Search results for: computer information systems

Authors: Claudia Trillo

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Regional innovation eco-ecosystems are composed of a variety of interconnected urban innovation eco-systems, mutually reinforcing each other and making the whole territorial system successful. Combining principles drawn from the new economic growth theory and from the socio-constructivist approach to the economic growth, with the new geography of innovation emerging from the networked nature of innovation districts, this paper explores the spatial configuration of urban innovation districts, with the aim of unveiling replicable spatial patterns and transferable portfolios of urban policies. While some authors suggest that cities should be considered ideal natural clusters, supporting cross-fertilization and innovation thanks to the physical setting they provide to the construction of collective knowledge, still a considerable distance persists between regional development strategies and urban policies. Moreover, while public and private policies supporting entrepreneurship normally consider innovation as the cornerstone of any action aimed at uplifting the competitiveness and economic success of a certain area, a growing body of literature suggests that innovation is non-neutral, hence, it should be constantly assessed against equity and social inclusion. This paper draws from a robust qualitative empirical dataset gathered through 4-years research conducted in Boston to provide readers with an evidence-based set of recommendations drawn from the lessons learned through the investigation of the chosen innovation districts in the Boston area. The evaluative framework used for assessing the overall performance of the chosen case studies stems from the Habitat III Sustainable Development Goals rationale. The concept of inclusive growth has been considered essential to assess the social innovation domain in each of the chosen cases. The key success factors for the development of the Boston innovation ecosystem can be generalized as follows: 1) a quadruple helix model embedded in the physical structure of the two cities (Boston and Cambridge), in which anchor Higher Education (HE) institutions continuously nurture the Entrepreneurial Environment. 2) an entrepreneurial approach emerging from the local governments, eliciting risk-taking and bottom-up civic participation in tackling key issues in the city. 3) a networking structure of some intermediary actors supporting entrepreneurial collaboration, cross-fertilization and co-creation, which collaborate at multiple-scales thus enabling positive spillovers from the stronger to the weaker contexts. 4) awareness of the socio-economic value of the built environment as enabler of cognitive networks allowing activation of the collective intelligence. 5) creation of civic-led spaces enabling grassroot collaboration and cooperation. Evidence shows that there is not a single magic recipe for the successful implementation of place-based and social innovation-driven strategies. On the contrary, the variety of place-grounded combinations of micro and macro initiatives, embedded in the social and spatial fine grain of places and encompassing a diversity of actors, can create the conditions enabling places to thrive and local economic activities to grow in a sustainable way.

Keywords: innovation-driven sustainable Eco-systems , place-based sustainable urban development, sustainable innovation districts, social innovation, urban policie

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Authors: Begona del Pino, Beatriz Prieto, Alberto Prieto

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Two opposite approaches to teaching can be considered: in-class learning (teacher-oriented) versus virtual learning (student-oriented). The most known example of the latter is Massive Online Open Courses (MOOCs). Both methodologies have pros and cons. Nowadays there is an increasing trend towards combining both of them. Blending learning is considered a valuable tool for improving learning since it combines student-centred interactive e-learning and face to face instruction. The aim of this contribution is to exchange and share the experience and research results of a blended-learning project that took place in the University of Granada (Spain). The research objective was to prove how combining didactic resources of a MOOC with in-class teaching, interacting directly with students, can substantially improve academic results, as well as student acceptance. The proposed methodology is based on the use of flipped learning technics applied to the subject ‘Fundamentals of Computer Science’ of the first course of two degrees: Telecommunications Engineering, and Industrial Electronics. In this proposal, students acquire the theoretical knowledges at home through a MOOC platform, where they watch video-lectures, do self-evaluation tests, and use other academic multimedia online resources. Afterwards, they have to attend to in-class teaching where they do other activities in order to interact with teachers and the rest of students (discussing of the videos, solving of doubts and practical exercises, etc.), trying to overcome the disadvantages of self-regulated learning. The results are obtained through the grades of the students and their assessment of the blended experience, based on an opinion survey conducted at the end of the course. The major findings of the study are the following: The percentage of students passing the subject has grown from 53% (average from 2011 to 2014 using traditional learning methodology) to 76% (average from 2015 to 2018 using blended methodology). The average grade has improved from 5.20±1.99 to 6.38±1.66. The results of the opinion survey indicate that most students preferred blended methodology to traditional approaches, and positively valued both courses. In fact, 69% of students felt ‘quite’ or ‘very’ satisfied with the classroom activities; 65% of students preferred the flipped classroom methodology to traditional in-class lectures, and finally, 79% said they were ‘quite’ or ‘very’ satisfied with the course in general. The main conclusions of the experience are the improvement in academic results, as well as the highly satisfactory assessments obtained in the opinion surveys. The results confirm the huge potential of combining MOOCs in formal undergraduate studies with on-campus learning activities. Nevertheless, the results in terms of students’ participation and follow-up have a wide margin for improvement. The method is highly demanding for both students and teachers. As a recommendation, students must perform the assigned tasks with perseverance, every week, in order to take advantage of the face-to-face classes. This perseverance is precisely what needs to be promoted among students because it clearly brings about an improvement in learning.

