To address slow response and scattered resources in patent service, this paper proposes a one-stop service business model based on scientific and technological resource bundle. The proposed one-step model is composed of a project model, a resource bundle model and a service product model through Web Service integration. This paper describes the patent resource bundle model from the aspects of content and context, and designs the configuration of patent service products and patent resource bundle. The model is then applied to the patent service of the Yangtze River Delta urban agglomeration in China, and the monthly agent volume increased by 38.8%, and the average response time decreased by 14.3%. Besides, it is conducive to improve user satisfaction and resource sharing efficiency of urban agglomeration.

Binary bent functions have a strictly specified number of non-zero values. In the same way, ternary bent functions satisfy certain requirements on the elements of their value vectors. These requirements can be used to specify six classes of ternary bent functions. Classes are mutually related by encoding of function values. Given a basic ternary bent function, other functions in the same class can be constructed by permutation matrices having a block structure similar to that of the factor matrices appearing in the Good-Thomas decomposition of Cooley-Tukey Fast Fourier transform and related algorithms.

This paper presents extended-domain Golomb (XDG) code, an extension of Golomb code for sparse geometric sources as well as a generalization of extended-domain Golomb-Rice (XDGR) code, based on the idea of almost instantaneous fixed-to-variable length (AIFV) codes. Showing that the XDGR encoding can be interpreted as extended usage of the code proposed in the previous works, this paper discusses the following two facts: The proposed XDG code can be constructed as an AIFV code relating to Golomb code as XDGR code does to Rice code; XDG and Golomb codes are symmetric in the sense of relative redundancy. The proposed XDG code can be efficiently used for losslessly compressing geometric sources too sparse for the conventional Golomb and Rice codes. According to the symmetry, its relative redundancy is guaranteed to be as low as Golomb code compressing non-sparse geometric sources. Awing to this fact, the parameter of the proposed XDG code, which is more finely tunable than the conventional XDGR code, can be optimized for given inputs using the conventional techniques. Therefore, it is expected to be more useful for many coding applications that deal with geometric sources at low bit rates.

In network function virtualization (NFV) environments, service chaining is an emerging technology that enables network operators to provide network service dynamically and flexibly by using virtual network function (VNF). In the service chaining, a service chain is expected to be constructed based on VNF performances such as dependences among VNFs and traffic changing effects in VNFs. For achieving optimal data transmission services in NFV environments, we focus on the optimal service chain construction based on VNF performances so that both the maximum amount of traffic on links and the total number of VNF instances are decreased. In this paper, at first, an optimization problem is formulated for determining placements of VNFs and a route for each service chain. The service chains can be constructed by solving this optimization problem with an optimization software or meta-heuristic algorithm. Then, for the optimization problem, we propose a heuristic service chain construction algorithm. By using our proposed algorithm, the service chains can be constructed appropriately more quickly. We evaluate the performance of the proposed heuristic algorithm with simulation, and we investigate the effectiveness of the heuristic algorithm from the performance comparison. From some numerical examples, we show that the proposed heuristic algorithm is effective to decrease the amount of traffic and the number of VNF instances. Moreover, it is shown that our proposed heuristic algorithm can construct service chains quickly.

This paper reports the results of a new test on what types of failure cause falls in the stock prices of telecommunication service providers. This analysis of stock price is complementary to our previous one on market share. A clear result of our new test is that the type of failure causing falls in stock price is different from the type causing decline in market share. Specifically, the previous study identified frequent failures as causes of decline in market share, while the current study indicates large failures affecting many users as causes of falls in stock price. Together, these analyses give important information for reliability designs of telecommunications networks.

This paper proposes two high-fidelity and computationally efficient neural voice conversion (VC) methods based on a direct waveform modification using spectral differentials. The conventional spectral-differential VC method with a minimum-phase filter achieves high-quality conversion for narrow-band (16 kHz-sampled) VC but requires heavy computational cost in filtering. This is because the minimum phase obtained using a fixed lifter of the Hilbert transform often results in a long-tap filter. Furthermore, when we extend the method to full-band (48 kHz-sampled) VC, the computational cost is heavy due to increased sampling points, and the converted-speech quality degrades due to large fluctuations in the high-frequency band. To construct a short-tap filter, we propose a lifter-training method for data-driven phase reconstruction that trains a lifter of the Hilbert transform by taking into account filter truncation. We also propose a frequency-band-wise modeling method based on sub-band multi-rate signal processing (sub-band modeling method) for full-band VC. It enhances the computational efficiency by reducing sampling points of signals converted with filtering and improves converted-speech quality by modeling only the low-frequency band. We conducted several objective and subjective evaluations to investigate the effectiveness of the proposed methods through implementation of the real-time, online, full-band VC system we developed, which is based on the proposed methods. The results indicate that 1) the proposed lifter-training method for narrow-band VC can shorten the tap length to 1/16 without degrading the converted-speech quality, and 2) the proposed sub-band modeling method for full-band VC can improve the converted-speech quality while reducing the computational cost, and 3) our real-time, online, full-band VC system can convert 48 kHz-sampled speech in real time attaining the converted speech with a 3.6 out of 5.0 mean opinion score of naturalness.

