Search results for: input–output analysis

Authors: Ubon Asuquo Essien, Okwudili Bismark Ibeagwa, Daberechi Peace Ubabuko

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The Broiler Poultry subsector is dominated by small scale production with low aggregate output. The high cost of inputs currently experienced in Nigeria tends to aggravate the situation; hence many broiler farmers struggle to break-even. This study was designed to examine income and input factors in small scale deep liter broiler production in Imo state, Nigeria. Specifically, the study examined; socio-economic characteristics of small scale deep liter broiler producing Poultry farmers; estimate cost and returns of broiler production in the area; analyze input factors in broiler production in the area and examined marketability, age and profitability of the enterprise. A multi-stage sampling technique was adopted in selecting 60 small scale broiler farmers who use deep liter system from 6 communities through the use of structured questionnaire. The socioeconomic characteristics of the broiler farmers and the profitability/ marketability age of the birds were described using descriptive statistical tools such as frequencies, means and percentages. Gross margin analysis was used to analyze the cost and returns to broiler production, while Cobb Douglas production function was employed to analyze input factors in broiler production. The result of the study revealed that the cost of feed (P<0.1), deep liter material (P<0.05) and medication (P<0.05) had a significant positive relationship with the gross return of broiler farmers in the study area, while cost of labour, fuel and day old chicks were not significant. Furthermore, Gross profit margin of the farmers who market their broiler at the 8th week of rearing was 80.7%; and 78.7% and 60.8% for farmers who market at the 10th week and 12th week of rearing, respectively. The business is, therefore, profitable but at varying degree. Government and Development partners should make deliberate efforts to curb the current rise in the prices of poultry feeds, drugs and timber materials used as bedding so as to widen the profit margin and encourage more farmers to go into the business. The farmers equally need more technical assistance from extension agents with regards to timely and profitable marketing.

Keywords: broilers, factor analysis, income, small scale

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Authors: Mubarack Ahmed, Gabriele Gradoni, Stephen C. Creagh, Gregor Tanner

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High-frequency cables commonly connect modern devices and sensors. Interestingly, the proportion of electric components is rising fast in an attempt to achieve lighter and greener devices. Modelling the propagation of signals through these cable networks in the presence of parameter uncertainty is a daunting task. In this work, we study the response of high-frequency cable networks using both Transmission Line and Quantum Graph (QG) theories. We have successfully compared the two theories in terms of reflection spectra using measurements on real, lossy cables. We have derived a generalisation of the vertex scattering matrix to include non-uniform networks – networks of cables with different characteristic impedances and propagation constants. The QG model implicitly takes into account the pseudo-chaotic behavior, at the vertices, of the propagating electric signal. We have successfully compared the asymptotic growth of eigenvalues of the Laplacian with the predictions of Weyl law. We investigate the nearest-neighbour level-spacing distribution of the resonances and compare our results with the predictions of Random Matrix Theory (RMT). To achieve this, we will compare our graphs with the generalisation of Wigner distribution for open systems. The problem of scattering from networks of cables can also provide an analogue model for wireless communication in highly reverberant environments. In this context, we provide a preliminary analysis of the statistics of communication capacity for communication across cable networks, whose eventual aim is to enable detailed laboratory testing of information transfer rates using software defined radio. We specialise this analysis in particular for the case of MIMO (Multiple-Input Multiple-Output) protocols. We have successfully validated our QG model with both TL model and laboratory measurements. The growth of Eigenvalues compares well with Weyl’s law and the level-spacing distribution agrees so well RMT predictions. The results we achieved in the MIMO application compares favourably with the prediction of a parallel on-going research (sponsored by NEMF21.)

