Understanding the structure and evolution of spatial-temporal networks is crucial for different fields ranging from urbanism to epidemiology. As location based technologies are pervasively used in our daily life, large amount of sensing data has brought the opportunities to study human activities and city dynamics. Ubiquitous cell phones can be such a sensor to analyze the social connection and boundaries of geographical regions. In this paper, we exploit user mobility based on large-scale mobile phone records to study urban areas. We collect the call data records from 1 million anonymous subscribers of 8 weeks and study the user mobility flux between different regions. First we construct the urban areas as a spatial network and use modularity detection algorithm to study the intrinsic connection between map areas. Second, another generative model which is widely used in linguistic context is adopted to explore the functions of regions. Based on mobile call records we are able to derive the partitions which match boundaries of the administrative districts. Our results can also catch the dynamics of urban area as the basis for city planning and policy making.

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.

This paper provides a prototype neural prosthesis system dedicated to restoring continence and micturition function for patients with lower urinary tract diseases, such as detrusor hyperreflexia and detrusor-sphincter dyssynergia. This system consists of an ultra low-noise electroneurogram (ENG) signal recording module, a bi-phasic electrical stimulator module and a control unit for closed-loop bladder monitoring and controlling. In order to record extremely weak ENG signal from extradural sacral nerve roots, the system provides a programmable gain from 80 dB to 117 dB. By combining of advantages of commercial-off-the-shelf (COTS) electronics and custom designed IC, the recording front-end acquires a fairly low input-referred noise (IRN) of 0.69 μVrms under 300 Hz to 3 kHz and high area-efficiency. An on-chip multi-steps single slope analog-to-digital converter (ADC) is used to digitize the ENG signals at sampling rate of 10 kSPS and achieves an effective number of bits (ENOB) of 12.5. A bi-phasic current stimulus generator with wide voltage supply range (±0.9 V to ±12.5 V) and variable output current amplitude (0-500 μA) is introduced to overcome patient-depended impedance between electrode and tissue electrolyte. The total power consumption of the entire system is 5.61 mW. Recording and stimulation function of this system is switched by control unit with time division multiplexing strategy. The functionality of this proposed prototype system has been successfully verified through in-vivo experiments from dogs extradural sacral nerve roots.

According to the match-degree between lightpaths, an HC-sharing approach is proposed to assign wavelength for an arriving transmission request for dynamic traffic in LOBS-based datacenter networks. The simulation results demonstrate that the proposed approach can provide lower block probability than other approaches for both unicast and multicast transmissions.

In Still-to-Video (S2V) face recognition, only a few high resolution images are registered for each subject, while the probe is video clips of complex variations. As faces present distinct characteristics under different scenarios, recognition in the original space is obviously inefficient. Thus, in this paper, we propose a novel discriminant analysis method to learn separate mappings for different scenario patterns (still, video), and further pursue a common discriminant space based on these mappings. Concretely, by modeling each video as a manifold and each image as point data, we form the scenario-oriented mapping learning as a Point-Manifold Discriminant Analysis (PMDA) framework. The learning objective is formulated by incorporating the intra-class compactness and inter-class separability for good discrimination. Experiments on the COX-S2V dataset demonstrate the effectiveness of the proposed method.

Multi-user MIMO (MU-MIMO) improves the system channel capacity by employing the transmission between a base station and multiple user terminals (UTs). Block Diagonalization (BD) has been proposed in order to realize MU-MIMO broadcast transmission. The BD algorithm cancels inter-user interference by creating the weights so that the channel matrixes for the other users are set to be zero matrixes. However, when the number of transmit antennas is equals to the total number of received antennas, the transmission rate by the BD algorithm is decreased. This paper proposes a new antenna selection method at the UTs to reduce the number of nulls for the other users except an intended user by the BD algorithm. It is verified via bit error rate (BER) evaluation that the proposed method is effective compared to the conventional BD algorithm, especially, when the number of users is increased with a low bit rate. Moreover, this paper evaluates the transmission rate based on IEEE802.11ac standard when considering BD algorithm with ideal user scheduling. Although the number of equivalent receive antenna is only one by the proposed method when the number of antennas at the the UT is two, it is shown that the transmission rate by the proposed method is higher than that by the conventional BD algorithm when the SNR is low even in the condition on user scheduling.

