Voice activity detection is very important process that voice activity separated form noisy speech signal for speech enhance. Over the past few years, many studies have been made on voice activity detection, but it has poor performance in low signal to noise ratio environment or fickle noise such as car noise. In this paper, it proposed new voice activity detection algorithm using ensemble variance based on wavelet band entropy and soft thresholding method. We conduct a survey in a lot of signal to noise ratio environment of car noise to evaluate performance of the proposed algorithm and confirmed performance of the proposed algorithm.

In this paper we suggest a new two-wheelers detection algorithm using uniform local binary pattern weighting value for projection vectors. The first, we calculate feature vectors using projection method which has robustness for rotation invariant and reducing dimensionality for each cell from origin image. The second, we applied new weighting values which are calculated by the modified local binary pattern showing the fast compute and simple to implement. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

Three synchronization issues, i.e., phase, frequency, and symbol time, have to be properly controlled to achieve distributed beamforming gain. In this paper, the impacts of synchronization errors in distributed beamforming are analyzed for both single-carrier and OFDM systems. When the channel is constant over a symbol duration, the performance degradation due to phase offset is the same for both single-carrier and OFDM systems. For symbol timing offset in OFDM systems, high frequency subcarriers are more susceptible as compared to low frequency ones. Frequency offset is critical in OFDM systems since it leads to interference from the other subcarriers as well as power loss in the desired signal.

Most of previous visual attention system finds attention regions based on saliency map which is combined by multiple extracted features. The differences of these systems are in the methods of feature extraction and combination. This paper presents a new system which has an improvement in feature extraction method of color and motion, and in weight decision method of spatial and temporal features. Our system dynamically extracts one color which has the strongest response among two opponent colors, and detects the moving objects not moving pixels. As a combination method of spatial and temporal feature, the proposed system sets the weight dynamically by each features' relative activities. Comparative results show that our suggested feature extraction and integration method improved the detection rate of attention region.

Doppler weather radar is an important tool for meteorological research. Through several decades of development, Doppler weather radar has enormous progress in understanding, detection and warning of meso and micro scale weather system. It makes a significant contribution to weather forecast and weather disaster warning. But the large amount of data process limits the application of Doppler weather radar. This paper proposed for fast weather radar data processing based on CUDA. CDUA is a powerful platform for highly parallel programming developed by NVIDIA. Through running plenty of threads, radar data can be calculated at same time. In experiment, CUDA parallel program can significantly improve weather data processing time.

Data hiding is one of protective methods that can authenticate the completeness of digital information and protect intelligent property rights and copyright through secret communications. In this paper, we propose a data hiding method using pixel-value modular operation that has a high capacity while maintaining a good visual quality. The proposed method can embed secret data on the every pixel of a cover image by modular operation. The experiment results demonstrate that the proposed method has a high capacity and good visual quality where the embedding capacity is 91,138 bytes, the PSNR is 47.94dB, and the Q index is 0.968.

In general, data packets from sensor nodes are transferred to the sink node in a wireless sensor networks. So many data packets are gathered around the sink node, resulting in significant packet collision and delay. In this paper, we propose an efficient packet transmission mechanism for multi-hop wireless sensor networks. The proposed mechanism is composed of two modes. One mode works between sink node and 1-hop nodes from sink. In this mode, data packets are transmitted in predefined time slots to reduce collisions. The other mode works between other nodes except sink node. In this mode, duplicated packets from neighbor nodes can be detected and dropped using some control signals. Our numerical analysis and simulation results show that our mechanism outperforms X-MAC and RI-MAC in terms of energy consumption and transmission delay.

Security supports are a significant factor in the design of mobile ad hoc networks. In the dynamic topology where the node changes frequently, private key generation and revocation for newly joining and leaving nodes must be considered. In addition, the identities of individual nodes must be protected as well in mobile networks to avoid personal privacy concerns. This paper proposes ID-based private key revocation scheme and non-interactive key agreement scheme in anonymous MANETs. The proposed scheme provides the user privacy using pseudonyms and private key generation and revocation schemes with consideration of dynamic user changes. Therefore, our schemes can be applied in dynamic and privacy-preserving MANETs which are helpful to share multimedia data.

