The Study of the Discrete Risk Model with Random Income

In this paper, we extend the compound binomial model to the case where the premium income process, based on a binomial process, is no longer a linear function. First, a mathematically recursive formula is derived for non ruin probability, and then, we examine the expected discounted penalty function, satisfy a defect renewal equation. Third, the asymptotic estimate for the expected discounted penalty function is then given. Finally, we give two examples of ruin quantities to illustrate applications of the recursive formula and the asymptotic estimate for penalty function.

Improved Robust Stability Criteria for Discrete-time Neural Networks

In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.

The Approximate Solution of Linear Fuzzy Fredholm Integral Equations of the Second Kind by Using Iterative Interpolation

in this paper, we propose a numerical method for the approximate solution of fuzzy Fredholm functional integral equations of the second kind by using an iterative interpolation. For this purpose, we convert the linear fuzzy Fredholm integral equations to a crisp linear system of integral equations. The proposed method is illustrated by some fuzzy integral equations in numerical examples.

Production of Apricot Vinegar Using an Isolated Acetobacter Strain from Iranian Apricot

Vinegar or sour wine is a product of alcoholic and subsequent acetous fermentation of sugary precursors derived from several fruits or starchy substrates. This delicious food additive and supplement contains not less than 4 grams of acetic acid in 100 cubic centimeters at 20°C. Among the large number of bacteria that are able to produce acetic acid, only few genera are used in vinegar industry most significant of which are Acetobacter and Gluconobacter. In this research we isolated and identified an Acetobacter strain from Iranian apricot, a very delicious and sensitive summer fruit to decay, we gathered from fruit's stores in Isfahan, Iran. The main culture media we used were Carr, GYC, Frateur and an industrial medium for vinegar production. We isolated this strain using a novel miniature fermentor we made at Pars Yeema Biotechnologists Co., Isfahan Science and Technology Town (ISTT), Isfahan, Iran. The microscopic examinations of isolated strain from Iranian apricot showed gram negative rods to cocobacilli. Their catalase reaction was positive and oxidase reaction was negative and could ferment ethanol to acetic acid. Also it showed an acceptable growth in 5%, 7% and 9% ethanol concentrations at 30°C using modified Carr media after 24, 48 and 96 hours incubation respectively. According to its tolerance against high concentrations of ethanol after four days incubation and its high acetic acid production, 8.53%, after 144 hours, this strain could be considered as a suitable industrial strain for a production of a new type of vinegar, apricot vinegar, with a new and delicious taste. In conclusion this is the first report of isolation and identification of an Acetobacter strain from Iranian apricot with a very good tolerance against high ethanol concentrations as well as high acetic acid productivity in an acceptable incubation period of time industrially. This strain could be used in vinegar industry to convert apricot spoilage to a beneficiary product and mentioned characteristics have made it as an amenable strain in food and agricultural biotechnology.

Newton-Raphson State Estimation Solution Employing Systematically Constructed Jacobian Matrix

Newton-Raphson State Estimation method using bus admittance matrix remains as an efficient and most popular method to estimate the state variables. Elements of Jacobian matrix are computed from standard expressions which lack physical significance. In this paper, elements of the state estimation Jacobian matrix are obtained considering the power flow measurements in the network elements. These elements are processed one-by-one and the Jacobian matrix H is updated suitably in a simple manner. The constructed Jacobian matrix H is integrated with Weight Least Square method to estimate the state variables. The suggested procedure is successfully tested on IEEE standard systems.

Effects of Energy Consumption on Indoor Air Quality

Continuous measurements and multivariate methods are applied in researching the effects of energy consumption on indoor air quality (IAQ) in a Finnish one-family house. Measured data used in this study was collected continuously in a house in Kuopio, Eastern Finland, during fourteen months long period. Consumption parameters measured were the consumptions of district heat, electricity and water. Indoor parameters gathered were temperature, relative humidity (RH), the concentrations of carbon dioxide (CO2) and carbon monoxide (CO) and differential air pressure. In this study, self-organizing map (SOM) and Sammon's mapping were applied to resolve the effects of energy consumption on indoor air quality. Namely, the SOM was qualified as a suitable method having a property to summarize the multivariable dependencies into easily observable two-dimensional map. Accompanying that, the Sammon's mapping method was used to cluster pre-processed data to find similarities of the variables, expressing distances and groups in the data. The methods used were able to distinguish 7 different clusters characterizing indoor air quality and energy efficiency in the study house. The results indicate, that the cost implications in euros of heating and electricity energy vary according to the differential pressure, concentration of carbon dioxide, temperature and season.

