Earticle

In this paper, a new error diffusion method is proposed that provides high quality ED results. The goal of half-toning method is to quantize each pixel to one bit binary pixel. The proposed error diffusion method is based on half toning method, which is known as Floyd and Steinberg’s filter. To expedite processing time, the denominator of the proposed method is chosen in 2k form, where k is integer number. Therefore, the method is faster than the previous methods, while preserving simplicity. Experimental results show that the obtained red, green, blue channels and color images look satisfactory for viewer.

A global optimal algorithm derived from electromagnetism-like mechanism (EM), called as enhanced searching electromagnetism-like (ESEM) algorithm, was developed in this paper. The original EM is a meta-heuristic algorithm utilizing an attraction-repulsion mechanism (called as force F) to move sample points towards optimality in global optimization problems. Compared to the original algorithm, the best historical visited positions of each point were added into the search process in the improved algorithm. In ESEM, the search direction and step length of points were determined together by its best previously visited position, best point in current swarm and total force F. Preliminary experiments showed that additional best historical positions can help to improve the convergence property. More importantly, the improved searching mechanism can effectively solve the problem of stagnation of the original algorithm caused by too small values of force F.

As the rate of internet users is increasing on a daily basis, a tremendous amount of these users are accessing online streaming websites and applications. This paper proposes a live streaming architecture that supports traffic balancing during peak times and bitrate adaptation. Rather than replicating content on multiple servers, we implemented traffic balancing by assigning a temporary regional server to manage the traffic at regional area. Bitrate adaptation at server side was also proposed and implemented to provide a fair video quality to all users. Through a few tests that has been run on the testbed, we can see the live video streaming was move seamlessly from one server to another server with an acceptable video quality among the users.

Panel acoustic contribution analysis (PACA) is an advanced engineering tool for noise control and acoustic design in a cabin. In this study, a novel computational method for PACA by using Helmholtz equation least squares (HELS) based on nearfield acoustical holography (NAH) was proposed. According to the new very definition of panel acoustic contribution, formulations of the present method are derived to analyze the relative panel acoustic contributions of each panel in the interior sound field. The significance of this methodology is that it can provide either positive or negative contribution and rank relative acoustic contributions of individual panels to acoustic radiation anywhere in the field based on a single set of the acoustic pressures measured in the near field. A numerical simulation of a scaled vehicle cabin has been investigated to demonstrate the validity of this method. Moreover, the results show the advantage of the proposed method, since it could reflect the contributions of individual panels more correctly than the ranking of acoustic power.

For the problem of compute nodes load unbalance leads to the overload node impact VM performance and the underload node waste electrical energy. Dynamic VM consolidation is an efficient approach for improving the utilization of servers and reducing energy costs. In this paper, we introduce dynamic consolidation into OpenStack and implement AMVM based on OpenStack. AMVM collect and analyze all performance data of VM and compute node in OpenStack. Then AMVM automatically schedules VM live migrate to the most appropriate node according to the real-time load of all compute nodes. Then we use hybrid-copy instead of pre-copy in AMVM to improve the efficiency of VM live migration. Finally, we analyze the performance of hybrid-copy, hybrid-copy can reduce page faults compared with post-copy and reduce total data transferred compared with pre-copy.

In order to verify the feasibility of the method of numerical simulation of supersonic noise, the flow field and noise at far field of a small solid fuel rocket engine F tested by National Aeronautics and Space Administration's Langley Research Center (NASA) was simulated by computational fluid dynamics (CFD) and computational aeroacoustics (CAA). The conjunction with large eddy simulation and FW-H integral method is adopted to simulate spectrums of the noise. The conjunction with large eddy simulation and Möhring sound analogy is adopted to predict the direction of the noise at the near-field. Comparing the result with the experimental data, the flow field coincides well, and in the sound field, the low and medium-frequency sound pressure level coincides well too, and the high-frequency sound pressure level is slightly lower than the estimated value. The error of overall sound pressure level of the measure point is small. The sound field resulted by high temperature, high pressure and high velocity fluid is simulated successfully.

