Search results for: modeling using hidden state variables

Authors: Elena Lyakso, Olga Frolova, Yuri Matveev

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The aim of the study is to determine the acoustic features of voice and speech of children with autism spectrum disorders (ASD) as a possible additional diagnostic criterion. The participants in the study were 95 children with ASD aged 5-16 years, 150 typically development (TD) children, and 103 adults – listening to children’s speech samples. Three types of experimental methods for speech analysis were performed: spectrographic, perceptual by listeners, and automatic recognition. In the speech of children with ASD, the pitch values, pitch range, values of frequency and intensity of the third formant (emotional) leading to the “atypical” spectrogram of vowels are higher than corresponding parameters in the speech of TD children. High values of vowel articulation index (VAI) are specific for ASD children’s speech signals. These acoustic features can be considered as diagnostic marker of autism. The ability of humans and automatic recognition of the psychoneurological state of children via their speech is determined.

Keywords: Autism spectrum disorders, biomarker of autism, child speech, voice features.

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: Retrieval, generative, deep learning, response generation, knowledge.

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Authors: Md. Asif Jahangir Chowdhury, Md. Shahriar Rizwan, M. S. Islam

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In CMOS integrated circuit design there is a trade-off between static power consumption and technology scaling. Recently, the power density has increased due to combination of higher clock speeds, greater functional integration, and smaller process geometries. As a result static power consumption is becoming more dominant. This is a challenge for the circuit designers. However, the designers do have a few methods which they can use to reduce this static power consumption. But all of these methods have some drawbacks. In order to achieve lower static power consumption, one has to sacrifice design area and circuit performance. In this paper, we propose a new method to reduce static power in the CMOS VLSI circuit using Variable Body Biasing technique without being penalized in area requirement and circuit performance.

Keywords: variable body biasing, state saving technique, stack effect, dual V-th, static power reduction.

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Authors: Naser Charkhsaz, Ashraf Sadat Mousavi, Navvab Shamspour

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This study aimed to evaluate the role of state education in increasing public awareness through mass media (with emphasis on newspapers and TV) coping with possible earthquake in Tehran. All residents aged 15 to 65 who live in the five regions of Tehran (North, South, East, West and Center) during the plan implementation were selected and studied. The required sample size in each region was calculated based on the Cochran formula (n=380). In order to collect and analyze the data, a questionnaire with reliability (82%) and a one-sample t-test has been used, respectively. The results showed that warnings related to the Tehran earthquake affected people in the pre-contemplation stage, while public education through mass media did not promote public awareness about prevention, preparedness and rehabilitation.

Keywords: Public education through mass media, public awareness, possible earthquake in Tehran, pre-contemplation.

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Authors: Nicholas D. Assimakis

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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: Discrete time, linear estimation, Kalman filter, Kalman filter gain.

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Authors: Irisa Murniece, Zanda Kruma, Ilze Skrabule

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Potatoes are a good source of carotenoids, which are lipophilic compounds synthesized in plastids from isoprenoids. The aim of this research was to determine the content of carotenoids in relationship with the colour of organically and conventionally cultivated potato genotypes before and after period of storage. In cooperation with the State Priekuli Plant Breeding Institute (Latvia), six potato genotypes were studied: 'Agrie dzeltenie', 'Prelma', 'Imanta', 'S-03135-10', 'S-99108-8' and 'S-01063-5'. All the genotypes were cultivated under three different conditions: organically and conventionally (two conditions). The content of carotenoids was determined by using spectrophotometer and the colour – L*a*b* system. The results of current research show that after the period of storage, carotenoid amount has increased and in conventionally cultivated potatoes it varies from 228.514 to 552.434 μg 100 g-1 while in organically cultivated potato genotypes – from 45.485 to 662.699 μg 100 g-1 FW. Colour of potato flesh was changing during storage.

Keywords: carotenoids, colour, organic and conventional cultivation, potato genotypes, storage

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Authors: Petr Gurný

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One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the creditscoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.

Keywords: Credit-scoring Models, Multidimensional Subordinated Lévy Model, Probability of Default.

