Search results for: random indices

Authors: Sokjoon Lee, Howon Kim, Kyoil Chung

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RFID system, in which we give identification number to each item and detect it with radio frequency, supports more variable service than barcode system can do. For example, a refrigerator with RFID reader and internet connection will automatically notify expiration of food validity to us. But, in spite of its convenience, RFID system has some security threats, because anybody can get ID information of item easily. One of most critical threats is privacy invasion. Existing privacy protection schemes or systems have been proposed, and these schemes or systems defend normal users from attempts that any attacker tries to get information using RFID tag value. But, these systems still have weakness that attacker can get information using analogous value instead of original tag value. In this paper, we mention this type of attack more precisely and suggest 'Tag Broker Model', which can defend it. Tag broker in this model translates original tag value to random value, and user can only get random value. Attacker can not use analogous tag value, because he/she is not able to know original one from it.

Keywords: Broker, EPC, Privacy, RFID.

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Authors: M. Mahdavi, M. Ismail, K. Jumari, Z. M. Hanapi

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For the sensor network to operate successfully, the active nodes should maintain both sensing coverage and network connectivity. Furthermore, scheduling sleep intervals plays critical role for energy efficiency of wireless sensor networks. Traditional methods for sensor scheduling use either sensing coverage or network connectivity, but rarely both. In this paper, we use random scheduling for sensing coverage and then turn on extra sensor nodes, if necessary, for network connectivity. Simulation results have demonstrated that the number of extra nodes that is on with upper bound of around 9%, is small compared to the total number of deployed sensor nodes. Thus energy consumption for switching on extra sensor node is small.

Keywords: Wireless sensor networks, energy efficient network, performance analysis, network coverage.

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, unmanned aerial vehicle, UAV, random, Kriging.

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Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti

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Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques with classifiers such as random forests, neural networks and support vector machines. The data sets are from MAGIC, a Cherenkov telescope experiment. The task is to classify gamma signals from overwhelmingly hadron and muon signals representing a rare class classification problem. We compare the individual classifiers with their ensemble counterparts and discuss the results. WEKA a wonderful tool for machine learning has been used for making the experiments.

Keywords: Ensembles, WEKA, Neural networks [NN], SupportVector Machines [SVM], Random Forests [RF].

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Authors: Abhijit Mitra

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Different pseudo-random or pseudo-noise (PN) as well as orthogonal sequences that can be used as spreading codes for code division multiple access (CDMA) cellular networks or can be used for encrypting speech signals to reduce the residual intelligence are investigated. We briefly review the theoretical background for direct sequence CDMA systems and describe the main characteristics of the maximal length, Gold, Barker, and Kasami sequences. We also discuss about variable- and fixed-length orthogonal codes like Walsh- Hadamard codes. The equivalence of PN and orthogonal codes are also derived. Finally, a new PN sequence is proposed which is shown to have certain better properties than the existing codes.

Keywords: Code division multiple access, pseudo-noise codes, maximal length, Gold, Barker, Kasami, Walsh-Hadamard, autocorrelation, crosscorrelation, figure of merit.

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Authors: M. A. Torkamani, S. Mahmoodzadeh, S. Pourroostaei, C. Lucas

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Daily production of information and importance of the sequence of produced data in forecasting future performance of market causes analysis of data behavior to become a problem of analyzing time series. But time series that are very complicated, usually are random and as a result their changes considered being unpredictable. While these series might be products of a deterministic dynamical and nonlinear process (chaotic) and as a result be predictable. Point of Chaotic theory view, complicated systems have only chaotically face and as a result they seem to be unregulated and random, but it is possible that they abide by a specified math formula. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) has been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom.

Keywords: Chaos, Exchange Rate, Nonlinear Models.

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Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan

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Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.

Keywords: Cathode spot, vacuum arc discharge, transverse magnetic field, random walk.

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Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su, Junjie Wang

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The Bernoulli filter is a precise Bayesian filter for single target tracking based on the random finite set theory. The standard Bernoulli filter often underestimates the number of the targets. This study proposes a Gaussian particle flow (GPF) Bernoulli filter employing particle flow to migrate particles from prior to posterior positions to improve the performance of the standard Bernoulli filter. By employing the particle flow filter, the computational speed of the Bernoulli filters is significantly improved. In addition, the GPF Bernoulli filter provides more accurate estimation compared with that of the standard Bernoulli filter. Simulation results confirm the improved tracking performance and computational speed in two- and three-dimensional scenarios compared with other algorithms.

