Search results for: bit error rate

Authors: Leila Vafajoo, Farhad Khorasheh, Mehrnoosh Hamzezadeh Nakhjavani, Moslem Fattahi

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In the present study, a procedure was developed to determine the optimum reaction rate constants in generalized Arrhenius form and optimized through the Nelder-Mead method. For this purpose, a comprehensive mathematical model of a fixed bed reactor for dehydrogenation of heavy paraffins over Pt–Sn/Al2O3 catalyst was developed. Utilizing appropriate kinetic rate expressions for the main dehydrogenation reaction as well as side reactions and catalyst deactivation, a detailed model for the radial flow reactor was obtained. The reactor model composed of a set of partial differential equations (PDE), ordinary differential equations (ODE) as well as algebraic equations all of which were solved numerically to determine variations in components- concentrations in term of mole percents as a function of time and reactor radius. It was demonstrated that most significant variations observed at the entrance of the bed and the initial olefin production obtained was rather high. The aforementioned method utilized a direct-search optimization algorithm along with the numerical solution of the governing differential equations. The usefulness and validity of the method was demonstrated by comparing the predicted values of the kinetic constants using the proposed method with a series of experimental values reported in the literature for different systems.

Keywords: Dehydrogenation, Pt-Sn/Al2O3 Catalyst, Modeling, Nelder-Mead, Optimization

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Authors: Kenneth M. Oba

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This study investigated factors affecting the price of cement in Nigeria, and developed a mathematical model that can predict future cement prices. Cement is key in the Nigerian construction industry. The changes in price caused by certain factors could affect economic and infrastructural development; hence there is need for proper proactive planning. Secondary data were collected from published information on cement between 2014 and 2019. In addition, questionnaires were sent to some domestic cement retailers in Port Harcourt in Nigeria, to obtain the actual prices of cement between the same periods. The study revealed that the most critical factors affecting the price of cement in Nigeria are inflation rate, population growth rate, and Gross Domestic Product (GDP) growth rate. With the use of data from United Nations, International Monetary Fund, and Central Bank of Nigeria databases, amongst others, a Multiple Linear Regression model was formulated. The model was used to predict the price of cement for 2020-2025. The model was then tested with 95% confidence level, using a two-tailed t-test and an F-test, resulting in an R² of 0.8428 and R² (adj.) of 0.6069. The results of the tests and the correlation factors confirm the model to be fit and adequate. This study will equip researchers and stakeholders in the construction industry with information for planning, monitoring, and management of present and future construction projects that involve the use of cement.

Keywords: Cement price, multiple linear regression model, Nigerian Construction Industry, price prediction.

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Authors: Kongsheng Zhang, Li Ge

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It is a one-sided hypothesis testing process for assessing bioequivalence. Bootstrap and modified large-sample(MLS) methods are considered to study individual bioequivalence(IBE), type I error and power of hypothesis tests are simulated and compared with FDA(2001). The results show that modified large-sample method is equivalent to the method of FDA(2001) .

Keywords: Individual bioequivalence, bootstrap, Bayesian bootstrap, modified large-sample.

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Authors: Qiangqiang Xu, Xu Ji, Jingyang Han, Changchun Yang, Ming Li

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Replacing of complex solar concentrating unit, this paper designs a solar heat-concentrating medium-temperature steam-generating system. Solar radiation is collected by using a large solar collecting and heat concentrating plate and is converged to the metal evaporating pipe with high efficient heat transfer. In the meantime, the heat loss is reduced by employing a double-glazed cover and other heat insulating structures. Thus, a high temperature is reached in the metal evaporating pipe. The influences of the system's structure parameters on system performance are analyzed. The steam production rate and the steam production under different solar irradiance, solar collecting and heat concentrating plate area, solar collecting and heat concentrating plate temperature and heat loss are obtained. The results show that when solar irradiance is higher than 600 W/m², the effective heat collecting area is 7.6 m² and the double-glazing cover is adopted, the system heat loss amount is lower than the solar irradiance value. The stable steam is produced in the metal evaporating pipe at 100 ℃, 110 ℃, and 120 ℃, respectively. When the average solar irradiance is about 896 W/m², and the steaming cumulative time is about 5 hours, the daily steam production of the system is about 6.174 kg. In a single day, the solar irradiance is larger at noon, thus the steam production rate is large at that time. Before 9:00 and after 16:00, the solar irradiance is smaller, and the steam production rate is almost 0.