Sound source localization (SSL), with a binaural input in practical environments, is a challenging task due to the effects of noise and reverberation. In psychoacoustic research field, one of the theories to explain the mechanism of human perception in such environments is the well-known equalization-cancellation (EC) model. Motivated by the EC theory, this paper investigates a binaural SSL method by integrating EC procedures into a beamforming technique. The principle idea is that the EC procedures are first utilized to eliminate the sound signal component at each candidate direction respectively; direction of sound source is then determined as the direction at which the residual energy is minimal. The EC procedures applied in the proposed method differ from those in traditional EC models, in which the interference signals in rooms are accounted in E and C operations based on limited prior known information. Experimental results demonstrate that our proposed method outperforms the traditional SSL algorithms in the presence of noise and reverberation simultaneously.

Information-centric networking (ICN) is a promising architecture and has attracted much attention in the area of future Internet architectures. As one of the key technologies in ICN, in-network caching can enhance content retrieval at a global scale without requiring any special infrastructure. In this paper, we propose a workload-aware caching policy, LRU-GT, which allows cache nodes to protect newly cached contents for a period of time (guard time) during which contents are protected from being replaced. LRU-GT can utilize the temporal locality and distinguish contents of different popularity, which are both the characteristics of the workload. Cache replacement is modeled as a semi-Markov process under the Independent Reference Model (IRM) assumption and a theoretical analysis proves that popular contents have longer sojourn time in the cache compared with unpopular ones in LRU-GT and the value of guard time can affect the cache hit ratio. We also propose a dynamic guard time adjustment algorithm to optimize the performance. Simulation results show that LRU-GT can reduce the average hops to get contents and improve cache hit ratio.

In this letter, we combine minimum-shift keying (MSK) with physical-layer network coding (PNC) to form a new scheme, i.e., MSK-PNC, for two-way relay channels (TWRCs). The signal detection of the MSK-PNC scheme is investigated, and two detection methods are proposed. The first one is orthogonal demodulation and mapping (ODM), and the second one is two-state differential detection (TSDD). The error performance of the proposed MSK-PNC scheme is evaluated through simulations.

Realization of a planar dual-band fork three-way power divider (PDBF3PD) with Cheng's equivalent structure is discussed. The Cheng's structure consists of two open-circuited stubs and a transmission line, and the characteristic impedances tend to be high. As a result, the realizable range of frequency ratios of upper frequency to lower frequency is limited in a narrow area. In this paper, an impedance scale factor is proposed to transform characteristic impedances into a realizable range and to facilitate the design of PDBF3PDs. Theoretical considerations are verified using a simulator of ADS2008U and by an experiment.

This paper proposes a sector base station antenna for mobile wireless communication systems employing multiple woodpile metamaterial reflectors and a multiband radiator that establishes the same beamwidth in the horizontal plane for more than two frequency bands. Electromagnetic Band Gap (EBG) characteristics of each metamaterial reflector can be controlled through structural parameters of the woodpile reflector, e.g., the rod width and rod spacing. As an example of the proposed antenna, a design for a triple-frequency-band antenna that radiates at 800 MHz, 2,GHz, and 4,GHz is shown. The algorithm used to adjust the beamwidth of the proposed antenna is newly introduced and adjusts the beamwidth to be the same for each band using the rod width of the woodpile. A prototype of the proposed antenna has the approximately 90$^{circ}$ beamwidth in the horizontal plane at the three frequencies, and the measurement results agree well with the electromagnetic field simulation results.

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%.

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.

To lengthen the operational time of mobile devices, power must be managed effectively. To achieve this objective, a Discontinuous Reception (DRX) mechanism is proposed for use in the long-term evolution (LTE) network to enable user equipment (UE) to consume power efficiently. The DRX mechanism provides parameters related to base stations such as evolved Node B (eNB) to configure and manage the transition of UEs between idle (sleep) and active states. Although these parameters can be adjusted dynamically in cooperation with the traffic scheduler, a high signaling overhead and processing load might be introduced in practical deployment if the parameters are adjusted too frequently. In this study, to examine power-saving efficiency, distinct traffic types were scheduled that were constrained by various quality of service (QoS) factors without dynamically changing the DRX parameters. The concept of burst-based scheduling is proposed, based on considering the state transitions and channel conditions of each UE, to increase power-saving efficiency while concurrently satisfying the desired QoS. Both Hypertext Transfer Protocol (HTTP) and video-stream traffic models were exhaustively simulated to examine the performance of the proposed scheme and numerous scheduling alternatives were tested to compare the proposed scheme with other schemes. The simulation results indicate that video-streaming traffic is more sensitive to the scheduling schemes than HTTP traffic. The simulation results were further analyzed in terms of traffic scheduling and parameter adjustment and the analysis results can help design future studies on power management in the LTE network.