Keywords: blended learning, educational paradigm, flipped classroom, flipped learning technologies, lessons learned, massive online open course, MOOC, teacher roles through technology

Procedia PDF Downloads 171

Authors: C. Njoku Paul

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This paper deals with systems engineering applications design for offshore oil drilling production platform in the Nigerian Marine Environment. Engineering Design model of the distribution and accumulation of petroleum hydrocarbons discharged into marine environment production platform and sources of impact of an offshore is treated.

Keywords: design of offshore oil drilling production platform, marine, environment, petroleum hydrocarbons

Procedia PDF Downloads 529

Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Rajlakshmi Guha, Sajjad Ansari, Shazia Nasreen, Hirak Banerjee, Jiaul Paik

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Dyslexia is a neurocognitive disorder, affecting around fifteen percent of the Indian population. The symptoms include difficulty in reading alphabet, words, and sentences. This can be difficult at the phonemic or recognition level and may further affect lexical structures. Therapeutic intervention of dyslexic children post assessment is generally done by special educators and psychologists through one on one interaction. Considering the large number of children affected and the scarcity of experts, access to care is limited in India. Moreover, unavailability of resources and timely communication with caregivers add on to the problem of proper intervention. With the development of Educational Technology and its use in India, access to information and care has been improved in such a large and diverse country. In this context, this paper proposes an ICT enabled home-based intervention program for dyslexic children which would support the child, and provide an interactive interface between expert, parents, and students. The paper discusses the details of the database design and system layout of the program. Along with, it also highlights the development of different technical aids required to build out personalized android applications for the Indian dyslexic population. These technical aids include speech database creation for children, automatic speech recognition system, serious game development, and color coded fonts. The paper also emphasizes the games developed to assist the dyslexic child on cognitive training primarily for attention, working memory, and spatial reasoning. In addition, it talks about the specific elements of the interactive intervention tool that makes it effective for home based intervention of dyslexia.

Keywords: Android applications, cognitive training, dyslexia, intervention

Procedia PDF Downloads 282

Authors: Aboli Dhanavade, Shweta Bhimnath, Rutuja Jumale, Ajay Nadargi

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Security to any of our personal thing is our most basic need. It is not possible to directly apply that standard Human-computer—interaction approaches. Important usability goal for authentication system is to support users in selecting best passwords. Users often select text-passwords that are easy to remember, but they are more open for attackers to guess. The human brain is good in remembering pictures rather than textual characters. So the best alternative is being designed that is Graphical passwords. However, Graphical passwords are still immature. Conventional password schemes are also vulnerable to Shoulder-surfing attacks, many shoulder-surfing resistant graphical passwords schemes have been proposed. Next, we have analyzed the security and usability of the proposed scheme, and show the resistance of the proposed scheme to shoulder-surfing and different accidental logins.

Keywords: shoulder-surfing, security, authentication, text-passwords

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Authors: Precious Roselyn Obuobi

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Background: In Ghana, water-borne diseases remain a public health concern due to its impact. While marine pollution has been linked to outbreak of diseases especially in communities along the coast, associated risks such as oil spillage, marine debris, erosion, improper waste disposal and management practices persist. Objective: The study seeks to investigate sanitation practices that contribute to marine pollution in Prampram and the prevalence of selected water-borne diseases (diarrhea and typhoid fever). Method: This study used a descriptive cross-sectional design, employing the mix-method (qualitative and quantitative) approach. Twenty-two (22) participants were selected and semistructured questionnaire were administered to them. Additionally, interviews were conducted to collect more information. Further, an observation check-list was used to aid the data collection process. Secondary data comprising information on water-borne diseases in the district was acquired from the district health directorate to determine the prevalence of selected water-borne diseases in the community. Data Analysis: The qualitative data was analyzed using NVIVO® software by adapting the six steps thematic analysis by Braun and Clarke whiles STATA® version 16 was used to analyze the secondary data collected from the district health directorate. A descriptive statistic employed using mean, standard deviation, frequencies and proportions were used to summarize the results. Results: The results showed that open defecation and indiscriminate waste disposal were the main practices contributing to marine pollution in Prampram and its effect on public health. Conclusion: These findings have implications on public health and the environment, thus effort needs to be stepped up in educating the community on best sanitation practices.

