Search results for: vibration isolation performance

Authors: Alok Madan, Arshad K. Hashmi

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Performance based design (PBD) is an iterative exercise in which a preliminary trial design of the building structure is selected and if the selected trial design of the building structure does not conform to the desired performance objective, the trial design is revised. In this context, development of a fundamental approach for performance based seismic design of masonry infilled frames with minimum number of trials is an important objective. The paper presents a plastic design procedure based on the energy balance concept for PBD of multi-story multi-bay masonry infilled reinforced concrete (R/C) frames subjected to near-field earthquakes. The proposed energy based plastic design procedure was implemented for trial performance based seismic design of representative masonry infilled reinforced concrete frames with various practically relevant distributions of masonry infill panels over the frame elevation. Non-linear dynamic analyses of the trial PBD of masonry infilled R/C frames was performed under the action of near-field earthquake ground motions. The results of non-linear dynamic analyses demonstrate that the proposed energy method is effective for performance based design of masonry infilled R/C frames under near-field as well as far-field earthquakes.

Keywords: masonry infilled frame, energy methods, near-fault ground motions, pushover analysis, nonlinear dynamic analysis, seismic demand

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Authors: Kahil Amar, Meziani Faroudja, Khelil Nacim

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The principal objective of this study is the evaluation of the seismic performance of reinforced concrete frame structures, taking into account of the behavior laws, reflecting the real behavior of materials, using CASTEM2000 software. A finite element model used is based in modified Takeda model with Timoshenko elements for columns and beams. This model is validated on a Vecchio experimental reinforced concrete (RC) frame model. Then, a study focused on the behavior of a RC frame with three-level and three-story in order to visualize the positioning the plastic hinge (plastic rotation), determined from the curvature distribution along the elements. The results obtained show that the beams of the 1^st and 2^nd level developed a very large plastic rotations, or these rotations exceed the values corresponding to CP (Collapse prevention with cp q_CP = 0.02 rad), against those developed at the 3^rd level, are between IO and LS (Immediate occupancy and life Safety with q_IO = 0.005 rad and rad q_LS = 0.01 respectively), so the beams of first and second levels submit a very significant damage.

Keywords: seismic performance, performance level, pushover analysis, plastic rotation, plastic hinge

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Authors: Jae-Yong Sim, Jung-Hun Kwon, Ji-Sung Park, Kee-Joe Lim

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One of the latest trends for insulation systems to improve the insulation performance is the use of eco-friendly hybrid insulation using compressed dry-air. Despite the excellent insulation performance of sulphurhexafluoride (SF6) gas, its use has been restricted due to the problems with significant global warming potential (GWP). Accordingly, lightning impulse performance of the hybrid insulation system covered with an aluminum trihydrate/silicone rubber (ATH/SIR) nanocomposite was examined in air at atmospheric pressure and in compressed air at pressures between 0.2 and 0.6 MPa. In the experiments, the most common breakdown path took place along the surface of the covered rod. The insulation reliability after several discharges should be guaranteed in hybrid insulation. On the other hand, the surface of the covered rod was carbonized after several discharges. Therefore, nanoscale ATH can be used as a reinforcement of covered dielectrics to inhibit carbonization on the surface of a covered rod. The results were analyzed in terms of the surface resistivity of the cover dielectrics.

Keywords: nanocomposite, hybrid insulation, ATH, dry-air

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Authors: Sheng Fu, Yinbo Gao, Hao Lin

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In the current mine air compressors monitoring system, there are some difficulties in the installation and maintenance because of the wired connection. To solve the problem, this paper introduces a new air compressors monitoring system based on ZigBee in which the monitoring parameters are transmitted wirelessly. The collecting devices are designed to form a cluster network to collect vibration, temperature, and pressure of air cylinders and other parameters. All these devices are battery-powered. Besides, the monitoring software in PC is developed using MFC. Experiments show that the designed wireless sensor network works well in the site environmental condition and the system is very convenient to be installed since the wireless connection. This monitoring system will have a wide application prospect in the upgrade of the old monitoring system of the air compressors.

Keywords: condition monitoring, wireless sensor network, air compressor, zigbee, data collecting

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Authors: Talah Aissa

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This paper reports an experimental study of the influence of marble powder used as a partial substitute for Portland cement (PC) on the mechanical properties and durability of high-performance concretes. The analysis of the experimental results on concrete at 15% content of marble powder with a fineness modulus of 11500 cm2/g, in a chloride environment, showed that it contributes positively to the perfection of its mechanical characteristics, its durability with respect to migration of chloride ions and oxygen permeability. On the basis of the experiments performed, it can be concluded that the marble powder is suitable for formulation of high performance concretes (HPC) and their properties are significantly better compared to the reference concrete (RC).

