Search results for: process performance

Authors: Yas Barzegaar, Atrin Barzegar

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The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

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Authors: Wen Po Cheng, Chia Yun Chung, Ruey Fang Yu, Chao Feng Chen

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The main objective of this research was to study the differences of aluminum hydrolytic products between two PACl preparation methods. These two methods were the acidification process of freshly formed amorphous Al(OH)₃ and the conventional alkalization process of aluminum chloride solution. According to Ferron test and ²⁷Al NMR analysis of those two PACl preparation procedures, the reaction rate constant (k) values and Al₁₃ percentage of acid addition process at high basicity value were both lower than those values of the alkaline addition process. The results showed that the molecular structure and size distribution of the aluminum species in both preparing methods were suspected to be significantly different at high basicity value.

Keywords: polyaluminum chloride, Al13, amorphous aluminum hydroxide, Ferron test

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Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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The use of Micro Gas Turbine (MGT) as the engine in Unmanned Aerobic Vehicles (UAVs) and power source in Robotics is widespread these days. Research has been conducted in the past decade or so to improve the performance of different components of MGT. This type of engine has interrelated components which have non-linear characteristics. Therefore, the overall engine performance depends on the individual engine element’s performance. Computational Fluid Dynamics (CFD) is one of the simulation method tools used to analyze or even optimize MGT system performance. In this study, the compressor of the MGT is designed, and performance optimization is being done using CFD. Performance of the micro compressor is improved in order to increase the overall performance of MGT. A high value of pressure ratio is to be achieved by studying the effect of change of different operating parameters like mass flow rate and revolutions per minute (RPM) and aerodynamical and geometrical parameters on the pressure ratio of the compressor. Two types of compressor designs are considered in this study; 3D centrifugal and ‘planar’ designs. For a 10 mm impeller, the planar model is the simplest compressor model with the ease in manufacturability. On the other hand, 3D centrifugal model, although more efficient, is very difficult to manufacture using current microfabrication resources. Therefore, the planar model is the best-suited model for a micro compressor. So. a planar micro compressor has been designed that has a good pressure ratio, and it is easy to manufacture using current microfabrication technologies. Future work is to fabricate the compressor to get experimental results and validate the theoretical model.

Keywords: computational fluid dynamics, microfabrication, MEMS, unmanned aerobic vehicles

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Authors: Obasan Kehinde

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Social Infrastructure such as transport, telecommunications, energy, water, health, housing, and educational facilities have become part and parcel of human existence and have since been seen as prerequisite for the development of any economy. It is difficult to imagine a modern world without these facilities. Using a survey research design, data was gathered through a multi-stage sampling and a random sampling method from a total of 117 respondents, the study investigates the role of social infrastructure on the performance of entrepreneurs drawn from 10 Local Government Areas across two carefully selected states in the South-West, Nigeria. The data was analyzed using a descriptive statistical analysis and a t-test. The result shows that the impact of social infrastructure on entrepreneur performance is significant at 0.00 level of significant. Thus, this study recommends that entrepreneurs should take note of the social infrastructures available in the environment for the purpose of citing business in order to reduce the cost of production and other business costs.

Keywords: social infrastructure, entrepreneur performance, entrepreneurship, business

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Authors: L. Shafiq, A. Rigby

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All polyethylene processes are highly exothermic, and the safe removal of the heat of reaction is a fundamental issue in the process design. In slurry and gas processes, the velocity of the polymer particles in the reactor and external coolers can be very high, and under certain conditions, this can lead to static charging of these particles. Such static charged polymer particles may start building up on the reactor wall, limiting heat transfer, and ultimately leading to severe reactor fouling and forced reactor shut down. Statsafe™ is an FDA approved anti-fouling additive currently used around the world for polyolefin production as an anti-fouling additive. The unique polymer chemistry aids static discharge, which prevents the build-up of charged polyolefin particles, which could lead to fouling. Statsafe™ is being used and trailed in gas, slurry, and a combination of these technologies around the world. We will share data to demonstrate how the use of Statsafe™ allows more stable operation at higher solids level by eliminating static, which would otherwise prevent closer packing of particles in the hydrocarbon slurry. Because static charge generation depends also on the concentration of polymer particles in the slurry, the maximum slurry concentration can be higher when using Statsafe™, leading to higher production rates. The elimination of fouling also leads to less downtime. Special focus will be made on the impact anti-static additives have on catalyst performance within the polymerization process and how this has been measured. Lab-scale studies have investigated the effect on the activity of Ziegler Natta catalysts when anti-static additives are used at various concentrations in gas and slurry, polyethylene and polypropylene processes. An in-depth gas phase study investigated the effect of additives on the final polyethylene properties such as particle size, morphology, fines, bulk density, melt flow index, gradient density, and melting point.

