In this paper, we used the data set of domain names Global Top 1M provided by Alexa to analyze the effectiveness of Fallback in ECN. For the same test server, we first negotiate a connection with Not-ECN-Capable, and then negotiate a connection with ECN-Capable, if the sender does not receive the response to ECN-Capable negotiation from the receiver by the end of retransmission timeout, it will enter the Fallback state, and switch to negotiating a connection with Not-ECN-Capable. By extracting the header fields of the TCP/IP packets, we confirmed that in most regions, connectivity will be slightly improved after Fallback is enabled and Fallback has a positive effect on the total time of the whole access process. Meanwhile, we provided the updated information about the characteristics related to ECN with Fallback in different regions by considering the geographical region distribution of all targeted servers.

Computer networks are facing serious threats from the emergence of sophisticated new DGA bots. These DGA bots have their own dictionary, from which they concatenate words to dynamically generate domain names that are difficult to distinguish from human-generated domain names. In this letter, we propose an approach for identifying the callback communications of DGA bots based on relations among the words that constitute the character string of each domain name. Our evaluation indicates high performance, with a recall of 0.9977 and a precision of 0.9869.

Metabolic networks represent the relationship between chemical reactions and compounds in cells. In useful metabolite production using microorganisms, it is often required to calculate reaction deletion strategies from the original network to result in growth coupling, which means the target metabolite production and cell growth are simultaneously achieved. Although simple elementary flux mode (EFM)-based methods are useful for listing such reaction deletions strategies, the number of cases to be considered is often proportional to the exponential function of the size of the network. Therefore, it is desirable to develop methods of narrowing down the number of reaction deletion strategy candidates. In this study, the author introduces the idea of L1 norm minimal modes to consider metabolic flows whose L1 norms are minimal to satisfy certain criteria on growth and production, and developed a fast metabolic design listing algorithm based on it (minL1-FMDL), which works in polynomial time. Computational experiments were conducted for (1) a relatively small network to compare the performance of minL1-FMDL with that of the simple EFM-based method and (2) a genome-scale network to verify the scalability of minL1-FMDL. In the computational experiments, it was seen that the average value of the target metabolite production rates of minL1-FMDL was higher than that of the simple EFM-based method, and the computation time of minL1-FMDL was fast enough even for genome-scale networks. The developed software, minL1-FMDL, implemented in MATLAB, is available on https://sunflower.kuicr.kyoto-u.ac.jp/~tamura/software, and can be used for genome-scale metabolic network design for metabolite production.

The progress of immersive technology enables researchers and developers to construct work spaces that are freed from real-world constraints. This has motivated us to investigate the role of the human body. In this research, we examine human cognitive behaviors in obtaining an understanding of the width of their virtual body through simple yet meaningful experiments using virtual reality (VR). In the experiments, participants were modeled as an invisible board, and a spherical object was thrown at the participants to provide information for exploring the width of their invisible body. Audio and visual feedback were provided when the object came into contact with the board (body). We first explored how precisely the participants perceived the virtual body width. Next, we examined how the body perception was generated and changed as the trial proceeded when the participants tried to move right or left actively for the avoidance of collision with approaching objects. The results of the experiments indicated that the participants could become successful in avoiding collision within a limited number of trials (14 at most) under the experimental conditions. It was also found that they postponed deciding how much they should move at the beginning and then started taking evasive action earlier as they become aware of the virtual body.

In recent years, checking sleep quality has become essential from a healthcare perspective. In this paper, we propose a respiratory rate (RR) monitoring system that can be used in the bedroom without wearing any sensor devices directly. To develop the system, passive radio-frequency identification (RFID) tags are introduced and attached to a blanket, instead of attaching them to the human body. The received signal strength indicator (RSSI) and phase values of the passive RFID tags are continuously obtained using an RFID reader through antennas located at the bedside. The RSSI and phase values change depending on the respiration of the person wearing the blanket. Thus, we can estimate the RR using these values. After providing an overview of the proposed system, the RR estimation flow is explained in detail. The processing flow includes noise elimination and irregular breathing period estimation methods. The evaluation demonstrates that the proposed system can estimate the RR and respiratory status without considering the user's body posture, body type, gender, or change in the RR.

