Search results for: OS based virtualization
26842 Design of Bayesian MDS Sampling Plan Based on the Process Capability Index
Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi
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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach
Procedia PDF Downloads 29226841 Real-Time Network Anomaly Detection Systems Based on Machine-Learning Algorithms
Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez
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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.Keywords: temporal graph network, anomaly detection, cyber security, IDS
Procedia PDF Downloads 9226840 Collision Avoidance Based on Model Predictive Control for Nonlinear Octocopter Model
Authors: Doğan Yıldız, Aydan Müşerref Erkmen
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The controller of the octocopter is mostly based on the PID controller. For complex maneuvers, PID controllers have limited performance capability like in collision avoidance. When an octocopter needs avoidance from an obstacle, it must instantly show an agile maneuver. Also, this kind of maneuver is affected severely by the nonlinear characteristic of octocopter. When these kinds of limitations are considered, the situation is highly challenging for the PID controller. In the proposed study, these challenges are tried to minimize by using the model predictive controller (MPC) for collision avoidance with a nonlinear octocopter model. The aim is to show that MPC-based collision avoidance has the capability to deal with fast varying conditions in case of obstacle detection and diminish the nonlinear effects of octocopter with varying disturbances.Keywords: model predictive control, nonlinear octocopter model, collision avoidance, obstacle detection
Procedia PDF Downloads 18126839 A Framework Based on Dempster-Shafer Theory of Evidence Algorithm for the Analysis of the TV-Viewers’ Behaviors
Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi
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In this paper, we propose an approach of detecting the behavior of the viewers of a TV program in a non-controlled environment. The experiment we propose is based on the use of three types of connected objects (smartphone, smart watch, and a connected remote control). 23 participants were observed while watching their TV programs during three phases: before, during and after watching a TV program. Their behaviors were detected using an approach based on The Dempster Shafer Theory (DST) in two phases. The first phase is to approximate dynamically the mass functions using an approach based on the correlation coefficient. The second phase is to calculate the approximate mass functions. To approximate the mass functions, two approaches have been tested: the first approach was to divide each features data space into cells; each one has a specific probability distribution over the behaviors. The probability distributions were computed statistically (estimated by empirical distribution). The second approach was to predict the TV-viewing behaviors through the use of classifiers algorithms and add uncertainty to the prediction based on the uncertainty of the model. Results showed that mixing the fusion rule with the computation of the initial approximate mass functions using a classifier led to an overall of 96%, 95% and 96% success rate for the first, second and third TV-viewing phase respectively. The results were also compared to those found in the literature. This study aims to anticipate certain actions in order to maintain the attention of TV viewers towards the proposed TV programs with usual connected objects, taking into account the various uncertainties that can be generated.Keywords: Iot, TV-viewing behaviors identification, automatic classification, unconstrained environment
Procedia PDF Downloads 22326838 Artificial Intelligence Methods for Returns Expectations in Financial Markets
Authors: Yosra Mefteh Rekik, Younes Boujelbene
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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation
Procedia PDF Downloads 43726837 Hand Gestures Based Emotion Identification Using Flex Sensors
Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan
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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.Keywords: emotion identification, emotion models, gesture recognition, user perception
Procedia PDF Downloads 27426836 Double Gaussian Distribution of Nonhomogeneous Barrier Height in Metal/n-type GaN Schottky Contacts
Authors: M. Mamor
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GaN-based compounds have attracted much interest in the fabrication of high-power, high speed and high-frequency electronic devices. Other examples of GaN-based applications are blue and ultraviolet (UV) light-emitting diodes (LEDs). All these devices require high-quality ohmic and Schottky contacts. Gaining an understanding of the electrical characteristics of metal/GaN contacts is of fundamental and technological importance for developing GaN-based devices. In this work, the barrier characteristics of Pt and Pd Schottky contacts on n-type GaN were studied using temperature-dependent forward current-voltage (I-V) measurements over a wide temperature range 80–400 K. Our results show that the barrier height and ideality factor, extracted from the forward I-V characteristics based on thermionic emission (TE) model, exhibit an abnormal dependence with temperature; i.e., by increasing temperature, the barrier height increases whereas the ideality factor decreases. This abnormal behavior has been explained based on the TE model by considering the presence of double Gaussian distribution (GD) of nonhomogeneous barrier height at the metal/GaN interface. However, in the high-temperature range (160-400 K), the extracted value for the effective Richardson constant A* based on the barrier inhomogeneity (BHi) model is found in fair agreement with the theoretically predicted value of about 26.9 A.cm-2 K-2 for n-type GaN. This result indicates that in this temperature range, the conduction current transport is dominated by the thermionic emission mode. On the other hand, in the lower temperature range (80-160 K), the corresponding effective Richardson constant value according to the BHi model is lower than the theoretical value, suggesting the presence of other current transport, such as tunneling-assisted mode at lower temperatures.Keywords: Schottky diodes, inhomogeneous barrier height, GaN semiconductors, Schottky barrier heights