Keywords: environment, sanitation, marine pollution, water-borne diseases

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Authors: Mehdi Boukri, Mohammed Naboussi Farsi, Mounir Naili, Omar Amellal, Mohamed Belazougui, Ahmed Mebarki, Nabila Guessoum, Brahim Mezazigh, Mounir Ait-Belkacem, Nacim Yousfi, Mohamed Bouaoud, Ikram Boukal, Aboubakr Fettar, Asma Souki

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The seismic risk to which the urban centres are more and more exposed became a world concern. A co-operation on an international scale is necessary for an exchange of information and experiments for the prevention and the installation of action plans in the countries prone to this phenomenon. For that, the 1990s was designated as 'International Decade for Natural Disaster Reduction (IDNDR)' by the United Nations, whose interest was to promote the capacity to resist the various natural, industrial and environmental disasters. Within this framework, it was launched in 1996, the RADIUS project (Risk Assessment Tools for Diagnosis of Urban Areas Against Seismic Disaster), whose the main objective is to mitigate seismic risk in developing countries, through the development of a simple and fast methodological and operational approach, allowing to evaluate the vulnerability as well as the socio-economic losses, by probable earthquake scenarios in the exposed urban areas. In this paper, we will present the adaptation and application of this methodology to the Algerian context for the seismic risk evaluation in urban areas potentially exposed to earthquakes. This application consists to perform an earthquake scenario in the urban centre of Constantine city, located at the North-East of Algeria, which will allow the building seismic damage estimation of this city. For that, an inventory of 30706 building units was carried out by the National Earthquake Engineering Research Centre (CGS). These buildings were digitized in a data base which comprises their technical information by using a Geographical Information system (GIS), and then they were classified according to the RADIUS methodology. The study area was subdivided into 228 meshes of 500m on side and Ten (10) sectors of which each one contains a group of meshes. The results of this earthquake scenario highlights that the ratio of likely damage is about 23%. This severe damage results from the high concentration of old buildings and unfavourable soil conditions. This simulation of the probable seismic damage of the building and the GIS damage maps generated provide a predictive evaluation of the damage which can occur by a potential earthquake near to Constantine city. These theoretical forecasts are important for decision makers in order to take the adequate preventive measures and to develop suitable strategies, prevention and emergency management plans to reduce these losses. They can also help to take the adequate emergency measures in the most impacted areas in the early hours and days after an earthquake occurrence.

Keywords: seismic risk, mitigation, RADIUS, urban areas, Algeria, earthquake scenario, Constantine

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Authors: Scholz Heiko, Kuhne Petra, Heckenberger Gerd

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Problems during the calving period (December to May) often result in a high body condition score (BCS) at this time. At the end of the grazing period (frequently after early weaning), however, an increase of BCS can often be observed under German conditions. In the last eight weeks before calving, the body condition should be reduced or at least not increased. Rations with a higher amount of crude fiber can be used (rations with straw or late mowed grass silage). Fermentative digestion of fiber is slow and incomplete; that’s why the fermentative process in the rumen can be reduced over a long feeding time. Viewed in this context, feed intake of suckler cows (8 weeks before calving) in different rations and fermentation in the rumen should be checked by taking rumen fluid. Eight suckler cows (Charolais) were feeding a Total Mixed Ration (TMR) in the last eight weeks before calving and grass silage after calving. By the addition of straw (30 % [TMR1] vs. 60 % [TMR2] of dry matter) was varied the amount of crude fiber in the TMR (grass silage, straw, mineral) before calving. After calving of the cow's grass, silage [GS] was fed ad libitum, and the last measurement of rumen fluid took place on the pasture [PS]. Rumen fluid, plasma, body weight, and backfat thickness were collected. Rumen fluid pH was assessed using an electronic pH meter. Volatile fatty acids (VFA), sedimentation, methylene-blue and amount of infusorians were measured. From these 4 parameters, an “index of rumen fermentation” [IRF] in the rumen was formed. Fixed effects of treatment (TMR1, TMR2, GS and PS) and a number of lactations (3-7 lactations) were analyzed by ANOVA using SPSS Version 25.0 (significant by p ≤ 5 %). Rumen fluid pH was significant influenced by variants (TMR 1 by 6.6; TMR 2 by 6.9; GS by 6.6 and PS by 6.9) but was not affected by other effects. The IRF showed disturbed fermentation in the rumen by feeding the TMR 1+2 with a high amount of crude fiber (Score: > 10.0 points) and a very good environment for fermentation during grazing the pasture (Score: 6.9 points). Furthermore, significant differences were found for VFA, methylene blue and the number of infusorians. The use of rations with the high amount of crude fiber from weaning to calving may cause deviations from undisturbed fermentation in the rumen and adversely affect the utilization of the feed in the rumen.

Keywords: suckler cow, feeding systems, crude fiber, digestibilty of organic matter

Procedia PDF Downloads 127

Authors: Michael Lekan-Kehinde, Abimbola Asojo, Bonnie Sanborn

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Good acoustic performance has been identified as one of the critical Indoor Environmental Quality (IEQ) factors for student learning and development by the National Research Council. Childhood presents the opportunity for children to develop lifelong skills that will support them throughout their adult lives. Acoustic performance of a space has been identified as a factor that can impact language acquisition, concentration, information retention, and general comfort within the environment. Increasingly, students learn by communication between both teachers and fellow students, making speaking and listening crucial. Neurodiversity - while initially coined to describe individuals with autism spectrum disorder (ASD) - widely describes anyone with a different brain process. As the understanding from cognitive and neurosciences increases, the number of people identified as neurodiversity is nearly 30% of the population. This research looks at guidelines and standard for spaces with good acoustical quality and relates it with the experiences of students with autism spectrum disorder (ASD), their parents, teachers, and educators through a mixed methods approach, including selected case studies interviews, and mixed surveys. The information obtained from these sources is used to determine if selected materials, especially properties relating to sound absorption and reverberation reduction, are equally useful in small, medium sized, and large learning spaces and methodologically approaching. The results describe the potential impact of acoustics on Neurodiverse students, considering factors that determine the complexity of sound in relation to the auditory processing capabilities of ASD students. In conclusion, this research extends the knowledge of how materials selection influences the better development of acoustical environments for autism students.

