Search results for: computer code

Authors: Mohsin Ali Shaikh, Weiguo Song, Rehmat Karim, Muhammad Kashan Surahio, Muhammad Usman Shahid

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Fire investigations face challenges due to the complexity of fire development, and real-world accidents lack repeatability, making it difficult to apply standardized approaches. The unpredictable nature of fires and the unique conditions of each incident contribute to the complexity, requiring innovative methods and tools for effective analysis and reconstruction. This study proposes to provide the modern accident analysis model through numerical reconstruction for fire investigation in textile buildings. This method employs computer simulation to enhance the overall effectiveness of textile-building investigations. The materials and evidence collected from past incidents reconstruct fire occurrences, progressions, and catastrophic processes. The approach is demonstrated through a case study involving a tragic textile factory fire in Karachi, Pakistan, which claimed 257 lives. The reconstruction method proves invaluable for determining fire origins, assessing losses, establishing accountability, and, significantly, providing preventive insights for complex fire incidents.

Keywords: fire investigation, numerical simulation, fire safety, fire incident, textile building

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Authors: Amir Peyman Soleymani, Jasna Jankovic

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The augmented demand of the clean and renewable energy has necessitated the fuel cell and battery industries to produce more efficient devices at the lower prices, which can be achieved through the improvement of the electrode. Microstructural characterization, as one of the main materials development tools, plays a pivotal role in the production of better clean energy devices. In this study, methods for characterization and studying of the defects and components distribution were performed on the polymer electrolyte membrane fuel cell (PEMFC) and Li-ion battery (LIB) electrodes in 2D and 3D. The particles distribution, porosity, mechanical defects, and component distribution were studied by Scanning Electron Microscope (SEM), SEM-Focused Ion Beam (SEM-FIB), and Scanning Transmission Electron Microscope equipped with Energy Dispersive Spectroscopy (STEM-EDS). The 3D results obtained from X-ray Computed Tomography (XCT) revealed the pathways for electron and ion conductivity and defects progression maps. Computer-aided methods (Avizo) were employed to simulate the properties and performance of the microstructure in the electrodes. The suggestions were provided to improve the performance of PEMFCs and LIBs by adjusting the microstructure and the distribution of the components in the electrodes.

Keywords: PEM fuel cells, Li-ion batteries, 2D and 3D imaging, materials characterizations

Procedia PDF Downloads 155

Authors: S. Alfalah, J. Falah, T. Alfalah, M. Elfalah, O. Falah

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The field of education is an ever-evolving area constantly enriched by newly discovered techniques provided by active research in all areas of technologies. The recent years have witnessed the introduction of a number of promising technologies and applications to enhance the teaching and learning experience. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing education in many fields. VR creates an artificial environment, using computer hardware and software, which is similar to the real world. This simulation provides a solution to improve the delivery of materials, which facilitates the teaching process by providing a useful aid to instructors, and enhances the learning experience by providing a beneficial learning aid. In order to assure future utilization of such systems, students’ perceptions were examined toward utilizing VR as an educational tool in the Faculty of Information Technology (IT) in The University of Jordan. A questionnaire was administered to IT undergraduates investigating students’ opinions about the potential opportunities that VR technology could offer and its implications as learning and teaching aid. The results confirmed the end users’ willingness to adopt VR systems as a learning aid. The result of this research forms a solid base for investing in a VR system for IT education.