Procedia PDF Downloads 4726835 Optimal Trajectories for Highly Automated Driving
Authors: Christian Rathgeber, Franz Winkler, Xiaoyu Kang, Steffen Müller
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In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results.Keywords: trajectory planning, direct method, indirect method, highly automated driving
Procedia PDF Downloads 52326834 Determination of Cohesive Zone Model’s Parameters Based On the Uniaxial Stress-Strain Curve
Authors: Y. J. Wang, C. Q. Ru
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A key issue of cohesive zone models is how to determine the cohesive zone model (CZM) parameters based on real material test data. In this paper, uniaxial nominal stress-strain curve (SS curve) is used to determine two key parameters of a cohesive zone model: the maximum traction and the area under the curve of traction-separation law (TSL). To this end, the true SS curve is obtained based on the nominal SS curve, and the relationship between the nominal SS curve and TSL is derived based on an assumption that the stress for cracking should be the same in both CZM and the real material. In particular, the true SS curve after necking is derived from the nominal SS curve by taking the average of the power law extrapolation and the linear extrapolation, and a damage factor is introduced to offset the true stress reduction caused by the voids generated at the necking zone. The maximum traction of the TSL is equal to the maximum true stress calculated based on the damage factor at the end of hardening. In addition, a simple specimen is simulated by Abaqus/Standard to calculate the critical J-integral, and the fracture energy calculated by the critical J-integral represents the stored strain energy in the necking zone calculated by the true SS curve. Finally, the CZM parameters obtained by the present method are compared to those used in a previous related work for a simulation of the drop-weight tear test.Keywords: dynamic fracture, cohesive zone model, traction-separation law, stress-strain curve, J-integral
Procedia PDF Downloads 50526833 Human Performance Evaluating of Advanced Cardiac Life Support Procedure Using Fault Tree and Bayesian Network
Authors: Shokoufeh Abrisham, Seyed Mahmoud Hossieni, Elham Pishbin
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In this paper, a hybrid method based on the fault tree analysis (FTA) and Bayesian networks (BNs) are employed to evaluate the team performance quality of advanced cardiac life support (ACLS) procedures in emergency department. According to American Heart Association (AHA) guidelines, a category relying on staff action leading to clinical incidents and also some discussions with emergency medicine experts, a fault tree model for ACLS procedure is obtained based on the human performance. The obtained FTA model is converted into BNs, and some different scenarios are defined to demonstrate the efficiency and flexibility of the presented model of BNs. Also, a sensitivity analysis is conducted to indicate the effects of team leader presence and uncertainty knowledge of experts on the quality of ACLS. The proposed model based on BNs shows that how the results of risk analysis can be closed to reality comparing to the obtained results based on only FTA in medical procedures.Keywords: advanced cardiac life support, fault tree analysis, Bayesian belief networks, numan performance, healthcare systems
Procedia PDF Downloads 14026832 A Corpus-Based Study on the Styles of Three Translators
Authors: Wang Yunhong
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The present paper is preoccupied with the different styles of three translators in their translating a Chinese classical novel Shuihu Zhuan. Based on a parallel corpus, it adopts a target-oriented approach to look into whether and what stylistic differences and shifts the three translations have revealed. The findings show that the three translators demonstrate different styles concerning their word choices and sentence preferences, which implies that identification of recurrent textual patterns may be a basic step for investigating the style of a translator.Keywords: corpus, lexical choices, sentence characteristics, style
Procedia PDF Downloads 25726831 Automatic Multi-Label Image Annotation System Guided by Firefly Algorithm and Bayesian Method
Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat
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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.Keywords: feature extraction, feature selection, image annotation, classification
Procedia PDF Downloads 57826830 Optimization Based Extreme Learning Machine for Watermarking of an Image in DWT Domain
Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA
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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.Keywords: BER, DWT, extreme leaning machine (ELM), PSNR
Procedia PDF Downloads 30226829 Control of Grid Connected PMSG-Based Wind Turbine System with Back-To-Back Converter Topology Using Resonant Controller
Authors: Fekkak Bouazza, Menaa Mohamed, Loukriz Abdelhamid, Krim Mohamed L.
