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.

Computing the Loop Bound in Iterative Data Flow Graphs Using Natural Token Flow

Signal processing applications which are iterative in nature are best represented by data flow graphs (DFG). In these applications, the maximum sampling frequency is dependent on the topology of the DFG, the cyclic dependencies in particular. The determination of the iteration bound, which is the reciprocal of the maximum sampling frequency, is critical in the process of hardware implementation of signal processing applications. In this paper, a novel technique to compute the iteration bound is proposed. This technique is different from all previously proposed techniques, in the sense that it is based on the natural flow of tokens into the DFG rather than the topology of the graph. The proposed algorithm has lower run-time complexity than all known algorithms. The performance of the proposed algorithm is illustrated through analytical analysis of the time complexity, as well as through simulation of some benchmark problems.

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.

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.

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.

Evaluation of Optimal Residence Time in a Hot Rolled Reheating Furnace

To calculate the temperature distribution of the slab in a hot rolled reheating furnace a mathematical model has been developed by considering the thermal radiation in the furnace and transient conduction in the slab. The furnace is modeled as radiating medium with spatially varying temperature. Radiative heat flux within the furnace including the effect of furnace walls, combustion gases, skid beams and buttons is calculated using the FVM and is applied as the boundary condition of the transient conduction equation of the slab. After determining the slab emissivity by comparison between simulation and experimental work, variation of heating characteristics in the slab is investigated in the case of changing furnace temperature with various time and the slab residence time is optimized with this evaluation.

Uncertainty Propagation and Sensitivity Analysis During Calibration of an Integrated Land Use and Transport Model

In this work, propagation of uncertainty during calibration process of TRANUS, an integrated land use and transport model (ILUTM), has been investigated. It has also been examined, through a sensitivity analysis, which input parameters affect the variation of the outputs the most. Moreover, a probabilistic verification methodology of calibration process, which equates the observed and calculated production, has been proposed. The model chosen as an application is the model of the city of Grenoble, France. For sensitivity analysis and uncertainty propagation, Monte Carlo method was employed, and a statistical hypothesis test was used for verification. The parameters of the induced demand function in TRANUS, were assumed as uncertain in the present case. It was found that, if during calibration, TRANUS converges, then with a high probability the calibration process is verified. Moreover, a weak correlation was found between the inputs and the outputs of the calibration process. The total effect of the inputs on outputs was investigated, and the output variation was found to be dictated by only a few input parameters.

A Novel Reversible Watermarking Method based on Adaptive Thresholding and Companding Technique

Embedding and extraction of a secret information as well as the restoration of the original un-watermarked image is highly desirable in sensitive applications like military, medical, and law enforcement imaging. This paper presents a novel reversible data-hiding method for digital images using integer to integer wavelet transform and companding technique which can embed and recover the secret information as well as can restore the image to its pristine state. The novel method takes advantage of block based watermarking and iterative optimization of threshold for companding which avoids histogram pre and post-processing. Consequently, it reduces the associated overhead usually required in most of the reversible watermarking techniques. As a result, it keeps the distortion small between the marked and the original images. Experimental results show that the proposed method outperforms the existing reversible data hiding schemes reported in the literature.

Integrating Visual Modeling throughout the Computer Science Curriculum

The purposes of this paper are to (1) promote excellence in computer science by suggesting a cohesive innovative approach to fill well documented deficiencies in current computer science education, (2) justify (using the authors- and others anecdotal evidence from both the classroom and the real world) why this approach holds great potential to successfully eliminate the deficiencies, (3) invite other professionals to join the authors in proof of concept research. The authors- experiences, though anecdotal, strongly suggest that a new approach involving visual modeling technologies should allow computer science programs to retain a greater percentage of prospective and declared majors as students become more engaged learners, more successful problem-solvers, and better prepared as programmers. In addition, the graduates of such computer science programs will make greater contributions to the profession as skilled problem-solvers. Instead of wearily rememorizing code as they move to the next course, students will have the problem-solving skills to think and work in more sophisticated and creative ways.

Nonlinear Evolution of Electron Density Under High-Energy-Density Conditions

Evolution of one-dimensional electron system under high-energy-density (HED) conditions is investigated, using the principle of least-action and variational method. In a single-mode modulation model, the amplitude and spatial wavelength of the modulation are chosen to be general coordinates. Equations of motion are derived by considering energy conservation and force balance. Numerical results show that under HED conditions, electron density modulation could exist. Time dependences of amplitude and wavelength are both positively related to the rate of energy input. Besides, initial loading speed has a significant effect on modulation amplitude, while wavelength relies more on loading duration.

