Search results for: Computer Simulation

Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Masahiro Suzuki, Nobuyuki Okura

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The crosswind effect on ground transportations has been extensively investigated for decades. The effect of tornado, however, has been hardly studied in spite of the fact that even heavy ground vehicles, namely, trains were overturned by tornadoes with casualties in the past. Therefore, aerodynamic effects of the tornado on the train were studied by several approaches in this study. First, an experimental facility was developed to clarify aerodynamic forces acting on a vehicle running through a tornado. Our experimental set-up consists of two apparatus. One is a tornado simulator, and the other is a moving model rig. PIV measurements showed that the tornado simulator can generate a swirling-flow field similar to those of the natural tornadoes. The flow field has the maximum tangential velocity of 7.4 m/s and the vortex core radius of 96 mm. The moving model rig makes a 1/40 scale model train of single-car/three-car unit run thorough the swirling flow with the maximum speed of 4.3 m/s. The model car has 72 pressure ports on its surface to estimate the aerodynamic forces. The experimental results show that the aerodynamic forces vary its magnitude and direction depends on the location of the vehicle in the flow field. Second, the aerodynamic forces on the train were estimated by using Rankin vortex model. The Rankin vortex model is a simple tornado model which widely used in the field of civil engineering. The estimated aerodynamic forces on the middle car were fairly good agreement with the experimental results. Effects of the vortex core radius and the path of the train on the aerodynamic forces were investigated using the Rankin vortex model. The results shows that the side and lift forces increases as the vortex core radius increases, while the yawing moment is maximum when the core radius is 0.3875 times of the car length. Third, a computational simulation was conducted to clarify the flow field around the train. The simulated results qualitatively agreed with the experimental ones.

Keywords: aerodynamic force, experimental method, tornado, train

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Authors: Hadj Brahim Mounia, Belhamel Farid, Souici Messoud

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In big cities, construction on sloping land (landslide) is becoming increasingly prevalent due to the unavailability of flat lands. This has created a major challenge for structural engineers with regard to structure design, due to the difficulties encountered during the implementation of projects, both for the structure and the soil. This paper analyses the effect of the number of floors of a building, founded on isolated footing on the stability of the slope using the computer code finite element PLAXIS 2D v. 8.2. The isolated footings of a building in this case were anchored in soil so that the levels of successive isolated footing realize a maximum slope of base of three for two heights, which connects the edges of the nearest footings, according to the Algerian building code DTR-BC 2.331: Shallow foundations. The results show that the embedment of the foundation into the soil reduces the value of the safety factor due to the change of the stress state of the soil by these foundations. The number of floors a building has also influences the safety factor. It has been noticed from this case of study that there is no risk of collapse of slopes for an inclination between 5° and 8°. In the case of slope inclination greater than 10° it has been noticed that the urbanization is prohibited.

Keywords: isolated footings, multi-storeys building, PLAXIS 2D, slope

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Authors: Terada Pinyo

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This study is a survey research designed to evaluate the quality of graduate students and factors influencing their quality. The sample group consists of 240 students. The data are collected from stratified sampling and are analyzed and calculated by instant computer program. Statistics used are percentage, mean, standard deviation, Pearson correlation coefficient, Cramer’s V and logistic regression analysis. It is found that the graduate students’ opinions regarding their characteristics according to the Thai Qualifications Framework for Higher Education (TQF) are at high score range both overall and specific category. The top categories that received the top score are interpersonal skills and responsibility, ethics and morals, knowledge, cognitive skills, numerical analysis with communication and information technology skills, respectively. On the other hand, factors affecting the quality of graduate students are cognitive skills, numerical analysis with communication and information technology, knowledge, interpersonal skills and responsibility, ethics and morals, and career regarding sales/business, respectively.

Keywords: student quality evaluation, Thai qualifications framework for higher education, graduate school, cognitive skills

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Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: Frodouard Minani

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Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.