Keywords: information, technology, virtual reality, education

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Authors: Apinya Mungaomklang, Natakamol Lookkham

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The purpose of this research is to study the characteristics of the graduates based on Thailand Qualification Framework (TQF) of the Faculty of Industrial Technology, Suan Sunandha Rajabhat University. The population of the research was employers/entrepreneurs/supervisors of students who were doing Professional Experiences course in their respective organizations during semester 1/2012. Data were collected during the month of September 2012 from the total number of 100 people. The tool used in this research was a questionnaire developed by the research team. Data were analyzed using percentage, mean and standard deviation using a computer program. The results showed that most of the surveyed organizations were private companies. The program with most students doing Professional Experiences course was Safety Technology and Occupational Health. The nature of work that most students did was associated with the document. Employers/ entrepreneurs/employers’ opinions on the characteristics of the graduates based on TQF received high scores. Cognitive skills received the highest score, followed by interpersonal relationships and responsibilities, ethics and moral, numerical analysis skills, communication and information technology skills, and knowledge, respectively.

Keywords: graduates characteristics, Thailand Qualification Framework, employers, entrepreneurs

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Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

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It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

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Authors: Eva Tvrdá, Hana Greifová, Peter Ivanič, Norbert Lukáč

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The aim of this study was to evaluate the dose- and time-dependent in vitro effects of berberine (BER), a natural alkaloid with numerous biological properties on bovine spermatozoa during three time periods (0 h, 2 h, 24 h). Bovine semen samples were diluted and cultivated in physiological saline solution containing 0.5% DMSO together with 200, 100, 50, 10, 5, and 1 μmol/L BER. Spermatozoa motility was assessed using the computer assisted semen analyzer. The viability of spermatozoa was assessed by the metabolic (MTT) assay, production of superoxide radicals was quantified using the nitroblue tetrazolium (NBT) test, and chemiluminescence was used to evaluate the generation of reactive oxygen species (ROS). Cell lysates were prepared and the extent of lipid peroxidation (LPO) was evaluated using the TBARS assay. The results of the movement activity showed a significant increase in the motility during long term cultivation in case of concentrations ranging between 1 and 10 μmol/L BER (P < 0.01; P < 0.001; 24 h). At the same time, supplementation of 1, 5 and 10 μmol/L BER led to a significant preservation of the cell viability (P < 0.001; 24 h). BER addition at a range of 1-50 μmol/L also provided a significantly higher protection against superoxide (P < 0.05) and ROS (P < 0.001; P < 0.01) overgeneration as well as LPO (P < 0.01; P<0.05) after a 24 h cultivation. We may suggest that supplementation of BER to bovine spermatozoa, particularly at concentrations ranging between 1 and 50 μmol/L, may offer protection to the motility, viability and oxidative status of the spermatozoa, particularly notable at 24 h.

Keywords: berberine, bulls, motility, oxidative profile, spermatozoa, viability

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Accurate Liver, spleen and kidneys segmentation in abdominal CT images is one of the most important steps for computer aided abdominal organs pathology diagnosis. In this paper, we have proposed a new semi-automatic algorithm for Liver, spleen and kidneys area extraction in abdominal CT images. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. The algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, multi-abdominal organ segmentation, mosaic image, the watershed algorithm

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Authors: Abdul Hakim Chikho

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Calculating the ultimate load of a column in a sway framed structure involves, in the currently used design method, the calculation of the column effective length and utilizing the interaction formulas or tables. Therefore, no allowance is usually made for the effects of the presence of semi rigid connections or the presence of infill panels. In this paper, a new and simple design procedure is recommend to calculate the ultimate load of a framed Column allowing for the presence of rotational end restraints, semi rigid connections, the column end moments resulted from the applied vertical and horizontal loading and infill panels in real steel structure. In order to verify the accuracy of the recommended method to predict good and safe estimations of framed column ultimate loads, several examples have been solved utilizing the recommended procedure, and the results were compared to those obtained using a second order computer program, and good correlation had been obtained. Therefore, the accuracy of the proposed method to predict the Behaviour of practical steel columns in framed structures has been verified.

