Search results for: dynamic capability

Authors: Shipra Sharma, Jagat Jerath

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Human resource training is an essential element of talent management in the current era of global competitiveness and dynamic trade in the manufacturing industry. Globally, India is behind only China as the largest textile manufacturer. The major challenges faced by the Indian textile manufacturing Industry are low technology levels, growing skill gaps, unorganized structure, lower efficiencies, etc. indicating the need for constant talent up-gradation. Assessment of training needs from a strategic perspective is an essential step for the formulation of effective training. The paper established the significance of training in the Indian textile industry and to determine the training needs on various parameters as presented. 40 HR personnel/s working in the textile and apparel companies based in the industrial region of Punjab, India, were the respondents for the study. The research tool used in this case was a structured questionnaire as per five-point Likert scale. Statistical analysis through descriptive statistics and chi-square test indicated the increased need for training whenever there were technical changes in the organizations. As per the data presented in this study, most of the HR personnel/s agreed that the variables associated with organizational analysis, task analysis, and individual analysis have a statistically significant role to play in determining the need for training in an organization.

Keywords: Indian textile manufacturing industry, significance of training, training needs analysis, parameters for training needs assessment

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Authors: Faghihnia Torshizi Mostafa, Saitoh Masato

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An efficient method is developed for the response of a group of vertical, cylindrical fixed-head, finite length piles embedded in a homogeneous elastic stratum, subjected to harmonic force atop the pile group cap. Pile to pile interaction is represented through simplified beam-on-dynamic-Winkler-foundation (BDWF) with realistic frequency-dependent springs and dashpots. Pile group effect is considered through interaction factors. New closed-form expressions for interaction factors and curvature ratios atop the pile are extended by considering different boundary conditions at the tip of the piles (fixed, hinged). In order to investigate the fundamental characteristics of inertial bending strains in pile groups, inertial bending strains at the head of each pile are expressed in terms of slenderness ratio. The results of parametric study give valuable insight in understanding the behavior of fixed head pile groups in fundamental natural frequency of soil stratum.

Keywords: Winkler-foundation, fundamental frequency of soil stratum, normalized inertial bending strain, harmonic excitation

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Authors: Doo W. Lee, Soo J. Lee, Bye R. Yoon, Jae Y. Jho, Kyehan Rhee

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Hand exoskeletons have been developed in order to assist daily activities for disabled and elder people. A figure exoskeleton was developed using ionic polymer metal composite (IPMC) actuators, and the performance of it was evaluated in this study. In order to study dynamic performance of a finger dummy performing pinching motion, force generating characteristics of an IPMC actuator and pinching motion of a thumb and index finger dummy actuated by IMPC actuators were analyzed. The blocking force of 1.54 N was achieved under 4 V of DC. A thumb and index finger dummy, which has one degree of freedom at the proximal joint of each figure, was manufactured by a three dimensional rapid prototyping. Each figure was actuated by an IPMC actuator, and the maximum fingertip force was 1.18 N. Pinching motion of a dummy was analyzed by two video cameras in vertical top and horizontal left end view planes. A figure dummy powered by IPMC actuators could perform flexion and extension motion of an index figure and a thumb.

Keywords: finger exoskeleton, ionic polymer metal composite, flexion and extension, motion analysis

Procedia PDF Downloads 232

Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: D. Suman, B. Nikitha, J. Sarvani, V. Archana

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Histological slides provide clinical diagnostic information about the subjects from the ancient times. Even with the advent of high resolution imaging cameras the image tend to have some background noise which makes the analysis complex. A study of the histological slides is done by using a nonlinear transfer function based image enhancement method. The method processes the raw, color images acquired from the biological microscope, which, in general, is associated with background noise. The images usually appearing blurred does not convey the intended information. In this regard, an enhancement method is proposed and implemented on 50 histological slides of human tissue by using nonlinear transfer function method. The histological image is converted into HSV color image. The luminance value of the image is enhanced (V component) because change in the H and S components could change the color balance between HSV components. The HSV image is divided into smaller blocks for carrying out the dynamic range compression by using a linear transformation function. Each pixel in the block is enhanced based on the contrast of the center pixel and its neighborhood. After the processing the V component, the HSV image is transformed into a colour image. The study has shown improvement of the characteristics of the image so that the significant details of the histological images were improved.

