Search results for: computer networks

Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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Authors: Jennifer Reese, Josh Biber, Howard Weeks, Rachel Hess

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Aim: The Edinburgh Postnatal Depression Screen (EPDS) is a mental health screening for pregnant women that has been widely used over the last 30 years. This screen is typically given in clinic on paper to patients throughout pregnancy and postpartum. The screen helps identify patients who may be at risk for pregnancy related depression or postpartum depression. In early 2016, University of Utah Health implemented an electronic version of the EPDS as well as the PROMIS Depression v1.0 instrument for all pregnant and postpartum patients. We asked patients both instruments to understand coverage of patients identified as at risk for each instrument. Methods: The EPDS is currently administered as part of our PRO template for pregnant and postpartum women. We also administer the PROMIS Depression as part of a standard PRO assessment to all patients. Patients are asked to complete an assessment no more often than every eight weeks. PRO assessments are either completed at home or in clinic with a tablet computer. Patients with a PROMIS score of ≥ 65 or a EPDS score of ≥ 10 were identified as at risk for depression Results: From April 2016 to April 2017, 1,330 unique patients were screened at University of Utah Health in OBGYN clinics with both the EPDS and PROMIS depression instrument on the same day. There were 28 (2.1%) patients were identified as at risk for depression using the PROMIS depression screen, while 262 (19.7%) patients were identified as at risk for postpartum depression using the EPDS screen. Overall, 27 (2%) patients were identified as at risk on both instruments. Conclusion: The EPDS identified a higher percent (19.7%) of patients at risk for depression when compared to the PROMIS depression (2.1%). Ninety-six percent of patients who screened positive on the PROMIS depression screen also screened positive on the EPDS screen. Mental health is an important component to a patient’s overall wellbeing. We want to ensure all patients, particularly pregnant or post-partum women, receive screening and treatment when necessary. A combination of screenings may be necessary to provide the overall best care for patients and to identify the highest percentage of patients at risk.

Keywords: patient reported outcomes, mental health, maternal, depression

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Authors: Marlene Yu Lilin Wätzold, Wisnu Harto Adiwijoyo, Meike Wollni

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Land-use conversion from tropical forests to cash crop production in the form of monocultures has drastic consequences for biodiversity. Meanwhile, high dependence on cash crop production is often associated with a decrease in other food crop production, thereby affecting household dietary diversity. Additionally, deforestation rates have been found to reduce households’ dietary diversity, as forests often offer various food sources. Agroforestry systems are seen as a potential solution to improve local biodiversity as well as provide a range of provisioning ecosystem services, such as timber and other food crops. While a number of studies have analyzed the effects of agroforestry on biodiversity, as well as household livelihood indicators, little is understood between potential trade-offs or synergies between the two. This interdisciplinary study aims to fill this gap by assessing cacao agroforestry’s role in enhancing local bird diversity, as well as farm household dietary diversity. Additionally, we will take a landscape perspective and investigate in what ways the landscape composition, such as the proximity to forests and forest patches, are able to contribute to the local bird diversity, as well as households’ dietary diversity. Our study will take place in two agro-ecological zones in Ghana, based on household surveys of 500 cacao farm households. Using a subsample of 120 cacao plots, we will assess the degree of shade tree diversity and density using drone flights and a computer vision tree detection algorithm. Bird density and diversity will be assessed using sound recordings that will be kept in the cacao plots for 24 hours. Landscape compositions will be assessed via remote sensing images. The results of our study are of high importance as they will allow us to understand the effects of agroforestry and landscape composition in improving simultaneous ecosystem services.

Keywords: agroforestry, biodiversity, landscape composition, nutrition

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Authors: Joel A. Gordon, Nazmiye Balta-Ozkan, Seyed Ali Nabavi

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Hydrogen-fueled technologies are rapidly advancing as a critical component of the low-carbon energy transition. In countries historically reliant on natural gas for home heating, such as the UK, hydrogen may prove fundamental for decarbonizing the residential sector, alongside other technologies such as heat pumps and district heat networks. While the UK government is set to take a long-term policy decision on the role of domestic hydrogen by 2026, there are considerable uncertainties regarding consumer preferences for ‘hydrogen homes’ (i.e., hydrogen-fueled appliances for space heating, hot water, and cooking. In comparison to other hydrogen energy technologies, such as road transport applications, to date, few studies have engaged with the social acceptance aspects of the domestic hydrogen transition, resulting in a stark knowledge deficit and pronounced risk to policymaking efforts. In response, this study aims to safeguard against undesirable policy measures by revealing the underlying relationships between the factors of domestic hydrogen acceptance and their respective dimensions: attitudinal, socio-political, community, market, and behavioral acceptance. The study employs an online survey (n=~2100) to gauge how different UK householders perceive the proposition of switching from natural gas to hydrogen-fueled appliances. In addition to accounting for housing characteristics (i.e., housing tenure, property type and number of occupants per dwelling) and several other socio-structural variables (e.g. age, gender, and location), the study explores the impacts of consumer heterogeneity on hydrogen acceptance by recruiting respondents from across five distinct groups: (1) fuel poor householders, (2) technology engaged householders, (3) environmentally engaged householders, (4) technology and environmentally engaged householders, and (5) a baseline group (n=~700) which filters out each of the smaller targeted groups (n=~350). This research design reflects the notion that supporting a socially fair and efficient transition to hydrogen will require parallel engagement with potential early adopters and demographic groups impacted by fuel poverty while also accounting strongly for public attitudes towards net zero. Employing a second-order multigroup confirmatory factor analysis (CFA) in Mplus, the proposed hydrogen acceptance model is tested to fit the data through a partial least squares (PLS) approach. In addition to testing differences between and within groups, the findings provide policymakers with critical insights regarding the significance of knowledge and awareness, safety perceptions, perceived community impacts, cost factors, and trust in key actors and stakeholders as potential explanatory factors of hydrogen acceptance. Preliminary results suggest that knowledge and awareness of hydrogen are positively associated with support for domestic hydrogen at the household, community, and national levels. However, with the exception of technology and/or environmentally engaged citizens, much of the population remains unfamiliar with hydrogen and somewhat skeptical of its application in homes. Knowledge and awareness present as critical to facilitating positive safety perceptions, alongside higher levels of trust and more favorable expectations for community benefits, appliance performance, and potential cost savings. Based on these preliminary findings, policymakers should be put on red alert about diffusing hydrogen into the public consciousness in alignment with energy security, fuel poverty, and net-zero agendas.