Keywords: Heat concentrating, heat loss, medium temperature, solar steam production.

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Authors: Min-Chuan Huang, I-Ping Chen, Shu-Ying Chung

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Taking the medical staff in an emergency ward of a medical center in Central Taiwan as the research object, the questionnaire data were collected by anonymous and voluntary reporting methods with structured questionnaires to explore organ donation’s actual situation, willingness, and attitude. Only 80 valid questionnaires were gathered. Of the 8 questions, the correct mean rate was 5.9 and the correct rate was 73.13%. According to the statistics of organ donation survey, only 8.7% have signed the consent for organ donation, 21.3% are willing but have not yet signed the consent for organ donation, 62.5% have not yet decided, and 7.5% are unwilling. The average total score (standard deviation) of attitude towards organ donation was 36.2. There is no significant difference between the demographic variables and the awareness and willingness of organ donation, but there is a significant correlation between marital status and the attitude toward organ donation.

Keywords: clinical psychology, organ donation, factors affecting psychological disorders, commitment

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Authors: Rajaram Kr. Gupta, Bhupendra Kumar, T. V. K. Gupta, D. S. Ramteke

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Machining of hard materials is a recent technology for direct production of work-pieces. The primary challenge in machining these materials is selection of cutting tool inserts which facilitates an extended tool life and high-precision machining of the component. These materials are widely for making precision parts for the aerospace industry. Nickel-based alloys are typically used in extreme environment applications where a combination of strength, corrosion resistance and oxidation resistance material characteristics are required. The present paper reports the theoretical and experimental investigations carried out to understand the influence of machining parameters on the response parameters. Considering the basic machining parameters (speed, feed and depth of cut) a study has been conducted to observe their influence on material removal rate, surface roughness, cutting forces and corresponding tool wear. Experiments are designed and conducted with the help of Central Composite Rotatable Design technique. The results reveals that for a given range of process parameters, material removal rate is favorable for higher depths of cut and low feed rate for cutting forces. Low feed rates and high values of rotational speeds are suitable for better finish and higher tool life.

Keywords: Speed, feed, depth of cut, roughness, cutting force, flank wear.

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Authors: A.R. Ismail, M. R. A. Rani, Z. K. M. Makhbul, M. J. M. Nor, M. N. A. Rahman

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The environmental factors such as temperature and relative humidity are very contribute to the effect of comfort, health, performance and worker productivity. To ensure an ergonomics work environment, it is possible to require a specific attention especially in industries. The aim of this study is to show the effect of temperature and relative humidity on worker productivity in automotive industry by taking a workstation in an automotive plant as the location to conduct the study. From the analysis of the data, there were relationship between temperature and relative humidity on worker productivity. Mathematical equation to represent the relationship between temperatures and relative humidity on the production rate is modelled. From the equation model, the production rate for the workstation can be predicted base on the value of temperature and relative humidity.

Keywords: WBGT, Relative Humidity, Comfort, Productivity.

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Authors: Hai Huu Le, Paul Junor, Moshi Geso, Graeme O’Keefe

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In this paper, the authors propose a personal wearable directionally-sensitive radiation dosimeter using multiple semiconductor CdZnTe detectors. The proposed dosimeter not only measures the real-time dose rate but also provide the direction of the radioactive source. A linear relationship between radioactive source direction and the radiation intensity measured by each detectors is established and an equation to determine the source direction is derived by the authors. The efficiency and accuracy of the proposed dosimeter is verified by simulation using Geant4 package. Results have indicated that in a measurement duration of about 7 seconds, the proposed dosimeter was able to estimate the direction of a 10μCi 137/55Cs radioactive source to within 2 degrees.

Keywords: Dose rate, Geant4 package, radiation detectors, radioactive source direction.

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Authors: Seok Hyoung Lee, Vladimir Shin

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An optimal mean-square fusion formulas with scalar and matrix weights are presented. The relationship between them is established. The fusion formulas are compared on the continuous-time filtering problem. The basic differential equation for cross-covariance of the local errors being the key quantity for distributed fusion is derived. It is shown that the fusion filters are effective for multi-sensor systems containing different types of sensors. An example demonstrating the reasonable good accuracy of the proposed filters is given.

