Search results for: input–output analysis

Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information

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Authors: Jolly Puri, Shiv Prasad Yadav

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Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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Authors: Dae-Hee Son, Soon-Ryul Nam

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The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.

Keywords: PSS/E user defined model, power deviation, frequency droop control, ROCOF (rate of change of frequency)

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Authors: J. A. Ujam, J. L. Chukwuneke, C. H. Achebe, G. O. R. Ikwu

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This work investigates the effect of head and bucket splitter angle on the power output of a pelton turbine (water turbine), so as to boost the efficiency of Hydro-electric power generation systems. A simulation program was developed using MatLab to depict the force generated by the bucket as the water jet strikes the existing splitter angle (100 to 150) and predicted (10 to 250) splitter angles. Result shows that in addition to the existing splitter angle, six more angles have been investigated for the two operating conditions to give maximum power. The angles are 250, 60 and 190 for high head and low flow with increased pressure while low head and high flow with decreased pressure are 230, 210 and 30 in order of the maximum generating power. The Turbine power output for simulation was more than that of the experiment. This was as a result of their head conditions and the bucket splitter angle.

Keywords: bucket splitter angle, force, head, modelling, pelton turbine, power output, shaft output

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Authors: Yasunori Kobori, Nobukazu Tsukiji, Nobukazu Takai, Haruo Kobayashi

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In this paper, we study a Pulse-WidthModulation (PWM) controlled Zero-Voltage-Switching (ZVS) for single-inductor dual-output (SIDO) converters. This method can meet the industry demands for high efficiency due to ZVS and small size and low cost, thanks to single-inductor per multiple voltages. We show the single inductor single-output (SISO) ZVS buck converter with its operation and simulation and then the experimental results. Next proposed ZVS-PWM controlled SIDO converters are explained in the simulation. Finally we have proposed EMI reduction method with spread spectrum.

Keywords: DC-DC switching converter, zero-oltage switching control, single-inductor dual-output converter, EMI reduction, spread spectrum

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Authors: Surinder Singh, Gursewak Singh Lovkesh

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We have designed wavelength conversion based on four wave mixing in an optical fiber at 10 Gb/s. The power of converted signal increases with increase in signal power. The converted signal power is investigated as a function of input signal power and pump power. On comparison of converted signal power at different value of input signal power, we observe that best converted signal power is obtained at -2 dBm input signal power for both up conversion as well as for down conversion. Further, FWM efficiency, quality factor is observed for increase in input signal power and optical fiber length.

Keywords: FWM, optical fiiber, wavelngth converter, quality

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Authors: Babar Rasheed, Saad Ghafoor

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Introduction: Idea campaigns are commonly held across organizations for generating employee engagement. The contribution is specifically designed to identify and solve prevalent issues. It is argued that numerous organizations fail to achieve their desired goals despite arranging for such campaigns and investing heavily in them. There are however practices that organizations use to achieve higher degree of effectiveness, and these practices may be up for exploration by research to make them usable for the other organizations. Purpose: The aim of this research is to surface the idea management practices of a leading electric company with global operations. The study involves a large sized, multi site organization that is attributed to have added challenges in terms of managing ideas from employees, in comparison to smaller organizations. The study aims to highlight the factors that are looked at as the idea management team strategies for the campaign, sets terms and rewards for it, makes follow up with the employees and lastly, evaluate and award ideas. Methodology: The study is conducted in a leading electric appliance corporation that has a large number of employees and is based in numerous regions of the world. A total of 7 interviews are carried out involving the chief innovation officer, innovation manager and members of idea management and evaluation teams. The interviews are carried out either on Skype or in-person based on the availability of the interviewee. Findings: While this being a working paper and while the study is under way, it is anticipated that valuable information is being achieved about specific details on how idea management systems are governed and how idea campaigns are carried out. The findings may be particularly useful for innovation consultants as resources they can use to promote idea campaigning. The usefulness of the best practices highlighted as a result is, in any case, the most valuable output of this study.

Keywords: employee engagement, motivation, idea campaigns, large organizations, best practices, employees input, organizational output

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Tran Gia Khanh, Dao Phuong Nam, Do Trong Tan, Nguyen Van Huong, Mai Xuan Sinh

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This work presents the problem of tube-based robust model predictive controller for a class of continuous-time systems in the presence of input disturbances. The main objective is to point out the state trajectory of closed system being maintained inside a sequence of tubes. An estimation of attraction region of the closed system is pointed out based on input state stability (ISS) theory and linearized model in each time interval. The theoretical analysis and simulation results demonstrate the performance of the proposed algorithm for a wheeled inverted pendulum system.

