With the rapid growth of high performance ICT (Information Communication Technologies) devices such as smart phones and tablet PCs, multitasking has become one of the popular ways of using mobile devices. The reasons users have adopted multitask operation are that it reduces the level of dissatisfaction regarding waiting time and makes effective use of time by switching their attention from the waiting process to other content. This is a good solution to the problem of waiting; however, it may cause another problem, which is the increase in traffic volume due to the multiple applications being worked on simultaneously. Thus, an effective method to control throughput adapted to the multitasking situation is required. This paper proposes a transmission rate control method for web browsing that takes multitasking behavior into account and quantitatively demonstrates the effect of service by two different field experiments. The main contribution of this paper is to present a service design process for a new transmission rate control that takes into account human-network interaction based on the human-centered approach. We show that the degree of satisfaction in relation to waiting time did not degrade even when a field trial using a testbed showed that throughput of the background task was reduced by 40%.

Orthogonal frequency division multiplexing (OFDM) has great advantages of high spectrum efficiency and robustness against multipath fading. When the received signal is deeply suppressed by deep fading, path loss and shadowing, the received carrier power must be increased in order to avoid degrading communication quality and provide high reliability at the cost of lower system throughput. A repetition coding is very attractive in providing the high reliability with simple configuration and the low decoding complexity of maximal ratio combining. In order to analytically confirm the effectiveness of repetition coded OFDM systems, we theoretically analyze the effect of increasing the number of repetitions (diversity branches) and acquiring both time and frequency diversity gain, and then derive a closed-form equation of average bit error rate (BER) to easily but precisely evaluate the performance.

Cloud computing is becoming increasingly popular. A large number of data are outsourced to the cloud by data owners motivated to access the large-scale computing resources and economic savings. To protect data privacy, the sensitive data should be encrypted by the data owner before outsourcing, which makes the traditional and efficient plaintext keyword search technique useless. So how to design an efficient, in the two aspects of accuracy and efficiency, searchable encryption scheme over encrypted cloud data is a very challenging task. In this paper, for the first time, we propose a practical, efficient, and flexible searchable encryption scheme which supports both multi-keyword ranked search and parallel search. To support multi-keyword search and result relevance ranking, we adopt Vector Space Model (VSM) to build the searchable index to achieve accurate search results. To improve search efficiency, we design a tree-based index structure which supports parallel search to take advantage of the powerful computing capacity and resources of the cloud server. With our designed parallel search algorithm, the search efficiency is well improved. We propose two secure searchable encryption schemes to meet different privacy requirements in two threat models. Extensive experiments on the real-world dataset validate our analysis and show that our proposed solution is very efficient and effective in supporting multi-keyword ranked parallel searches.

A threshold secret sharing scheme protects content by dividing it into many pieces and distributing them among different servers. This scheme can also be utilized for the reliable delivery of important content. Thanks to this scheme, the receiver can still reconstruct the original content even if several pieces are lost during delivery due to a multiple-link failure. Nevertheless, the receiver cannot reconstruct the original content unless it receives pieces more than or equal to the threshold. This paper aims to obtain reliable delivery routes for the pieces, as this will minimize the probability that the receiver cannot reconstruct the original content. Although such a route optimization problem can be formulated using an integer linear programming (ILP) model, computation of globally optimum delivery routes based on the ILP model requires large amounts of computational resources. Thus, this paper proposes a lightweight method for computing suboptimum delivery routes. The proposed greedy method computes each of the delivery routes successively by using the conventional shortest route algorithm repeatedly. The link distances are adjusted iteratively on the basis of the given probability of failure on each link and they are utilized for the calculation of each shortest route. The results of a performance evaluation show that the proposed method can compute sub-optimum delivery routes efficiently thanks to the precise adjustment of the link distances, even in backbone networks on a real-world scale.