Keywords: Bernoulli filter, particle filter, particle flow filter, random finite sets, target tracking.

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Authors: Susanta Banerjee, Sanjaya Kumar Patro

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Buildings with floating column are highly undesirable built in seismically active areas. Many urban multi-storey buildings today have floating column buildings which are adopted to accommodate parking at ground floor or reception lobbies in the first storey. The earthquake forces developed at different floor levels in a building need to be brought down along the height to the ground by the shortest path; any deviation or discontinuity in this load transfer path results in poor performance of the building. Floating column buildings are severely damaged during earthquake. Damage on this structure can be reduce by taking the effect of infill wall. This paper presents the effect of stiffness of infill wall to the damage occurred in floating column building when ground shakes. Modelling and analysis are carried out by non linear analysis programme IDARC-2D. Damage occurred in beams, columns, storey are studied by formulating modified Park & Ang model to evaluate damage indices. Overall structural damage indices in buildings due to shaking of ground are also obtained. Dynamic response parameters i.e. lateral floor displacement, storey drift, time period, base shear of buildings are obtained and results are compared with the ordinary moment resisting frame buildings. Formation of cracks, yield, plastic hinge, are also observed during analysis.

Keywords: Floating column, Infill Wall, Park-Ang Damage Index, Damage State.

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Authors: Hilal A. Fadhil, Syed A. Aljunid, R. Badlishah Ahmed

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In this paper we study the use of a new code called Random Diagonal (RD) code for Spectral Amplitude Coding (SAC) optical Code Division Multiple Access (CDMA) networks, using Fiber Bragg-Grating (FBG), FBG consists of a fiber segment whose index of reflection varies periodically along its length. RD code is constructed using code level and data level, one of the important properties of this code is that the cross correlation at data level is always zero, which means that Phase intensity Induced Phase (PIIN) is reduced. We find that the performance of the RD code will be better than Modified Frequency Hopping (MFH) and Hadamard code It has been observed through experimental and theoretical simulation that BER for RD code perform significantly better than other codes. Proof –of-principle simulations of encoding with 3 channels, and 10 Gbps data transmission have been successfully demonstrated together with FBG decoding scheme for canceling the code level from SAC-signal.

Keywords: FBG, MFH, OCDMA, PIIN, BER.

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Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

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In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest.

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Authors: Masoud Nasri, Sadat Feiznia, Mohammad Jafari, Hasan Ahmadi

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Today, incorrect use of lands and land use changes, excessive grazing, no suitable using of agricultural farms, plowing on steep slopes, road construct, building construct, mine excavation etc have been caused increasing of soil erosion and sediment yield. For erosion and sediment estimation one can use statistical and empirical methods. This needs to identify land unit map and the map of effective factors. However, these empirical methods are usually time consuming and do not give accurate estimation of erosion. In this study, we applied GIS techniques to estimate erosion and sediment of Menderjan watershed at upstream Zayandehrud river in center of Iran. Erosion faces at each land unit were defined on the basis of land use, geology and land unit map using GIS. The UTM coordinates of each erosion type that showed more erosion amounts such as rills and gullies were inserted in GIS using GPS data. The frequency of erosion indicators at each land unit, land use and their sediment yield of these indices were calculated. Also using tendency analysis of sediment yield changes in watershed outlet (Menderjan hydrometric gauge station), was calculated related parameters and estimation errors. The results of this study according to implemented watershed management projects can be used for more rapid and more accurate estimation of erosion than traditional methods. These results can also be used for regional erosion assessment and can be used for remote sensing image processing.

Keywords: Erosion and sedimentation, Gully, Rill, GIS, GPS, Menderjan Watershed

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Authors: Ivana Šimonová

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As widely accepted, didactic multiple-choice tests are referred as a tool providing feedback easily and quickly. Despite the final test scores are corrected by a special formula and number of high plausibility distractors is taken into consideration, the results may be influenced by the random choice. The survey was held in three academic years at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic, where the multiple-choice test scores were compared to the open-answer ones. The research sample included 567 respondents. The collected data were processed by the NCSS2007 statistic software by the method of frequency and multiple regression analysis and presented in the form of figures and tables. The results proved statistically significant differences in test scores in academic years 2 and 3, and were discussed from the point of the credit system and conditions for teaching/learning English in the Czech education system.

Keywords: ESP, higher education, multiple-choice test, open-answer test.

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Authors: S. Hutasavi, D. Chen

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The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: Built-up area extraction, Google earth engine, adaptive thresholding method, rapid mapping.