The intent is to determine whether or not the custody transfer is helpful for data transmission in challenging underwater communications when running Bundle protocol or underwater protocols. From the point of view defending side, Underwater Acoustic Network (UAN) will be a serious threat for its strong functionality long rang and high precision of surveillance and detection. Therefore, countermeasures must be taken to weaken its effect. Our purpose is analyzed that how to benefit from the UIoT to learn from, exploit and preserve the natural underwater resources. Delay/Disruption Tolerant Network (DTN) is essential part of the network heterogeneity communication network. The vulnerability and potential security factors of UIoT are studied thereafter. Security mechanisms for an underwater environment are difficult to apply owing to the limited bandwidth. Therefore, for underwater security, appropriate security mechanisms and security requirements must be defined simultaneously. The paper consists of mathematical and security model. Most important point of view in the security challenges of effective Buffer and Storage management in DTN.

All data created in BigData times is included potentially meaning and correlation in data. A variety of data during a day in all society sectors has become created and stored. Research areas in analysis and grasp meaning between data is proceeding briskly. Especially, accuracy of meaning prediction and data imbalance problem between data for analysis is part in course of something important in data analysis field. In this paper, we proposed data prediction model based on data weights and neural network using R for meaning analysis between data. Proposed data prediction model is composed of classification model and analysis model. Classification model is working as weights application of normal distribution and optimum independent variable selection of multiple regression analysis. Analysis model role is increased prediction accuracy of output variable through neural network. Performance evaluation result, we were confirmed superiority of prediction model so that performance of result prediction through primitive data was measured 87.475% by proposed data prediction model.

We study relay selection in decode-and-forward (DF)-based relay networks consisting of a source, a destination, an eavesdropper, and multiple relays, where each terminal has a single antenna and operates in a half-duplex mode. In these networks, it is desirable to protect the confidential message from the source to the destination against the eavesdropper with the help of a single selected relay. Specifically, we begin by investigating DF-based networks for the scenario instantaneous signal-to-noise ratios (SNRs) related to the eavesdropper are available. For the scenario, we propose relay selection to maximize the secrecy rate of DF-based networks with and without direct-paths, and we derive the exact secrecy outage probabilities in closed-form.

Wireless power transmission which can transmit the electrical power through the air is the promise technology. In this paper, the effects of wireless power transmission using magnetic resonance method have been studied on coil material, resonance frequency, and antenna type. We have found copper tube as a coil material had the better characteristics than that of enameled wire, and the optimal resonance frequency was 13.6MHz in the range of from 1MHz to 20MHz. And the double square spiral type antenna as a load coil was the best. The power transmission distance by magnetic resonance method with 13.6MHz was 150 cm.

Since the concept of software engineering was first used in 1968 by NATO Science Committee, a lot of research work and improvements have been made on software development methodology and software quality control, but they still fall short of ensuring successful development of small and medium scale software systems. Under these circumstances, Center for Software Engineering (CSE) at National IT Industry Promotion Agency(NIPA) has been conducting studies on quality control methodologies of software visualization well-suited for small and medium scale software systems, and also working on the systemization and quantification of software quality control. In this paper, we attempt to scope on the software development management of domestic and foreign small and medium-sized enterprises that are lying in the blind spot, compared to large enterprises with well-organized software development systems. In particular, based on software visualization that CSE is pursuing for small and medium-sized developers, we propose a practical quality control methodology well-suited for small and medium scale projects, and a low-cost quality control management tool by combining open-source quality control tools. Our proposal is expected to induce developers' mind change in SI-specialized small and medium-sized software enterprises, increase their profits and improve customer satisfaction through project quality control.

There are many prior studies for more natural Human-Computer Interaction. Until now, the efforts is continued in order to recognize motions in various directions. In this paper, we suggest a user-specific recognition by hit detection method using Kinect camera and human proportion. This algorithm extracts the user-specific valid recognition rage after recognizing the user's body initially. And it corrects the difference in horizontal position between the user and Kinect, so that we can estimate a action of user by matching cursor to target using only one frame. Ensure that efficient hand recognition in the game to take advantage of this method of suggestion.

Falls are the main cause of serious injuries and accidental deaths in people over the age of 65. Due to widespread adoption of smartphones, there has been a growing interest in the use of smartphones for detecting human behavior and activities. Modern smartphones are equipped with a wide variety of sensors such as an accelerometer, a gyroscope, camera, GPS, digital compass and microphone. In this paper, we introduce a new method that determines the fall direction of human subjects by analyzing the three axis components of acceleration vector.