Keywords: hydrogen homes, social acceptance, consumer heterogeneity, heat decarbonization

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Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

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Authors: Dennis Schmickle

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Introductory statement: Augmented reality (AR) can be used to breathe life into traditional graphic design media, such as posters, book covers, and album art. AR superimposes a unique image/video on a user’s view of the real world, which makes it more immersive and realistic than traditional 2D media. This study developed a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. The results of this study suggest that AR can be an effective tool for teaching graphic design. Abstract: Traditional graphic design media, such as posters, book covers, and album art, could be considered to be “old media.” However, augmented reality (AR) can breathe life into these formats by making them more interactive and engaging for students and audiences alike. AR is a technology that superimposes a computer-generated image on a user’s view of the real world. This allows users to interact with digital content in a way that is more immersive and interactive than traditional 2D media. AR is becoming increasingly popular, as more and more people have access to smartphones and other devices that can support AR experiences. This study is comprised of a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. In these projects, students learn to create traditional design objects, such as posters, book covers, and album art. However, they are also required to create an animated version of their design and to use AR software to create an AR experience with which viewers can interact. The results of this study suggest that AR can be an effective and exciting tool for teaching graphic design. The students who participated in the study were able to learn the fundamental principles of graphic design, and they also developed the skills they need to create effective AR content. This study has implications for the future of graphic design education. As AR becomes more popular, it is likely that it will become an increasingly important tool for teaching graphic design.

Keywords: graphic design, augmented reality, print media, new media, AR, old media

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Magdy I. A. Alshourbagi

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Background: The National Institute for Deafness and Communication Disorders defines idiopathic sudden sensorineural hearing loss as the idiopathic loss of hearing of at least 30 dB across 3 contiguous frequencies occurring within 3 days.The most common clinical presentation involves an individual experiencing a sudden unilateral hearing loss, tinnitus, a sensation of aural fullness and vertigo. The etiologies and pathologies of ISSNHL remain unclear. Several pathophysiological mechanisms have been described including: vascular occlusion, viral infections, labyrinthine membrane breaks, immune associated disease, abnormal cochlear stress response, trauma, abnormal tissue growth, toxins, ototoxic drugs and cochlear membrane damage. The rationale for the use of hyperbaric oxygen to treat ISSHL is supported by an understanding of the high metabolism and paucity of vascularity to the cochlea. The cochlea and the structures within it require a high oxygen supply. The direct vascular supply, particularly to the organ of Corti, is minimal. Tissue oxygenation to the structures within the cochlea occurs via oxygen diffusion from cochlear capillary networks into the perilymph and the cortilymph. . The perilymph is the primary oxygen source for these intracochlear structures. Unfortunately, perilymph oxygen tension is decreased significantly in patients with ISSHL. To achieve a consistent rise of perilymph oxygen content, the arterial-perilymphatic oxygen concentration difference must be extremely high. This can be restored with hyperbaric oxygen therapy. Subject and Methods: A 37 year old man was presented at the clinic with a five days history of muffled hearing and tinnitus of the right ear. Symptoms were sudden onset, with no associated pain, dizziness or otorrhea and no past history of hearing problems or medical illness. Family history was negative. Physical examination was normal. Otologic examination revealed normal tympanic membranes bilaterally, with no evidence of cerumen or middle ear effusion. Tuning fork examination showed positive Rinne test bilaterally but with lateralization of Weber test to the left side, indicating right ear sensorineural hearing loss. Audiometric analysis confirmed sensorineural hearing loss across all frequencies of about 70- dB in the right ear. Routine lab work were all within normal limits. Clinical diagnosis of idiopathic sudden sensorineural hearing loss of the right ear was made and the patient began a medical treatment (corticosteroid, vasodilator and HBO therapy). The recommended treatment profile consists of 100% O2 at 2.5 atmospheres absolute for 60 minutes daily (six days per week) for 40 treatments .The optimal number of HBOT treatments will vary, depending on the severity and duration of symptomatology and the response to treatment. Results: As HBOT is not yet a standard for idiopathic sudden sensorineural hearing loss, it was introduced to this patient as an adjuvant therapy. The HBOT program was scheduled for 40 sessions, we used a 12-seat multi place chamber for the HBOT, which was started at day seven after the hearing loss onset. After the tenth session of HBOT, improvement of both hearing (by audiogram) and tinnitus was obtained in the affected ear (right). Conclusions: In conclusion, HBOT may be used for idiopathic sudden sensorineural hearing loss as an adjuvant therapy. It may promote oxygenation to the inner ear apparatus and revive hearing ability. Patients who fail to respond to oral and intratympanic steroids may benefit from this treatment. Further investigation is warranted, including animal studies to understand the molecular and histopathological aspects of HBOT and randomized control clinical studies.