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Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: Correlation filter, long-term tracking, random fern, real-time tracking.

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity is a low-grade inflammatory disease and may lead to health problems such as hypertension, dyslipidemia, diabetes. It is also associated with important risk factors for cardiovascular diseases. This requires the detailed evaluation of obesity, particularly in children. The aim of this study is to enlighten the potential associations between lipid ratios and obesity indices and to introduce those with discriminating features among children with obesity and metabolic syndrome (MetS). A total of 408 children (aged between six and eighteen years) participated in the scope of the study. Informed consent forms were taken from the participants and their parents. Ethical Committee approval was obtained. Anthropometric measurements such as weight, height as well as waist, hip, head, neck circumferences and body fat mass were taken. Systolic and diastolic blood pressure values were recorded. Body mass index (BMI), diagnostic obesity notation model assessment index-II (D2 index), waist-to-hip, head-to-neck ratios were calculated. Total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDLChol), low-density lipoprotein cholesterol (LDLChol) analyses were performed in blood samples drawn from 110 children with normal body weight, 164 morbid obese (MO) children and 134 children with MetS. Age- and sex-adjusted BMI percentiles tabulated by World Health Organization were used to classify groups; normal body weight, MO and MetS. 15^th-to-85^th percentiles were used to define normal body weight children. Children, whose values were above the 99th percentile, were described as MO. MetS criteria were defined. Data were evaluated statistically by SPSS Version 20. The degree of statistical significance was accepted as p≤0.05. Mean±standard deviation values of BMI for normal body weight children, MO children and those with MetS were 15.7±1.1, 27.1±3.8 and 29.1±5.3 kg/m², respectively. Corresponding values for the D2 index were calculated as 3.4±0.9, 14.3±4.9 and 16.4±6.7. Both BMI and D2 index were capable of discriminating the groups from one another (p≤0.01). As far as other obesity indices were considered, waist-to hip and head-to-neck ratios did not exhibit any statistically significant difference between MO and MetS groups (p≥0.05). Diagnostic obesity notation model assessment index-II was correlated with the triglycerides-to-HDL-C ratio in normal body weight and MO (r=0.413, p≤0.01 and r=0.261, (p≤0.05, respectively). Total cholesterol-to-HDL-C and LDL-C-to-HDL-C showed statistically significant differences between normal body weight and MO as well as MO and MetS (p≤0.05). The only group in which these two ratios were significantly correlated with waist-to-hip ratio was MetS group (r=0.332 and r=0.334, p≤0.01, respectively). Lack of correlation between the D2 index and the triglycerides-to-HDL-C ratio was another important finding in MetS group. In this study, parameters and ratios, whose associations were defined previously with increased cardiovascular risk or cardiac death have been evaluated along with obesity indices in children with morbid obesity and MetS. Their profiles during childhood have been investigated. Aside from the nature of the correlation between the D2 index and triglycerides-to-HDL-C ratio, total cholesterol-to-HDL-C as well as LDL-C-to- HDL-C ratios along with their correlations with waist-to-hip ratio showed that the combination of obesity-related parameters predicts better than one parameter and appears to be helpful for discriminating MO children from MetS group.

Keywords: Children, lipid ratios, metabolic syndrome, obesity indices.

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Authors: C. Ardil

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This paper presents a software product quality evaluation model based on the ISO/IEC 25010 quality model. The evaluation characteristics and sub characteristics were identified from the ISO/IEC 25010 quality model. The multidimensional structure of the quality model is based on characteristics such as functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability, and associated sub characteristics. Random numbers are generated to establish the decision maker’s importance weights for each sub characteristics. Also, random numbers are generated to establish the decision matrix of the decision maker’s final scores for each software product against each sub characteristics. Thus, objective criteria importance weights and index scores for datasets were obtained from the random numbers. In the proposed model, five different software product quality evaluation datasets under three different weight vectors were applied to multiple criteria decision analysis method, preference analysis for reference ideal solution (PARIS) for comparison, and sensitivity analysis procedure. This study contributes to provide a better understanding of the application of MCDMA methods and ISO/IEC 25010 quality model guidelines in software product quality evaluation process.

Keywords: ISO/IEC 25010 quality model, multiple criteria decisions making, multiple criteria decision making analysis, MCDMA, PARIS, Software Product Quality Evaluation Model, Software Product Quality Evaluation, Software Evaluation, Software Selection, Software

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: Coupled Markov random field, environment, object-based analysis, Polarimetric SAR images.