Keywords: marble powder, durability, concrete, cement

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Authors: A. N. Sharma

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A traditional medicine comprises a knowledge system, practices related to the cure of various ailments that developed over generations by indigenous people or populations. The indigenous populations developed a unique understanding with wild plants, herbs, etc., and earned specialized knowledge of disease pattern and curative therapy-though hard experiences, common sense, trial, and error methods. Here, an attempt has been made to study the possible aspects of traditional medicines for the enhancement of male sexual performance among the indigenous populations of Madhya Pradesh, India. Madhya Pradesh state is situated more or less in the central part of India. The data have been collected from the 305 Bharias of Patalkot, traditional health service providers of Sagar district, and other indigenous populations of Madhya Pradesh. It may be concluded that sizable traditional medicines exist in Madhya Pradesh, India, for the enhancement of male sexual performance, which still awaits for scientific exploration and intensive pharmaceutical investigations.

Keywords: Bharias, indigenous, Madhya Pradesh, sexual performance, traditional medicine

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Authors: R. Ajith, Kamal Bijlani

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Over the past few years, tremendous evolutions have happened in the educational discipline. Serious game, which is regarded as one of the most important inventions is being widely for learning purposes. Serious games can be used to negate the various drawbacks that the current evaluation and assessment methods have, like examination anxiety and the lack of proper feedback given to the learners. This paper proposes serious game as a tool for conducting evaluations and assessments. The examination anxiety faced by learners can be reduced, as they are provided with a game as an examination. The serious game also tracks learner’s actions, records them and provide feedback based on the predefined set of actions according to the course objectives. The appropriate feedback given to the learner will help in developmental activities in the learning process.

Keywords: serious games, evaluation, performance assessment, examination anxiety, performance feedback

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Authors: Elhameh Narimani, Mikhail Sorin, Philippe Micheau, Hakim Nesreddine

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Numerical models of the heat exchangers in ejector refrigeration system (ERS) were developed and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which were capable of estimating the zones’ lengths, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS based on its coefficient of performance (COP) and exergy efficiency. It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the exergy efficiency goes through a maximum before decreasing.

Keywords: Coefficient of Performance, COP, Ejector Refrigeration System, ERS, exergy efficiency (ηII), heat exchangers modeling, moving boundary method

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Authors: Jia Yi Yap, Angela S. H. Lee

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With the use of big data technologies, organization can get result that they are interested in. Big data technologies simply load all the data that is useful for the organizations and provide organizations a better way of analysing data. The purpose of this research is to get employees’ opinion from films in Malaysia to explore the use of big data technologies in their organization in order to provide how it may affect the perception of the employees on job performance. Therefore, in order to identify will accepting big data technologies in the organization affect the perception of the employee, questionnaire will be distributed to different employee from different Small and medium-sized enterprises (SME) organization listed in Malaysia. The conceptual model proposed will test with other variables in order to see the relationship between variables.

Keywords: big data technologies, employee, job performance, questionnaire

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Authors: Tang Wei, Yang Xiaofeng, Gui Yewei, Du Yanxia

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Complex lifting entry was selected for precise landing performance during the Mars Science Laboratory entry. This study aims to develop the three-dimensional numerical method for precise computation and the surface panel method for rapid engineering prediction. Detailed flow field analysis for Mars exploration mission was performed by carrying on a series of fully three-dimensional Navier-Stokes computations. The static aerodynamic performance was then discussed, including the surface pressure, lift and drag coefficient, lift-to-drag ratio with the numerical and engineering method. Computation results shown that the shock layer is thin because of lower effective specific heat ratio, and that calculated results from both methods agree well with each other, and is consistent with the reference data. Aerodynamic performance analysis shows that CG location determines trim characteristics and pitch stability, and certain radially and axially shift of the CG location can alter the capsule lifting entry performance, which is of vital significance for the aerodynamic configuration des0ign and inner instrument layout of the Mars entry capsule.

