Search results for: BIM service based cloud computing

Authors: Matthew T. McCarthy, Sarah Janse, Natalie M. Pizzimenti, Anthony K. Savino, Brian Crosser, Sean C. Rose

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Concussion is diagnosed clinically using a comprehensive history and exam, supported by ancillary testing. Frequently, symptom checklists are used as part of the evaluation of concussion. Existing symptom scales are based on a subjective Likert scale, without relation of symptoms to clinical or functional impairment. This is a retrospective review of 133 patients under age 30 seen in an outpatient neurology practice within 30 days of a probable or definite concussion. Each patient completed 2 symptom checklists at the initial visit – the SCAT-3 symptom evaluation (22 symptoms, 0-6 scale) and a scale based on the degree of clinical impairment for each symptom (22 symptoms, 0-3 scale related to functional impact of the symptom). Final clearance date was determined by the treating physician. 60.9% of patients were male with mean age 15.7 years (SD 2.3). Mean time from concussion to first visit was 6.9 days (SD 6.2), and 101 patients had definite concussions (75.9%), while 32 were diagnosed as probable (24.1%). 94 patients had a known clearance date (70.7%) with mean clearance time of 20.6 days (SD 18.6) and median clearance time of 19 days (95% CI 16-21). Mean total symptom score was 27.2 (SD 22.9) on the SCAT-3 and 14.7 (SD 11.9) for the functional impairment scale. Pearson’s correlation between the two scales was 0.98 (p < 0.001). After adjusting for patient and injury characteristics, an equivalent increase in score on each scale was associated with longer time to clearance (SCAT-3 hazard ratio 0.885, 95%CI 0.835-0.938, p < 0.001; functional impairment scale hazard ratio 0.851, 95%CI 0.802-0.902, p < 0.001). A concussion symptom scale based on degree of functional impairment correlates strongly with the SCAT-3 scale and demonstrates a similar association with time to clearance. By assessing the degree of impact on clinical functioning, this symptom scale reflects a more intuitive approach to rating symptoms and can be used in the management of concussion.

Keywords: checklist, concussion, neurology, scale, sports, symptoms

Procedia PDF Downloads 143

Authors: André Lages, Victor Dmitriev, Juliano Bazzo, Gianni Portela

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This work evaluates the feasibility of the graphene application to perform as a wideband reconfigurable material for lens antennas in 5G/6G and satellite applications. Based on transformation optics principles, the electromagnetic waves can be efficiently guided by modifying the effective refractive index. Graphene behavior can range between a lossy dielectric and a good conductor due to the variation of its chemical potential bias, thus arising as a promising solution for electromagnetic devices. The graphene properties and a lens antenna comprising multiples layers and periodic arrangements of graphene patches were analyzed using full-wave simulations. A dipole directivity was improved from 7 to 18.5 dBi at 29 GHz. In addition, the realized gain was enhanced 7 dB across a 14 GHz bandwidth within the Ka/5G band.

Keywords: 5G/6G, graphene, lens, reconfigurable, satellite

Procedia PDF Downloads 133

Authors: Katharina Fellnhofer, Kaisu Puumalainen

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Despite the current worldwide increasing interest in entrepreneurship education (EE), little attention has been paid to innovative web-based ways such as the narrative approach by telling individual stories of entrepreneurs via multimedia for demonstrating the impact on individuals towards entrepreneurship. In addition, this research discipline is faced with no consensus regarding its effective content of teaching materials and tools. Therefore, a qualitative hypothesis-generating research contribution is required to aim at drawing new insights from published works in the EE field of research to serve for future research related to multimedia entrepreneurial narratives. Based on this background, our effort will focus on finding support regarding following introductory statement: Multimedia success and failure stories of real entrepreneurs show potential to change perceptions towards entrepreneurship in a positive way. The proposed qualitative conceptual paper will introduce the underlying background for this research framework. Therefore, as a qualitative hypothesis-generating research contribution it aims at drawing new insights from published works in the EE field of research related to entrepreneurial narratives to serve for future research. With the means of the triangulation of multiple theories, we will utilize the foundation for multimedia-based entrepreneurial narratives applying a learning-through-multimedia-real-entrepreneurial-narratives pedagogical tool to facilitate entrepreneurship. Our effort will help to demystify how value-oriented entrepreneurs telling their stories multimedia can simultaneously enhance EE. Therefore, the paper will build new-fangled bridges between well-cited theoretical constructs to build a robust research framework. Overall, the intended contribution seeks to emphasize future research of currently under-researched issues in the EE sphere, which are considered to be essential not only to academia, as well as to business and society having future jobs-providing growth-oriented entrepreneurs in mind. The Authors would like to thank the Austrian Science Fund FWF: [J3740 – G27].