Keywords: eigenvalues, multiple-input multiple-output, quantum graph, random matrix theory, transmission line

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory

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Authors: Young-San Shin, Seongsoo Lee

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Hall sensor is widely used to measure rotation angle. When the Hall voltage is measured for linear displacement, it is converted to angular displacement using arctangent function, which requires a large lookup table. In this paper, a lookup table reduction technique is presented for angle measurement. When the input of the lookup table is small within a certain threshold, the change of the outputs with respect to the change of the inputs is relatively small. Thus, several inputs can share same output, which significantly reduce the lookup table size. Its error analysis was also performed, and the threshold was determined so as to maintain the error less than 1°. When the Hall voltage has 11-bit resolution, the lookup table size is reduced from 1,024 samples to 279 samples.

Keywords: hall sensor, angle measurement, lookup table, arctangent

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Authors: Tomotaka Aoki, Isao Tomita

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We examined the on-off ratio and frequency components of output signals from an electron-interference device made of GaAs/AlₓGa₁₋ₓAs by solving the time-dependent Schrödinger's equation on conducting electrons in the channel waveguide of the device. For electron-wave modulation, a periodic voltage of frequency f was applied to the channel. Furthermore, we examined the voltage-amplitude dependence of the signals in time and frequency domains and found that large applied voltage deformed the output-signal waveform and created additional side modes (frequencies) near the modulation frequency f and that there was a trade-off between on-off ratio and side-mode creation.

Keywords: electrical conduction, electron interference, frequency spectrum, on-off ratio

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Jamil Ahmed

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Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.

Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm

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Authors: Ge Zheng, Jun Peng

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Unbalanced power output from individual cells of Proton Exchange Membrane Fuel Cell (PEMFC) has direct effects on PEMFC stack performance, in particular under transient operation. In the paper, a multi-layer ANN (Artificial Neural Network) model Radial Basis Functions (RBF) has been developed for predicting cells' output profiles by applying gas supply parameters, cooling conditions, temperature measurement of individual cells, etc. The feed-forward ANN model was validated with experimental data. Influence of relevant parameters of RBF on the network accuracy was investigated. After adequate model training, the modelling results show good correspondence between actual measurements and reconstructed output profiles. Finally, after the model was used to optimize the stack output performance under steady-state and transient operating conditions, it suggested that the developed ANN control model can help PEMFC stack to have obvious improvement on power output under fast acceleration process.

Keywords: proton exchange membrane fuel cell, PEMFC, artificial neural network, ANN, cell output profile, transient

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Authors: Naser Alajmi, Ali Alobaidly, Mubarak Alhajri, Salem Salamah, Muhammad Alsubaie

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Iterative Learning Control (ILC) known to be a controlling tool to overcome periodic disturbances for repetitive systems. This technique is required to let the error signal tends to zero as the number of operation increases. The learning process that lies within this context is strongly dependent on the initial input which if selected properly tends to let the learning process be more effective compared to the case where a system starts from blind. ILC uses previous recorded execution data to update the following execution/trial input such that a reference trajectory is followed to a high accuracy. Error convergence in ILC is generally highly dependent on the input applied to a plant for trial $1$, thus a good choice of initial starting input signal would make learning faster and as a consequence the error tends to zero faster as well. In the work presented within, an upper limit based on the Singular Values Principle (SV) is derived for the initial input signal applied at trial $1$ such that the system follow the reference in less number of trials without responding aggressively or exceeding the working envelope where a system is required to move within in a robot arm, for example. Simulation results presented illustrate the theory introduced within this paper.

Keywords: initial input, iterative learning control, maximum input, singular values

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Authors: Vaishali D. Khairnar

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The main aim is to provide lower-latency and highly reliable communication facilities for vehicles in the automobile industry; vehicle-to-everything (V2X) communication basically intends to increase expressway road security and its effectiveness. The Ultra-Reliable Low-Latency Communications (URLLC) algorithm and cellular networks are applied in combination with Mobile Broadband (MBB). This is particularly used in express way safety-based driving applications. Expressway vehicle drivers (humans) will communicate in V2X systems using the sixth-generation (6G) communication systems which have very high-speed mobility features. As a result, we need to determine how to ensure reliable and consistent wireless communication links and improve the quality to increase channel gain, which is becoming a challenge that needs to be addressed. To overcome this challenge, we proposed a unique multi-user scheduling algorithm for ultra-massive multiple-input multiple-output (MIMO) systems using 6G. In wideband wireless network access in case of high traffic and also in medium traffic conditions, moreover offering quality-of-service (QoS) to distinct service groups with synchronized contemporaneous traffic on the highway like the Mumbai-Pune expressway becomes a critical problem. Opportunist MAC (OMAC) is a way of proposing communication across a wireless communication link that can change in space and time and might overcome the above-mentioned challenge. Therefore, a multi-user scheduling algorithm is proposed for MIMO systems using a cross-layered MAC protocol to achieve URLLC and high reliability in V2X communication.