Keywords: input state stability (ISS), tube-based robust MPC, continuous-time nonlinear systems, wheeled inverted pendulum

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Edwina G. Rodrigues, S. J. Bindhu, A. V. Rajesh

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This paper proposes a switched capacitor based driver circuit for high power light emitting diodes with a front end rectifier. LEDs are low-voltage light sources, requiring a constant DC voltage or current to operate optimally. LEDs, therefore, require a device that can convert incoming AC power to the proper DC voltage, and regulate the current flowing through the LED during operation. Proposed topology has a front end converter. It is an AC-DC rectifier that works on bridgeless boost topology which shapes the input current waveform. The front end converter is followed by a DC-DC converter which provides a constant DC voltage across the LEDs. A 12V AC input is given to the input of frontend converter which rectifies and boost the voltage to 24v DC and gives it to the DC-DC converter. The DC-DC converter converts the 24V DC and regulates this constant DC voltage across the LEDs.

Keywords: bridgeless rectifier, power factor correction(PFC), SC converter, total harmonic distortion (THD)

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Authors: Mohammad Hassanzadeh

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As far as incidental vocabulary learning is concerned, the basic contention of the Involvement Load Hypothesis (ILH) is that retention of unfamiliar words is, generally, conditional upon the degree of involvement in processing them. This study examined input modality and incidental vocabulary uptake in a task-induced setting whereby three variously loaded task types (marginal glosses, fill-in-task, and sentence-writing) were alternately assigned to one group of students at Allameh Tabataba’i University (n=2l) during six classroom sessions. While one round of exposure was comprised of the audiovisual medium (TV talk shows), the second round consisted of textual materials with approximately similar subject matter (reading texts). In both conditions, however, the tasks were equivalent to one another. Taken together, the study pursued the dual objectives of establishing a litmus test for the ILH and its proposed values of ‘need’, ‘search’ and ‘evaluation’ in the first place. Secondly, it sought to bring to light the superiority issue of exposure to audiovisual input versus the written input as far as the incorporation of tasks is concerned. At the end of each treatment session, a vocabulary active recall test was administered to measure their incidental gains. Running a one-way analysis of variance revealed that the audiovisual intervention yielded higher gains than the written version even when differing tasks were included. Meanwhile, task 'three' (sentence-writing) turned out the most efficient in tapping learners' active recall of the target vocabulary items. In addition to shedding light on the superiority of audiovisual input over the written input when circumstances are relatively held constant, this study for the most part, did support the underlying tenets of ILH.

Keywords: Keywords— Evaluation, incidental vocabulary learning, input mode, Involvement Load Hypothesis, need, search.

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Authors: Hale Kirer Silva Lecuna, Beyza Aydin

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Health is one of the main components of human capital and sustainable development, and it is very important for economic growth. Health economics, which is an indisputable part of the science of economics, has five stages in general. These are health and development, financing of health services, economic regulation in the health, allocation of resources and efficiency of health services. A well-developed and efficient health sector plays a major role by increasing the level of development of countries. The most crucial pillars of the health sector are the hospitals that are divided into public and private. The main purpose of the hospitals is to provide more efficient services. Therefore the aim is to meet patients’ satisfaction by increasing the service quality. Health-related studies in Turkey date back to the Ottoman and Seljuk Empires. In the near past, Turkey applied 'Health Sector Transformation Programs' under different titles between 2003 and 2010. Our aim in this paper is to measure how effective these transformation programs are for the health sector, to see how much they can increase the efficiency of hospitals over the years, to see the return of investments, to make comments and suggestions on the results, and to provide a new reference for the literature. Within this framework, the public and private hospitals in Balıkesir, Bilecik, Bursa, Çanakkale, Edirne, Istanbul, Kirklareli, Kocaeli, Sakarya, Tekirdağ, Yalova will be examined by using Data Envelopment Analysis (DEA) for the years between 2000 and 2019. DEA is a linear programming-based technique, which gives relatively good results in multivariate studies. DEA basically estimates an efficiency frontier and make a comparison. Constant returns to scale and variable returns to scale are two most commonly used DEA methods. Both models are divided into two as input and output-oriented. To analyze the data, the number of personnel, number of specialist physicians, number of practitioners, number of beds, number of examinations will be used as input variables; and the number of surgeries, in-patient ratio, and crude mortality rate as output variables. 11 hospitals belonging to the Marmara region were included in the study. It is seen that these hospitals worked effectively only in 7 provinces (Balıkesir, Bilecik, Bursa, Edirne, İstanbul, Kırklareli, Yalova) for the year 2001 when no transformation program was implemented. After the transformation program was implemented, for example, in 2014 and 2016, 10 hospitals (Balıkesir, Bilecik, Bursa, Çanakkale, Edirne, İstanbul, Kocaeli, Kırklareli, Tekirdağ, Yalova) were found to be effective. In 2015, ineffective results were observed for Sakarya, Tekirdağ and Yalova. However, since these values are closer to 1 after the transformation program, we can say that the transformation program has positive effects. For Sakarya alone, no effective results have been achieved in any year. When we look at the results in general, it shows that the transformation program has a positive effect on the effectiveness of hospitals.