Keywords: entrepreneurship education, entrepreneurial attitudes and perceptions, entrepreneurial intention, entrepreneurial narratives

Procedia PDF Downloads 239

Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

Procedia PDF Downloads 157

Authors: Debdut Roy, Vidyasagar Guggilla

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In this research, we highlight our exploratory work on modified zeolite based catalysts for catalytic cracking of hydrocarbons for production of light olefin i.e. ethylene and propylene. The work is focused on understanding the catalyst structure and activity correlation. Catalysts are characterized by surface area and pore size distribution analysis, inductively coupled plasma optical emission spectrometry (ICP-OES), Temperature Programmed Desorption (TPD) of ammonia, pyridine Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Thermo-gravimetric Analysis (TGA) and correlated with the catalytic activity. It is observed that the yield of lighter olefins increases with increase of Bronsted acid strength.

Keywords: catalytic cracking, zeolite, propylene, structure-activity correlation

Procedia PDF Downloads 204

Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

Procedia PDF Downloads 135

Authors: Sikander Nawaz Khan

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Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information of natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provide precise and accurate locations and other related information like speed, track, direction and distance of target object to emergency responders. Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing vital role in disaster management. Early on Geographic Information System (GIS) was used to collect, arrange, and map the spatial information but now it has capability to analyze spatial data. This analytical ability of GIS is the main cause of its adaption by different emergency services providers like police and ambulance service. Full potential of these so called 3S technologies cannot be used in alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

Keywords: disaster mitigation, GIS, GPS, remote sensing

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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

Procedia PDF Downloads 307

Authors: Shafaq Rubab

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One of the biggest reasons of dropouts from schools is lack of motivation and interest among the students, particularly in mathematics. Many developing countries are facing this problem and this issue is lowering the literacy rate in these developing countries. The best solution for increasing motivation level and interest among the students is using tablet game-based learning. However, a pedagogically sound game required a well-planned instructional design model to enhance learner’s attention and confidence otherwise effectiveness of the learning games suffers badly. This research aims to evaluate the impact of the pedagogically sound instructional design model on students’ motivation by using tablet game-based learning. This research was conducted among the out-of-school-students having an age range from 7 to 12 years and the sample size of two hundred students was purposively selected without any gender discrimination. Qualitative research was conducted by using a survey tool named Instructional Material Motivational Survey (IMMS) adapted from Keller Arcs model. A comparison of results from both groups’ i.e. experimental group and control group revealed that motivation level of the students taught by the game was higher than the students instructed by using conventional methodologies. Experimental group’s students were more attentive, confident and satisfied as compared to the control group’s students. This research work not only promoted the trend of digital game-based learning in developing countries but also supported that a pedagogically sound instructional design model utilized in an educational game can increase the motivation level of the students and can make the learning process a totally immersive and interactive fun loving activity.

Keywords: digital game-based learning, student’s motivation, instructional design model, learning process

Procedia PDF Downloads 414

Authors: Arun K. Yadav, Adam J. Carroll, Gonzalo M. Estavillo, Greg J. Rebetzke, Barry J. Pogson

