There exist two intrinsic issues in multiple-shot person re-identification: (1) large differences in camera view, illumination, and non-rigid deformation of posture that make the intra-class variance even larger than the inter-class variance; (2) only a few training data that are available for learning tasks in a realistic re-identification scenario. In our previous work, we proposed a local distance comparison framework to deal with the first issue. In this paper, to deal with the second issue (i.e., to derive a reliable distance metric from limited training data), we propose an adaptive learning method to learn an adaptive distance metric, which integrates prior knowledge learned from a large existing auxiliary dataset and task-specific information extracted from a much smaller training dataset. Experimental results on several public benchmark datasets show that combined with the local distance comparison framework, our adaptive learning method is superior to conventional approaches.

Internet traffic classification is an essential step for stable service provision. The payload signature classifier is considered a reliable method for Internet traffic classification but is prohibitively computationally expensive for real-time handling of large amounts of traffic on high-speed networks. In this paper, we describe several design techniques to minimize the search space of traffic classification and improve the processing speed of the payload signature classifier. Our suggestions are (1) selective matching algorithms based on signature type, (2) signature reorganization using hierarchical structure and traffic locality, and (3) early packet sampling in flow. Each can be applied individually, or in any combination in sequence. The feasibility of our selections is proved via experimental evaluation on traffic traces of our campus and a commercial ISP. We observe 2 to 5 times improvement in processing speed against the untuned classification system and Snort Engine, while maintaining the same level of accuracy.

A discriminative reference-based method for scene image categorization is presented in this letter. Reference-based image classification approach combined with K-SVD is approved to be a simple, efficient, and effective method for scene image categorization. It learns a subspace as a means of randomly selecting a reference-set and uses it to represent images. A good reference-set should be both representative and discriminative. More specifically, the reference-set subspace should well span the data space while maintaining low redundancy. To automatically select reference images, we adapt affinity propagation algorithm based on data similarity to gather a reference-set that is both representative and discriminative. We apply the discriminative reference-based method to the task of scene categorization on some benchmark datasets. Extensive experiment results demonstrate that the proposed scene categorization method with selected reference set achieves better performance and higher efficiency compared to the state-of-the-art methods.

A path loss model for low antenna heights below surrounding buildings in residential areas is presented to contribute to the construction of VHF band wireless systems. The model is constructed on the basis of measurement results at 167.65MHz, near center frequency at VHF band. Path loss characteristics in the middle VHF band are compared to those in bands above UHF. The dominant paths in bands above UHF include propagation paths below surrounding buildings, such as paths along roads. However, in the middle VHF band, these paths are instantly attenuated because their 1st Fresnel zone radius is larger than the average building height or road width. The dominant path in the middle VHF band is the over-roof propagation path, and the 1st Fresnel zone of the path is shielded by the buildings and the ground surface. The proposed path loss model has two features. First, it derives the effective height of the ground surface from the terrain profile of the buildings and the ground surface. Second, it uses formulas of a two-path model to take the shielding of the 1st Fresnel zone into account. Finally, it is shown that the proposed model is able to predict the path loss measurement results more accurately than the conventional model.

We have improved a compact model for the injection-enhancedinsulated-gate bipolar transistor for inverter circuit simulation. The holeaccumulation of floating-base region and potential change are modeled. It turned out that negative capacitance which occurs by floating-base region has the dependence of frequency. It is necessary to consider the frequency dependence of the total gate capacitance for transient simulation. We analyzed the relationship between negative gate capacitance and current rise rate at the switch turn-on timing and device structure. The development model simulation result is well reproduced $I_{ extrm{c}}$ and $V_{ extrm{ce}}$ of measurement data, and the switching loss calculation accuracy is improved.