Keywords: data envelopment analysis, efficiency, health sector, Marmara region

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Chao Xu

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Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result.

Keywords: vulnerability, probability seismic demand analysis, ground motion intensity measure, sufficiency, efficiency, inelastic time history analysis

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Authors: Joon-Hoon Park

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The fundamental concept of observability is important in both theoretical and practical points of modern control systems. In modern control theory, a control system has criteria for determining the design solution exists for the system parameters and design objectives. The idea of observability relates to the condition of observing or estimating the state variables from the output variables that is generally measurable. To design closed-loop control system, the practical problems of implementing the feedback of the state variables must be considered and implementing state feedback control problem has been existed in this case. All the state variables are not available, so it is requisite to design and implement an observer that will estimate the state variables form the output parameters. However sometimes unknown inputs are presented in control systems as practical cases. This paper presents a design method and algorithm for observer of control system with unknown input parameters based on Rationalized Haar transform. The proposed method is more advantageous than the other numerical method.

Keywords: orthogonal functions, rationalized Haar transforms, control system observer, algebraic method

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Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

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A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference to signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: noise signal, pulse interference, signal power, spectrum width, detection

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Authors: Jianlin Wang, Jiajia Zhao

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This paper applies the theory and empirical method to examine the relationship between electricity price and coal price, as well as electricity and industry output, for China during Jan 1999-Dec 2012. Our results indicate that there is no any causality between coal price and electricity price under other factors are controlled. However, we found a bi-directional causality between electricity consumption and industry output. Overall, the electricity price set by China’s NDRC is inefficient, which lead to the electricity supply shortage after 2004. It is time to reform electricity price system for China’s reformers.

Keywords: electricity price, coal price, power supply, China

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Authors: Hamid Goharnejad, Amir Hossein Eghbali

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Recent investigations have demonstrated the global sea level rise due to climate change impacts. In this study climate changes study the effects of increasing water level in the strait of Hormuz. The probable changes of sea level rise should be investigated to employ the adaption strategies. The climatic output data of a GCM (General Circulation Model) named CGCM3 under climate change scenario of A1b and A2 were used. Among different variables simulated by this model, those of maximum correlation with sea level changes in the study region and least redundancy among themselves were selected for sea level rise prediction by using stepwise regression. One models of Discrete Wavelet artificial Neural Network (DWNN) was developed to explore the relationship between climatic variables and sea level changes. In these models, wavelet was used to disaggregate the time series of input and output data into different components and then ANN was used to relate the disaggregated components of predictors and predictands to each other. The results showed in the Shahid Rajae Station for scenario A1B sea level rise is among 64 to 75 cm and for the A2 Scenario sea level rise is among 90 to 105 cm. Furthermore the result showed a significant increase of sea level at the study region under climate change impacts, which should be incorporated in coastal areas management.

Keywords: climate change scenarios, sea-level rise, strait of Hormuz, forecasting

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Authors: Pornpimol Chaiwuttisak

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The study aims to compare the performance of the logistics for Thailand’s wholesale and retail trade industries (except motor vehicles, motorcycle, and stalls) by using data (data envelopment analysis). Thailand Standard Industrial Classification in 2009 (TSIC - 2009) categories that industries into sub-group no. 45: wholesale and retail trade (except for the repair of motor vehicles and motorcycles), sub-group no. 46: wholesale trade (except motor vehicles and motorcycles), and sub-group no. 47: retail trade (except motor vehicles and motorcycles. Data used in the study is collected by the National Statistical Office, Thailand. The study consisted of four input factors include the number of companies, the number of personnel in logistics, the training cost in logistics, and outsourcing logistics management. Output factor includes the percentage of enterprises having inventory management. The results showed that the average relative efficiency of small-sized enterprises equals to 27.87 percent and 49.68 percent for the medium-sized enterprises.