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This paper presents modeling and control strategy for the grid connected wind turbine system based on Permanent Magnet Synchronous Generator (PMSG). The considered system is based on back-to-back converter topology. The Grid Side Converter (GSC) achieves the DC bus voltage control and unity power factor. The Machine Side Converter (MSC) assures the PMSG speed control. The PMSG is used as a variable speed generator and connected directly to the turbine without gearbox. The pitch angle control is not either considered in this study. Further, Optimal Tip Speed Ratio (OTSR) based MPPT control strategy is used to ensure the most energy efficiency whatever the wind speed variations. A filter (L) is put between the GSC and the grid to reduce current ripple and to improve the injected power quality. The proposed grid connected wind system is built under MATLAB/Simulink environment. The simulation results show the feasibility of the proposed topology and performance of its control strategies.Keywords: wind, grid, PMSG, MPPT, OTSR
Procedia PDF Downloads 35326828 The Design of Intelligent Passenger Organization System for Metro Stations Based on Anylogic
Authors: Cheng Zeng, Xia Luo
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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization
Procedia PDF Downloads 16526827 The Experience of Community-based Tourism in Yunguilla, Ecuador and Its Social-Cultural Impact
Authors: York Neudel
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The phenomenon of tourism has been considered as tool to overcome cultural frontiers, to comprehend the other and to cope with mutual mistrust and suspicion. Well, that has been a myth, at least when it comes to mass-tourism. Other approaches, like community-based tourism, still are based on the idea of embracing the other in order to help or to understand the cultural difference. In 1997, two American NGOs incentivized a tourism-project in a community in the highlands of Ecuador, in order to protect the cloud forest from destructive exploitation of its own inhabitants. Nineteen years after that, I analyze in this investigation the interactions between the Ecuadorian hosts in the mestizo-community of Yunguilla and the foreign tourist in the quest for “authentic life” in the Ecuadorian cloud forest. As a sort of “contemporary pilgrim” the traveller tries to find authenticity in other times and places far away from their everyday life in Europe or North America. Therefore, tourists are guided by stereotypes and expectations that are produced by the touristic industry. The host, on the other hand, has to negotiate this pre-established imaginary. That generates a kind of theatre-play with front- and backstage in organic gardens, little fabrics and even private housing, since this alternative project offers to share the private space of the host with the tourist in the setting the community-based tourism. In order to protect their privacy, the community creates new hybrid spaces that oscillate between front- and backstages that culminates in a game of hide and seek – a phenomenon that promises interesting frictions for an anthropological case-study.Keywords: Tourism, Authenticity, Community-based tourism, Ecuador, Yunguilla
Procedia PDF Downloads 27626826 Study on Construction of 3D Topography by UAV-Based Images
Authors: Yun-Yao Chi, Chieh-Kai Tsai, Dai-Ling Li
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In this paper, a method of fast 3D topography modeling using the high-resolution camera images is studied based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D) urban landscape modeling. Firstly, the existing high-resolution digital camera with special design of overlap images is designed by reconstructing and analyzing the auto-flying paths of UAVs, which improves the self-calibration function to achieve the high precision imaging by software, and further increased the resolution of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of urban land surfaces and the texture extraction. Finally, the aerial photography and 3D topography construction are both developed in campus of Chang-Jung University and in Guerin district area in Tainan, Taiwan, provide authentication model for construction of 3D topography based on combined UAV-based camera images from system. The results demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D topography production, and the technology solution in this paper offers a new, fast, and technical plan for the 3D expression of the city landscape, fine modeling and visualization.Keywords: 3D, topography, UAV, images
Procedia PDF Downloads 29726825 Development of a Few-View Computed Tomographic Reconstruction Algorithm Using Multi-Directional Total Variation
Authors: Chia Jui Hsieh, Jyh Cheng Chen, Chih Wei Kuo, Ruei Teng Wang, Woei Chyn Chu
