Earticle

Due to the complexity of the algorithm own limitations and environmental parameters, makes for complex work in the process of localization is bigger, computational complexity, a larger error. In order to ensure the reliability and effectiveness of communication data, ensure that improve the localization accuracy, the proposed multi-channel data transmission mechanism, to realize the collection of real-time data information effectively. Based on the traditional localization algorithm principle and error source is analyzed, combined with Bayesian filtering probability model for RSSI localization algorithm was improved, the received signal strength indicator effectively restrain random fluctuations. Through to the node coordinates between areas corrections, make the final balance of signal strength. Experiments show that improved the reliability of the improved algorithm has higher localization accuracy, and shows the validity and the correctness of the algorithm.

The use of robots in medical applications has increased considerably in the last decade. Today, there are robots being used in complex surgeries such as those of the brain, eye, heart, and hip. Complex surgeries have complex requirements, such as high precision, reliability over multiple and long procedures, ease of use for physicians and other personnel, and a demonstrated advantage, to the patient, of using a robot. Furthermore, all new technologies in the medical area have to undergo strict regulatory clearance procedures, which may include clinical trials, as outlined by various government regulatory agencies. Variable Structure controller is a powerful nonlinear robust controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for surgical joints. Limitation of robustness in uncertain dynamic parameter is the main drawback in pure Variable Structure controller. This challenge in pure Variable Structure controller and intelligent Variable Structure controller is reduced by using sliding surface auto-tuning. Artificial intelligence theory is used to reduce the system’s limitation. In this research, PI fuzzy sliding surface tuning Variable Structure controller is introduced. To eliminate the uncertain limitation, 49 rules Mamdani inference system is design and supervised the Variable Structure methodology. This method is based on resolve the on line sliding surface slope as well as improve the output performance by tuning the sliding surface slope coefficient. The sliding surface gain (𝝀) of this controller is adjusted online depending on the last values of error (𝑒) and integral of error (Σ𝑒) by sliding surface slope updating factor (𝛼). Fuzzy-based tuning controller is stable controller, which does not need to limits the dynamic model of surgical joints.

We proposed a task scheduling in cloud computing based on intelligence firefly algorithm aimed at the disadvantages of cloud computing task scheduling. Firstly, on the basis of cloud model, used intelligence firefly algorithm with strong ability of global searching to find the better solution of cloud computing task scheduling then turned the better solution into the initial pheromone of improved firefly algorithm, and found out the cloud computing task scheduling and the algorithm’s global optimal solution through improved firefly information communications and feedbacks. Finally, made comparison test of the three benchmark function on the basis of MATLAB, the results showed, compared with traditional intelligence firefly algorithms, the improved algorithm can preferably allocate the resources in cloud computing model, the effect of prediction model time is more close to actual time, can efficiently limit the possibility of falling into local convergence, the optimal solution’s time of objective function value is shorten which meet the user’s needs more.

This paper investigates the influence of alcohol on brain complexity. Considering electro-encephalogram (EEG) has the nonlinear dynamics characteristic of time-varying and non-stationary, we introduce the wavelet entropy (WE) analysis. We denoise EEG signal by using wavelet decomposition, then calculate the wavelet entropy of the denoised signal and analyze the nonlinear complexity. In 64 conductive poles experiments and in different stimulus experiments for FP2 electrode's EEG, the drinkers' EEG wavelet entropy is greater than normal people's. The wavelet entropy of every conductive pole of drinkers’ or normal persons’ is inconformity.