Keywords: base station, clustering algorithm, energy efficient, sensors, wireless sensor networks

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Authors: Bhenjamin Jordan L. Ona

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Weather modification is an act of altering weather systems that catches interest on scientific studies. Cloud seeding is a common form of weather alteration. On the same principle, tropical cyclone mitigation experiment follows the methods of cloud seeding with intensity to account for. This study will present the effects of aerosol to tropical cyclone cloud microphysics and intensity. The framework of Weather Research and Forecasting (WRF) model incorporated with Thompson aerosol-aware scheme is the prime host to support the aerosol-cloud microphysics calculations of cloud condensation nuclei (CCN) ingested into the tropical cyclones before making landfall over the Philippine coast. The coupled microphysical and radiative effects of aerosols will be analyzed using numerical data conditions of Tropical Storm Ketsana (2009), Tropical Storm Washi (2011), and Typhoon Haiyan (2013) associated with varying CCN number concentrations per simulation per typhoon: clean maritime, polluted, and very polluted having 300 cm-3, 1000 cm-3, and 2000 cm-3 aerosol number initial concentrations, respectively. Aerosol species like sulphates, sea salts, black carbon, and organic carbon will be used as cloud nuclei and mineral dust as ice nuclei (IN). To make the study as realistic as possible, investigation during the biomass burning due to forest fire in Indonesia starting October 2015 as Typhoons Mujigae/Kabayan and Koppu/Lando had been seeded with aerosol emissions mainly comprises with black carbon and organic carbon, will be considered. Emission data that will be used is from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). The physical mechanism/s of intensification or deintensification of tropical cyclones will be determined after the seeding experiment analyses.

Keywords: aerosol, CCN, IN, tropical cylone

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Authors: Melissa C. LaDuke

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The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and spoke to either teacher-centered or student-centered educational practices within Defense Acquisitions University. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses, including the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Faris Tarlochan, Siva Mahesh Tangutooru

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Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies, each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 µm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral Geniculate Nucleus, visual cortex, finite element, glaucoma, neuroprostheses

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Authors: Anukriti Verma, Bhawna Rathi, Shivani Sharda

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Reactive Arthritis (ReA) is a disorder that causes inflammation in joints due to certain infections at distant sites in the body. ReA begins with stiffness, pain, and inflammation in these areas especially the ankles, knees, and hips. It gradually causes several complications such as conjunctivitis in the eyes, skin lesions in hand, feet and nails and ulcers in the mouth. Nowadays the diagnosis of ReA is based upon a differential diagnosis pattern. The parameters for differentiating ReA from other similar disorders include physical examination, history of the patient and a high index of suspicion. There are no standard lab tests or markers available for ReA hence the early diagnosis of ReA becomes difficult and the chronicity of disease increases with time. It is reported that enteric disorders such as Inflammatory Bowel Disease (IBD) that is inflammation in gastrointestinal tract namely Crohn’s Disease (CD) and Ulcerative Colitis (UC) are reported to be linked with ReA. Several microorganisms are found such as Campylobacter, Salmonella, Shigella and Yersinia causing IBD leading to ReA. The aim of our study was to perform the in-silico analysis in order to find interactions between microorganisms and human host causing IBD leading to ReA. A systems biology approach for metabolic network reconstruction and simulation was used to find the essential genes of the reported microorganisms. Interactomics study was used to find the interactions between the pathogen genes and human host. Genes such as nhaA (pathogen), dpyD (human), nagK (human) and kynU (human) were obtained that were analysed further using the functional, pathway and network analysis. These genes can be used as putative drug targets and biomarkers in future for early diagnosis, prevention, and treatment of IBD leading to ReA.

