In this paper, we investigate an adaptive cognitive radio (CR) scheme where a sensing duration and a detection threshold for spectrum sensing are adaptively determined according to the channel condition in a fading channel. We optimize the sensing duration and detection threshold of a secondary user to maximize the performance of the secondary user guaranteeing a primary user's secure communication. In addition, we analyze the effect of channel fading on the optimization of the sensing duration and detection threshold. Our numerical results show that the performance of the adaptive CR scheme can be drastically improved if a secondary user can take the advantage of channel information between primary and secondary users.

In this article, new microstrip slow-wave bandpass filters using open loop resonator loaded with inter-digital capacitive fingers is proposed. The filter features not only compact in size, but also exhibits spurious stop-band rejection. Filters of this type with elliptic function and Chebyshev response are demonstrated. There is good agreement between experimental and full-wave electromagnetic (EM) simulation results.

In RFID System, when multiple tags respond simultaneously, a collision can occur. A method that solves this collision is referred to anti-collision algorithm. In 13.56MHz RFID system, STAC protocol is defined as an anti-collision algorithm for multiple tag reading. In STAC protocol, there is no differentiation between the collided tags and others in the identification process. Therefore, tags may never be successfully identified because its responses may always collide with others. This situation may cause the tag starvation problem. This paper proposes a fair identification scheme for STAC protocol. In the proposed scheme, if the number of collided slots is large during a query round, the reader broadcasts a CollisionRound command to begin a collision round. During the collision round, the reader identifies only tags that are experienced collision during the previous query round.

The advancement of technology enables smart phones or handheld devices to render complex 3D graphics. However, the processing power and memory of smart phones remain very limited to render high polygon and details 3D models especially on games which requires animation, physic engine, or augmented reality. In this paper, several techniques will be introduced to speed up the computation and reducing the number of vertices of the 3D meshes without losing much detail.

In this paper, we present a hybrid encryption for a digital hologram which is the most valuable image content. The encryption algorithm is based on a hybrid technique implementation a four-dimensional transform combining the discrete wavelet transform(DWT) and the discrete cosine transform (DCT). The encryption scheme is composed on the basis of the energy distribution. The experimental results showed that encrypting only 0.0244% of the entire data was enough to hide the constants of the hologram. The encryption algorithm expected to be used effectively on the researches on encryption and others for digital holographic display.

This paper presents a method of constructing the switching function using edge-valued decision diagrams. The proposed method is as following. The edge-valued decision diagram is a new data structure type of decision diagram which is recently used in constructing the digital logic systems based on the graph theory. Next, we apply edge-valued decision diagram to function minimization of digital logic systems. The proposed method has the visible, schematic and regular properties.

Recently, a name retrieval function is widely used on navigation systems. In this paper, we propose the new dynamic hashing algorithm for a name retrieval function on it. The proposed dynamic hashing algorithm by constructing an index using the variance information of character is the better than existing methods in terms of storage capacity and retrieval speed. The algorithm proposed in this paper can be useful on systems that have limited resources as well as navigation systems.

This paper proposes a search system using the topic maps that it extends XMDR into Knowledge based XMDR for solving of the problems of the heterogeneity of distributed data on a network and integrate data by an efficient way. The proposed system combined Topic Maps and the extended metadata registry effectively. The Topic Maps represent related knowledge and reasoning relationship by associations of topic. And the extended metadata registry standards and manages the metadata of the local systems through registration and certification on the distributed environment. We also proposed a meta layer, include the meta topic and meta association to achieve semantic classification grouping of topics and to define relationship between Topic Maps and extended metadata registry.

Twitter is a popular microblogging service that enables the users to send and read short text messages. These messages are becoming source to analyze topic trends and identify relations among temporal topics. In this paper, we propose a method to classify the temporal topics on Twitter as a problem of grouping the similar patterns. To provide a starting point for a classification under the same topics, we identify the content word weighting scheme based on Latent Dirichlet Allocation (LDA). And we formulate how the temporal topics in the time window can be classified like peaky topics, constant topics, and periodic topics. We provide different real case studies which show the validity of the proposed method. Evaluations show that the proposed method is useful as a classifying model in the analysis of the temporal topics.

This paper describes the possibility of a low-power, high-resolution fingerprint sensor chip. A modified capacitive detection circuit of charge sharing scheme is proposed, which reduces the static power dissipation and increases the voltage difference between a ridge and valley more than conventional circuit. The detection circuit is designed and simulated in 3.3V, 0.35${\mu}$m standard CMOS process, 40MHz condition. The result shows about 27% power dissipation reduction and 90% improvement of difference between a ridge and valley sensing voltage. The proposed circuit is more stable and effective than a typical circuit.

This paper proposes a new rotational frequency detector (RFD) for phase-locked loop (PLL) or clock and data recovery (CDR) applications for fast frequency acquisition. The proposed RFD uses the four states finite state machine (FSM) model to accelerate the frequency acquisition time. It is modeled and simulated with MATLAB Simulink. The functionalities of the proposed RFD are examined and the results are compared to those of a conventional RFD. The proposed RFD's frequency acquisition time is four times faster than that of a conventional one. The proposed RFD incorporated with a phase detector (PD) in PLL or CDR is expected to improve the frequency and phase acquisition performance later greatly.

