Although many companies have developed robots that assist humans in the activities of daily living, safety requirements and test methods for such robots have not been established. Given the risk associated with a robot malfunctioning in the human living space, from the viewpoints of safety and EMC, it is necessary that the robot does not create a hazardous situation even when exposed to possibly severe electromagnetic disturbances in the operating environment. Thus, in immunity tests for personal care robots, the safety functions should be more rigorously tested than the other functions, and be repeatedly activated in order to ascertain that the safety functions are not lost in the presence of electromagnetic disturbances. In this paper, immunity test procedures for personal care robots are proposed that take into account functional safety requirements. A variety of test apparatuses are presented, which were built for activating the safety functions of robots, and detecting whether they were in a safe state. The practicality of the developed immunity test system is demonstrated using actual robots.

Distance bounding protocols permit a verifier to compute the distance to a prover by measuring the execution time of n rounds of challenge-response authentication. Many protocols have been proposed to reduce the false acceptance rate of the challenge-response procedure. Until now, it has been widely believed that the lowest bound of the false acceptance rate is (1/2)n when n is the number of rounds and the prover can send only one response bit for each round. In this paper, we propose a new distance bounding protocol whose false acceptance rate is (1/3)n against the distance fraud attacks and the mafia fraud attacks. To reduce the false acceptance rate, we use two challenge bits for each iteration and introduce a way of expressing three cases with the use of only one response bit, the same bit length as existing protocols. Our protocol is the first distance bounding protocol whose false acceptance rate is lower than the currently believed minimal bound without increasing the number of response bits for each round.

We fabricated highly dense Si nano-columnar structures accompanied with Si nanocrystals on W-coated quartz and characterized their local electrical transport in the thickness direction in a non-contact mode by using a Rh-coated Si cantilever with pulse bias application, in which Vmax, Vmin, and the duty ratio were set at +3.0V, -14V, and 50%, respectively. By applying a pulse bias to the bottom W electrode with respect to a grounded top electrode made of ∼10-nm-thick Au on a sample surface, non-uniform current images in correlation with surface morphologies reflecting electron emission were obtained. The change in the surface potential of the highly dense Si nano-columnar structures accompanied with Si nanocrystals, which were measured at room temperature by using an AFM/Kelvin probe technique, indicated electron injection into and extraction from Si nanocrystals, depending on the tip bias polarity. This result is attributable to efficient electron emission under pulsed bias application due to electron charging from the top electrode to the Si nanocrystals in a positively biased duration at the bottom electrode and subsequent quasi-ballistic transport through Si nanocrystals in a negatively biased duration.

The large and complicated safety-critical systems today need to keep changing to accommodate ever-changing objectives and environments. Accordingly, runtime analysis for safe reconfiguration or evaluation is currently a hot topic in the field, whereas information acquisition of external environment is crucial for runtime safety analysis. With the rapid development of web services, mobile networks and ubiquitous computing, abundant realtime information of environment is available on the Internet. To integrate these public information into runtime safety analysis of critical systems, this paper brings forward a framework, which could be implemented with open source and cross platform modules and encouragingly, applicable to various safety-critical systems.

This paper proposes out-of-band emission reduction schemes for IEEE 802.11af based Wireless Local Area Network (WLAN) systems operating in TV White Spaces (TVWS). IEEE 802.11af adopts Orthogonal Frequency Division Multiplexing (OFDM) to exploit the TVWS spectrum effectively. The combination of the OFDM and TVWS may be able to solve the problem of frequency depletion. However the TVWS transmitter must satisfy a strict transmission spectrum mask and reduce out-of-band emission to protect the primary users. The digital convolution filter is one way of reducing the out-of-band emission. Unfortunately, implementing a strict mask needs a large number of filter taps, which causes high implementation complexity. Time-domain windowing is another effective approach. This scheme reduces out-of-band emission with low complexity but at the price of shortening the effective guard interval. This paper proposes a mechanism that jointly uses these two schemes for out-of-band emission reduction. Moreover, the appropriate windowing duration design is proposed in terms of both the out-of-band emission suppression and throughput performance for all mandatory mode of IEEE 802.11af system. The proposed time-domain windowing design reduces the number of multiplier by 96.5%.

