Search results for: machine performance

Authors: Pooree Sakot, Marndarath Suksanga

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Organizations are under increasing pressure to improve performance and maximize the contribution of every employee. Employee engagement has become an attractive business proposition. The triple bottom line consists of three Ps: profit, people and planet. It aims to measure the financial, social and environmental performance of the corporation over a period of time. People are the most important asset of every organization. Most of the studies suggest that employee engagement improves the bottom line in almost every instance and it is well worth all organizational efforts to actively engage employees. Engaged employees have an impact on productivity and financial performance. Efficient leadership and effective management can take place if emerging paradigm like employee engagement is appropriately understood and put into practice. Employee engagement starts at the first step i.e. recruitment of an employee to the last step i.e. retirement .The HR Practices of an organization play the most major role in helping the employees walk the extra mile. Effective employee engagement is the key component for improved organizational performance.

Keywords: employee engagement, higher education, tool, success

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Authors: Ambra Giovannelli, Erika Maria Archilei

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The amount of the electrical power required by refrigeration systems is relevant worldwide. It is evaluated in the order of 15% of the total electricity production taking refrigeration and air-conditioning into consideration. For this reason, in the last years several energy saving techniques have been proposed to reduce the power demand of such plants. The paper deals with the development of an innovative internal recovery system for cryogenic cooling plants. Such a system consists in a Compressor-Expander Group (CEG) designed on the basis of the automotive turbocharging technology. In particular, the paper is focused on the design of the expander, the critical component of the CEG system. Due to the low volumetric flow entering the expander and the high expansion ratio, a commercial turbocharger expander wheel was strongly modified. It was equipped with a transonic nozzle, designed to have a radially inflow full admission. To verify the performance of such a machine and suggest improvements, two different set of nozzles have been designed and modelled by means of the commercial Ansys-CFX software. steady-state 3D CFD simulations of the second-generation prototype are presented and compared with the initial ones.

Keywords: vapour cCompression systems, energy saving, refrigeration plant, organic fluids, radial turbine

Procedia PDF Downloads 192

Authors: Melissa Ramirez, Mohammad Awal

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The Inflow Performance Relationship (IPR) of a well is a relation between the oil production rate and flowing bottom-hole pressure. This relationship is an important tool for petroleum engineers to understand and predict the well performance. In the petroleum industry, IPR correlations are used to design and evaluate well completion, optimizing well production, and designing artificial lift. The most commonly used IPR correlations models are Vogel and Wiggins, these models are applicable to homogeneous and isotropic reservoir data. In this work, a new IPR model is developed to determine inflow performance relationship of oil wells in a naturally fracture reservoir. A 3D black-oil reservoir simulator is used to develop the oil mobility function for the studied reservoir. Based on simulation runs, four flow rates are run to record the oil saturation and calculate the relative permeability for a naturally fractured reservoir. The new method uses the result of a well test analysis along with permeability and pressure-volume-temperature data in the fluid flow equations to obtain the oil mobility function. Comparisons between the new method and two popular correlations for non-fractured reservoirs indicate the necessity for developing and using an IPR correlation specifically developed for a fractured reservoir.

Keywords: inflow performance relationship, mobility function, naturally fractured reservoir, well test analysis

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Authors: Majid Ali, Xinfang Jin, Victor Eniola, Henning Hoene

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The performance of proton exchange membrane (PEM) fuel cells is sensitive to several factors, including power fluctuations, hydrogen utilization, and the quality orientation of the fuel cell stack. In this study, we investigate the impact of these factors on the performance of a PEM fuel cell. We start by analyzing the power fluctuations that are typical in renewable energy systems and their effects on the 50 Watt fuel cell's performance. Next, we examine the hydrogen utilization rate (0-1000 mL/min) and its impact on the cell's efficiency and durability. Finally, we investigate the quality orientation (three different positions) of the fuel cell stack, which can significantly affect the cell's lifetime and overall performance. The basis of our analysis is the utilization of experimental results, which have been further validated by comparing them with simulations and manufacturer results. Our results indicate that power fluctuations can cause significant variations in the fuel cell's voltage and current, leading to a reduction in its performance. Moreover, we show that increasing the hydrogen utilization rate beyond a certain threshold can lead to a decrease in the fuel cell's efficiency. Finally, our analysis demonstrates that the orientation of the fuel cell stack can affect its performance and lifetime due to non-uniform distribution of reactants and products. In summary, our study highlights the importance of considering power fluctuations, hydrogen utilization, and quality orientation in designing and optimizing PEM fuel cell systems. The findings of this study can be useful for researchers and engineers working on the development of fuel cell systems for various applications, including transportation, stationary power generation, and portable devices.