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Compressed sensing (CS) based computed tomographic (CT) reconstruction algorithm utilizes total variation (TV) to transform CT image into sparse domain and minimizes L1-norm of sparse image for reconstruction. Different from the traditional CS based reconstruction which only calculates x-coordinate and y-coordinate TV to transform CT images into sparse domain, we propose a multi-directional TV to transform tomographic image into sparse domain for low-dose reconstruction. Our method considers all possible directions of TV calculations around a pixel, so the sparse transform for CS based reconstruction is more accurate. In 2D CT reconstruction, we use eight-directional TV to transform CT image into sparse domain. Furthermore, we also use 26-directional TV for 3D reconstruction. This multi-directional sparse transform method makes CS based reconstruction algorithm more powerful to reduce noise and increase image quality. To validate and evaluate the performance of this multi-directional sparse transform method, we use both Shepp-Logan phantom and a head phantom as the targets for reconstruction with the corresponding simulated sparse projection data (angular sampling interval is 5 deg and 6 deg, respectively). From the results, the multi-directional TV method can reconstruct images with relatively less artifacts compared with traditional CS based reconstruction algorithm which only calculates x-coordinate and y-coordinate TV. We also choose RMSE, PSNR, UQI to be the parameters for quantitative analysis. From the results of quantitative analysis, no matter which parameter is calculated, the multi-directional TV method, which we proposed, is better.Keywords: compressed sensing (CS), low-dose CT reconstruction, total variation (TV), multi-directional gradient operator
Procedia PDF Downloads 24726824 Improved Hash Value Based Stream CipherUsing Delayed Feedback with Carry Shift Register
Authors: K. K. Soundra Pandian, Bhupendra Gupta
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In the modern era, as the application data’s are massive and complex, it needs to be secured from the adversary attack. In this context, a non-recursive key based integrated spritz stream cipher with the circulant hash function using delayed feedback with carry shift register (d-FCSR) is proposed in this paper. The novelty of this proposed stream cipher algorithm is to engender the improved keystream using d-FCSR. The proposed algorithm is coded using Verilog HDL to produce dynamic binary key stream and implemented on commercially available FPGA device Virtex 5 xc5vlx110t-2ff1136. The implementation of stream cipher using d-FCSR on the FPGA device operates at a maximum frequency of 60.62 MHz. It achieved the data throughput of 492 Mbps and improved in terms of efficiency (throughput/area) compared to existing techniques. This paper also briefs the cryptanalysis of proposed circulant hash value based spritz stream cipher using d-FCSR is against the adversary attack on a hardware platform for the hardware based cryptography applications.Keywords: cryptography, circulant function, field programmable gated array, hash value, spritz stream cipher
Procedia PDF Downloads 24026823 A Constrained Neural Network Based Variable Neighborhood Search for the Multi-Objective Dynamic Flexible Job Shop Scheduling Problems
Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir
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In this paper, a new neural network based variable neighborhood search is proposed for the multi-objective dynamic, flexible job shop scheduling problems. The neural network controls the problems' constraints to prevent infeasible solutions, while the Variable Neighborhood Search (VNS) applies moves, based on the critical block concept to improve the solutions. Two approaches are used for managing the constraints, in the first approach, infeasible solutions are modified according to the constraints, after the moves application, while in the second one, infeasible moves are prevented. Several neighborhood structures from the literature with some modifications, also new structures are used in the VNS. The suggested neighborhoods are more systematically defined and easy to implement. Comparison is done based on a multi-objective flexible job shop scheduling problem that is dynamic because of the jobs different release time and machines breakdowns. The results show that the presented method has better performance than the compared VNSs selected from the literature.Keywords: constrained optimization, neural network, variable neighborhood search, flexible job shop scheduling, dynamic multi-objective optimization
Procedia PDF Downloads 33726822 Gamification Teacher Professional Development: Engaging Language Learners in STEMS through Game-Based Learning
Authors: Karen Guerrero