Keywords: HSV space, histology, enhancement, image

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Authors: Guantao Bai

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Public space is an indispensable and important component of the urban built environment. How to more accurately evaluate the usage characteristics of public space can help improve its spatial quality. Compared to traditional survey methods, computer vision technology based on deep learning has advantages such as dynamic observation and low cost. This study takes the public space of Shaping Park as an example and, based on deep learning computer vision technology, processes and analyzes the image data of the public space to obtain the spatial usage characteristics and spatiotemporal characteristics of the public space. Research has found that the spontaneous activity time in public spaces is relatively random with a relatively short average activity time, while social activities have a relatively stable activity time with a longer average activity time. Computer vision technology based on deep learning can effectively describe the spatial usage characteristics of the research area, making up for the shortcomings of traditional research methods and providing relevant support for creating a good public space.

Keywords: computer vision, deep learning, public spaces, using features

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Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

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Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: decision support system, event-sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine

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Authors: Chunying Fang, Haifeng Li, Lin Ma, Mancai Zhang

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Speech intelligibility assessment is an important measure to evaluate the functional outcomes of surgical and non-surgical treatment, speech therapy and rehabilitation. The assessment of pathological speech plays an important role in assisting the experts. Pathological speech usually is non-stationary and mutational, in this paper, we describe a multi-granularity combined feature schemes, and which is optimized by hierarchical visual method. First of all, the difference granularity level pathological features are extracted which are BAFS (Basic acoustics feature set), local spectral characteristics MSCC (Mel s-transform cepstrum coefficients) and nonlinear dynamic characteristics based on chaotic analysis. Latterly, radar chart and F-score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96-dimensions.The experimental results denote that new features by support vector machine (SVM) has the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.

Keywords: pathological speech, multi-granularity feature, MSCC (Mel s-transform cepstrum coefficients), F-score, radar chart

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Authors: Libo Jiang, Huan Li, Rongling Wu

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Ordinary differentiation equations (ODE) have proven to be powerful for reconstructing precise and informative gene regulatory networks (GRNs) from dynamic gene expression data. However, joint modeling and analysis of all genes, essential for the systematical characterization of genetic interactions, are challenging due to high dimensionality and a complex pattern of genetic regulation including activation, repression, and antitermination. Here, we address these challenges by unifying variable selection and game theory through ODE. Each gene within a GRN is co-expressed with its partner genes in a way like a game of multiple players, each of which tends to choose an optimal strategy to maximize its “fitness” across the whole network. Based on this unifying theory, we designed and conducted a real experiment to infer salt tolerance-related GRNs for Euphrates poplar, a hero tree that can grow in the saline desert. The pattern and magnitude of interactions between several hub genes within these GRNs were found to determine the capacity of Euphrates poplar to resist to saline stress.

Keywords: gene regulatory network, ordinary differential equation, game theory, LASSO, saline resistance

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Authors: Kexin Chen

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As an important method of transportation to solve the demand and supply contradiction generated in the rapid urbanization process, urban rail traffic system has been rapidly developed over the past ten years in China. During the rapid development, the space of urban rail Transit has encountered many problems, such as space simplification, sensory experience dullness, and poor regional identification, etc. This paper, focus on the study of the negative space of subway station and spatial softening, by comparing and learning from foreign cases. The article sorts out cases at home and abroad, make a comparative study of the cases, analysis more diversified setting of public art, and sets forth propositions on the domestic type of public art in the space of urban rail transit for reference, then shows the relationship of the spatial attribute in the space of urban rail transit and public art form. In this foundation, it aims to characterize more diverse setting ways for public art; then suggests the three public art forms corresponding properties, such as static presenting mode, dynamic image mode, and spatial softening mode; finds out the method of urban public art to optimize negative space.

