Search results for: Average Run Length

Authors: A. J. Al-Shareef, E. A. Mohamed, E. Al-Judaibi

Abstract:

Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

Keywords: Artificial neural networks, short-term load forecasting, back propagation.

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Authors: Carlo Cernicchiaro, Pedro D. Gaspar, Martim L. Aguiar

Abstract:

The agricultural sector is becoming more critical than ever in view of the expected overpopulation of the Earth. The introduction of robotic solutions in this field is an increasingly researched topic to make the most of the Earth's resources, thus going to avoid the problems of wear and tear of the human body due to the harsh agricultural work, and open the possibility of a constant careful processing 24 hours a day. This project is realized for a terrestrial autonomous robot aimed to navigate in an orchard collecting fallen peaches below the trees. When it receives the signal indicating the low battery, it has to return to the docking station where it will replace its battery and then return to the last work point and resume its routine. Considering a preset path in orchards with tree rows with variable length by which the robot goes iteratively using the algorithm D*. In case of low battery, the D* algorithm is still used to determine the fastest return path to the docking station as well as to come back from the docking station to the last work point. MATLAB simulations were performed to analyze the flexibility and adaptability of the developed algorithm. The simulation results show an enormous potential for adaptability, particularly in view of the irregularity of orchard field, since it is not flat and undergoes modifications over time from fallen branch as well as from other obstacles and constraints. The D* algorithm determines the best route in spite of the irregularity of the terrain. Moreover, in this work, it will be shown a possible solution to improve the initial points tracking and reduce time between movements.

Keywords: Path planning, fastest return path, agricultural terrestrial robot, autonomous, docking station.

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Authors: Won Song, Bo-Ra Koo, Seok Eui Choi, Yong-Taeg Oh, Dong-Chan Shin

Abstract:

Optical properties of sputter-deposited ZnS thin films were investigated as potential replacements for CBD(chemical bath deposition) CdS buffer layers in the application of CIGS solar cells. ZnS thin films were fabricated on glass substrates at RT, 150oC, 200oC, and 250oC with 50 sccm Ar gas using an RF magnetron sputtering system. The crystal structure of the thin film is found to be zinc blende (cubic) structure. Lattice parameter of ZnS is slightly larger than CdS on the plane and thus better matched with that of CIGS. Within a 400-800 nm wavelength region, the average transmittance was larger than 75%. When the deposition temperature of the thin film was increased, the blue shift phenomenon was enhanced. Band gap energy of the ZnS thin film tended to increase as the deposition temperature increased. ZnS thin film is a promising material system for the CIGS buffer layer, in terms of ease of processing, low cost, environmental friendliness, higher transparency, and electrical properties

Keywords: ZnS thin film, Buffer layer, CIGS, Solar cell.

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Authors: D. Bheenick, M. Young, M. Elmussareh, A. Ali

Abstract:

Coronavirus disease 2019 (COVID-19) has had unprecedented effects on the healthcare system in the UK. The pandemic has impacted every service within secondary care, including urology. Our objective is to determine how COVID-19 has influenced acute urology admissions in a busy district general hospital in the UK. To conduct the study, retrospective data of patients presenting acutely to the urology department were collected between January 13 to March 22, 2020 (pre-lockdown period) and March 23 to May 31, 2020 (lockdown period). The nature of referrals, types of admission encountered, and management required in accordance with the new set of protocols established during the lockdown period were analysed and compared to the same data prior to UK lockdown. Included in the study were 1092 patients. The results show that an overall reduction of 32.5% was seen in the total number of admissions. A marked decrease was seen in non-urological pathology as compared to other categories. Urolithiasis showed the highest proportional increase. Treatment varied proportionately to the diagnosis, with conservative management accounting for the most likely treatment during lockdown. However, the proportion of patients requiring interventions during the lockdown period increased overall. No comparative differences were observed during the two periods in terms of source of referral, length of stay and patient age. The results of the study concluded that the admission rate showed a decrease, with no significant difference in the nature and timing of presentation. Our department was able to continue providing effective management to patients presenting acutely during the COVID-19 outbreak.