Keywords: DEA, wholesales and retails, logistics, Thailand

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Authors: Vishal Pareek, Shubham Gupta, Sushil Chandra Jain

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With increasing high-speed computation demand the power consumption, heat dissipation and chip size issues are posing challenges for logic design with conventional technologies. Recovery of bit loss and bit errors is other issues that require reversibility and fault tolerance in the computation. The reversible computing is emerging as an alternative to conventional technologies to overcome the above problems and helpful in a diverse area such as low-power design, nanotechnology, quantum computing. Bit loss issue can be solved through unique input-output mapping which require reversibility and bit error issue require the capability of fault tolerance in design. In order to incorporate reversibility a number of combinational reversible logic based circuits have been developed. However, very few sequential reversible circuits have been reported in the literature. To make the circuit fault tolerant, a number of fault model and test approaches have been proposed for reversible logic. In this paper, we have attempted to incorporate fault tolerance in sequential reversible building blocks such as D flip-flop, T flip-flop, JK flip-flop, R-S flip-flop, Master-Slave D flip-flop, and double edge triggered D flip-flop by making them parity preserving. The importance of this proposed work lies in the fact that it provides the design of reversible sequential circuits completely testable for any stuck-at fault and single bit fault. In our opinion our design of reversible building blocks is superior to existing designs in term of quantum cost, hardware complexity, constant input, garbage output, number of gates and design of online testable D flip-flop have been proposed for the first time. We hope our work can be extended for building complex reversible sequential circuits.

Keywords: parity preserving gate, quantum computing, fault tolerance, flip-flop, sequential reversible logic

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Authors: Isah Wada

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The current research investigates the role of financial development in an environmental sustainability-energy consumption nexus for OPEC-1 member countries. The empirical findings suggest that financial development increases environmental sustainability but energy consumption and real output expansion diminishes environmental sustainability, generally. Thus, whilst real output and financial development accelerates energy consumption, environmental sustainability quality diminishes clean energy initiatives. Even more so, energy consumption and financial development stimulates real output growth. The result empirically demonstrates that policy advocates must address broader issues relating to financial development whilst seeking to achieve environmental sustainability due largely to energy consumption.

Keywords: energy consumption, environmental sustainability, financial development, OPEC, real output

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Authors: Myunggon Yoon, Jung-Ho Moon

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In this paper, we present a transfer function representation of a general one-dimensional combustor. The input of the transfer function is a heat rate perturbation of a burner and the output is a flow velocity perturbation at the burner. This paper considers a general combustor model composed of multiple cans with different cross sectional areas, along with a non-zero flow rate.

Keywords: combustor, dynamics, thermoacoustics, transfer function

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Authors: Bentoutou Houari, Boutte Aissa, Belaidi El Yazid, Limam Lakhdar

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The integration of a load switch with a DC/DC buck converter using LM2596 for power distribution in low-cost educational nanosatellites is a technique that aims to efficiently manage the power distribution system in these small spacecraft. The converter is based on the LM2596 regulator and designed to step down the input voltage of +16.8V to +12V, +5V, and +3.3V output, which are suitable for the nanosatellite's various subsystems. The load switch is based on MOSFET and is used to turn on or off the power supply to a particular load and protect the nanosatellite from power surges. A prototype of a +12V DC/DC buck converter with a high side load switch has been realized and tested, which meets our requirements and shows a good efficiency of 89%. In addition, the prototype features a capacitor between the source and gate of the MOSFET, which has effectively reduced the inrush current, demonstrating the effectiveness of this approach in reducing surges of current when the load is connected. The output current and voltage were measured at 0.7A and 11.89V, respectively, making this design suitable for use in low-cost educational nanosatellites.