A Search Algorithm for Solving the Economic Lot Scheduling Problem with Reworks under the Basic Period Approach

In this study, we are interested in the economic lot scheduling problem (ELSP) that considers manufacturing of the serviceable products and remanufacturing of the reworked products. In this paper, we formulate a mathematical model for the ELSP with reworks using the basic period approach. In order to solve this problem, we propose a search algorithm to find the cyclic multiplier ki of each product that can be cyclically produced for every ki basic periods. This research also uses two heuristics to search for the optimal production sequence of all lots and the optimal time length of the basic period so as to minimize the average total cost. This research uses a numerical example to show the effectiveness of our approach.

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

Unified, Low-Cost Analysis Framework for the Cycling Situation in Cities

We propose a low-cost uniform analysis framework allowing comparison of the strengths and weaknesses of the bicycling experience within and between cities. A primary component is an expedient, one-page mobility survey from which mode share is calculated. The bicycle mode share of many cities remains unknown, creating a serious barrier for both scientists and policy makers aiming to understand and increase rates of bicycling. Because of its low cost and expedience, this framework could be replicated widely, uniformly filling the data gap. The framework has been applied to 13 Central European cities with success. Data is collected on multiple modes with specific questions regarding both behavior and quality of travel experience. Individual preferences are also collected, examining the conditions under which respondents would change behavior to adopt more sustainable modes (bicycling or public transportation). A broad analysis opportunity results, intended to inform policy choices.

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.

Approaches to Developing Semantic Web Services

It has been recognized that due to the autonomy and heterogeneity, of Web services and the Web itself, new approaches should be developed to describe and advertise Web services. The most notable approaches rely on the description of Web services using semantics. This new breed of Web services, termed semantic Web services, will enable the automatic annotation, advertisement, discovery, selection, composition, and execution of interorganization business logic, making the Internet become a common global platform where organizations and individuals communicate with each other to carry out various commercial activities and to provide value-added services. This paper deals with two of the hottest R&D and technology areas currently associated with the Web – Web services and the semantic Web. It describes how semantic Web services extend Web services as the semantic Web improves the current Web, and presents three different conceptual approaches to deploying semantic Web services, namely, WSDL-S, OWL-S, and WSMO.

A Comparison of Conventional and Biodegradable Chelating Agent in Different Type of Surfactant Solutions for Soap Scum Removal

One of the most challenges for hard surface cleaning product is to get rid of soap scum, a filmy sticky layer in the bathroom. The deposits of soap scum can be removed by using a proper surfactant solution with chelating agent. Unfortunately, the conventional chelating agent, ethylenediamine tetraacetic acid (EDTA), has low biodegradability, which can be tolerance in water resources and harmful to aquatic animal and microorganism. In this study, two biodegradable chelating agents, ethylenediamine disuccinic acid (EDDS) and glutamic acid diacetic acid (GLDA) were introduced as a replacement of EDTA. The result shows that using GLDA with amphoteric surfactant gave the highest equilibrium solubility of soap scum.

Removal of Heavy Metals from Wastewater by Adsorption and Membrane Processes: a Comparative Study

This research aimed at investigating the Cr (III), Cd (II) and Pb (II) removal efficiencies by using the newly synthesized metal oxides/ polyethersulfone (PES), Al2O3/PES and ZrO2/PES, membranes from synthetic wastewater and exploring fouling mechanisms. A Comparative study between the removal efficiencies of Cr (III), Cd (II) and Pb (II) from synthetic and natural wastewater by using adsorption onto agricultural by products and the newly synthesized Al2O3/PES and ZrO2/PES membranes was conducted to assess the advantages and limitations of using the metal oxides/PES membranes for heavy metals removal. The results showed that about 99 % and 88 % removal efficiencies were achieved by the tested membranes for Pb (II) and Cr (III), respectively.

On the Factors Influencing the Competitiveness of Chinese Service Trade after Entering WTO

Service trade is an important force of influencing economic development. A review on the related literatures is done firstly. Then through the construction of a Diamond Model, the main factors which influence the competitiveness of Chinese service trade are determined. With three competitiveness indexes served as the reference series respectively, the influencing factors served as the comparable series, three grey incidence models are then built up to conduct an empirical analysis on the main factors influencing the competitiveness of service trade after China entering WTO. The result indicates that urbanization level, open degree of service industry and foreign direct investment have larger impacts on Chinese service trade competitiveness, followed in turn by GDP in service industry and human capital, while commodity trade has the minimum impact. Further discussion provides train of thought for the upgrade of Chinese service trade competitiveness.