In this paper, we propose a novel energy-efficient sensor device management scheme called sensor device personalization (SDP) for the Internet of things (IoT) and wireless sensor networks (WSNs) based on the IEEE 802.15.4 unslotted carrier sense multiple access with collision avoidance (CSMA/CA). In the IoT and WSNs with the star topology, a coordinator device (CD), user devices (UDs), and sensor devices (SDs) compose a network, and the UDs such as smart phones and tablet PCs manage the SDs, which consist of various sensors and communication modules, e.g., smart fridge, robot cleaner, heating and cooling system, and so on, through the CD. Thus, the CD consumes a lot of energy to relay packets between the UDs and the SDs and also has a longer packet transmission delay. Therefore, in order to reduce the energy consumption and packet transmission delay, in the proposed SDP scheme, the UDs obtain a list of SD profiles (including SDs' address information) that the UDs want to manage from the CD, and then the UDs and the SDs directly exchange control messages using the addresses of the SDs. Through analytical models, we show that the proposed SDP scheme outperforms the conventional scheme in terms of normalized throughput, packet transmission delay, packet loss probability, and total energy consumption.

We proposed and evaluated a speech intelligibility estimation method that does not require a clean speech reference signal. The propose method uses the features defined in the ITU-T standard P.563, which estimates the overall quality of speech without the reference signal. We selected two sets of features from the P.563 features; the basic 9-feature set, which includes basic features that characterize both speech and background noise, e.g., cepstrum skewness and LPC kurtosis, and the extended 31-feature set with 22 additional features for a more accurate description of the degraded speech and noise, e.g., SNR, average pitch, and spectral clarity among others. Four hundred noise samples were added to speech, and about 70% of these samples were used to train a support vector regression (SVR) model. The trained models were used to estimate the intelligibility of speech degraded by added noise. The proposed method showed a root mean square error (RMSE) value of about 10% and correlation with subjective intelligibility of about 0.93 for speech distorted with known noise type, and RMSE of about 16% and a correlation of about 0.84 for speech distorted with unknown noise type, both with either the 9 or the 31-dimension feature set. These results were higher than the estimation using frequency-weighed SNR calculated in critical frequency bands, which requires the clean reference signal for its calculation. We believe this level of accuracy proves the proposed method to be applicable to real-time speech quality monitoring in the field.

We previously proposed an inaudible non-blind digital-audio watermarking approach based on cochlear delay (CD) characteristics. There are, however, three remaining issues with regard to blind-detectability, frame synchronization related to confidentiality, and reversibility. We attempted to solve these issues in developing the proposed approach by taking blind-detectability and reversibility of audio watermarking into consideration. Frame synchronization was also incorporated into the proposed approach to improve confidentiality. We evaluated inaudibility, robustness, and reversibility with the new approach by carrying out three objective tests (PEAQ, LSD, and bit-detection or SNR) and six robustness tests. The results revealed that inaudible, robust, blindly-detectable, and semi-reversible watermarking based on CD could be accomplished.

The sense of presence is crucial to evaluate the performance of audio-visual (AV) equipment and content. Previously, the overall presence was evaluated for a set of AV content items by asking subjects to judge the presence of the entire content item. In this study, the sense of presence is evaluated for a time-series using the method of continuous judgment by category. Specifically, the audio signals of 40 content items with durations of approximately 30 s each were recorded with a dummy head, and then presented as stimuli to subjects via headphones. The corresponding visual signals were recorded using a video camera in the full-HD format, and reproduced on a 65-inch display. In the experiments, 20 subjects evaluated the instantaneous sense of presence of each item on a seven-point scale under two conditions: audio-only or audio-visual. At the end of the time-series, the subjects also evaluated the overall presence of the item by seven categories. Based on these results, the effects of visual information on the sense of presence were examined. The overall presence is highly correlated with the ten-percentile exceeded presence score, S10, which is the score that is exceeded for the 10% of the time during the responses. Based on the instantaneous presence data in this study, we are one step closer to our ultimate goal of developing a real-time operational presence meter.

While online social networking is a popular way for people to share information, it carries the risk of unintentionally disclosing personal information. One way to reduce this risk is to anonymize personal information in messages before they are posted. Furthermore, if personal information is somehow disclosed, the person who disclosed it should be identifiable. Several methods developed for anonymizing personal information in natural language text simply remove sensitive phrases, making the anonymized text message unnatural. Other methods change the message by using synonymization or structural alteration to create fingerprints for detecting disclosure, but they do not support the creation of a sufficient number of fingerprints for friends of an online social network user. We have developed a system for anonymizing personal information in text messages that generalizes sensitive phrases. It also creates a sufficient number of fingerprints of a message by using synonyms so that, if personal information is revealed online, the person who revealed it can be identified. A distribution metric is used to ensure that the degree of anonymization is appropriate for each group of friends. A threshold is used to improve the naturalness of the fingerprinted messages so that they do not catch the attention of attackers. Evaluation using about 55,000 personal tweets in English demonstrated that our system creates sufficiently natural fingerprinted messages for friends and groups of friends. The practicality of the system was demonstrated by creating a web application for controlling messages posted on Facebook.