Keywords: acoustics, autism spectrum disorder (ASD), children, education, learning, learning spaces, materials, neurodiversity, sound

Procedia PDF Downloads 93

Authors: Alessandro Evangelista, Vito M. Manghisi, Michele Gattullo, Enricoandrea Laviola

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In this work, we propose a custom visualization technique for Out-Of-View-Objects in Virtual and Augmented Reality applications using Head Mounted Displays. In the last two decades, Augmented Reality (AR) and Virtual Reality (VR) technologies experienced a remarkable growth of applications for navigation, interaction, and collaboration in different types of environments, real or virtual. Both environments can be potentially very complex, as they can include many virtual objects located in different places. Given the natural limitation of the human Field of View (about 210° horizontal and 150° vertical), humans cannot perceive objects outside this angular range. Moreover, despite recent technological advances in AR e VR Head-Mounted Displays (HMDs), these devices still suffer from a limited Field of View, especially regarding Optical See-Through displays, thus greatly amplifying the challenge of visualizing out-of-view objects. This problem is not negligible when the user needs to be aware of the number and the position of the out-of-view objects in the environment. For instance, during a maintenance operation on a construction site where virtual objects serve to improve the dangers' awareness. Providing such information can enhance the comprehension of the scene, enable fast navigation and focused search, and improve users' safety. In our research, we investigated how to represent out-of-view-objects in HMD User Interfaces (UI). Inspired by commercial video games such as Call of Duty Modern Warfare, we designed a customized Compass. By exploiting the Unity 3D graphics engine, we implemented our custom solution that can be used both in AR and VR environments. The Compass Bar consists of a graduated bar (in degrees) at the top center of the UI. The values of the bar range from -180 (far left) to +180 (far right), the zero is placed in front of the user. Two vertical lines on the bar show the amplitude of the user's field of view. Every virtual object within the scene is represented onto the compass bar as a specific color-coded proxy icon (a circular ring with a colored dot at its center). To provide the user with information about the distance, we implemented a specific algorithm that increases the size of the inner dot as the user approaches the virtual object (i.e., when the user reaches the object, the dot fills the ring). This visualization technique for out-of-view objects has some advantages. It allows users to be quickly aware of the number and the position of the virtual objects in the environment. For instance, if the compass bar displays the proxy icon at about +90, users will immediately know that the virtual object is to their right and so on. Furthermore, by having qualitative information about the distance, users can optimize their speed, thus gaining effectiveness in their work. Given the small size and position of the Compass Bar, our solution also helps lessening the occlusion problem thus increasing user acceptance and engagement. As soon as the lockdown measures will allow, we will carry out user-tests comparing this solution with other state-of-the-art existing ones such as 3D Radar, SidebARs and EyeSee360.

Keywords: augmented reality, situation awareness, virtual reality, visualization design

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Authors: Omogoriola Hannah Omoloye

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Fish is a key ingredient on the global menu, a vital factor in the global environment and an important basis for livelihood worldwide1. The length – weight relationships (LWRs) is of great importance in fishery assessment2,3. Its importance is pronounced in estimated the average weight at a given length group4 and in assessing the relative well being of a fish population5. Length and weight measurement in conjunction with age data can give information on the stock composition, age at maturity, life span, mortality, growth and production4,5,6,7. In addition, the data on length and weight can also provides important clues to climatic and environmental changes and the change in human consumption practices8,9. However, the size attained by the individual fish may also vary because of variation in food supply, and these in turn may reflect variation in climatic parameters and in the supply of nutrient or in the degree of competition for food. Environment deterioration, for example, may reduce growth rates and will cause a decrease in the average age of the fish. The condition factor and the relative condition factor10 are the quantitative parameters of the well being state of the fish and reflect recent feeding condition of the fish. It is based on the hypothesis that heavier fish of a given length are in better condition11. This factor varies according to influences of physiological factors, fluctuating according to different stages of the development. Condition factor has been used as an index of growth and feeding intensity12. Condition factor decrease with increase in length 12,13 and also influences the reproductive cycle in fish14. The objective here is to determine the length-weight relationships and condition factor for direct use in fishery assessment and for future comparisons between populations of the same species at different locations. To provide quantitative information on the biology of marine fish species trawl from Nigeria coastal water.