Keywords: idiopathic sudden sensorineural hearing loss (issnhl), hyperbaric oxygen therapy (hbot), the decibel (db), oxygen (o2)

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Authors: Mark Andrew

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Geopolitical tensions are at a thirty-year high, and the pace of technological innovation is driving asymmetry in force capabilities between nation states and between non-state actors. Technology futures are a vital component of defence capability growth, and investments in technology futures need to be informed by accurate and reliable forecasts of the options for ‘systems of systems’ innovation, development, and deployment. This paper describes a method for forecasting technology futures developed through an analysis of four key systems’ development stages, namely: technology domain categorisation, scanning results examining novel systems’ signals and signs, potential system-of systems’ implications in warfare theatres, and political ramifications in terms of funding and development priorities. The method has been applied to several technology domains, including physical systems (e.g., nano weapons, loitering munitions, inflight charging, and hypersonic missiles), biological systems (e.g., molecular virus weaponry, genetic engineering, brain-computer interfaces, and trans-human augmentation), and information systems (e.g., sensor technologies supporting situation awareness, cyber-driven social attacks, and goal-specification challenges to proliferation and alliance testing). Although the current application of the method has been team-centred using paper-based rapid prototyping and iteration, the application of autonomous language models (such as GPT-3) is anticipated as a next-stage operating platform. The importance of forecasting accuracy and reliability is considered a vital element in guiding technology development to afford stronger contingencies as ideological changes are forecast to expand threats to ecology and earth systems, possibly eclipsing the traditional vulnerabilities of nation states. The early results from the method will be subjected to ground truthing using longitudinal investigation.

Keywords: forecasting, technology futures, uncertainty, complexity

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Authors: Vishal V. R. Nandigana, Mohammad Heiranian, Narayana R. Aluru

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Graphene material has found tremendous applications in water desalination, DNA sequencing and energy storage. Multiple nanopores are etched to create opening for water desalination and energy storage applications. The nanopores created are of the order of 3-5 nm allowing multiple ions to transport through the pore. In this paper, we present for the first time, molecular dynamics study of single ion transport, where only one ion passes through the graphene nanopore. The diameter of the graphene nanopore is of the same order as the hydration layers formed around each ion. Analogous to single electron transport resulting from ionic transport is observed for the first time. The current-voltage characteristics of such a device are similar to single electron transport in quantum dots. The current is blocked until a critical voltage, as the ions are trapped inside a hydration shell. The trapped ions have a high energy barrier compared to the applied input electrical voltage, preventing the ion to break free from the hydration shell. This region is called “Coulomb blockade region”. In this region, we observe zero transport of ions inside the nanopore. However, when the electrical voltage is beyond the critical voltage, the ion has sufficient energy to break free from the energy barrier created by the hydration shell to enter into the pore. Thus, the input voltage can control the transport of the ion inside the nanopore. The device therefore acts as a binary storage unit, storing 0 when no ion passes through the pore and storing 1 when a single ion passes through the pore. We therefore postulate that the device can be used for fluidic computing applications in chemistry and biology, mimicking a computer. Furthermore, the trapped ion stores a finite charge in the Coulomb blockade region; hence the device also acts a super capacitor.

Keywords: graphene nanomembrane, single ion transport, Coulomb blockade, nanofluidics

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Khaled Barkaoui

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Research on second-language (L2) learning tends to focus on comparing students with different levels of proficiency at one point in time. However, to understand L2 development, we need more longitudinal research. In this study, we adopt a longitudinal approach to examine changes in three indicators of L2 ability, complexity, accuracy, and fluency (CAF), as reflected in the writing of L2 learners when writing on different tasks before and after a period L2 instruction. Each of 85 Chinese learners of English at three levels of English language proficiency responded to two writing tasks (independent and integrated) before and after nine months of English-language study in China. Each essay (N= 276) was analyzed in terms of numerous CAF indices using both computer coding and human rating: number of words written, number of errors per 100 words, ratings of error severity, global syntactic complexity (MLS), complexity by coordination (T/S), complexity by subordination (C/T), clausal complexity (MLC), phrasal complexity (NP density), syntactic variety, lexical density, lexical variation, lexical sophistication, and lexical bundles. Results were then compared statistically across tasks, L2 proficiency levels, and time. Overall, task type had significant effects on fluency and some syntactic complexity indices (complexity by coordination, structural variety, clausal complexity, phrase complexity) and lexical density, sophistication, and bundles, but not accuracy. L2 proficiency had significant effects on fluency, accuracy, and lexical variation, but not syntactic complexity. Finally, fluency, frequency of errors, but not accuracy ratings, syntactic complexity indices (clausal complexity, global complexity, complexity by subordination, phrase complexity, structural variety) and lexical complexity (lexical density, variation, and sophistication) exhibited significant changes after instruction, particularly for the independent task. We discuss the findings and their implications for assessment, instruction, and research on CAF in the context of L2 writing.