Keywords: anti-static additives, catalyst performance, FDA approved anti-fouling additive, polymerisation

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Authors: Adriano Pinargote, Josue Mosquera, Eduardo Montero, Dalton Noboa, Jenny Venegas, Genesis Vasquez Escuela

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In the framework of Pre University learning of the Polytechnic School of the Litoral, Guayaquil, Ecuador, the methodology of Active Learning (Flipped Classroom) has been implemented for applicants who wish to obtain a quota within the university. To complement the Active Learning cycle, it has been proposed that the respective students influence the qualification of their work groups, for which a web platform has been created that allows them to evaluate the performance of their peers through a digital coevaluation that measures through statistical methods, the group and individual performance score that can reflect in numbers a weighting score corresponding to the grade of each student. Their feedback provided by the group help to improve the performance of the activities carried out in classes because the note reflects the commitment with their classmates shown in the class, within this analysis we will determine if this implementation directly influences the performance of the grades obtained by the student.

Keywords: active learning, coevaluation, flipped classroom, pre university

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Authors: Muhammad Tufail, Jawad Hussain, Hammad Hussain, Imran Hafeez, Naveed Ahmad

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Road safety performance index is a composite index which combines various indicators of road safety into single number. Development of a road safety performance index using appropriate safety performance indicators is essential to enhance road safety. However, a road safety performance index in developing countries has not been given as much priority as needed. The primary objective of this research is to develop a general Road Safety Performance Index (RSPI) for developing countries based on the facility as well as behavior of road user. The secondary objectives include finding the critical inputs in the RSPI and finding the better method of making the index. In this study, the RSPI is developed by selecting four main safety performance indicators i.e., protective system (seat belt, helmet etc.), road (road width, signalized intersections, number of lanes, speed limit), number of pedestrians, and number of vehicles. Data on these four safety performance indicators were collected using observation survey on a 20 km road section of the National Highway N-125 road Taxila, Pakistan. For the development of this composite index, two methods are used: a) Principal Component Analysis (PCA) and b) Equal Weighting (EW) method. PCA is used for extraction, weighting, and linear aggregation of indicators to obtain a single value. An individual index score was calculated for each road section by multiplication of weights and standardized values of each safety performance indicator. However, Simple Average technique was used for weighting and linear aggregation of indicators to develop a RSPI. The road sections are ranked according to RSPI scores using both methods. The two weighting methods are compared, and the PCA method is found to be much more reliable than the Simple Average Technique.

Keywords: indicators, aggregation, principle component analysis, weighting, index score

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Authors: E. Kaygan, A. Gatto

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An investigation of adaptable winglets for morphing aircraft control and performance is described in this paper. The concepts investigated consist of various winglet configurations fundamentally centred on a baseline swept wing. The impetus for the work was to identify and optimize winglets to enhance controllability and the aerodynamic efficiency of a small unmanned aerial vehicle. All computations were performed with Athena Vortex Lattice modelling with varying degrees of twist, swept, and dihedral angle considered. The results from this work indicate that if adaptable winglets were employed on small scale UAV’s improvements in both aircraft control and performance could be achieved.