Keywords: condition factor, growth pattern, marine fish species, Nigerian Coastal water

Procedia PDF Downloads 404

Authors: John Zanetich

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Due to their positive associations with student learning and retention, certain undergraduate opportunities are designated ‘high-impact.’ High-Impact Practices (HIPs) such as, learning communities, community based projects, research, internships, study abroad and culminating senior experience, share several traits bin common: they demand considerable time and effort, learning occurs outside of the classroom, and they require meaningful interactions between faculty and students, they encourage collaboration with diverse others, and they provide frequent and substantive feedback. As a result of experiential learning in these practices, participation in these practices can be life changing. High impact learning helps individuals locate tacit knowledge, and build mental models that support the accumulation of knowledge. On-going learning from experience and knowledge conversion provides the individual with a way to implicitly organize knowledge and share knowledge over a lifetime. Knowledge conversion is a knowledge management component which focuses on the explication of the tacit knowledge that exists in the minds of students and that knowledge which is embedded in the process and relationships of the classroom educational experience. Knowledge conversion is required when working with tacit knowledge and the demand for a learner to align deeply held beliefs with the cognitive dissonance created by new information. Knowledge conversion and tacit knowledge result from the fact that an individual's way of knowing, that is, their core belief structure, is considered generalized and tacit instead of explicit and specific. As a phenomenon, tacit knowledge is not readily available to the learner for explicit description unless evoked by an external source. The development of knowledge–related capabilities such as Aggressive Development of Tacit Knowledge (ADTK) can be used in experiential educational programs to enhance knowledge, foster behavioral change, improve decision making, and overall performance. ADTK allows the student in HIPs to use their existing knowledge in a way that allows them to evaluate and make any necessary modifications to their core construct of reality in order to amalgamate new information. Based on the Lewin/Schein Change Theory, the learner will reach for tacit knowledge as a stabilizing mechanism when they are challenged by new information that puts them slightly off balance. As in word association drills, the important concept is the first thought. The reactionary outpouring to an experience is the programmed or tacit memory and knowledge of their core belief structure. ADTK is a way to help teachers design their own methods and activities to unfreeze, create new learning, and then refreeze the core constructs upon which future learning in a subject area is built. This paper will explore the use of ADTK as a technique for knowledge conversion in the classroom in general and in HIP programs specifically. It will focus on knowledge conversion in curriculum development and propose the use of one-time educational experiences, multi-session experiences and sequential program experiences focusing on tacit knowledge in educational programs.

Keywords: tacit knowledge, knowledge management, college programs, experiential learning

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Authors: Huang Wei-Chi, Li Wei, Yu Tien-Chieh

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Medication adherence is crucial for treatment success. Adherence problem is common in patients with polypharmacy, especially in the geriatric population who are vulnerable to multiple chronic conditions but averagely less knowledgeable about diseases and medications. In order to help patients take medications appropriately and enhance the understanding of diseases or medications, a Line official account named e-Pharmacist was designed. The line is a popular freeware app with the highest penetration rate (95.7%) in Taiwan. The interface of e-Pharmacist is user-friendly for easy-to-read and convenient operating. Differ from other medication adherence apps, users just added e-Pharmacist as a LINE friend without installing any more apps and the drug lists were automatically downloaded from the personal electronic medical records with security permission. Over and above medication reminder, several additional capabilities were set up and engaged in the platform of e-Pharmacist including prescription refill reservation, laboratory examination consultation, medical appointment registration, and “Daily Health Log” where patients can record and track data of blood pressure/blood sugar and daily meals for self-health management as well as can share the important information to clinical professionals when seeking medical help. Additionally, a Line chatbot was utilized to provide tailored medicine information for the individual user. From July 2020 to March 2022, around 3000 patients added e-pharmacist as Line friends. Every day more than 1500 patients receive messages from e-pharmacist to notify them to take medicine. Thanks to the e-pharmacist alert system and Chatbot, the low-compliance patients (defined by Program on Adherence to Medication, PAM) significantly dropped from 36% to 6%, whereas the high-compliance patients dramatically increased from 13% to 77%. The user satisfaction is 98%. In brief, an e-pharmacist is not only a medication reminder but also a tailored personal assistant with value-added service for health management.

Keywords: e-pharmacist, self-health management, medication reminder, value-added service

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Authors: Ahmad Shahin, Fadi Chakik, Walid Moudani

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Our study is about elaborating a potential solution for a search engine that involves semantic technology to retrieve information and display it significantly. Semantic search engines are not used widely over the web as the majorities are still in Beta stage or under construction. Many problems face the current applications in semantic search, the major problem is to analyze and calculate the meaning of query in order to retrieve relevant information. Another problem is the ontology based index and its updates. Ranking results according to concept meaning and its relation with query is another challenge. In this paper, we are offering a light meta-engine (QESM) which uses Google search, and therefore Google’s index, with some adaptations to its returned results by adding multi-query expansion. The mission was to find a reliable ranking algorithm that involves semantics and uses concepts and meanings to rank results. At the beginning, the engine finds synonyms of each query term entered by the user based on a lexical database. Then, query expansion is applied to generate different semantically analogous sentences. These are generated randomly by combining the found synonyms and the original query terms. Our model suggests the use of semantic similarity measures between two sentences. Practically, we used this method to calculate semantic similarity between each query and the description of each page’s content generated by Google. The generated sentences are sent to Google engine one by one, and ranked again all together with the adapted ranking method (QESM). Finally, our system will place Google pages with higher similarities on the top of the results. We have conducted experimentations with 6 different queries. We have observed that most ranked results with QESM were altered with Google’s original generated pages. With our experimented queries, QESM generates frequently better accuracy than Google. In some worst cases, it behaves like Google.