Keywords: ultra-reliable low latency communications, vehicle-to-everything communication, multiple-input multiple-output systems, multi-user scheduling algorithm

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Authors: Huey-Kuo Chen

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This paper applies directional marginal productivity model to study the shadow price of emissions by transportation modes in the years of 2011 and 2013 with the aim to provide a reference for policy makers to improve the emission of pollutants. One input variable (i.e., energy consumption), one desirable output variable (i.e., vehicle kilometers traveled) and three undesirable output variables (i.e., carbon dioxide, sulfur oxides and nitrogen oxides) generated by road transportation modes were used to evaluate directional marginal productivity and directional shadow price for 18 transportation modes. The results show that the directional shadow price (DSP) of SOx is much higher than CO2 and NOx. Nevertheless, the emission of CO2 is the largest among the three kinds of pollutants. To improve the air quality, the government should pay more attention to the emission of CO2 and apply the alternative solution such as promoting public transportation and subsidizing electric vehicles to reduce the use of private vehicles.

Keywords: marginal productivity, road transportation modes, shadow price, undesirable outputs

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Authors: P. Gunnasegaran, M. Z. Abdullah, M. Z. Yusoff, Nur Irmawati

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This study presents experimental and optimization of nanoparticle mass concentration and heat input based on the total thermal resistance (Rth) of loop heat pipe (LHP), employed for PC-CPU cooling. In this study, silica nanoparticles (SiO2) in water with particle mass concentration ranged from 0% (pure water) to 1% is considered as the working fluid within the LHP. The experimental design and optimization is accomplished by the design of the experimental tool, Response Surface Methodology (RSM). The results show that the nanoparticle mass concentration and the heat input have a significant effect on the Rth of LHP. For a given heat input, the Rth is found to decrease with the increase of the nanoparticle mass concentration up to 0.5% and increased thereafter. It is also found that the Rth is decreased when the heat input is increased from 20W to 60W. The results are optimized with the objective of minimizing the Rt, using Design-Expert software, and the optimized nanoparticle mass concentration and heat input are 0.48% and 59.97W, respectively, the minimum thermal resistance being 2.66(ºC/W).

Keywords: loop heat pipe, nanofluid, optimization, thermal resistance

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Authors: Sopida Vacharasukpo, Sudarat Khwan-On

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This paper proposes a high step-up DC-DC converter topology for renewable energy system applications. The proposed converter employs only a single power switch instead of using several switches. Compared to the conventional DC-DC step-up converters the higher voltage gain with small output ripples can be achieved by using the proposed high step-up DC-DC converter topology. It can step up the low input voltage (20-50Vdc) generated from the photovoltaic modules to the high output voltage level approximately 600Vdc in order to supply the three-phase inverter fed the three-phase motor drive. In this paper, the operating principle of the proposed converter topology and its control strategy under the continuous conduction mode (CCM) are described. Finally, simulation results are shown to demonstrate the effectiveness of the proposed high step-up DC-DC converter with its control strategy to increase the voltage step-up conversion ratio.