In recent years, ray space (or light field in other literatures) photography has become popular in the area of computer vision and image processing, and the capture of a ray space has become more significant to these practical applications. In order to handle the huge data problem in the acquisition stage, original data are compressively sampled in the first place and completely reconstructed later. In this paper, in order to achieve better reconstruction quality and faster reconstruction speed, we propose a statistically weighted model in the reconstruction of compressively sampled ray space. This model can explore the structure of ray space data in an orthogonal basis, and integrate this structure into the reconstruction of ray space. In the experiment, the proposed model can achieve much better reconstruction quality for both 2D image patch and 3D image cube cases. Especially in a relatively low sensing ratio, about 10%, the proposed method can still recover most of the low frequency components which are of more significance for representation of ray space data. Besides, the proposed method is almost as good as the state-of-art technique, dictionary learning based method, in terms of reconstruction quality, and the reconstruction speed of our method is much faster. Therefore, our proposed method achieves better trade-off between reconstruction quality and reconstruction time, and is more suitable in the practical applications.

Provisioning multiple paths can improve fault tolerance and transport capability of multi-routing in wireless networks. Disjoint paths can improve the diversity of paths and further reduce the risk of simultaneous link failure and network congestion. In this paper we first address a many-to-one disjoint-path problem (MOND) for multi-path routing in a multi-hop wireless network. The objective of this problem is to maximize the minimum number of disjoint paths of every source to the destination. We prove that it is NP-hard to obtain k disjoint paths for every source when k ≥ 3. To solve this problem efficiently, we propose a heuristic algorithm called TOMAN based on network flow theory. Experimental results demonstrate that it outperforms three related algorithms.

Oblivious RAM (ORAM) schemes, the concept introduced by Goldreich and Ostrovsky, are very useful technique for protecting users' privacy when storing data in remote untrusted servers and running software on untrusted systems. However they are usually considered impractical due to their huge overhead. In order to reduce overhead, many improvements have been presented. Thanks to these improvements, ORAM schemes can be considered practical on cloud environment where users can expect huge storage and high computational power. Especially for private information retrieval (PIR), some literatures demonstrated they are usable. Also dedicated PIRs have been proposed and shown that they are usable in practice. Yet, they are still impractical for protecting software running on untrusted systems. We first survey recent researches on ORAM and PIR. Then, we present a practical software-based memory protection scheme applicable to several environments. The main feature of our scheme is that it records the history of accesses and uses the history to hide the access pattern. We also address implementing issues of ORAM and propose practical solutions for these issues.

As the development of Internet-of-Things is moving towards large scale industry, such as logistic and manifacturing, there is a need for end-users to get involved in the process of creating IoT easily. In this paper, we introduce PaperIO, a paper-based 3D I/O interface, in which a single piece of paper can be sensed and actuated at the same time in three dimensions using the technology of selective inductive power transmission. With this technology, paper material with multiple embedded receivers, can not only selectively receive inductive power to perform paper-computing behavior, but also work as input sensors to communicate with power transmitter wirelessly. This technology allows the creation of paper-based sensor and actuators, and forms an Interent of Embedded Paper-craft. This paper presents the detailed implementation of the system, results of the technical experiments, and a few sample applications of the presented paper-based 3D I/O interface, and finally discusses the future plan of this research.

In this paper, we propose a texture descriptor based on amplitude distribution and phase distribution of the discrete Fourier transform (DFT) of an image. One dimensional DFT is applied to all the rows and columns of an image. Histograms of the amplitudes and gradients of the phases between adjacent rows/columns are computed as the feature descriptor, which is called aggregated DFT (ADFT). ADFT can be easily combined with completed local binary pattern (CLBP). The combined feature captures both global and local information of the texture. ADFT is designed for isotropic textures and demonstrated to be effective for roughness classification of castings. Experimental results show that the amplitude part of ADFT is also discriminative in describing anisotropic textures and it can be used as a complementary descriptor of local texture descriptors such as CLBP.

