We report the control of threshold voltage (Vth) for low voltage (5V) operation in OFET by using double gate dielectric layers composed of poly (vinyl cinnamate) and SiO2. We succeeded in realizing a driving voltage of -5V and Vth shift by c.a. 1.0V. And programmed Vth was almost unchanged for 104s, where the relative change of Vth remains more than 99%.

We have developed the flexible dual-gate OFET based pressure sensor using a thin polyethylene naphthalate (PEN, 25 µm) film as a substrate. The performance was equivalent to that fabricated on the glass substrate, and it could also be used on the curved surface. Drain current in the flexible pressure sensor was increased according to the pressure load without application of gate voltage. The magnitude of the change in drain current with respect to pressure application was about 2.5 times larger than that for the device on the glass substrate.

In this paper, a surveillance system by multiple agents, which is called a multi-agent surveillance system, is studied. A surveillance area is given by an undirected connected graph. Then, the optimal control problem for multi-agent surveillance systems (the optimal surveillance problem) is to find trajectories of multiple agents that travel each node as evenly as possible. In our previous work, this problem is reduced to a mixed integer linear programming problem. However, the computation time for solving it exponentially grows with the number of agents. To overcome this technical issue, a new model predictive control method for multi-agent surveillance systems is proposed. First, a procedure of individual optimization, which is a kind of approximate solution methods, is proposed. Next, a method to improve the control performance is proposed. In addition, an event-triggering condition is also proposed. The effectiveness of the proposed method is presented by a numerical example.

The Game of Life, a two-dimensional computationally universal cellular automaton, is known to exhibits 1/f noise in the evolutions starting from random configurations. In this paper we perform the spectral analysis on the computation process by a Turing machine constructed on the array of the Game of Life. As a result, the power spectrum averaged over the whole array has almost flat line at low frequencies and a lot of sharp peaks at high frequencies although some regions in which complicated behavior such as frequent memory rewriting occurs exhibit 1/f noise. This singular power spectrum is, however, easily turned into 1/f by slightly deforming the initial configuration of the Turing machine. These results emphasize the peculiarity of the computation process on the Game of Life that is never shared with the evolutions from random configurations. The Lyapunov exponents have positive values in three out of six trials and zero or negative values in other three trails. That means the computation process is essentially chaotic but it has capable of recovering a slight error in the configuration of the Turing machine.

Two kinds of composite right/left-handed coaxial lines (CRLH CLs) are designed for an antenna element. The dispersion relations of the infinite periodic CRLH CLs are designed to occur -1st resonance at around 700 MHz, respectively. The designed CRLH CLs comprise a monopole and a choke structure for antenna elements. To verify the resonant modes and frequencies, the monopole structure, the choke structure, and the antenna element which is combined the monopole and the choke structures are simulated by eigenmode analysis. The resonant frequencies correspond to the dispersion relations. The monopole and the choke structures are applied to the coaxially fed antenna. The proposed antenna matches at 710 MHz and radiates. At the resonant frequency, the total length of the proposed antenna which is the length of the monopole structure plus the choke structure is 0.12 wavelength. The characteristics of the proposed antenna has been compared with that of the conventional coaxially fed monopole antenna without the choke structure and the sleeve antenna with the quarter-wavelength choke structure. The radiation pattern of the proposed antenna is omnidirectional, the total antenna efficiency is 0.73 at resonant frequencies, and leakage current is suppressed lesser than -10 dB at resonant frequency. The propose antenna is fabricated and measured. The measured |S11| characteristics, radiation patterns, and the total antenna efficiency are in good agreement with the simulated results.

In this paper, we consider cloud-assisted Peer-to-Peer (P2P) video streaming systems, in which a given video stream is divided into several sub-streams called stripes and those stripes are delivered to all subscribers through different spanning trees of height two, with the aid of cloud upload capacity. We call such a low latency delivery of stripes a 2-hop delivery. This paper proves that if the average upload capacity of the peers equals to the bit rate of the video stream and the video stream is divided into a stripes, then 2-hop delivery of all stripes to n peers is possible if the upload capacity assisted by the cloud is 3n/a. If those peers have a uniform upload capacity, then the amount of cloud assistance necessary for the 2-hop delivery reduces to n/a.

With the rising importance of information security, the necessity of implementing better security measures in the physical layer as well as the upper layers is becoming increasing apparent. Given the development of more accurate and less expensive measurement devices, high-performance computers, and larger storage devices, the threat of advanced attacks at the physical level has expanded from the military and governmental spheres to commercial products. In this paper, we review the issue of information security degradation through electromagnetic (EM)-based compromising of security measures in the physical layer (i.e., EM information security). Owing to the invisibility of EM radiation, such attacks can be serious threats. We first introduce the mechanism of information leakage through EM radiation and interference and then present possible countermeasures. Finally, we explain the latest research and standardization trends related to EM information security.