Keywords: column ultimate load, semi rigid connections, steel column, infill panel, steel structure

Procedia PDF Downloads 180

Authors: P. Ramesh, Aby Joseph, Arya G. Lal, U. S. Aji

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Integration of distributed green renewable energy sources in addition with battery energy storage is an inevitable requirement in a smart grid environment. To achieve this, an Intelligent Green Energy Management System (i-GEMS) needs to be incorporated to ensure coordinated operation between supply and load demand based on the hierarchy of Renewable Energy Sources (RES), battery energy storage and distribution grid. A bi-directional energy harvester is an integral component facilitating Intelligent Green Energy Management System (i-GEMS) and it is required to meet the technical challenges mentioned as follows: (1) capability for bi-directional mode of operation (buck/boost) (2) reduction of circuit parasitic to suppress voltage spikes (3) converter startup problem (4) high frequency magnetics (5) higher power density (6) mode transition issues during battery charging and discharging. This paper is focused to address the above mentioned issues and targeted to design, develop and implement a bi-directional energy harvester with galvanic isolation. In this work, the hardware architecture for bi-directional energy harvester rated 3.5 kW is developed with Isolated Full Bridge Boost Converter (IFBBC) as well as Dual Active Bridge (DAB) Converter configuration using modular power electronics hardware which is identical for both solar PV array and battery energy storage. In IFBBC converter, the current fed full bridge circuit is enabled and voltage fed full bridge circuit is disabled through Pulse Width Modulation (PWM) pulses for boost mode of operation and vice-versa for buck mode of operation. In DAB converter, all the switches are in active state so as to adjust the phase shift angle between primary full bridge and secondary full bridge which in turn decides the power flow directions depending on modes (boost/buck) of operation. Here, the control algorithm is developed to ensure the regulation of the common DC link voltage and maximum power extraction from the renewable energy sources depending on the selected mode (buck/boost) of operation. The circuit analysis and simulation study are conducted using PSIM 9.0 in three scenarios which are - 1.IFBBC with passive clamp, 2. IFBBC with active clamp, 3. DAB converter. In this work, a common hardware prototype for bi-directional energy harvester with 3.5 kW rating is built for IFBBC and DAB converter configurations. The power circuit is equipped with right choice of MOSFETs, gate drivers with galvanic isolation, high frequency transformer, filter capacitors, and filter boost inductor. The experiment was conducted for IFBBC converter with passive clamp under boost mode and the prototype confirmed the simulation results showing the measured efficiency as 88% at 2.5 kW output power. The digital controller hardware platform is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the bi-directional energy harvester is written in C language and developed using code composer studio. The comprehensive analyses of the power circuit design, control strategy for battery charging/discharging under buck/boost modes and comparative performance evaluation using simulation and experimental results will be presented.

Keywords: bi-directional energy harvester, dual active bridge, isolated full bridge boost converter, intelligent green energy management system, maximum power point tracking, renewable energy sources

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Authors: Yadgar Tayfur, Antony Darby, Tim Ibell, Mark Evernden, John Orr

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Fabric form-work is a technique to cast concrete structures with a great advantage of saving concrete material of up to 40%. This technique is particularly associated with the optimized concrete structures that usually have smaller cross-section dimensions than equivalent prismatic members. However, this can make the structural system produced from these members prone to smaller serviceability safety margins. Therefore, it is very important to understand the serviceability issue of non-prismatic concrete structures. In this paper, an analytical computer-based model to optimize concrete beams and to predict load-deflection behaviour of both prismatic and non-prismatic concrete beams is presented. The model was developed based on the method of sectional analysis and integration of curvatures. Results from the analytical model were compared to load-deflection behaviour of a number of beams with different geometric and material properties from other researchers. The results of the comparison show that the analytical program can accurately predict the load-deflection response of concrete beams with medium reinforcement ratios. However, it over-estimates deflection values for lightly reinforced specimens. Finally, the analytical program acceptably predicted load-deflection behaviour of on-prismatic concrete beams.