Keywords: semantic search engine, Google indexing, query expansion, similarity measures

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Authors: Yasser Abo El-Magd, Wael Fawzy Mohamed

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Due to the great development in construction and building field, there are many projects and huge works appeared which consume many construction materials. Accordingly, that causes difficulty in handling traditional transportation means (ordinary cranes) due to their limited capacity; there is an urgent need to use high capacity cranes such as tower cranes. However, with regard to their high expense, we have to take into consideration selecting what type of cranes to be utilized which has been discussed by many researchers. In this research, a proposed technique was created to select the suitable type of crane and the best place for crane erection, in addition to minimum radius for requested crane in order to minimize cost. To fulfill that target, a computer program is designed to numerate these problems, demonstrating an example explaining how to apply program and the result donated the best place.

Keywords: tower crane, jib length, operating time, location, feasible area

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Qudratullah Muradi

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Geothermal energy is a renewable energy source that can be found in abundance on our planet. Only a small fraction of it is currently converted to electrical power, though in recent years installed geothermal capacity has increased considerably all over the world. In this paper, we assumed a model for designing of Enhanced Geothermal System, EGS. We used computer modeling group, CMG reservoir simulation software to create the typical Hot Dry Rock, HDR reservoir. In this research two wells, one injection of cold water and one production of hot water are included in the model. There are some hydraulic fractures created by the mentioned software. And cold water is injected in order to produce energy from the reservoir. The result of injecting cold water to the reservoir and extracting geothermal energy is defined by some graphs at the end of this research. The production of energy is quantified in a period of 10 years.

Keywords: geothermal energy, EGS, HDR, hydraulic fracturing

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Authors: Walaa Diab, Baher Atlam, Nadia El Nimer

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Egypt faces many obvious economic challenges, and it is so clear that a real economic transformation is needed to address those problems, especially after the recent decisions of floating the Egyptian pound and the gradual subsidy cuts that are trying to meet the needed conditions to get the IMF support of (a £12bn loan) for its economic reform program. Following the post-2008 revival of the interest in the fiscal policy and its vital role in speeding up or slowing down the economic growth. Here comes the value of this paper as it seeks to analyze the macroeconomic effects of fiscal policy in Egypt by applying A Bayesian SVAR Approach. The study uses the Bayesian method because it includes the prior information and no relevant information is omitted and so it is well suited for rational, evidence-based decision-making. Since the study aims to define the effects of fiscal policy shocks in Egypt to help the decision-makers in determining the proper means to correct the structural problems in the Egyptian economy, it has to study the period of 1990s economic reform, but unfortunately; the available data is on an annual frequency. Thus, it uses annual time series to study the period 1991: 2005 And quarterly data over the period 2006–2016. It uses a set of six main variables includes government expenditure and net tax revenues as fiscal policy arms affecting real GDP, unemployment, inflation and the interest rate. The study also tries to assess the 'crowding out' effects by considering the effects of government spending and government revenue shocks on the composition of GDP, namely, on private consumption and private investment. Last but not least the study provides its policy implications regarding the needed role of fiscal policy in Egypt in the upcoming economic reform building on the results it concludes from the previous reform program.

Keywords: fiscal policy, government spending, structural vector autoregression, taxation

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Authors: A. H. Alenezi

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Cooling by impingement jet is known to have a significant high local and average heat transfer coefficient which make it widely used in industrial cooling systems. The heat transfer characteristics of an impinging jet on rib-roughened flat plate has been investigated numerically. This paper was set out to investigate the effect of rib height on the heat transfer rate. Since the flow needs to have enough spacing after passing the rib to allow reattachment especially for high Reynolds numbers, this study focuses on finding the optimum rib height which would be the best to maximize the heat transfer rate downstream the plate. This investigation employs a round nozzle with hydraulic diameter (Dh) of 13.5 mm, Jet-to-target distance of (H/D) of 4, rib location=1.5D and and finally jet angels of 45˚ and 90˚ under the influence of Re =10,000.

Keywords: jet impingement, CFD, turbulence model, heat transfer

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Authors: Navid Mirzaei Varzeghani, Mahmoud Saffarzadeh, Ali Naderan, Amirhossein Taheri

