Earticle

The joint replenishment and delivery model with deterministic resource restriction for deteriorating item is developed. The model is formulated as cost minimization problem, including the ordering cost, the inventory holding cost, the transportation cost, the customer waiting cost and the deterioration cost. Differential evolution (DE) algorithm is proposed to solve the model. Numerical illustrations of the model and algorithm are presented and the sensitivity analysis with respect to deterioration rate of item is performed. The comparison between DE and genetic algorithm (GA) for solving the model are also made.

Multi-core processors have become the dominant market trend because they provide a great opportunity in increasing processing performance by exploiting various parallelisms. In JPEG (Joint Photographic Experts Group) compression, color space conversion is one of the major kernels known as a computationally expensive module. This paper presents a fast solution for color space conversion with multi-core parallel computation. For this purpose, we utilize Threading Building Blocks (TBB), a runtime library based on C++, and OpenMP (Open Multi-processing), a shared programming language. A RGB image is transformed into a luminance-chrominance color space such as YCbCr. The implementation results show that parallel implementations achieve greater performance improvement regarding processing speed compared with the serial implementation.

Compressed sensing is a new signal sampling theory that fully makes use of signal’s sparsity or compressibility. The theory shows that, the acquisition of a small amount of the sparse or compressible signal value can be used for exact signal reconstruction. Based on the study and summarization of the existing reconstruction algorithms, this paper proposes a novel blocking variable step size forward-backward pursuit (BVSSFBP). This paper proposed variable step size forward-backward pursuit algorithm by introducing the concept of sparse phase and variable step size to deal with different situations. The algorithm also divides two-dimensional image into blocks, in order to reduce the scale of observation matrix during single processing, reduce the single processing speed and the overall running time. Experimental results show BVSSFBP algorithm can obtain better reconstructed image quality.

For moving objects detection, a background subtraction algorithm based on adaptive Gaussian mixture model is proposed in order to extract moving regions. The OTSU algorithm is researched in order to adapt to the changes in the background images; In order to accelerate model updating rate, a novel mechanism is the combination of expected sufficient statistics and L-recent window.

In the present article, an algorithm is obtained for calculating the speed of a golf ball that flies after being hit by the head of a golf club. First, the golf club moves at a given speed to hit the golf ball. Then, the head of the golf club moves forward in the same direction at a given speed. At this time, the speed of the golf ball flying upon impact of the golf ball with the club head is calculated. The purpose of the present article is to calculate the speed of the club head, the impact, the speed of flying ball after the impact, the moving directional pattern of the ball after impact, etc. Results of the study through experiments and implications as well are exhibited in details.

Face recognition is a well-known approach for identity recognition. Variation in head pose is a main factor that interferes with face recognition systems. This paper proposes an efficient head pose determination method and its application to face recognition on a multi-pose face DB in order to solve the pose variation-related problem. The first step is to detect a facial region using Adaboost. Next, after undergoing preprocessing on the detected face, a mask is placed to cover it. At the detected facial region, the pose is determined by relations of the position of the centroid points of the eyes and lip regions detected by using ellipse-fitting method. Finally, face recognition is conducted by applying template matching between a set of facial images in multi-pose face DB pertinent to the determined head pose and the input face image. In experiments, the proposed approach outperformed the conventional PCA-based face recognition approach depending on a single-pose face DB.

Electrical industry is with the rapid development. Vacuum circuit breaker, with advantages of good arc resistance, suitable for frequent operation, long electrical service life, high reliability, long maintenance cycle, has been widely used in many applications. Modern conditions need high voltage vacuum circuit breaker and it has a difference with common vacuum circuit breaker. Mechanism characteristics are a most important aspect for the vacuum circuit breaker and more attention should be paid attention. In this paper, mechanism characteristics are studied for a certain model of vacuum circuit breaker and a simulation method is developed. With the method, curves variation of travel, speed, length increasing of contact spring with time has been developed and given in the paper. With responsible device, some parameters are tested in the experiment. The test results show that the simulation results are coincidence with the test results, which mean the effect of the simulation method. Mechanism characteristics can be well described with the model the paper proposed.