Choosing the best page size for Virtual Memory requires considering several factors. A smaller page size reduces the amount of internal fragmentation. On the other hand, a larger page needs smaller page tables. However, this paper argues that the main reason to prefer a larger page is to increase the virtual to physical translation speed i.e. because the size of a TLB is limited, to facilitate increasing of TLB coverage we have to use larger pages

Static task scheduling in multiprocessor frameworks is one of the well-defined NP Hard Problem. Due to optimal utilization of processors and in addition investing less time, the Scheduling of tasks in multiprocessor frameworks is of extraordinary significance. To Solve NP Hard Problem using traditional strategies takes reasonable measures of time. Over the time, various heuristic procedures were presented for comprehending it. Therefore, heuristic methods such as Genetic Algorithms are appropriate methods for task scheduling in multiprocessor system. In this paper, a new GA for static task scheduling in multiprocessor systems has been presented whose priority of tasks’ execution is based on the height of task in graph and other mentioned parameters and then scheduling is performed. This proposed method is simulated and then compared with Basic Genetic algorithm.

Fractional order has the characteristics of memory and non-locality and it is different with integer order. Therefore, fractional differential equations can be used to describe some abnormal natural phenomena. At the same time, how to solve the fractional order partial differential equation and differential equations with fractional order has become a very important research field. Besides analytic solution, it is also important to investigate the numerical methods for fractional differential equations. In the paper, fundamental solution of the time fractional partial differential equation has been deduced, which is derived by Furrier transform and Laplace transform. According to the simulation, there is little difference between numerical solution and the exact solution when the solution is the time variable function. The results show the validity of the method.

Magnetotactic bacteria optimization algorithm(MBOA) is an optimization algorithm based on the characteristics of magnetotactic bacteria, which is a kind of polyphyletic group of prokaryotes with the characteristics of magnetotaxis that make them orient and swim along geomagnetic field lines. In this paper, an improved MBOA is proposed. At first, it generates moments based on the interaction energy of cells. Then, the moments of cells are regulated based on the best cell. Some cells have chance to move towards the best one. At last, some worse cells will be replaced by randomly generated solutions in order to keep diversity. Thus, it can find optimum solution. It is tested on ten standard function problems and compared with many popular optimization algorithms, including CLPSO, LeDE and ABC. Experiment results show that the improved MBOA is very effective in optimization problems and has superior performance to the compared methods on many benchmark functions.

The VANET security is an important issue with the rise of the automatically driven vehicle based technologies. The automatically driven vehicle based clusters are programmed for each vehicle to run individually by coordinating with all of the other nodes in the VANET cluster. The proposed model has been designed to detect and mitigate the DoS and DDoS attacks in the VANET clusters to avoid any of the misbehavior or mis-happening in the form of VANET node failure, collision or in any other form. The DDoS attack prevention algorithm works as the real time attack detection and overhead data filtering algorithm in order to protect against the DoS and DDoS attacks. The proposed model result has been obtained on the basis of network load, throughput, packet delivery ratio, etc. The experimental results have proved the efficiency of the proposed model in comparison with the existing models.

In the new era, rapid growth of national economy more and more relies on the transformation of industrial structure. Therefore with the in-depth development of industrialization, a very effective way to make our country more prosperous is optimizing industry structure by integration of informatization and industrialization. In this paper, we create a compound synergetic model and use panel data of Jiangxi Province and the country covering the period 2001-2010 to test order degree of the integration. The main results suggest that promoting the synergy degree of intergration would accelerate the economic development. We should make full use of informatization to promote the synergy degree of informatization with industrialization.

In this paper, in order to solve the question of the winding tracks affected by tension leading to pipeline performance degradation, we analyze the tension on the wound composite pipes and establish a winding model about six degrees of freedom robotic arm and find the solver of the kinematic equations. We designed a winding track and established on a MATLAB and ADAMS co-simulation platform. The winding track affected by the tension is simulated. According to the results, we can obtain the force of the joints of the robot. Taking these force data as the compensation of the joint force, the robot can do the desired track overcoming the winding tension.

Predicting sales in a shoe industry is a typical job due to unpredictable demand of products. Many models are suggested for forecasting the product in the literature over the past few decades. Most shoe manufacturing organizations are in a continuous effort for increasing their profits and reducing their costs. Exact sales forecasting is certainly an inexpensive way to meet the organization goals. This paper studies and compares different forecasting techniques as moving average, single exponential smoothing, double exponential smoothing and winter’s method. For this, domestic sales data from a shoe industry is collected and then data were analyzed by statistics technique using Minitab 17 software. The result shows that the demand of shoes fluctuate over the period of time. The factor that influences the choice of forecasting model is the least value of Mean square deviation (MSD).