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Countries are progressing, and the world's busiest airports see year-on-year increases in travel demand. Passenger acceptability of an airport depends on the airport's appeals, which may include one of these routes between the city and the airport, as well as the facilities to reach them. One of the critical roles of transportation planners is to predict future transportation demand so that an integrated, multi-purpose system can be provided and diverse modes of transportation (rail, air, and land) can be delivered to a destination like an airport. In this study, 356 questionnaires were filled out in person over six days. First, the attraction of business and non-business trips was studied using data and a linear regression model. Lower travel costs, a range of ages more significant than 55, and other factors are essential for business trips. Non-business travelers, on the other hand, have prioritized using personal vehicles to get to the airport and ensuring convenient access to the airport. Business travelers are also less price-sensitive than non-business travelers regarding airport travel. Furthermore, carrying additional luggage (for example, more than one suitcase per person) undoubtedly decreases the attractiveness of public transit. Afterward, based on the manner and purpose of the trip, the locations with the highest trip generation to the airport were identified. The most famous district in Tehran was District 2, with 23 visits, while the most popular mode of transportation was an online taxi, with 12 trips from that location. Then, significant variables in separation and behavior of travel methods to access the airport were investigated for all systems. In this scenario, the most crucial factor is the time it takes to get to the airport, followed by the method's user-friendliness as a component of passenger preference. It has also been demonstrated that enhancing public transportation trip times reduces private transportation's market share, including taxicabs. Based on the responses of personal and semi-public vehicles, the desire of passengers to approach the airport via public transportation systems was explored to enhance present techniques and develop new strategies for providing the most efficient modes of transportation. Using the binary model, it was clear that business travelers and people who had already driven to the airport were the least likely to change.

Keywords: multimodal transportation, demand modeling, travel behavior, statistical models

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Authors: Dagim Dessalegn Haile

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This study investigated the interaction between the drivers' socio-demographic background information (age, gender, and driving experience) and the risky events score in the i-DREAMS platform. Further, the relationship between the participants' background driving behavior and the i-DREAMS platform behavioral output scores of risky events was also investigated. The i-DREAMS acronym stands for Smart Driver and Road Environment Assessment and Monitoring System. It is a European Union Horizon 2020 funded project consisting of 13 partners, researchers, and industry partners from 8 countries. A total of 25 Belgian car drivers (16 male and nine female) were considered for analysis. Drivers' ages were categorized into ages 18-25, 26-45, 46-65, and 65 and older. Drivers' driving experience was also categorized into four groups: 1-15, 16-30, 31-45, and 46-60 years. Drivers are classified into two clusters based on the recorded score for risky events during phase 1 (baseline) using risky events; acceleration, deceleration, speeding, tailgating, overtaking, and lane discipline. Agglomerative hierarchical clustering using SPSS shows Cluster 1 drivers are safer drivers, and Cluster 2 drivers are identified as risky drivers. The analysis result indicated no significant relationship between age groups, gender, and experience groups except for risky events like acceleration, tailgating, and overtaking in a few phases. This is mainly because the fewer participants create less variability of socio-demographic background groups. Repeated measure ANOVA shows that cluster 2 drivers improved more than cluster 1 drivers for tailgating, lane discipline, and speeding events. A positive relationship between background drivers' behavior and i-DREAMS platform behavioral output scores is observed. It implies that car drivers who in the questionnaire data indicate committing more risky driving behavior demonstrate more risky driver behavior in the i-DREAMS observed driving data.

Keywords: i-dreams, car drivers, socio-demographic background, risky events

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Authors: Jean Berger, Mohamed Barkaoui

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Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: search path planning, false alarm, search-and-delivery, entropy, genetic algorithm

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Authors: Wei-Kuo Soong

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The forecasting of typhoon tracks remains a formidable challenge, primarily attributable to the paucity of observational data in the open sea and the intricate influence of weather systems at varying scales. This study investigates the case of Typhoon Hinnamnor in 2022, examining its trajectory and intensity fluctuations in relation to the interaction with a concurrent tropical cyclone and sea surface temperatures (SST). Utilizing the Weather Research and Forecasting Model (WRF), to simulate and analyze the interaction between Typhoon Hinnamnor and its environmental factors, shedding light on the mechanisms driving typhoon development and enhancing forecasting capabilities.

Keywords: typhoon, sea surface temperature, forecasting, WRF

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Authors: Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh

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The goal of this research is to explore the evolution of the concept of “blended learning” over a twenty-year period, to see whether or not the conceptualization has remained consistent or if it has become either more specific or more general. To achieve this goal, the term “blended learning” (and variations) was searched for in various bibliographical repositories for each year 2003-2022 to locate a highly cited paper that is not behind a paywall, to locate unique definitions that would be freely available to all academics each year. Each of the twenty unique definitions is explored to identify how they categorize both the Classroom Component and the Computer Component of blended learning, as well as identify which discipline each definition originates from and which country it comes from to see if there are any significant geographical variations. Based on this analysis, trends that appear in the definitions are noted, as well as an overall interpretation of the notion of “Blended Learning.”

Keywords: blended learning, definitions of blended learning, e-learning, thematic searches

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Authors: Júlio Cesar Lopes de Oliveira, Carlos Henrique Gonçalves Treviso

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The shortage of the automotive market in relation to options for sources of high power car audio systems, led to development of this work. Thus, we developed a source with stabilized voltage with 4320 W effective power. Designed to the voltage of 14.4 V and a choice of two currents: 30 A load option in battery banks and 300 A at full load. This source can also be considered as a source of general use dedicated commercial with a simple control circuit in analog form based on discrete components. The assembly of power circuit uses a methodology for higher power than the initially stipulated.