Demand for wireless communication is increasing significantly, but the frequency resources available for wireless communication are quite limited. Currently, various countries are prompting the use of TV white spaces (TVWS). IEEE 802.11 Working Group (WG) has started a Task Group (TG), namely IEEE 802.11af, to develop an international standard for Wireless local Area Networks (WLANs) in TVWS. In order to increase maximum throughput, a channel aggregation mechanism is introduced in the draft standard. In Japan, ISDB-T based area-one-segment broadcasting system (Area-1seg) which is a digital TV broadcast service in limited areas has been permitted to offer actual TVWS services since April 2012. The operation of the IEEE 802.11af system shall not jeopardize the Area-1seg system due to the common operating frequency band. If the Area-1seg partially overlaps with the IEEE 802.11af in some frequency, the IEEE 802.11af cannot use the channel aggregation mechanism due to a lack of channels. As a result, the throughput of the IEEE 802.11af deteriorates. In this paper, the physical layer of IEEE 802.11af D4.0 is introduced briefly, and a partial subcarrier system for IEEE 802.11af is proposed to efficiently use the TVWS spectrum. The IEEE 802.11af co-exist with the Area-1seg by using null subcarriers. Computer simulation shows up to around 70% throughput gain is achieved with the proposed mechanism.

A new type of the affine projection (AP) algorithms which incorporates the sparsity condition of a system is presented. To exploit the sparsity of the system, a weighted l1-norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weightings for l1-norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results show that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems.

With the ever-growing prevalence of web 2.0, users can access information and resources easily and ubiquitously. It becomes increasingly important to understand the characteristics of user's complex behavior for efficient network management and security monitoring. In this paper, we develop a novel method to visualize and measure user's web-communication-behavior character in large-scale networks. First, we employ the active and passive monitoring methods to collect more than 20,000 IP addresses providing web services, which are divided into 12 types according to the content they provide, e.g. News, music, movie and etc, and then the IP address library is established with elements as (servicetype, IPaddress). User's behaviors are complex as they stay in multiple service types during any specific time period, we propose the behavior spectrum to model this kind of behavior characteristics in an easily understandable way. Secondly, two kinds of user's behavior characters are analyzed: the character at particular time instants and the dynamic changing characters among continuous time points. We then employ Renyi cross entropy to classify the users into different groups with the expectation that users in the same groups have similar behavior profiles. Finally, we demonstrated the application of behavior spectrum in profiling network traffic patterns and finding illegal users. The efficiency and correctness of the proposed methods are verified by the experimental results using the actual traffic traces collected from the Northwest Regional Center of China Education and Research Network (CERNET).

The percentage of pedestrian deaths in traffic accidents is on the rise in Japan. In recent years, there have been calls for measures to be introduced to protect vulnerable road users such as pedestrians and cyclists. In this study, a method to detect and track pedestrians using an in-vehicle camera is presented. We improve the technology of detecting pedestrians by using the highly accurate images obtained with a monocular camera. In the detection step, we employ ECoHOG as the feature descriptor; it accumulates the integrated gradient intensities. In the tracking step, we apply an effective motion model using optical flow and the proposed feature descriptor ECoHOG in a tracking-by-detection framework. These techniques were verified using images captured on real roads.

Cooperative wireless communication is a communication mechanism to attain diversity through virtual antenna array that is formed by sharing resources among different users. Different strategies of resource utilization such as amplify-and-forward (AF) and decode-and-forward (DF) already exist in cooperative networks. Although the implementation of these strategies is simple, their utilization of the channel state information (CSI) is generally poor. As a result, the outage and bit error rate (BER) performances need much more improvement in order to satisfy the upcoming high data rate demands. For that to happen the spectral efficiency supported by a wireless system at a very low outage probability should be increased. In this paper a new approach, based on the previously existing ones, called CSI directed estimate and forward (CDEF) with a reduced estimation domain is proposed. A closed form solution for the optimal signal estimation at the relay using minimum mean square error (MMSE) as well as a possible set reduction of the estimation domain is given. It will be shown that this new strategy attains better symbol error rate (SER) and outage performance than AF or DF when the source relay link is comparatively better than the relay destination link. Simulation results also show that it has got better spectral efficiency at low outage probability for a given signal to noise ratio (SNR) as well as for a fixed outage probability in any operating SNR range.