Keywords: aircraft, rolling, wing, winglet

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Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

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With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation, pressure drop

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Authors: Aldé Belgard Tchicaya Loemba, Baraka Kichonge, Thomas Kivevele, Juma Rajabu Selemani

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Plants used for medicinal purposes are extremely perishable, owing to moisture-enhanced enzymatic and microorganism activity, climate change, and improper handling and storage. Experiments have shown that drying the medicinal plant without affecting the active nutrients and controlling the moisture content as much as possible can extend its shelf life. Different traditional and modern drying techniques for preserving medicinal plants have been developed, with some still being improved in Sub-Saharan Africa. However, many of these methods fail to address the most common issues encountered when drying medicinal plants, such as nutrient loss, long drying times, and a limited capacity to dry during the evening or cloudy hours. Heat pump drying is an alternate drying method that results in no nutritional loss. Furthermore, combining a heat pump dryer with a solar energy storage system appears to be a viable option for all-weather drying without affecting the nutritional values of dried products. In this study, a solar-assisted heat pump dryer integrated with thermal energy storage is developed for drying moringa leaves. The study also discusses the performance analysis of the developed dryer as well as the proximate analysis of the dried moringa leaves. All experiments were conducted from 11 a.m. to 4 p.m. to assess the dryer's performance in “daytime mode”. Experiment results show that the drying time was significantly reduced, and the dryer demonstrated high performance in preserving all of the nutrients. In 5 hours of the drying process, the moisture content was reduced from 75.7 to 3.3%. The average COP value was 3.36, confirming the dryer's low energy consumption. The findings also revealed that after drying, the content of protein, carbohydrates, fats, fiber, and ash greatly increased.

Keywords: heat pump dryer, efficiency, moringa leaves, proximate analysis

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Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

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Authors: Marianna Maiaru, Gregory M. Odegard

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During the processing of high-performance thermoset polymer matrix composites, chemical reactions occur during elevated pressure and temperature cycles, causing the constituent monomers to crosslink and form a molecular network that gradually can sustain stress. As the crosslinking process progresses, the material naturally experiences a gradual shrinkage due to the increase in covalent bonds in the network. Once the cured composite completes the cure cycle and is brought to room temperature, the thermal expansion mismatch of the fibers and matrix cause additional residual stresses to form. These compounded residual stresses can compromise the reliability of the composite material and affect the composite strength. Composite process modeling is greatly complicated by the multiscale nature of the composite architecture. At the molecular level, the degree of cure controls the local shrinkage and thermal-mechanical properties of the thermoset. At the microscopic level, the local fiber architecture and packing affect the magnitudes and locations of residual stress concentrations. At the macroscopic level, the layup sequence controls the nature of crack initiation and propagation due to residual stresses. The goal of this research is use molecular dynamics (MD) and finite element analysis (FEA) to predict the residual stresses in composite laminates and the corresponding effect on composite failure. MD is used to predict the polymer shrinkage and thermomechanical properties as a function of degree of cure. This information is used as input into FEA to predict the residual stresses on the microscopic level resulting from the complete cure process. Virtual testing is subsequently conducted to predict strength allowables. Experimental characterization is used to validate the modeling.

Keywords: molecular dynamics, finite element analysis, processing modeling, multiscale modeling

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Authors: Jihad Daba, Jean-Pierre Dubois

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Multi path fading noise degrades the performance of cellular communication, most notably in femto- and pico-cells in 3G and 4G systems. When the wireless channel consists of a small number of scattering paths, the statistics of fading noise is not analytically tractable and poses a serious challenge to developing closed canonical forms that can be analysed and used in the design of efficient and optimal receivers. In this context, noise is multiplicative and is referred to as stochastically local fading. In many analytical investigation of multiplicative noise, the exponential or Gamma statistics are invoked. More recent advances by the author of this paper have utilized a Poisson modulated and weighted generalized Laguerre polynomials with controlling parameters and uncorrelated noise assumptions. In this paper, we investigate the statistics of multi-diversity stochastically local area fading channel when the channel consists of randomly distributed Rayleigh and Rician scattering centers with a coherent specular Nakagami-distributed line of sight component and an underlying doubly stochastic Poisson process driven by a lognormal intensity. These combined statistics form a unifying triply stochastic filtered marked Poisson point process model.