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Authors: Tin Lai Win, Nant Christina Kyaw

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This paper is taken into consideration the problem of cryptanalysis of stream ciphers. There is some attempts need to improve the existing attacks on stream cipher and to make an attempt to distinguish the portions of cipher text obtained by the encryption of plain text in which some parts of the text are random and the rest are non-random. This paper presents a tutorial introduction to symmetric cryptography. The basic information theoretic and computational properties of classic and modern cryptographic systems are presented, followed by an examination of the application of cryptography to the security of VoIP system in computer networks using LFSR algorithm. The implementation program will be developed Java 2. LFSR algorithm is appropriate for the encryption and decryption of online streaming data, e.g. VoIP (voice chatting over IP). This paper is implemented the encryption module of speech signals to cipher text and decryption module of cipher text to speech signals.

Keywords: Linear Feedback Shift Register.

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Authors: Lebari B. Gboeloh

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Ficus exasperata is a plant used in the traditional management of malaria in south-south Nigeria. An investigation into the effects of the ethanolic extract of the leaf of the plant on some biochemical indices in albino mice infected with Plasmodium berghei (NK 65) was conducted. 48 mice with weight range of 13-23 g were grouped into six (A, B, C, D, E, and F). Each group contained 8 mice. Groups A, B, C, D and E were infected with blood containing the parasite. Group F was not infected and served as the normal control. On the 6^th day after infection, 4 mice from each group were sacrificed and blood samples are collected for investigation. The remaining mice in each group were treated. Mice in Groups A, B and C were administered orally with 200, 300 and 500 mg/kg body weight of Ficus exasperata respectively for six days. Group D was not treated while Group F was given distilled water. Group E was treated with 5 mg/kg body weight of chloroquine. On the 6^th day post treatment, these mice were sacrificed and blood samples were collected for biochemical analysis. The results indicated that on the 6^th day post inoculation, the levels of aspartate aminotransferase (AST), alkaline phosphatase (ALP) and alanine aminotransferase (ALT) in all the mice infected with the parasite were significantly (p < 0.05) elevated. However, on the 6^th day post administration of extract, the increased levels of AST, ALP and ALT were significantly (p < 0.05) reduced in groups administered with 300 and 500 mg/kg body weight of the extract compared with groups D and F. The reduction in the levels of these enzymes is an indication that F. exasperata have no hepatotoxic effect on the mice at the dose levels administered.

Keywords: Ficus exasperata, albino mice, Plasmodium berghei, biochemical parameters.

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Authors: Shivakumar, G. S. Vijay, P. Srinivas Pai, B. R. Shrinivasa Rao

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In the present study, RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tex and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: Radial Basis Function networks, emissions, Performance parameters, Fuzzy c means.

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Authors: V.A. Baronenko, S.I. Bugreeva, K.R. Mekhdieva

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Differentiated impact of team sports (basketball, indoor soccer, handball) on general haemodynamics and aerobic potential of students who specialize in technical subjects is detected only on the fourth year of studies in the institute of higher education. Those who play basketball and indoor soccer have shown increase of stroke and minute volume of blood indices, pumping and contractile function of the heart, oxygenation of blood and oxygen delivery to tissues, aerobic energy supply and balance of sympathetic and parasympathetic activity of the nervous regulation mechanism of the circulatory system. Those who play handball have shown these indices statistically decreased. On the whole playing basketball and indoor soccer optimizes the strategy for adaptation of students to the studying process, but playing handball does the opposite thing. The leading factor for adaptation of students is: those who play basketball have increase of minute blood volume which stipulates velocity of the system blood circulation and well-timed oxygen delivery to tissues; those who play indoor soccer have increase of power and velocity of contractile function of the heart; those who play handball have increase of resistance of thorax to the system blood flow which minimizes contractile function of the heart, blood oxygen saturation and delivery of oxygen to tissues.

Keywords: team sports, general haemodynamics, aerobic potential, strategy for adaptation.