ICT development progresses, and many cryptographic algorithms are used. The most of cryptographic algorithms require assumptions to guarantee their security, but it is sometimes not clearly written. This causes many problems. This paper shows previous cases, and suggests to concede cryptographers and system developer each other from an industrial cryptographers viewpoint.

MDC-4 is the enhanced version of MDC-2, which is a well-known hash mode of block ciphers. However, it does not guarantee sufficient securities required for a cryptographic hash function. In the ideal cipher model, the MDC-4 compression function has the collision security bound close to 25n/8 and the preimage security bound close to 25n/4, where the underlying block cipher has the block size of n bits. We have studied how to improve MDC-4 with simple modification to strengthen its security. It is meaningful work because users often want to improve their familiar systems with low cost. In this paper, we achieve it by proposing MDC-4+, which is a light variation of MDC-4. We prove that MDC-4+ is much more secure than MDC-4 by showing that it has the collision security bound close to optimal 2n and the preimage security bound close to 24n/3. We also discuss its efficiency by comparing existing hash modes.

Socially aware networking is an emerging research field that aims to improve the current networking technologies and realize novel network services by applying social network analysis (SNA) techniques. Conducting socially aware networking studies requires knowledge of both SNA and communication networking, but it is not easy for communication networking researchers who are unfamiliar with SNA to obtain comprehensive knowledge of SNA due to its interdisciplinary nature. This paper therefore aims to fill the knowledge gap for networking researchers who are interested in socially aware networking but are not familiar with SNA. This paper surveys three types of important SNA techniques for socially aware networking: identification of influential nodes, link prediction, and community detection. Then, this paper introduces how SNA techniques are used in socially aware networking and discusses research trends in socially aware networking.

In this paper, we propose a novel algorithm called multi-projection ensemble discriminant clustering (MPEDC) for JPEG steganalysis. The scheme makes use of the optimal projection of linear discriminant analysis (LDA) algorithm to get more projection vectors by using the micro-rotation method. These vectors are similar to the optimal vector. MPEDC combines unsupervised K-means algorithm to make a comprehensive decision classification adaptively. The power of the proposed method is demonstrated on three steganographic methods with three feature extraction methods. Experimental results show that the accuracy can be improved using iterative discriminant classification.

Fully integrated CMOS power amplifiers (PAs) with a two-winding and single-winding combined transformer (TS transformer) are presented. The general analysis of the TS transformer and other power-combining transformers, i.e., the series-combining transformer and parallel-combining transformer, is presented in terms of the transformer design parameters. Compared with other power-combining transformers, the proposed power-combining TS transformer offers high-efficiency with a compact form factor. In addition, a fully integrated CMOS PA using the TS transformer with multi-gated transistors (MGTRs) and adaptive bias circuit has been proposed to improve linearity. The proposed PAs are implemented using 65-nm CMOS technology. The implemented PA with the TS transformer achieves a saturated output power of 26.7 dBm with drain efficiency (DE) of 47.7%. The PA achieves 20.13-dBm output power with 21.4% DE while satisfying the -25-dB error vector magnitude (EVM) requirement when tested with the WLAN 802.11g signal. The implemented PA using the TS transformer with MGTRs and adaptive bias circuit achieves the -30-dB EVM requirement up to an output power of 17.13 dBm with 10.43% DE when tested using the WLAN 802.11ac signal.

Malware has become a growing threat as malware writers have learned that signature-based detectors can be easily evaded by packing the malware. Packing is a major challenge to malware analysis. The generic unpacking approach is the major solution to the threat of packed malware, and it is based on the intrinsic nature of the execution of packed executables. That is, the original code should be extracted in memory and get executed at run-time. The existing generic unpacking approaches need a simulated environment to monitor the executing of the packed executables. Unfortunately, the simulated environment is easily detected by the environment-sensitive packers. It makes the existing generic unpacking approaches easily evaded by the packer. In this paper, we propose a novel unpacking approach, BareUnpack, to monitor the execution of the packed executables on the bare-metal operating system, and then extracts the hidden code of the executable. BareUnpack does not need any simulated environment (debugger, emulator or VM), and it works on the bare-metal operating system directly. Our experimental results show that BareUnpack can resist the environment-sensitive packers, and improve the unpacking effectiveness, which outperforms other existing unpacking approaches.

The response times of solid state drives (SSDs) have decreased dramatically due to the growing use of non-volatile memory express (NVMe) devices. Such devices have response times of less than 100 micro seconds on average. The response times of all-flash-array systems have also decreased dramatically through the use of NVMe SSDs. However, there are applications, particularly virtual desktop infrastructure and in-memory database systems, that require storage systems with even shorter response times. Their workloads tend to contain many input-output (IO) concentrations, which are aggregations of IO accesses. They target narrow regions of the storage volume and can continue for up to an hour. These narrow regions occupy a few percent of the logical unit number capacity, are the target of most IO accesses, and appear at unpredictable logical block addresses. To drastically reduce the response times for such workloads, we developed an automated tiered storage system called “automated tiered storage with fast memory and slow flash storage” (ATSMF) in which the data in targeted regions are migrated between storage devices depending on the predicted remaining duration of the concentration. The assumed environment is a server with non-volatile memory and directly attached SSDs, with the user applications executed on the server as this reduces the average response time. Our system predicts the effect of migration by using the previously monitored values of the increase in response time during migration and the change in response time after migration. These values are consistent for each type of workload if the system is built using both non-volatile memory and SSDs. In particular, the system predicts the remaining duration of an IO concentration, calculates the expected response-time increase during migration and the expected response-time decrease after migration, and migrates the data in the targeted regions if the sum of response-time decrease after migration exceeds the sum of response-time increase during migration. Experimental results indicate that ATSMF is at least 20% faster than flash storage only and that its memory access ratio is more than 50%.