Keywords: fuel cell, proton exchange membrane, renewable energy, power fluctuation, experimental

Procedia PDF Downloads 112

Authors: Ranjit Singh

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Body fat % lean body mass and body type play vital role in sports performance. A sports person who is having optional body composition can show its performance flawlessly whereas other who is not physical fit may be more prone to injury. Competitive swimming is an association of plethora of aspects like morphological, physiological, biochemical, biomechanical and psychological. The primary key of the present research is to examine the correlation among selected morphological dimensions such as height, weight, body fat%, lean body mass, somatotype and swimming performance. The present study also focused to investigate by potential deficiencies if any and to find out remedial measures to curb the training stresses. Thirty (age group 10-14 years) swimmers undergoing training under skilled and professional coaches were selected in the present study. The morphological variables and performance criterion like 50 meter swimming time and speed were calculated by using standard training methodology. Correlation coefficient among body composition, somatotype and performance variables were assessed by using standard statistical package SPSS. Mean height, weight, fat% and lean body mass of the present group is 150.97±8.68 cm, 44.0±9.34 kg., 15.97±4.42 % and 37.10±8.77 kg respectively. Somatotype of the young swimmers of this research is revealed ectomorphic mesomorph. The analysis of the results Illustrated that swimming performance is significantly correlated (p<0.05) with height, body weight, mesomorphoic component and lean body mass. Body fat is significantly and negatively correlated (p<0.05) with mesomorphic component, lean body mass and swimming speed. From this present study, it can be concluded that along with techniques and tactics other the physical attributes also play significant role in swimming performance which can help the swimmers to excel in higher level of competition and swimmers having improved morphological qualities can ultimately perform well.

Keywords: body fat, mass, mesomorphic component, somatotype

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Authors: A. R. Mirzaee, M. Khajehpour

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Due to Simple Design, reasonable cost and easy implementation most people are reluctant to build buildings with masonry construction. Masonry Structures performance at earthquake are so limited. Of most earthquakes occurred in Iran and other countries, we can easily see that most of the damages are for masonry constructions and this is the evidence that we lack proper understanding of the performance of masonry buildings in earthquake. In this paper, according to field studies, conducted in past earthquakes. To evaluate the strengths and weaknesses points of the masonry constructions and also provide a solution to prevent such damage should be presented, and also program Examples of the correct bearing wall and tie-column design with the valid regulations (MSJC-08 (ASD)) will be explained.

Keywords: Masonry constructions, performance at earthquake, MSJC-08 (ASD), bearing wall, tie-column

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Authors: Michel Wakim, Rodrigo Rivera Tinoco

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Supersonic ejector is an economical device that use high pressure vapor to compress a low pressure vapor without any rotating parts or external power sources. Entrainment ratio is a major characteristic of the ejector performance, so the ejector performance is highly dependent on its geometry. The aim of this paper is to design ejector geometry, based on pre-specified operating conditions, and to study the flow behavior inside the ejector by using computational fluid dynamics ‘CFD’ by using ‘ANSYS FLUENT 15.0’ software. In the first section; 1-D mathematical model is carried out to predict the ejector geometry. The second part describes the flow behavior inside the designed model. CFD is the most reliable tool to reveal the mixing process at different parts of the supersonic turbulent flow and to study the effect of the geometry on the effective ejector area. Finally, the results show the effect of the geometry on the entrainment ratio.