Two types of 3D folded dipole antenna with feed line (FDAFL) were reported for a small terminal, which covered WiMAX 2.5/3.5GHz bands and WLAN 2.4GHz band. In this study, folded monopole antenna (FMA) is proposed as a variant of FDAFL. We show the broadband characteristics of FMA and determine the most suitable configuration of FMA array for realizing MIMO system. Also, a multiband variant is created by introducing a parasitic element to FMA. The result is a multiband FMA array with parasitic elements operating at 5GHz band of WiMAX and WLAN as well as WiMAX 2.5/3.5GHz bands and WLAN 2.4GHz band with total antenna efficiency of between 70% to 96% and the envelope correlation coefficient of less than 0.02. Finally, a prototype antenna is implemented, and we confirm the validity of the simulation by comparison to measured results.

This paper proposes a noise reduction method for impact noise with damped oscillation caused by clinking a glass, hitting a bottle, and so on. The proposed method is based on the zero phase (ZP) signal defined as the IDFT of the spectral amplitude. When the target noise can be modeled as the sum of the impact part and the damped oscillation part, the proposed method can reduce them individually. First, the proposed method estimates the damped oscillation spectra and subtracts them from the observed spectra. Then, the impact part is reduced by replacing several samples of the ZP observed signal. Simulation results show that the proposed method improved 10dB of SNR of real impact noise.

Boneh et al. proposed the new idea of pairing-based cryptography by using the composite order group instead of prime order group. Recently, many cryptographic schemes using pairings of composite order group were proposed. Miller's algorithm is used to compute pairings, and the time of computing the pairings depends on the cost of calculating the Miller loop. As a method of speeding up calculations of the pairings of prime order, the number of iterations of the Miller loop can be reduced by choosing a prime order of low Hamming weight. However, it is difficult to choose a particular composite order that can speed up the pairings of composite order. Kobayashi et al. proposed an efficient algorithm for computing Miller's algorithm by using a window method, called Window Miller's algorithm. We can compute scalar multiplication of points on elliptic curves by using a window hybrid binary-ternary form (w-HBTF). In this paper, we propose a Miller's algorithm that uses w-HBTF to compute Tate pairing efficiently. This algorithm needs a precomputation both of the points on an elliptic curve and rational functions. The proposed algorithm was implemented in Java on a PC and compared with Window Miller's Algorithm in terms of the time and memory needed to make their precomputed tables. We used the supersingular elliptic curve y2=x3+x with embedding degree 2 and a composite order of size of 2048-bit. We denote w as window width. The proposed algorithm with w=6=2·3 was about 12.9% faster than Window Miller's Algorithm with w=2 although the memory size of these algorithms is the same. Moreover, the proposed algorithm with w=162=2·34 was about 12.2% faster than Window Miller's algorithm with w=7.

This paper focuses on the S-parameter method that is a basic method for measuring the input impedance of balanced-fed antennas. The basic concept of the method is summarized using the two-port network, and it is shown that the method can be enhanced to the unbalanced antennas using a formulation based on incident and reflected waves. The compensation method that eliminates the influence of a measurement jig and the application of the S-parameter method for the measurement of a radiation pattern with reduced unbalanced currents are explained. Further, application of the method for measuring the reflection and coupling coefficients of multiple antennas is introduced. The measured results of the input impedance of a dipole antenna, radiation patterns of a helical antenna on a small housing, and S-parameters of multiple antennas on a small housing are examined, and the measured results obtained with the S-parameter method are verified.

The performance in terms of the user separation of multi-user multiple-input multiple-output (MU-MIMO) depends on not only the spatial correlation but also the location of the mobile stations (MSs). In order to take into account the performance in terms of the user separation, we need to consider the granularity of the beam and null width of the precoded antenna pattern in addition to the spatial correlation to determine the base station (BS) antenna configuration. In this paper, we propose Smart Vertical MIMO (SV-MIMO) as the best antenna configuration that achieves both spatial correlation and granularity of the beam and null width of the precoded antenna pattern. We evaluate SV-MIMO in a field experiment using a downlink 4-by-2 MU-MIMO configuration focusing on the dependency of the location of the MSs in Yokosuka, Japan. The majority of the measurement course is under line-of-sight (LOS) conditions in a single cell environment. The MSs are almost uniformly set 30 to 60 degrees in azimuth and 12 to 30 degrees in elevation and the distance from the BS antennas is approximately 150m at maximum. We also evaluate the performance of 4-by-2 MU-MIMO using the conventional type of horizontal array antenna and show the difference. The field experimental results show that throughput of greater than 1Gbps is achieved at the Cumulative Distribution Function (CDF) of 14% by employing SV-MIMO for Rank-4 MU-MIMO. The throughput of SV-MIMO is 30% higher than that for the horizontal array antenna configuration at the CDF of 50%.