Keywords: Mars entry capsule, static aerodynamics, computational fluid dynamics, hypersonic

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Authors: Ndagi Salihu

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Corporate governance mechanisms are the control measures for ensuring that all the interests groups are equally represented and management are working towards wealth creation in the interest of all. Therefore, there are many empirical studies during the last three decades on corporate governance and firm performance. However, little is known about the effects of family ownership on the relationship between corporate governance and firm performance, especially in the developing economy like Nigeria. This limit our understanding of the unique governance dynamics of family ownership with regards firm performance. This study examined the impact of family ownership on the relationship between governance mechanisms and financial performance of publicly listed companies in Nigeria. The study adopted quantitative research methodology using correlational ex-post factor design and secondary data from annual reports and accounts of a sample of 23 listed companies for a period of 5 years (2014-2018). The explanatory variables are the board size, board composition, board financial expertise, and board audit committee attributes. Financial performance is proxy by Return on Assets (ROA) and Return on Equity (ROE). Multiple panel regression technique of data analysis was employed in the analysis, and the study found that family ownership has a significant positive effect on the relationships between corporate governance mechanisms and financial performance of publicly listed firms in Nigeria. This finding is the same for both the ROA and ROE. However, the findings indicate that board size, board financial expertise, and board audit committee attributes have a significant positive impact on the ROA and ROE of the sample firms after the moderation. Moreover, board composition has significant positive effect on financial performance of the sample listed firms in terms of ROA and ROE. The study concludes that the use of family ownership in the control of firms in Nigeria could improve performance by reducing the opportunistic actions managers as well as agency problems. The study recommends that publicly listed companies in Nigeria should allow significant family ownership of equities and participation in management.

Keywords: profitability, board characteristics, agency theory, stakeholders

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Authors: Kostas Metaxiotis, Kostas Liagkouras

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This study presents an Expert System specially designed to be used with Multiobjective Evolutionary Algorithms (MOEAs) for the solution of the portfolio selection problem. The validation of the proposed hybrid System is done by using data sets from Hang Seng 31 in Hong Kong, DAX 100 in Germany and FTSE 100 in UK. The performance of the proposed system is assessed in comparison with the Non-dominated Sorting Genetic Algorithm II (NSGAII). The evaluation of the performance is based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it. The results show that the proposed hybrid system is efficient for the solution of this kind of problems.

Keywords: expert systems, multi-objective optimization, evolutionary algorithms, portfolio selection

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Authors: Abul Bashar

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The recent surge in the adoption of cloud computing systems by various organizations has brought forth the challenge of evaluating their performance. One of the major issues faced by the cloud service providers and customers is to assess the ability of cloud computing systems to provide the desired services in accordance to the QoS and SLA constraints. To this end, an opportunity exists to develop means to ensure that the desired performance levels of such systems are met under simulated environments. This will eventually minimize the service disruptions and performance degradation issues during the commissioning and operational phase of cloud computing infrastructure. However, it is observed that several simulators and modelers are available for simulating the cloud computing systems. Therefore, this paper presents a critical evaluation of the state-of-the-art modeling and simulation frameworks applicable to cloud computing systems. It compares the prominent simulation frameworks in terms of the API features, programming flexibility, operating system requirements, supported services, licensing needs and popularity. Subsequently, it provides recommendations regarding the choice of the most appropriate framework for researchers, administrators and managers of cloud computing systems.

Keywords: cloud computing, modeling framework, performance evaluation, simulation tools

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Jihad S. Daba, Jean-Pierre Dubois, Georges El Soury

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Fifth generation wireless networks guarantee significant capacity enhancement to suit more clients and services at higher information rates with better reliability while consuming less power. The deployment of massive multiple-input-multiple-output technology guarantees broadband wireless networks with the use of base station antenna arrays to serve a large number of users on the same frequency and time-slot channels. In this work, we evaluate the performance of massive multiple-input-multiple-output systems (MIMO) systems in 5^th generation cellular networks in terms of capacity and bit error rate. Several cases were considered and analyzed to compare the performance of massive MIMO systems while varying the number of antennas at both transmitting and receiving ends. We found that, unlike classical MIMO systems, reducing the number of transmit antennas while increasing the number of antennas at the receiver end provides a better solution to performance enhancement. In addition, enhanced orthogonal frequency division multiplexing and beam division multiple access schemes further improve the performance of massive MIMO systems and make them more reliable.

Keywords: beam division multiple access, D2D communication, enhanced OFDM, fifth generation broadband, massive MIMO

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Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

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Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

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Authors: Binoy Chandra Sarma, S. K. Deb

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Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study. Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study.