Recently, Impagliazzo et al. constructed a nontrivial algorithm for the satisfiability problem for sparse threshold circuits of depth two which is a class of circuits with cn wires. We construct a nontrivial algorithm for a larger class of circuits. Two gates in the bottom level of depth two threshold circuits are dependent, if the output of the one is always greater than or equal to the output of the other one. We give a nontrivial circuit satisfiability algorithm for a class of circuits which may not be sparse in gates with dependency. One of our motivations is to consider the relationship between the various circuit classes and the complexity of the corresponding circuit satisfiability problem of these classes. Another background is proving strong lower bounds for TC0 circuits, exploiting the connection which is initiated by Ryan Williams between circuit satisfiability algorithms and lower bounds.

This paper describes a novel method to improve the performance of second language speech recognition when the mother tongue of users is known. Considering that second language speech usually includes less fluent pronunciation and more frequent pronunciation mistakes, the authors propose using a reduced phoneme set generated by a phonetic decision tree (PDT)-based top-down sequential splitting method instead of the canonical one of the second language. The authors verify the efficacy of the proposed method using second language speech collected with a translation game type dialogue-based English CALL system. Experiments show that a speech recognizer achieved higher recognition accuracy with the reduced phoneme set than with the canonical phoneme set.

Secret sharing (SS) has been extensively studied as for both secure data storage and a fundamental building block for multiparty computation (MPC). Recently, Kikuchi et al. proposed a passively and unconditionally secure conversion protocol that converts from a share of a ramp scheme to another of homomorphic SS scheme. The share-size of the ramp scheme is small, and the homomorphic SS scheme is a class of SS schemes that includes Shamir's and replicated SS schemes, which are convenient for MPC. Therefore, their protocol is a conversion from an SS scheme whose share-size is small to MPC-friendly SS schemes, and can be applied to reduce the amount of data storage while maintaining extendibility to MPC. We propose five unconditionally and actively secure protocols in the honest majority. In this paper, we consider a privacy and correctness as security requirement and does not consider a robustness: A cheat caused by an active adversary must be detected. These protocols consist of two conversion protocols, two reveal protocols and a protocol generating specific randomness. Main protocols among them are two conversion protocols for bilateral conversion between a ramp scheme and linear SS scheme, and the others are building blocks of the main protocols. Linear SS scheme is a subset of homomorphic SS scheme but includes both Shamir's and replicated SS schemes. Therefore, these main protocols are conversions between an SS scheme whose share-size is small to MPC-friendly SS schemes. These main protocols are unconditionally and actively secure so if MPC protocols used after the conversion are actively secure, the whole system involving SS scheme, conversion, and MPC protocols can be unconditionally and actively secure by using our main protocols. One of our two main protocols is the first to convert from MPC-friendly SS schemes to the ramp scheme. This enhances applications, such as secure backup, of the conversion protocol. Other than the two main protocols, we propose a protocol for generating specific randomnesses and two reveal protocols as building blocks. The latter two reveal protocols are actively and unconditionally secure in the honest majority and requires O(n||F||)-bit communication per revealing, and we believe that it is independently interest.