Keywords: COVID-19, lockdown, admissions, urology

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Authors: Charawee Butbumrung

Abstract:

The purpose of this research was to study customer relationship management on social media affecting brand loyalty of Siam Commercial Bank in Bangkok. The statistics used in data analysis were frequency, mean, standard deviation, and Pearson’s correlation coefficient based on social science statistic program. The result of the study found that the majority of the respondents were female, 37–47 years old of age, bachelor degree of education and monthly income between 10,001 and 15,000 Baht. In addition, customer relationship management in the overall and by each aspect of formulating, maintaining, and extending the customer relationship had a high score. Furthermore, the result of hypothesis testing showed that the difference of the customer’s age, education, occupation, average monthly income had the difference in brand loyalty with the statistical significance level of 0.05 and customer relationship management had related with brand loyalty in the same direction with the low level of statistical significance 0.05.

Keywords: Brand loyalty, customer relationship, management, Siam Commercial Bank, social media.

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Authors: Muhammad Rizwan Azhar, Emadadeen Ali

Abstract:

In this paper, periodic force operation of a wastewater treatment process has been studied for the improved process performance. A previously developed dynamic model for the process is used to conduct the performance analysis. The static version of the model was utilized first to determine the optimal productivity conditions for the process. Then, feed flow rate in terms of dilution rate i.e. (D) is transformed into sinusoidal function. Nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal function. The parameters of the feed cyclic functions are determined which resulted in improved productivity than the optimal productivity under steady state conditions. The improvement in productivity is found to be marginal and is satisfactory in substrate conversion compared to that of the optimal condition and to the steady state condition, which corresponds to the average value of the periodic function. Successful results were also obtained in the presence of modeling errors and external disturbances.

Keywords: Dilution rate, nonlinear model predictive control, sinusoidal function, wastewater treatment.

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Authors: S. Khamtree, T. Ratanawilai, C. Nuntadusit

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Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 °C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (R²), Root Mean Square Error (RMSE) and Chi-square (χ²) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (R² = 0.9963) for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments.

Keywords: Empirical models, hot air, moisture ratio, rubberwood.

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Authors: Ab. Rashid M.F.F., Gan S.Y., Muhammad N.Y.

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Surface roughness (Ra) is one of the most important requirements in machining process. In order to obtain better surface roughness, the proper setting of cutting parameters is crucial before the process take place. This research presents the development of mathematical model for surface roughness prediction before milling process in order to evaluate the fitness of machining parameters; spindle speed, feed rate and depth of cut. 84 samples were run in this study by using FANUC CNC Milling α-Τ14ιE. Those samples were randomly divided into two data sets- the training sets (m=60) and testing sets(m=24). ANOVA analysis showed that at least one of the population regression coefficients was not zero. Multiple Regression Method was used to determine the correlation between a criterion variable and a combination of predictor variables. It was established that the surface roughness is most influenced by the feed rate. By using Multiple Regression Method equation, the average percentage deviation of the testing set was 9.8% and 9.7% for training data set. This showed that the statistical model could predict the surface roughness with about 90.2% accuracy of the testing data set and 90.3% accuracy of the training data set.

Keywords: Surface roughness, regression analysis.

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Authors: K. Ramash Kumar, S. Jeevananthan

Abstract:

The Object of this paper is to design and analyze a Hysteresis modulation based sliding mode control (HMSMC) for positive output elementary super lift Luo converter (POESLLC), which is the start-of-the-art DC-DC converter. The positive output elementary super lift Luo converter performs the voltage conversion from positive source voltage to positive load voltage. This paper proposes a HMSMC capable of providing the good steady state and dynamic performance compared to conventional controllers. Dynamic equations describing the positive output elementary super lift luo converter are derived by using state space average method. The simulation model of the positive output elementary super lift Luo converter with its control circuit is implemented in Matlab/Simulink. The HMSMC for positive output elementary super lift Luo converter is tested for line changes, load changes and also for components variations.

Keywords: DC-DC converter, Positive output elementarysuper lift Luo converter (POESLLC), Hysteresis modulation basedsliding mode control (HMSMC).