Keywords: cellular communication, femto and pico-cells, stochastically local area fading channel, triply stochastic filtered marked Poisson point process

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Authors: Umer Mukhtar

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Supply Chain Competitiveness is the capability of a supply chain to deliver value to the customer for the sake of competitive advantage. Service Performance and Quality intervene between supply chain actors including functions inside the firm in a significant way for the supply chain to achieve a competitive position in the market to gain competitive advantage. Supply Chain competitiveness is the current issue of interest because of supply chains’ competition for competitive advantage rather than firms’. A proposed theoretical model is developed by extracting and integrating different theories to pursue further inquiry based on case studies and survey design. It is also intended to develop a scale of service performance for functions of the focal firm that is a revolving center for a whole supply chain.

Keywords: supply chain competitiveness, service performance in supply chain, service quality in supply chain, competitive advantage by supply chain, networks and supply chain, customer value, value supply chain, value chain

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Authors: Sara Mostofian

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The nuclear industry is a technology that can fulfill future energy needs but requires special attention to ensure safety and reliability while minimizing any environmental impact. To meet these expectations, the nuclear industry is exploring different reactor technologies for power production. Several designs are under development and the technical viability of these new designs is the subject of many ongoing studies. One of these studies considers the radioactive emissions and radioactive waste generated during the life of a nuclear power production plant to allow a successful license process. For all the modern technologies, a good understanding of the radioactivity generated in the process systems of the plant is essential. Some of that understanding may be gleaned from the performance of some prototype reactors of similar design that operated decades ago. This paper presents how, with that understanding, a model can be developed to estimate the emissions as well as the radioactive waste during the normal operation of a nuclear power plant. The model would predict the radioactive material concentrations in different waste streams. Using this information, the radioactive emission and waste generated during the life of these new technologies can be estimated during the early stages of the design of the plant.

Keywords: SMRs, activity transport, model, radioactive waste

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Authors: Maciej Czarnecki

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Even though growth is one of the most important strategic objectives for many enterprises, we know relatively little about this phenomenon. This research contributes to broaden our knowledge of managerial consequences of growth. Scales for measuring organizational development and growing pains were developed. Conceptual model of connections among growth, organizational development, growing pains, selected development factors and financial performance were examined. The research process contained literature review, 20 interviews with managers, examination of 12 raters’ opinions, pilot research and 7 point Likert scale questionnaire research on 138 Polish enterprises employing 50-249 people which increased their employment at least by 50% within last three years. Factor analysis, Pearson product-moment correlation coefficient, student’s t-test and chi-squared test were used to develop scales. High Cronbach’s alpha coefficients were obtained. The verification of correlations among the constructs was carried out with factor correlations, multiple regressions and path analysis. When the enterprise grows, it is necessary to implement changes in its structure, management practices etc. (organizational development) to meet challenges of growing complexity. In this paper, organizational development was defined as internal changes aiming to improve the quality of existing or to introduce new elements in the areas of processes, organizational structure and culture, operational and management systems. Thus; H1: Growth has positive effects on organizational development. The main thesis of the research is that if organizational development does not catch up　with growing complexity of growing enterprise, growing pains will arise (lower work comfort, conflicts, lack of control etc.). They will exert a negative influence on the financial performance and may result in serious organizational crisis or even bankruptcy. Thus; H2: Growth has positive effects on growing pains, H3: Organizational development has negative effects on growing pains, H4: Growing pains have negative effects on financial performance, H5: Organizational development has positive effects on financial performance. Scholars considered long lists of factors having potential influence on organizational development. The development of comprehensive model taking into account all possible variables may be beyond the capacity of any researcher or even statistical software used. After literature review, it was decided to increase the level of abstraction and to include following constructs in the conceptual model: organizational learning (OL), positive organization (PO) and high performance factors (HPF). H1a/b/c: OL/PO/HPF has positive effect on organizational development, H2a/b/c: OL/PO/HPF has negative effect on growing pains. The results of hypothesis testing: H1: partly supported, H1a/b/c: supported/not supported/supported, H2: not supported, H2a/b/c: not supported/partly supported/not supported, H3: supported, H4: partly supported, H5: supported. The research seems to be of a great value for both scholars and practitioners. It proved that OL and HPO matter for organizational development. Scales for measuring organizational development and growing pains were developed. Its main finding, though, is that organizational development is a good way of improving financial performance.