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Authors: Hossein Shahinzadeh, Ladan Darougaran, Ebrahim Jalili Sani, Hamed Yavari, Mahdi Mozaffari Legha

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This paper present a new method for design of power system stabilizer (PSS) based on sliding mode control (SMC) technique. The control objective is to enhance stability and improve the dynamic response of the multi-machine power system. In order to test effectiveness of the proposed scheme, simulation will be carried out to analyze the small signal stability characteristics of the system about the steady state operating condition following the change in reference mechanical torque and also parameters uncertainties. For comparison, simulation of a conventional control PSS (lead-lag compensation type) will be carried out. The main approach is focusing on the control performance which later proven to have the degree of shorter reaching time and lower spike.

Keywords: Power system stabilizer (PSS), multi-machine power system, sliding mode control

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Authors: See Zi Siang, Khairul Hazrin Hashim, Harold Thwaites, Lee Xia Sheng, Ooi Wooi Har

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The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.

Keywords: High Dynamic Range Image, Photography Workflow Optimization, Digital Negative Image, Architectural Image

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Authors: I. Lolic, P. Soric, M. Cizmesija

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Based on Business and Consumer Survey (BCS) data, the European Commission (EC) regularly publishes the monthly Economic Sentiment Indicator (ESI) for each EU member state. ESI is conceptualized as a leading indicator, aimed ad tracking the overall economic activity. In calculating ESI, the EC employs arbitrarily chosen weights on 15 BCS response balances. This paper raises the predictive quality of ESI by applying nonlinear programming to find such weights that maximize the correlation coefficient of ESI and year-on-year GDP growth. The obtained results show that the highest weights are assigned to the response balances of industrial sector questions, followed by questions from the retail trade sector. This comes as no surprise since the existing literature shows that the industrial production is a plausible proxy for the overall Croatian economic activity and since Croatian GDP is largely influenced by the aggregate personal consumption.

Keywords: Business and Consumer Survey, Economic Sentiment Indicator, Leading Indicator, Nonlinear Optimization with Constraints.

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Authors: Md. Masum Billah, Mohiuddin Ahmed, Soheli Farhana

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In modern day disaster recovery mission has become one of the top priorities in any natural disaster management regime. Smart autonomous robots may play a significant role in such missions, including search for life under earth quake hit rubbles, Tsunami hit islands, de-mining in war affected areas and many other such situations. In this paper current state of many walking robots are compared and advantages of hexapod systems against wheeled robots are described. In our research we have selected a hexapod spider robot; we are developing focusing mainly on efficient navigation method in different terrain using apposite gait of locomotion, which will make it faster and at the same time energy efficient to navigate and negotiate difficult terrain. This paper describes the method of terrain negotiation navigation in a hazardous field.

Keywords: Walking robots, locomotion, hexapod robot, gait, hazardous field.

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Authors: Adriana Ávila Zúñiga Nordfjeld

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This paper provides a literature review to document the state of the art with respect to handling “human bias” in decision making within the established quality management systems (QMS) and LEAN theory, in the context of shipbuilding. Previous research shows that in shipbuilding there is a huge deviation from the planned man-hours under the project management to the actual man-hours used because of errors in planning and reworks caused by human bias in the information flows, among others. This reduces the efficiency, and increases operational costs. Thus, the research question is how QMS and LEAN handle biases. The findings show the gap in studying the integration of methods to handle human bias in decision making into QMS and lean, not only within shipbuilding, but in general. Theoretical and practical implications are discussed for researchers and practitioners in the areas of decision making, QMS and LEAN, and future research is suggested.

Keywords: Human bias, decision making, LEAN Shipbuilding, quality management systems.

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Authors: Kazuo Komatsu, Hitoshi Takata

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The objective of this study is to propose an observer design for nonlinear systems by using an augmented linear system derived by application of a formal linearization method. A given nonlinear differential equation is linearized by the formal linearization method which is based on Taylor expansion considering up to the higher order terms, and a measurement equation is transformed into an augmented linear one. To this augmented dimensional linear system, a linear estimation theory is applied and a nonlinear observer is derived. As an application of this method, an estimation problem of transient state of electric power systems is studied, and its numerical experiments indicate that this observer design shows remarkable performances for nonlinear systems.

Keywords: nonlinear system, augmented linear system, nonlinear observer, formal linearization, electric power system.