Keywords: computational fluids dynamics, ejector, entrainment ratio, geometry optimization, performance

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Authors: Moti Zwilling, Srečko Natek

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This paper aims to present an innovative predictive analytics analysis in order to find the best combination between two consumers who strive to find their partner or in internet sites. The methodology shown in this paper is based on analysis of consumer preferences and involves data mining and machine learning search techniques. The study is composed of two parts: The first part examines by means of descriptive statistics the correlations between a set of parameters that are taken between man and women where they intent to meet each other through the social media, usually the internet. In this part several hypotheses were examined and statistical analysis were taken place. Results show that there is a strong correlation between the affiliated attributes of man and woman as long as concerned to how they present themselves in a social media such as "Facebook". One interesting issue is the strong desire to develop a serious relationship between most of the respondents. In the second part, the authors used common data mining algorithms to search and classify the most important and effective attributes that affect the response rate of the other side. Results exhibit that personal presentation and education background are found as most affective to achieve a positive attitude to one's profile from the other mate.

Keywords: dating sites, social networks, machine learning, decision trees, data mining

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Authors: D. P. Rahardja, M. Rahman Hakim, V. Sri Lestari

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An experiment was conducted to elucidate the effects of turmeric powder supplementation on egg production performance of old laying hens (104 weeks of age). There were 40 hens of Hysex Brown strain used in the study. They were caged individually, and randomly divided into 4 treatment groups of diet containing 0 (control), 1, 2 and 4 % oven dried turmeric powder for 3 periods of 4 weeks; Egg production (% hen day) and feed intake of the 4 treatment groups at the commencement of the experiment were not significantly different. In addition to egg production performance (%HD and egg weight), feed and water intakes were measured daily. The results indicated that feed intakes of the hen were significantly lowered when 4% turmeric powder supplemented, while there were no significant changes in water intakes. Egg production (%HD) were significantly increased and maintained at a higher level by turmeric powder supplementation up to 4% compared with the control, while the weight of eggs were not significantly affected. The research markedly demonstrated that supplementation of turmeric powder up to 4% could improve and maintain egg production performance of the old laying hen.

Keywords: curcumin, feed and water intake, old laying hen, egg production

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Authors: Akshay Dirisala

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Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.

Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models

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Authors: Trupti Diwan

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Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

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Authors: Fang Gong

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Distance measures are an indispensable part of many instance-based learning (IBL) and machine learning (ML) algorithms. The value difference metrics (VDM) and inverted specific-class distance measure (ISCDM) are among the top-performing distance measures that address nominal attributes. VDM performs well in some domains owing to its simplicity and poorly in others that exist missing value and non-class attribute noise. ISCDM, however, typically works better than VDM on such domains. To maximize their advantages and avoid disadvantages, in this paper, a selection approach: a discriminative model for nominal attributes-based distance measures is proposed. More concretely, VDM and ISCDM are built independently on a training dataset at the training stage, and the most credible one is recorded for each training instance. At the test stage, its nearest neighbor for each test instance is primarily found by any of VDM and ISCDM and then chooses the most reliable model of its nearest neighbor to predict its class label. It is simply denoted as a discriminative distance measure (DDM). Experiments are conducted on the 34 University of California at Irvine (UCI) machine learning repository datasets, and it shows DDM retains the interpretability and simplicity of VDM and ISCDM but significantly outperforms the original VDM and ISCDM and other state-of-the-art competitors in terms of accuracy.

Keywords: distance measure, discriminative model, nominal attributes, nearest neighbor

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Fekkak Bouazza, Menaa Mohamed, Loukriz Abdelhamid, Krim Mohamed L.

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This paper presents modeling and control strategy for the grid connected wind turbine system based on Permanent Magnet Synchronous Generator (PMSG). The considered system is based on back-to-back converter topology. The Grid Side Converter (GSC) achieves the DC bus voltage control and unity power factor. The Machine Side Converter (MSC) assures the PMSG speed control. The PMSG is used as a variable speed generator and connected directly to the turbine without gearbox. The pitch angle control is not either considered in this study. Further, Optimal Tip Speed Ratio (OTSR) based MPPT control strategy is used to ensure the most energy efficiency whatever the wind speed variations. A filter (L) is put between the GSC and the grid to reduce current ripple and to improve the injected power quality. The proposed grid connected wind system is built under MATLAB/Simulink environment. The simulation results show the feasibility of the proposed topology and performance of its control strategies.