Keywords: Kalman filtering, fusion formula, multi-sensor, mean-square error.

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Authors: Sh. Khalilarya, S. Jafarmadar, H. Khatamnezhad, Gh. Javadirad, M. Pourfallah

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One promising way to achieve low temperature combustion regime is the use of a large amount of cooled EGR. In this paper, the effect of injection timing on low temperature combustion process and emissions were investigated via three dimensional computational fluid dynamics (CFD) procedures in a DI diesel engine using high EGR rates. The results show when increasing EGR from low levels to levels corresponding to reduced temperature combustion, soot emission after first increasing, is decreased beyond 40% EGR and get the lowest value at 58% EGR rate. Soot and NOx emissions are simultaneously decreased at advanced injection timing before 20.5 ºCA BTDC in conjunction with 58% cooled EGR rate in compared to baseline case.

Keywords: Diesel Engine, Low Temperature Combustion, High Cooled EGR Rates, Combustion, Emissions

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Authors: Snežana T. Tanasković, Sonja M. Gvozdenac, Branka D. Popović, Vesna M. Đurović, Matthias Erb

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Western corn rootworm – WCR (Diabrotica virgifera sp.virgifera, Coleoptera, Chrysomelidae) is economically the most important pest of maize worldwide. WCR natural population is already very abundant on Serbian fields, and keeps increasing each year. Tolerance is recognized by larger root size and bigger root regrowth. Severe larval injuries cause lack of compensatory regrowth and lead to reduction of plant growth and yield. The aim of this research was to evaluate tolerance of commercial Serbian maize hybrid NS 640, under natural WCR infestation and under conditions of artificial infestation, and to obtain the information about its tolerance to WCR larval feeding in two consecutive years. Field experiments were conducted in 2015 and 2016, in Bečej (Vojvodina province, Serbia). In experimental field, 96 plants were selected, marked and arranged in 48 pairs. Each pair represented two plants. The first plant was artificially infested with 4 mL WCR egg suspension in agar (550 eggs plant^-1) in the root zone (D plant). The second plant represented control plant (C plant) with injection of 4 mL distilled water in root zone. The experimental field was inspected weekly. A hybrid tolerance was assessed based on root injury level and root mass. Root injury was rated using the Node-Injury Scale 1-6, during the last field inspection (September – October). Comparing the root injuries on D and C plants in 2015, more severe damages were recorded on D plants (12 plants - rate 5 and 17 plants - rate 6) compared to C plants (2 plants - rate 5 and 8 plants - rate 6). Also, the highest number of plants with healthy roots (rate 1), was registered in the control (25 plants), while only 4 D plants were rated as injury level 1. In 2016, root injuries caused by WCR larvae on D and C plants did not differ significantly. The reason is the difference in climatic conditions between the years. The 2015 was extremely dry and more suitable for WCR larval development and movement in the soil, compared to 2016. Thus, more severe damages appeared on artificially infested plants (D plants). Root mass was in strong correlation with the level of root injury, but did not differ significantly between D and C plants, in both years.

Keywords: D. v. virgifera, maize, root injury, tolerance.

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Authors: Jianhua Wang, Yan Yu

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This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid model intrusion detection system uses DARPA data set to do test evaluation. It uses ROC curve to display the test result intuitively. After the experiment it proves this hybrid model intrusion detection system can effectively improve the detection rate, and reduce the rate of false alarm and fail.

Keywords: RBF, Elman, anomaly detection, misuse detection, hybrid neural network.

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Authors: Lakshman Singh, Rajeshwar Singh, Naveen Kumar Singh, Davinder Singh, Pargat Singh

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Tungsten Inert Gas (TIG) welding is a high quality welding process used to weld the thin metals and their alloy. 5083 Aluminium alloys play an important role in engineering and metallurgy field because of excellent corrosion properties, ease of fabrication and high specific strength coupled with best combination of toughness and formability.