Keywords: drug targets, inflammatory bowel disease, reactive arthritis, systems biology

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: lexicon of disasters, modelling, Petri nets, text annotation, social disasters

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Authors: Manuela Nayantara Jeyaraj

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Information Technology (IT) is considered to be the prime contributor towards most of the energy releases and hence recursively impacting on the environmental Carbon Footprint on a major scale. The hostile effects brought about due to this massive carbon release such as global warming and ecosystem wipe-outs are currently being realized in Sri Lanka due to the rapid development and merging of computer based technologies. Sri Lanka, being a nature-rich island, has the undying need to preserve its natural environment hence resolving to better ‘Green IT’ practices in all possible spheres. Green IT implies the IT related practices for environmental sustainability. But the industrial divisions in Sri Lanka are still hesitant to fully realize the benefits of applying better “Green IT” principles due to considerations related to costs and other issues. In order to bring about a positive awareness of Green IT, the use of Smart Grids, which is yet a conceptualized principle within the Sri Lankan context, can be considered as a feasible proof in hand. This paper tends to analyze the feasibility of utilizing Smart Grids to ensure minimized cost and effects in preserving the environment hence ensuring Sustainable Green IT practices in an economically and technologically viable manner in Sri Lanka.

Keywords: green IT, industry, smart grid, Sri Lanka, sustainability

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Authors: Rodrigo Lentini, Beatrice Ionascu, Friederike A. Eyssel, Scandar Copti, Mohamad Eid

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The haptic modality has brought a new dimension to human computer interaction by engaging the human sense of touch. However, designing appropriate haptic stimuli, and in particular tactile stimuli, for various applications is still challenging. To tackle this issue, we present an intuitive system that facilitates the authoring of tactile gestures for various applications. The system transforms a hand gesture into a tactile gesture that can be rendering using a home-made haptic jacket. A case study is presented to demonstrate the ability of the system to develop tactile gestures that are recognizable by human subjects. Four tactile gestures are identified and tested to intensify the following four emotional responses: high valence – high arousal, high valence – low arousal, low valence – high arousal, and low valence – low arousal. A usability study with 20 participants demonstrated high correlation between the selected tactile gestures and the intended emotional reaction. Results from this study can be used in a wide spectrum of applications ranging from gaming to interpersonal communication and multimodal simulations.

Keywords: tactile stimulation, tactile gesture, emotion reactions, arousal, valence

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Authors: Ashish Bhattarai, Bishnu Bhatta, Hem Raj Joshi, Nabin Neupane, Pankaj Yadav

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This report concerns the design, development, and analysis of the combined Darrieus and Savonius wind turbine. Vertical Axis Wind Turbines (VAWT's) are of two type's viz. Darrieus (lift type) and Savonius (drag type). The problem associated with Darrieus is the lack of self-starting while Savonius has low efficiency. There are 3 straight Darrieus blades having the cross-section of NACA(National Advisory Committee of Aeronautics) 0018 placed circumferentially and a helically twisted Savonius blade to get even torque distribution. This unique design allows the use of Savonius as a method of self-starting the wind turbine, which the Darrieus cannot achieve on its own. All the parts of the wind turbine are designed in CAD software, and simulation data were obtained via CFD(Computational Fluid Dynamics) approach. Also, the design was imported to FlashForge Finder to 3D print the wind turbine profile and finally, testing was carried out. The plastic material used for Savonius was ABS(Acrylonitrile Butadiene Styrene) and that for Darrieus was PLA(Polylactic Acid). From the data obtained experimentally, the hybrid VAWT so fabricated has been found to operate at the low cut-in speed of 3 m/s and maximum power output has been found to be 7.5537 watts at the wind speed of 6 m/s. The maximum rpm of the rotor blade is recorded to be 431 rpm(rotation per minute) at the wind velocity of 6 m/s, signifying its potentiality of wind power production. Besides, the data so obtained from both the process when analyzed through graph plots has shown the similar nature slope wise. Also, the difference between the experimental and theoretical data obtained has shown mechanical losses. The objective is to eliminate the need for external motors for self-starting purposes and study the performance of the model. The testing of the model was carried out for different wind velocities.