Keywords: wind, grid, PMSG, MPPT, OTSR

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Authors: Ashish Lochan, Anil K. Dahiya, Amit Verma

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The idea of combining photovoltaic and solar thermal collector to provide electrical and heat energy is not new, however, it is an area of limited attention. Hybrid photovoltaic-thermals have become a focus point of interest in the field of solar energy. Integration of both (photovoltaic and thermal collector) provide greater opportunity for the use of renewable solar energy. This system converts solar energy into electricity and heat energy simultaneously. Theoretical performance analyses of hybrid PV/Ts have been carried out. Also, the temperature of water (as a heat carrier) have been calculated for different seasons with the help of TRANSYS.

Keywords: photovoltaic-thermal, solar energy, seasonal performance analysis, TRANSYS

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Hafsi Khebab, Zirari Mounir, Mohamed Nadjib Bouaziz

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High Global Warming Potential refrigerants (HydroFluroCarbons) are one of the worst greenhouse gases used in a wide variety of applications, including refrigeration and air-conditioning. Nanotechnology is a promising field in sustainable energy to reduce energy and ecological resource consumption for HVACR (heat, ventilation, air conditioning, and refrigeration) systems. Most researchers reported an improvement in heat transfer coefficient, Coefficient of performance. In this report, a brief summary has been done on the performance enhancement of the Vapor Compression Refrigeration system using HFC134a with nano refrigerants.

Keywords: nanorefrigerant, HFCs, greenhouse gases, GWP, HVACR systems, energy saving

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Authors: Mahendrasingh J. Pawar, M. D. Gaoner

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Ta-doped Nb2O5 (Ta content 0.5-2% mole fraction) nanoparticles in the range of 20-40 nm were synthesized by combustion technique. The crystalline phase, morphology and size of the nanoparticles were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM) and UV-vis spectroscopy. The specific surface area of the nanoparticles was measured by nitrogen adsorption (BET analysis). The undoped Nb2O5 nanoparticles were found to have the particles size in the range of 50−80 nm. The photocatalytic performance of the samples was characterized by degrading 20 mg/L toluene under UV−Vis irradiation. The results show that the Ta-doped Nb2O5 nanoparticles exhibit a significant increase in photocatalytic performance over the undoped Nb2O5 nanoparticles, and the Nb2O5 nanoparticles doped with 1.5% Ta and calcined at 450°C show the best photocatalytic performance.

Keywords: Nb2O5, Ta-doped Nb2O5, photodegradation of Toluene, combustion method

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Authors: Marco Morini, Nicolandrea Calabrese, Dario Chello

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Despite the international commitment of Algeria towards the development of energy efficiency and renewable energy in the country, the internal energy demand has been continuously growing during the last decade due to the substantial increase of population and of living conditions, which in turn has led to an unprecedented expansion of the residential building sector. The thermal building regulation is the technical document that establishes the calculation framework for the thermal performance of buildings in Algeria, setting up minimum obligatory targets for the thermal performance of new buildings. An update of this regulation is due in the coming years, and this paper discusses some proposals in this regard, with the aim to improve the energy efficiency of the building sector, particularly with regard to social housing. In particular, it proposes a methodology for drafting an energy performance label of new Algerian residential buildings, moving from the results of the thermal compliance verification and sizing of technical systems as defined in the RTB. Such an energy performance label – whose calculation method is briefly described in the paper – aims to raise citizens' awareness of the benefits of energy efficiency. It can represent the first step in a process of integrating technical installations into the calculation of the energy performance of buildings in Algeria.

Keywords: building, energy certification, energy efficiency, social housing, international cooperation, Mediterranean region

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Authors: Osuagwu Justine Ugochukwu

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Investigating the effects of transformational and transactional leadership styles on the performance of healthcare employees at the University Teaching Hospital (UNTH) in Enugu, Nigeria, was the goal of the research. The respondents were asked to fill out a structured questionnaire. The respondents were chosen using a straightforward random sampling technique and consisted of 370 health workers at the hospital. The result of the analysis revealed that transactional and transformational leadership style has a positive while ambidextrous leadership has a negative effect on healthcare workers' performance in UNTH, Enugu. Therefore, the management of public hospitals that have the capacity to change their top management approach to leadership styles will gain substantial support from their employees’ thereby increasing organizational commitment and performance among health workers. This will have remarkable social implications, one of which is a change in the work culture and attitude of medical personnel from the seemingly anti-community of patients to friendly engagement and treatment of patients leading to a harmonious coexistence among these individuals in society. Investigating ambidextrous leadership and the use of nonparametric analysis is unique and has brought brand-new knowledge to leadership literature.