This note presents a new approach for the robustness of Hurwitz polynomials under coefficient perturbation. The s-domain Hurwitz polynomial is transformed to the z-domain polynomial by the bilinear transformation. Then an approach based on the Rouché theorem introduced in the literature is applied to compute a crude bound for the allowable coefficient variation such that the perturbed polynomial maintains the Hurwitz stability property. Three methods to obtain improved bounds are also suggested. The results of this note are computationally more efficient than the existing direct s-domain approaches especially for polynomials of higher degree. Furthermore examples indicate that the exact bound for the coefficient variation can be obtained in some cases.

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.

Cloud computing, a novel distributed paradigm to provide powerful computing capabilities, is usually adopted by developers and researchers to execute complicated IoT applications such as complex workflows. In this scenario, it is fundamentally important to make an effective and efficient workflow application scheduling and execution by fully utilizing the advantages of the cloud (as virtualization and elastic services). However, in the current stage, there is relatively few research for workflow scheduling in cloud environment, where they usually just bring the traditional methods directly into cloud. Without considering the features of cloud, it may raise two kinds of problems: (1) The traditional methods mainly focus on static resource provision, which will cause the waste of resources; (2) They usually ignore the performance fluctuation of virtual machines on the physical machines, therefore it will lead to the estimation error of task execution time. To address these problems, a novel mechanism which can estimate the probability distribution of subtask execution time based on background VM load series over physical machines is proposed. An elastic performance fluctuations-aware stochastic scheduling algorithm is introduced in this paper. The experiments show that our proposed algorithm can outperform the existing algorithms in several metrics and can relieve the influence of performance fluctuations brought by the dynamic nature of cloud.

Operating system (OS) reboots are an essential part of updating kernels and applications on laptops and desktop PCs. Long downtime during OS reboots severely disrupts users' computational activities. This long disruption discourages the users from conducting OS reboots, failing to enforce them to conduct software updates. Although the dynamic updatable techniques have been widely studied, making the system “reboot-free” is still difficult due to their several limitations. As a result, users cannot benefit from new functionality or better performance, and even worse, unfixed vulnerabilities can be exploited by attackers. This paper presents ShadowReboot, a virtual machine monitor (VMM)-based approach that shortens downtime of OS reboots in software updates. ShadowReboot conceals OS reboot activities from user's applications by spawning a VM dedicated to an OS reboot and systematically producing the rebooted state where the updated kernel and applications are ready for use. ShadowReboot provides an illusion to the users that the guest OS travels forward in time to the rebooted state. ShadowReboot offers the following advantages. It can be used to apply patches to the kernels and even system configuration updates. Next, it does not require any special patch requiring detailed knowledge about the target kernels. Lastly, it does not require any target kernel modification. We implemented a prototype in VirtualBox 4.0.10 OSE. Our experimental results show that ShadowReboot successfully updated software on unmodified commodity OS kernels and shortened the downtime of commodity OS reboots on five Linux distributions (Fedora, Ubuntu, Gentoo, Cent, and SUSE) by 91 to 98%.

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.

Since electromagnetic (EM) noise resulting from an arc discharge disturbs other electric devices, parameters on electromagnetic compatibility, as well as lifetime and reliability, are important properties for electrical contacts. To clarify the characteristics and the mechanism of the generation of the EM noise, the arc column and voltage fluctuations generated by slowly breaking contacts with external direct current (DC) magnetic field, up to 20,mT, was investigated experimentally using Ag$_{90.7{ m wt%}}$SnO$_{2,9.3{ m wt}%}$ material. Firstly the motion of the arc column is measured by high-speed camera. Secondary, the distribution of the motion of the arc and contact voltage are discussed. It was revealed that the contact voltage fluctuation in the arc duration is related to the arc column motion.