Since most sensor data depend on each other, time-series anomaly detection is one of practical applications of IoT devices. Such tasks are handled by Recurrent Neural Networks (RNNs) with a feedback structure, such as Long Short Term Memory. However, their learning phase based on Stochastic Gradient Descent (SGD) is computationally expensive for such edge devices. This issue is addressed by executing their learning on high-performance server machines, but it introduces a communication overhead and additional power consumption. On the other hand, Recursive Least-Squares Echo State Network (RLS-ESN) is a simple RNN that can be trained at low cost using the least-squares method rather than SGD. In this paper, we propose its area-efficient hardware implementation for edge devices and adapt it to human activity anomaly detection as an example of interdependent time-series sensor data. The model is implemented in Verilog HDL, synthesized with a 45 nm process technology, and evaluated in terms of the anomaly capability, hardware amount, and performance. The evaluation results demonstrate that the RLS-ESN core with a feedback structure is more robust to hyper parameters than an existing Online Sequential Extreme Learning Machine (OS-ELM) core. It consumes only 1.25 times larger hardware amount and 1.11 times longer latency than the existing OS-ELM core.

Network function virtualization (NFV) enables network operators to flexibly provide diverse virtualized functions for services such as Internet of things (IoT) and mobile applications. To meet multiple quality of service (QoS) requirements against time-varying network environments, infrastructure providers must dynamically adjust the amount of computational resources, such as CPU, assigned to virtual network functions (VNFs). To provide agile resource control and adaptiveness, predicting the virtual server load via machine learning technologies is an effective approach to the proactive control of network systems. In this paper, we propose an adjustment mechanism for regressors based on forgetting and dynamic ensemble executed in a shorter time than that of our previous work. The framework includes a reducing training data method based on sparse model regression. By making a short list of training data derived from the sparse regression model, the relearning time can be reduced to about 57% without degrading provisioning accuracy.

In this study, we propose a secure data-providing system by using a verifiable attribute-based keyword search (VABKS), which also has the functions of privacy preservation and feedback to providers with IP anonymous server. We give both theoretic and experimental result, which show that our proposed system is a secure system with real-time property. One potential application of the system is to Integrated Broadcast-Broadband (IBB) services, which acquire information related to broadcast programs via broadband networks. One such service is a recommendation service that delivers recommendations matching user preferences (such as to TV programs) determined from the user's viewing history. We have developed a real-time system outsourcing data to the cloud and performing keyword searches on it by dividing the search process into two stages and performing heavy processing on the cloud side.

In this paper, in order to avoid the cascading failure by increasing the number of links in the physical network in D2D-based SNS, we propose an autonomous device placement algorithm. In this method, some relay devices are placed so as to increase the number of links in the physical network. Here, relay devices can be used only for relaying data and those are not SNS users. For example, unmanned aerial vehicles (UAV) with D2D communication capability and base stations with D2D communication capability are used as the relay devices. In the proposed method, at first, an optimization problem for minimizing node resilience which is a performance metric in order to place relay devices. Then, we investigate how relay devices should be placed based on some approximate optimal solutions. From this investigation, we propose an autonomous relay device placement in the physical network. In our proposed algorithm, relay devices can be placed without the complete information on network topology. We evaluate the performance of the proposed method with simulation, and investigate the effectiveness of the proposed method. From numerical examples, we show the effectiveness of our proposed algorithm.

Connected services have been under development in the automotive industry. Meanwhile, the volume of predictive notifications that utilize travel-related data is increasing, and there are concerns that drivers cannot process such an amount of information or do not accept and follow such predictive instructions straightforwardly because the information provided is predicted. In this work, an interactive voice system using two agents is proposed to realize notifications that can easily be accepted by drivers and enhance the reliability of the system by adding contextual information. An experiment was performed using a driving simulator to compare the following three forms of notifications: (1) notification with no contextual information, (2) notification with contextual information using one agent, and (3) notification with contextual information using two agents. The notification content was limited to probable near-miss incidents. The results of the experiment indicate that the driver may decelerate more with the one- and two-agent notification methods than with the conventional notification method. The degree of deceleration depended the number of times the notification was provided and whether there were cars parked on the streets.