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Kindergarten-12th grade teachers engaged in teacher professional development (PD) on game-based learning techniques and strategies to support teaching STEMSS (STEM + Social Studies with an emphasis on geography across the curriculum) to language learners. Ten effective strategies have supported teaching content and language in tandem. To provide exiting teacher PD on summer and spring breaks, gamification has integrated these strategies to engage linguistically diverse student populations to provide informal language practice while students engage in the content. Teachers brought a STEMSS lesson to the PD, engaged in a wide variety of games (dice, cards, board, physical, digital, etc.), critiqued the games based on gaming elements, then developed, brainstormed, presented, piloted, and published their game-based STEMSS lessons to share with their colleagues. Pre and post-surveys and focus groups were conducted to demonstrate an increase in knowledge, skills, and self-efficacy in using gamification to teach content in the classroom. Provide an engaging strategy (gamification) to support teaching content and language to linguistically diverse students in the K-12 classroom. Game-based learning supports informal language practice while developing academic vocabulary utilized in the game elements/content focus, building both content knowledge through play and language development through practice. The study also investigated teacher's increase in knowledge, skills, and self-efficacy in using games to teach language learners. Mixed methods were used to investigate knowledge, skills, and self-efficacy prior to and after the gamification teacher training (pre/post) and to understand the content and application of developing and utilizing game-based learning to teach. This study will contribute to the body of knowledge in applying game-based learning theories to the K-12 classroom to support English learners in developing English skills and STEMSS content knowledge.Keywords: gamification, teacher professional development, STEM, English learners, game-based learning
Procedia PDF Downloads 7326821 Promoting Teaching and Learning Structures Based on Innovation and Entrepreneurship in Valahia University of Targoviste
Authors: Gabriela Teodorescu, Ioana Daniela Dulama
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In an ever-changing society, the education system needs to constantly evolve to meet market demands. During its 30 years of existence, Valahia University of Targoviste (VUT) tried to offer its students a series of teaching-learning schemes that would prepare them for a remarkable career. In VUT, the achievement of performance through innovation can be analyzed by reference to several key indicators (i.e., university climate, university resources, and innovative methods applied to classes), but it is possible to differentiate between activities in the classic format: participate to courses; interactive seminars and tutorials; laboratories, workshops, project-based learning; entrepreneurial activities, through simulated enterprises; mentoring activities. Thus, VUT has implemented over time a series of schemes and projects based on innovation and entrepreneurship, and in this paper, some of them will be briefly presented. All these schemes were implemented by facilitating an effective dialog with students and the opportunity to listen to their views at all levels of the University and in all fields of study, as well as by developing a partnership with students to set out priority areas. VUT demonstrates innovation and entrepreneurial capacity through its new activities for higher education, which will attract more partnerships and projects dedicated to students.Keywords: Romania, project-based learning, entrepreneurial activities, simulated enterprises
Procedia PDF Downloads 15326820 A Corpus-Based Discourse Analysis of the Disappearance of MH370 in Malaysia and United Kingdom Newspapers: A Pilot Study
Authors: Theng Theng Ong
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This pilot study adopts a corpus-based discourse analysis to explore the construction of Malaysia airline tragedy MH370 in the selected Malaysian and United Kingdom (UK) newspapers. Fairclough’s three-dimensional model is adopted in the study to support the corpus-based analysis. The analysis aims to determine the ways in which Malaysian Airline tragedy MH370 is linguistically defined and constructed in terms of keywords and collocation. The study also seeks to identify the types of discourse that are presented in the news articles. In addition, the differences or similarities in terms of keywords, topics or issues covered by the selected Malaysian and UK news media are examined.Keywords: corpus, CDA, newspapers, airline tragedies
Procedia PDF Downloads 28826819 Finite Element Analysis of Thermally-Induced Bistable Plate Using Four Plate Elements