To test the effectiveness of flash intensity in digital close-range photogrammetry, test methods for the light intensity adjustment of a ring-flash on close-range photographic imaging quality and measuring precision were researched respectively. First, according to the efficiency of the flash, the imaging characteristics, and the gray distribution of the mark points of the image, the identified method of the image gray value for subjective visual analysis was presented, and a quality standard for the close-range photographic image was provided. Then, as a precondition to obtaining the best image quality, based on the estimation theory governing measurement adjustment precision, the changes in measuring precision under conditions of different light intensity and different photographic distances were analysed, and the relationships between measurement precision and light intensity, or photographic distance, were obtained. Finally, the globally optimal imaging quality and measurement precision for any given light intensity were quantified. Experimental results indicated that the root mean square (RMS) errors of the measurement adjustment precision were 0.028 mm, 0.039 mm, and 0.085 mm: the RMS errors in the measuring precision and the corresponding coordinate repeatability were 0.038 mm, 0.053 mm, and 0.118 mm. The best imaging quality was achieved at photographic distances of 3 m, 5 m, and 7 m, with corresponding output light intensities of 1/64, 1/32, and 1/16 under certain conditions, respectively. This can satisfy the precision requirements for large-scale coordinate measurement, and provides a basis for formulating a reasonable light intensity output from a ring-flash in the digital close-range photogrammetry.

Many textures based image retrieval researchers use global texture features for representing and retrieval of images from an image database. However, this leads to misrepresentation of local information leading to the inefficient image retrieval performance. This paper presents an approach to overcome the problem. The approach focuses on extracting local Haralick’s texture feature based on a predetermined region using the color co-occurrence matrix method, the selection of the ‘significant’ Haralik’s texture features and evaluation of the performance of the combination of the ‘significant’ features. The proposed method which is an Average Analysis and a well known method, Principal Component Analysis were applied to obtain ‘significant’ features. In order to compare the performance, a series of experiments were carried out for both methods, which is the proposed Average Analysis and the Principal Component Analysis. Experiments were performed on a 1000 selected images from the Coral image database which were divided into ten categories. Based on the experimental results, it is interesting to note that for the combination ‘significant’ features obtained from the proposed Average Analysis showed better retrieval performance compared to the Principal Component Analysis for almost all categories. This finding has an important implication in deciding the correct combination of ‘significant’ features for certain image properties. It has shown that the proposed method is able to produce less computational processing time due to a reduced amount of processing involved. The result is also compared to the previous researches and has shown an increase of an average precision from 8.5% to 26%.

The precise measurement of the geomagnetic element is the key to realize navigation and positioning with the development of geomagnetic navigation technology. In this paper, a kind of underwater vehicle three-component geomagnetic field differential measurement method is presented based on the ideas of the difference. The threecomponent geomagnetic field mathematical model of traditional measurement method is improved and new differential measurement model(DMM) is established. Difference expressions of measurement magnetic field in the DMM obviously reduce the impact of interference magnetic field in the process of geomagnetic field measurement and improve the measuring precision of the three-component geomagnetic field. Finally, the method’s effectiveness is validated by simulation. The precision of DMM method is 10 ± 5nT which is about two times that of traditional measurement model (TMM) method under the condition of ± 25nT stray outside interference magnetic field. The method effectively improves the geomagnetic field measurement precision and has stronger antiinterference ability. It is of significance for practical application of underwater geomagnetic navigation method.

Aiming at the problem of limited logical resources of FPGA and low rates of internal resource utilization, the design of the static reconfiguration system was introduced in this paper. Based on the structure of CPLD matching FPGA, the static reconfiguration system is able to enhance the scalability of the FPGA device. Major functionality in the static reconfiguration system is accomplishing field reconfiguration of the FPGA device without PC. Users are able to flexibly change the different configuration files in FPGA for that the internal resources of FPGA are occupied by the configuration files of different function at different times. The experimental results showed that the system achieved dynamic switching between different logic function and time division multiplexing of internal resources. The generality of FPGA and the rates of internal resource utilization were improved and the power dissipation was reduced by this design.