TIG welding technique is one of the precise and fastest processes used in aerospace, ship and marine industries. TIG welding process is used to analyze the data and evaluate the influence of input parameters on tensile strength of 5083 Al-alloy specimens with dimensions of 100mm long x 15mm wide x 5mm thick. Welding current (I), gas flow rate (G) and welding speed (S) are the input parameters which effect tensile strength of 5083 Al-alloy welded joints. As welding speed increased, tensile strength increases first till optimum value and after that both decreases by increasing welding speed further. Results of the study show that maximum tensile strength of 129 MPa of weld joint are obtained at welding current of 240 Amps, gas flow rate of 7 Lt/min and welding speed of 98 mm/min. These values are the optimum values of input parameters which help to produce efficient weld joint that have good mechanical properties as a tensile strength.

Keywords: 5083 Aluminium alloy, Gas flow rate, TIG welding, Welding current, Welding speed and Tensile strength.

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Authors: Shinji Kajiwara

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The spring-driven ball-type check valve is one of the most important components of hydraulic systems: it controls the position of the ball and prevents backward flow. To simplify the structure, the spring must be eliminated, and to accomplish this, the flow pattern and the behavior of the check ball in L-shaped pipe must be determined. In this paper, we present a full-scale model of a check ball made of acrylic resin, and we determine the relationship between the initial position of the ball, the position and diameter of the inflow port. The check flow rate increases in a standard center inflow model, and it is possible to greatly decrease the check-flow rate by shifting the inflow from the center.

Keywords: Hydraulics, Pipe Flow, Numerical Simulation, Flow Visualization, Check ball, L-shaped Pipe.

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Authors: S. A. Kondratyev, O. I. Ibragimova

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The authors discuss the collecting abilities of desorbable species (DS) of saturated fatty acids. The DS species of the reagent are understood as species capable of moving from the surface of the mineral particle to the bubble at the moment of the rupture of the interlayer of liquid separating these objects of interaction. DS species of carboxylic acids (molecules and ionic-molecular complexes) have the ability to spread over the surface of the bubble. The rate of their spreading at pH 7 and 10 over the water surface is determined. The collectibility criterion of saturated fatty acids is proposed. The values of forces exerted by the spreading DS species of reagents on liquid in the interlayer and the liquid flow rate from the interlayer are determined.

Keywords: Criterion of action of physically adsorbed reagent, flotation, saturated fatty acids, surface pressure.

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Authors: Yukiko Sasaki Alam, Shahid Alam

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Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: Machine translation, error analysis, syntactic errors, knowledge required for parsing.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The root mean square errors (RMSE) between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: Neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition.

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Authors: Vongsathorn Ngampuak, Yutachai Chookaew, Wipawee Dejtisakdi

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Dunaliella salina has great potential as a system for generating commercially valuable products, including beta-carotene, pharmaceuticals, and biofuels. Our goal is to improve this potential by enhancing growth rate and other properties of D. salina under optimal growth conditions. We used ethyl methane sulfonate (EMS) to generate random mutants in D. salina KU11, a strain classified in Thailand. In a preliminary experiment, we first treated D. salina cells with 0%, 0.8%, 1.0%, 1.2%, 1.44% and 1.66% EMS to generate a killing curve. After that, we randomly picked 30 candidates from approximately 300 isolated survivor colonies from the 1.44% EMS treatment (which permitted 30% survival) as an initial test of the mutant screen. Among the 30 survivor lines, we found that 2 strains (mutant #17 and #24) had significantly improved growth rates and cell number accumulation at stationary phase approximately up to 1.8 and 1.45 fold, respectively, 2 strains (mutant #6 and #23) had significantly decreased growth rates and cell number accumulation at stationary phase approximately down to 1.4 and 1.35 fold, respectively, while 26 of 30 lines had similar growth rates compared with the wild type control. We also analyzed cell size for each strain and found there was no significant difference comparing all mutants with the wild type. In addition, mutant #24 had shown an increase of biomass accumulation approximately 1.65 fold compared with the wild type strain on day 5 that was entering early stationary phase. From these preliminary results, it could be feasible to identify D. salina mutants with significant improved growth rate, cell accumulation and biomass production compared to the wild type for the further study; this makes it possible to improve this microorganism as a platform for biotechnology application.

Keywords: Dunaliella salina, mutant, ethyl methane sulfonate, growth rate, biomass.