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Water limits crop productivity, so selecting for minimal yield-gap in drier environments is critical to mitigate against climate change and land-use pressures. To date, no markers measured in glasshouses have been reported to predict field-based drought tolerance. In the field, the best measure of drought tolerance is yield-gap; but this requires multisite trials that are an order of magnitude more resource intensive and can be impacted by weather variation. We investigated the responses of relative water content (RWC), stomatal conductance (gs), chlorophyll content and metabolites in flag leaves of commercial wheat (Triticum aestivum L.) cultivars to three drought treatments in the glasshouse and field environments. We observed strong genetic associations between glasshouse-based RWC, metabolites and Yield gap-based Drought Tolerance (YDT): the ratio of yield in water-limited versus well-watered conditions across 24 field environments spanning sites and seasons. Critically, RWC response to glasshouse drought was strongly associated with both YDT (r2 = 0.85, p < 8E-6) and RWC under field drought (r2 = 0.77, p < 0.05). Multiple regression analyses revealed that 98% of genetic YDT variance was explained by drought responses of four metabolites: serine, asparagine, methionine and lysine (R2 = 0.98; p < 0.01). Fitted coefficients suggested that, for given levels of serine and asparagine, stronger methionine and lysine accumulation was associated with higher YDT. Collectively, our results demonstrate that high-throughput, targeted metabolic phenotyping of glasshouse-grown plants may be an effective tool for the selection of wheat cultivars with high YDT in the field.

Keywords: drought stress, grain yield, metabolomics, stomatal conductance, wheat

Procedia PDF Downloads 252

Authors: Jincan Li, Mingyu Gao, Zhiwei He, Yuxiang Yang, Zhongfei Yu, Yuanyuan Liu

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Building an appropriate motion model is crucial for trajectory planning of robots and determines the operational quality directly. An adaptive acceleration and deceleration motion planning based on trigonometric functions for the end-effector of 6-DOF robots in Cartesian coordinate system is proposed in this paper. This method not only achieves the smooth translation motion and rotation motion by constructing a continuous jerk model, but also automatically adjusts the parameters of trigonometric functions according to the variable inputs and the kinematic constraints. The results of computer simulation show that this method is correct and effective to achieve the adaptive motion planning for linear trajectories.

Keywords: kinematic constraints, motion planning, trigonometric function, 6-DOF robots

Procedia PDF Downloads 255

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

Procedia PDF Downloads 481

Authors: Senthuran Manoharan, Rathesan Sivagananalingam

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One of the main issues in system security is Authentication. Authentication can be defined as the process of recognizing the user's identity and it is the most important step in the access control process to safeguard data/resources from being accessed by unauthorized users. The static method of authentication cannot ensure the genuineness of the user. Due to this reason, more innovative authentication mechanisms came into play. At first two factor authentication was introduced and later, multi-factor authentication was introduced to enhance the security of the system. It also had some issues and later, adaptive authentication was introduced. In this research paper, the design of an adaptive authentication engine was put forward. The user risk profile was calculated based on the user parameters and then the user was challenged with a suitable authentication method.

Keywords: authentication, adaptive authentication, machine learning, security

Procedia PDF Downloads 226

Authors: Smrity Dwivedi

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The present paper has revealed the effect of double substrates over a bandwidth performance for planar antennas. The used material has its own importance to get minimum return loss and improved directivity. The author has taken double substrates to enhance the efficiency in terms of gain of antenna. Metamaterial based antenna has its own specific structure which increased the performance of antenna. Improved return loss is -20 dB, and the voltage standing wave ratio (VSWR) is 1.2, which is better than single substrate having return loss of -15 dB and VSWR of 1.4. Complete results are obtained using commercial software CST microwave studio.

Keywords: CST microwave studio, metamaterial, return loss, VSWR

Procedia PDF Downloads 382

Authors: Seyedeh Mozhgan Seyed-Talebi, Javad Beheshtian

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The toxicity of lead associated with the lifecycle of perovskite solar cells (PSCs( is a serious concern which may prove to be a major hurdle in the path toward their commercialization. The current proposed lead-free PSCs including Ag(I), Bi(III), Sb(III), Ti(IV), Ge(II), and Sn(II) low-toxicity cations are still plagued with the critical issues of poor stability and low efficiency. This is mainly because of their chemical stability. In the present research, utilization of all inorganic CsSnGeI₃ based materials offers the advantages to enhance resistance of device to degradation, reduce the cost of cells, and minimize the carrier recombination. The presence of inorganic halide perovskite improves the photovoltaic parameters of PCSs via improved surface coverage and stability. The inverted structure of simulated devices using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves TCOHTL/Perovskite/ETL/Au contact layer. PEDOT:PSS, PCBM, and CsSnGeI₃ used as hole transporting layer (HTL), electron transporting layer (ETL), and perovskite absorber layer in the inverted structure for the first time. The holes are injected from highly stable and air tolerant Sn_0.5Ge_0.5I₃ perovskite composition to HTM and electrons from the perovskite to ETL. Simulation results revealed a great dependence of power conversion efficiency (PCE) on the thickness and defect density of perovskite layer. Here the effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnGeI₃ based perovskite devices is investigated. Comparison between simulated CsSnGeI₃ based PCSs and similar real testified devices with spiro-OMeTAD as HTL showed that the extraction of carriers at the interfaces of perovskite absorber depends on the energy level mismatches between perovskite and HTL/ETL. We believe that optimization results reported here represent a critical avenue for fabricating the stable, low-cost, efficient, and eco-friendly all-inorganic Cs-Sn-Ge based lead-free perovskite devices.