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Authors: M. Jaditager, J. Lovisa, N. Sivakugan

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The Port of Townsville conducts regular annual maintenance dredging to maintain depths of its harbor basin and approach channels for the navigational safety of the vessels against the natural accumulation of marine sediments. In addition to the regular maintenance dredging, the port undertakes emergency dredging in cases where large quantities of sediments are mobilized and deposited in port waters by cyclone or major flood events. The maintenance dredging material derived from the port may be disposed at sea or on land in accordance with relevant state and commonwealth regulations. For the land disposal, the dredged mud slurry is hydraulically placed into containment ponds and left to undergo sedimentation and self-weight consolidation to form fill material for land reclamation. This paper provides an overview of the maintenance dredging at the Port of Townsville and emphasis on maintenance dredging requirements, sediment quality, bathymetry, dredging methods used, and dredged material disposal options.

Keywords: Consolidation, dredged material, maintenance dredging, marine sediments, sedimentation.

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Authors: F. Vallée, J-F. Toubeau, Z. De Grève, J. Lobry

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When evaluating the capacity of a generation park to cover the load in transmission systems, traditional Loss of Load Expectation (LOLE) and Expected Energy not Served (EENS) indices can be used. If those indices allow computing the annual duration and severity of load non covering situations, they do not take into account the fact that the load excess is generally shifted from one penury state (hour or quarter of an hour) to the following one. In this paper, a sequential Monte Carlo framework is introduced in order to compute adjusted LOLE and EENS indices. Practically, those adapted indices permit to consider the effect of load excess transfer on the global adequacy of a generation park, providing thus a more accurate evaluation of this quantity.

Keywords: Expected Energy not Served, Loss of Load Expectation, Monte Carlo simulation, reliability, wind generation.

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Authors: F. I. Belheouane, M. Bensaibi

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The seismic feedback experiences in Algeria have shown higher percentage of damages for non-code conforming reinforced concrete (RC) buildings. Furthermore, the vulnerability of these buildings was further aggravated due to presence of many factors (e.g. weak the seismic capacity of these buildings, shorts columns, Pounding effect, etc.). Consequently Seismic risk assessments were carried out on populations of buildings to identify the buildings most likely to undergo losses during an earthquake. The results of such studies are important in the mitigation of losses under future seismic events as they allow strengthening intervention and disaster management plans to be drawn up. Within this paper, the state of the existing structures is assessed using "the vulnerability index" method. This method allows the classification of RC constructions taking into account both, structural and non structural parameters, considered to be ones of the main parameters governing the vulnerability of the structure. Based on seismic feedback from past earthquakes DPM (damage probability matrices) were developed too.

Keywords: Seismic vulnerability, Reinforced concrete buildings, Earthquake, DPM, Algeria.

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Authors: A. S. Kipcak, P. Gurses, E. Moroydor Derun, S. Piskin

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Borate minerals have attracted considerable attention in the past years due to their structural chemistry and mechanical properties in several industries. Recently, increasing attention has been paid to the use of; synthetically produced magnesium borates as catalysts reinforcing material for plastics, the conversion of hydrocarbons, electro-conductive treating agent, anti-wear and anti-corrosion materials. Magnesium borates can be synthesized by several methods such as; hydrothermal and solid-state (thermal) processes. In this study the hydrothermal production method was applied at the modest temperature of 80C along with convenient crystal growth. Using MgCl2.6H2O, H3BO3, and NaOH as starting materials, 30, 60, 120, 240 minutes of reaction times were studied. After all, the crystal structure and the morphology of the products were examined by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR). As a result the forms of Admontite and Mcallisterite minerals were synthesized.

Keywords: FT-IR, hydrothermal method, magnesium borates, XRD.

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Authors: Raied Salman, Nazar Younis

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In a none-super-competitive environment the concepts of closed system, management control remains to be the dominant guiding concept to management. The merits of closed loop have been the sources of most of the management literature and culture for many decades. It is a useful exercise to investigate and poke into the dynamics of the control loop phenomenon and draws some lessons to use for refining the practice of management. This paper examines the multitude of lessons abstracted from the behavior of the Input /output /feedback control loop model, which is the core of control theory. There are numerous lessons that can be learned from the insights this model would provide and how it parallels the management dynamics of the organization. It is assumed that an organization is basically a living system that interacts with the internal and external variables. A viable control loop is the one that reacts to the variation in the environment and provide or exert a corrective action. In managing organizations this is reflected in organizational structure and management control practices. This paper will report findings that were a result of examining several abstract scenarios that are exhibited in the design, operation, and dynamics of the control loop and how they are projected on the functioning of the organization. Valuable lessons are drawn in trying to find parallels and new paradigms, and how the control theory science is reflected in the design of the organizational structure and management practices. The paper is structured in a logical and perceptive format. Further research is needed to extend these findings.