Keywords: DC-DC converter, high step-up ratio, renewable energy, single switch

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Authors: Ramin Mansouri

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The manhole is one of the types of structures that are installed at the site of change direction or change in the pipe diameter or sewage pipes as well as in step slope areas to reduce the flow velocity. In this study, the flow characteristics of hydraulic structures in a manhole structure have been investigated with a numerical model. In this research, the types of computational grid coarse, medium, and fines have been used for simulation. In order to simulate flow, k-ε model (standard, RNG, Realizable) and k-w model (standard SST) are used. Also, in order to find the best wall conditions, two types of standard and non-equilibrium wall functions were investigated. The turbulent model k-ε has the highest correlation with experimental results or all models. In terms of boundary conditions, constant speed is set for the flow input boundary, the output pressure is set in the boundaries which are in contact with the air, and the standard wall function is used for the effect of the wall function. In the numerical model, the depth at the output of the second manhole is estimated to be less than that of the laboratory and the output jet from the span. In the second regime, the jet flow collides with the manhole wall and divides into two parts, so hydraulic characteristics are the same as large vertical shaft hydraulic characteristics. In this situation, the turbulence is in a high range since it can be seen more energy loss in it. According to the results, energy loss in numerical is estimated at 9.359%, which is more than experimental data.

Keywords: manhole, energy, depreciation, turbulence model, wall function, flow

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Authors: R. A. Ribeiro, P. D. Angelo Assunção, E. M. Braga

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The microhardness in weld beads is a function of the microstructure obtained in the welding process, and this by its time is dependent of the input variables established at the outset of the process. In this study the influence of angle between the plate and the cold wire, the position in which the cold wire is introduced and the rate in which this introduction is made are assessed as input parameters in CW-GMAW process. This paper looks to show that ordinary changes in the frame of CW-GMAW can improve microhardness, which is expected to vary as the input parameters change. To properly correlate the changes in the input parameters to consequent changes in microhardness of the weld bead, a full factorial design was employed. In fact, changes in the operational parameters improved the overall microhardness of the weld bead, which in turns can be an indication of improvement in the resistance to abrasive wear, constituting a cheap way to augment the abrasion wear resistance of welds used for cladding.

Keywords: abrasion, CW-GMAW, full factorial design, microhardness

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Ojo Johnson Adelakun

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This study explores the long-term relationships between manufacturing output (MO) and several economic determinants, interest rate (IR), inflation rate (INF), exchange rate (EX), credit to the private sector (CPSM), gross claims on the government sector (GCGS), using monthly data from March 1966 to December 2023. Employing advanced econometric techniques including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR), the analysis provides several key insights. The findings reveal a positive association between interest rates and manufacturing output, which diverges from traditional economic theory that predicts a negative correlation due to increased borrowing costs. This outcome is attributed to the financial resilience of large enterprises, allowing them to sustain investment in production despite higher interest rates. In addition, inflation demonstrates a positive relationship with manufacturing output, suggesting that stable inflation within target ranges creates a favourable environment for investment in productivity-enhancing technologies. Conversely, the exchange rate shows a negative relationship with manufacturing output, reflecting the adverse effects of currency depreciation on the cost of imported raw materials. The negative impact of CPSM underscores the importance of directing credit efficiently towards productive sectors rather than speculative ventures. Moreover, increased government borrowing appears to crowd out private sector credit, negatively affecting manufacturing output. Overall, the study highlights the need for a coordinated policy approach integrating monetary, fiscal, and financial sector strategies. Policymakers should account for the differential impacts of interest rates, inflation, exchange rates, and credit allocation on various sectors. Ensuring stable inflation, efficient credit distribution, and mitigating exchange rate volatility are critical for supporting manufacturing output and promoting sustainable economic growth. This research provides valuable insights into the economic dynamics influencing manufacturing output and offers policy recommendations tailored to South Africa’s economic context.

Keywords: domestic credit, government claims, financial variables, manufacturing output, financial analysis

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Authors: Mahnaz Hosseinzadeh, Mohammad Reza Mehregan

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In this paper, we have developed a morphological field to assist multi- methodology (combining methodologies together in whole or part) in Operations Research (OR) for the problem contexts in Iranian organizations. So, we have attempted to identify some dimensions for problem context according to Iranian organizational problems. Then, a general morphological program is designed which helps the OR practitioner to determine the suitable OR methodology as output for any configuration of conditions in a problem context as input and to reveal the fields necessary to be improved in OR. Applying such a program would have interesting results for OR practitioners.