In this paper, a 4-port broadband mobile phone multiple input multiple output (MIMO) antenna is designed and implemented for use in femto cell communications. The assembly consists of 4 antennas with one main antenna that covers the entire design band and 3 sub antennas that cover the data communication bands. Each of the antennas is located on the top and bottom corners of the bare board, and we tested them on a PC board with the same board ground circumstances as practical phone ground. The main antenna operates in the CDMA, GSM, LTE class 2~3 and class 33~34 service bands, and the sub antenna operates in the LTE class 1~4, and Wibro band for data communications. The voltage standing wave ratio (VSWR) was less than 3:1, and the maximum isolation between the antennas was -8.5dB over the entire design band. The average gains for the main antenna were measured from -2.48 to -0.54dBi, with efficiencies from 56.45 to 88.3% while those for the sub antennas were between -1.96 to -1.2dBi and 63.75 to 75.92%, respectively. The envelop correlation coefficient (ECC) for the MIMO system was under 0.148 over the entire data communications band.

The quantum particle swarm optimization (QPSO) algorithm exists some defects, such as premature convergence, poor search ability and easy falling into local optimal solutions. The adaptive adjustment strategy of inertia weight, chaotic search method and neighborhood mutation strategy are introduced into the QPSO algorithm in order to propose an improved quantum particle swarm optimization (AMCQPSO) algorithm in this paper. In the AMCQPSO algorithm, the chaotic search method is employed to promote the quality of initial population. The adaptive adjustment strategy of inertia weight is used to adjust the global search ability and local search ability of particles in the running process of QPSO algorithm. The neighborhood mutation strategy is used to increase the diversity of population and avoid premature convergence. Finally, in order to evaluate the performance of the AMCQPSO algorithm, several well-known benchmark functions are selected in this paper. The experiment simulations show that the proposed AMCQPSO algorithm can effectively improve the quality of solutions, and takes on powerful optimizing ability and more quickly convergence speed.

Geometric transformations such as rotation or mirroring of JPEG images may result in image quality distortion. Our experiments found further quality degradation of rotated JPEG images as the number of rotations increases. In this paper, we propose a fast and lossless JPEG image transformation in spatial domain based on changes of discrete cosine transform (DCT) coefficient in frequency domain. The key idea of our proposed approach is that permutation and/or sign changes of DCT coefficients in JPEG image results in geometric change without any information loss. Our experiments shows that the proposed transformation algorithm results in no information loss and is faster than conventional methods by 1.67 times on average.

Owing to flat plate induction heating can’t guarantee to heat equally, especially the existence of no heated zone, it haven’t been used in these industrial fields like SMD which require high accuracy and easy to control while heating. But some places need its characteristic of contact heating, eco-friendly and high efficiency, for this reason, it is fundamental to research the heating style further as well as the no heating zone. Because induction heating is based on eddy current, firstly, the relationship between eddy current and induction heating is explained and several factors which would influence the eddy current are put forward. Then finite element analysis and calculation of eddy current field is mainly done. At last, the conclusion is obtained by analyzing the results of calculation. Due to the analysis above, after improving the structure of the iron plate, the problem of no heating zone is solved. At the same time, the efficiency evaluation is brought out. It can make the following research more easily.

Software Defined Networking (SDN) is an open source networking framework recently introduced. It allows developers to program and reprogram the network so that intelligence and new features can be integrated to optimize and enhance the performance of the network. This paper is focused on optimizing the routing implementation of SDN (i.e. SDN Controller). We have used the Floodlight Open Source SDN Controller1 in our experimentation. The Floodlight controller provide source Java libraries and APIs.. It uses Dijkstra’s algorithm to calculate the shortest path between any source and any destination within the network. However, the default routing implementation of Floodlight Controller is such that, while calculating any path, it ignores the actual bandwidth of the link as it takes a unit value for each link. The resultant calculated path becomes a least hop path. This least hop path may be an optimal path where all the links in the network have equal bandwidth and may not be optimal where the networks have unequal link bandwidth. However, today’s networks are mostly consisting of unequal link bandwidth. The goal of this paper is to re-structure the Floodlight Controller so that it can collect the actual bandwidth of all the links in the network and use this information to calculate

In order to enhance prediction precision of online public opinion, it put forward a kind of online public opinion prediction model (PSR-SVR) with the combination of chaos theory and support vector regression. First of all, the original data of online public opinion were obtained throughout topic segmentation, hotspot extraction, and data aggregate. Then, time sequence of online public opinion was reconstructed throughout phase-space reconstruction. Finally, the reconstructed time sequence of online public opinion was input support vector regression for modeling and prediction, and then it was compared with other online public opinion prediction model by experiment. The result shows that compared with the contrast model, PSR-SVR improves the prediction precision and reliability of online public opinion, and the prediction results have certain practical value.