Keywords: diversification, negative space, optimization strategy, public art planning

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Authors: Ione Loots, Marco van Dijk, Jay Bhagwan

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Historically, South Africa had various small-scale hydropower installations in remote areas that were not incorporated in the national electricity grid. Unfortunately, in the 1960s most of these plants were decommissioned when Eskom, the national power utility, rapidly expanded its grid and capability to produce cheap, reliable, coal-fired electricity. This situation persisted until 2008, when rolling power cuts started to affect all citizens. This, together with the rising monetary and environmental cost of coal-based power generation, has sparked new interest in small-scale hydropower development, especially in remote areas or at locations (like wastewater treatment works) that could not afford to be without electricity for long periods at a time. Even though South Africa does not have the same, large-scale, hydropower potential as some other African countries, significant potential for micro- and small-scale hydropower is hidden in various places. As an example, large quantities of raw and potable water are conveyed daily under either pressurized or gravity conditions over large distances and elevations. Due to the relative water scarcity in the country, South Africa also has more than 4900 registered dams of varying capacities. However, institutional capacity and skills have not been maintained in recent years and therefore the identification of hydropower potential, as well as the development of micro- and small-scale hydropower plants has not gained significant momentum. An assessment model and decision support system for low head hydropower development has been developed to assist designers and decision makers with first-order potential analysis. As a result, various potential sites were identified and many of these sites were situated at existing infrastructure like weirs, barrages or pipelines. One reason for the specific interest in existing infrastructure is the fact that capital expenditure could be minimized and another is the reduced negative environmental impact compared to greenfield sites. This paper will explore the case study of retrofitting an unconventional and innovative hydropower plant to the outlet of a wastewater treatment works in South Africa.

Keywords: low head hydropower, retrofitting, small-scale hydropower, wastewater treatment works

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Authors: A. Moualdia, D. J. Boudana, O. Bouchhida, A. Medjber

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, the cost of this energy is still too high to compete with traditional fossil fuels, especially on sites less windy. The performance of a wind turbine depends on three parameters: the power of wind, the power curve of the turbine and the generator's ability to respond to wind fluctuations. This paper presents a control chain conversion based on a double-fed asynchronous machine and flow-oriented. The supply system comprises of two identical converters, one connected to the rotor and the other one connected to the network via a filter. The architecture of the device is up by three commands are necessary for the operation of the turbine control extraction of maximum power of the wind to control itself (MPPT) control of the rotor side converter controlling the electromagnetic torque and stator reactive power and control of the grid side converter by controlling the DC bus voltage and active power and reactive power exchanged with the network. The proposed control has been validated in both modes of operation of the three-bladed wind 7.5 kW, using Matlab/Simulink. The results of simulation control technology study provide good dynamic performance and static.

Keywords: D.F.I.G, variable wind speed, hypersynchrone, energy quality, hyposynchrone

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Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

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Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: identification, Hammerstein-Wiener, optimization, quantization

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Authors: Lourena M. Veríssimo, Lucas A. Machado, Renata Rutckeviski, Francisco H. Xavier Júnior, Éverton N. Alencar, Andreza R. V. Morais, Teresa R. F. Dantas, Christian M. Oliveira, Arnóbio A. Silva Júnior, Eryvaldo S. T. Egito

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This study aimed to obtain emulsion systems based on bullfrog oil (BO). The BO was extracted at 80ºC and analyzed by Gas Chromatography-Mass Spectrometry (GC/MS). The critical Hydrophilic-Lipophilic Balance (HLBc) Assay of the BO was performed through BO, Tween® 20, Span® 80 and deionized water mixtures using an Ultra-Turrax® and determined using dynamic light scattering, pH, electrical conductivity and creaming rate. Then, a pseudoternary phase diagram (PPD) was constructed by water titration. The GC/MS analysis of BO suggested Methyl Oleate (9.26%) as major compound. The HLBc was 12.1, wherein the correspondent emulsion showed a pH of 4.83±1.29, electrical conductivity of 103.65 µS, creaming rate of 2.51±0.54%, droplet size of 207.07±8.31 nm and polydispersity index of 0.212±0.005. The PPD showed different formulations characterized as O/W emulsions. Thus, the PPD proved to be a useful tool to produce BO emulsions, in which their constituents may vary within the range of the desired system.