Keywords: second language writing, Fluency, accuracy, complexity, longitudinal

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Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

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E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

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Authors: Japinder Wadhawan, Pradeep Rajan, Alok K. Saran, Navdeep S. Sidhu, Daanvir K. Dhir

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Currently, research focus in the development of agricultural equipment and tractor parts in India is innovation and use of alternate materials like austempered ductile iron (ADI). Three-point linkage mechanism of the tractor is susceptible to unpredictable load conditions in the field, and one of the critical components vulnerable to failure is lift arm. Conventionally, lift arm is manufactured either by forging or casting (SG Iron) and main objective of the present work is to reduce the failure occurrences in the lift arm, which is achieved by changing the manufacturing material, i.e ADI, without changing existing design. Effect of four pertinent variables of manufacturing ADI, viz. austenitizing temperature, austenitizing time, austempering temperature, austempering time, was investigated using Taguchi method for design of experiments. To analyze the effect of parameters on the mechanical properties, mean average and signal-to-noise (S/N) ratio was calculated based on the design of experiments with L9 orthogonal array and the linear graph. The best combination for achieving the desired mechanical properties of lift arm is austenitization at 860°C for 90 minutes and austempering at 350°C for 60 minutes. Results showed that the developed component is having 925 MPA tensile strength, 7.8 per cent elongation and 120 joules toughness making it more suitable material for lift arm manufacturing. The confirmatory experiment has been performed and found a good agreement between predicted and experimental value. Also, the CAD model of the existing design was developed in computer aided design software, and structural loading calculations were performed by a commercial finite element analysis package. An optimized shape of the lift arm has also been proposed resulting in light weight and cheaper product than the existing design, which can withstand the same loading conditions effectively.

Keywords: austempered ductile iron, design of experiment, finite element analysis, lift arm

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Authors: A. Raj Kumar, A. Okunseinde, P. Raghavan, V. Kapila

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Stroke is the leading cause of adult disability worldwide. With recent advances in immediate post-stroke care, there is an increasing number of young stroke survivors, under the age of 65 years. While most stroke survivors will regain the ability to walk, they often experience long-term arm and hand motor impairments. Long term upper limb rehabilitation is needed to restore movement and function, and prevent deterioration from complications such as learned non-use and learned bad-use. We have developed a novel virtual coach, a wearable instrumented rehabilitation jacket, to motivate individuals to participate in long-term skill re-learning, that can be personalized to their impairment profile. The jacket can estimate the movements of an individual’s arms using embedded off-the-shelf sensors (e.g., 9-DOF IMU for inertial measurements, flex-sensors for measuring angular orientation of fingers) and a Bluetooth Low Energy (BLE) powered microcontroller (e.g., RFduino) to non-intrusively extract data. The 9-DOF IMU sensors contain 3-axis accelerometer, 3-axis gyroscope, and 3-axis magnetometer to compute the quaternions, which are transmitted to a computer to compute the Euler angles and estimate the angular orientation of the arms. The data are used in a gaming environment to provide visual, and/or haptic feedback for goal-based, augmented-reality training to facilitate re-learning in a cost-effective, evidence-based manner. The full paper will elaborate the technical aspects of communication, interactive gaming environment, and physical aspects of electronics necessary to achieve our stated goal. Moreover, the paper will suggest methods to utilize the proposed system as a cheaper, portable, and versatile system vis-à-vis existing instrumentation to facilitate post-stroke personalized arm rehabilitation.

Keywords: feedback, gaming, Euler angles, rehabilitation, augmented reality

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Authors: M. Towhidur Rahman, Nasim Zaman Piyas, M. Sadiqul Baree, Shahnewaz Ahmed

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The design of high-speed craft has recently become one of the most active areas of naval architecture. Speed increase makes these vehicles more efficient and useful for military, economic or leisure purpose. The planing hull is designed specifically to achieve relatively high speed on the surface of the water. Speed on the water surface is closely related to the size of the vessel and the installed power. The Savitsky method was first presented in 1964 for application to non-monohedric hulls and for application to stepped hulls. This method is well known as a reliable comparative to CFD analysis of hull resistance. A computer program based on Savitsky’s method has been developed using MATLAB. The power of high-speed vessels has been computed in this research. At first, the program reads some principal parameters such as displacement, LCG, Speed, Deadrise angle, inclination of thrust line with respect to keel line etc. and calculates the resistance of the hull using empirical planning equations of Savitsky. However, some functions used in the empirical equations are available only in the graphical form, which is not suitable for the automatic computation. We use digital plotting system to extract data from nomogram. As a result, value of wetted length-beam ratio and trim angle can be determined directly from the input of initial variables, which makes the power calculation automated without manually plotting of secondary variables such as p/b and other coefficients and the regression equations of those functions are derived by using data from different charts. Finally, the trim angle, mean wetted length-beam ratio, frictional coefficient, resistance, and power are computed and compared with the results of Savitsky and good agreement has been observed.