This paper has presented doping profile dependent threshold voltage for DGMOSFET using analytical transport model based on Gaussian function. Two dimensional analytical transport model has been derived from Poisson's equation for symmetrical Double Gate MOSFETs(DGMOSFETs). Threshold voltage roll-off is very important short channel effects(SCEs) for nano structures since it determines turn on/off of MOSFETs. Threshold voltage has to be constant with decrease of channel length, but it shows roll-off due to SCEs. This analytical transport model is used to obtain the dependence of threshold voltage on channel doping profile for DGMOSFET profiles. Also we have analyzed threshold voltage for structure of channel such as channel length and gate oxide thickness.

The orientation space representation is constructed by treating the orientation parameters, which Gabor filters can be turned, as a continuous variable. The problem of multiple orientation line segmentation is dealt with by thresholding 3D images of the orientation space and then detecting the connected components therein. In this way, X-junctions and T-junctions are able to be separated effectively. Experimental results are presented using synthesized image.

In computing the optical flow. Horn and Schunck's method which is a representative algorithm is based on differentiation. But it is difficult to estimate the velocity for a large displacement by this algorithm. To cope with this problem multigrid method has been proposed. In this paper, we have proposed a scaled multigrid algorithm which the initial flow for a level is calculated by the summation of the optimally scaled flow and error flow. The optimally scaled flow is the scaled expanded flow of the previous level, which can generate an estimated second image having the least RMS error with respect to the original second image, and the error flow is the flow between the estimated second image (generated by the optimally scaled flow) and the original second image. The flow for this level is then estimated using the original first and second images and the initial flow for that level. From among the various coarsest starting levels of the multigrid algorithm, we select the one that finally gives the best estimated flow. Better results were achieved using our proposed method compared with Horn and Schunck's method and a conventional multigrid algorithm.

Due to the wide growth and popularity of social network website, large numbers of users discover these social network sites are a place where they can be able to spend their leisure time sharing interests, sharing ideas freely, sharing personal experience, and also to search for new friends or partners. These websites give an opportunity for its users to socialize with new people and to keep in touch or reconnect with current or old friends and families across disperse continents, which traditionally replace the common traditional methods. These social network websites need accurate and careful investigations and findings on the usability issues for effective interactivity and more usability. However, little research might have previously invested on the usability of these social network websites. Therefore, we propose a new framework to study and test the usability of these social network sites. We namely call our framework "Interactivity". This framework will enable developers to assess the usability of the social network sites. It will provide an overview of the user's behavior while interacting in these social network websites. Performance of the framework will be performed using Camtasia software. This software will entirely capture the interactivity of users including the screen and the movements, which the screen and the motion of the user action will undergo to analysis at the end of our research.

Digital images are often corrupted by impulse noise, and it is very important to remove random-valued impulse noise. Cleaning such noise is far more difficult than cleaning salt and pepper impulse noise. In this paper, we proposed an efficient way to remove random-valued impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the random-valued impulse noise in the image and the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the random-valued impulse noise from the image. In this stage, only the "noise pixels" are processed. The "noise-free pixels" are copied directly to the output image. Simulation results indicated that our method provides a significant improvement over many other existing algorithms.

Many approaches to image restoration are aimed at removing either gauss or impulse noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by Gaussian noise in the image acquisition procedure, undergoes impulsive corruption during its digital transmission. Here we proposed an algorithm first judge the type of the noise according to the difference values of pixel's neighborhood region and impulse noise's characteristic. Then removes the gauss noise by modified weighted mean filter and removes the impulse noise by modified nonlinear filter. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms. The proposed method can not only remove mixed noise effectively, but also preserve image details.

Wireless sensor networks (WSNs) are formed by a great quantity of sensor nodes, which are consisted of battery-powered and some tiny devices. In WSN, both efficient energy management and Quality of Service (QoS) are important issues for some applications. Real-time services are usually employed to satisfy QoS requirements in critical environment. This paper proposes a real-time MAC (Medium Access Control) protocol with extended backoff scheme for wireless sensor networks. The basic idea of the proposed protocol employs (m,k)-firm constraint scheduling which is to adjust the contention window (CW) around the optimal value for decreasing the dynamic failure and reducing collisions DBP (Distant Based Priority). In the proposed protocol, the scheduling algorithm dynamically assigns uniform transmitting opportunities to each node. Numerical results reveal the effect of the proposed backoff mechanism.

In this paper, although Radar has been used for a long time, integrated scheme with visual camera is an efficient way to enhance marine surveillance system. Camera image is focused by radar information but it is easy to be fallen into inaccurate operation due to environmental noises. We have proposed a method to filter the noises by moving average filter and Kalman filter. It is proved that Kalman filtered results preserves linearity while the former includes larger variance.