Keywords: hard, soft and emancipatory operations research, General Morphological Analysis (GMA), multi-methodology, problem context

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Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.

Keywords: Box-Jenkins's problem, double-input rule module, fuzzy inference model, obstacle avoidance, single-input rule module

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Authors: Prateek Guleria, Shubham Sharma, Rakesh Kumar Shukla, Harshit Sharma

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Performance measurement of small and medium-sized businesses is the primary need for all companies to survive and thrive in a dynamic global company. A structured and systematic, integrated organization increases employee reliability, sustainability, and loyalty. This paper is a case study of a gear manufacturing industry that was facing the problem of rejection due to dents and damages in gear. The DMAIC cycle, along with different tools used in the research work includes SIPOC (Supply, Input, Process, Output, Control) Pareto analysis, Root & Cause analysis, and FMEA (Failure Mode and Effect Analysis). The six-sigma level was improved from 4.06 to 3.46, and the rejection rate was reduced from 7.44% to 1.56%. These findings highlighted the influence of a Lean Six Sigma module in the gear manufacturing unit, which has already increased operational quality and continuity to increase market success and meet customer expectations. According to the findings, applying lean six sigma tools will result in increased productivity. The results could assist businesses in deciding the quality tools that were likely to improve efficiency, competitiveness, and expense.

Keywords: six sigma, DMAIC, SIPOC, failure mode, effect analysis

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Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

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Authors: Murat Iskender Aktaş, Sadi Ergin, Rasime Acar Aktaş

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In the light of fast-paced changes and developments in the health sector, the Ministry of Health started a new structuring with decree law numbered 663 within the scope of the Project of Transformation in Health. Accordingly, hospitals should ensure patient satisfaction through more efficient, more effective use of resources and sustainable finance by placing patients in the centre and should operate to increase efficiency to its maximum level while doing these. Within this study, in order to find out how efficient the hospitals were in terms of medical waste management between the years 2011-2014, the data from six hospitals of Amasya Public Hospitals Union were evaluated separately through Data Envelopment Analysis (DEA) method. First of all, input variables were determined. Input variables were the number of patients admitted to polyclinics, the number of inpatients in clinics, the number of patients who were operated and the number of patients who applied to the laboratory. Output variable was the cost of medical wastes in Turkish liras. Each hospital’s total medical waste level before and after public hospitals union; the amounts of average medical waste per patient admitted to polyclinics, per inpatient in clinics, per patient admitted to laboratory and per operated patient were compared within each group. In addition, average medical waste levels and costs were compared for Turkey in general and Europe in general. Paired samples t-test was used to find out whether the changes (increase-decrease) after public hospitals union were statistically significant. The health facilities that were unsuccessful in terms of medical waste management before and after public hospital union and the factors that caused this failure were determined. Based on the results, for each health facility that was ineffective in terms of medical waste management, the level of improvement required for each input was determined. The results of the study showed that there was an improvement in medical waste management applications after the health facilities became a member of public hospitals union; their medical waste levels were lower than the average of Turkey and Europe while the averages of cost of disposal were the highest.

Keywords: medical waste management, cost of medical waste, public hospitals, data envelopment analysis

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Authors: M. Heydari Vini

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There is a complicated relation between effective input parameters of cold rolling and output rolling force and exit thickness of strips.in many mathematical models, the effect of some rolling parameters have been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips,the width of the strips,rolling speeds,mandrill tensions and the required exit thickness of strips with rolling force and the real exit thickness of the rolled strip. First of all, in this paper the effective parameters of cold rolling process modeled using an artificial neural network according to the optimum network achieved by using a written program in MATLAB,it has been shown that the prediction of rolling stand parameters with different properties and new dimensions attained from prior rolled strips by an artificial neural network is applicable.