Firefly Algorithm is a nature-inspired optimization method, which has been shown to implement well on numerous optimization problems. But it can easily fall into the local optima and low precision. Therefore, it is very important to overcome these defects. In this paper, we use a dynamic strategy for step setting, which takes into account the population diversity of fireflies. The experiments show that the proposed algorithm improves the performance of original firefly algorithm.

By using empirical data collected from 278 manufacturing firms in Korea, this study investigates the relationship between technological innovations (i.e., product and process innovations) and non-technological innovations (i.e., organizational and marketing innovations) and innovation success. We propose that non-technological innovation is considered an essential precondition of technological innovation, leading to innovation success. We highlight that technological innovation exerts a strong influence on innovation success only when non-technological innovation adequately strains the relationship between them. The findings of this study show that the indirect effect of non-technological innovation on innovation success through technological innovations enables firms to enhance firm performance and that no synergistic effect exists between technological and non-technological innovation on innovation success.

In order to improve the fault positioning accuracy of distributed generation power distribution network, it puts forward fault positioning method of distribution network equipment based on blended data association rule data mining method. Based on fuzzy rough set theory, it studies classification rule mining method on hybrid data, through the introduction of the rule to obtain the a generalized threshold of the algorithm, and control the scale and complexity of the obtained rule set, so as to improve the classification efficiency of rough set method of knowledge discovery on the failure data and get the fault positioning feature of distribution network, finally adopts the support vector machine (SVM) to make fault classification, and tests the performance of the algorithm with simulation experiment. The simulation results show that, this paper can be quickly and accurately to locate fault power section, and the fault positioning accuracy is higher than other fault positioning methods of distribution network.

In allusion to such problems in the traditional face recognition methods as poor recognition accuracy and dissatisfactory processing effect for directivity and anisotropic characteristic in face data, lasso regularized Gabor shearlet face multivariate sparse function approximation algorithm is proposed in this article. Firstly, Gabor improved shearlet algorithm is adopted at the level of the face-image biological signals for the sparse expansion representation of the face data characteristics, and meanwhile this algorithm is also adopted to extract the geometrical characteristics of the expansion face with directivity and anisotropic characteristic. Secondly, in order to balance the algorithm effect, lasso regularization theory is introduced therein to control and weigh the relation between the fidelity and the smoothness of the face data. Finally, the corresponding simulation experiment is carried out to compare the proposed algorithm and the existing algorithms in the standard test database in order to verify the advantages of the proposed algorithm in the aspect of face recognition accuracy and efficiency.

Multimedia messaging in instant messenger (IM) application (app) usage has become increasingly popular on smartphones today. Sharing of multimedia messages such as images, web links, videos and audio messages has become prevalent on smartphones. The IM app causes smartphone battery to drain owing to its intensive data upload / download operations when users share multimedia messages. This work focus on instant messenger app performs upload / download to share multimedia message impact on a smartphone battery. Our collected data shows that IM users share a large number of redundant multimedia messages with server side and also existing in local storage. A redundant network traffic directly can increase access wireless network (3G or Wi-Fi) usage and leading to high energy consumption in a smartphone. This paper proposes an energy efficient multimedia message sharing scheme to prevent redundant network traffic. The underlying principle of the proposed design is verifying hashes of shared multimedia messages prior to an instant messenger application uploading or downloading them. Our evaluation shows that our proposal saves up to 60 % of energy consumption.

The synchronization technology is one of the key technologies in fast frequency hopping communication system. The performance of synchronous loop will directly affect the whole performance of the fast frequency hopping communication system. In view of the deficiency of synchronization time and synchronization anti-interference in the existing synchronization methods, an improved synchronization acquisition method is put forward, that is double judgment circular correlation method. The test results show that the improved synchronization acquisition method can effectively improve synchronization speed, increase synchronization anti-interference performance and reduce the complexity of synchronization loop.