Most peer-to-peer (P2P) systems build their own overlay networks for implementing peer selection strategies without taking into account the locality on the underlay network. As a result, a large quantity of traffic crossing internet service providers (ISPs) or autonomous systems (ASes) is generated on the Internet. Controlling the P2P traffic is therefore becoming a big challenge for the ISPs. To control the cost of the cross-ISP/AS traffic, ISPs often throttle and/or even block P2P applications in their networks. In this paper, we propose a router-aided approach for localizing the P2P traffic hierarchically; it features the insertion of additional delay into each P2P packet based on geographical location of its destination. Compared to the existing approaches that solve the problem on the application layer, our proposed method does not require dedicated servers, cooperation between ISPs and P2P users, or modification of existing P2P application software. Therefore, the proposal can be easily utilized by all types of P2P applications. Experiments on P2P streaming applications indicate that our hierarchical traffic localization method not only reduces significantly the inter-domain traffic but also maintains a good performance of P2P applications.

Our prior papers proposed a traffic engineering scheme to further localize traffic in peer-assisted content delivery networks (CDNs). This scheme periodically combines the content files and allows them to obtain the combined content files while keeping the price unchanged from the single-content price in order to induce altruistic clients to download content files that are most likely to contribute to localizing network traffic. However, the selection algorithm in our prior work determined which and when content files should be combined according to the cache states of all clients, which is a kind of unrealistic assumption in terms of computational complexity. This paper proposes a new concept of virtual local server to reduce the computational complexity. We could say that the source server in our mechanism has a virtual caching network inside that reflects the cache states of all clients in the ‘actual’ caching network and combines content files based on the virtual caching network. In this paper, without determining virtual caching network according to the cache states of all clients, we approximately estimated the virtual caching network from the cache states of the virtual local server of the local domain, which is the aggregated cache state of only altruistic clients in a local domain. Furthermore, we proposed a content selection algorithm based on a virtual caching network. In this paper, we used news life-cycle model as a content model that had the severe changes in cache states, which was a striking instance of dynamic content models. Computer simulations confirmed that our proposed algorithm successfully localized network traffic.

In this letter, we propose an Adaptive Modulation and Coding (AMC) scheme with relay protocols, such as Amplify-and-Forward (AF), Decode-and-Forward (DF) and De-Modulate-and-Forward (DMF). We perform simulations based on 3GPP Long Term Evolution-Advanced (LTE-A) parameters to compare the performance of an adaptive Modulation and Coding Scheme (MCS) using relay protocols of AF, DF, and DMF with non-adaptive MCS, with the same relay protocols. We analyze the performance of the proposed scheme and observe how the proposed AMC scheme with DMF performs at various Signal to Noise Ratio (SNR) regions. The simulation results have shown that the performance of the proposed AMC scheme with relay protocols of DMF is much better at lower and a higher SNR regions and also provides higher average throughput.

Traffic classification has recently gained much attention in both academic and industrial research communities. Many machine learning methods have been proposed to tackle this problem and have shown good results. However, when applied to traffic with out-of-sequence packets, the accuracy of existing machine learning approaches decreases dramatically. We observe the main reason is that the out-of-sequence packets change the spatial representation of feature vectors, which means the property of linear mapping relation among features used in machine learning approaches cannot hold any more. To address this problem, this paper proposes an Improved Dynamic Time Warping (IDTW) method, which can align two feature vectors using non-linear alignment. Experimental results on two real traces show that IDTW achieves better classification accuracy in out-of-sequence traffic classification, in comparison to existing machine learning approaches.

This letter presents a novel approach for automatic multimodal affect recognition. The audio and visual channels provide complementary information for human affective states recognition, and we utilize Boltzmann zippers as model-level fusion to learn intrinsic correlations between the different modalities. We extract effective audio and visual feature streams with different time scales and feed them to two component Boltzmann chains respectively. Hidden units of the two chains are interconnected to form a Boltzmann zipper which can effectively avoid local energy minima during training. Second-order methods are applied to Boltzmann zippers to speed up learning and pruning process. Experimental results on audio-visual emotion data recorded by ourselves in Wizard of Oz scenarios and collected from the SEMAINE naturalistic database both demonstrate our approach is robust and outperforms the state-of-the-art methods.