Keywords: dryer, polygeneration, moisture, equilibrium, humidity

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Authors: Ron Cottam, Nils Langloh, Willy Ranson, Roger Vounckx

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We start by formally describing the requirements for environmental-reaction survival computation in a natural temporally-demanding medium, and develop this into a more general model of the evolutionary context as a computational machine. The effect of this development is to replace deterministic logic by a modified form which exhibits a continuous range of dimensional fractal diffuseness between the isolation of perfectly ordered localization and the extended communication associated with nonlocality as represented by pure causal chaos. We investigate the appearance of life and consciousness in the derived general model, and propose a representation of Nature within which all localizations have the character of quasi-quantal entities. We compare our conclusions with Heisenberg’s uncertainty principle and nonlocal teleportation, and maintain that computability is the principal influence on evolution in the model we propose.

Keywords: computability, evolution, life, localization, modeling, nonlocality

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Authors: Chechen Liao, Chin Yi Yang

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Although several factors that affect learning to program have been identified over the years, there continues to be no indication of any consensus in understanding why some students learn to program easily and quickly while others have difficulty. Seldom have researchers considered the problem of how to help the students enhance the programming learning outcome. The research had been conducted at a high school in Taiwan. Students participating in the study consist of 330 tenth grade students enrolled in the Basic Computer Concepts course with the same instructor. Two types of training methods-instruction-oriented and exploration-oriented were conducted. The result of this research shows that the instruction-oriented training method has better learning performance than exploration-oriented training method.

Keywords: learning performance, programming learning, TDD, training method

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Authors: Tawanda Mushiri, Charles Mbohwa

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The performance of door assembly is very significant for the vehicle design. In the present paper, the finite element method is used in the development processes of the door assembly. The stiffness, strength, modal characteristic, and anti-extrusion of a newly developed passenger vehicle door assembly are calculated and evaluated by several finite element analysis commercial software. The structural problems discovered by FE analysis have been modified and finally achieved the expected door structure performance target of this new vehicle. The issue in focus is to predict the performance of the door assembly by powerful finite element analysis software, and optimize the structure to meet the design targets. It is observed that this method can be used to forecast the performance of vehicle door efficiently when it’s designed. In order to reduce lead time and cost in the product development of vehicles more development will be made virtually.

Keywords: vehicle door, structure, strength, stiffness, modal characteristic, anti-extrusion, Finite Element Method

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: adaptive filtering, sparse system identification, TD-LMS algorithm, VSSLMS algorithm

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Authors: Ould Bouamama, M. Bressel, D. Hissel, M. Hilairet

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Fuel cell (FC) is one of the best alternatives of fossil energy. Recently, the research community of fuel cell has shown a considerable interest for diagnosis in view to ensure safety, security, and availability when faults occur in the process. The problematic for model based FC diagnosis consists in that the model is complex because of coupling of several kind of energies and the numerical values of parameters are not always known or are uncertain. The present paper deals with use of one tool: the Linear Fractional Transformation bond graph tool not only for uncertain modelling but also for monitorability (ability to detect and isolate faults) analysis and formal generation of robust fault indicators with respect to parameter uncertainties.The developed theory applied to a nonlinear FC system has proved its efficiency.

Keywords: bond graph, fuel cell, fault detection and isolation (FDI), robust diagnosis, structural analysis

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Authors: Thammanoon Charmjuree, Yuosre F. Badir, Umar Safdar

