalence, even after adjustment for smoking intensity. This merits further exploration, as the association may be related to unexplored aspects of smoking (such as the number of years smoked) or may be related to other related exposures, such as smoking heroin or crack cocaine.

Keywords: methadone, respiratory disease, smoking cessation, substance misuse

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