Keywords: fabric-formed concrete, continuous beams, optimisation, serviceability

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Authors: Borja Bordel, Ramón Alcarria, Marina Pérez

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In March 2020, in Spain, a sanitary and unexpected crisis caused by COVID-19 was declared. All of a sudden, all degrees, classes and evaluation tests and projects had to be transformed into online activities. However, the chaotic situation generated by a complex operation like that, executed without any well-established procedure, led to very different experiences and, finally, results. In this paper, we are describing three experiences in two different Universities in Madrid. On the one hand, the Technical University of Madrid, a public university with little experience in online education. On the other hand, Alfonso X el Sabio University, a private university with more than five years of experience in online teaching. All analyzed subjects were related to computer engineering. Professors and students answered a survey and personal interviews were also carried out. Besides, the professors’ workload and the students’ academic results were also compared. From the comparative analysis of all these experiences, we are extracting the most successful strategies, methodologies, and activities. The recommendations in this paper will be useful for courses during the next months when the sanitary situation is still affecting an educational organization. While, at the same time, they will be considered as input for the upcoming digitalization process of higher education.

Keywords: educational experience, online education, higher education digitalization, COVID, Spain

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Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

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In computer science, the purpose of finding useful information is still one of the most active and important research topics. The most popular application of information retrieval (IR) are Search Engines, they meet users' specific needs and aim to locate the effective information in the web. However, these search engines have some limitations related to the relevancy of the results and the ease to explore those results. In this context, we proposed in previous works a Multi-Space Search Engine model that is based on a multidimensional interpretation universe. In the present paper, we integrate an additional dimension that allows to offer users new research experiences. The added component is based on creating user profiles and calculating the similarity between them that then allow the use of collaborative filtering in retrieving search results. To evaluate the effectiveness of the proposed model, a prototype is developed. The experiments showed that the additional dimension has improved the relevancy of results by predicting the interesting items of users based on their experiences and the experiences of other similar users. The offered personalization service allows users to approve the pertinent items, which allows to enrich their profiles and further improve research.

Keywords: information retrieval, v-facets, user behavior analysis, user profiles, topical ontology, association rules, data personalization

Procedia PDF Downloads 264

Authors: Vivek Krishna, Nikhil Jain, A. Mary Posonia A., Albert Mayan J

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Terrorism and insurgency are significant global issues that require constant attention and effort from governments and scientists worldwide. To combat these threats, nations invest billions of dollars in developing new defensive technologies to protect civilians. Breakthroughs in vehicle automation have led to the use of sophisticated machines for many dangerous and critical anti-terrorist activities. Our concept of an "Unmanned Ground Vehicle" can carry out tasks such as border security, surveillance, mine detection, and active combat independently or in tandem with human control. The robot's movement can be wirelessly controlled by a person in a distant location or can travel to a pre-programmed destination autonomously in situations where personal control is not feasible. Our defence system comprises two units: the control unit that regulates mobility and the motion tracking unit. The remote operator robot uses the camera's live visual feed to manually operate both units, and the rover can automatically detect movement. The rover is operated by manpower who controls it using a joystick or mouse, and a wireless modem enables a soldier in a combat zone to control the rover via an additional controller feature.

Keywords: robotics, computer vision, Machine learning, Artificial intelligence, future of AI

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Authors: Hamza Javar Magnier, Leslie V. Woodcock

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It has been reported that at temperatures above the critical there is no “continuity of liquid and gas”, as originally hypothesized by van der Waals. Rather, both gas and liquid phases, with characteristic properties as such, extend to supercritical temperatures. Each phase is bounded by the locus of a percolation transition, i.e. a higher-order thermodynamic phase change associated with percolation of gas clusters in a large void, or liquid interstitial vacancies in a large cluster. Between these two-phase bounds, it is reported there exists a mesophase that resembles an otherwise homogeneous dispersion of gas micro-bubbles in liquid (foam) and a dispersion of liquid micro-droplets in gas (mist). Such a colloidal-like state of a pure one-component fluid represents a hitherto unchartered equilibrium state of matter besides pure solid, liquid or gas. Here we provide compelling evidence, from molecular dynamics (MD) simulations, for the existence of this supercritical mesophase and its colloidal nature. We report preliminary results of computer simulations for a model fluid using a simplistic representation of atoms or molecules, i.e. a hard-core repulsion with an attraction so short that the atoms are referred to as “adhesive spheres”. Molecular clusters, and hence percolation transitions, are unambiguously defined. Graphics of color-coded clusters show colloidal characteristics of the supercritical mesophase.