Keywords: cold rolling, artificial neural networks, rolling force, real rolled thickness of strips

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Authors: Sanket S. Jugade, Swapneel U. Naphade, Satyabodh M. Kulkarni

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Microscale energy harvesters can be used to convert ambient mechanical vibrations to electrical energy. Such devices have great applications in low powered electronics in remote environments like powering wireless sensor nodes of Internet of Things, lightings on highways or in ships, etc. In this paper, a Microelectromechanical systems (MEMS) based energy harvester has been modeled using Analytical and Finite Element Method (FEM). The device consists of a microcantilever with a proof mass attached to its free end and a Polyvinylidene Fluoride (PVDF) piezoelectric thin film deposited on the surface of microcantilever in a unimorph or bimorph configuration. For the analytical method, the energy harvester was modeled as an equivalent electrical system in SIMULINK. The Finite element model was developed and analyzed using the commercial package COMSOL Multiphysics. The modal analysis was performed first to find the fundamental natural frequency and its variation with geometrical parameters of the system. Then the harmonic analysis was performed to find the input mechanical power, output electrical voltage, and power for a range of excitation frequencies and base acceleration values. The variation of output power with load resistance, PVDF film thickness, and damping values was also found out. The results from FEM were then validated with that of the analytical model. Finally, the performance of the device was optimized with respect to various electro-mechanical parameters. For a unimorph configuration consisting of single crystal silicon microcantilever of dimensions 8mm×2mm×80µm and proof mass of 9.32 mg with optimal values of the thickness of PVDF film and load resistance as 225 µm and 20 MΩ respectively, the maximum electrical power generated for base excitation of 0.2g at 630 Hz is 0.9 µW.

Keywords: bimorph, energy harvester, FEM, harmonic analysis, MEMS, PVDF, unimorph

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Authors: Eunsu Jang, Kang Park

Abstract:

In developing an armored ground combat vehicle (AGCV), it is a very important step to analyze the vulnerability (or the survivability) of the AGCV against enemy’s attack. In the vulnerability analysis, the penetration equations are usually used to get the penetration depth and check whether a bullet can penetrate the armor of the AGCV, which causes the damage of internal components or crews. The penetration equations are derived from penetration experiments which require long time and great efforts. However, they usually hold only for the specific material of the target and the specific type of the bullet used in experiments. Thus, penetration simulation using ANSYS can be another option to calculate penetration depth. However, it is very important to model the targets and select the input parameters in order to get an accurate penetration depth. This paper performed a sensitivity analysis of input parameters of ANSYS on the accuracy of the calculated penetration depth. Two conflicting objectives need to be achieved in adopting ANSYS in penetration analysis: maximizing the accuracy of calculation and minimizing the calculation time. To maximize the calculation accuracy, the sensitivity analysis of the input parameters for ANSYS was performed and calculated the RMS error with the experimental data. The input parameters include mesh size, boundary condition, material properties, target diameter are tested and selected to minimize the error between the calculated result from simulation and the experiment data from the papers on the penetration equation. To minimize the calculation time, the parameter values obtained from accuracy analysis are adjusted to get optimized overall performance. As result of analysis, the followings were found: 1) As the mesh size gradually decreases from 0.9 mm to 0.5 mm, both the penetration depth and calculation time increase. 2) As diameters of the target decrease from 250mm to 60 mm, both the penetration depth and calculation time decrease. 3) As the yield stress which is one of the material property of the target decreases, the penetration depth increases. 4) The boundary condition with the fixed side surface of the target gives more penetration depth than that with the fixed side and rear surfaces. By using above finding, the input parameters can be tuned to minimize the error between simulation and experiments. By using simulation tool, ANSYS, with delicately tuned input parameters, penetration analysis can be done on computer without actual experiments. The data of penetration experiments are usually hard to get because of security reasons and only published papers provide them in the limited target material. The next step of this research is to generalize this approach to anticipate the penetration depth by interpolating the known penetration experiments. This result may not be accurate enough to be used to replace the penetration experiments, but those simulations can be used in the early stage of the design process of AGCV in modelling and simulation stage.