Keywords: Management theory, control theory, feed back, input/output, strategy, change, information technology, informationsystems, IS, organizational environment, organizations, opensystems, closed systems.

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Authors: S. Abdollahi Pour, M. Saneei

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This paper propose a new circuit design which monitor total leakage current during standby mode and generates the optimal reverse body bias voltage, by using the adaptive body bias (ABB) technique to compensate die-to-die parameter variations. Design details of power monitor are examined using simulation framework in 65nm and 32nm BTPM model CMOS process. Experimental results show the overhead of proposed circuit in terms of its power consumption is about 10 μW for 32nm technology and about 12 μW for 65nm technology at the same power supply voltage as the core power supply. Moreover the results show that our proposed circuit design is not far sensitive to the temperature variations and also process variations. Besides, uses the simple blocks which offer good sensitivity, high speed, the continuously feedback loop.

Keywords: leakage current, leakage power monitor, body biasing, low power

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Authors: Gugyong Kim, Sugnsu Kang, Yongjun Lee, Sooncheol Park, Wonwook Jung

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When cars are released from the factory, strut noises are very small and therefore it is difficult to perceive them. As the use time and travel distance increase, however, strut noises get larger so as to cause users much uneasiness. The noises generated at the field include engine noises and flow noises and therefore it is difficult to clearly discern the noises generated from struts. This study developed a test method which can reproduce field strut noises in the lab. Using the newly developed noise evaluation test, this study analyzed the effects that insulator performance degradation and failure can have on car noises. The study also confirmed that the insulator durability test by the simple back-and-forth motion cannot completely reflect the state of the parts failure in the field. Based on this, the study also confirmed that field noises can be reproduced through a durability test that considers heat aging.

Keywords: Insulator, noise, performance degradation, strut

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Authors: Yunseok Noh, Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park

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Scripts are one of the basic text resources to understand broadcasting contents. Topic modeling is the method to get the summary of the broadcasting contents from its scripts. Generally, scripts represent contents descriptively with directions and speeches, and provide scene segments that can be seen as semantic units. Therefore, a script can be topic modeled by treating a scene segment as a document. Because scene segments consist of speeches mainly, however, relatively small co-occurrences among words in the scene segments are observed. This causes inevitably the bad quality of topics by statistical learning method. To tackle this problem, we propose a method to improve topic quality with additional word co-occurrence information obtained using scene similarities. The main idea of improving topic quality is that the information that two or more texts are topically related can be useful to learn high quality of topics. In addition, more accurate topical representations lead to get information more accurate whether two texts are related or not. In this paper, we regard two scene segments are related if their topical similarity is high enough. We also consider that words are co-occurred if they are in topically related scene segments together. By iteratively inferring topics and determining semantically neighborhood scene segments, we draw a topic space represents broadcasting contents well. In the experiments, we showed the proposed method generates a higher quality of topics from Korean drama scripts than the baselines.

Keywords: Broadcasting contents, generalized P´olya urn model, scripts, text similarity, topic model.

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Authors: S. A. Moeini, M. T.Ahmadian

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Structural behavior of ring stiffened thick walled cylinders made of functionally graded materials (FGMs) is investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture of metal and ceramic. The gradient compositional variation of the constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction. A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and modal behavior of stiffened FGM thick walled cylinders. By using this super-element the number of elements, which are needed for modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by comparison to finite element formulation with conventional elements. Comparison indicates a good conformity between results.

Keywords: FGMs, Modal analysis, Static analysis, Stiffened cylinders.

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: Enhanced ideal gas molecular movement, ideal gas molecular movement, model updating method, probability-based damage detection, uncertainty quantification.