The outage performance of a multiuser two-way amplify-and-forward (AF) relaying network, where N-th best selection scheme with the consideration to the feedback delay, is investigated. Specifically, the new closed-form expressions for cumulative distribution function (CDF) and outage probability (OP) are presented over time varying Rayleigh-fading channels. Furthermore, simple approximate OP is derived assessing the high signal-to-noise-ratio (SNR), which identifies the diversity behavior. Numerical results show excellent agreement with theoretical results.

A joint superimposed sequence design, known as SuperImposed sequence for PAPR Reduction, or SIPR, using per-tone affine precoding technique is proposed to jointly estimate MIMO-OFDM channels and reduce the peak-to-average power ratio (PAPR) for MIMO-OFDM systems. The proposed technique optimizes the trade-off between BER, MSE of the channel estimate, and PAPR reduction performance. Moreover, it does not require side information to be transmitted for the removal of the sequence at the receiver, and the transmit redundancy can be as small as 1 symbol/subcarrier. The superimposed sequence is designed by solving a convex quadratically constrained quadratic programming problem and has a computational complexity comparable to previous technique using linear programming. It is shown that SIPR can be regarded as a generalization of the popular tone reservation (TR) technique, and thus, is able to outperform TR in terms PAPR reduction performance, with less transmit overhead. Simulation results and transmit redundancy analysis of SIPR and TR are shown to illustrate the efficacy of the proposed scheme.

We present an acoustic model adaptation method where the transformation matrix for a new speaker is given by the product of bases and a weight matrix. The bases are built from the parallel factor analysis 2 (PARAFAC2) of training speakers' transformation matrices. We perform continuous speech recognition experiments using the WSJ0 corpus.

This paper investigates potential to improve fault-detection coverage by means of on-chip redundancy. The international standard on functional safety, namely, IEC61508 Ed. 2.0 Part 2 Annex E.3 prescribes the upper bound of βIC (common cause failure (CCF) ratio to all failures) is 0.25 to satisfy frequency upper bound of dangerous failure in the safety function for SIL (Safety Integrated Level) 3. On the other hand, this paper argues that the βIC does not necessarily have to be less than 0.25 for SIL 3, and that the upper bound of βIC can be determined depending on failure rate λ and CCF detection coverage. In other words, the frequency upper bound of dangerous failure for SIL3 can also be satisfied with βIC higher than 0.25 if the failure rate λ is lower than 400[fit]. Moreover, the paper shows that on-chip redundancy has potential to satisfy SIL 4 requirement; the frequency upper bound of dangerous failure for SIL4 can be satisfied with feasible ranges of βIC, λ and CCF coverage which can be realized by redundant code.

Multi-view video consists of multiple video sequences which are captured by multiple closely spaced cameras from different angles and positions. It enables each user to freely switch viewpoints by playing different video sequences. However, the transmission of multi-view video requires more bandwidth than conventional multimedia. To reduce the bandwidth, UDMVT (User Dependent Multi-view Video Transmission) based on MVC (Multi-view Video Coding) for a single user has been proposed. In UDMVT, the same frames are encoded into different versions for different users, which increases the redundant transmission. To overcome this problem and extend UDMVT to multiple users' environment, this paper proposes UMSM (User dependent Multi-view video Streaming for Multi-users). UMSM calculates the overlapping and un-overlapping frame area for multiple users from all frames based on feedback information at a server. Proposed UMSM exploits the combination of multicasting overlapping area to multiple users and unicasting un-overlapping area to each user. By means of this concept, UMSM only transmits required frames for each user. To achieve further reduction of the traffic, UMSM combines other two features with this concept. The first one is that offset of the requests from multiple users is aligned periodically to maximize the overlapping frame area. The second one is that the SP-frames standardized in H.264/AVC are exploited as the anchor frame of overlapping frame area to prevent redundant transmissions of overlapping frames. The combination of these three techniques achieves substantial reduction of the transmission bitrate for multiple users in multi-view video streaming. Simulation results using benchmark test sequences provided by MERL show that UMSM decreases the transmission bit-rate 47.2% on average for 4 users are watching the same multi-view video compared to UDMVT.