Keywords: VAWT, Darrieus, Savonius, helical blades, CFD, flash forge finder, ABS, PLA

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Authors: Fatemeh Daneshvartarigh

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New technologies and applications have radically altered construction techniques in recent years. In order to anticipate how the building will act, perform, and appear, these technologies encompass a wide range of visualization, simulation, and analytic tools. These new technologies and applications have a considerable impact on completing construction projects in today's (architecture, engineering and construction)AEC industries. The rate of changes in BIM-related topics is different worldwide, and it depends on many factors, e.g., the national policies of each country. Therefore, there is a need for comprehensive research focused on a specific area with common characteristics. Therefore, one of the necessary measures to increase the use of this new approach is to examine the challenges and obstacles facing it. In this research, based on the Delphi method, at first, the background and related literature are reviewed. Then, using the knowledge obtained from the literature, a primary questionnaire is generated and filled by experts who are selected using snowball sampling. It covered the experts' attitudes towards implementing BIM in renovation projects and their view of the benefits and obstacles in this regard. By analyzing the primary questionnaire, the second group of experts is selected among the participants to be interviewed. The results are analyzed using Theme analysis. Six themes, including Management support, staff resistance, client willingness, Cost of software and implementation, the difficulty of implementation, and other reasons, are obtained. Then a final questionnaire is generated from the themes and filled by the same group of experts. The result is analyzed by the Fuzzy Delphi method, showing the exact ranking of the obtained themes. The final results show that management support, staff resistance, and client willingness are the most critical barrier to BIM usage in renovation projects.

Keywords: building information modeling, BIM, BIM implementation, BIM barriers, BIM in renovation

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Authors: Jonathan Martino, Kristof Harri

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In some cases, the increase in computing resources makes simulation methods more affordable. The increase in processing speed also allows real time analysis or even more rapid tests analysis offering a real tool for test prediction and design process optimization. Vibration tests are no exception to this trend. The so called ‘Virtual Vibration Testing’ offers solution among others to study the influence of specific loads, to better anticipate the boundary conditions between the exciter and the structure under test, to study the influence of small changes in the structure under test, etc. This article will first present a virtual vibration test modeling with a main focus on the shaker model and will afterwards present the experimental parameters determination. The classical way of modeling a shaker is to consider the shaker as a simple mechanical structure augmented by an electrical circuit that makes the shaker move. The shaker is modeled as a two or three degrees of freedom lumped parameters model while the electrical circuit takes the coil impedance and the dynamic back-electromagnetic force into account. The establishment of the equations of this model, describing the dynamics of the shaker, is presented in this article and is strongly related to the internal physical quantities of the shaker. Those quantities will be reduced into global parameters which will be estimated through experiments. Different experiments will be carried out in order to design an easy and practical method for the identification of the shaker parameters leading to a fully functional shaker model. An experimental modal analysis will also be carried out to extract the modal parameters of the shaker and to combine them with the electrical measurements. Finally, this article will conclude with an experimental validation of the model.

Keywords: lumped parameters model, shaker modeling, shaker parameters, state-space, virtual vibration

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Authors: Sedat Cereci

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This study investigates character of communication, evaluates communication and information need of people, handles relation between communication and contemporary technology, and emphasizes technological lack on communication education in many societies. To get information and communication are of main needs of people and people developed different instruments and technics to learn and to communicate in the past. Because of social need, communication became social matter and governments contributed facilities of communication and set communication places for people to meet and to communicate. Industrial Revolution and technological developments also contributed communication technics and proved numerous technological facilities for communication. Education in the world also use developed technology in any department and communication education especially necessities high technological facilities in schools. Many high schools and universities have communication departments and most of them use contemporary technological facilities, but they are not sufficient. Communication departments in educational organizations in Turkey have computer classrooms, monitors, cameras, microphones, telephones, different softwares, and others. However, despite all this, technological facilities and teaching methods are not sufficient because of contemporary developments. Technology develops rapidly due to hopes of people and technological facilities in education cannot catch developments and people always hope more.