Keywords: nomogram, planing hull, principal parameters, regression

Procedia PDF Downloads 392

Authors: Julius Steinkopf, Eric Rost, Aike Hessel, Sonia Lippke

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Objective: This study examined possible determinants of return to work (RTW) in individuals who participated in a medical rehabilitation program longitudinally over a time period of six months. Design/methodology/approach: N=1,044 rehabilitants were included in the baseline measurement in terms of completing a questionnaire during their medical rehabilitation. About 30% (n=350) have remained in the study in terms of participating in computer-assisted telephone interviewing (CATI) six months later. Frequency analyses and Regression analyses were run. Findings: About 70% of the rehabilitants returned to work six months after rehabilitation. Regression analyses revealed that the RTW rates were significantly predicted by gender (OR=0.12, men were more likely to return), perceived social support (OR=3.01) and current physical functioning (OR=1.25). Furthermore RTW motives, like expected monetary rewards (OR=25.2) and feelings of being needed (OR=0.18) same as motives for not returning to work (nRTW), like the wish to stop working in order to spend time with the spouse (OR=0.13) or a lack of enjoyment of work (OR=3.81), significantly predicted return to work rates. Life satisfaction, self-efficacy beliefs, mental health, current income, educational background or age did not significantly increase explained variance (all ps > .05). Practical implications: Taking theses predictors into account provides options to increase the effectiveness of interventions aiming at increasing RTW: Medical rehabilitations should not only aim at improving the physical functioning but also to enhance beneficial motives and social support as well as support women specifically in order to improve the effectiveness of medical rehabilitation and public health interventions. Originality/value: Illness-caused work absences are related to high financial costs and individual burden. Despite of the public health and societal implications, this is one of the very few studies investigating systematically fitness and health for the return to work.

Keywords: gender, fitness, health, physical functioning

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Authors: Yasir Hassan Satti Mohammed

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The wheat cleaner was designed, manufactured, and tested in the workshop of the department of agricultural engineering, faculty of agricultural sciences, university of Dongola, the northern state of Sudan, for the purpose of enhancing productivity for small-scale-farmers who used to plant their saved wheat seeds every season with all risk of weed infestation and low viability. A one-season field experiment was then conducted according to the Randomized Complete Block Design (RCBD) experimental design in the demonstration farm of Dongola research station using clean seeds and unclean seeds of a local wheat variety (Imam); two different planting methods were also adopted in the experiment. One is the traditional seed drilling within the recommended seed rate (50 kg.feddan⁻¹), whereas the other was the precision seeding method using half of the recommended seed rate (25 kg.feddan⁻¹). The effect of seed type and planting method on field parameters were investigated, and the data was then analyzed using a computer application SAS system version 9.3. The results revealed significant (P ≥ 0.05) and highly significant (P ≥ 0.01) differences between treatments. The precision seeding method with clean seeds increased the number of kernels per spike (KS), tillers per plant (TPP), one thousand kernels mass (TKM), the biomass of wheat (BWT), and total yield (TOY), whereas weeds per area (WSM), the biomass of weeds (BWD) and weight of weed seeds were apparently decreased compared to seed drilling with unclean seed. Wheat seed cleaner could be of great benefit for small-scale wheat farmers in Sudan who cannot afford the cleaned seeds commercially provided by the local government.

Keywords: wheat cleaner, precision seeding, seed drilling method, small-scale farmers

Procedia PDF Downloads 86

Authors: Y. Jin, N. Zhang, X. Luo, W. Zhang

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China with annual increasing 0.5-0.6 billion squares city residence has brought in enormous energy consumption by HVAC facilities and other appliances. In this regard, governments and researchers are encouraging renewable energy like solar energy, geothermal energy using in houses. However, high cost of equipment and low energy conversion result in a very low acceptable to residents. So what’s the equilibrium point of eco-feedback to reach economic benefit and thermal comfort? That is the main question should be answered. In this paper, the objective is an on-site solar PV and heater house, which has been evaluated as a low energy building. Since HVAC system is considered as main energy consumption equipment, the residence with 24-hour monitoring system set to measure temperature, wind velocity and energy in-out value with no HVAC system for one month of summer and winter. Thermal comfort time period will be analyzed and confirmed; then the air-conditioner will be started within thermal discomfort time for the following one summer and winter month. The same data will be recorded to calculate the average energy consumption monthly for a purpose of whole day thermal comfort. Finally, two analysis work will be done: 1) Original building thermal simulation by computer at design stage with actual measured temperature after construction will be contrastive analyzed; 2) The cost of renewable energy facilities and power consumption converted to cost efficient rate to assess the feasibility of renewable energy input for residence. The results of the experiment showed that a certain deviation exists between actual measured data and simulated one for human thermal comfort, especially in summer period. Moreover, the cost-effectiveness is high for a house in targeting city Guilin now with at least 11 years of cost-covering. The conclusion proves that an eco-feedback of a low energy residence is never only consideration of its energy net value, but also the cost efficiency that is the critical factor to push renewable energy acceptable by the public.

