Potential games form a class of non-cooperative games where the convergent of unilateral improvement dynamics is guaranteed in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed.

This paper describes 0.8-/1.5-GHz-band GaAs-HBT power amplifier modules with a newly designed analog bias control scheme. This scheme has two features. One is to achieve approximately linear quiescent current control using not a BiFET process but only the usual HBT process. The other is to help improve linearity under reduced supply voltage and lower quiescent current operation. The following two key techniques are incorporated into the bias scheme. The first is to employ two different kinds of bias circuits: emitter follower bias and current injection bias. The second is the unique current injection bias block, based on the successful combination of an input buffer with an emitter resistance load and a current mirror. These techniques allow quiescent current control that is almost proportional to an externally applied analog control voltage. To confirm the effectiveness of the scheme, 0.8-GHz-band and 1.5-GHz-band power amplifier modules were designed and fabricated using the usual HBT process. Measurements conducted under the conditions of a 3.4V supply voltage and an HSDPA WCDMA modulated signal are as follows. The 0.8-GHz-band amplifier can deliver a 28-dBm output power (Pout), a 28.4-dB power gain (Gp), and 42% PAE while restricting the ACLR to less than -40dBc. For the 1.5-GHz-band amplifier, 28dBm of Pout, 29dB of Gp, and 41% of PAE are obtained with the same ACLR levels. The measurements also confirm that the quiescent current for the second stage in the amplifiers is approximately linearly changed from 14mA to 58mA over a control voltage ranging from 1.1V to 2.2V. In addition, our measured DG.09-based current dissipation with both supply voltage and analog bias controls is as low as 16.9mA, showing that the analog bias control scheme enables an average current reduction of more than 20%, as compared to a conventional supply voltage and two-step quiescent current control.

To eliminate casting shadows of moving objects, which cause difficulties in vision applications, a novel method is proposed based on Visual background extractor by altering its updating mechanism using relevant spatiotemporal information. An adaptive threshold and a spatial adjustment are also employed. Experiments on typical surveillance scenes validate this scheme.

A mobile ad hoc network (MANET) consists of mobile wireless terminals without using base stations. MANETs are expected to be utilized for various purposes such as traffic jam information announcements for vehicles and safety confirmation systems in disaster. Each MANET uses unique routing protocols that have been adapted for particular applications. Therefore, utilizing a common routing protocol for multiple MANETs is difficult. In this paper, we propose an Autonomous Clustering-based Inter-Domain Routing protocol to communicate between MANETs. Using the autonomous clustering, the proposed inter-domain routing scheme can change the network gateways between MANETs adaptively according to the network topology changes.

Due to ease of implementation for various user interactive applications, much research on motion recognition has been completed using Kinect. However, one drawback of Kinect is that the skeletal information obtained is provided under the assumption that the user faces Kinect. Thus, the skeletal information is likely incorrect when the user turns his back to Kinect, which may lead to difficulty in motion recognition from the application. In this paper, we implement a highly accurate human motion capture system by installing six Kinect sensors over 360 degrees. The proposed method enables skeleton to be obtained more accurately by assigning higher weights to skeletons captured by Kinect in which the user faces forward. Toward this goal, the front vector of the user is temporally traced to determine whether the user is facing Kinect. Then, more reliable joint information is utilized to construct a skeletal representation of each user.

This paper proposes and analyses an improved direction finding (DF) method that uses a rotating interferometer. The minimum sampling frequency is deduced in order to eliminate the phase ambiguity associated with a long baseline, the influence of phase imbalance of receiver is quantitatively discussed and the Root Mean Square Error (RMSE) of both bearing angle and pitch angle are also demonstrated. The theoretical analysis of the rotating interferometer is verified by simulation results, which show that it achieves better RMSE performance than the conventional method.

Traditional sparse representation-based methods for human action recognition usually pool over the entire video to form the final feature representation, neglecting any spatio-temporal information of features. To employ spatio-temporal information, we present a novel histogram representation obtained by statistics on temporal changes of sparse coding coefficients frame by frame in the spatial pyramids constructed from videos. The histograms are further fed into a support vector machine with a spatial pyramid matching kernel for final action classification. We validate our method on two benchmarks, KTH and UCF Sports, and experiment results show the effectiveness of our method in human action recognition.

Machine learning is used in various fields and demand for implementations is increasing. Within machine learning, a Random Forest is a multi-class classifier with high-performance classification, achieved using bagging and feature selection, and is capable of high-speed training and classification. However, as a type of ensemble learning, Random Forest determines classifications using the majority of multiple trees; so many decision trees must be built. Performance increases with the number of decision trees, requiring memory, and decreases if the number of decision trees is decreased. Because of this, the algorithm is not well suited to implementation on small-scale hardware as an embedded system. As such, we have proposed Boosted Random Forest, which introduces a boosting algorithm into the Random Forest learning method to produce high-performance decision trees that are smaller. When evaluated using databases from the UCI Machine learning Repository, Boosted Random Forest achieved performance as good or better than ordinary Random Forest, while able to reduce memory use by 47%. Thus, it is suitable for implementing Random Forests on embedded hardware with limited memory.