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Authors: Hassan Masoumi, Rashed Alavi

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Wheat is one of the strategic crops in Iran, on which the household food basket is highly dependent. Although this crop is cultivated and produced in almost all provinces of the country, its production efficiency is lower than the global and regional averages due to the lack of optimal use of allocated resources. In this research, which was carried out with a documentary and library method, first, the total and partial productivity indices of irrigated wheat production were calculated in large, medium and small exploitation scales in different provinces of the country, and then the provinces were clustered in terms of these indices. The results showed that the total productivity of production factors had a direct correlation with the scale of exploitation, so that with the increase in the size of exploitations, the total productivity index increased. On the scale of small exploitations, North Khorasan, Zanjan, Chaharmahal and Bakhtiari Province, on a medium scale, Chaharmahal and Bakhtiari Province and on the scale of large exploitations, Zanjan, Chaharmahal and Bakhtiari provinces, Kohkiloyeh and Boyer Ahmad and North Khorasan, with better use of production resources compared to other provinces, were placed in the best cluster in terms of total productivity index. The high total productivity index in Zanjan, Chaharmahal and Bakhtiari Province is related to the higher productivity of factors such as mechanization and land in these provinces. Finally, the methods of using these factors in productive provinces, along with technical and specialized regional guidelines, can facilitate the improvement of productivity in less productive provinces.

Keywords: Clustering, Irrigated wheat, Iran, total productivity.

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Authors: V. C. Shruti, P. F. Rodríguez-Espinosa, D. C. Escobedo-Urías, Estefanía Martinez Tavera, M. P. Jonathan

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Atoyac River, a major south-central river flowing through the states of Puebla and Tlaxcala in Mexico is significantly impacted by the natural volcanic inputs in addition with wastewater discharges from urban, agriculture and industrial zones. In the present study, core samples were collected from R. Atoyac and analyzed for sediment granularity, major (Al, Fe, Ca, Mg, K, P and S) and trace elemental concentrations (Ba, Cr, Cd, Mn, Pb, Sr, V, Zn, Zr). The textural studies reveal that the sediments are mostly sand sized particles exceeding 99% and with very few to no presence of mud fractions. It is observed that most of the metals like (avg: all values in μg g^-1) Ca (35,528), Mg (10,789), K (7453), S (1394), Ba (203), Cr (30), Cd (4), Pb (11), Sr (435), Zn (76) and Zr (88) are enriched throughout the sediments mainly sourced from volcanic inputs, source rock composition of Atoyac River basin and industrial influences from the Puebla city region. Contamination indices, such as anthropogenic factor (AF), enrichment factor (EF) and geoaccumulation index (I_geo), were used to investigate the level of contamination and toxicity as well as quantitatively assess the influences of human activities on metal concentrations. The AF values (>1) for Ba, Ca, Mg, Na, K, P and S suggested volcanic inputs from the study region, where as Cd and Zn are attributed to the impacts of industrial inputs in this zone. The EF and I_geo values revealed an extreme enrichment of S and Cd. The ecological risks were evaluated using potential ecological risk index (RI) and the results indicate that the metals Cd and V pose a major hazard for the biological community.

Keywords: Atoyac River, contamination indices, metal concentrations, Mexico, textural studies.

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Authors: Dongseok Cho, Mitchell Driedger, Sera Han, Noman Khan, Mohammed Elmorsy, Mohamad El-Hajj

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Since the approval of the COVID-19 vaccine in late 2020, vaccination rates have varied around the globe. Access to a vaccine supply, mandated vaccination policy, and vaccine hesitancy contribute to these rates. This study used COVID-19 vaccination data from Our World in Data and the Multilateral Leaders Task Force on COVID-19 to create two COVID-19 vaccination indices. The first index is the Vaccine Utilization Index (VUI), which measures how effectively each country has utilized its vaccine supply to doubly vaccinate its population. The second index is the Vaccination Acceleration Index (VAI), which evaluates how efficiently each country vaccinated their populations within their first 150 days. Pearson correlations were created between these indices and country indicators obtained from the World Bank. Results of these correlations identify countries with stronger Health indicators such as lower mortality rates, lower age-dependency ratios, and higher rates of immunization to other diseases display higher VUI and VAI scores than countries with lesser values. VAI scores are also positively correlated to Governance and Economic indicators, such as regulatory quality, control of corruption, and GDP per capita. As represented by the VUI, proper utilization of the COVID-19 vaccine supply by country is observed in countries that display excellence in health practices. A country’s motivation to accelerate its vaccination rates within the first 150 days of vaccinating, as represented by the VAI, was largely a product of the governing body’s effectiveness and economic status, as well as overall excellence in health practises.

Keywords: Data mining, Pearson Correlation, COVID-19, vaccination rates, hesitancy.

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Authors: Kailash C. Madan

Abstract:

We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.

Keywords: A three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state.