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Authors: M. Tamilarasi, T.G. Palanivelu

Abstract:

Mobile Ad Hoc Networks (MANETs) are multi-hop wireless networks in which all nodes cooperatively maintain network connectivity. In such a multi-hop wireless network, every node may be required to perform routing in order to achieve end-to-end communication among nodes. These networks are energy constrained as most ad hoc mobile nodes today operate with limited battery power. Hence, it is important to minimize the energy consumption of the entire network in order to maximize the lifetime of ad hoc networks. In this paper, a mechanism involving the integration of load balancing approach and transmission power control approach is introduced to maximize the life-span of MANETs. The mechanism is applied on Ad hoc On-demand Vector (AODV) protocol to make it as energy aware AODV (EA_AODV). The simulation is carried out using GloMoSim2.03 simulator. The results show that the proposed mechanism reduces the average required transmission energy per packet compared to the standard AODV.

Keywords: energy aware routing, load balance, Mobile Ad HocNetworks, MANETs , on demand routing, transmission power control.

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Authors: B. J. C. Perera, D. A. Sachindra, W. Godoy., A.F. Barton, F. Huang

Abstract:

Many water supply systems in Australia are currently undergoing significant reconfiguration due to reductions in long term average rainfall and resulting low inflows to water supply reservoirs since the second half of the 20th century. When water supply systems undergo change, it is necessary to develop new operating rules, which should consider climate, because the climate change is likely to further reduce inflows. In addition, water resource systems are increasingly intended to be operated to meet complex and multiple objectives representing social, economic, environmental and sustainability criteria. This is further complicated by conflicting preferences on these objectives from diverse stakeholders. This paper describes a methodology to develop optimum operating rules for complex multi-reservoir systems undergoing significant change, considering all of the above issues. The methodology is demonstrated using the Grampians water supply system in northwest Victoria, Australia. Initial work conducted on the project is also presented in this paper.

Keywords: Climate change, Multi-objective planning, Pareto optimal; Stakeholder preference, Statistical downscaling, Water supply systems.

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Authors: U. Amin, A. Talib, S. A. Qureshi, M. J. Hossain, G. Ahmad

Abstract:

The choice evaluation between oil-immersed and dry-type transformers is often controlled by cost, location, and application. This paper compares the electrical performance of liquid- filled and dry-type transformers, which will assist the customer to choose the right and efficient ones for particular applications. An accurate assessment of the time-average flux density, electric field intensity and voltage distribution in an oil-insulated and a dry-type transformer have been computed and investigated. The detailed transformer modeling and analysis has been carried out to determine electrical parameter distributions. The models of oil-immersed and dry-type transformers are developed and solved by using the finite element method (FEM) to compare the electrical parameters. The effects of non-uniform and non-coherent voltage gradient, flux density and electric field distribution on the power losses and insulation properties of transformers are studied in detail. The results show that, for the same voltage and kilo-volt-ampere (kVA) rating, oil-immersed transformers have better insulation properties and less hysteresis losses than the dry-type.

Keywords: Finite element method, flux density, transformer, voltage gradient.

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Authors: Quanru Pan

Abstract:

How to maintain the service speeds for the business to make the biggest profit is a problem worthy of study, which is discussed in this paper with the use of queuing theory. An M/M/1/N queuing model with variable input rates, variable service rates and impatient customers is established, and the following conclusions are drawn: the stationary distribution of the model, the relationship between the stationary distribution and the probability that there are n customers left in the system when a customer leaves (not including the customer who leaves himself), the busy period of the system, the average operating cycle, the loss probability for the customers not entering the system while they arriving at the system, the mean of the customers who leaves the system being for impatient, the loss probability for the customers not joining the queue due to the limited capacity of the system and many other indicators. This paper also indicates that the following conclusion is not correct: the more customers the business serve, the more profit they will get. At last, this paper points out the appropriate service speeds the business should keep to make the biggest profit.

Keywords: variable input rates, impatient customer, variable servicerates, profit maximization.

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Authors: A. Umemuro, M. Sato, M. Narita, S. Hori, S. Sakurai, T. Nakayama, A. Nakazawa, T. Ogura

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Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.

Keywords: EEG scanner, eye-detector, mammography, observers.