To analyze the influence caused by different cutting parameters on the cutting force and get the coefficient of milling force obtained under the state of high-speed milling, the high-speed milling test was conducted through carbide cutting tools milling the titanium impeller under the state of high speed. Firstly, the influence on the three target force, caused by every parameter, was analyzed through orthogonal experiment. And then, the milling force coefficient got from two different formula was compared in this article. Calculated and experimental results show that the milling force coefficient got by means of the empirical formula reduced flutter stability limit, however, he milling force coefficient got by means of parsing not. At last, it also provide data to support to avoid the chatter occurred between tool and workpiece and select the processing parameters optimally.

E Voting system requires strong voter verification. voter verification is achieved by using two factor authentications method i.e. something the voter know that is static code and something the voter has that is one time password. The key benefit of encompassing a mobile handset is that maximum voter previously have mobile headsets, and therefore no need of any additional hardware essentials to be bought, installed, or maintained. This system mainly develops to increase the overall voting percentage and to reduce the overall cost which is used in election.by using this system people who live out of their native place are able to cast the votes. This system manage the user detail, candidate detail, and election related details and provide result efficiently.it provide hassle free voting to the general public

The main concern is over rising temperature during the testing of complex system-on-chip (SOC), this paper studies SOC wrapper and test access mechanism (TAM), and proposes an improved algorithm of TAM assignment under the constraints of temperature. The algorithm uses temperature superposition method and adds compression process. This algorithm can find the test structure that uses shorter test time.

In recent years, machine learning is increasingly becoming an important field of computer science. A new method using KNN classification algorithm identifies the layered boundary to find subgoal condition, to automatic classifying of large state space, reaches the dimension reduction of state space, and on the basis of generated subspace classifying to structure subtasks, and then realizes the hierarchical learning tasks automatically. In autonomous system, Agent assigns to their task through interaction with the environment, using hierarchical reinforcement learning technology can help the Agent in the large, complex environment to improve learning efficiency. Through the experimental results the effectiveness of the proposed algorithm is demonstrated. The goal of this paper is to provide a basic overview for both specialists and non-specialists to how to decide a good reinforcement learning algorithm for classification.

Optical correspondence for different access has turn into the standard for scientists as the utility rate in optical correspondence these days is expanding quickly. As different gets to, the more clients uses the system, date rate, limit and security have turn into the discriminating issue for the optical framework. The development of remote correspondence with code-division multiple access (CDMA) system have persuaded the joining of CDMA method into optical system, as it is substantially more alluring since it permits different users in a local area network (LAN) environment to get to the same fiber channel non concurrently at all times. Besides, the power of CDMA method in remote system is yet to demonstrate that OCDMA offers security preferences over other various access frameworks by keeping up the nature of administrations. In this paper, the study on OCDMA is in light of exhibiting an analysis on Optical Spectral-Amplitude Code (SAC) OCDMA organized with uniform fiber Bragg gratings. It shows a three-clients SAC-OCDMA For three-client SAC-OCDMA system working at 1550 nm wavelength with 622 Mb/s information rate and 10 Gchip/s chip rate, the greatest suitable transmission separation for a bit mistake rate (BER) < 10-9 at 50km SMF utilizing RZ group [8].