Keywords: ANSYS, input parameters, penetration depth, sensitivity analysis

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Authors: Anupama Purohit

Abstract:

The paper is a study on the inevitable cross-linguistic effect found in the early multilingual learners. The cross-linguistic behaviour like code-mixing, code-switching, foreign accent, literal translation, redundancy and syntactic manipulation effected due to other languages on the English language output of a non-native pre-school child are discussed here. A case study method is adopted in this paper to support the claim of the title. A simultaneously tetra lingual pre-school child’s (within 1;3 to 4;0) language behaviour is analysed here. The sample output data of the child is gathered from the diary entries maintained by her family, regular observations and video recordings done since her birth. She is getting the input of her mother tongue, Sambalpuri, from her grandparents only; Hindi, the local language from her play-school and the neighbourhood; English only from her mother and occasional visit of other family friends; Odia only during the reading of the Odia story book. The child is exposed to code-mixing of all the languages throughout her childhood. But code-mixing, literal translation, redundancy and duplication were absent in her initial stage of multilingual acquisition. As the child was more proficient in English in comparison to her other first languages and had never heard code-mixing in English language; it was expected from her input pattern of English (one parent, English language) that she would maintain purity in her use of English while talking to the English language interlocutor. But with gradual increase in the language proficiency in each of the languages of the child, her handling of the multiple codes becomes deft cross-linguistically. It can be deduced from the case study that after attaining certain milestone proficiency in each language, the child’s linguistic faculty can operate at a metalinguistic level. The functional use of each morpheme, their arrangement in words and in the sentences, the supra segmental features, lexical-semantic mapping, culture specific use of a language and the pragmatic skills converge to give a typical childlike multilingual output in an intelligible manner to the multilingual people (with the same set of languages in combination). The result is appealing because for expressing the same ideas which the child used to speak (may be with grammatically wrong expressions) in one language, gradually, she starts showing cross-linguistic effect in her expressions. So the paper pleads for the separatist view from the very beginning of the holophrastic phase (as the child expresses in addressee-specific language); but development of a metalinguistic ability that helps the child in communicating in a sophisticated way according to the linguistic status of the addressee is unique to the multilingual child. This metalinguistic ability is independent of the mode if input of a multilingual child.

Keywords: code-mixing, cross-linguistic effect, early multilingualism, literal translation

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Authors: Eyhab El-Kharashi, Maher El-Dessouki

Abstract:

The paper is dedicated to precise assessment of the induction motor output energy during the unbalanced operation. Since many years ago and until now the voltage complex unbalance factor (CVUF) is used only to assess the output energy of the induction motor while this output energy for asymmetry supply voltage does not depend on the value of unbalanced voltage only but also on the machine parameters. The paper illustrates the variation of the two unbalance factors, complex voltage unbalance factor (CVUF) and impedance unbalance factor (IUF), with positive sequence voltage component, reveals that degree and manner of unbalance in supply voltage. From this point of view the paper delineates the current unbalance factor (CUF) to exactly reflect the output energy during unbalanced operation. The paper proceeds to illustrate the importance of using this factor in the multi-machine system to precise prediction of the output energy during the unbalanced operation. The use of the proposed unbalance factor (CUF) avoids the accumulation of the error due to more than one machine in the system which is expected if only the complex voltage unbalance factor (CVUF) is used.