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Authors: Hekmatpanah M., Fadavinia, A.

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Failure modes and effects analysis (FMEA) is an effective technique for preventing potential problems and actions needed to error cause removal. On the other hand, the oil producing companies paly a critical role in the oil industry of Iran as a developing country out of which, Sepahan Oil Co. has a considerable contribution. The aim of this research is to show how FMEA could be applied and improve the quality of products at Sepahan Oil Co. For this purpose, the four liter production line of the company has been selected for investigation. The findings imply that the application of FMEA has reduced the scraps from 50000 ppm to 5000 ppm and has resulted in a 0.92 percent decrease of the oil waste.

Keywords: FMEA, Iran, Sepahan Oil Co., Canning, Waste, Scrap

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Authors: Andra Costache, Rădiţa Alexe

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The analysis of the spatial disparities of social marginalization is a requirement in the present-day socio-economic and political context of Romania, an East-European state, member of the European Union since 2007, at present faced with the imperatives of the growth of its territorial cohesion. The main objective of this article is to develop a methodology for the assessment of social marginalization, in order to understand the intensity of the marginalization phenomenon at different spatial scales. The article proposes a social marginalization index (SMI), calculated through the integration of ten indicators relevant for the two components of social marginalization: the material component and the symbolical component. The results highlighted a strong connection between the total degree of social marginalization and the dependence on social benefits, unemployment rate, non-inclusion in the compulsory education, criminality rate, and the type of pension insurance.

Keywords: Romania, social marginalization index, territorial disparities.

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Authors: Xunan Huang, Caicai Zhang

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This paper investigated the code-mixing features in Mandarin-English bilingual children in Singapore. First, it examined whether the code-mixing rate was different in Mandarin Chinese and English contexts. Second, it explored the syntactic categories of code-mixing in Singapore bilingual children. Moreover, this study investigated whether morphological information was preserved when inserting syntactic components into the matrix language. Data are derived from the Singapore Bilingual Corpus, in which the recordings and transcriptions of sixty English-Mandarin 5-to-6-year-old children were preserved for analysis. Results indicated that the rate of code-mixing was asymmetrical in the two language contexts, with the rate being significantly higher in the Mandarin context than that in the English context. The asymmetry is related to language dominance in that children are more likely to code-mix when using their nondominant language. Concerning the syntactic categories of code-mixing words in the Singaporean bilingual children, we found that noun-mixing, verb-mixing, and adjective-mixing are the three most frequently used categories in code-mixing in the Mandarin context. This pattern mirrors the syntactic categories of code-mixing in the Cantonese context in Cantonese-English bilingual children, and the general trend observed in lexical borrowing. Third, our results also indicated that English vocabularies that carry morphological information are embedded in bare forms in the Mandarin context. These findings shed light upon how bilingual children take advantage of the two languages in mixed utterances in a bilingual environment.

Keywords: Code-mixing, Mandarin Chinese, English, bilingual children.

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Authors: K. Jayakumar, S. Thangavel

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In this paper proposed the effective fault detection of industrial drives by using Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system. This system was focused to reducing the current flow and to identify faults with lesser execution time with harmonic values obtained through fifth derivative. Initially, the construction of Biorthogonal vibration signal-data based wavelet transform in BPPVS-WNN system localizes the time and frequency domain. The Biorthogonal wavelet approximates the broken bearing using double scaling and factor, identifies the transient disturbance due to fault on induction motor through approximate coefficients and detailed coefficient. Posterior Probabilistic Neural Network detects the final level of faults using the detailed coefficient till fifth derivative and the results obtained through it at a faster rate at constant frequency signal on the industrial drive. Experiment through the Simulink tool detects the healthy and unhealthy motor on measuring parametric factors such as fault detection rate based on time, current flow rate, and execution time.

Keywords: Biorthogonal Wavelet Transform, Posterior Probabilistic Neural Network, Induction Motor.