Modeling of Single-Particle Impact in Abrasive Water Jet Machining

This work presents a study on the abrasive water jet (AWJ) machining. An explicit finite element analysis (FEA) of single abrasive particle impact on stainless steel 1.4304 (AISI 304) is conducted. The abrasive water jet machining is modeled by FEA software ABAQUS/CAE. Shapes of craters in FEM simulation results were used and compared with the previous experimental and FEM works by means of crater sphericity. The influence of impact angle and particle velocity was observed. Adaptive mesh domain is used to model the impact zone. Results are in good agreement with those obtained from the experimental and FEM simulation. The crater-s depth is also obtained for different impact angle and abrasive particle velocities.

Novel Adaptive Channel Equalization Algorithms by Statistical Sampling

In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.

Effect of Muscle Loss on Hip Muscular Effort during the Swing Phase of Transfemoral Amputee Gait: A Simulation Study

The effect of muscle loss due to transfemoral amputation, on energy expenditure of hip joint and individual residual muscles was simulated. During swing phase of gait, with each muscle as an ideal force generator, the lower extremity was modeled as a two-degree of freedom linkage, for which hip and knee were joints. According to results, muscle loss will not lead to higher energy expenditure of hip joint, as long as other parameters of limb remain unaffected. This finding maybe due to the role of biarticular muscles in hip and knee joints motion. Moreover, if hip flexors are removed from the residual limb, residual flexors, and if hip extensors are removed, residual extensors will do more work. In line with the common practice in transfemoral amputation, this result demonstrates during transfemoral amputation, it is important to maintain the length of residual limb as much as possible.

Prediction of Protein Subchloroplast Locations using Random Forests

Protein subchloroplast locations are correlated with its functions. In contrast to the large amount of available protein sequences, the information of their locations and functions is less known. The experiment works for identification of protein locations and functions are costly and time consuming. The accurate prediction of protein subchloroplast locations can accelerate the study of functions of proteins in chloroplast. This study proposes a Random Forest based method, ChloroRF, to predict protein subchloroplast locations using interpretable physicochemical properties. In addition to high prediction accuracy, the ChloroRF is able to select important physicochemical properties. The important physicochemical properties are also analyzed to provide insights into the underlying mechanism.

Switching Rule for the Exponential Stability and Stabilization of Switched Linear Systems with Interval Time-varying Delays

This paper is concerned with exponential stability and stabilization of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton-s formula, a switching rule for the exponential stability and stabilization of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability and stabilization of the systems are first established in terms of LMIs. Numerical examples are included to illustrate the effectiveness of the results.

On Adaptive Optimization of Filter Performance Based on Markov Representation for Output Prediction Error

This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

Comparison of the Music Sound System between Thailand and Vietnam

Thai and Vietnamese music had been influenced and inspired by the traditional Chinese music. Whereby the differences of the tuning systems as well as the music modes are obviously known . The research examined the character of musical instruments, songs and culture between Thai and Vietnamese. An analyzing of songs and modes and the study of tone vibration as well as timbre had been done accurately. This qualitative research is based on documentary and songs analysis, field study, interviews and focus group discussion of Thai and Vietnamese masters. The research aims are to examine the musical instruments and songs of both Thai and Vietnamese as well as the comparison of the sounding system between Thailand and Vietnam. The finding of the research has revealed that there are similarities in certain kinds of instruments but differences in the sound systems regarding songs and scale of Thailand and Vietnam. Both cultural musical instruments are diverse and synthetic combining native and foreign inspiring. An integral part of Vietnam has been highly impacted by Chinese musical convention. Korea, Mongolia and Japan music have also play an active and effectively influenced as their geographical related. Whereas Thailand has been influenced by Chinese and Indian traditional music. Both Thai and Vietnamese musical instruments can be divided into four groups: plucked strings, bowed strings, winds and percussion. Songs from both countries have their own characteristics. They are playing a role in touching people heart in ceremonies, social functions and an essential element of the native performing arts. The Vietnamese music melodies have been influenced by Chinese music and taken the same character as Chinese songs. Thai song has specific identity and variety showed in its unique melody. Pentatonic scales have effectively been used in composing Thai and Vietnamese songs, but in different implementing concept.

Performance of an Electrocoagulation Process in Treating Direct Dye: Batch and Continuous Upflow Processes

This study presents an investigation of electrochemical variables and an application of the optimal parameters in operating a continuous upflow electrocoagulation reactor in removing dye. Direct red 23, which is azo-based, was used as a representative of direct dyes. First, a batch mode was employed to optimize the design parameters: electrode type, electrode distance, current density and electrocoagulation time. The optimal parameters were found to be iron anode, distance between electrodes of 8 mm and current density of 30 A·m-2 with contact time of 5 min. The performance of the continuous upflow reactor with these parameters was satisfactory, with >95% color removal and energy consumption in the order of 0.6-0.7 kWh·m-3.