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There is a consensus among innovation scholars that knowledge is a vital antecedent for firm’s innovation; e.g., process innovation. Recently, there has been an increasing amount of attention to more open approaches to innovation. This open model emphasizes the use of purposive flows of knowledge across the organization boundaries. Firms adopt open innovation strategy to improve their innovation performance by bringing knowledge into the organization (inbound open innovation) to accelerate internal innovation or transferring knowledge outside (outbound open innovation) to expand the markets for external use of innovation. Reviewing open innovation research reveals the following. First, the majority of existing studies have focused on inbound open innovation and less on outbound open innovation. Second, limited research has considered the possible interaction between both and how this interaction may impact the firm’s innovation performance. Third, scholars have focused mainly on the impact of open innovation strategy on product innovation and less on process innovation. Therefore, our knowledge of the relationship between firms’ inbound and outbound open innovation and how these two impact process innovation is still limited. This study focuses on the firm’s external technology acquisition (ETA) and external technology exploitation (ETE) and the firm’s process innovation performance. The ETA represents inbound openness in which firms rely on the acquisition and absorption of external technologies to complement their technology portfolios. The ETE, on the other hand, refers to commercializing technology assets exclusively or in addition to their internal application. This study hypothesized that both ETA and ETE have a positive relationship with process innovation performance and that ETE fully mediates the relationship between ETA and process innovation performance, i.e., ETA has a positive impact on ETE, and turn, ETE has a positive impact on process innovation performance. This study empirically explored these hypotheses in software development firms in Thailand. These firms were randomly selected from a list of Software firms registered with the Department of Business Development, Ministry of Commerce of Thailand. The questionnaires were sent to 1689 firms. After follow-ups and periodic reminders, we obtained 329 (19.48%) completed usable questionnaires. The structure question modeling (SEM) has been used to analyze the data. An analysis of the outcome of 329 firms provides support for our three hypotheses: First, the firm’s ETA has a positive impact on its process innovation performance. Second, the firm’s ETA has a positive impact its ETE. Third, the firm’s ETE fully mediates the relationship between the firm’s ETA and its process innovation performance. This study fills up the gap in open innovation literature by examining the relationship between inbound (ETA) and outbound (ETE) open innovation and suggest that in order to benefits from the promises of openness, firms must engage in both. The study went one step further by explaining the mechanism through which ETA influence process innovation performance.

Keywords: process innovation performance, external technology acquisition, external technology exploitation, open innovation

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Authors: Ali H. Daraji, Ye Jianqiao

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The micro electrical devices of the wireless sensor network are continuously developed and become very small and compact with low electric power requirements using limited period life conventional batteries. The low power requirement for these devices, cost of conventional batteries and its replacement have encouraged researcher to find alternative power supply represented by energy harvesting system to provide an electric power supply with infinite period life. In the last few years, the investigation of energy harvesting for structure health monitoring has increased to powering wireless sensor network by converting waste mechanical vibration into electricity using piezoelectric sensors. Optimisation of energy harvesting is an important research topic to ensure a flowing of efficient electric power from structural vibration. The harvesting power is mainly based on the properties of piezoelectric material, dimensions of piezoelectric sensor, its position on a structure and value of an external electric load connected between sensor electrodes. Larger surface area of sensor is not granted larger power harvesting when the sensor area is covered positive and negative mechanical strain at the same time. Thus lead to reduction or cancellation of piezoelectric output power. Optimisation of energy harvesting is achieved by locating these sensors precisely and efficiently on the structure. Limited published work has investigated the energy harvesting for aircraft wing. However, most of the published studies have simplified the aircraft wing structure by a cantilever flat plate or beam. In these studies, the optimisation of energy harvesting was investigated by determination optimal value of an external electric load connected between sensor electrode terminals or by an external electric circuit or by randomly splitting piezoelectric sensor to two segments. However, the aircraft wing structures are complex than beam or flat plate and mostly constructed from flat and curved skins stiffened by stringers and ribs with more complex mechanical strain induced on the wing surfaces. This aircraft wing structure bonded with discrete macro fibre composite sensors was modelled using multiphysics finite element to optimise the energy harvesting by determination of the optimal number of sensors, location and the output resistance load. The optimal number and location of macro fibre sensors were determined based on the maximization of the open and close loop sensor output voltage using frequency response analysis. It was found different optimal distribution, locations and number of sensors bounded on the top and the bottom surfaces of the aircraft wing.

Keywords: energy harvesting, optimisation, sensor, wing

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Authors: Vitoldas Vaitkevičius, Evaldas Šerelis

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Silica fume, also known as microsilica (MS) or condensed silica fume is a by-product of the production of silicon metal or ferrosilicon alloys. Silica fume is one of the most effective pozzolanic additives which could be used for ultrahigh performance and other types of concrete. Despite the fact, however is not entirely clear, which amount of silica fume is most optimal for UHPC. Main objective of this experiment was to find optimal amount of silica fume for UHPC with and without thermal treatment, when different amount of quartz powder is substituted by silica fume. In this work were investigated four different composition of UHPC with different amount of silica fume. Silica fume were added 0, 10, 15 and 20% of cement (by weight) to UHPC mixture. Optimal amount of silica fume was determined by slump, viscosity, qualitative and quantitative XRD analysis and compression strength tests methods.

