Search results for: Global Accuracy Indicator (GAI)

Authors: Leigh G. Hayden, Susan E. Shepley, Cristina Passarelli, William Tingo

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Introduction: Sensory interventions are popular therapeutic and recreational approaches for people living with all stages of dementia. However, it is unknown which sensory interventions are used to achieve which outcomes across all subtypes of dementia. Methods: To address this gap, we conducted a scoping review of sensory interventions for people living with dementia. We conducted a search of the literature for any article published in English from 1 January 1990 to 1 June 2019, on any sensory or multisensory intervention targeted to people living with any kind of dementia, which reported on patient health outcomes. We did not include complex interventions where only a small aspect was related to sensory stimulation. We searched the databases Medline, CINHAL, and Psych Articles using our institutional discovery layer. We conducted all screening in duplicate to reduce Type 1 and Type 2 errors. The data from all included papers were extracted by one team member, and audited by another, to ensure consistency of extraction and completeness of data. Results: Our initial search captured 7654 articles, and the removal of duplicates (n=5329), those that didn’t pass title and abstract screening (n=1840) and those that didn’t pass full-text screening (n=281) resulted in 174 articles included. The countries with the highest publication in this area were the United States (n=59), the United Kingdom (n=26) and Australia (n=15). The most common type of interventions were music therapy (n=36), multisensory rooms (n=27) and multisensory therapies (n=25). Seven articles were published in the 1990’s, 55 in the 2000’s, and the remainder since 2010 (n=112). Discussion: Multisensory rooms have been present in the literature since the early 1990’s. However, more recently, nature/garden therapy, art therapy, and light therapy have emerged since 2008 in the literature, an indication of the increasingly diverse scholarship in the area. The least popular type of intervention is a traditional food intervention. Taste as a sensory intervention is generally avoided for safety reasons, however it shows potential for increasing quality of life. Agitation, behavior, and mood are common outcomes for all sensory interventions. However, light therapy commonly targets sleep. The majority (n=110) of studies have very small sample sizes (n=20 or less), an indicator of the lack of robust data in the field. Additional small-scale studies of the known sensory interventions will likely do little to advance the field. However, there is a need for multi-armed studies which directly compare sensory interventions, and more studies which investigate the use of layering sensory interventions (for example, adding an aromatherapy component to a lighting intervention). In addition, large scale studies which enroll people at early stages of dementia will help us better understand the potential of sensory and multisensory interventions to slow the progression of the disease.

Keywords: sensory interventions, dementia, scoping review

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Authors: Milad Yousefi, Moslem Yousefi, Ricarpo Poley, Amer Nordin Darus

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Design optimization of heat exchangers is a very complicated task that has been traditionally carried out based on a trial-and-error procedure. To overcome the difficulties of the conventional design approaches especially when a large number of variables, constraints and objectives are involved, a new method based on a well-stablished evolutionary algorithm, particle swarm optimization (PSO), weighted sum approach and a novel constraint handling strategy is presented in this study. Since, the conventional constraint handling strategies are not effective and easy-to-implement in multi-objective algorithms, a novel feasibility-based ranking strategy is introduced which is both extremely user-friendly and effective. A case study from industry has been investigated to illustrate the performance of the presented approach. The results show that the proposed algorithm can find the near pareto-optimal with higher accuracy when it is compared to conventional non-dominated sorting genetic algorithm II (NSGA-II). Moreover, the difficulties of a trial-and-error process for setting the penalty parameters is solved in this algorithm.

Keywords: Heat exchanger, Multi-objective optimization, Particle swarm optimization, NSGA-II Constraints handling.

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Authors: S. O. Uwaifo

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The paper examines the pivotal role of the library in university education through the provision of a wide range of information materials (print and non- print) required for the teaching, learning and research activities of the university. However certain impediments to the effectiveness of Nigerian university libraries, such as financial constraints, high foreign exchange, global disparities in accessing the internet, lack of local area networks, erratic electric power supply, absence of ICT literacy, poor maintenance culture, etc., were identified. Also, the necessity of repositioning Nigerian university libraries for effective information provision and delivery was stressed by pointing out their dividends, such as users’ access to Directory of Open Access Journals (DOAJ), Online Public Access Catalogue (OPAC), Institutional Repositories, Electronic Document Delivery, Social Media Networks, etc. It therefore becomes necessary for the libraries to be repositioned by way of being adequately automated or digitized for effective service delivery, in this age of globalization. Based on the identified barriers by this paper, some recommendations were proffered.