LID facilities on the green area-sidewalk-road in cities can be applied in different types and forms according to the status and characteristics of a space. There are some limitations of using LID facilities with respect to area, these limitations can overcome by using the suitable combination of LID practices in an area. For this purpose, the Water Cycle Sidewalk (WCS) was used through the connections of various LID techniques. The WCS could manage stormwater runoff and water quality in a space adjacent to green area-sidewalk-road as a part of WCS, a permeable block pavement (PBP) was installed on the sidewalk, and a vertical infiltration pipe (VIP) and an infiltration-storage tank were located underneath the PBP. Runoff on the sidewalk was pre-treated by a first flash treatment facility and then stored in a storage tank for watering the green area. The average infiltration capacity of a PBP with a storage tank under the pavement was 0.30 mm/sec, about 6 times higher than that of a general PBP section. From the results, the infiltration capacity of a single VIP was approximately 0.35 mm/sec. The overall efficiency rate of runoff reduction from this facility was between 50% and 70%. In addition, the rainwater in the Storage Tank analyzed to be appropriate to use water for landscaping.

This paper presents design and implementation of an attitude and heading reference system (AHRS) based on Gauss Newton and Complementary Filtering algorithm (CF). The algorithm uses data measured from the MEMS sensor which contains a three-axis magnetometer, a three-axis angular rate sensor, and a three-axis accelerometer. The filter represents rotations using quaternions rather than Euler angles, which eliminates the long-standing problem of singularities associated with attitude estimation. A process model for rigid body angular motions and angular rate measurements is defined. The process model converts angular rates into quaternion rates, which are integrated to obtain quaternions. The Gauss-Newton iteration algorithm is utilized to find the optimal quaternion that relates the measured accelerations and earth magnetic field in the body coordinate frame to calculated values in the earth coordinate frame. Then fuse the optimal quaternion with the quaternion updated from gyroscope and calculate the attitude angle based on the complementary filtering algorithm . Extensive testing of the filter have proved feasibility and acceptable performance of this AHRS design.

Particle swarm optimization (PSO) algorithm is a population-based search algorithm by simulating the social behavior of birds within a flock. It is a simple and efficient optimization algorithm. But it exists the low computational speed and easy falling into local optimal solution in solving the complex problem. So the quantum theory, adaptive inertia weight, disturbance factor and diversity mutation strategy are introduced into the PSO algorithm in order to propose an improved PSO(IWDMDQPSO) algorithm in this paper. In the IWDMDQPSO algorithm, the quantum theory is used to change the updating mode of the particles for guaranteeing the simplification and effectiveness of the algorithm. The adaptive inertia weight is used to improve the premature convergence of the algorithm. The disturbance factor is used to avoid the premature of the algorithm. The diversity mutation strategy is used to improve the global searching ability and computation speed. Finally, the famous benchmark functions are selected to prove the performance and effectiveness of the proposed IWDMDQPSO algorithm. The experiment results show that the proposed IWDMDQPSO algorithm takes on better solving accuracy and higher computation speed in solving the complex function. So it has a remarkable optimization performance.

As accidents and crimes have increased at an alarming rate lately, most people are faced with the necessity of security and surveillance in private places as well as in public places. Therefore, the demand for intelligent surveillance systems has been increasing, and various technologies for image recognition and analysis from cameras are being developed for use in automatic monitoring. Among these techniques, the most popular and advanced method is deep learning. It is a field of machine learning based on neural networks. In this paper, we propose the object classifier technique with the Convolutional Neural Networks (CNN) algorithm, which is most widely used in image processing. Additionally, we implement the image analysis bot system based on the above proposed algorithm.

Aiming to the traditional acoustic detection array with measuring the target coordinate, the accuracy of measurement data is affected by the propagation velocity of the acoustic pressure. This paper proposes a new measurement method, which obtain the mathematical model of the target parameter information when the target passing through acoustic sensor array based on acoustic array structure establish. From the model the target parameter information is just associated with the respective probe element’s delay time of the acoustic pressure when the target passing through the acoustic detector, thereby it is effective to avoid the measurement accuracy influence from acoustic pressure velocity of the target parameter information. In order to obtaining the signal characteristics when the target passing through acoustic detector array, it would adopt time-frequency transform method to analyzed signals of the target through the acoustic array. By the simulation experiment it can improve the measurement precision of the target parameters information, and get frequency-domain characteristics of target information based on the measured analog signals of acoustic pressure. The result is benefit to enhance precision of target parameter information from acoustic array detection system, and it has certain guiding significance for the study of acoustic array structure.