Recent studies utilize multiple kernel learning to deal with incomplete-data problem. In this study, we introduce new methods that do not only complete multiple incomplete kernel matrices simultaneously, but also allow control of the flexibility of the model by parameterizing the model matrix. By imposing restrictions on the model covariance, overfitting of the data is avoided. A limitation of kernel matrix estimations done via optimization of an objective function is that the positive definiteness of the result is not guaranteed. In view of this limitation, our proposed methods employ the LogDet divergence, which ensures the positive definiteness of the resulting inferred kernel matrix. We empirically show that our proposed restricted covariance models, employed with LogDet divergence, yield significant improvements in the generalization performance of previous completion methods.

Defects in spacecraft software may result in loss of life and serious economic damage. To avoid such consequences, the software development process incorporates code review activity. A code review conducted by a third-party organization independently of a software development team can effectively identify defects in software. However, such review activity is difficult for third-party reviewers, because they need to understand the entire structure of the code within a limited time and without prior knowledge. In this study, we propose a tool to visualize inter-module dataflow for source code of spacecraft software systems. To evaluate the method, an autonomous rover control program was reviewed using this visualization. While the tool does not decreases the time required for a code review, the reviewers considered the visualization to be effective for reviewing code.

In terms of spatial online aggregation, traditional stand-alone serial methods gradually become limited. Although parallel computing is widely studied nowadays, there scarcely has research conducted on the index-based parallel online aggregation methods, specifically for spatial data. In this letter, a parallel multilevel indexing method is proposed to accelerate spatial online aggregation analyses, which contains two steps. In the first step, a parallel aR tree index is built to accelerate aggregate query locally. In the second step, a multilevel sampling data pyramid structure is built based on the parallel aR tree index, which contribute to the concurrent returned query results with certain confidence degree. Experimental and analytical results verify that the methods are capable of handling billion-scale data.

The number of infected hosts on enterprise networks has been increased by drive-by download attacks. In these attacks, users of compromised popular websites are redirected toward websites that exploit vulnerabilities of a browser and its plugins. To prevent damage, detection of infected hosts on the basis of proxy logs rather than blacklist-based filtering has started to be researched. This is because blacklists have become difficult to create due to the short lifetime of malicious domains and concealment of exploit code. To detect accesses to malicious websites from proxy logs, we propose a system for detecting malicious URL sequences on the basis of three key ideas: focusing on sequences of URLs that include artifacts of malicious redirections, designing new features related to software other than browsers, and generating new training data with data augmentation. To find an effective approach for classifying URL sequences, we compared three approaches: an individual-based approach, a convolutional neural network (CNN), and our new event de-noising CNN (EDCNN). Our EDCNN reduces the negative effects of benign URLs redirected from compromised websites included in malicious URL sequences. Evaluation results show that only our EDCNN with proposed features and data augmentation achieved a practical classification performance: a true positive rate of 99.1%, and a false positive rate of 3.4%.

Two kinds of problems - multiterminal hypothesis testing and one-to-many lossy source coding - are investigated in a unified way. It is demonstrated that a simple key idea, which is developed by Iriyama for one-to-one source coding systems, can be applied to multiterminal source coding systems. In particular, general bounds on the error exponents for multiterminal hypothesis testing and one-to-many lossy source coding are given.

As semiconductor device manufacturing technology evolves toward higher integration and reduced feature size, the gap between the defect level estimated at the design stage and that reported for fabricated devices has become wider, making it more difficult to control total manufacturing cost including test cost and cost for field failure. To estimate fault coverage more precisely considering occurrence probabilities of faults, we have proposed weighted fault coverage estimation based on critical area corresponding to each fault. Previously different fault models were handled separately; thus, pattern compression efficiency and runtime were not optimized. In this study, we propose a fast test pattern generation scheme that considers weighted bridge and open fault coverage in an integrated manner. The proposed scheme applies two-step test pattern generation, wherein test patterns generated at second step that target only bridge faults are reordered with a search window of fixed size, achieving O(n) computational complexity. Experimental results indicate that with 10% of the initial target fault size and a fixed, small window size, the proposed scheme achieves approximately 100 times runtime reduction when compared to simple greedy-based reordering, in exchange for about 5% pattern count increment.