Sieve algorithms are regarded as the best algorithms to solve the shortest vector problem (SVP) on account of its good asymptotical quality, which could make it outperform enumeration algorithms in solving SVP of high dimension. However, due to its large memory requirement, sieve algorithms are not practical as expected, especially on high dimension lattice. To overcome this bottleneck, TupleSieve algorithm was proposed to reduce memory consumption by a trade-off between time and memory. In this work, aiming to make TupleSieve algorithm more practical, we combine TupleSieve algorithm with SubSieve technique and obtain a sub-exponential gain in running time. For 2-tuple sieve, 3-tuple sieve and arbitrary k-tuple sieve, when selecting projection index d appropriately, the time complexity of our algorithm is O(20.415(n-d)), O(20.566(n-d)) and $O(2^{rac{kmathrm{log}_2p}{1-k}(n-d)})$ respectively. In practice, we propose a practical variant of our algorithm based on GaussSieve algorithm. Experimental results show that our algorithm implementation is about two order of magnitude faster than FPLLL's GuassSieve algorithm. Moreover, techniques such as XOR-POPCNT trick, progressive sieving and appropriate projection index selection can be exploited to obtain a further acceleration.

Edge computing offers computing capability with ultra-low response times by leveraging servers close to end-user devices. Due to the mobility of end-user devices, the latency between the servers and the end-user devices can become long and the response time might become unacceptable for an application service. Service (container) migration that follows the handover of end-user devices retains the response time. Service migration following the mass movement of people in the same geographic area and at the same time due to an event (e.g., commuting) generates heavy bandwidth usage in the mobile backhaul network. Heavy usage by service migration reduces available bandwidth for ordinary application traffic in the network. Shaping the migration traffic limits the bandwidth usage while delaying service migration and increasing the response time of the container for the moving end-user device. Furthermore, targets of migration decisions increase (i.e., the system load) because delaying a migration process accumulates containers waiting for migration. In this paper, we propose a migration scheduling method to control bandwidth usage for migration in a network and ensure timely processing of service migration. Simulations that compare the proposal with state-of-the-art methods show that the proposal always suppresses the bandwidth usage under the predetermined threshold. The method reduced the number of containers exceeding the acceptable response time up to 40% of the compared state-of-the-art methods. Furthermore, the proposed method minimized the targets of migration decisions.

Sparse orthogonal matrices are proposed to improve the convergence property of expectation propagation (EP) for sparse signal recovery from compressed linear measurements subject to known dense and ill-conditioned multiplicative noise. As a typical problem, this letter addresses generalized spatial modulation (GSM) in over-loaded and spatially correlated multiple-input multiple-output (MIMO) systems. The proposed sparse orthogonal matrices are used in precoding and constructed efficiently via a generalization of the fast Walsh-Hadamard transform. Numerical simulations show that the proposed sparse orthogonal precoding improves the convergence property of EP in over-loaded GSM MIMO systems with known spatially correlated channel matrices.

In this paper, we propose a real-time BSS (Blind Source Separation) system with two microphones that extracts only desired sound sources. Under the assumption that the desired sound sources are close to the microphones, the proposed BSS system suppresses distant sound sources as undesired sound sources. We previously developed a BSS system that can estimate the distance from a microphone to a sound source and suppress distant sound sources, but it was not a real-time processing system. The proposed BSS system is a real-time version of our previous BSS system. To develop the proposed BSS system, we simplify some BSS procedures of the previous system. Simulation results showed that the proposed system can effectively suppress the distant source signals in real-time and has almost the same capability as the previous system.

In this paper, we clarify the importance of performance evaluation using a plurality of smartphones in a positioning system based on radio waves. Specifically, in a positioning system using bluetooth low energy, the positioning performance of two types of positioning algorithms is performed using a plurality of smartphones. As a result, we confirmed that the fingerprint algorithm does not always provide sufficient positioning performance. It depends on the model of the smartphone used. On the other hand, the hybrid algorithm that the authors have already proposed is robust in the difference of the received signal characteristics of the smartphone. Consequently, we spotlighted that the use of multiple devices is essential for providing high-quality location-based services in real environments in the performance evaluation of radio wave-based positioning systems using smartphones.

Side-channel (SC) leakage from a cryptographic device chip is simulated as the dynamic current flowing out of the chip. When evaluating the simulated current, an evaluation by comparison with an actual measurement is essential; however, it is difficult to compare them directly. This is because a measured waveform is typically the output voltage of probe placed at the observation position outside the chip, and the actual dynamic current is modified by several transfer impedances. Therefore, in this paper, the probe voltage is converted into the dynamic current by using an EMC macro-model of a cryptographic device being evaluated. This paper shows that both the amplitude and the SC analysis (correlation power analysis and measurements to disclosure) results of the simulated dynamic current were evaluated appropriately by using the EMC macro-model. An evaluation confirms that the shape of the simulated current matches the measured one; moreover, the SC analysis results agreed with the measured ones well. On the basis of the results, it is confirmed that a register-transfer level (RTL) simulation of the dynamic current gives a reasonable estimation of SC traces.