Keywords: DC/DC buck converter, load switch, LM2596, electrical power subsystems, nanosatellite, inrush current

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Authors: Mahdi Shaghaghi, Amir Ghaebi, Fariba Ahmadi

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Purpose: The main purpose of the present research is to analyze the knowledge creation environment at a Iranian University (Alzahra University) as a typical University in Iran, using a combination of the i-System and Ba models. This study is necessary for understanding the determinants of knowledge creation at Alzahra University as a typical University in Iran. Methodology: To carry out the present research, which is an applied study in terms of purpose, a descriptive survey method was used. In this study, a combination of the i-System and Ba models has been used to analyze the knowledge creation environment at Alzahra University. i-System consists of 5 constructs including intervention (input), intelligence (process), involvement (process), imagination (process), and integration (output). The Ba environment has three pillars, namely the infrastructure, the agent, and the information. The integration of these two models resulted in 11 constructs which were as follows: intervention (input), infrastructure-intelligence, agent-intelligence, information-intelligence (process); infrastructure-involvement, agent-involvement, information-involvement (process); infrastructure-imagination, agent-imagination, information-imagination (process); and integration (output). These 11 constructs were incorporated into a 52-statement questionnaire and the validity and reliability of the questionnaire were examined and confirmed. The statistical population included the faculty members of Alzahra University (344 people). A total of 181 participants were selected through the stratified random sampling technique. The descriptive statistics, binomial test, regression analysis, and structural equation modeling (SEM) methods were also utilized to analyze the data. Findings: The research findings indicated that among the 11 research constructs, the levels of intervention, information-intelligence, infrastructure-involvement, and agent-imagination constructs were average and not acceptable. The levels of infrastructure-intelligence and information-imagination constructs ranged from average to low. The levels of agent-intelligence and information-involvement constructs were also completely average. The level of infrastructure-imagination construct was average to high and thus was considered acceptable. The levels of agent-involvement and integration constructs were above average and were in a highly acceptable condition. Furthermore, the regression analysis results indicated that only two constructs, viz. the information-imagination and agent-involvement constructs, positively and significantly correlate with the integration construct. The results of the structural equation modeling also revealed that the intervention, intelligence, and involvement constructs are related to the integration construct with the complete mediation of imagination. Discussion and conclusion: The present research suggests that knowledge creation at Alzahra University relatively complies with the combination of the i-System and Ba models. Unlike this model, the intervention, intelligence, and involvement constructs are not directly related to the integration construct and this seems to have three implications: 1) the information sources are not frequently used to assess and identify the research biases; 2) problem finding is probably of less concern at the end of studies and at the time of assessment and validation; 3) the involvement of others has a smaller role in the summarization, assessment, and validation of the research.

Keywords: i-System, Ba model , knowledge creation , knowledge management, knowledge creation environment, Iranian Universities

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

Abstract:

In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we use a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation, estimates, full-band, mixtures, sub-band

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Authors: Isabela Romanha de Alcantara, Jose Eustaquio Ribeiro Vieira Filho, Jose Garcia Gasques

Abstract:

Innovation and technology can be determinant factors to ensure agricultural and sustainable growth, as well as productivity gains. Technical change has contributed considerably to supply agricultural expansion in Brazil. This agricultural growth could be achieved by incorporating more land or capital. If capital is the main source of agricultural growth, it is possible to increase production per unit of land. The objective of this paper is to estimate: 1) total factor productivity (TFP), which is measured in terms of the rate of output per unit of input; and 2) the land-saving effect (LSE) that is the amount of land required in the case that yield rate is constant over time. According to this study, from 1990 to 2019, it appears that 87 percent of Brazilian agriculture product growth comes from the gains of productivity; the rest of 13 percent comes from input growth. In the same period, the total LSE was roughly 400 Mha, which corresponds to 47 percent of the national territory. These effects reflect the greater efficiency of using productive factors, whose technical change has allowed an increase in agricultural production based on productivity gains.

Keywords: agriculture, land-saving effect, livestock, productivity

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Authors: Kittipong Tripetch, Nobuhiko Nakano

Abstract:

Two types of floating active resistors based on a complementary regulated cascode topology with cross-coupled regulated transistors are presented in this paper. The first topology is a high swing complementary regulated cascode active resistor. The second topology is a complementary common gate with a regulated cross coupled transistor. The small-signal input resistances of the floating resistors are derived. Three graphs of the input current versus the input voltage for different aspect ratios are designed and plotted using the Cadence Spectre 0.18-µm Rohm Semiconductor process. The total harmonic distortion graphs are plotted for three different aspect ratios with different input-voltage amplitudes and different input frequencies. From the simulation results, it is observed that a resistance of approximately 8.52 MΩ can be obtained from supply voltage at  ±0.9 V.

Keywords: floating active resistor, complementary common gate, complementary regulated cascode, current mirror

Procedia PDF Downloads 237