Cross-component linear model (CCLM) chromaticity prediction is a new technique introduced in Versatile Video Coding (VVC), which utilizes the reconstructed luminance component to predict the chromaticity parts, and can improve the coding performance. However, it increases the coding complexity. In this paper, how to accelerate the chroma intra-prediction process is studied based on texture characteristics. Firstly, two observations have been found through experimental statistics for the process. One is that the choice of the chroma intra-prediction candidate modes is closely related to the texture complexity of the coding unit (CU), and the other is that whether the direct mode (DM) is selected is closely related to the texture similarity between current chromaticity CU and the corresponding luminance CU. Secondly, a fast chroma intra-prediction mode decision algorithm is proposed based on these observations. A modified metric named sum modulus difference (SMD) is introduced to measure the texture complexity of CU and guide the filtering of the irrelevant candidate modes. Meanwhile, the structural similarity index measurement (SSIM) is adopted to help judging the selection of the DM mode. The experimental results show that compared with the reference model VTM8.0, the proposed algorithm can reduce the coding time by 12.92% on average, and increases the BD-rate of Y, U, and V components by only 0.05%, 0.32%, and 0.29% respectively.

Scalable networking for scientific research data transfer is a vital factor in the progress of data-intensive research, such as collaborative research on observation of black hole. In this paper, investigations of the nature of practical research traffic allow us to introduce optical flow switching (OFS) and contents delivery network (CDN) technologies into a wide area network (WAN) to realize highly scalable networking. To measure the scalability of networks, energy consumption in the WAN is evaluated by considering the practical networking equipment as well as reasonable assumptions on scientific research data transfer networks. In this study, we explore the energy consumption performance of diverse Japan and US topologies and reveal that the energy consumption of a routing and wavelength assignment algorithm in an OFS scheduler becomes the major hurdle when the number of nodes is high, for example, as high as that of the United States of America layer 1 topology. To provide computational scalability of a network dimensioning algorithm for the CDN based WAN, a simple heuristic algorithm for a surrogate location problem is proposed and compared with an optimal algorithm. This paper provides intuitions and design rules for highly scalable research data transfer networks, and thus, it can accelerate technology advancements against the encountering big-science problems.

The use of locating arrays is motivated by the use of generating software test suites to locate interaction faults in component-based systems. In this paper, we introduce a new combinatorial configuration, with which a general combinatorial description of $(ar{1},t)$-locating arrays is presented. Based on this characterization, a number of locating arrays by means of SSOA and difference covering arrays with prescribed properties are constructed effectively. As a consequence, upper bounds on the size of locating arrays with small number of factors are then obtained.

This letter proposes a downlink multiple-input multiple-output (MIMO) non-orthogonal multiple access technique that mitigates multi-cell interference (MCI) at cell-edge users, regardless of the number of interfering cells, thereby improving the spectral efficiency. This technique employs specific receive beamforming vectors at the cell-edge users in clusters to minimize the MCI. Based on the receive beamforming vectors adopted by the cell-edge users, the transmit beamforming vectors for a base station (BS) and the receive beamforming vectors for cell-center users are designed to eliminate the inter-cluster interference and maximize the spectral efficiency. As each user can directly obtain its own receive beamforming vector, this technique does not require channel feedback from the users to a BS to design the receive beamforming vectors, thereby reducing the system overhead. We also derive the upper bound of the average sum rate achievable using the proposed technique. Finally, we demonstrate through simulations that the proposed technique achieves a better sum rate performance than the existing schemes and that the derived upper bound is valid.

We have proposed a waveguide to microstrip line transition, which perpendicularly connects one waveguide into two microstrip lines. It consists of only a waveguide and a dielectric substrate with copper foils. A backshort waveguide for typical transitions is not needed. Additionally, the transition does not require via holes on the substrate. These innovations simplify the structure and the manufacturing process. We assume that our transition and antennas are co-located on the substrate. We reduced the undesirable radiation from the transition so as not to contaminate the desirable radiation pattern. In this paper, we address output phase of our transition. Since the transition has two MSL output ports connecting to different radiation elements, the phase error between two dividing signals leads to beam shift in the radiation pattern. Unfortunately, misalignment of etching pattern between copper layers of the substrate is unavoidable. The structural asymmetry causes the phase error. In order to tolerate the misalignment, we propose to add a pair of open stubs to the transition. We show that the structure drastically stabilizes the output phase. Though the stubs create some extra radiation, we confirm that the impact is not significant. Moreover, we fabricate and measure a prototype antenna that uses the transition. In the case of with stubs, the radiation pattern is unchanged even if the misalignment is severe.

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.

An n-variate Farlie-Gumbel-Morgenstern (FGM) copula consists of 2n - n - 1 parameters that express multivariate dependence among random variables. Motivated by the dependence structure of the n-variate FGM copula, we derive the exact range of the n-variate FGM copula's parameter. The exact range of the parameter is given by a closed-form expression under the condition that all parameters take the same value. Moreover, under the same condition, we reveal that the n-variate FGM copula becomes the independence copula for n → ∞. This result contributes to the dependence modeling such as reliability analysis considering dependent failure occurrence.

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.