A Transform-Free HOC Scheme for Incompressible Viscous Flow past a Rotationally Oscillating Circular Cylinder

A numerical study is made of laminar, unsteady flow behind a rotationally oscillating circular cylinder using a recently developed higher order compact (HOC) scheme. The stream function vorticity formulation of Navier-Stokes (N-S) equations in cylindrical polar coordinates are considered as the governing equations. The temporal behaviour of vortex formation and relevant streamline patterns of the flow are scrutinized over broad ranges of two externally specified parameters namely dimensionless forced oscillating frequency Sf and dimensionless peak rotation rate αm for the Reynolds-s number Re = 200. Excellent agreements are found both qualitatively and quantitatively with the existing experimental and standard numerical results.

Questions in the School

Paper deals with the topic of questions as important components of information behavior in the school. By analyzing the Corpus Schola2010, the state of contemporary education in terms of questioning is proven unsatisfactory: 80% of the questions are asked by teachers; most of teacher-s questions are asked at the beginning of the first grade, than their number decreases and is settling down on 80±10 questions per lesson. The average number of questions within one lesson per one pupil is generally less than one whole question. The highest values are achieved in the first, sixth, eighth and tenth grade,, i.e. in the transition years in which pupils are moving into higher levels of education and every following year it declines. We can state Czech school do not support questioning and question skill of their pupils, thereby typical Czech schools are neglecting the development of thinking, reasoning and cooperation of their pupils.

A Vehicular Visual Tracking System Incorporating Global Positioning System

Surveillance system is widely used in the traffic monitoring. The deployment of cameras is moving toward a ubiquitous camera (UbiCam) environment. In our previous study, a novel service, called GPS-VT, was firstly proposed by incorporating global positioning system (GPS) and visual tracking techniques for the UbiCam environment. The first prototype is called GODTA (GPS-based Moving Object Detection and Tracking Approach). For a moving person carried GPS-enabled mobile device, he can be tracking when he enters the field-of-view (FOV) of a camera according to his real-time GPS coordinate. In this paper, GPS-VT service is applied to the tracking of vehicles. The moving speed of a vehicle is much faster than a person. It means that the time passing through the FOV is much shorter than that of a person. Besides, the update interval of GPS coordinate is once per second, it is asynchronous with the frame rate of the real-time image. The above asynchronous is worsen by the network transmission delay. These factors are the main challenging to fulfill GPS-VT service on a vehicle.In order to overcome the influence of the above factors, a back-propagation neural network (BPNN) is used to predict the possible lane before the vehicle enters the FOV of a camera. Then, a template matching technique is used for the visual tracking of a target vehicle. The experimental result shows that the target vehicle can be located and tracking successfully. The success location rate of the implemented prototype is higher than that of the previous GODTA.

Groundwater Level Prediction at a Pilot Area in Southeastern Part of the UAE using Shallow Seismic Method

The groundwater is one of the main sources for sustainability in the United Arab Emirates (UAE). Intensive developments in Al-Ain area lead to increase water demand, which consequently reduced the overall groundwater quantity in major aquifers. However, in certain residential areas within Al-Ain, it has been noticed that the groundwater level is rising, for example in Sha-ab Al Askher area. The reasons for the groundwater rising phenomenon are yet to be investigated. In this work, twenty four seismic refraction profiles have been carried out along the study pilot area; as well as field measurement of the groundwater level in a number of available water wells in the area. The processed seismic data indicated the deepest and shallowest groundwater levels are 15m and 2.3 meters respectively. This result is greatly consistent with the proper field measurement of the groundwater level. The minimum detected value may be referred to perched subsurface water which may be associated to the infiltration from the surrounding water bodies such as lakes, and elevated farms. The maximum values indicate the accurate groundwater level within the study area. The findings of this work may be considered as a preliminary help to the decision makers.

Extraction Condition of Phaseolus vulgaris

Theoptimal extraction condition of dried Phaseolus vulgaris powderwas studied. The three independent variables are raw material concentration, shaking and centrifugaltime. The dependent variables are both yield percentage of crude extract and alphaamylase enzyme inhibition activity. The experimental design was based on box-behnkendesign. Highest yield percentage of crude extract could get from extraction condition at concentration of 1, 0,1, concentration of 0.15 M ,extraction time for 2hour, and separationtime for60 min. Moreover, the crude extract with highest alpha-amylase enzyme inhibition activityoccurred by extraction condition at concentration of 0.10 M, extraction time for 2 min, and separation time for 45 min

Automated Textile Defect Recognition System Using Computer Vision and Artificial Neural Networks

Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.