Input devices based on direct touch have replaced traditional ones and become the mainstream interactive technology for handheld devices. Although direct touch interaction proves to be easy to use, its problems, e.g. the occlusion problem and the fat finger problem, lower user experience. Camera-based mobile interaction is one of the solutions to overcome the problems. There are two typical interaction styles to generate camera-based pointing interaction for handheld devices: move the device or move an object before the camera. In the first interaction style, there are two approaches to move a cursor's position across the handheld display: move it towards the same direction or the opposite direction which the device moves to. In this paper, the results of a comparison research, which compared the pointing performances of three camera-based pointing techniques, are presented. All pointing techniques utilized input from the rear-facing camera. The results indicate that the interaction style of moving a finger before the camera outperforms the other one in efficiency, accuracy, and throughput. The results also indicate that within the interaction style of moving the device, the cursor positioning style of moving the cursor to the opposite direction is slightly better than the other one in efficiency and throughput. Based on the findings, we suggest giving priority to the interaction style of moving a finger when deploying camera-based pointing techniques on handheld devices. Given that the interaction style of moving the device supports one-handed manipulation, it also worth deploying when one-handed interaction is needed. According to the results, the cursor positioning style of moving the cursor towards the opposite direction which the device moves to may be a better choice.

This paper expands our previously proposed semi-blind uplink interference suppression scheme for multicell multiuser massive MIMO systems to support multi modulus signals. The original proposal applies the channel state information (CSI) aided blind adaptive array (BAA) interference suppression after the beamspace preprocessing and the decision feedback channel estimation (DFCE). BAA is based on the constant modulus algorithm (CMA) which can fully exploit the degree of freedom (DoF) of massive antenna arrays to suppress both inter-user interference (IUI) and inter-cell interference (ICI). Its effectiveness has been verified under the extensive pilot contamination constraint. Unfortunately, CMA basically works well only for constant envelope signals such as QPSK and thus the proposed scheme should be expanded to cover QAM signals for more general use. This paper proposes to apply the multi modulus algorithm (MMA) and the minimum mean square error weight derivation based on data-aided sample matrix inversion (MMSE-SMI). It can successfully realize interference suppression even with the use of multi-level envelope signals such as 16QAM with satisfactorily outage probability performance below the fifth percentile.

At the FSE conference of ToSC 2018, Kranz et al. presented their results on shortest linear programs for the linear layers of several well known block ciphers in literature. Shortest linear programs are essentially the minimum number of 2-input xor gates required to completely describe a linear system of equations. In the above paper the authors showed that the commonly used metrics like d-xor/s-xor count that are used to judge the “lightweightedness” do not represent the minimum number of xor gates required to describe a given MDS matrix. In fact they used heuristic based algorithms of Boyar-Peralta and Paar to find implementations of MDS matrices with even fewer xor gates than was previously known. They proved that the AES mixcolumn matrix can be implemented with as little as 97 xor gates. In this paper we show that the values reported in the above paper are not optimal. By suitably including random bits in the instances of the above algorithms we can achieve implementations of almost all matrices with lesser number of gates than were reported in the above paper. As a result we report an implementation of the AES mixcolumn matrix that uses only 95 xor gates. In FSE conference of ToSC 2019, Li et al. had tweaked the Boyar-Peralta algorithm to get low depth implementations of many matrices. We show that by introducing randomness in the tweaked algorithm, it is again possible to get low depth implementations with lesser number of gates than the above paper. As a result, we report a depth implementation of the AES mixcolumn matrix that uses only 103 xor gates, which is 2 gates less than the previous implementation. In the second part of the paper, we observe that most standard cell libraries contain both 2 and 3-input xor gates, with the silicon area of the 3-input xor gate being smaller than the sum of the areas of two 2-input xor gates. Hence when linear circuits are synthesized by logic compilers (with specific instructions to optimize for area), most of them would return a solution circuit containing both 2 and 3-input xor gates. Thus from a practical point of view, reducing circuit size in presence of these gates is no longer equivalent to solving the shortest linear program. In this paper we show that by adopting a graph based heuristic it is possible to convert a circuit constructed with 2-input xor gates to another functionally equivalent circuit that utilizes both 2 and 3-input xor gates and occupies less hardware area. As a result we obtain more lightweight implementations of all the matrices listed in the ToSC paper.