Keywords: DC-DC power converters, converters, power conversion, pulse width modulation converters

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Mustafa A. Al-Refai

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This paper investigates the energy storage technologies that can potentially enhance the use of solar energy. Water electrolysis systems are seen as the principal means of producing a large amount of hydrogen in the future. Starting from the analysis of the models of the system components, a complete simulation model was realized in the Matlab-Simulink environment. Results of the numerical simulations are provided. The operation of electrolysis and photovoltaic array combination is verified at various insulation levels. It is pointed out that solar cell arrays and electrolysers are producing the expected results with solar energy inputs that are continuously varying.

Keywords: electrolyzer, simulink, solar energy, storage system

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Authors: J. Martin Leal-Graciano, Juan J. Pérez-Gavilán, A. Reyes-Salazar, J. H. Castorena, J. L. Rivera-Salas

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The experimental results about the global behavior of twelve 1:2 scaled reinforced concrete frames subject to in-plane lateral load are presented. The main objective was to generate experimental evidence about the use of steel bars within mortar bed joints as shear reinforcement in infill walls. Similar to the Canadian and New Zealand standards, the Mexican code includes specifications for this type of reinforcement. However, these specifications were obtained through experimental studies of load-bearing walls, mainly confined walls. Little information is found in the existing literature about the effects of joint reinforcement on the seismic behavior of infill masonry walls. Consequently, the Mexican code establishes the same equations to estimate the contribution of joint reinforcement for both confined walls and infill walls. Confined masonry construction and a reinforced concrete frame infilled with masonry walls have similar appearances. However, substantial differences exist between these two construction systems, which are mainly related to the sequence of construction and to how these structures support vertical and lateral loads. To achieve the objective established, ten reinforced concrete frames with masonry infill walls were built and tested in pairs, having both specimens in the pair identical characteristics except that one of them included joint reinforcement. The variables between pairs were the type of units, the size of the columns of the frame, and the aspect ratio of the wall. All cases included tie columns and tie beams on the perimeter of the wall to anchor the joint reinforcement. Also, two bare frames with identical characteristics to the infilled frames were tested. The purpose was to investigate the effects of the infill wall on the behavior of the system to in-plane lateral load. In addition, the experimental results were compared with the prediction of the Mexican code. All the specimens were tested in a cantilever under reversible cyclic lateral load. To simulate gravity load, constant vertical load was applied on the top of the columns. The results indicate that the contribution of the joint reinforcement to lateral strength depends on the size of the columns of the frame. Larger size columns produce a failure mode that is predominantly a sliding mode. Sliding inhibits the production of new inclined cracks, which are necessary to activate (deform) the joint reinforcement. Regarding the effects of joint reinforcement in the performance of confined masonry walls, many facts were confirmed for infill walls. This type of reinforcement increases the lateral strength of the wall, produces a more distributed cracking, and reduces the width of the cracks. Moreover, it reduces the ductility demand of the system at maximum strength. The prediction of the lateral strength provided by the Mexican code is a property in some cases; however, the effect of the size of the columns on the contribution of joint reinforcement needs to be better understood.

Keywords: experimental study, infill wall, infilled frame, masonry wall

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Authors: Arezou Rezazadeh, Nasrin Omidvar, Hassan Eini-Zinab, Mahmoud Ghazi-Tabatabaie, Reza Majdzadeh, Saeid Ghavamzadeh, Sakineh Nouri-Saeidlou

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Dietary pattern analysis method can reflect more information about the nutritional etiology of chronic diseases such as obesity. The aim of this study was to determine the relationship between major dietary patterns and anthropometric measures in men and women living in the city of Urmia. In this cross-sectional study, 723 participants (427 women and 296 men), aged 20–64 in Urmia city were selected from all four zones of Urmia city, in the north-west of Iran. Anthropometrics (weight, height, waist and hip circumference) were measured with standard methods. Body Mass Index (BMI) was calculated by dividing weight (in kilograms) by the square of height (in meter). Dietary intake information was collected by a semi-quantitative food frequency questionnaire in the last year. Dietary patterns were determined using principal component analysis. The relationship between dietary patterns and obesity was analyzed by logistic regression. Three major dietary patterns (DPs) were identified that were named ‘Traditional Higher SES (THS)’, ‘Traditional Low SES (TLS)’ and ‘Transitional’. THS DP was positively and Transitional DP was negatively associated with BMI and waist circumference (W.C), however, after adjusting for confounding variables (age, gender, ethnicity, energy intake, physical activity and SES), the associations were not significant. The TLS was not significantly associated with BMI, but after adjusting for confounders, a significant positive association was detected with W.C and Waist to hip ratio (WHR). Findings showed that both traditional patterns were positively and the western type transitional pattern was reversely associated with anthropometric indices. But this relationship was highly affected by demographic, socioeconomic and energy input and output determinants. The results indicate the inevitable effect of environmental factors on the relationship between dietary patterns and anthropometric indices.

Keywords: anthropometric indices, dietary pattern, Iran, North-west

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