Keywords: bullfrog (Rana catesbeiana Shaw) oil, emulsion production, hydrophilic-lipophilic balance, gas chromatography/mass spectrometry analysis

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Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

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The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

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Authors: Suchart Tripopsakul

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This paper uses data from the Global Entrepreneurship Monitor (GEM) to investigate the difference of attitudes towards entrepreneurial intention (EI). EI is generally assumed to be the single most relevant predictor of entrepreneurial behavior. The aim of this paper is to examine a range of attitudes effect on individual’s intent to start a new venture. A cross-cultural comparison between Asia and Europe is used to further investigate the possible differences between potential entrepreneurs from these distinct national contexts. The empirical analysis includes a GEM data set of 10 countries (n = 10,306) which was collected in 2013. Logistic regression is used to investigate the effect of individual’s attitudes on EI. Independent variables include individual’s perceived capabilities, the ability to recognize business opportunities, entrepreneurial network, risk perceptions as well as a range of socio-cultural attitudes. Moreover, a cross-cultural comparison of the model is conducted including six ASEAN (Malaysia, Indonesia, Philippines, Singapore, Vietnam and Thailand) and four European nations (Spain, Sweden, Germany, and the United Kingdom). The findings support the relationship between individual’s attitudes and their entrepreneurial intention. Individual’s capability, opportunity recognition, networks and a range of socio-cultural perceptions all influence EI significantly. The impact of media attention on entrepreneurship and was found to influence EI in ASEAN, but not in Europe. On the one hand, Fear of failure was found to influence EI in Europe, but not in ASEAN. The paper develops and empirically tests attitudes toward Entrepreneurial Intention between ASEAN and Europe. Interestingly, fear of failure was found to have no significant effect in ASEAN, and the impact of media attention on entrepreneurship and was found to influence EI in ASEAN. Moreover, the resistance of ASEAN entrepreneurs to the otherwise high rates of fear of failure and high impact of media attention are proposed as independent variables to explain the relatively high rates of entrepreneurial activity in ASEAN as reported by GEM. The paper utilizes a representative sample of 10,306 individuals in 10 countries. A range of attitudes was found to significantly influence entrepreneurial intention. Many of these perceptions, such as the impact of media attention on entrepreneurship can be manipulated by government policy. The paper also suggests strategies by which Asian economy in particular can benefit from their apparent high impact of media attention on entrepreneurship.

Keywords: an entrepreneurial intention, attitude, GEM, ASEAN and Europe

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Authors: Lo Kar Yin, Law Ka Mei

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Architectural, engineering, construction and operations (AECO) industry practitioners have been well adapting to the dynamic construction market from the fundamental training of its discipline. As further triggered by the pandemic since 2019, great steps are taken in virtual environment and the best collaboration is strived with project teams without boundaries. With adoption of Building Information Modeling-based approach and qualitative analysis, this paper is to review quantity take-off and cost estimation process through modeling techniques in liaison with suppliers, fabricators, subcontractors, contractors, designers, consultants and services providers in the construction industry value chain for automatic project cost budgeting, project cost control and cost evaluation on design options of in-situ reinforced-concrete construction and Modular Integrated Construction (MiC) at design stage, variation of works and cash flow/spending analysis at construction stage as far as practicable, with a view to sharing the findings for enhancing mutual trust and co-operation among AECO industry practitioners. It is to foster development through a common prototype of design and build project delivery method in NEC Engineering and Construction Contract (ECC) Options A and C.

Keywords: building information modeling, cost estimation, quantity take-off, modeling techniques

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Authors: Elham Azimzadeh, Saeedeh Sepehri, Hamidollah Hassanlouei