The methods to resolve Information overload can mainly classify two kinds: Information Retrieval and Information Filtering. Based on the needs of the people, Information Retrieval will search out the related information and technology from the information stored in some way. Information Filtering will choose out user preferred personalized information from the dynamic information flow based on the filtering requests of the people. The paper analyzed micro-blogs users needs and motivation, According to micro-blogs users motivation, effectively, an approach based on tem frequency inverse document frequency (TF-IDF) was proposed. This article constructed personalized recommendation models in on-line social streams based on ties strength, topic relevance and trust dimensions. The experiments on the Sina blogs data showed that the proposed method could reduce the ranks of irrelevant tweets effectively and achieve better performance than several baseline methods based on cosine and hash tags

Advances in science and technology have impacted the field of education in manners unthought-of in the past. Information and Communication Technology based systems have resulted in ubiquitous learning becoming a reality, where classrooms are not restricted within boundaries or four walls. Self-paced learning is now the order of the day, which requires the learner to be aided in his learning endeavors at times that suits him. The present paper proposes a system that gives the learner an automated tool to learn a subject at his own pace. The preparatory stage includes feeding in a couple of model answers to every question which the learner has to answer. Thereafter, the learner tries to answer the questions with aid in the form of hints available and is evaluated based on his response. Results show that learners taking help from this system performs better than those using traditional methods.

For superalloy GH4169poor processing, tool wear serious, affecting the surface quality of the workpiece and other issues, using the finite element software AdvantEdge to simulate the formation process of superalloy GH4169 chip in two-dimensional, and researching the characterization of serrated chip. Take the single factor experiment and conduct finite element simulation for superalloy GH4169 in changing the rake angle and tip arc radius of the situation. The simulation and the chip shape taking from experiments will be compared to prove the feasibility of the simulation. And find out changes of rake angle and tiparc radius; make clear the influence of degree of serrated chip. The results show: with the rake angle increases, serrated degree increases, and with tiparc radius increases, serrated degree increases. The study provides a reference for reasonable choice of optimized cutting tool geometric parameters.

The ultrasonic buffer rod used for polymer testing under the high temperature, not only needs high transmission ultrasound characteristic of SNR, but also low acoustic attenuation, high temperature and strong mechanical properties etc are needed. The role PEEK rod plays in this paper is transmitting ultrasonic guided waves and temperature buffer, so the design of PEEK rod is the key. Through the experimental analysis, the SNR with different diameter and length is gave, and the effect on the ultrasonic characteristics of echo signal is also presented, in order to ensure the high SNR. The conclusions provide a theoretical basis for NDT.

Non-destructive testing (NDT) techniques have been employed in all kinds of fields successfully for many years. Newly developed and applied NDT methods of detecting and monitoring fatigue crack in metal material are reviewed in this paper. Some methods based on machine vision technique and image recognition techniques are introduced for at or near surface visible crack testing. As a newborn offspring of acoustic emission technique, electromagnetically induced acoustic emission methods also introduced for both visible and invisible fatigue cracks on metal structure. Nonlinear ultrasonic method and some other NDT methods presently available are mentioned, too. The principles, applied testing fields, data processing algorithms, advantages and disadvantages of these methods are discussed.

In order to meet the increasing daily demands of customers and reduce the unnecessary cost in retail stores as far as possible, the inventory management of retail stores becoming more and more important. However, because of various characteristics of demand in retail stores, the traditional demand forecasting technologies can’t work well. In this paper, we use the modified K-means clustering analysis to help determine the groups with different characteristics of demand. In addition, a demand forecasting model integrated BP neural networks and grey model is proposed to make the prediction more intelligent and general. The example illustrates that the proposed method for forecast is feasible by the comparative analysis between the predicted values and the actual values.

The paper presents the designs of two Sierpinski carpet fractal antennas. The fractal properties have been applied in order to designs compact and wideband antennas. The antennas are analyzed in term of radiation parameters such as reflection coefficients, voltage standing wave ratio and radiation patterns. The results shows that the bandwidths of the antennas at the reflection coefficient less than -10dB are 5.5GHz and 7.25GHz ranging from 8.3GHz to 2.8GHz and 4.75GHz to 12GHz respectively. The directivities of antenna are 5.109dBi, 6.952dBi, 6.696dBi and the gains are 5.11dBi, 6.95dBi, and 6.7dBi. The bandwidth is largest at high resonance points with increasing the number of iterations. The proposed designs are suitable for wireless applications such as Wi-Fi, WiMAX, WLAN, Bluetooth, WCDMA and GSM.