Fuzzy search algorithm with hybrid semantic similarity is proposed aiming at serious performance issues in information retrieval, which results from fuzzy search condition, in search engine land. First of all, new conceptual extraction method is proposed according to similarity calculation concept; after that, TF-IQF is adopted to divide the link into tabs, and the set comprised of these tabs is used for indicating the query; ultimately, binary graph is constructed to identify related queries and is employed to compute query similarity. Experimental results show that proposed algorithm has achieved better recall ratio, retrieval precision and F-measure compared with clicking document, related queries and reverse query algorithm.

Binary-tree support vector machine (SVM) has such advantages as small repeated operation workload, fast classification speed and dead zone inexistence, but the structural design can influence the classification accuracy thereof. In order to rationally design the structure of the binary-tress SVM, a multi-classification algorithm (AHP-BSVM) combining analytic hierarchy process (AHP) and binary-tree SVM is proposed in this paper. Firstly, the analytic hierarchy process is adopted to establish the evaluation system model so as to comprehensively evaluate multiple influencing factors for determining the weight values of various faults; then, the faults are ordered by the weight values and the structure of the binary-tree SVM is determined according to the fault sequence; finally, the proposed algorithm is adopted for fault diagnosis and analysis. The simulation experiment shows: compared with other algorithms, the proposed algorithm has higher recognition accuracy and higher classification accuracy, and is applicable to multi-classification, thus having good promotion prospect.

Many of fuzzy control applications require real-time operation; higher density programmable logic devices such as field programmable gate array (FPGA) can be used to integrate large amounts of logic in a single IC. This work, proposes a developed method to fuzzifier algorithm with optimal-tunable gains method-using FPGA. The maximum frequency in FPGA-based design is about 72.4 MHz and the delay time in this design is about 13.78 ns. It is observed that this algorithm is able to make as a fast response at 13.78 clock period with 72.4 of a maximum frequency and 2.1 ns for minimum input arrival time after clock. From investigation and synthesis summary, 24.3 for maximum input arrival time after clock with 13.9 MHZ frequencies, this design has 13.78 ns delays for each controller to 46 logic elements and the offset before CLOCK is 82.1 ns.

The main problem of empty containers repositioning (ECR) is to dispatch the empty containers among the ports meanwhile cut the costs as possible as. According to the actual operations, the stock policy and various constrains are considered together in this paper firstly. Then we build a multiple periods minimal cost programming optimization model with stock to solve this problem. Furthermore, we adopt the heuristic rule to effectively operate the empty containers since there is a large amount of calculation. Finally, some simulate data are given to assess the model. The results show that our proposed model is feasible and efficient to minimize the operation cost as well as satisfy the demand of customers. Moreover by analyzing the data it can guide us to set the inventory of empty containers of ports in different supply and demand scenarios.

It is unclear to what extent accounting information can reduce capital risks related to the expected return on a firm’s stock, this is a nonlinear problem; meanwhile, PCA-BP method is suitable for nonlinear problem. This study evaluates accounting information' effect on listed companies' capital cost at Stock Exchange based on PCA-BP method. Results show that implementation of accounting information at listed companies can evaluate the cost of capital by the internal controls, the quality of the financial reports and the process of the company’s transactions. Our finding provides a direct link between the evaluation of a firm's accounting information and its cost of capital.

As the FACTS controllers are an inequitable part of power system due to their fast and very flexible control. With the enhancement of FACTS technology, their role in the marginal cost determination should be considered taking their cost function into account. The aim of this paper is to compare the optimal performance of static VAR compensator (SVC) in voltage stability enhancement problem. During last decade, FACTS devices are broadly used for maximizing the margin of voltage stability and loadability of existing power system transmission networks. To get the optimal system, cost analysis might be necessary. In the cost analysis of SVC, authors analyzed the installation cost of SVC devices in USD, the cost of SVC in USD/KVAR and the average value of installation cost for given systems. Here, the voltage stability enhancement problem is solved applying Gravitational Search algorithm incorporating SVC. The following conditions are investigated with the incorporation of SVC: the role of SVC for improving the voltage profile, loss minimization and the approximate analysis on cost recovery and payback period with SVC in voltage stability enhancement problem. With this motivation, the location of SVC is finalized through weak bus identification methods. Voltage stability indices namely Fast Voltage Stability Index (FVSI) is utilized to identify weak buses in the systems. For calculation of the Size of SVC, an optimization routine Gravitational Search Algorithm (GSA) is established. The main purpose of optimization is to minimize the FVSI. The proposed approach has been tested on three standard IEEE bus systems with different loading scenarios. General Terms: Flexible AC Transmission System (FACTS), Marginal Cost, Voltage Stability Assessment, Static VAR Compensators.