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Obesity is associated with postural instability, might influence the quality of daily life, and could be considered a potential factor for falling in obese people. The fat body mass especially in the abdominal area may increase body sway. Furthermore, loss of visual feedback may induce a larger postural sway in obese people. Moreover, Muscle fatigue may impair the work capacity of the skeletal muscle and may alter joint proprioception. So, the purpose of this study was to investigate the effect of physical fatigue and visual feedback on body sway and strength of lower extremities in obese people. 12 obese (4 female, 8 male; BMI >30 kg/m2), and 12 normal weight (4 female, 8 male; BMI: 20-25 kg/m2) subjects aged 37- 47 years participated in this study. The postural stability test on the Biodex balance system was used to characterize postural control along the anterior-posterior (AP) and mediolateral (ML) directions in eyes open and eyes closed conditions and maximal voluntary contraction (MVC) of knee extensors and flexors were measured before and after the high-intensity exhausting exercise protocol on the ergometer bike to confirm the presence of fatigue. Results indicated that the obese group demonstrated significantly greater body sway, in all indices (ML, AP, overall) compared with the normal weight group (eyes open). However, when visual feedback was eliminated, fatigue impaired the balance in the overall and AP indicators in both groups; ML sway was higher only in the obese group after exerting the fatigue in the eyes closed condition. Also, maximal voluntary contraction of knee extensors was impaired in the fatigued normal group but, there was no significant impairment in knee flexors MVC in both group. According to the findings, peripheral fatigue was associated with altered postural control in upright standing when eyes were closed, and that mechanoreceptors of the feet may be less able to estimate the position of the body COM over the base of support in the loss of visual feedback. This suggests that the overall capability of the postural control system during upright standing especially in the ML direction could be lower due to fatigue in obese individuals and could be a predictor of future falls.

Keywords: maximal voluntary contraction, obesity, peripheral fatigue, postural control, visual feedback

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Authors: T. D. Tran, H. Schlegel, R. Neugebauer

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Ball screws are an important component in machine tools. In mechatronic systems and machine tools, a ball screw has to work usually at a high speed. Otherwise the axial compliance of the ball screw, in combination with the inertia of the slide, the motor, the coupling and the screw, will cause an oscillation resonance, which limits the systems bandwidth and consequently influences performance of the motion controller. In this paper, the modal analysis method by measuring and analysing the vibrating parameters of the ball screw system to determine the dynamic characteristic of existing structures is used. On the one hand, the results of this study were obtained by the theoretical analysis and the modal testing of a ball screw system test station with the help of an impact hammer, respectively using excitation by motor. The experimental study showed oscillating forms of the ball screw for each frequency and obtained eigenfrequencies of the ball screw system. On the other hand, in this research a simulation with the help of the numerical modal analysis in order to analyse the oscillation and to find the eigenfrequencies of the ball screw system is used. Furthermore, the model order reduction by modal reduction and also according to Guyan is carried out. On the basis of these results a secure and also rapid commissioning of the control loops with regard to operating in their optimal function is targeted.

Keywords: modal analysis, ball screw, controller system, machine tools

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Authors: Eiji Okano, Kazuyuki Inagaki

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We revisit Uribe's `Fiscal Theory of Sovereign Risk' advocating that there is a trade-off between stabilizing inflation and suppressing default. We develop a class of dynamic stochastic general equilibrium (DSGE) model with nominal rigidities and compare two de facto inflation stabilization policies, optimal monetary policy and optimal monetary and fiscal policy with the minimizing interest rate spread policy which completely suppress the default. Under the optimal monetary and fiscal policy, not only the nominal interest rate but also the tax rate work to minimize welfare costs through stabilizing inflation. Under the optimal monetary both inflation and output gap are completely stabilized although those are fluctuating under the optimal monetary policy. In addition, volatility in the default rate under the optimal monetary policy is considerably lower than one under the optimal monetary policy. Thus, there is not the SI-SD trade-off. In addition, while the minimizing interest rate spread policy makes inflation rate severely volatile, the optimal monetary and fiscal policy stabilize both the inflation and the default. A trade-off between stabilizing inflation and suppressing default is not so severe what pointed out by Uribe.