Keywords: hole transporting layer, lead-free, perovskite solar cell, SCAPS-1D, Sn-Ge based

Procedia PDF Downloads 143

Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

Procedia PDF Downloads 136

Authors: Arun Prabhakar

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Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

Procedia PDF Downloads 128

Authors: N. Stevulova, I. Schwarzova

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The possibility of using industrial hemp as a source of natural fibers for purpose of construction, mainly for the preparation of lightweight composites based on hemp hurds is described. In this article, an overview of measurement results of important technical parameters (compressive strength, density, thermal conductivity) of composites based on organic filler - chemically modified hemp hurds in three solutions (EDTA, NaOH and Ca(OH)2) and inorganic binder MgO-cement after 7, 28, 60, 90 and 180 days of hardening is given. The results of long-term water storage of 28 days hardened composites at room temperature were investigated. Changes in the properties of composites caused by chemical treatment of hemp material are discussed.

Keywords: hemp hurds, chemical modification, lightweight composites, testing material properties

Procedia PDF Downloads 339

Authors: Jonathan A. Sánchez Muñoz, Gustavo Flores Eraña, Juan M. Silva

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Mexican Mezcal industry has reached attention during the last decade due to it has been a popular beverage demanded by North American and European markets, reaching popularity due to its crafty character. Despite its wide demand, productive processes are still made with rudimentary equipment, and there is a lack of evidence to improve kiln energy efficiency. Tec21 is a challenge-based learning curricular model implemented by Tecnológico de Monterrey since 2019, where each formation unit requires an industrial partner. “Problem processes solution” is a formation unity designed for mechatronics engineers, where students apply the acquired knowledge in thermofluids and apply electronic. During five weeks, students are immersed in an industrial problem to obtain a proper level of competencies according to formation unit designers. This work evaluates the competencies acquired by the student through qualitative research methodology. Several evaluation instruments (report, essay, and poster) were selected to evaluate etic argumentation, principles of sustainability, implemented actions, process modelling, and redesign feasibility.

Keywords: applied electronic, challenge based learning, competencies, mezcal industry, thermofluids

Procedia PDF Downloads 110

Authors: Akanksha Pareek

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The Indian Handloom clusters are known for its tradition and heritage of excellent craftsmanship. The design development of Indian handloom clusters are oriented on traditionally dobby and jacquard design. This comprehensive paper proposes practises on handloom woven design based on primary colour gradation with the help of basic weaved on four shaft. The innovative design ideas are inspired from Nature and transferred into the handloom samples to achieve colour gradation with primary colours. In this paper, design methodology where in woven samples are strategically designed in such way that traditional knowledge of the weavers will be oriented to leveraged their skills.

Keywords: handloom, weaving, colour gradation, shaft

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: M. J. Park, S. H. Lee, C. H. Lee, O. M. Kwon

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This paper studies a secondary voltage control framework of the microgrids based on the consensus for a communication network of multiagent. The proposed control is designed by the communication network with one-way links. The communication network is modeled by a directed graph. At this time, the concept of sampling is considered as the communication constraint among each distributed generator in the microgrids. To analyze the sampling effects on the secondary voltage control of the microgrids, by using Lyapunov theory and some mathematical techniques, the sufficient condition for such problem will be established regarding linear matrix inequality (LMI). Finally, some simulation results are given to illustrate the necessity of the consideration of the sampling effects on the secondary voltage control of the microgrids.