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Authors: Long Van Hoang, Mitsuyasu Yabe

Abstract:

Environmental factors affect agriculture production productivity and efficiency resulted in changing of profit efficiency. This paper attempts to estimate the impacts of environmental factors to profitability of rice farmers in the Red River Delta of Vietnam. The dataset was extracted from 349 rice farmers using personal interviews. Both OLS and MLE trans-log profit functions were used in this study. Five production inputs and four environmental factors were included in these functions. The estimation of the stochastic profit frontier with a two-stage approach was used to measure profitability. The results showed that the profit efficiency was about 75% on the average and environmental factors change profit efficiency significantly beside farm specific characteristics. Plant disease, soil fertility, irrigation apply and water pollution were the four environmental factors cause profit loss in rice production. The result indicated that farmers should reduce household size, farm plots, apply row seeding technique and improve environmental factors to obtain high profit efficiency with special consideration is given for irrigation water quality improvement.

Keywords: Profit efficiency; Profit function; Environmental factors; OLS and MLE estimations; Rice Production; Vietnam

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Authors: Yu-Jen Chang, Yun Chen, Hei-Lam Wong

Abstract:

The Economic Lot Scheduling Problem (ELSP) is a valuable mathematical model that can support decision-makers to make scheduling decisions. The basic period approach is effective for solving the ELSP. The assumption for applying the basic period approach is that a product must use its maximum production rate to be produced. However, a product can lower its production rate to reduce the average total cost when a facility has extra idle time. The past researches discussed how a product adjusts its production rate under the common cycle approach. To the best of our knowledge, no studies have addressed how a product lowers its production rate under the basic period approach. This research is the first paper to discuss this topic. The research develops a simple fixed rate approach that adjusts the production rate of a product under the basic period approach to solve the ELSP. Our numerical example shows our approach can find a better solution than the traditional basic period approach. Our mathematical model that applies the fixed rate approach under the basic period approach can serve as a reference for other related researches.

Keywords: Economic Lot, Basic Period, Genetic Algorithm, Fixed Rate.

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Authors: El-Sayed Atlam, Masao Fuketa, Kazuhiro Morita, Jun-ichi Aoe

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Field Association (FA) terms are a limited set of discriminating terms that give us the knowledge to identify document fields which are effective in document classification, similar file retrieval and passage retrieval. But the problem lies in the lack of an effective method to extract automatically relevant Arabic FA Terms to build a comprehensive dictionary. Moreover, all previous studies are based on FA terms in English and Japanese, and the extension of FA terms to other language such Arabic could be definitely strengthen further researches. This paper presents a new method to extract, Arabic FA Terms from domain-specific corpora using part-of-speech (POS) pattern rules and corpora comparison. Experimental evaluation is carried out for 14 different fields using 251 MB of domain-specific corpora obtained from Arabic Wikipedia dumps and Alhyah news selected average of 2,825 FA Terms (single and compound) per field. From the experimental results, recall and precision are 84% and 79% respectively. Therefore, this method selects higher number of relevant Arabic FA Terms at high precision and recall.

Keywords: Arabic Field Association Terms, information extraction, document classification, information retrieval.

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Authors: Yin Yin Phyo, Tun Lin Naing

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This paper investigated the simulation of two-phase interleaved boost converter (IBC) with free and open-source software Scilab/Xcos. By using interleaved method, it can reduce current stress on components, components size, input current ripple and output voltage ripple. The required mathematical model is obtained from the equivalent circuit of its different four modes of operation for simulation. The equivalent circuits are considered in continuous conduction mode (CCM). The average values of the system variables are derived from the state-space equation to find the equilibrium point. Scilab is now becoming more and more popular among students, engineers and scientists because it is open-source software and free of charge. It gives a great convenience because it has powerful computation and simulation function. The waveforms of output voltage, input current and inductors current are obtained by using Scilab/Xcos.

Keywords: Two-phase boost converter, continuous conduction mode, free and open-source, interleaved method, dynamic simulation.