Keywords: sovereign risk, optimal monetary policy, fiscal theory of the price level, DSGE

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Authors: Rasha S. Kamal, Reham I. El-Shazly, Reem K. Farag

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Green nano-branched structural compounds were synthesized by adding 1% by weight of clay nanoparticle to different moles ratios of either dodecyl acrylate or triethylenetetramine using a simple one-pot method. The synthesized nano polymers were provided with different terminations. In order to confirm the chemical structure of the produced nanocomposites, FTIR and 1HNMR spectroscopy were performed. Additionally, Dynamic Light Scattering (DLS) analysis was used to assess the size and dispersion of the produced branching nano polymers. Using a Gel-permeation chromatograph, the molecular weights of the produced modified green nano hyperbranched polymer with various terminations were determined. the prepared nano samples with different molar feed ratios dodecyl acrylate: triethylenetetramine (DDA: TETA) was designed as An, Bn, Cn, Dn and En. Moreover, the synthesized compounds are expressed as viscosity index improvers (VII); The VI rises when prepared additive concentrations in the solution improve, as does the VI as prepared hyperbranched polymers' triethylenetetramine content rises, and the most effective VI is (E). All of the synthesized green hyperbranched nanocomposites have Newtonian rheological behavior as their rheological behavior.

Keywords: green hyperbranched polymer, DLS, viscosity index improver, Michael addition, nano clay

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Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

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In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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Authors: Babak Mohajeri, Sen Bao, Timo Nyberg

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Customer experience is increasingly the differentiator between successful companies and those who struggle. Currently, customer experiences become more dynamic; and they advance with each interaction between the company and a customer. Every customer conversation and any effort to evolve these conversations would be beneficial and should ultimately result in a positive customer experience. The aim of this paper is to analyze the evolving customer experience management landscape and the relevant challenges and opportunities. A case study on the “paper machine” companies is chosen. Hence, this paper analyzes the challenges and opportunities in customer experience management of paper machine companies for the case of “road to steel”. Road to steel shows the journey of steel from raw material to end product (i.e. paper machine in this paper). ALPHA (Steel company) and BETA (paper machine company), are chosen and their efforts to evolve the customer experiences are investigated. Semi-structured interviews are conducted with experts in those companies to identify the challenges and opportunities of the evolving customer experience management from their point of view. The findings of this paper contribute to the theory and business practices in the realm of the evolving customer experience management landscape.

Keywords: Customer Experience Management, Paper Machine , Value Chain Management, Risk Analysis

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Authors: Christian H. Sanabria-Montaña, Rodrigo Huerta-Quintanilla

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A lattice network is a special type of network in which all nodes have the same number of links, and its boundary conditions are periodic. The most basic lattice network is the ring, a one-dimensional network with periodic border conditions. In contrast, the Cartesian product of d rings forms a d-dimensional lattice network. An analytical expression currently exists for the clustering coefficient in this type of network, but the theoretical value is valid only up to certain connectivity value; in other words, the analytical expression is incomplete. Here we obtain analytically the clustering coefficient expression in d-dimensional lattice networks for any link density. Our analytical results show that the clustering coefficient for a lattice network with density of links that tend to 1, leads to the value of the clustering coefficient of a fully connected network. We developed a model on criminology in which the generalized clustering coefficient expression is applied. The model states that delinquents learn the know-how of crime business by sharing knowledge, directly or indirectly, with their friends of the gang. This generalization shed light on the network properties, which is important to develop new models in different fields where network structure plays an important role in the system dynamic, such as criminology, evolutionary game theory, econophysics, among others.

Keywords: clustering coefficient, criminology, generalized, regular network d-dimensional

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Authors: Shi Yu Wang, Qian Wei Zhang, He Li, Hao Han He, Yun Bo Li

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The spatial controls of electromagnetic (EM) waves have always been a research hot spot in recent years. And the rapid development of metasurface-based technologies has provided more freedoms for manipulating the EM waves. Here we propose the design of reconfigurable and non-reciprocal metasurface with independent controls of transmission gain, attenuation and phase. The proposed meta-atom mainly consists of the cascaded textures including the receiving antenna, the middle layer in which the power amplifiers (PAs), programmable attenuator and phase shifter locate, and the transmitting antenna. The programmable attenuator and phase shifter can realize the dynamic controls of transmission amplitude and phase independently, and the PA devices in the meta-atom can actualize the performance of non-reciprocal transmission. The proposed meta-atom is analyzed applying field-circuit co-simulation and a sample of the meta-atom is fabricated and measured under using two standard waveguides. The measured results verify the ability of the independent manipulation for transmission amplitude and phase of the proposed the meta-atom and the design method has been verified very well correspondingly.