Authors: Jixiao Tao, Xiaoqiao He
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The present study deals with the finite element (FE) analysis of thermally-induced bistable plate using various plate elements. The quadrilateral plate elements include the 4-node conforming plate element based on the classical laminate plate theory (CLPT), the 4-node and 9-node Mindlin plate element based on the first-order shear deformation laminated plate theory (FSDT), and a displacement-based 4-node quadrilateral element (RDKQ-NL20). Using the von-Karman’s large deflection theory and the total Lagrangian (TL) approach, the nonlinear FE governing equations for plate under thermal load are derived. Convergence analysis for four elements is first conducted. These elements are then used to predict the stable shapes of thermally-induced bistable plate. Numerical test shows that the plate element based on FSDT, namely the 4-node and 9-node Mindlin, and the RDKQ-NL20 plate element can predict two stable cylindrical shapes while the 4-node conforming plate predicts a saddles shape. Comparing the simulation results with ABAQUS, the RDKQ-NL20 element shows the best accuracy among all the elements.Keywords: Bistable, finite element method, geometrical nonlinearity, quadrilateral plate elements
Procedia PDF Downloads 21326818 A Hybrid Normalized Gradient Correlation Based Thermal Image Registration for Morphoea
Authors: L. I. Izhar, T. Stathaki, K. Howell
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Analyzing and interpreting of thermograms have been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. In this paper, a novel system is proposed to improve diagnosis and monitoring of morphoea skin disorder based on integration with the published lines of Blaschko. In the proposed system, image registration based on global and local registration methods are found inevitable. This paper presents a modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images that are represented by smooth gray edge maps is proposed for the global registration approach. This method is improved further by incorporating an iterative-based normalized cross-correlation coefficient (NCC) method. It is found that by replacing the final registration part of the NGC method where translational differences are solved in the spatial Fourier domain with the NCC method performed in the spatial domain, the performance and robustness of the NGC method can be greatly improved. It is shown in this paper that the hybrid NGC method not only outperforms phase correlation (PC) method but also improved misregistration due to translation, suffered by the modified NGC method alone for thermograms with ill-defined jawline. This also demonstrates that by using the gradients of the gray edge maps and a hybrid technique, the performance of the PC based image registration method can be greatly improved.Keywords: Blaschko’s lines, image registration, morphoea, thermal imaging
Procedia PDF Downloads 30126817 The Relationship between Competency-Based Learning and Learning Efficiency of Media Communication Students at Suan Sunandha Rajabhat University
Authors: Somtop Keawchuer
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This research aims to study (1) the relationship between competency-based learning and learning efficiency of new media communication students at Suan Sunandha University (2) the demographic factor effect on learning efficiency of students at Suan Sunandha University. This research method will use quantitative research; data was collected by questionnaires distributed to students from new media communication in management science faculty of Suan Sunandha Rajabhat University for 1340 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including T-test, ANOVA and Pearson correlation for hypothesis testing. The results showed that the competency-based learning in term of ability to communicate, ability to think and solve the problem, life skills and ability to use technology has a significant relationship with learning efficiency in term of the cognitive domain, psychomotor domain and affective domain at the 0.05 level and which is in harmony with the research hypotheses.Keywords: competency-based learning, learning efficiency, new media communication students, Suan Sunandha Rajabhat University
Procedia PDF Downloads 23726816 Overcoming Challenges of Teaching English as a Foreign Language in Technical Classrooms: A Case Study at TVTC College of Technology
Authors: Sreekanth Reddy Ballarapu