Keywords: induction motor, electromagnetic torque, voltage unbalance, energy conversion

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Authors: MeiBo, ZhaoXing, LuoLei, YuQingkui, TangMin, HanZhengsheng

Abstract:

The Single Event Transients (SETs) were investigated on 0.18μm PDSOI transistors and 100 series CMOS inverter chain using pulse laser. The effect of different laser energy and device bias for waveform on SET was characterized experimentally, as well as the generation and propagation of SET in inverter chain. In this paper, the effects of struck transistors type and struck locations on SETs were investigated. The results showed that when irradiate NMOSFETs from 100th to 2nd stages, the SET pulse width measured at the output terminal increased from 287.4 ps to 472.9 ps; and when irradiate PMOSFETs from 99th to 1st stages, the SET pulse width increased from 287.4 ps to 472.9 ps. When struck locations were close to the output of the chain, the SET pulse was narrow; however, when struck nodes were close to the input, the SET pulse was broadening. SET pulses were progressively broadened up when propagating along inverter chains. The SET pulse broadening is independent of the type of struck transistors. Through analysis, history effect induced threshold voltage hysteresis in PDSOI is the reason of pulse broadening. The positive pulse observed by oscilloscope, contrary to the expected results, is because of charging and discharging of capacitor.

Keywords: single event transients, pulse laser, partially-depleted silicon-on-insulator, propagation-induced pulse broadening effect

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Authors: Y. Kobori, S. Tanaka, N. Tsukiji, N. Takai, H. Kobayashi

Abstract:

This paper proposes two kinds of new single-inductor dual-output (SIDO) DC-DC switching converters with ripple-based hysteretic control. First SIDO converters of type 1 utilize the triangular signal generated by the CR-circuit connected across the inductor. This triangular signal is used for generating the PWM signal instead of the saw-tooth signal used in the conventional converters. Second SIDO converters of type 2 utilize the triangular signal generated by the CR-circuit connected across the voltage error amplifier. This paper describes circuit topologies, Operation principles, simulation results and experimental results of the proposed SIDO converters. In simulation results of both type of SIDO converters, static output voltage ripples are less than 5mVpp and over/under shoots of the dynamic load regulations for the output current step are less than +/- 10mV. In experimental results of single output converter of type 2, static output voltage ripples are about 20mVpp. Output ripples of SIDO type 1 converter are about 80mVpp.

Keywords: DC-DC converter, switching converter, SIDO converter, hysteretic control, ripple-based control

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Authors: Mukisa Simon Peter Turker, Etomaru Irene

Abstract:

This study examined factors determining the success of University-Industry Collaboration (UIC) in the science academic units (SAUs) at Makerere University. This was prompted by concerns about weak linkages between industry and the academic units at Makerere University. The study examined institutional, relational, output, and framework factors determining the success of UIC in the science academic units at Makerere University. The study adopted a predictive cross-sectional survey design. Data was collected using a questionnaire survey from 172 academic staff from the six SAUs at Makerere University. Stratified, proportionate, and simple random sampling techniques were used to select the samples. The study used descriptive statistics and linear multiple regression analysis to analyze data. The study findings reveal a coefficient of determination (R-square) of 0.403 at a significance level of 0.000, suggesting that UIC success was 40.3% at a standardized error of estimate of 0.60188. The strength of association between Institutional factors, Relational factors, Output factors, and Framework factors, taking into consideration all interactions among the study variables, was at 64% (R= 0.635). Institutional, Relational, Output and Framework factors accounted for 34% of the variance in the level of UIC success (adjusted R2 = 0.338). The remaining variance of 66% is explained by factors other than Institutional, Relational, Output, and Framework factors. The standardized coefficient statistics revealed that Relational factors (β = 0.454, t = 5.247, p = 0.000) and Framework factors (β = 0.311, t = 3.770, p = 0.000) are the only statistically significant determinants of the success of UIC in the SAU in Makerere University. Output factors (β = 0.082, t =1.096, p = 0.275) and Institutional factors β = 0.023, t = 0.292, p = 0.771) turned out to be statistically insignificant determinants of the success of UIC in the science academic units at Makerere University. The study concludes that Relational Factors and Framework Factors positively and significantly determine the success of UIC, but output factors and institutional factors are not statistically significant determinants of UIC in the SAUs at Makerere University. The study recommends strategies to consolidate Relational and Framework Factors to enhance UIC at Makerere University and further research on the effects of Institutional and Output factors on the success of UIC in universities.

Keywords: university-industry collaboration, output factors, relational factors, framework factors, institutional factors

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