Keywords: critical phenomena, mesophase, supercritical, square-well, critical parameters

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Authors: Tien Wei Daniel Hwang

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The computer program inventors, particularly in Fintech, are unwilling to apply for patents in Taiwan after 2014. Passing the ‘statutory subject matter eligibility’ test and becoming the system patent are not the only cause to the reduction in the number of application. Taiwanese court needs to resolve whether the defendants had ‘used’ that software patent in patent direct infringement suit. Both 35 U.S.C. § 271(a) and article 58 paragraph 2 of Taiwan Patent Law don’t define the meaning of ‘use’ in the statutes. Centillion Data Sys., LLC v. Qwest Commc’ns Int’l, Inc. reconsidered the meaning of ‘use’ in system patent infringement, and held that ‘a party must put the invention into service, i.e., control the system as a whole and obtain benefit from it.’ In Taiwan, Intellectual Property Office, Ministry of Economic Affairs, has explained that ‘using’ the patent is ‘achieving the technical effect of the patent.’ Nonetheless, this definition is too broad to apply to not only the software patent but also the traditional patent. To supply the friendly environment for Fintech corporations, this article aims to let Taiwanese court realize why and how United States District Court, S.D. Indiana, Indianapolis Division and United States Court of Appeals, Federal Circuit defined the meaning of ‘use’ in 35 U.S.C. § 271(a). However, this definition is so lax and confuses many defendants in United States. Accordingly, this article indicates the elements in Taiwan Patent Law are different with 35 U.S.C. § 271(a), so Taiwanese court can follow the interpretation of ‘use’ in Centillion Data case without the same obstacle.

Keywords: direct infringement, FinTech, software patent, use

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Authors: Kanika Sood, Sijie Shang

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A fundamental goal of education includes preparing students to become a part of the global workforce by making beneficial contributions to society. In this paper, we analyze student performance for multiple courses that involve different teaching pedagogies: a cooperative learning technique and an inquiry-based learning strategy. Student performance includes student engagement, grades, and attendance records. We perform this study in the Computer Science department for online and in-person courses for 450 students. We will perform correlation analysis to study the relationship between student scores and other parameters such as gender, mode of learning. We use natural language processing and machine learning to analyze student feedback data and performance data. We assess the learning outcomes of two teaching pedagogies for undergraduate and graduate courses to showcase the impact of pedagogical adoption and learning outcome as determinants of academic achievement. Early findings suggest that when using the specified pedagogies, students become experts on their topics and illustrate enhanced engagement with peers.

Keywords: bag-of-words, cooperative learning, education, inquiry-based learning, in-person learning, natural language processing, online learning, sentiment analysis, teaching pedagogy

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Authors: Antonios Panagopoulos, Stamoulis Georgios

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Dyslexia's diagnosis is made taking into account reading and writing skills and is carried out by qualified scientific staff. In addition, there are screening tests that are designed to give an indication of possible dyslexic difficulties. Their main advantage is that they create a pleasant environment for the user and reduce the stress that can lead to false results. An online application was created for the first time, as far as authors' knowledge, for screening Dyslexia in Greek high school students named «DyScreTe». Thus, a sample of 240 students between 16 and 18 years old in Greece was taken, of which 120 were diagnosed with dyslexia by an official authority in Greece, and 120 were typically developed. The main hypothesis that was examined is that students who were diagnosed with dyslexia by official authorities in Greece had significantly lower performance in the respective software tests. The results verified the hypothesis we made those children with dyslexia in each test had a lower performance com-pared to the type developed in successful responses, except for the intelligence test. After random sampling, it was shown that the new online application was a useful tool for screening dyslexia. However, computer evaluation cannot replace the diagnosis by a professional expert, but with the results of this application, the interdisciplinary team that deals with the differential diagnosis will create and evaluate, at a later time, the appropriate intervention program.