Keywords: organizational development, growth, growing pains, financial performance

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Authors: Kukuri Tavartkiladze, Nana Bolashvili

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The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed.  The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.

Keywords: aridity, climate change, desertification, precipitation

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Authors: Mona Baniahmadi, Saied Haghanifar

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Radio Frequency Identification (RFID) is regarded as a promising technology for the optimization of supply chain processes since it improves manufacturing and retail operations from forecasting demand for planning, managing inventory, and distribution. This study precisely aims at learning to know the RFID technology and at explaining how it can concretely be used for supply chain management and how it can help improving it in the case of Hejrat Company which is located in Iran and works on the distribution of medical drugs and cosmetics. This study uses some statistical analysis to calculate the expected benefits of an integrated RFID system on supply chain obtained through competitive advantages increases with decreasing cost factor. The study investigates how the cost of storage process, labor cost, the cost of missing goods, inventory management optimization, on-time delivery, order cost, lost sales and supply process optimization affect the performance of the integrated RFID supply chain regarding cost factors and provides a competitive advantage.

Keywords: cost, competitive advantage, radio frequency identification, supply chain

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Authors: Zahid Ali Ghazi

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Supercapacitors (SCs) have emerged as auspicious energy storage devices because of their fast charge-discharge characteristics and high power densities. In the current study, a simple approach is used to coat activated carbon (AC) with a thin layer of nickel (Ni) by an electroless deposition process to enhance the electrochemical performance of the SC. The synergistic combination of large surface area and high electrical conductivity of the AC, as well as the pseudocapacitive behavior of the metallic Ni, has shown great potential to overcome the limitations of traditional SC materials. First, the materials were characterized using X-ray diffraction (XRD) for crystallography, scanning electron microscopy (SEM) for surface morphology and energy dispersion X-ray (EDX) for elemental analysis. The electrochemical performance of the nickel-coated activated carbon (Ni-AC) is systematically evaluated through various techniques, including galvanostatic charge-discharge (GCD), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). The GCD results revealed that Ni/AC has a higher specific capacitance (1559 F/g) than bare AC (222 F/g) at 1 A/g current density in a 2 M KOH electrolyte. Even at a higher current density of 20 A/g, the Ni/AC showed a high capacitance of 944 F/g as compared to 77 F/g by AC. The specific capacitance (1318 F/g) calculated from CV measurements for Ni-AC at 10mV/sec was in close agreement with GCD data. Furthermore, the bare AC exhibited a low energy of 15 Wh/kg at a power density of 356 W/kg whereas, an energy density of 111 Wh/kg at a power density of 360 W/kg was achieved by Ni/AC-850 electrode and demonstrated a long life cycle with 94% capacitance retention over 50000 charge/discharge cycles at 10 A/g. In addition, the EIS study disclosed that the Rs and Rct values of Ni/AC electrodes were much lower than those of bare AC. The superior performance of Ni/AC is mainly attributed to the presence of excessive redox active sites, large electroactive surface area and corrosive resistance properties of Ni. We believe that this study will provide new insights into the controlled coating of ACs and other porous materials with metals for developing high-performance SCs and other energy storage devices.