Keywords: workers performance, transformational leadership, transactional leadership, governance quality, ambidextrous leadership

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Authors: H. Mansor, S. B. Mohd-Noor, T. S. Gunawan, S. Khan, N. I. Othman, N. Tazali, R. B. Islam

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This paper provides a comparative study on the performances of standard PID and adaptive PID controllers tested on travel angle of a 3-Degree-of-Freedom (3-DOF) Quanser bench-top helicopter. Quanser, a well-known manufacturer of educational bench-top helicopter has developed Proportional Integration Derivative (PID) controller with Linear Quadratic Regulator (LQR) for all travel, pitch and yaw angle of the bench-top helicopter. The performance of the PID controller is relatively good; however its performance could also be improved if the controller is combined with adaptive element. The objective of this research is to design adaptive PID controller and then compare the performances of the adaptive PID with the standard PID. The controller design and test is focused on travel angle control only. Adaptive method used in this project is self-tuning controller, which controller’s parameters are updated online. Two adaptive algorithms those are pole-placement and deadbeat have been chosen as the method to achieve optimal controller’s parameters. Performance comparisons have shown that the adaptive (deadbeat) PID controller has produced more desirable performance compared to standard PID and adaptive (pole-placement). The adaptive (deadbeat) PID controller attained very fast settling time (5 seconds) and very small percentage of overshoot (5% to 7.5%) for 10° to 30° step change of travel angle.

Keywords: adaptive control, deadbeat, pole-placement, bench-top helicopter, self-tuning control

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Authors: Somdech Rungsrisawas

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The objectives of this study are to examine the relationship between the competitive advantage of small and medium enterprises (SMEs) and their overall performance. A mixed method has been applied to identify the effect of determinants toward competitive advantage. The sample is composed of SMEs in product and service businesses. The study has been tested at an organizational level with samples of SME entrepreneurs, business successors, and board of directors or management team. Quantitative analysis has been conducted through multiple regression analysis with 400 samples. The findings illustrate that each aspect of competitive advantage needs a different set of driving factors to explain either the direct or the indirect effect on firm performance. Interestingly, technological capability is a perfect mediator and interorganizational cooperation toward competitive advantage. In addition, differentiation is difficult to be perceived by customers, as well as difficult to manage; however, it is considered important to develop an SMEs product or service for firm sustainably.

Keywords: competitive advantage, firm performance, technological capability, Small and Medium Enterprise (SMEs)

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Authors: Abeer K. Jameel, Harry Evdorides

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The Assessment of the road safety performance is a challengeable issue. This is not only because of the ineffective and unreliability of road and traffic crash data system but also because of its systematic character. Recent strategic plans and interventions implemented in some of the developed countries where a significant decline in the rate of traffic and road crashes considers that the road safety is a system. This system consists of four main elements which are: road user, road infrastructure, vehicles and speed in addition to other supporting elements such as the institutional framework and post-crash care system. To assess the performance of a system, it is required to assess all its elements. To present an understandable results of the assessment, it is required to present a unique term representing the performance of the overall system. This paper aims to develop an overall performance indicator which may be used to assess the road safety system. The variables of this indicators are the main elements of the road safety system. The data regarding these variables will be collected from the World Health Organization report. Multi-criteria analysis method is used to aggregate the four sub-indicators for the four variables. Two weighting methods will be assumed, equal weights and different weights. For the different weights method, the factor analysis method is used. The weights then will be converting to scores. The total score will be the overall indicator for the road safety performance in a national scale. This indicator will be used to compare and rank countries according to their road safety performance indicator. The country with the higher score is the country which provides most sustainable and effective interventions for successful road safety system. These indicator will be tested by comparing them with the aggregate real crash rate for each country.

Keywords: factor analysis, Multi-criteria analysis, road safety assessment, safe system indicator

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Authors: Bonsoo Koo, Seong Shin Hong, Byung Kwon Lee

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Most of apartments in Korea have wall type structure that present poor performance regarding floor impact sound insulation. In order to minimize the transmission of floor impact sound, flooring structures are used in which an insulating material, 30 mm thickness pad of EPS or EVA, is sandwiched between a concrete slab and the finished mortar. Generally, a single-material pad used for insulation has a heavyweight impact sound level of 44~47 dB with 210 mm thickness slab. This study provides an analysis of the floor impact sound insulation performance using thermoplastic poly urethane (TPU), ethylene vinyl acetate (EVA), and expanded polystyrene (EPS) materials with buffering performance. Following mock-up tests the effect of lightweight impact sound turned out to be similar but heavyweight impact sound was decreased by 3 dB compared to conventional single material insulation pad.