Keywords: dyslexia, screening tests, deficits, application

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Authors: Kadrefi Athanasia, Fronimaki Evgenia, Mavri Maria

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3D Printing (3DP) is a distinct, disruptive technology that belongs to a wider group of manufacturing technologies, Additive Manufacturing (AM). In 3DP, a custom digital file turns into a solid object using a single computer and a 3D printer. Among multiple advantages, 3DP offers production with fewer steps compared to conventional manufacturing, lower production costs, and customizable designs. 3DP can be performed by several techniques, while the most common is Fused Deposition Modeling (FDM). FDM belongs to a wider group of AM techniques, material extrusion, where a digital file converts into a solid object using raw material (called filament) melted in high temperatures. As in most manufacturing procedures, environmental issues have been raised here, too. This study aims to review the literature on issues that determine technical and mechanical factors that affect the sustainability and resilience of a final 3D-printed object. The research focuses on the collection of papers that deal with 3D printing techniques and use keywords or phrases like ‘3D printed objects’, ‘factors of 3DP sustainability’, ‘waste materials,’ ‘infill patterns,’ and ‘support structures.’ After determining factors, a pilot survey will be conducted at the 3D Printing Lab in order to define the significance of each factor in the final 3D printed object.

Keywords: additive manufacturing, 3D printing, sustainable manufacturing, sustainable production

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Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate the benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. Developments improving the ease of ITS creation have recently increased their proliferation, leading many K-12 schools and institutions of higher education in the United States to regularly use ITS within classrooms. We investigated how students perceive their experience using an ITS. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course and were subsequently asked for feedback on their experience. Results show that their perceptions were generally favorable of the ITS, and most would seek to use an ITS both for STEM and non-STEM courses in the future. Along with detailed transaction-level data, this feedback also provides insights on the design of user-friendly interfaces, guidance on accessibility for students with impairments, the sequencing of exercises, students’ expectation of achievement, and comparisons to other tutoring experiences. We discuss how these findings are important for the creation, implementation, and evaluation of ITS as a mode and method of teaching and learning.

Keywords: college statistics course, intelligent tutoring systems, in vivo study, student perceptions of tutoring

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Authors: Sahar Jahani, Meryem Ayse Yucel, David Boas, Seyed Kamaledin Setarehdan

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Near-infrared spectroscopy allows monitoring of oxy- and deoxy-hemoglobin concentration changes associated with hemodynamic response function (HRF). HRF is usually affected by natural physiological hemodynamic (systemic interferences) which occur in all body tissues including brain tissue. This makes HRF extraction a very challenging task. In this study, we used Kalman filter based on a general linear model (GLM) of brain activity to define the proportion of systemic interference in the brain hemodynamic. The performance of the proposed algorithm is evaluated in terms of the peak to peak error (Ep), mean square error (MSE), and Pearson’s correlation coefficient (R2) criteria between the estimated and the simulated hemodynamic responses. This technique also has the ability of real time estimation of single trial functional activations as it was applied to classify finger tapping versus resting state. The average real-time classification accuracy of 74% over 11 subjects demonstrates the feasibility of developing an effective functional near infrared spectroscopy for brain computer interface purposes (fNIRS-BCI).