In this paper, we consider a parallel ring-line rat-race circuit realized by replacing some parts of the ring-lines with composite right-/left-handed transmission lines (CRLH-TLs). For a conventional rat-race circuit, the minimum coupling factor is limited by the highest impedance of the ring-lines that can be manufactured by general printed circuit board (PCB) technologies. However, the coupling factor of the parallel ring-line type rat-race circuit proposed in this paper is determined by the difference between the admittances of the parallel ring-lines. As a result of designing parallel ring-line rat-race circuits having coupling factors of $-20$ and $-30$,dB for an operation frequency of 4,GHz, the proposed rat-race circuit realizes broadband characteristics of about 35.5% according to the numerical results for the $-20$,dB circuit. Furthermore, broadband characteristics including reflection, isolation, and couplings can be maintained for the fabricated $-20$,dB rat-race circuit up to an input power of 40,dBm.

This paper addresses a noise matching problem for MIMO receiver with mutual coupling in the presence of signal and antenna noise coupling. The matching network in this paper is designed to maximize the system's ergodic capacity by means of minimizing the noise figure matrix. For reducing RF circuit complexity, low noise matching design without crossover elements of the matching circuit is derived for compact symmetrical 2$ imes$2 MIMO receiver system with mutually coupled antenna. Numerical simulation verifies our analytical results and demonstrates the superiority of the proposed matching method among feasible ones. The paper furthermore investigates the lossy matching circuit with the corresponding circuit parameters in a specific condition and the effect of practical matching circuit.

Anomaly detection has several practical applications in different areas, including intrusion detection, image processing, and behavior analysis among others. Several approaches have been developed for this task such as detection by classification, nearest neighbor approach, and clustering. This paper proposes alternative clustering algorithms for the task of anomaly detection. By employing a weighted kernel extension of the least squares fitting of linear manifolds, we develop fuzzy clustering algorithms for kernel manifolds. Experimental results show that the proposed algorithms achieve promising performances compared to hard clustering techniques.

We present a low-complexity complementary pair affine projection (CP-AP) adaptive filter which employs the intermittent update of the filter coefficients. To achieve both a fast convergence rate and a small residual error, we use a scheme combining fast and slow AP filters, while significantly reducing the computational complexity. By employing an evolutionary method which automatically determines the update intervals, the update frequencies of the two constituent filters are significantly decreased. Experimental results show that the proposed CP-AP adaptive filter has an advantage over conventional adaptive filters with a parallel structure in that it has a similar convergence performance with a substantial reduction in the total number of updates.

This paper describes the design method of a broadband CMOS stacked power amplifier using harmonic control over wide bandwidths in a 0.11,$mu $m standard CMOS process. The high-efficiency can be obtained over wide bandwidths by designing a load impedance circuit as purely reactive as possible to the harmonics with broadband fundamental matching, which is based on continuous Class-F mode of operation. Furthermore, the stacked topology overcomes the low breakdown voltage limit of CMOS transistor and increases output impedance. With a 5-V supply and a fixed matching circuitry, the suggested power amplifier (PA) achieves a saturated output power of over 26.7,dBm and a drain efficiency of over 38% from 1.6,GHz to 2.2,GHz. In W-CDMA modulation signal measurements, the PA generates linear power and power added efficiency of over 23.5,dBm and 33% (@ACLR $=-33$,dBc).