Keywords: active circuits, independent controls of multiple electromagnetic features, non-reciprocal electromagnetic transmission, reconfigurable and programmable

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Authors: Khries Sawsan

Abstract:

the phenomenon of urbanization is considered as one of the most important tourism resources that differ from one country to another and from one region to another in the same country. Our concern in tourism accommodation is explained by the fact that their location is directly related to the movement to tourist sites .Besides, these constructions comport security considered as the most important motivation for tourists in their choice of any destination. Hotels are the most representative expression of tourism. This is due to their physical prominence in the landscape and being the sole urban component totally unique to tourism. This study sheds light on the impact of tourism development on the spatial pattern in Jordan. It describes the linkages between existing tourism development policies and the spatial development patterns that have occurred as a result throughout Jordan, particularly looking at the impact that tourism has had on the physical environment of major tourism destinations. It puts an illustrative plan of the impact of the augmentation of tourism accommodations in Jordan in the past 40 years ago. The findings of this study help us to understand better the operation of Jordan’ dynamic changes in the location An intensive analysis is then applied on a representative case study in three regions: Amman, Petra and Aqaba. The study proceeds from an historical perspective to, show the evolution of the current development patterns an increase of tourism’s impact on spatial, in the presence of factors as political and economic stability, is expected.

Keywords: spatial patterns, urbanisation, spatial transformations, tourism planning, Jordan

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Authors: Yuntao Liu, Lei Wang, Haoran Xia

Abstract:

Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Van-Dycke Sarpong Asare, Vincent Adongo

Abstract:

Field measurement of subsurface seismic p-wave velocities was undertaken through seismic refraction tomography. The aim of this work is to obtain a model of the shallow subsurface material elastic properties relevant for geotechnical site characterization. The survey area is at Pwalugu in Northern Ghana, where a multipurpose dam, for electricity generation, irrigation, and potable water delivery, is being planned. A 24-channel seismograph and 24, 10 Hz electromagnetic geophones, deployed 5 m apart constituted the acquisition hardware. Eleven (2-D) seismic refraction profiles, nine of which ran almost perpendicular and two parallel to the White Volta at Pwalugu, were acquired. The refraction tomograms of the thirteen profiles revealed a subsurface model consisting of one minor and one major acoustic impedance boundaries – the top dry/loose sand and the variably weathered sandstone contact, and the overburden-sandstones bedrock contact respectively. The p-wave velocities and by inference, with a priori values of poison ratios, the s-wave velocities, assisted in characterizing the geotechnical conditions of the proposed site and also in evaluating the dynamic properties such as the maximum shear modulus, the bulk modulus, and the Young modulus.

Keywords: tomography, characterization, consolidated, Pwalugu and seismograph

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

Abstract:

This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

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Authors: Shamima Akhter, Samira Bagheri, M. Shalauddin, Wan Jefrey Basirun

Abstract:

In the present study, a nanocomposite of f-MWCNTs-Chitosan was prepared by the immobilization of Co(II) transition metal through self-assembly method and used for the simultaneous voltammetric determination of paracetamol (PA). The composite material was characterized by field emission scanning electron microscopy (FESEM) and energy dispersive X-Ray analysis (EDX). The electroactivity of cobalt immobilized f-MWCNTs with excellent adsorptive polymer chitosan was assessed during the electro-oxidation of paracetamol. The resulting GCE modified f-MWCNTs/CTS-Co showed electrocatalytic activity towards the oxidation of PA. The electrochemical performances were investigated using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV) methods. Under favorable experimental conditions, differential pulse voltammetry showed a linear dynamic range for paracetamol solution in the range of 0.1 to 400µmol L⁻¹ with a detection limit of 0.01 µmol L⁻¹. The proposed sensor exhibited significant selectivity for the paracetamol detection. The proposed method was successfully applied for the determination of paracetamol in commercial tablets and human serum sample.

Keywords: nanomaterials, paracetamol, electrochemical technique, multi-wall carbon nanotube

Procedia PDF Downloads 198