Keywords: floor impact sound, thermoplastic poly urethane, ethylene vinyl acetate, heavyweight impact sound

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Ian Marc Gealon Cabugsa, Eleanor Pastrano Corcino, Gina Lapaza Montalan

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This study focused on the effect of Online Web-Learning (OWL) in the performance of the freshmen Civil Engineering Students of Ateneo de Davao University in their Chem 12 subject. The grades of the students that were required to use OWL were compared to students without OWL. The result of the study suggests promising result for the use of OWL in increasing the performance rate of students taking up Chem 12. Furthermore, there was a positive correlation between the final grade and OWL grade of the students that had OWL. While the majority of the students find OWL to be helpful in supporting their chemistry knowledge needs, most of them still prefer to learn using the traditional face-to-face instruction.

Keywords: chemistry education, enhanced performance, engineering chemistry, online web-based learning

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: Michal Gregor, Jiri Polcar, Petr Horejsi, Michal Simon

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Machine visualization is an area of interest with fast and progressive development. We present a method of machine visualization which will be applicable in real industrial conditions according to current needs and demands. Real factory data were obtained in a newly built research plant. Methods described in this paper were validated on a case study. Input data were processed and the virtual environment was created. The environment contains information about dimensions, structure, disposition, and function. Hardware was enhanced by modular machines, prototypes, and accessories. We added new functionalities and machines into the virtual environment. The user is able to interact with objects such as testing and cutting machines, he/she can operate and move them. Proposed design consists of an environment with two degrees of freedom of movement. Users are in touch with items in the virtual world which are embedded into the real surroundings. This paper describes the development of the virtual environment. We compared and tested various options of factory layout virtualization and visualization. We analyzed possibilities of using a 3D scanner in the layout obtaining process and we also analyzed various virtual reality hardware visualization methods such as Stereoscopic (CAVE) projection, Head Mounted Display (HMD), and augmented reality (AR) projection provided by see-through glasses.

Keywords: augmented reality, spatial scanner, virtual environment, virtual reality

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Authors: J. BalaRaju, M. Govinda Raj, C. S. N. Murthy

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Every organization in the competitive world tends to improve its economy by increasing their production and productivity rates. Unequivocally, the production in Indian underground mines over the years is not satisfactory, due to a variety of reasons. There are manifold of avenues for the betterment of production, and one such approach is through enhanced utilization of mechanized equipment such as Load Haul Dumper (LHD). This is used as loading and hauling purpose in underground mines. In view of the aforementioned facts, this paper delves into identification of the key influencing factors such as LHDs maintenance effectiveness, vehicle condition, operator skill and utilization of the machines on performance of LHDs. An attempt has been made for improvement of performance of the equipment through evaluation of Overall Equipment Effectiveness (OEE). Two different approaches for evaluation of OEE have been adopted and compared under various operating conditions. The use of OEE calculation in terms of percentage availability, performance and quality and the hitherto existing situation of the underground mine production is evaluated. Necessary recommendations are suggested to mining industry on the basis of OEE.

Keywords: utilization, maintenance, availability, performance and quality

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Authors: Amandeep Singh Dhaliwal

Abstract:

Networking solutions, particularly wireless local area networks have revolutionized the technological advancement. Wireless Local Area Networks (WLANs) have gained a lot of popularity as they provide location-independent network access between computing devices. There are a number of access methods used in Wireless Networks among which DCF and PCF are the fundamental access methods. This paper emphasizes on the impact of DCF and PCF access mechanisms on the performance of the IEEE 802.11a, 802.11b and 802.11g standards. On the basis of various parameters viz. throughput, delay, load etc performance is evaluated between these three standards using above mentioned access mechanisms. Analysis revealed a superior throughput performance with low delays for 802.11g standard as compared to 802.11 a/b standard using both DCF and PCF access methods.

Keywords: DCF, IEEE, PCF, WLAN

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