Fast mode decision algorithms in video intra coding are very useful and necessary for implementing practical real-time performance of the encoder. It can reduce the computational complexity by excluding impossible modes from candidate set. Anyway, most of these algorithms may give rise to the remarkable quality degradation, especially for the all intra coding scenario. In order to improve the encoding speed while avoiding the quality loss, this paper presents a new algorithm for fast CU size decision and mode decision in HEVC intra coding. First, the size of the coding unit is pre-determined according to judging the coding unit whether has the sub-block whose depth is 3 and analyzing the depth of the adjacent CU. Then a judgment by block-DCT coefficients is made on the texture direction of image block, determining candidate mode set based on the calculated direction and the best prediction mode of the adjacent block, which can reduce the number of candidate mode, thereby reducing the amount of computation to save coding time. The experimental results show that the algorithm provides about 34.6% reduction of intra coding time compared with the latest HM13.0 with negligible loss of PSNR and a little increase of bite-rate.

In order to verify the integrity of the original voice and determine the voice match, researches on analyzing speakers' own voice have been undergoing. However, spectrogram and waveform analysis technologies that are currently used have issues of lack of accuracy and reliability when determining the voice match. In this paper, ways of determining and performing voice match are suggested and proven by confirming the original voice frequency form of each individual with voice analysis methods using spectral contents. Also, the circuit for correcting or improving the quality of voice is designed and proposed. When the form of voice recording signals was analog, improved voice analysis data was secured by eliminating unnecessary noise and increasing property during PCM process. Thus, portability of voice analysis more enhanced than existing research results was verified and studied.

In this paper, an enhanced data driven model-free adaptive yaw control tracking control scheme is proposed for the yaw channel of an unmanned-aerial-vehicle helicopter that is non-affine in the control input. By dynamic linearization and observer techniques, the proposed control algorithm is only based on the PPD parameter estimation derived online from the I/O data of the controlled system, and Lyapunov-based stability analysis is used to prove all signals of close-loop control system are bounded. Compared with the traditional model free adaptive control, the proposed enhanced model free control algorithm can make the closes-loop control system with stronger robustness and better anti-jamming ability. Finally, the simulation results of the dynamic model of a real helicopter-on-arm are offered to demonstrate the effectiveness of the proposed new control techniques.

To improve the accuracy of model predictive control, this paper presents an improved multiple cell linear parameter varying model predictive control method for carrier-based aircraft. After establishing the lateral dynamic model of carrier-based aircraft for multiple cell predictive controller, the output-feedback linear parameter varying control based on states observation should be implemented. The model simulation results indicate the better performance of the new method in comparison with the traditional controller with more accuracy and practicability.

RT-based Concealed Information Test (CIT) has been suggested to detect lying with high accuracy. However, because previous research have been conducted with a minimum of five probes, limited evidence is available to determine whether or not the RT-based CIT is also useful in precisely detecting lies with less than five probes. In this study, the accuracy of an RT-based Concealed Information Test (CIT) was examined by varying the numbers of probes used for the test. Results suggested that the RT-based CIT produces accurate lie detecting outcomes as the number of probes increases from a single probe to three probes. When five probes were used, however, the accuracy level did not improve from the level achieved with three probes. Interestingly, the accuracy decreased when the stimuli for the RT-based CIT were constructed with numeric elements of an event such as the amount of money. Further discussed are possible explanations in regards to the differences observed in the RT-based CIT accuracy rates dependent on the numbers of probes.

In the process of freshwater fish farming in pond, the levels of dissolved oxygen must be monitored by creating a closed loop PID control system. But traditional PID controller has weak stability and slow response speed, because dissolved oxygen changes with delay. In this paper, a PID control algorithm with optimal Smith predictor is proposed, to eliminate negative effects caused by delay component. The result of experiment data indicates that the optimal algorithm can reduce settling time and overshoot, and has better robustness and disturbance rejection performance than traditional PID controller. Meanwhile, a hardware circuit design plan based on ARM Cortex-M3 embedded processor is supposed, which gets stronger performance than C51 MCU control system with traditional PID algorithm. The hardware selection and plan design realize high cost performance, it is valuable to small and medium freshwater aquaculture enterprises.