Keywords: compressive strength, silica fume, ultrahigh performance concrete, XRD

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Authors: Hager Elsheikh

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Context: Pancreatitis is a condition characterized by inflammation in the pancreas, which can lead to serious complications if untreated. Both acute and chronic pancreatitis are associated with immune reactions and fibrosis, which further damage the pancreas. The type 2 immune response, primarily driven by alternative activated macrophages (AAMs), plays a significant role in the development of fibrosis. The IL-4/STAT6 pathway is a crucial signaling pathway for the activation of M2 macrophages. Pancreatic fibrosis is induced by dysregulated inflammatory responses and can result in the autodigestion and necrosis of pancreatic acinar cells. Research Aim: The aim of this study is to investigate the impact of STAT6, a crucial molecule in the IL-4/STAT6 pathway, on the severity and development of fibrosis during acute and chronic pancreatitis. The research also aims to understand the influence of the JAK/STAT6 signaling pathway on the balance between fibrosis and regeneration in the presence of different macrophage populations. Methodology: The research utilizes murine models of acute and chronic pancreatitis induced by cerulean injection. Animal models will be employed to study the effect of STAT6 knockout on disease severity and fibrosis. Isolation of acinar cells and cell culture techniques will be used to assess the impact of different macrophage populations on wound healing and regeneration. Various techniques such as PCR, histology, immunofluorescence, and transcriptomics will be employed to analyze the tissues and cells. Findings: The research aims to provide insights into the mechanisms underlying tissue fibrosis and wound healing during acute and chronic pancreatitis. By investigating the influence of the JAK/STAT6 signaling pathway and different macrophage populations, the study aims to understand their impact on tissue fibrosis, disease severity, and pancreatic regeneration. Theoretical Importance: This research contributes to our understanding of the role of specific signaling pathways, macrophage polarization, and the type 2 immune response in pancreatitis. It provides insights into the molecular mechanisms underlying tissue fibrosis and the potential for targeted therapies. Data Collection and Analysis Procedures: Data will be collected through the use of murine models, isolation and culture of acinar cells, and various experimental techniques such as PCR, histology, immunofluorescence, and transcriptomics. Data will be analyzed using appropriate statistical methods and techniques, and the findings will be interpreted in the context of the research objectives. Conclusion: By investigating the mechanisms of tissue fibrosis and wound healing during acute and chronic pancreatitis, this research aims to enhance our understanding of the disease progression and potential therapeutic targets. The findings have theoretical importance in expanding our knowledge of pancreatic fibrosis and the role of macrophage polarization in the context of the type 2 immune response.

Keywords: immunity in chronic diseases, pancreatitis, macrophages, immune response

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Authors: Jun Wang, Ge Zhang

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Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: R. A. Moronfolu, I. M. Ndaks, O. E. Ifekoya

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This study investigated Gender Stereotypes in Leadership Behaviour and its consequent effect on Job Performance of Sports Council Personnel in Lagos State. The descriptive research method was adapted in conducting the study, while eighty sports personnel of Lagos State sports council, Lagos, Nigeria were drawn as respondents using the stratified random sampling technique. A self-structured questionnaire titled “ Gender- Leader Performance Questionnaire (GLPQ) ”was used for data collection. The GLPQ was face validated by three experts in sports management and was subjected to a pilot test using the test retest method for reliability. A total of eighty copies of the validated GLPQ were administered on selected respondents and retrieved on the spot. The descriptive statistics of frequency counts and percentages were used in describing the demographic data collected, while the inferential statistics of Chi-square (X2) and Analysis of Variance (ANOVA) were used in drawing inferences at a level of significance of 0.05. It was observed that gender stereotypes and behaviours of leaders in Lagos State Sports Council, significantly differ. In addition, gender stereotypes and leadership behavior were observed to significantly influence the job performance of sports council personnel in Lagos State.

Keywords: gender, leadership, stereotype, performance

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Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

Abstract:

The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

Procedia PDF Downloads 461

Authors: Yassine Jadi, Lin Jie

Abstract:

In order to serve the society in an electronic manner, many developing countries have launched tremendous e-government projects. The strategies of development and implementation e-government system have reached different levels, and to ensure consistency of development, the governments need to evaluate e-government performance. The United nation has design e-government development ranking index (EGDI) that rely on three indexes, Online service index (OSI), Telecommunication Infrastructure index (TII), and human capital index( HCI) which are not reflecting the interaction between a government and their citizens. Based on data envelopment analyses (DEA) technique, we are using E-participating index (EPI) as an output of government effort to evaluate the performance of e-government system. Therefore, the ranking index can be achieved in efficiency manner.

Keywords: e-government, DEA, efficiency measurement, EGDI

Procedia PDF Downloads 376