Keywords: supercapacitor, cyclic voltammetry, coating, energy density, activated carbon

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Authors: S. B. Rathna Kumar, Pranjali A Ujwane, Panchanan Mohanty

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The present study aimed to develop a battery for assessing speech recognition performance by adults in Marathi. A total of four word lists were developed by considering word frequency, word familiarity, words in common use, and phonemic balance. Each word list consists of 25 words (15 monosyllabic words in CVC structure and 10 monosyllabic words in CVCV structure). Equivalence analysis and performance-intensity function testing was carried using the four word lists on a total of 150 native speakers of Marathi belonging to different regions of Maharashtra (Vidarbha, Marathwada, Khandesh and Northern Maharashtra, Pune, and Konkan). The subjects were further equally divided into five groups based on above mentioned regions. It was found that there was no significant difference (p > 0.05) in the speech recognition performance between groups for each word list and between word lists for each group. Hence, the four word lists developed were equally difficult for all the groups and can be used interchangeably. The performance-intensity (PI) function curve showed semi-linear function, and the groups’ mean slope of the linear portions of the curve indicated an average linear slope of 4.64%, 4.73%, 4.68%, and 4.85% increase in word recognition score per dB for list 1, list 2, list 3 and list 4 respectively. Although, there is no data available on speech recognition tests for adults in Marathi, most of the findings of the study are in line with the findings of research reports on other languages. The four word lists, thus developed, were found to have sufficient reliability and validity in assessing speech recognition performance by adults in Marathi.

Keywords: speech recognition performance, phonemic balance, equivalence analysis, performance-intensity function testing, reliability, validity

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Authors: Rosemary Saidu, Taiyelolu Martins Ogunjirin

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The study examines the teaching environment and instructional materials on the performance of students in the English Language in selected secondary schools in Ogun State and its implication for counselling. Two research questions guided the study were developed. The study adopted a descriptive survey design. A multi-stage sampling technique was employed for the study. Samples of 100 students of Senior Secondary School Two (SSS11) were drawn. Purposive sampling technique was to select the five schools. Additionally, the instruments known as Teaching Environment and Instructional Materials on Students Performance in English Inventory (TEIMEI) and Student Achievement Scores (SAS) were used to elicit information. Thereafter, inferential statistics and the non-parametric chi-square statistics at 0.05 alpha levels and 3 degree of freedom were adopted as analytical tools. From the study, it was discovered among others that teaching environment and instructional materials significantly contributed to the performance of students in the English language. From the findings, it was recommended that among others functional language laboratory in the schools, counselors to regularly give guidance talk on the importance of the subject.

Keywords: performance, English language, teaching environment, instructional materials

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Imtiaz Ahmed Khan, Sabu John, Sania Waqar, Lijing Wang, Mac Fergusson, Ilija Najdovski

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Evolution of textiles, from its orthodox to more interactive role has stirred the researchers to uncover its application in numerous arenas. The idea of using textile based materials for wearable energy harvesting and storage devices have gained immense popularity. This is mainly due to textile comfort and flexibility features. In this work, nano-carbonous materials were infused on cellulosic fibers using caustic soda treatment. This paper presents the complete procedure of yarn supercapacitors fabrication process through dip coating technique and its characterization method. The main objective is to study, the effect of varying caustic soda concentration on mass loading of activated carbon on yarns and the related capacitance output of the designed yarn supercapacitor. Polyvinyl alcohol and Phosphoric acid were used as electrolyte in a two-electrode cell assembly to measure device electrochemical performance. The results show a promising increase in capacitance value using this technique.

Keywords: yarn supercapacitors, activated carbon, dip coating, caustic soda, electrolyte, electrochemical characterization

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Authors: Manoj Kumar

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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper, we compare AODV, DSDV, DSR, and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyze these routing protocols by extensive simulations in OPNET simulator and show how to pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, sent data traffic, throughput, retransmission attempts.

Keywords: AODV, DSDV, DSR, ZRP

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Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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Authors: Niran Watchrodom

Abstract:

An experimental study was carried out to investigate the energy performance of a 1.5 Tr commercial split type air conditioner operating at different indoor set points and different air flowrate circulating through the cooling coil. The refrigerant R-22 was used as working fluid. In this paper, the test conditions considered were varied as follows: The room temperature varied from 23, 24, 25, 26, and 27 C, the air velocity passing through the evaporator was varied from 1.9, 2.1 and 2.4 m/s. The air velocity passing through the condenser was kept constant at 5 m/s. The results showed that when the indoor temperature was high, 27 C, and air velocity was 1.9 m/s, the coefficient of performance (COP) of the system was 3.74. The electrical power consumption of compressor was 1.64 kW, the rate of heat transfer in the condenser and evaporator were 7.79 and 6.10 kW, respectively. The amount corresponding amount of condensed water coming out of evaporator was 8.20 liter. The system can applied to commercial building.