This work presents a DNN accelerator architecture specifically designed for performing efficient inference on compressed and sparse DNN models. Leveraging the data sparsity, a runtime processing scheme is proposed to deal with the encoded weights and activations directly in the compressed domain without decompressing. Furthermore, a new data flow is proposed to facilitate the reusage of input activations across the fully-connected (FC) layers. The proposed design is implemented and verified using the Xilinx Virtex-7 FPGA. Experimental results show it achieves 1.99×, 1.95× faster and 20.38×, 3.04× more energy efficient than CPU and mGPU platforms, respectively, running AlexNet.

An eye model expressed by a revolution about the optical axis of the eye is one of the most accurate models for use in a 3D gaze estimation method. The measurement range of the previous gaze estimation method that uses two cameras based on the eye model is limited by the larger of the two angles between the gaze and the optical axes of two cameras. The previous method cannot calculate the gaze when exceeding a certain limit of the rotation angle of the eye. In this paper, we show the characteristics of reflections on the surface of the eye from two light sources, when the eye rotates. Then, we propose a method that extends the rotation angle of the eye for a 3D gaze estimation based on this model. The proposed method uses reflections that were not used in the previous method. We developed an experimental gaze tracking system for a wide projector screen and experimentally validated the proposed method with 20 participants. The result shows that the proposed method can measure the gaze of more number of people with increased accuracy compared with the previous method.

We experimentally evaluate the performance of a noncontact system that measures the heartbeat of a sleeping person. The proposed system comprises a pair of radar systems installed at two different positions. We use millimeter-wave ultra-wideband multiple-input multiple-output array radar systems and evaluate the performance attained in measuring the heart inter-beat interval and body movement. The importance of using two radar systems instead of one is demonstrated in this paper. We conduct three types of experiments; the first and second experiments are radar measurements of three participants lying on a bed with and without body movement, while the third experiment is the radar measurement of a participant actually sleeping overnight. The experiments demonstrate that the performance of the radar-based vital measurement strongly depends on the orientation of the person under test. They also show that the proposed system detects 70% of rolling-over movements made overnight.

An olfactory display is a device to present smells. Temporal characteristics of three types of olfactory displays such as one based upon high-speed switching of solenoid valves, desktop-type one based on SAW atomizer and wearable-type one based on SAW atomizer were evaluated using three odorants with different volatilities. The sensory test revealed that the olfactory displays based on SAW atomizer had the presentation speeds faster than that of solenoid valves switching. Especially, the wearable one had an excellent temporal characteristic. These results largely depend on the difference in the odor delivery method. The data obtained in this study provides basic knowledge when we make olfactory contents.

This paper proposes an optimization model under uncertain traffic demands to design the backup network to minimize the total capacity of a backup network to protect the primary network from multiple link failures, where the probability of link failure is specified. The hose uncertainty is adopted to express uncertain traffic demands. The probabilistic survivability guarantee is provided by determining both primary and backup network routing, simultaneously. Robust optimization is introduced to provide probabilistic survivability guarantees for different link capacities in the primary network model under the hose uncertainty. Robust optimization in the proposed model handles two uncertain items: uncertain failed primary link with different capacities and uncertain traffic demands. We formulate an optimization problem for the proposed model. Since it is difficult to directly solve it, we introduce a heuristic approach for the proposed model. By using the heuristic approach, we investigate how the probability of link failure affects both primary and backup network routing. Numerical results show that the proposed model yields a backup network with lower total capacity requirements than the conventional model for the link failure probabilities examined in this paper. The results indicate that the proposed model reduces the total capacity of the backup network compared to the conventional model under the hose uncertainty. The proposed model shares more effectively the backup resources to protect primary links by determining routing in both primary and backup networks.

This paper presents a method to optimize 2-D sparse array configurations along with a technique to interpolate holes to accurately estimate the direction of arrival (DOA). Conventional 2-D sparse arrays are often defined using a closed-form representation and have the property that they can create hole-free difference co-arrays that can estimate DOAs of incident signals that outnumber the physical elements. However, this property restricts the array configuration to a limited structure and results in a significant mutual coupling effect between consecutive sensors. In this paper, we introduce an optimization-based method for designing 2-D sparse arrays that enhances flexibility of array configuration as well as DOA estimation accuracy. We also propose a method to interpolate holes in 2-D co-arrays by nuclear norm minimization (NNM) that permits holes and to extend array aperture to further enhance DOA estimation accuracy. The performance of the proposed optimum arrays is evaluated through numerical examples.

In this paper, we propose a cross-correlation method applied to multistatic ground penetrating radar (GPR) data sets to detect road pavement damage. Pavement cracks and delamination cause variations in electromagnetic wave propagation. The proposed method can detect velocity change using cross-correlation of data traces at different times. An artificially damaged airport taxiway model was measured, and the method captures the positions of damaged parts.