Context fusion is a very important aspect in a system that has to adequately simplify a required task in achieving context awareness in the Internet of things (IoT). IoT generates a large amount of data, which are massive, multi-source, heterogeneous, dynamic and sparse. Context information fusion is an important tool in the manipulation and management of these data in order to improve processing efficiency, provide advanced intelligence and increase reliability. Context information fusion can reduce the amount of data traffic, filter noisy measurements, and make predictions and inferences in any stages of data processing in IoT. As such when context is acquired from this domain, it has low confidence level due to reliability factors. In this paper Context information’s reliability has been addressed through the use quality of context (QoC) by determining the combined confidence for acquired context from multiple sources. Particle Swarm Optimization selects the context information with the highest level of confidence and Dempster Shafer rule of combination fuses this context into more reliable information that can be used by the system to effectively adapt to changing context. From the obtained results the proposed solution indicates an improved fusion process with increased confidence.

This paper presents a RST (rotation, scaling and translation) invariant reversible watermarking method for 2D vector maps. Firstly, the proposed algorithm selects two reference vertices to calculate the normalized quantization step. Then, for each vertex, the Euclidean distance between a reference vertex and the vertex is divided into equal segments using the normalized quantization step. According to the segment which the vertex is divided into, a watermark is embedded by moving the vertex within its corresponding segment in a revertible manner. This algorithm not only recovers the original content after watermark extraction, but also correctly extracts the embedded watermarks after RST transformations. In addition, to control the distortions introduced by watermark embedding, the embedding parameter is carefully selected. Theoretical analysis and experimental results show that the proposed scheme provides RST invariance property, and good reversibility, invisibility, computational complexity and data capacity.

Based on the concentrated parameters theory, a 7-freedom coupled vibration dynamic model of the spiral bevel gear transmission system is established, which includes transmission error, time-varying mesh stiffness and the tooth backlash clearance. In the model, the axial vibration, the torsion oscillation of the gear pair aroused by tooth meshing force and the lateral oscillations resulting from flexional deformation of the gear shaft are taken into account. The mesh stiffness fluctuation is developed as 5-order Fourier series and the tooth backlash clearance is fitted by 7-order polynomial function. Through the Gear method, the dynamic response of the system is obtained, and the vibration characteristics are analyzed.

For amateur astronomers, it is not easy to find a specific celestial object in the night sky. The celestial calculations are also complex and hard to be correctly achieved. However, there are very few numbers of supporting tools for them. We represent a 3D celestial map rendering platform which reproduces the virtual night sky at the specific time and location. With the OpenGL-based full 3D-graphics features, our platform brings a sense of spatial realism, with user-friendly interfaces. For the more accurate celestial map rendering, we referred to a set of more than 10,000 stars from the famous celestial lists such as the Messier list, the Yale BSC list, and others. For each celestial object, our system provides three-dimensional views and additional two-dimensional simulations for more details. Since it is developed on typical PCs, our system can provide accurate celestial maps in an interactive manner, without any special equipment. Our system is helpful for amateur astronomers and ordinary persons to find the specific celestial object in the real night sky.

Field programmable gate array (FPGA) has the characteristics of high speed, low power consumption, high integration, flexibility and, small size, etc. In this paper, I design a real time infrared image processing and display system based on FPGA for the requirement of real time infrared image processing, which will realize the transmission, transformation, and storage of the image information, and then complete the infrared image edge detection based on Sobel algorithm by using this system as a platform. At last, the advantages of infrared image processing with this system compared with other methods will be verified in this paper. The experimental results show that the system spends 11.44ms on processing the colorful image whose resolution is 640480.The system has realized the real time, high speed, stable and reliable acquisition, processing and display of infrared image and we can realize the infrared target feature extraction, recognition and tracking when we combine the system with other algorithms.

To create a system that provides a comparison of multiple algorithms that may be tested in the Prisoner’s Dilemma decision problem using two subjects in a dual agent environment. As an addition to understanding the effects of various algorithms and logic that helps influence a single agent’s decision, our system aims at analysing the performance of the same algorithms in iterative and multi agent systems. The results are obtained by using concepts of Swarm Intelligence, Multiple Agent Systems and Super Agents within the testing system. The results of the research are to expose the advantages and disadvantages of each schema to help plan investments, predict outcomes and for real world application of the Prisoner’s Dilemma in fields of Environmental Sciences, Psychology, Economics and many more such fields.