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Authors: Renáta Iváncsy, István Vajk

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The various types of frequent pattern discovery problem, namely, the frequent itemset, sequence and graph mining problems are solved in different ways which are, however, in certain aspects similar. The main approach of discovering such patterns can be classified into two main classes, namely, in the class of the levelwise methods and in that of the database projection-based methods. The level-wise algorithms use in general clever indexing structures for discovering the patterns. In this paper a new approach is proposed for discovering frequent sequences and tree-like patterns efficiently that is based on the level-wise issue. Because the level-wise algorithms spend a lot of time for the subpattern testing problem, the new approach introduces the idea of using automaton theory to solve this problem.

Keywords: Frequent pattern discovery, graph mining, pushdownautomaton, sequence mining, state machine, tree mining.

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Authors: Andras Szekrenyes

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This work presents the mixed-mode II/III prestressed split-cantilever beam specimen for the fracture testing of composite materials. In accordance with the concept of prestressed composite beams one of the two fracture modes is provided by the prestressed state of the specimen, and the other one is increased up to fracture initiation by using a testing machine. The novel beam-like specimen is able to provide any combination of the mode-II and mode-III energy release rates. A simple closed-form solution is developed using beam theory as a data reduction scheme and for the calculation of the energy release rates in the new configuration. The applicability and the limitations of the novel fracture mechanical test are demonstrated using unidirectional glass/polyester composite specimens. If only crack propagation onset is involved then the mixed-mode beam specimen can be used to obtain the fracture criterion of transparent composite materials in the GII - GIII plane in a relatively simple way.

Keywords: Composite, fracture mechanics, toughness testing, mixed-mode II/III fracture.

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: Startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship.

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Authors: Mahawish Masud, Muhammad Iqbal, M. U. Khan, Farooque Azam

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Manual writing of test cases from functional requirements is a time-consuming task. Such test cases are not only difficult to write but are also challenging to maintain. Test cases can be drawn from the functional requirements that are expressed in natural language. However, manual test case generation is inefficient and subject to errors.  In this paper, we have presented a systematic procedure that could automatically derive test cases from user stories. The user stories are specified in a restricted natural language using a well-defined template.  We have also presented a detailed methodology for writing our test ready user stories. Our tool “Test-o-Matic” automatically generates the test cases by processing the restricted user stories. The generated test cases are executed by using open source Selenium IDE.  We evaluate our approach on a case study, which is an open source web based application. Effectiveness of our approach is evaluated by seeding faults in the open source case study using known mutation operators.  Results show that the test case generation from restricted user stories is a viable approach for automated testing of web applications.

Keywords: Automated testing, natural language, user story modeling, software engineering, software testing, test case specification, transformation and automation, user story, web application testing.

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Authors: Junaid Rashid, Waqar Mehmood, Muhammad Wasif Nisar

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This survey paper shows the recent state of model comparison as it’s applies to Model Driven engineering. In Model Driven Engineering to calculate the difference between the models is a very important and challenging task. There are number of tasks involved in model differencing that firstly starts with identifying and matching the elements of the model. In this paper, we discuss how model matching is accomplished, the strategies, techniques and the types of the model. We also discuss the future direction. We found out that many of the latest model comparison strategies are geared near enabling Meta model and similarity based matching. Therefore model versioning is the most dominant application of the model comparison. Recently to work on comparison for versioning has begun to deteriorate, giving way to different applications. Ultimately there is wide change among the tools in the measure of client exertion needed to perform model comparisons, as some require more push to encourage more sweeping statement and expressive force.

Keywords: Model comparison, model clone detection, model versioning, EMF Model, model diff.

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: Bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow.

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Authors: Mohd Ariff Admon, Abdul Rahman Mohd Kasim, Sharidan Shafie

Abstract:

This paper considers the effect of heat generation proportional l to (T - T∞ )p , where T is the local temperature and T∞ is the ambient temperature, in unsteady free convection flow near the stagnation point region of a three-dimensional body. The fluid is considered in an ambient fluid under the assumption of a step change in the surface temperature of the body. The non-linear coupled partial differential equations governing the free convection flow are solved numerically using an implicit finite-difference method for different values of the governing parameters entering these equations. The results for the flow and heat characteristics when p ≤ 2 show that the transition from the initial unsteady-state flow to the final steadystate flow takes place smoothly. The behavior of the flow is seen strongly depend on the exponent p.

Keywords: Free convection, Boundary layer flow, Stagnationpoint, Heat generation

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