Keywords: information, communication education, technology, technological lack, contemporary conditions, technics

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Authors: O. Rahli, N. Mimouni, R. Bennacer, K. Bouhadef

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This numerical study investigates the travelling wave’s appearance and the behavior of Poiseuille-Rayleigh-Benard (PRB) flow induced in 3D thermosolutale mixed convection (TSMC) in horizontal rectangular channels. The governing equations are discretized by using a control volume method with third order Quick scheme in approximating the advection terms. Simpler algorithm is used to handle coupling between the momentum and continuity equations. To avoid the excessively high computer time, full approximation storage (FAS) with full multigrid (FMG) method is used to solve the problem. For a broad range of dimensionless controlling parameters, the contribution of this work is to analyzing the flow regimes of the steady longitudinal thermoconvective rolls (noted R//) for both thermal and mass transfer (TSMC). The transition from the opposed volume forces to cooperating ones, considerably affects the birth and the development of the longitudinal rolls. The heat and mass transfers distribution are also examined.

Keywords: heat and mass transfer, mixed convection, poiseuille-rayleigh-benard flow, rectangular duct

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Authors: Siyao Zhu, Yifang Xu

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After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. The hands-free requirement from the first responders excludes the use of tedious manual control and operation. In unknown, unstructured, and obstructed environments, natural-language-based supervision is not amenable for first responders to formulate, and is difficult for robots to understand. Brain-computer interface is a promising option to overcome the limitations. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: consensus assessment, electroencephalogram, emergency response, human-robot collaboration, intention recognition, search and rescue

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Authors: Semayat Fanta, P.M. Mohite, C.S. Upadhyay

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Damage meso-model for laminates is one of the most widely applicable approaches for the analysis of damage induced in laminated fiber-reinforced polymeric composites. Damage meso-model for laminates has been developed over the last three decades by many researchers in experimental, theoretical, and analytical methods that have been carried out in micromechanics as well as meso-mechanics analysis approaches. It has been fundamentally developed based on the micromechanical description that aims to predict the damage initiation and evolution until the failure of structure in various loading conditions. The current damage meso-model for laminates aimed to act as a bridge between micromechanics and macro-mechanics of the laminated composite structure. This model considers two meso-constituents for the analysis of damage in ply and interface that imparted from low-velocity impact. The damages considered in this study include fiber breakage, matrix cracking, and diffused damage of the lamina, and delamination of the interface. The damage initiation and evolution in laminae can be modeled in terms of damaged strain energy density using damage parameters and the thermodynamic irreversible forces. Interface damage can be modeled with a new concept of spherical micro-void in the resin-rich zone of interface material. The damage evolution is controlled by the damage parameter (d) and the radius of micro-void (r) from the point of damage nucleation to its saturation. The constitutive martial model for meso-constituents is defined in a user material subroutine VUMAT and implemented in ABAQUS/Explicit finite element modeling tool. The model predicts the damages in the meso-constituents level very accurately and is considered the most effective technique of modeling low-velocity impact simulation for laminated composite structures.

Keywords: mesomodel, laminate, low-energy impact, micromechanics

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Prashant Dhiman, Viranshu Kumar, Pradeep Joshi

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Lot of research is going on to study the effect of cryogenic treatment on materials. Cryogenic treatment is a heat treatment process which is used widely to enhance the mechanical and metallurgical properties of various materials whether the material is ferrous or non ferrous. In almost all ferrous metals, it is found that retained austenite is converted into martensite. Generally deep cryogenic treatment is done using liquid nitrogen having temperature of -195 ℃. The austenite is unstable at this stage and converts into martensite. In non ferrous materials there presents a microcavity and under the action of stress it becomes crack. When this crack propagates, fracture takes place. As the metal contract under low temperature, by doing cryogenic treatment these microcavities will be filled hence increases the soundness of the material. Properties which are enhanced by cryogenic treatment of both ferrous and non ferrous materials are hardness, tensile strength, wear rate, electrical and thermal conductivity, and others. Also there is decrease in residual stress. A large number of manufacturing process (EDM, CNC etc.) are using cryogenic treatment on different tools or workpiece to reduce their wear. In this Review paper the use of cryogenic heat treatment in different manufacturing has been shown along with their advantages.