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Authors: Mohammad Hosein Hojati, Fardin Boustani

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Groundwater is one of the most important water resources in Fars province. Based on this study, 95 percent of the total annual water consumption in Fars is used for agriculture, whereas the percentages for domestic and industrial uses are 4 and 1 percent, respectively. Population growth, urban and industrial growth, and agricultural development in Fars have created a condition of water stress. In this province, farmers and other users are pumping groundwater faster than its natural replenishment rate, causing a continuous drop in groundwater tables and depletion of this resource. In this research variation of groundwater level, their effects and ways to help control groundwater levels in aquifer of the Kavar- Maharloo plains in Fars plain were evaluated .Excessive exploitation of groundwater in this aquifer caused the groundwater levels fall too fast or to unacceptable levels. The average drawdown of the groundwater level in this plain were 17 meters during 1995 to 2006. The purpose of this study is to evaluate water level changes in the Kavar-Maharloo Aquifer in the Fars province in order to determine the areas of greatest depletion, the cause of depletion, and predict the remaining life of the aquifer.

Keywords: Aquifer , ground water depletion, water table

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Authors: M. Yousaf, S. Usman

Abstract:

Numerical studies were conducted using Lattice Boltzmann Method (LBM) to study the natural convection in a square cavity in the presence of roughness. An algorithm based on a single relaxation time Bhatnagar-Gross-Krook (BGK) model of Lattice Boltzmann Method (LBM) was developed. Roughness was introduced on both the hot and cold walls in the form of sinusoidal roughness elements. The study was conducted for a Newtonian fluid of Prandtl number (Pr) 1.0. The range of Ra number was explored from 10^3 to 10^6 in a laminar region. Thermal and hydrodynamic behavior of fluid was analyzed using a differentially heated square cavity with roughness elements present on both the hot and cold wall. Neumann boundary conditions were introduced on horizontal walls with vertical walls as isothermal. The roughness elements were at the same boundary condition as corresponding walls. Computational algorithm was validated against previous benchmark studies performed with different numerical methods, and a good agreement was found to exist. Results indicate that the maximum reduction in the average heat transfer was 16.66 percent at Ra number 10^5.

Keywords: Lattice Boltzmann Method Natural convection, Nusselt Number Rayleigh number, Roughness.

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Authors: Fatemeh Mosalman Yazdi

Abstract:

One of the most important requirements for the operation and planning activities of an electrical utility is the prediction of load for the next hour to several days out, known as short term load forecasting. This paper presents the development of an artificial neural network based short-term load forecasting model. The model can forecast daily load profiles with a load time of one day for next 24 hours. In this method can divide days of year with using average temperature. Groups make according linearity rate of curve. Ultimate forecast for each group obtain with considering weekday and weekend. This paper investigates effects of temperature and humidity on consuming curve. For forecasting load curve of holidays at first forecast pick and valley and then the neural network forecast is re-shaped with the new data. The ANN-based load models are trained using hourly historical. Load data and daily historical max/min temperature and humidity data. The results of testing the system on data from Yazd utility are reported.

Keywords: Artificial neural network, Holiday forecasting, pickand valley load forecasting, Short-term load-forecasting.

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Authors: Rafsan Al Mamun, Md. Motaharul Islam, Rabana Tajrin, Nabiha Noor, Shafinaz Qader

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In an attempt to enrich the lives of billions of people by providing proper information, security and a way of communicating with others, the need for efficient and improved satellites is constantly growing. Thus, there is an increasing demand for better error detection and correction (EDAC) schemes, which are capable of protecting the data onboard the satellites. The paper is aimed towards detecting and correcting such errors using a special algorithm called the Hamming Code, which uses the concept of parity and parity bits to prevent single-bit errors onboard a satellite in Low Earth Orbit. This paper focuses on the study of Low Earth Orbit satellites and the process of generating the Hamming Code matrix to be used for EDAC using computer programs. The most effective version of Hamming Code generated was the Hamming (16, 11, 4) version using MATLAB, and the paper compares this particular scheme with other EDAC mechanisms, including other versions of Hamming Codes and Cyclic Redundancy Check (CRC), and the limitations of this scheme. This particular version of the Hamming Code guarantees single-bit error corrections as well as double-bit error detections. Furthermore, this version of Hamming Code has proved to be fast with a checking time of 5.669 nanoseconds, that has a relatively higher code rate and lower bit overhead compared to the other versions and can detect a greater percentage of errors per length of code than other EDAC schemes with similar capabilities. In conclusion, with the proper implementation of the system, it is quite possible to ensure a relatively uncorrupted satellite storage system.