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Authors: Natalia A. Salazar, Erika K. Méndez, Catalina Álvarez, Carlos E. Orrego

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Lyophilization, also called freeze-drying, is an important dehydration technique mainly used for pharmaceuticals. Food industry also uses lyophilization when it is important to retain most of the nutritional quality, taste, shape and size of dried products and to extend their shelf life. Vacuum-Induced during freezing cycle (VI) has been used in order to control ice nucleation and, consequently, to reduce the time of primary drying cycle of pharmaceuticals preserving quality properties of the final product. This procedure has not been applied in freeze drying of foods. The present work aims to investigate the effect of VI on the lyophilization drying time, final moisture content, density and reconstitutional properties of mango (Mangifera indica L.) slices (MS) and mango pulp-maltodextrin dispersions (MPM) (30% concentration of total solids). Control samples were run at each freezing rate without using induced vacuum. The lyophilization endpoint was the same for all treatments (constant difference between capacitance and Pirani vacuum gauges). From the experimental results it can be concluded that at the high freezing rate (0.4°C/min) reduced the overall process time up to 30% comparing process time required for the control and VI of the lower freeze rate (0.1°C/min) without affecting the quality characteristics of the dried product, which yields a reduction in costs and energy consumption for MS and MPM freeze drying. Controls and samples treated with VI at freezing rate of 0.4°C/min in MS showed similar results in moisture and density parameters. Furthermore, results from MPM dispersion showed favorable values when VI was applied because dried product with low moisture content and low density was obtained at shorter process time compared with the control. There were not found significant differences between reconstitutional properties (rehydration for MS and solubility for MPM) of freeze dried mango resulting from controls, and VI treatments.

Keywords: Drying time, lyophilization, mango, vacuum induced freezing.

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Authors: S. H. Sabzpoushan

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In this research we show that the dynamics of an action potential in a cell can be modeled with a linear combination of the dynamics of the gating state variables. It is shown that the modeling error is negligible. Our findings can be used for simplifying cell models and reduction of computational burden i.e. it is useful for simulating action potential propagation in large scale computations like tissue modeling. We have verified our finding with the use of several cell models.

Keywords: Linear model, Action potential, gating dynamics.

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: CNC milling, CNC turning, surface roughness, Taguchi analysis.

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

Abstract:

Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and electrocardiogram (ECG)-based systems are unquestionably the best choice due to their appealing inherent characteristics. The Convolutional Neural Networks (CNNs) are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the caliber of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest False Acceptance Rate (FAR)  of 0.04% and the highest False Rejection Rate (FRR)  of 5%, the best performing network achieved an identification accuracy of 99.94%. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable, but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, dense networks, identification rate, train/test split ratio.

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Authors: Shu-Chiao Yang, Jong-Jiann Shieh

Abstract:

A Simultaneous Multithreading (SMT) Processor is capable of executing instructions from multiple threads in the same cycle. SMT in fact was introduced as a powerful architecture to superscalar to increase the throughput of the processor. Simultaneous Multithreading is a technique that permits multiple instructions from multiple independent applications or threads to compete limited resources each cycle. While the fetch unit has been identified as one of the major bottlenecks of SMT architecture, several fetch schemes were proposed by prior works to enhance the fetching efficiency and overall performance. In this paper, we propose a novel fetch policy called queue situation identifier (QSI) which counts some kind of long latency instructions of each thread each cycle then properly selects which threads to fetch next cycle. Simulation results show that in best case our fetch policy can achieve 30% on speedup and also can reduce the data cache level 1 miss rate.

Keywords: SMT, QSI, DL1 miss rate.

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Authors: P. V. Pramila, V. Mahesh

Abstract:

Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients resulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects) with the aforementioned input features. It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, as well as yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV1, Multivariate Adaptive Regression Splines Pulmonary Function Test, Random Forest.

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Authors: Md. Sohidul Islam, Ahmad Fartheen Khan

Abstract:

In recent times, Non-Orthogonal Multiple Access (NOMA) has received significant attention as an upcoming candidate in the world of 5G systems. The main reason for getting NOMA in 5G is because of its capacity to provide services to many users who have the same time and frequency resources. It is best used as "multiple-input, multiple-output" (MIMO) technology. In this paper, we are going to investigate outage probability as a function of signal-to-noise ratio (SNR) and target rate user. These methods will be implemented using cooperative communication and fair power allocation, respectively.

Keywords: Non-orthogonal Multiple Access, Fair Power Allocation, Outage Probability, Target Rate User, Cooperative Communication, massive multiple input multiple output, MIMO, Successive Interference Cancellation.

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