Coking production process is very complex, and full of risk factors, toxic and harmful substance, it’s a typical high risk industry. In view of the prominent safety hazards and strong interference to safety monitoring in coking production, put forward a kind of safety monitoring and warning system based on information fusion for coking production. To achieve the target that safety condition was monitored accurately and hazardous situation warned reliably, safety information of the monitoring and warning areas was collected by sensor network which include combustible gas sensor, dust sensor, temperature sensor, pressure sensor, flowmeter and IP camera ,and the information fusion model of safety monitoring and warning was established, and then, through the BP neural network and the D-S evidence theory algorithm, various safety information was fused. Actual tests show that it has achieved the goal that monitoring accurately and warning reliably. It is of great significance to ensure the security of coking production.

In the practical application of Ultra Wideband (UWB) through-wall radar imaging, the walls that are generally encountered consist of multiple layers, and there may be multiple targets, which presents challenges for the imaging algorithm. In this study, both the back-projection (BP) algorithm, which is a time-domain algorithm, and the phase-shift migration (PSM) algorithm, which is a frequency-domain algorithm, are used to locate two targets behind a two-layer wall. The image quality, the azimuth and range resolutions, the image entropy and the processing time of the two algorithms are compared. The simulation results demonstrate that the BP algorithm produces better image quality and that the PSM algorithm is faster. The effect of the sampling interval on the image entropy and processing time is discussed. In addition, the feasibility and the validity of the two algorithms are tested under noisy conditions. The results show that the two algorithms are robust, regardless of the presence of noise.

This paper proposes a new method for measuring the wind speed in the pipe, which overcomes the shortcomings of the traditional mechanical instrument with lower accuracy and ultrasonic measurement method with the high cost, it has the advantages of low cost and high precision. This paper introduces the principle of pendulum method to measure wind speed, the wind speed in the pipe is calculated by the space angle based on the spatial geometric relationship. On the other hand, the space angle is obtained by horizontal angle and vertical angle, which are gathered by the cameras placed in the ends of the bracket. Image processing technology is an important part of this method, including the image gray processing, binarization processing, edge detection and Hough transform steps, at last, the experimental results proved the feasibility of this method.

Numerous studies have focused on feature selection using many algorithms, but most of these algorithms encounter problems when the amount of data is large. In this paper, we propose an algorithm that handles a large amount of data by partitioning the data to process a reduction, and then selecting the intersection of all reducts as a stable reduct. This algorithm is successful but may suffer from loss of information if the samples are unsuitable. The proposed algorithm is based on discernibility matrix and function. Furthermore, the method can address the case in which the data consist of a significant amount of information. Our results show that the proposed algorithm is powerful and flexible enough to successfully target a range of different domains and can effectively reduce computational complexity as well as increase reduction efficiency. The efficiency of Proposed Algorithm is illustrated by experiments with UCI datasets further.

This research focuses on online reviews deviation in B2C platform, and tries to analyze the phenomenon that shops which have large sales volume are lowly recommended compared with the average in Tmall. After verifying the validity of online reviews, we find out that the consumers' sensibility for negative comments become weaker. And the sellers’ sincerity that reflected by their replies to negative comments have little influence on sales. Only the number of total comments and positive comments can obviously influence on sales . Shops, in B2C platform, just concern about taking part in sales promotion to create hot products, instead of devoting to the quality of service. B2C platform whose primary business is selling entrance of users flow, prefers to protect large sellers, and the unreasonable rules in online reviews is the main reason for partial failure in the influence of reviews to sales.