Keywords: microgrids, secondary control, multiagent, sampling, LMI

Procedia PDF Downloads 318

Authors: Kumiko Inagaki

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Qualitative changes to the undergraduate education have recently become the focus of attention in Japan. This is occurring against the backdrop of declining birthrate and increasing university enrollment, as well as drastic societal changes of advance toward globalization and a knowledge-based society. This paper describes the cases of Japanese universities that promoted various forms of experiential learning around the theme of social participation. The opportunity of learning through practical experience, where students turn their attention to social problems and take pains to consider means of resolving them, creates opportunities to demonstrate “human power” applicable to all sorts of activities the following graduation, thereby guaranteeing students’ continuous growth throughout their careers.

Keywords: career education, experiential learning, subjective learning, university education

Procedia PDF Downloads 297

Authors: Godwin Chigozie Okpara, Eugine Iheanacho

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The paper set out to assess the sustainability of debt in the Nigerian economy. Precisely, it sought to determine the level of debt sustainability and its impact on the growth of the economy; whether internationalization of capital market has positively influenced debt sustainability’s impact on economic growth; and to ascertain the direction of causality between external debt sustainability and the growth of GDP. In the light of these objectives, ratio analysis was employed for the determination of debt sustainability. Our findings revealed that the periods 1986 – 1994 and 1999 – 2004 were periods of severe unsustainable borrowing. The unit root test showed that the variables of the growth model were integrated of order one, I(1) and the cointegration test provided evidence for long run stability. Considering the dawn of internationalization of capital market, the researcher employed the structural break approach using Chow Breakpoint test on the vector error correction model (VECM). The result of VECM showed that debt sustainability, measured by debt to GDP ratio exerts negative and significant impact on the growth of the economy while debt burden measured by debt-export ratio and debt service export ratio are negative though insignificant on the growth of GDP. The Cho test result indicated that internationalization of capital market has no significant effect on the debt overhang impact on the growth of the Economy. The granger causality test indicates a feedback effect from economic growth to debt sustainability growth indicators. On the bases of these findings, the researchers made some necessary recommendations which if followed religiously will go a long way to ameliorating debt burdens and engendering economic growth.

Keywords: debt sustainability, internalization, capital market, cointegration, chow test

Procedia PDF Downloads 420

Authors: Jiahao Cui

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In the past centuries, due to climate change and intense whaling, the global whale population has dramatically declined. Among the various whale species, the fin whale experienced the most drastic drop in number due to its popularity in whaling. Under this background, identifying fin whale calls could be immensely beneficial to the preservation of the species. This paper uses feature extraction to process the input audio signal, then a network based on AlexNet and three networks based on the ResNet model was constructed to classify fin whale calls. A mixture of the DOSITS database and the Watkins database was used during training. The results demonstrate that a modified ResNet network has the best performance considering precision and network complexity.

Keywords: convolutional neural network, ResNet, AlexNet, fin whale preservation, feature extraction

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Authors: Amalia Sholihati, Bambang Riyanto Trilaksono

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As an island nation, is a necessity for the Republic of Indonesia to have a capable military defense on land, sea or air that the development of military weapons such as rockets for air defense becomes very important. RKX rocket-200 is one of the guided missiles which are developed by consortium Indonesia and coordinated by LAPAN that serve to intercept the target. RKX-200 is designed to have the speed of Mach 0.5-0.9. RKX rocket-200 belongs to the category two-stage rocket that control is carried out on the second stage when the rocket has separated from the booster. The requirement for better performance to intercept missiles with higher maneuverability continues to push optimal guidance law development, which is derived from non-linear equations. This research focused on the design and implementation of a guidance system based OGL on the rocket RKX-200 while considering the limitation of rockets such as aerodynamic rocket and actuator. Guided missile control system has three main parts, namely, guidance system, navigation system and autopilot systems. As for other parts such as navigation systems and other supporting simulated on MATLAB based on the results of previous studies. In addition to using the MATLAB simulation also conducted testing with hardware-based ARM TWR-K60D100M conjunction with a navigation system and nonlinear models in MATLAB using Hardware-in-the-Loop Simulation (HILS).