Keywords: cost efficiency, eco-feedback, low energy residence, thermal comfort

Procedia PDF Downloads 245

Authors: Alexandra-Monica Toma

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Internet memes are an element of computer mediated communication and an important part of online culture that combines text and image in order to generate meaning. This term coined by Richard Dawkings refers to more than a mere way to briefly communicate ideas or emotions, thus naming a complex and an intensely perpetuated phenomenon in the virtual environment. This paper approaches memes as a cultural artefact and a virtual trope that mirrors societal concerns and issues, and analyses the pragmatics of their use. Memes have to be analysed in series, usually relating to some image macros, which is proof of the interplay between imitation and creativity in the memes’ writing process. We believe that their potential to become viral relates to three key elements: adaptation to context, reference to a successful meme series, and humour (jokes, irony, sarcasm), with various pragmatic functions. The study also uses the concept of multimodality and stresses how the memes’ text interacts with the image, discussing three types of relations: symmetry, amplification, and contradiction. Moreover, the paper proves that memes could be employed as speech acts with illocutionary force, when the interaction between text and image is enriched through the connection to a specific situation. The features mentioned above are analysed in a corpus that consists of memes related to the COVID-19 pandemic. This corpus shows them to be highly adaptable to context, which helps build the feeling of connection and belonging in an otherwise tremendously fragmented world. Some of them are created based on well-known image macros, and their humour results from an intricate dialogue between texts and contexts. Memes created in relation to the COVID-19 pandemic can be considered speech acts and are often used as such, as proven in the paper. Consequently, this paper tackles the key features of memes, makes a thorough analysis of the memes sociocultural, linguistic, and situational context, and emphasizes their intertextuality, with special accent on their illocutionary potential.

Keywords: context, memes, multimodality, speech acts

Procedia PDF Downloads 189

Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

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The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

Procedia PDF Downloads 86

Authors: Harrys Purnama, Wardatul Jannah, Rizkia Nita Hawari

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In the development of the times, there are many materials used to plan a building structure. Steel became one of the most widely used materials in building construction that works as the main structure. Steel Castellated Beam is a type of innovation in the use of steel in building construction. Steel Castellated Beam is a beam that used for long span construction (more than 10 meters). The Castellated Beam is two steel profiles that unified into one to get the appropriate profile height (more than 10 meters). The profile is perforated to minimize the profile's weight, increase the rate, save costs, and have architectural value. The perforations shape in the Castellated Beam can be circular, elliptical, hexagonal, and rectangular. The Castellated beam has a height (h) almost 50% higher than the initial profile thus increasing the axial bending value and the moment of inertia (Iₓ). In this analysis, there are 3 specimens were used with 12.1 meters span of Castellated Beam as the sample with varied perforation, such us round, hexagon, and octagon. Castellated Beam testing system is done with computer-based applications that named Staad Pro V8i. It is to provide a central load in the middle of the steel beam span. It aims to determine the effect of perforation on bending behavior on the steel Castellated Beam by applying some form of perforations on the steel Castellated Beam with test specimen WF 200.100.5.5.8. From the analysis, results found the behavior of steel Castellated Beam when receiving such central load. From the results of the analysis will be obtained the amount of load, shear, strain, and Δ (deflection). The result of analysis by using Staad Pro V8i shows that with the different form of perforations on the profile of Castellated steel, then we get the different tendency of inertia moment. From the analysis, results obtained the moment of the greatest inertia can increase the stiffness of Castellated steel. By increasing the stiffness of the steel Castellated Beam the deflection will be smaller, so it can withstand the moment and a large strength. The results of the analysis show that the most effective and efficient perforations are the steel beam with a hexagon perforation shape.

Keywords: Castellated Beam, the moment of inertia, stress, deflection, bending test

Procedia PDF Downloads 159

Authors: Agboka Komi Mensah, John Odindi, Elfatih M. Abdel-Rahman, Onisimo Mutanga, Henri Ez Tonnang

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Ecosystems are networks of organisms and populations that form a community of various species interacting within their habitats. Such habitats are defined by abiotic and biotic conditions that establish the initial limits to a population's growth, development, and reproduction. The habitat’s conditions explain the context in which species interact to access resources such as food, water, space, shelter, and mates, allowing for feeding, dispersal, and reproduction. Dispersal is an essential life-history strategy that affects gene flow, resource competition, population dynamics, and species distributions. Despite the importance of dispersal in population dynamics and survival, understanding the mechanism underpinning the dispersal of organisms remains challenging. For instance, when an organism moves into an ecosystem for survival and resource competition, its progression is highly influenced by extrinsic factors such as its physiological state, climatic variables and ability to evade predation. Therefore, greater spatial detail is necessary to understand organism dispersal dynamics. Understanding organisms dispersal can be addressed using empirical and mechanistic modelling approaches, with the adopted approach depending on the study's purpose Cellular automata (CA) is an example of these approaches that have been successfully used in biological studies to analyze the dispersal of living organisms. Cellular automata can be briefly described as occupied cells by an individual that evolves based on proper decisions based on a set of neighbours' rules. However, in the ambit of modelling individual organisms dispersal at the landscape scale, we lack user friendly tools that do not require expertise in mathematical models and computing ability; such as a visual analytics framework for tracking and forecasting the dispersal behaviour of organisms. The term "visual analytics" (VA) describes a semiautomated approach to electronic data processing that is guided by users who can interact with data via an interface. Essentially, VA converts large amounts of quantitative or qualitative data into graphical formats that can be customized based on the operator's needs. Additionally, this approach can be used to enhance the ability of users from various backgrounds to understand data, communicate results, and disseminate information across a wide range of disciplines. To support effective analysis of the dispersal of organisms at the landscape scale, we therefore designed Pydisp which is a free visual data analytics tool for spatiotemporal dispersal modeling built in Python. Its user interface allows users to perform a quick and interactive spatiotemporal analysis of species dispersal using bioecological and climatic data. Pydisp enables reuse and upgrade through the use of simple principles such as Fuzzy cellular automata algorithms. The potential of dispersal modeling is demonstrated in a case study by predicting the dispersal of Fopius arisanus (Sonan), endoparasitoids to control Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) in Kenya. The results obtained from our example clearly illustrate the parasitoid's dispersal process at the landscape level and confirm that dynamic processes in an agroecosystem are better understood when designed using mechanistic modelling approaches. Furthermore, as demonstrated in the example, the built software is highly effective in portraying the dispersal of organisms despite the unavailability of detailed data on the species dispersal mechanisms.