Keywords: repositioning, Nigerian university libraries, effective information provision and delivery, globalization

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: Reinhold Kosfeld, Andreas Gohs

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In the reduction of CO₂ emissions, the transition to environmentally friendly transport modes has a high significance. In Germany, the climate protection programme 2030 includes various measures for promoting electromobility. Although electric cars at present hold a market share of just over one percent, its stock more than doubled in the past two years. Special measures like tax incentives and a buyer’s premium have been put in place to promote the shift towards electric cars and boost their diffusion. Knowledge of the future expansion of electric cars is required for planning purposes and adaptation measures. With a view of these objectives, we particularly investigate the effect of spatial spillovers on forecasting performance. For this purpose, time series econometrics and panel econometric models are designed for pure electric cars and hybrid cars for Germany. Regional forecasting models with spatial interactions are consistently estimated by using spatial econometric techniques. Regional data on the stocks of electric cars and their determinants at the district level (NUTS 3 regions) are available from the Federal Motor Transport Authority (Kraftfahrt-Bundesamt) for the period 2017 - 2019. A comparative examination of aggregated regional and national predictions provides quantitative information on accuracy gains by allowing for spatial spillovers in forecasting electric mobility.

Keywords: electric mobility, forecasting market diffusion, regional panel data model, spatial interaction

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Authors: Seyedmohammad Mousavian, Hanlu Fan, Quingliang Tang

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Climate change is emerging as a severe threat to our society, so businesses are expected to take actions to mitigate carbon emissions. However, the actions to be taken depend on managers’ perceptions of climate change risks. Yet, there is scant research on this issue, and understanding of the determinants of corporate perceptions of climate change is extremely limited. The purpose of this study is to close this gap by examining the relationship between perceptions of climate risk and firm-level and country-level factors. In this study, climate change risk captures physical, regulatory, and other risks, and we use data from European companies that participated in CDP from 2010 to 2017. This study reveals those perceptions of climate change risk are significantly positively associated with the environmental, social, and governance score, firm size, and membership in a carbon-intensive sector. In addition, we find that managers in firms operating in a geographic area that is sensitive to the consequences of global warming are more likely to perceive and formally recognize carbon-related risks in their CDP reports.

Keywords: carbon actions, CDP, climate change risk, risk perception

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Authors: Shin-Jer Yang, Kai-Tai Yang

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In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: cloud service, multi-tenancy, NFC, IAM, mobile device

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Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

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Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

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Authors: Mohammadreza Akbari, Pooya Soleimani Besheli, Reza khalili, Sara Akbari, Davood Domiri Ganji

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In this symposium, our aims are accuracy, capabilities and power at solving of the complicate non-linear differential at the reaction chemical in the catalyst reactor (heterogeneous reaction). Our purpose is to enhance the ability of solving the mentioned nonlinear differential equations at chemical engineering and similar issues with a simple and innovative approach which entitled ‘’Akbari-Ganji's Method’’ or ‘’AGM’’. In this paper we solve many examples of nonlinear differential equations of chemical reactions and its investigate. The chemical reactor with the energy changing (non-isotherm) in two reactors of mixed and plug are separately studied and the nonlinear differential equations obtained from the reaction behavior in these systems are solved by a new method. Practically, the reactions with the energy changing (heat or cold) have an important effect on designing and function of the reactors. This means that possibility of reaching the optimal conditions of operation for the maximum conversion depending on nonlinear nature of the reaction velocity toward temperature, results in the complexity of the operation in the reactor. In this case, the differential equation set which governs the reactors can be obtained simultaneous solution of mass equilibrium and energy and temperature changing at concentration.

Keywords: new method (AGM), nonlinear differential equation, tubular and mixed reactors, catalyst bed

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Authors: Bao Liu, Maarten Vanierschot, Frank Buysschaert

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The present work examines the wake dynamics of a rim-driven thruster (RDT) with Computational Fluid Dynamics (CFD). Unsteady Reynolds-averaged Navier-Stokes (URANS) equations were solved in the commercial solver ANSYS Fluent in combination with the SST k-ω turbulence model. The application of the moving reference frame (MRF) and sliding mesh (SM) approach to handling the rotational movement of the propeller were compared in the transient simulations. Validation and verification of the numerical model was performed to ensure numerical accuracy. Two representative scenarios were considered, i.e., the bollard condition (J=0) and a very light loading condition(J=0.7), respectively. From the results, it’s confirmed that compared to the SM method, the MRF method is not suitable for resolving the unsteady flow features as it only gives the general mean flow but smooths out lots of characteristic details in the flow field. By evaluating the simulation results with the SM technique, the instantaneous wake flow field under both conditions is presented and analyzed, most notably the helical vortex structure. It’s observed from the results that the tip vortices, blade shed vortices, and hub vortices are present in the wake flow field and convect downstream in a highly non-linear way. The shear layer vortices shedding from the duct displayed a strong interaction with the distorted tip vortices in an irregularmanner.