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The perception of the whole process of teaching and learning is undergoing a drastic and radical change. More and more student-centered, pragmatic, and flexible approaches are gradually replacing teacher-centered lecturing and structural-syllabus instruction. The issue of teaching English as a Foreign language is no exception in this regard. The traditional Present-Practice-Produce (P-P-P) method of teaching English is overtaken by Task-Based Teaching which is a subsidiary branch of Communicative Language Teaching. At this juncture this article strongly tries to convey that - Task-based learning, has an advantage over other traditional methods of teaching. All teachers of English must try to customize their texts into productive tasks, apply them, and evaluate the students as well as themselves. Task Based Learning is a double edged tool which can enhance the performance of both the teacher and the taught. The sample for this case study is a class of 35 students from Semester III - Network branch at TVTC College of Technology, Adhum - Kingdom of Saudi Arabia. The students are high school passed out and aged between 19-21years.For the present study the prescribed textbook Technical English 1 by David Bonamy was used and a number of language tasks were chalked out during the pre- task stage and the learners were made to participate voluntarily and actively. The Action Research methodology was adopted within the dual framework of Communicative Language Teaching and Task-Based Learning. The different tools such as questionnaires, feedback and interviews were used to collect data. This study provides information about various techniques of Communicative Language Teaching and Task Based Learning and focuses primarily on the advantages of using a Task Based Learning approach. This article presents in detail the objectives of the study, the planning and implementation of the action research, the challenges encountered during the execution of the plan, and the pedagogical outcome of this project. These research findings serve two purposes: first, it evaluates the effectiveness of Task Based Learning and, second, it empowers the teacher's professionalism in designing and implementing the tasks. In the end, the possibility of scope for further research is presented in brief.Keywords: action research, communicative language teaching, task based learning, perception
Procedia PDF Downloads 23226815 Impact of Herbicides on Soil Biology in Rapeseed
Authors: M. Eickermann, M. K. Class, J. Junk
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Winter oilseed rape, Brassica napus L., is characterized by a high number of herbicide applications. Therefore, its cultivation can lead to massive contamination of ground water and soil by herbicide and their metabolites. A multi-side long-term field experiment (EFFO, Efficient crop rotation) was set-up in Luxembourg to quantify these effects. Based on soil sampling and laboratory analysis, preliminary results showed reduced dehydrogenase activities of several soil organisms due to herbicide treatments. This effect is highly depending on the soil type. Relation between the dehydrogenase activity and the amount of microbial carbon showed higher variability on the test side with loamy Brown Earth, based on Bunter than on those with sandy-loamy Brown Earth, based on calciferous Sandstone.Keywords: cropping system, dehydrogenase activity, herbicides, mechanical weed control, oilseed rape
Procedia PDF Downloads 23926814 Tracking Filtering Algorithm Based on ConvLSTM
Authors: Ailing Yang, Penghan Song, Aihua Cai
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The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention
Procedia PDF Downloads 15226813 The Effect of Behavioral and Risk Factors of Investment Growth on Stock Returns
Authors: Majid Lotfi Ghahroud, Seyed Jalal Tabatabaei, Ebrahim Karami, AmirArsalan Ghergherechi, Amir Ali Saeidi
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In this study, the relationship between investment growth and stock returns of companies listed in Tehran Stock Exchange and whether their relationship -behavioral or risk factors- are discussed. Generally, there are two perspectives; risk-based approach and behavioral approach. According to the risk-based approach due to increase investment, systemic risk and consequently the stock returns are reduced. But due to the second approach, an excessive optimism or pessimism leads to assuming stock price with high investment growth in the past, higher than its intrinsic value and the price of stocks with lower investment growth, less than its intrinsic value. The investigation period is eight years from 2007 to 2014. The sample consisted of all companies listed on the Tehran Stock Exchange. The method is a portfolio test, and the analysis is based on the t-student test (t-test). The results indicate that there is a negative relationship between investment growth and stock returns of companies and this negative correlation is stronger for firms with higher cash flow. Also, the negative relationship between asset growth and stock returns is due to behavioral factors.Keywords: behavioral theory, investment growth, risk-based theory, stock returns
Procedia PDF Downloads 147