Keywords: cellular automata, fuzzy logic, landscape, spatiotemporal

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Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

Procedia PDF Downloads 358

Authors: Loretta Ichim, Dan Popescu, Grigore Stamatescu

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The paper reports the collaboration between a top university from Romania and three companies for the implementation of a research project in a multidisciplinary domain, focusing on the impact and benefits both for the education and industry. The joint activities were developed under the Space Technology and Advanced Research Program (STAR), funded by the Romanian Space Agency (ROSA) for a university-industry partnership. The context was defined by linking the European Space Agency optional programs, with the development and promotion national research, with the educational and industrial capabilities in the aeronautics, security and related areas by increasing the collaboration between academic and industrial entities as well as by realizing high-level scientific production. The project name is Multisensory Robotic System for Aerial Monitoring of Critical Infrastructure Systems (MUROS), which was carried 2013-2016. The project included the University POLITEHNICA of Bucharest (coordinator) and three companies, which manufacture and market unmanned aerial systems. The project had as main objective the development of an integrated system for combined ground wireless sensor networks and UAV monitoring in various application scenarios for critical infrastructure surveillance. This included specific activities related to fundamental and applied research, technology transfer, prototype implementation and result dissemination. The core area of the contributions laid in distributed data processing and communication mechanisms, advanced image processing and embedded system development. Special focus is given by the paper to analyzing the impact the project implementation in the educational process, directly or indirectly, through the faculty members (professors and students) involved in the research team. Three main directions are discussed: a) enabling students to carry out internships at the partner companies, b) handling advanced topics and industry requirements at the master's level, c) experiments and concept validation for doctoral thesis. The impact of the research work (as the educational component) developed by the faculty members on the increasing performances of the companies’ products is highlighted. The collaboration between university and companies was well balanced both for contributions and results. The paper also presents the outcomes of the project which reveals the efficient collaboration between high education and industry: master thesis, doctoral thesis, conference papers, journal papers, technical documentation for technology transfer, prototype, and patent. The experience can provide useful practices of blending research and education within an academia-industry cooperation framework while the lessons learned represent a starting point in debating the new role of advanced research and development performing companies in association with higher education. This partnership, promoted at UE level, has a broad impact beyond the constrained scope of a single project and can develop into long-lasting collaboration while benefiting all stakeholders: students, universities and the surrounding knowledge-based economic and industrial ecosystem. Due to the exchange of experiences between the university (UPB) and the manufacturing company (AFT Design), a new project, SIMUL, under the Bridge Grant Program (Romanian executive agency UEFISCDI) was started (2016 – 2017). This project will continue the educational research for innovation on master and doctoral studies in MUROS thematic (collaborative multi-UAV application for flood detection).

Keywords: education process, multisensory robotic system, research and innovation project, technology transfer, university-industry partnership

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Kyle Yatich Terik, Collins Oduor

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The current healthcare system has made healthcare more accessible and efficient by the use of information technology through the implementation of computer algorithms that generate menus based on the diagnosis. While many systems just like these have been created over the years, their main objective is to help healthy individuals calculate their calorie intake and assist them by providing food selections based on a pre-specified calorie. That application has been proven to be useful in some ways, and they are not suitable for monitoring, planning, and managing hospital patients, especially that critical condition their dietary needs. The system also addresses a number of objectives, such as; the main objective is to be able to design, develop and implement an efficient, user-friendly as well as and interactive dietary management system. The specific design development objectives include developing a system that will facilitate a monitoring feature for users using graphs, developing a system that will provide system-generated reports to the users, dietitians, and system admins, design a system that allows users to measure their BMI (Body Mass Index), the system will also provide food template feature that will guide the user on a balanced diet plan. In order to develop the system, further research was carried out in Kenya, Nairobi County, using online questionnaires being the preferred research design approach. From the 44 respondents, one could create discussions such as the major challenges encountered from the manual dietary system, which include no easily accessible information of the calorie intake for food products, expensive to physically visit a dietitian to create a tailored diet plan. Conclusively, the system has the potential of improving the quality of life of people as a whole by providing a standard for healthy living and allowing individuals to have readily available knowledge through food templates that will guide people and allow users to create their own diet plans that consist of a balanced diet.