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Authors: Orkide Donma, M. Metin Donma, Burcin Nalbantoglu, Birol Topcu, Feti Tulubas, Murat Aydin, Tuba Gokkus, Ahmet Gurel

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Increasing prevalence of childhood obesity has increased the interest in early and late indicators of gaining weight. Cell blood counts may be indicators of pro-inflammatory states. The aim was to evaluate associations of hematological parameters, including hematocrit (HTC), hemoglobin, blood cell counts and their indices with the degree of obesity in pediatric population. A total of 249; -139 morbidly obese (MO), 82 healthy normal weight (NW) and 28 overweight (OW) children were included into the scope of the study. WHO BMI-for age percentiles were used to form age- and sexmatched groups. Informed consent forms and the Ethics Committee approval were obtained. Anthropometric measurements were performed. Hematological parameters were determined. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. Significant differences (p=0.000) between waist-to-hip ratios and head-to- neck ratios (hnrs) of MO and NW children were detected. A significant difference between hnrs of OW and MO children (p=0.000) was observed. Red cell distribution width (RDW) was higher in OW children than NW group (p=0.030). Such finding couldn’t be detected between MO and NW groups. Increased RDW was prominent in OW children. The decrease in mean corpuscular hemoglobin concentration (MCHC) values in MO children was sharper than the values in OW children (p=0.006 vs p=0.042) compared to those in NW group. Statistically higher HTC levels were observed between MO-NW (p=0.014), but none between OW-NW. Though the cause-effect relationship between obesity and erythrocyte indices still needs further investigation, alterations in RDW, HTC, MCHC during obesity may be of significance in the early life.

Keywords: Anthropometry, children, erythrocytes, obesity.

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Authors: Hilal Adnan Fadhil, Syed Alwei, R. Badlishah Ahmad

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A new code for spectral-amplitude coding optical code-division multiple-access system is proposed called Random diagonal (RD) code. This code is constructed using code segment and data segment. One of the important properties of this code is that the cross correlation at data segment is always zero, which means that Phase Intensity Induced Noise (PIIN) is reduced. For the performance analysis, the effects of phase-induced intensity noise, shot noise, and thermal noise are considered simultaneously. Bit-error rate (BER) performance is compared with Hadamard and Modified Frequency Hopping (MFH) codes. It is shown that the system using this new code matrices not only suppress PIIN, but also allows larger number of active users compare with other codes. Simulation results shown that using point to point transmission with three encoded channels, RD code has better BER performance than other codes, also its found that at 0 dbm PIIN noise are 10-10 and 10-11 for RD and MFH respectively.

Keywords: OCDMA, MFH, PIIN, and BER.

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Authors: Ju-Hong Lee, Ching-Wei Liao, Kun-Che Lee

Abstract:

This paper deals with the problem of using antenna sensors for adaptive beamforming in the presence of random steering mismatch. We present an efficient adaptive array beamformer with robustness to deal with the considered problem. The robustness of the proposed beamformer comes from the efficient designation of the steering vector. Using the received array data vector, we construct an appropriate correlation matrix associated with the received array data vector and a correlation matrix associated with signal sources. Then, the eigenvector associated with the largest eigenvalue of the constructed signal correlation matrix is designated as an appropriate estimate of the steering vector. Finally, the adaptive weight vector required for adaptive beamforming is obtained by using the estimated steering vector and the constructed correlation matrix of the array data vector. Simulation results confirm the effectiveness of the proposed method.

Keywords: Adaptive beamforming, antenna array, linearly constrained minimum variance, robustness, steering vector.

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Authors: M. Rahou, A. Cheikh, F. Sebaa

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Manufacturing tolerancing is intended to determine the intermediate geometrical and dimensional states of the part during its manufacturing process. These manufacturing dimensions also serve to satisfy not only the functional requirements given in the definition drawing, but also the manufacturing constraints, for example geometrical defects of the machine, vibration and the wear of the cutting tool. In this paper, an experimental study on the influence of the wear of the cutting tool (systematic dispersions) is explored. This study was carried out on three stages .The first stage allows machining without elimination of dispersions (random, systematic) so the tolerances of manufacture according to total dispersions. In the second stage, the results of the first stage are filtered in such way to obtain the tolerances according to random dispersions. Finally, from the two previous stages, the systematic dispersions are generated. The objective of this study is to model by the least squares method the error of manufacture based on systematic dispersion. Finally, an approach of optimization of the manufacturing tolerances was developed for machining on a CNC machine tool

Keywords: Dispersions, Compensation, modeling, manufacturing Tolerance, machine tool.

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