Keywords: hemodynamic response function, functional near-infrared spectroscopy, adaptive filter, Kalman filter

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Marwan Ahmed Swileh, Amal Hussein Abuaffan

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Objective: This study aimed to explore the existence of golden proportion (GP) between the widths of maxillary anterior teeth and golden standard (GS) for width to height ratio of maxillary central incisor in individuals with attractive and non-attractive smiles. Materials and methods: A total of 82 females were recruited and divided into 2 groups: attractive smile (n= 41) and non-attractive smile (n= 41). Frontal photographs were taken, scanned, and saved on a personal computer. The apparent mesiodistal width of each anterior tooth was measured. The data were analyzed using the appropriate statistical tests at p-value < 0.05. Results: Frequency of GP was very low among the total sample, and most proportions were higher than GP. No significant differences were found between both groups in relation to central-to-lateral ratio while significant differences were found in relation to canine-to-lateral ratio. Similarly, most proportions of width to height ratio were higher than GS. Difference between groups was significant for left side and for both sides (p < 0.05) but was not for right side (p > 0.05). Conclusion: Frequency of golden proportion was very low among the study population. Smile attractiveness is not related that much to the proportions between the teeth.

Keywords: golden proportion, golden standard, attractive smile, esthetic, anterior teeth

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

Procedia PDF Downloads 574

Authors: Martin Alexander Eder, Sergei Semenov

Abstract:

Many glass-epoxy composite structures, such as large utility wind turbine rotor blades (WTBs), comprise of adhesive joints with typically thick bond lines used to connect the different components during assembly. Performance optimization of rotor blades to increase power output by simultaneously maintaining high stiffness-to-low-mass ratios entails intricate geometries in conjunction with complex anisotropic material behavior. Consequently, adhesive joints in WTBs are subject to multiaxial stress states with significant stress gradients depending on the local joint geometry. Moreover, the dynamic aero-elastic interaction of the WTB with the airflow generates non-proportional, variable amplitude stress histories in the material. Empiricism shows that a prominent failure type in WTBs is high cycle fatigue failure of adhesive bond line interfaces, which in fact over time developed into a design driver as WTB sizes increase rapidly. Structural optimization employed at an early design stage, therefore, sets high demands on computationally efficient interface fatigue models capable of predicting the critical locations prone for interface failure. The numerical stress-based interface fatigue model presented in this work uses the Drucker-Prager criterion to compute three different damage indices corresponding to the two interface shear tractions and the outward normal traction. The two-parameter Drucker-Prager model was chosen because of its ability to consider shear strength enhancement under compression and shear strength reduction under tension. The governing interface damage index is taken as the maximum of the triple. The damage indices are computed through the well-known linear Palmgren-Miner rule after separate rain flow-counting of the equivalent shear stress history and the equivalent pure normal stress history. The equivalent stress signals are obtained by self-similar scaling of the Drucker-Prager surface whose shape is defined by the uniaxial tensile strength and the shear strength such that it intersects with the stress point at every time step. This approach implicitly assumes that the damage caused by the prevailing multiaxial stress state is the same as the damage caused by an amplified equivalent uniaxial stress state in the three interface directions. The model was implemented as Python plug-in for the commercially available finite element code Abaqus for its use with solid elements. The model was used to predict the interface damage of an adhesively bonded, tapered glass-epoxy composite cantilever I-beam tested by LM Wind Power under constant amplitude compression-compression tip load in the high cycle fatigue regime. Results show that the model was able to predict the location of debonding in the adhesive interface between the webfoot and the cap. Moreover, with a set of two different constant life diagrams namely in shear and tension, it was possible to predict both the fatigue lifetime and the failure mode of the sub-component with reasonable accuracy. It can be concluded that the fidelity, robustness and computational efficiency of the proposed model make it especially suitable for rapid fatigue damage screening of large 3D finite element models subject to complex dynamic load histories.