Keywords: condensed water, coefficient of performance, air velocity

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Authors: A. Nuchitprasittichai, N. Lerdritsirikoon, T. Khamsing

Abstract:

Simulation modeling can be used to solve real world problems. It provides an understanding of a complex system. To develop a simplified model of process simulation, a suitable experimental design is required to be able to capture surface characteristics. This paper presents the experimental design and algorithm used to model the process simulation for optimization problem. The CO₂ liquefaction based on external refrigeration with two refrigeration circuits was used as a simulation case study. Latin Hypercube Sampling (LHS) was purposed to combine with existing Central Composite Design (CCD) samples to improve the performance of CCD in generating the second order model of the system. The second order model was then used as the objective function of the optimization problem. The results showed that adding LHS samples to CCD samples can help capture surface curvature characteristics. Suitable number of LHS sample points should be considered in order to get an accurate nonlinear model with minimum number of simulation experiments.

Keywords: central composite design, CO2 liquefaction, latin hypercube sampling, simulation-based optimization

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Authors: Margerita Topalli

Abstract:

In this paper, we analyze the impact of corruption (business environment, informal payments and state capture), crime and tax time, on the enterprise's performance during economic transition in the Central and Eastern Europe and the role of privatization as a moderator. We examine this effect by comparing the performance of the privatized enterprises and the state-owned-enterprises, while controlling for various forms of selection bias. The present study is based on firm-level panel data collected by the BEEPS for 27 transition countries over 2002, 2005, 2007, and 2011. In addition to firm characteristics, BEEPS collects valuable survey information on different forms of corruption, crime, tax time and firm ownership. We estimate the impact of corruption, crime, tax time on the different performance measures (sales, productivity, employment, labor costs and material costs) of the enterprise, whereby we control for firm ownership, with a special focus on the role of the privatization as a moderator. It argues that in general terms, the privatization has positive effects on the performance of enterprises during transition, but these effects are significantly different, depending on the examined performance measure (sales, productivity, employment, labor costs and material costs). When the privatization is effective, the privatized enterprises show a considerable performance improvements, particularly in terms of revenue growth and productivity growth. It also argues that the effects of privatization are different depending on the types of owner (outsider or insider) to whom it gives control. The results show that privatization to insider owners has no significant performance effect.

Keywords: effects of privatization, enterprise performance, state capture, corruption, firm ownership, economic transition, Central and Eastern Europe

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Authors: Amin Mojiri, Hamidi Abdul Aziz

Abstract:

Leachate is created while water penetrates through the waste in a landfill, carrying some forms of pollutants. In literature, for treatment of wastewater and leachate, different ways of biological treatment were used. Sequencing batch reactor (SBR) is a kind of biological treatment. This study investigated the co-treatment of landfill leachate and domestic waste water by SBR and powdered activated carbon augmented (PAC) SBR process. The response surface methodology (RSM) and central composite design (CCD) were employed. The independent variables were aeration rate (L/min), contact time (h), and the ratio of leachate to wastewater mixture (%; v/v)). To perform an adequate analysis of the aerobic process, three dependent parameters, i.e. COD, color, and ammonia-nitrogen (NH3-N or NH4-N) were measured as responses. The findings of the study indicated that the PAC-SBR showed a higher performance in elimination of certain pollutants, in comparison with SBR. With the optimal conditions of aeration rate (0.6 L/min), leachate to waste water ratio (20%), and contact time (10.8 h) for the PAC-SBR, the removal efficiencies for color, NH3-N, and COD were 72.8%, 98.5%, and 65.2%, respectively.

Keywords: co-treatment, landfill Leachate, wastewater, sequencing batch reactor, activate carbon

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Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

Abstract:

Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

Procedia PDF Downloads 377