Keywords: computational fluid dynamics, rim-driven thruster, sliding mesh, wake dynamics

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Authors: Shih-Heng Tung, Ming-Hsiang Shih, Wen-Pei Sung

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Because of the rapid development of digital camera and computer, digital image correlation method has drawn lots of attention recently and has been applied to a variety of fields. However, the image distortion is inevitable when the image is captured through a lens. This image distortion problem can result in an innegligible error while using digital image correlation method. There are already many different ways to correct the image distortion, and most of them require specific image patterns or precise control points. A new distortion correction method is proposed in this study. The proposed method is based on the fact that a flat surface should keep flat when it is measured using three-dimensional (3D) digital image measurement technique. Lens distortion can be divided into radial distortion, decentering distortion and thin prism distortion. Because radial distortion has a more noticeable influence than the other types of distortions, this method deals only with radial distortion. The simplified 3D digital image measurement technique is adopted to measure the surface coordinates of a flat specimen. Then the gradient method is applied to find the best correction parameters. A few experiments are carried out in this study to verify the correctness of this method. The results show that this method can achieve a good accuracy and it is suitable for both large and small distortion conditions. The most important advantage is that it requires neither mark with specific pattern nor precise control points.

Keywords: 3D DIC, radial distortion, distortion correction, planarity

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Authors: Petronella Jonck, Martin Chanza, Anna-Marie Pelser

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Ascribed to the global pandemic most higher education institutions responded by relocating content presented by means of contact sessions to an online platform giving rise to digital pedagogy. The purpose of the research reported on was to explore emerging challenges linked to digital pedagogy from a practitioner stance. Digital pedagogy has emerged as a powerful tool to compliment traditional methods. However, stumbling blocks should be identified and addressed for future utilization. A qualitative research design was implemented by means of a semi-structured interview schedule distributed to practitioners during the COVID-19 pandemic. Results revealed that institutional type influenced the implementation of digital pedagogy. Other challenges relate to the increased cost of education, decreased access, limited knowledge about digital pedagogy, behavioral intent to adopt a multi-modal approach, lack of ICT infrastructure to mention a few. Higher education institutions should address challenges towards the optimal use of digital pedagogy in future.

Keywords: COVID-19, digital pedagogy, higher education institutions, information communication technology

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Authors: Elżbieta Frołowicz

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Throughout the ages, pedeutological reflection has been accompanied by numerous controversies resulting from public discourse of social, economic and political forces. According to accepted ideologies or represented interests, these forces generate various visions of self, which should be the result of the educational process at school. Accuracy of visions is particularly important in times of fast and significant socio-cultural changes witnessed by us. The teacher – also the music teacher – is responsible for accomplishing them. The author tries to characterize the group of music teachers and some contexts of their functioning in modern Polish schools based on literature analysis and according to results of her research conducted in the years 2013-2014 and ten years later (2023-2024). The source of analysis material is mostly interviews with music teachers from different types of elementary schools in Poland. This research used a partially structured individual depth interview to ensure a quality encounter between two personalities during a personal conversation. Interviews were conducted with 8 people in 2013-2014 and with 7 in 2023-24. Music teachers' problems have remained essentially unchanged over the decade. In an attempt to formulate some general conclusions, the author offers an assertion that the functioning of music teachers at school is vastly restrained by the coercion of an institution and is not compatible with the present requirements in which they operate.

Keywords: educational strategies, interview, music teacher, public education

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Authors: Peter L. Varkonyi, Andras A. Sipos

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The quasi-static growth of elastic fibers is studied in the presence of distributed contact with an immobile surface, subject to isotropic dry or viscous friction. Unlike classical problems of elastic stability modelled by autonomous dynamical systems with multiple time scales (slowly varying bifurcation parameter, and fast system dynamics), this problem can only be formulated as a non-autonomous system without time scale separation. It is found that the fibers initially converge to a trivial, straight configuration, which is later replaced by divergence reminiscent of buckling phenomena. In order to capture the loss of stability, a new definition of exponential stability against infinitesimal perturbations for systems defined over finite time intervals is developed. A semi-analytical method for the determination of the critical length based on eigenvalue analysis is proposed. The post-critical behavior of the fibers is studied numerically by using variational methods. The emerging post-critical shapes and the asymptotic behavior as length goes to infinity are identified for simple spatial distributions of growth. Comparison with physical experiments indicates reasonable accuracy of the theoretical model. Some applications from modeling plant root growth to the design of soft manipulators in robotics are briefly discussed.