For both internal and external Geneva mechanism, the kinematics coefficient of the Geneva mechanism is a constant if the groove number of the Geneva wheel is a constant. The elliptic crank using as the drive crank of the Geneva wheel is equal to the mechanism which has a variable length and a variable speed along the elliptical moving crank. Therefore the kinematics coefficient of the Geneva mechanism can be changed. In this paper the analysis method of the combined Geneva mechanism is presented. The synthesis method of the combined Geneva mechanism is put forward based upon the kinematics coefficients. The calculation method of the extreme kinematics coefficient is proposed. In the end, the design example is given.

Aiming at the degeneration phenomenon of images taken in mist, according to the features of the degraded images, an improved haze removal algorithm based on genetic fuzzy clustering is presented in this paper after analyzing its defects and shortcomings. Firstly, the improved atmospheric scattering model is established. Secondly, the original image is converted into a standard image through the improved model, and then we present a new multi-scale image edge detection by genetic fuzzy clustering, Based on this observation, we can use the multi-scale image edge detection to estimate the haze thickness directly and recover a high quality haze-free image. The new algorithm uses good global search ability of the genetic algorithm, which will implement the transfer from the scene defogging problem into the optimal estimation problem under global contrast optimal point. Compared with other algorithms for degraded images, the improved haze removal algorithm not only detects image edge precisely, but also has better performance in situations of dense haze. Theoretical analysis and experimental results demonstrate that, the new algorithm improved in this paper are effective for removal of fog-degraded images, and can be applied to the practical situations.

Electronic commerce, commonly known as eCommerce is trade in products using the internet. Security at the e-commerce becomes more and more important. Electronic transaction security is a challenging task because of the insecure communication channel. In this paper, we proposed a new algorithm to make an e commerce transaction more secure. In this work we are using AES to encrypt data and this data is embedded to image edges to perform Stenography in this paper target on compress the time of encryption and decryption adopting parallel processing on which AES will be applied freely. In the results show the comparison between our work and previous work and we found that parallel processing and multi threading on the AES algorithm our results are quite improved, our proposed algorithm is taking much less time in encrypt and embedding or decrypt and extraction.

Many machine learning methods have been applied on the biomedical named entity recognition and achieve good results on GENIA corpus. However most of those methods reply on the feature engineering which is labor-intensive. In this paper，huge potential feature information represented as word vectors are generated by neutral networks based on unlabeled biomedical text files. We propose a Biomedical Named Entity Recognition (Bio-NER) method based on deep neural network architecture which has multiple layers and each layer abstracts features based upon the features generated by lower layers. Our system achieved F-score 71.01% on GENIA regular test corpus , F-score values for 5-fold cross-validation is 71.01% and this result is closed to the state-of-the-art performance with only POS (Part-of-speech) feature and represents the deep learning can effectively performed on biomedical NER.

Removal of noises from real-time speech signal is a typical problem. The signal interference initiated by background noise is a major problem in voice communication systems. Adaptive Filtering methods have emerged as an important technology for communication systems. This technique has been employed to improve the quality of the speech signal by cancelling the undesirable phenomenon such as acoustic noise. In this paper, for the removal of additional noise from speech signal an adaptive filter has been designed using LMS, NLMS, SLMS and VSS-LMS algorithms. This paper presents the instigation of Least Mean Square algorithm (LMS), Normalized Least Mean Square algorithm (NLMS), Sign Least mean square algorithm (SLMS) and Variable step size (VSS) algorithm on an infinite impulse response (IIR) filter using adaptive filter toolkit of LabVIEW software. User interface is designed using LabVIEW to obtain the learning curves for these adaptive algorithms. The final results show the comparison of the performance of the entire proposed algorithms with each other. The complete performance of the designed system in terms of stability and convergence rate has been observed.