Keywords: cyrogenic treatment, EDM (Electrical Discharge Machining), CNC (Computer Numeric Control), Mechanical and Metallurgical Properties

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Authors: Kaznah Alshammari, Thomas Beach, Yacine Rezgui

Abstract:

Technological advances in the construction sector are helping to make smart cities a reality by means of cyber-physical systems (CPS). CPS integrate information and the physical world through the use of information communication technologies (ICT). An increasingly common goal in the built environment is to integrate building information models (BIM) with the Internet of Things (IoT) and sensor technologies using CPS. Future advances could see the adoption of digital twins, creating new opportunities for CPS using monitoring, simulation, and optimisation technologies. However, researchers often fail to fully consider the security implications. To date, it is not widely possible to assimilate BIM data and cybersecurity concepts, and, therefore, security has thus far been overlooked. This paper reviews the empirical literature concerning IoT applications in the built environment and discusses real-world applications of the IoT intended to enhance construction practices, people’s lives and bolster cybersecurity. Specifically, this research addresses two research questions: (a) how suitable are the current IoT and CPS security stacks to address the cybersecurity threats facing digital twins in the context of smart buildings and districts? and (b) what are the current obstacles to tackling cybersecurity threats to the built environment CPS? To answer these questions, this paper reviews the current state-of-the-art research concerning digital twins in the built environment, the IoT, BIM, urban cities, and cybersecurity. The results of these findings of this study confirmed the importance of using digital twins in both IoT and BIM. Also, eight reference zones across Europe have gained special recognition for their contributions to the advancement of IoT science. Therefore, this paper evaluates the use of digital twins in CPS to arrive at recommendations for expanding BIM specifications to facilitate IoT compliance, bolster cybersecurity and integrate digital twin and city standards in the smart cities of the future.

Keywords: BIM, cybersecurity, digital twins, IoT, urban cities

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Abbasali Abouei Mehrizi, Hao Wang

Abstract:

The thin film region is so important in heat transfer process due to its low thermal resistance. On the other hand, the dynamic contact angle is crucial boundary condition in numerical simulations. While different modeling contains different assumption of the microscopic contact angle, none of them has experimental evidence for their assumption, and the contact line movement mechanism still remains vague. The experimental investigation in complete wetting is more popular than partial wetting, especially in nanoscale resolution when there is sharp variation in thin film profile in partial wetting. In the present study, an experimental investigation of water film morphology near the triple phase contact line during the condensation is performed. The state-of-the-art tapping-mode atomic force microscopy (TM-AFM) was used to get the high-resolution film profile goes down to 2 nm from the contact line. The droplet was put in saturated chamber. The pristine silicon wafer was used as a smooth substrate. The substrate was heated by PI film heater. So the chamber would be over saturated by droplet evaporation. By turning off the heater, water vapor gradually started condensing on the droplet and the droplet advanced. The advancing speed was less than 20 nm/s. The dominant results indicate that in contrast to nonvolatile liquid, the film profile goes down straightly to the surface till 2 nm from the substrate. However, small bending has been observed below 20 nm, occasionally. So, it can be claimed that for the low condensation rate the microscopic contact angle equals to the optically detectable macroscopic contact angle. This result can be used to simplify the heat transfer modeling in partial wetting. The experimental result of the equality of microscopic and macroscopic contact angle can be used as a solid evidence for using this boundary condition in numerical simulation.

Keywords: advancing, condensation, microscopic contact angle, partial wetting

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

Abstract:

Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

Procedia PDF Downloads 259