Keywords: buckling, elastica, friction, growth

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Authors: Gulbakhyt Sultanova

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Business education institutions assess the progress of their students by giving them grades for courses completed and calculating a Grade Point Average (GPA). Whether the participation in these courses has led to the development of competences enabling graduates to successfully compete in the labor market should be measured using a new index: Employment Readiness Assessment (ERA). The higher the ERA, the higher the quality of education at a business school. This is applied, empirical research conducted by using a method of linear optimization. The aim of research is to identify factors which lead to the minimization of the deviation of GPA from ERA as well as to the maximization of ERA. ERA is composed of three components resulting from testing proficiency in Business English, testing work and personal skills, and job interview simulation. The quality of education is improving if GPA approximates ERA and ERA increases. Factors which have had a positive effect on quality enhancement are academic mobility of students and staff, practical-oriented courses taught by staff with work experience, and research-based courses taught by staff with research experience. ERA is a better index to measure the quality of business education than traditional indexes such as GPA due to its greater accuracy in assessing the level of graduates’ competences demanded in the labor market. Optimizing the educational process in pursuit of quality enhancement, ERA has to be used in parallel with GPA to find out which changes worked and resulted in improvement.

Keywords: assessment and evaluation, competence evaluation, education quality, employment readiness

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Authors: Sanjoy Mukherjee

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Discussions on concepts of Single Axis Tracker (SAT) are becoming more and more apt for developing countries like India not just as an advancement in racking technology but due to the utmost necessity of reaching at the lowest Levelized Cost of Energy (LCOE) targets. With this increasing competition and significant fall in feed-in tariffs of solar PV projects, developers are under constant pressure to secure investment for their projects and eventually earn profits from them. Moreover, being the second largest populated country, India suffers from scarcity of land because of higher average population density. So, to mitigate the risk of this dual edged sword with reducing trend of unit (kWh) cost at one side and utilization of land on the other, tracking evolved as the call of the hour. Therefore, the prime objectives of this paper are not only to showcase how STT proves to be an effective mechanism to get more gain in Global Incidence in collector plane (G_inc) with respect to traditional mounting systems but also to introduce Seasonally Tilted Tracker (STT) technology as a possible option for high latitude locations.

Keywords: tracking system, grid connected solar PV plant, CAPEX reduction, levelized cost of energy

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Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

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In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: Anzor Abralava, Ketevan Kokrashvili, Rusudan Kutateladze, Nino Pailodze, Ketevan Kutateladze, Giorgi Sulashvili

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Nowadays when the integration of states is growing fast, it is urgent to study the rules of behavior which they resort to in case of conflicts and disagreements. The reason of disagreement in many ways is the Foreign policy carried out by separate countries, as the market participants define production and export capacity and structure as well as level of international division of labor due to the competition among them. We can say over and over again that outbreak of conflicts in Georgia displays the serious controversy between political and economic powerhouses. However, to tell the truth existence of the unsolved conflicts in Georgia is the result of weakness and inadequacy of Georgian politics. Today the main task of political quarters in Georgia should be a direction to Caucasus, as to the region burdened with the most complicated problems which blockade the settlement of conflicts and farther development of our country (or vice versa). In this situation rehabilitation of our authority, leading role and hegemony; expansion and consolidation of peacekeeping and other missions are considered as the exact activities for accomplishing all Georgian economic and political goals.

Keywords: Awara Group, political centers, administrative services, dynamic process

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Authors: N. Pegahfar, P. Ghafarian

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In this research, the synoptic weather conditions during the heavy flood of 10-12 January 2020 in the Sistan-va-Balouchestan Province of Iran will be analyzed. To this aim, reanalysis data from the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), NCEP Global Forecasting System (GFS) analysis data, measured data from a surface station together with satellite images from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) have been used from 9 to 12 January 2020. Atmospheric parameters both at the lower troposphere and also at the upper part of that have been used, including absolute vorticity, wind velocity, temperature, geopotential height, relative humidity, and precipitation. Results indicated that both lower-level and upper-level currents were strong. In addition, the transport of a large amount of humidity from the Oman Sea and the Red Sea to the south and southeast of Iran (Sistan-va-Balouchestan Province) led to the vast and unexpected precipitation and then a heavy flood.