Keywords: RKX-200, guidance system, optimal guidance law, Hils

Procedia PDF Downloads 240

Authors: Bahar Ayhan

Abstract:

The present paper is concerned with the numerical modeling of the inelastic behavior of the anisotropically damaged ductile materials, which are based on a generalized macroscopic theory within the framework of continuum damage mechanics. Kinematic decomposition of the strain rates into elastic, plastic and damage parts is basis for accomplishing the structure of continuum theory. The evolution of the damage strain rate tensor is detailed with the consideration of anisotropic effects. Helmholtz free energy functions are constructed separately for the elastic and inelastic behaviors in order to be able to address the plastic and damage process. Additionally, the constitutive structure, which is based on the standard dissipative material approach, is elaborated with stress tensor, a yield criterion for plasticity and a fracture criterion for damage besides the potential functions of each inelastic phenomenon. The finite element method is used to approximate the linearized variational problem. Stress and strain outcomes are solved by using the numerical integration algorithm based on operator split methodology with a plastic and damage (multiplicator) variable separately. Numerical simulations are proposed in order to demonstrate the efficiency of the formulation by comparing the examples in the literature.

Keywords: anisotropic damage, finite element method, plasticity, coupling

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Authors: Davoud Ansari Kejal, Meysam Sabour

Abstract:

For long, there has been a belief that a reader can easily comprehend a text if he is strong enough in vocabulary and grammatical knowledge but there was no account for the ability of understanding different subjects based on readers’ understanding of the surrounding world which is called world background knowledge. This paper attempts to investigate the reading comprehension process applying the schema theory as an influential factor in comprehending texts, in order to prove the important role of background knowledge in reading comprehension. Based on the discussion, some teaching methods are suggested for employing world background knowledge for an elaborated teaching of reading comprehension in an active learning environment in EFL classes.

Keywords: background knowledge, reading comprehension, schema theory, ELT classes

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Authors: Natalia Marulanda, Henry González, Gonzalo León, Alejandro Hincapié

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Continuous improvement tools are the result of a set of studies that developed theories and methodologies. These methodologies enable organizations to increase their levels of efficiency, effectiveness, and productivity. Based on these methodologies, lean manufacturing philosophy, which is based on the optimization of resources, waste disposal, and generation of value to products and services, was developed. Lean application has been massive globally, but Colombian companies have been made it incipiently. Therefore, the purpose of this article is to identify the impacts generated by the implementation of lean manufacturing tools in five companies located in Colombia and Medellín metropolitan area. It also seeks to make a comparison of the results obtained from the implementation of lean philosophy and Theory of Constraints. The methodology is qualitative and quantitative, is based on the case study interview from dialogue with the leaders of the processes that used lean tools. The most used tools by research companies are 5's with 100% and TPM with 80%. The less used tool is the synchronous production with 20%. The main reason for the implementation of lean was supply chain management with 83.3%. For the application of lean and TOC, we did not find significant differences between the impact, in terms of methodology, areas of application, staff initiatives, supply chain management, planning, and training.

Keywords: business strategy, lean manufacturing, theory of constraints, supply chain

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Authors: Dorsaf Ben Malek

Abstract:

The function of culture in language teaching changed because of globalization and the latest technologies. English became a lingua franca which resulted in altering the teaching objectives. The re-evaluation of cultural awareness is one of them. Business English teaching has also been subject to all these changes. It is therefore a wrong idea if we try to consider it as a diffusion of unlimited listing of lexis, diagrams, charts, and statistics. In fact, business students’ future career will require business terminology together with intercultural communicative competence (ICC) to handle different multicultural encounters and contribute to the international community. The first part of this paper is dedicated to the necessity of empowering business students with intercultural communicative competence and the second turns around the potential of multicultural literature in implementing ICC in business English teaching. This was proved through a qualitative action research done on a group of Tunisian MA business students. It was an opportunity to discover the potential of multicultural literature together with inquiry-based learning in enhancing business students’ intercultural communicative competence. Data were collected through classroom observations, journals and semi-structured interviews. Results were in favour of using multicultural literature to enhance business students’ ICC. In addition, the short story may be a motivating tool to read literature, and inquiry-based learning can be an effective approach to teaching literature.

Keywords: intercultural communicative competence, multicultural literature, short stories, inquiry-based learning

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