Keywords: Bit-flips, Hamming code, low earth orbit, parity bits, satellite, single error upset.

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Authors: Seyed Sina Khamesi, Rana Rafiei

Abstract:

The extensive aeration process is widely used for wastewater treatment. However, due to the high energy consumption of this process, which is closely related to the issues of environmental sustainability and global climate change, this article presents a simple solution to reduce energy consumption in this process. The amount of required energy is one of the critical considerations for various wastewater treatment techniques. For this purpose, an industrial wastewater treatment plant and all energy-consumer equipment in terms of energy consumption have been analyzed. The investigations and measurements revealed that the aeration unit has the highest energy consumption rate. To address this, an innovative approach is proposed to reduce energy consumption in the identified high-consumer unit. The proposed solution involves introducing baffles to divide the tank into multiple parts and using a tank with a small width and long length to enhance the mixing process. This approach reduces the need for additional equipment and significantly lowers energy consumption. To thoroughly scrutinize the proposed solution and analyze the behavior of the multi-phase fluid inside the tank, the sewage flow has been modeled using the computational fluid dynamics (CFD) method. The study presents an optimal design for the aeration unit based on these findings. The results indicate that implementing the technique suggested in this article can decrease total energy consumption by 33.15% and can be applied to all types of biological treatment plants.

Keywords: Wastewater treatment, aeration, energy consumption, Computational Fluid Dynamics, activated sludge.

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Authors: S. Gharbi, S. Labidi, M. Mars, M. Chelli, F. Ladeb

Abstract:

The purpose of this study is to reduce radiation dose for chest CT examination by including Tube Current Modulation (TCM) to a standard CT protocol. A scan of an anthropomorphic male Alderson phantom was performed on a 128-slice scanner. The estimation of effective dose (ED) in both scans with and without mAs modulation was done via multiplication of Dose Length Product (DLP) to a conversion factor. Results were compared to those measured with a CT-Expo software. The size specific dose estimation (SSDE) values were obtained by multiplication of the volume CT dose index (CTDIvol) with a conversion size factor related to the phantom’s effective diameter. Objective assessment of image quality was performed with Signal to Noise Ratio (SNR) measurements in phantom. SPSS software was used for data analysis. Results showed including CARE Dose 4D; ED was lowered by 48.35% and 51.51% using DLP and CT-expo, respectively. In addition, ED ranges between 7.01 mSv and 6.6 mSv in case of standard protocol, while it ranges between 3.62 mSv and 3.2 mSv with TCM. Similar results are found for SSDE; dose was higher without TCM of 16.25 mGy and was lower by 48.8% including TCM. The SNR values calculated were significantly different (p=0.03<0.05). The highest one is measured on images acquired with TCM and reconstructed with Filtered back projection (FBP). In conclusion, this study proves the potential of TCM technique in SSDE and ED reduction and in conserving image quality with high diagnostic reference level for thoracic CT examinations.

Keywords: Anthropomorphic phantom, computed tomography, CT-expo, radiation dose.

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Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: Cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis.

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Authors: Ashwani K. Rana, Narottam Chand, Vinod Kapoor

Abstract:

Aggressive scaling of MOS devices requires use of ultra-thin gate oxides to maintain a reasonable short channel effect and to take the advantage of higher density, high speed, lower cost etc. Such thin oxides give rise to high electric fields, resulting in considerable gate tunneling current through gate oxide in nano regime. Consequently, accurate analysis of gate tunneling current is very important especially in context of low power application. In this paper, a simple and efficient analytical model has been developed for channel and source/drain overlap region gate tunneling current through ultra thin gate oxide n-channel MOSFET with inevitable deep submicron effect (DSME).The results obtained have been verified with simulated and reported experimental results for the purpose of validation. It is shown that the calculated tunnel current is well fitted to the measured one over the entire oxide thickness range. The proposed model is suitable enough to be used in circuit simulator due to its simplicity. It is observed that neglecting deep sub-micron effect may lead to large error in the calculated gate tunneling current. It is found that temperature has almost negligible effect on gate tunneling current. It is also reported that gate tunneling current reduces with the increase of gate oxide thickness. The impact of source/drain overlap length is also assessed on gate tunneling current.