A salient feature extraction algorithm is proposed to improve the recognition rate of the speech emotion. Firstly, the spectrogram of the emotional speech is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Each map is normalized and down-sampled to form the low resolution feature matrix. Then, each feature matrix is converted to the row vector and the principal component analysis (PCA) is used to reduce features redundancy to make the subsequent classification algorithm more practical. Finally, the speech emotion is classified with the support vector machine. Compared with the tradition features, the improved recognition rate reaches 15%.

In this letter we present an imperceptible and robust watermarking algorithm that uses a cryptographic hash function in the authentication application of digital medical imaging. In the proposed scheme we combine discrete Fourier transform (DFT) and local image masking to detect the watermark after a geometrical distortion and improve its imperceptibility. The image quality is measured by metrics currently used in digital image processing, such as VSNR, SSIM and PSNR.

Radio channel modeling is fundamental for designing wireless communication systems. In millimeter or sub-millimeter wave short range communication, shadowing effect by electrically-large objects is one of the most important factors determining the field strength and thus the coverage. Unfortunately, numerical methods like MoM, FDTD, FEM are unable to compute the field scattered by large objects due to their excessive time and memory requirements. Ray theory like geometrical theory of diffraction (GTD) by Keller is an effective and popular solution but suffers various kinds of singularities at geometrical boundaries such as incidence shadow boundary (ISB) or reflection shadow boundary (RSB). Modified edge representation (MER) equivalent edge current (EEC) is an accurate and a fast high frequency diffraction technique which expresses the fields in terms of line integration. It adopts classical Keller-type knife-edge diffraction coefficients and still provides uniform and highly accurate fields everywhere including geometrical boundaries. MER is used here to compute the millimeter-wave field distribution in compact range communication systems where shadowing effects rather than multi-path ones dominate the radio environments. For further simplicity, trigonometric functions in Keller's diffraction coefficients are replaced by the path lengths of source to the observer via the edge point of integration of the scatterers in the form of Fresnel zone number (FZN). Complexity, Computation time and the memory were reduced drastically without degrading the accuracy. The dipole wave scattering from flat rectangular plates is discussed with numerical examples.

A gold coated carbon nanotubes composite was used as a contact material in Micro-Electrical-Mechanical-System (MEMS) switches. The switching contact was tested under typical conditions of MEMS relay applications: load voltage of 4 V, contact force of 1 mN, and load current varied between 20-200 mA. This paper focuses on the wear process over switching lifetime, and the dependence of the wear area on the current is discussed. It was shown that the contact was going to fail when the wear area approached the whole contact area, at which point the contact resistance increased sharply to three times the nominal resistance.

In indoor localization using sensor networks, performance improvements are required for non-line-of-sight (NLOS) environments in which the estimation error is high. NLOS mitigation schemes involve the detection and elimination of the NLOS measurements. The iterative minimum residual (IMR) scheme, which is often applied to the localization scheme using the time of arrival (TOA), is commonly employed for this purpose. The IMR scheme is a low-complexity scheme and its NLOS detection performance is relatively high. However, when there are many NLOS nodes in a sensor field, the NLOS detection error of the IMR scheme increases and the estimation accuracy deteriorates. Therefore, we propose a new scheme that exploits coarse NLOS detection based on stochastic characteristics prior to the application of the IMR scheme to improve the localization accuracy. Improved performances were confirmed in two NLOS channel models by performing numerical simulations.

This paper presents an inter-satellite link (ISL) reassignment method to optimize the snapshot routing performance for polar-orbit LEO satellite networks. When the snapshot routing tables are switching simultaneously in all satellites, we propose to reassign the inter-plane ISLs with regularity to improve the quality of the next snapshot, such as snapshot duration, on-board transceiver utilization ratio and end to end delay. Evaluations indicate that our method can attain equal-length snapshots regardless of the latitude of the polar area border, and so is superior to the natural partition method. Meanwhile, compared with the equal partition method which is used in the Iridium system, our method can prolong 82.87% snapshot duration, increase 8.68% on-board transceiver utilization ratio and reduce 5.30% average end to end delay of the whole network. Therefore, we believe that the ISL reassignment method can be efficiently applied in all practical polar-orbit LEO satellite networks.