Keywords: adhesive, fatigue, interface, multiaxial stress

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Authors: Monisha Pattanaik

Abstract:

In scenarios where users have to work with large amounts of hierarchical data structures combined with visualizations (For example, Construction 3d Models, Manufacturing equipment's models, Gantt charts, Building Plans), the data structures have a high density in terms of consisting multiple parent nodes up to 50 levels and their siblings to descendants, therefore convey an immediate feeling of complexity. With customers moving to consumer-grade enterprise software, it is crucial to make sophisticated features made available to touch devices or smaller screen sizes. This paper evaluates the UI component that allows users to scroll through all deep density levels using a slider overlay on top of the hierarchy table, performing several actions to focus on one set of objects at any point in time. This overlay component also solves the problem of excessive horizontal scrolling of the entire table on a fixed pane for a hierarchical table. This component can be customized to navigate through parents, only siblings, or a specific component of the hierarchy only. The evaluation of the UI component was done by End Users of application and Human-Computer Interaction (HCI) experts to test the UI component's usability with statistical results and recommendations to handle complex hierarchical data visualizations.

Keywords: building information modeling, digital twin, navigation, UI component, user interface, usability, visualization

Procedia PDF Downloads 139

Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

Abstract:

The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: dimensional affect prediction, output-associative RVM, multivariate regression, fast testing

Procedia PDF Downloads 286

Authors: Zainurrasyid Abdullah, Mohamed Fadzlee Sulaiman, Muhammad Fadzlan Zainal, M. Zabri Adil Talib, Aswami Fadillah M. Ariffin

Abstract:

The Onion Router (Tor) browser is a well-known tool and widely used by people who seeking for web anonymity when browsing the internet. Criminals are taking this advantage to be anonymous over the internet. Accessing the dark web could be the significant reason for the criminal in order for them to perform illegal activities while maintaining their anonymity. For a digital forensic analyst, it is crucial to extract the trail of evidence in proving that the criminal’s computer has used Tor browser to conduct such illegal activities. By applying the digital forensic methodology, several techniques could be performed including application analysis, memory analysis, and registry analysis. Since Windows 10 is the latest operating system released by Microsoft Corporation, this study will use Windows 10 as the operating system platform that running Tor browser. From the analysis, significant artifacts left by Tor browser were discovered such as the execution date, application installation date and browsing history that can be used as an evidence. Although Tor browser was designed to achieved anonymity, there is still some trail of evidence can be found in Windows 10 platform that can be useful for investigation.

Keywords: artifacts analysis, digital forensics, forensic analysis, memory analysis, registry analysis, tor browser, Windows 10

Procedia PDF Downloads 171

Authors: Kaushik Sathupadi, Sandesh Achar

Abstract:

Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

Procedia PDF Downloads 42

Authors: Steffon Campbell

Abstract:

This research explores the potential of using artificial intelligence (AI) autoethnographies to study, document, explore, and understand aspects of Caribbean culture. As a digital research methodology, AI autoethnography merges computer science and technology with ethnography, providing a fresh approach to collecting and analyzing data to generate novel insights. This research investigates how AI autoethnography can best be applied to understanding the various complexities and nuances of Caribbean culture, as well as examining how technology can be a valuable tool for enriching study of the region. By applying AI autoethnography to Caribbean studies, the research aims to produce new and innovative ways of discovering, understanding, and appreciating the Caribbean. The study found that AI autoethnographies can offer a valuable method for exploring Caribbean culture. Specifically, AI autoethnographies can facilitate experiences of self-reflection, facilitate reconciliation with the past, and provide a platform to explore and understand the cultural, social, political, and economic concerns of Caribbean people. Findings also reveal that these autoethnographies can create a space for people to reimagine and reframe the conversation around Caribbean culture by enabling them to actively participate in the process of knowledge creation. The study also finds that AI autoethnography offers the potential for cross-cultural dialogue, allowing participants to connect with one another over cultural considerations and engage in meaningful discourse.

Keywords: artificial intelligence, autoethnography, caribbean, culture

Procedia PDF Downloads 28