This paper presents an efficient method for differential fault analysis (DFA) on substitution-permutation network (SPN)-based block ciphers. A combination of a permutation cancellation and an algebraic key filtering technique makes it possible to reduce the computational cost of key filtering significantly and therefore perform DFAs with new fault models injected at an earlier round, which defeats conventional countermeasures duplicating or recalculating the rounds of interest. In this paper, we apply the proposed DFA to the LED block cipher. Whereas existing DFAs employ fault models injected at the 30th round, the proposed DFA first employs a fault model injected at the 29th round. We demonstrate that the proposed DFA can obtain the key candidates with only one pair of correct and faulty ciphertexts in about 2.1h even from the 29th round fault model and the resulting key space is reduced to 24.04

Resonant scattering of flexural waves in acoustic waveguide is analysed by using the recursive transfer method (RTM). Because flexural waves are governed by a fourth-order differential equation, a localized wave tends to be induced around the scattering region and dampening wave tails from the localized wave may reach the ends of a simulation domain. A notable feature of RTM is its ability to extract the localized wave even if the dampening tail reaches the end of the simulation domain. Using RTM, the enhanced reflection caused by a localized wave is predicted and the shape of the localized wave is explored at its resonance with the incident wave.

This letter studies the problem of cooperative spectrum sensing in wideband cognitive radio networks. Based on the basis expansion model (BEM), the problem of estimation of power spectral density (PSD) is transformed to estimation of BEM coefficients. The sparsity both in frequency domain and space domain is used to construct a sparse estimation structure. The theory of L1/2 regularization is used to solve the compressed sensing problem. Simulation results demonstrate the effectiveness of the proposed method.

This letter deals with the signal declipping algorithm based on the matrix rank minimization approach, which can be applied to the signal restoration in linear systems. We focus on the null space of a low-rank matrix and provide a block adaptive algorithm of the matrix rank minimization approach to signal declipping based on the null space alternating optimization (NSAO) algorithm. Numerical examples show that the proposed algorithm is faster and has better performance than other algorithms.

This paper proposes a disaster recovery method for transport networks. In a scenario of recovery from a disaster, a network is repaired through multiple restoration stages because repair resources are limited. In a practical case, a network should provide the reachability of important traffic in transient stages, even as service interruption risks and/or operational overheads caused by transport paths switching are suppressed. Then, we define the multi-objective optimization problem: maximizing the traffic recovery ratio and minimizing the number of switched transport paths at each stage. We formulate our problem as linear programming, and show that it yields pareto-optimal solutions of traffic recovery versus the number of switched paths. We also propose a heuristic algorithm for applying to networks consisting of a few hundred nodes, and show that it can produce sub-optimal solutions that differ only slightly from optimal solutions.

A multi-port device is characterized using measurement results of a two-port Vector Network Analyzer (VNA) with four different structures. The loads used as terminations are open-, or short-circuited transmission lines (TLs), which are characterized along with Ground-Signal-Ground pads based on L-2L de-embedding method. A new characterization method for a four-port device is introduced along with its theory. The method is validated using simulation and measurement results. The characterized four-port device is a Crossing Transmission Line (CTL), mainly used for over-pass or under-pass of RF signals. Four measurement results are used to characterize the CTL. The S-parameter response of the CTL is found. To compare the results, reconstructed responses compared with the measurements. Results show good agreement between the measured and modeled results from 1 GHz to 110 GHz.

Network traffic load usually differs significantly at different times of a day due to users' different time-preference. Network congestion may happen in traffic peak times. In order to prevent this from happening, network service providers (NSPs) can either over-provision capacity for demand at peak times of the day, or use dynamic time-dependent pricing (TDP) scheme to reduce the demand at traffic peak times. Since over-provisioning network capacity is costly, many researchers have proposed TDP schemes to control congestion as well as to improve the revenue of NSPs. To the best of our knowledge, all the studies on TDP schemes consider only the monopoly or duopoly NSP case. In our previous work, the duopoly NSP case has been studied with the assumption that each NSP has complete information of quality of service (QoS) of the other NSP. In this paper, an oligopoly NSP case is studied. NSPs try to maximize their overall revenue by setting time-dependent price, while users choose NSPs by considering their own time preference, congestion status in the networks and the price set by the NSPs. The interactions among NSPs are modeled as an oligopoly Bertrand game. Firstly, assuming that each NSP has complete information of QoS of all NSPs, a unique Nash equilibrium of the game is established under the assumption that users' valuation of QoS is uniformly distributed. Secondly, the assumption of complete information of QoS of all NSPs is relaxed, and a learning algorithm is proposed for NSPs to achieve the Nash equilibrium of the game. Analytical and experimental results show that NSPs can benefit from TDP scheme, however, not only the competition effect but also the incomplete information among NSPs causes revenue loss for NSPs under the TDP scheme.