Keywords: Sistan-va-Balouchestn Province, heavy flood, synoptic, analysis data

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Authors: Bela Lebedeva

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Characteristics of the Web as a channel of information dissemination - accessibility and openness, interactivity and multimedia news - become wider and cover the audience quickly, positively affecting the perception of content, but blur out the understanding of the journalistic work. As a result audience and advertisers continue migrating to the Internet. Moreover, online targeting allows monetizing not only the audience (as customarily given to traditional media) but also the content and traffic more accurately. While the users identify themselves with the qualitative characteristics of the new market, its actors are formed. Conflict of interests is laid in the base of the economy of their relations, the problem of traffic tax as an example. Meanwhile, content monetization actualizes fiscal interest of the state too. The balance of supply and demand is often violated due to the political risks, particularly in terms of state capitalism, populism and authoritarian methods of governance such social institutions as the media. A unique example of access to journalistic material, limited by monetization of content is a television channel Dozhd' (Rain) in Russian web space. Its liberal-minded audience has a better possibility for discussion. However, the channel could have been much more successful in terms of unlimited free speech. Avoiding state pressure and censorship its management has decided to save at least online performance and monetizing all of the content for the core audience. The study Methodology was primarily based on the analysis of journalistic content, on the qualitative and quantitative analysis of the audience. Reconstructing main events and relationships of actors on the market for the last six years researcher has reached some conclusions. First, under the condition of content monetization the capitalization of its quality will always strive to quality characteristics of user, thereby identifying him. Vice versa, the user's demand generates high-quality journalism. The second conclusion follows the previous one. The growth of technology, information noise, new political challenges, the economy volatility and the cultural paradigm change – all these factors form the content paying model for an individual user. This model defines him as a beneficiary of specific knowledge and indicates the constant balance of supply and demand other conditions being equal. As a result, a new economic quality of information is created. This feature is an indicator of the market as a self-regulated system. Monetized information quality is less popular than that of the Public Broadcasting Service, but this audience is able to make decisions. These very users keep the niche sectors which have more potential of technology development, including the content monetization ways. The third point of the study allows develop it in the discourse of media space liberalization. This cultural phenomenon may open opportunities for the development of social and economic relations architecture both locally and regionally.

Keywords: content monetization, state capitalism, media liberalization, media economy, information quality

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Alisha Gupta

Abstract:

Osteoarthritis (OA) is the most common form of arthritis which is a degenerative joint disease causing joints to begin to break down and underlying bones to change. This “wear and tear” most frequently affects hands, hips, and knees. This is important because OA pain is considered to be a leading cause of mobility impairment in older adults, with hip and knee OA ranked 11th highest contributors to global disability. Bone tissue engineering utilizing polymer scaffolds and hydrogels is an emerging field for treating osteoarthritis. Polymer scaffolds provide a three-dimensional structure for tissue growth, and hydrogels can be used to deliver drugs and growth factors. The combination of the two materials creates a hybrid structure that can better withstand physiological and mechanical demands while also providing a more controlled environment for drug and nutrient delivery. I think using bone tissue engineering for making scaffold-hydrogel composites that are self-regenerating and vascularizing might be useful in solving this problem. Successful implementation can reconstruct healthy, simulated bone tissue on deficient applicants.

Keywords: tissue engineering, regenerative medicine, scaffold-hydrogel composites, osteoarthritis

Procedia PDF Downloads 107

Authors: Morteza Ghourchi, Meraj Jafari, Atena Soheilazizi

Abstract:

Today, with the globalization of communications and the connection of countries within the framework of the global economy, free zones play the most important role as the engine of global economic development and globalization of countries. In this regard, corridors have a fundamental role in linking countries and free zones physically with each other. One of these corridors is the New Silk Road corridor (One Belt, One Road initiative), which is being built by China to connect with European countries. In connecting this corridor to European countries, Iran and Turkey are among the countries that play an important role in linking China to European countries through this corridor. The New Silk Road corridor, by connecting Iran’s free zones (Sarakhs and Maku) and Turkey’s free zones (Anatolia and Europe), can provide the best opportunity for expanding economic cooperation and regional development between Iran and Turkey. It can also provide economic links between Iran and Turkey with Central Asian countries and especially the port of Khorgos. On the other hand, it can expand Iran-Turkey economic relations more than ever before with Europe in a vast economic network. The research method was descriptive-analytical, using library resources, documents of Iranian free zones, and the Internet. In an interview with Fars News Agency, Mohammad Reza Kalaei, CEO of Sarakhs Free Zone, said that the main goal of Sarakhs Special Economic Zone is to connect Iran with the Middle East and create a transit corridor towards East Asian countries, including Turkey. Also, according to an interview with Hussein Gharousi, CEO of Maku Free Zone, the importance of this region is due to the fact that Maku Free Zone, due to its geographical location and its position on the China-Europe trade route, the East-West corridor, which is the closest point to the European Union through railway and transit routes, and also due to its proximity to Eurasian countries, is an ideal opportunity for industrial and technological companies. Creating a transit corridor towards East Asian countries, including Turkey, is one of the goals of this project Free zones between Iran and Turkey can sign an agreement within the framework of the New Silk Road to expand joint investments and economic cooperation towards regional convergence. The purpose of this research is to develop economic links between Iranian and Turkish free zones along the New Silk Road, which will lead to the expansion and development of regional cooperation between the two countries within the framework of neighboring policies. The findings of this research include the development of economic diplomacy between the Secretariat of the Supreme Council of Free Zones of Iran and the General Directorate of Free Zones of Turkey, the agreement to expand cooperation between the free zones of Sarakhs, Maku, Anatolia, and Europe, holding biennial conferences between Iranian free zones along the New Silk Road with Turkish free zones, creating a joint investment fund between Iran and Turkey in the field of developing free zones along the Silk Road, helping to attract tourism between Iranian and Turkish free zones located along the New Silk Road, improving transit infrastructure and transportation to better connect Iranian free zones to Turkish free zones, communicating with China, and creating joint collaborations between China’s dry ports and its free zones with Iranian and Turkish free zones.

Keywords: network economy, new silk road (one belt, one road initiative), free zones (Sarakhs, Maku, Anatolia, Europe), regional development, neighborhood policies

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Authors: Khitem Amiri, Mohamed Farah

Abstract:

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

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

Procedia PDF Downloads 274

Authors: Swathi M. Vanniarajan

Abstract:

Reading research suggests that online contextual vocabulary comprehension while reading is an interactive and integrative process. One’s success in it depends on a variety of factors including the amount and the nature of available linguistic and nonlinguistic cues, his/her analytical and integrative skills, schema memory (content familiarity), and processing speed characterized along the continuum of controlled to automatic processing. The experiment reported here, conducted with 30 native speakers as one group and 30 nonnative speakers as another group (all graduate students), hypothesized that while working on (24) tasks which required them to comprehend an unfamiliar word in real time without backtracking, due to the differences in the nature of their respective reading processes, the nonnative subjects would be less able to construct the meanings of the unknown words by integrating the multiple but sufficient contextual cues provided in the text but the native subjects would be able to. The results indicated that there were significant inter-group as well as intra-group differences in terms of the quality of definitions given. However, when given additional time, while the nonnative speakers could significantly improve the quality of their definitions, the native speakers in general would not, suggesting that all things being equal, time is a significant factor for success in nonnative vocabulary and reading comprehension processes and that accuracy precedes automaticity in the development of nonnative reading processes also.

Keywords: reading, second language processing, vocabulary comprehension

Procedia PDF Downloads 157

Authors: Nasser Almonawer

Abstract:

Timely reaction to an evolving global business environment and volatile market conditions necessitates system and process flexibility, which in turn demands agile and adaptable architecture and a steady infusion of affordable new technologies. On the contrary, a large number of organizations utilize systems characterized by inflexible and obsolete legacy architectures. To effectively respond to the dynamic contemporary business environments, such architectures must be migrated to robust and modular open architectures. To this end, this paper proposes an integrated decision support system for a seamless migration to open systems. The proposed decision support system (DSS) integrates three well-established quantitative and qualitative decision-making models—namely, the Delphi method, Analytic Hierarchy Process (AHP) and Goal Programming (GP) to (1) assess risks and establish evaluation criteria; (2) formulate migration strategy and rank candidate systems; and (3) allocate resources among the selected systems.

Keywords: decision support systems, open systems architecture, analytic hierarchy process (AHP), goal programming (GP), delphi method

Procedia PDF Downloads 31