Keywords: Gate tunneling current, analytical model, gate dielectrics, non uniform poly gate doping, MOSFET, fringing field effect and image charges.

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Authors: M. Hosseinnezhad, K. Gharanjig

Abstract:

Natural dyes, extracted from black carrot and bramble, were utilized as photosensitizers to prepare dye-sensitized solar cells (DSSCs). Spectrophotometric studies of the natural dyes in solution and on a titanium dioxide substrate were carried out in order to assess changes in the status of the dyes. The results show that the bathochromic shift is seen on the photo-electrode substrate. The chemical binding of the natural dyes at the surface photo-electrode were increased by the chelating effect of the Ti(IV) ions. The cyclic voltammetry results showed that all extracts are suitable to be performed in DSSCs. Finally, photochemical performance and stability of DSSCs based on natural dyes were studied. The DSSCs sensitized by black carrot extract have been reported to achieve up to Jsc=1.17 mAcm^-2, Voc= 0.55 V, FF= 0.52, η=0.34%, whereas Bramble extract can obtain up to Jsc=2.24 mAcm^-2, Voc= 0.54 V, FF= 0.57, η=0.71%. The power conversion efficiency was obtained from the mixed dyes in DSSCs. The power conversion efficiency of dye-sensitized solar cells using mixed Black carrot and Bramble dye is the average of the their efficiency in single DSSCs.

Keywords: Anthocyanin, dye-sensitized solar cells, green energy, optical materials.

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Authors: Maryam Hsaini, Mostafa Nouri-Baygi

Abstract:

A critical problem in wireless sensor networks is limited battery and memory of nodes. Therefore, each node in the network could maintain only a subset of its neighbors to communicate with. This will increase the battery usage in the network because each packet should take more hops to reach its destination. In order to tackle these problems, spanner graphs are defined. Since each node has a small degree in a spanner graph and the distance in the graph is not much greater than its actual geographical distance, spanner graphs are suitable candidates to be used for the topology of a wireless sensor network. In this paper, we study Yao graphs and their behavior for a randomly selected set of points. We generate several random point sets and compare the properties of their Yao graphs with the complete graph. Based on our data sets, we obtain several charts demonstrating how Yao graphs behave for a set of randomly chosen point set. As the results show, the stretch factor of a Yao graph follows a normal distribution. Furthermore, the stretch factor is in average far less than the worst case stretch factor proved for Yao graphs in previous results. Furthermore, we use Yao graph for a realistic point set and study its stretch factor in real world.

Keywords: Wireless sensor network, spanner graph, Yao Graph.

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Authors: José M. Merigó, Pilar López-Jurado, M.Carmen Gracia, Montserrat Casanovas

Abstract:

We present a method for the selection of students in interdisciplinary studies based on the hybrid averaging operator. We assume that the available information given in the problem is uncertain so it is necessary to use interval numbers. Therefore, we suggest a new type of hybrid aggregation called uncertain induced generalized hybrid averaging (UIGHA) operator. It is an aggregation operator that considers the weighted average (WA) and the ordered weighted averaging (OWA) operator in the same formulation. Therefore, we are able to consider the degree of optimism of the decision maker and grades of importance in the same approach. By using interval numbers, we are able to represent the information considering the best and worst possible results so the decision maker gets a more complete view of the decision problem. We develop an illustrative example of the proposed scheme in the selection of students in interdisciplinary studies. We see that with the use of the UIGHA operator we get a more complete representation of the selection problem. Then, the decision maker is able to consider a wide range of alternatives depending on his interests. We also show other potential applications that could be used by using the UIGHA operator in educational problems about selection of different types of resources such as students, professors, etc.

Keywords: Decision making, Selection of students, Uncertainty, Aggregation operators.

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

Abstract:

Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean   Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: Air quality prediction, deep learning algorithms, time series forecasting, look-back window.

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