Keywords: DMS, dietitian, patient, administrator

Procedia PDF Downloads 147

Authors: Ozen Asut, Gulifeiya Abuduxike, Imge Begendi, Mustafa O. Canatan, Merve Colak, Gizem Ozturk, Lara Tasan, Ahmed Waraiet, Songul A. Vaizoglu, Sanda Cali

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Obesity among children and adolescents is one of the critical public health problems worldwide. Internet addiction is one of the sedentary behaviors that cause obesity due to the excessive screen time and reduced physical activities. We aimed to examine the relationships between the screen time, internet addiction and other lifestyle behaviors with obesity among high school students in the Near East College in Nicosia, Northern Cyprus. A cross-sectional study conducted among 469 secondary school students, mean age 11.95 (SD, 0.81) years. A self-administrated questionnaire was applied to assess the screen time and lifestyle behaviors. The Turkish adopted version of short-form of internet addiction test was used to assess internet addiction problems. Height and weight were measured to calculate BMI and classified based on the BMI percentiles for sex and age. Descriptive analysis, Chi-Square test, and multivariate regression analysis were done. Of all, 17.2% of the participants were overweight and obese, and 18.1% had internet addictions, while 40.7% of them reported having screen time more than two hours. After adjusting the analysis for age and sex, eating snacks while watching television (OR, 3.04; 95% CI, 1.28-7.21), self- perceived body weight (OR, 24.9; 95% CI, 9.64-64.25) and having a play station in the room (OR, 4.6; 95% CI, 1.85 - 11.42) were significantly associated with obesity. Screen time (OR, 4.68; 95% CI, 2.61-8.38; p=0.000) and having a computer in bedroom (OR, 1.7; 95% CI, 1.01- 2.87; p=0.046) were significantly associated with internet addiction, whereas parent’s compliant regarding the lengthy technology use (OR, 0.23; 95% CI, 0.11-0.46; p=0.000) was found to be a protective factor against internet addiction. Prolonged screen time, internet addiction, sedentary lifestyles, and reduced physical and social activities are interrelated, multi-dimensional factors that lead to obesity among children and adolescents. A family - school-based integrated approach should be implemented to tackle obesity problems.

Keywords: adolescents, internet addiction, lifestyle, Northern Cyprus, obesity, screen time

Procedia PDF Downloads 131

Authors: Michelle V. Tomczak, Reyhaneh Bakhtiari, Aaron Granley, Anthony Singhal

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Objective: Cannabis and cocaine are associated with a range of mental and physical effects that can impair aspects of human behavior. Driving is a complex cognitive behavior that is an essential part of everyday life and can be broken down into many subcomponents, each of which can uniquely impact road safety. With the growing movement of jurisdictions to legalize cannabis, there is an increased focus on impairment and driving. The purpose of this study was to identify driving-related cognitive-performance deficits that are impacted by recreational drug use. Design and Methods: With the assistance of law enforcement agencies, we recruited over 300 participants under the influence of various drugs including cannabis and cocaine. These individuals performed a battery of computer-based tasks scientifically proven to be re-lated to on-road driving performance and designed to test response-speed, memory processes, perceptual-motor skills, and decision making. Data from a control group with healthy non-drug using adults was collected as well. Results: Compared to controls, the drug group showed def-icits in all tasks. The data also showed clear differences between the cannabis and cocaine groups where cannabis users were faster, and performed better on some aspects of the decision-making and perceptual-motor tasks. Memory performance was better in the cocaine group for simple tasks but not more complex tasks. Finally, the participants who consumed both drugs performed most similarly to the cannabis group. Conclusions: Our results show distinct and combined effects of cannabis and cocaine on human performance relating to driving. These dif-ferential effects are likely related to the unique effects of each drug on the human brain and how they distinctly contribute to mental states. Our results have important implications for road safety associated with driver impairment.

Keywords: driving, cognitive impairment, recreational drug use, cannabis and cocaine

Procedia PDF Downloads 113

Authors: Poonsook Thatchaopas, Nik Kamariah Nikmat, Nattakarn Eakuru

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Since 2003, the Thai Government has implemented several initiatives to encourage and incubate entrepreneurial skills and motivation among her citizens. One of the initiatives is the “One College One Product” business model or well known as ‘OCOP’, launched by the Vocational Education Commission to encourage partnership between college students to choose at least one product for business venture. In line with this mission, several business enterprises were established such as food products, restaurants, spa, Thai massage, minimart, computer maintenance, karaoke centre, internet café, mini theater etc. Currently, these business incubator projects can be observed at 404 vocational colleges and 21 incubation centres to encourage entrepreneurial small and medium enterprise (SME) development. However, the number of successful OCOP projects is still minimal. Out of the 404 individual OCOP projects at Vocational Colleges around Thailand, very few became successful. The objective of this paper is to identify the critical success factors needed to be a successful OCOP business entrepreneur. This study uses qualitative method by interviewing business partners of an OCOP business called Crispy Roti Krua Acheeva Brand (CRKAB). It is a snack food company that is developed at Pattani Vocational College in South Thailand. This project was initiated by three female entrepreneurs who were alumni student cum owners of the CRKAB. The finding shows that the main critical success factors are self-confidence, creativity or innovativeness, knowledge, skills and perseverance. Additionally, they reiterated that the keys to business success are product quality, perceived price, promotion, branding, new packaging to increase sales and continuous developments. The results implies for a student business SME to be successful, the company should have credible partners and effective marketing plan.

Keywords: student entrepreneurship, business incubator, food industry, qualitative, Thailand

Procedia PDF Downloads 382