A new algorithm for separating mass spectra into individual substances for explosives detection is proposed. In the field of mass spectrometry, separation methods, such as principal-component analysis (PCA) and independent-component analysis (ICA), are widely used. All components, however, have no negative values, and the orthogonality condition imposed on components also does not necessarily hold in the case of mass spectra. Because these methods allow negative values and PCA imposes an orthogonality condition, they are not suitable for separation of mass spectra. The proposed algorithm is based on probabilistic latent-component analysis (PLCA). PLCA is a statistical formulation of non-negative matrix factorization (NMF) using KL divergence. Because PLCA imposes the constraint of non-negativity but not orthogonality, the algorithm is effective for separating components of mass spectra. In addition, to estimate the components more accurately, a sparsity constraint is applied to PLCA for explosives detection. The main contribution is industrial application of the algorithm into an explosives-detection system. Results of an experimental evaluation of the algorithm with data obtained in a real railway station demonstrate that the proposed algorithm outperforms PCA and ICA. Also, results of calculation time demonstrate that the algorithm can work in real time.

An integral attack is one of the most powerful attacks against block ciphers. We propose a new technique for the integral attack called the Fast Fourier Transform (FFT) key recovery. When N chosen plaintexts are required for the integral characteristic and the guessed key is k bits, a straightforward key recovery requires the time complexity of O(N2k). However, the FFT key recovery only requires the time complexity of O(N+k2k). As a previous result using FFT, at ICISC 2007, Collard etal proposed that FFT can reduce the time complexity of a linear attack. We show that FFT can also reduce the complexity of the integral attack. Moreover, the estimation of the complexity is very simple. We first show the complexity of the FFT key recovery against three structures, the Even-Mansour scheme, a key-alternating cipher, and the Feistel structure. As examples of these structures, we show integral attacks against Prøst, AES, PRESENT, and CLEFIA. As a result, an 8-round Prøst P128,K can be attacked with about an approximate time complexity of 279.6. For the key-alternating cipher, a 6-round AES and a 10-round PRESENT can be attacked with approximate time complexities of 251.7 and 297.4, respectively. For the Feistel structure, a 12-round CLEFIA can be attacked with approximate time complexities of 287.5.

This paper presents a nonlinear model of human brain activity in response to visual stimuli according to Blood-Oxygen-Level-Dependent (BOLD) signals scanned by functional Magnetic Resonance Imaging (fMRI). A BOLD signal often contains a low frequency signal component (trend), which is usually removed by detrending because it is considered a part of noise. However, such detrending could destroy the dynamics of the BOLD signal and ignore an essential component in the response. This paper shows a model that, in the absence of detrending, can predict the BOLD signal with smaller errors than existing models. The presented model also has low Schwarz information criterion, which implies that it will be less likely to overfit the experimental data. Comparison between the various types of artificial trends suggests that the trends are not merely the result of noise in the BOLD signal.

A predicate encryption scheme enables the owner of the master key to enforce fine-grained access control on encrypted cloud data through the delegation of predicate tokens to cloud storages. In particular, Blundo et al. proposed a construction where a predicate token reveals partial information of the involved keywords to enable efficient operations on encrypted keywords. However, we found that a predicate token reveals more information than what was claimed because of the encoding scheme. In this letter, we not only analyze this extra information leakage but also present an improved encoding scheme for the Blundo et al's scheme and the other similar schemes to preserve predicate privacy.

This paper proposes a foreground segmentation method for indoor environments using depth images only. It uses a morphological operator and histogram analysis to segment the foreground. In order to compare the accuracy for foreground segmentation, we use metric measurements of false positive rate (FPR), false negative rate (FNR), total error (TE), and a similarity measure (S). A series of experimental results using video sequences collected under various circumstances are discussed. The proposed system is also designed in a field-programmable gate array (FPGA) implementation with low hardware resources.

This paper proposes a rate adaptation scheme (RAS) for a wireless local area network (WLAN) station powered with microwave power transmission (MPT). A WLAN station attempting to transmit data frames when exposed to microwave radiation for MPT, experiences a reduction in the physical (PHY) layer data rate because frames are lost even when the carrier sense mechanism is used. The key idea of the proposed scheme is to utilize the output of the rectenna used for receiving microwave power. Using rectenna output, a WLAN station based on the proposed scheme assesses whether the station is exposed to microwave radiation for MPT. Then, using historical data corresponding to the assessment result, the station selects an appropriate PHY data rate. The historical data are obtained from previous transmission results, e.g., historical data pertaining to the data frame loss ratio. The proposed scheme was implemented and verified through an experiment. Experimental results showed that the proposed scheme prevents the reduction in the PHY data rate, which is caused by the use of historical data stored in a single memory. Thus, the proposed scheme leads to an improvement in the WLAN throughput.