On surfaces of tris-(8-hydroxyquinolate) aluminum (Alq) and tris(7-propyl-8-hydroxyquinolinato) aluminum (Al7p) thin-films, positive and negative polarization charges appear, respectively, owing to spontaneous orientation of these polar molecules. Alq is a typical electron transport material where electrons are injected from cathode. Because the polarization charge exists at the Alq/cathode interface, it is likely that it affects the electron injection process because of Coulomb interaction. In order to evaluate an impact of polarization charge on electron injection from cathode, electron only devices (EODs) composed of Alq or Al7p were prepared and evaluated by displacement current measurement. We found that Alq-EOD has lower resistance than Al7p-EOD, indicating that the positive polarization charge at Alq/cathode interface enhances the electron injection due to Coulomb attraction, while the electron injection is suppressed by the negative polarization charge at the Al7p/Al interface. These results clearly suggest that it is necessary to design organic semiconductor devices by taking polarization charge into account.

Brain-computer interfaces (BCIs) have been used by users to convey their intentions directly with brain signals. For example, a spelling system that uses EEGs allows letters on a display to be selected. In comparison, previous studies have investigated decoding speech information such as syllables, words from single-trial brain signals during speech comprehension, or articulatory imagination. Such decoding realizes speech recognition with a relatively short time-lag and without relying on a display. Previous magnetoencephalogram (MEG) research showed that a template matching method could be used to classify three English sentences by using phase patterns in theta oscillations. This method is based on the synchronization between speech rhythms and neural oscillations during speech processing, that is, theta oscillations synchronized with syllabic rhythms and low-gamma oscillations with phonemic rhythms. The present study aimed to approximate this classification method to a BCI application. To this end, (1) we investigated the performance of the EEG-based classification of three Japanese sentences and (2) evaluated the generalizability of our models to other different users. For the purpose of improving accuracy, (3) we investigated the performances of four classifiers: template matching (baseline), logistic regression, support vector machine, and random forest. In addition, (4) we propose using novel features including phase patterns in a higher frequency range. Our proposed features were constructed in order to capture synchronization in a low-gamma band, that is, (i) phases in EEG oscillations in the range of 2-50 Hz from all electrodes used for measuring EEG data (all) and (ii) phases selected on the basis of feature importance (selected). The classification results showed that, except for random forest, most classifiers perform similarly. Our proposed features improved the classification accuracy with statistical significance compared with a baseline feature, which is a phase pattern in neural oscillations in the range of 4-8 Hz from the right hemisphere. The best mean accuracy across folds was 55.9% using template matching trained by all features. We concluded that the use of phase information in a higher frequency band improves the performance of EEG-based sentence classification and that this model is applicable to other different users.

This paper gives an overview on the design process of modulated metasurface (MTS) antennas and focus on their performance in terms of efficiency and bandwidth. The basic concept behind MTS antennas is that the MTS imposes the impedance boundary conditions (IBCs) seen by a surface wave (SW) propagating on it. The MTS having a spatially modulated equivalent impedance transforms the SW into a leaky wave with controlled amplitude, phase and polarization. MTS antennas are hence highly customizable in terms of performances by simply changing the IBCs imposed by the MTS, without affecting the overall structure. The MTS can be configured for high gain (high aperture efficiency) with moderate bandwidth, for wide bandwidth with moderate aperture efficiency, or for a trade-off performance for bandwidth and aperture efficiency. The design process herein described relies on a generalized form of the Floquet wave theorem adiabatically applied to curvilinear locally periodic IBCs. Several technological solutions can be adopted to implement the IBCs defined by the synthesis process, from sub-wavelength patches printed on a grounded slab at microwave frequencies, to a bed of nails structure for millimeter waves: in any case, the resulting device has light weight and a low profile.

Recent carrier-grade networks use many network elements (switches, routers) and servers for various network-based services (e.g., video on demand, online gaming) that demand higher quality and better reliability. Network log data generated from these elements, such as router syslogs, are rich sources for quickly detecting the signs of critical failures to maintain service quality. However, log data contain a large number of text messages written in an unstructured format and contain various types of network events (e.g., operator's login, link down); thus, genuinely important log messages for network operation are difficult to find automatically. We propose a proactive failure-detection system for large-scale networks. It automatically finds abnormal patterns of log messages from a massive amount of data without requiring previous knowledge of data formats used and can detect critical failures before they occur. To handle unstructured log messages, the system has an online log-template-extraction part for automatically extracting the format of a log message. After template extraction, the system associates critical failures with the log data that appeared before them on the basis of supervised machine learning. By associating each log message with a log template, we can characterize the generation patterns of log messages, such as burstiness, not just the keywords in log messages (e.g. ERROR, FAIL). We used real log data collected from a large production network to validate our system and evaluated the system in detecting signs of actual failures of network equipment through a case study.

Semitransparent organic solar cells were fabricated using lamination process. The devices were realized by using two independent substrates with transparent indium-tin-oxide electrode. One substrate was coated with poly(ethylenedioxy-thiophene)/poly(styrenesulfonate) layer and active layer of poly(3-hexylthiophene-2,5-diyl) (P3HT) and (6,6)-phenyl-C61 butyric acid methyl ester mixture. Another substrate was coated with ultra-thin polyethylenimine ethoxylated. The two substrates were laminated using hot press system. The device exhibited semitransparency and showed typical photovoltaic characteristics with open voltage of 0.59 V and short circuit current of 2.9 mA/cm2.

Photophysical properties of water-soluble porphyrin were studied in aqueous solutions with/without DNA and in DNA solid films. Ultrathin films were prepared from aqueous DNA solutions by a spin-coating method on glass or on gold nanoparticles (AuNPs). Remarkable enhancement of phosphorescence was observed for porphyrin immobilized in DNA films spin-coated on AuNPs, which was attributed to the electric field enhancement and the increased radiative rate by localized surface plasmon resonance of AuNPs.

In this work, we report the in situ growth of gold nanoparticles (AuNPs) for the improvement of a transmission surface plasmon resonance (T-SPR) sensor to detect human immunoglobulin G (IgG). Human IgG was immobilized on an activated self-assembled monolayer of 11-mercaptoundecanoic on a gold-coated grating substrate. The T-SPR system was also used to monitor the construction of sensor chips as well as the binding of IgG and anti-IgG conjugated with AuNPs. After specific adsorption with IgG, the T-SPR signal was further enhanced by the in situ growth of AuNPs bound with anti-IgG. Using AuNP conjugation and in situ growth of bound AuNPs, the sensitivity of the IgG immunosensor was improved by two orders of magnitude compared with that without conjugated AuNPs.

Copper (Cu) electroless plating was conducted on planar and microstructured polydimethylsiloxane (PDMS) substrates. In this study, organic thin films terminated with nitrogen (N)-containing groups, e.g. poly (dimethylaminoethyl methacrylate) brush (PDMAEMA), aminopropyl trimethoxysilane monolayer (APTES), and polydopamine (PDA) were used to anchor palladium (Pd) catalyst. While electroless plating was successfully promoted on all sample surfaces, PDMAEMA was found to achieve the best adhesion strength to the PDMS surfaces, compared to APTES- and PDA-covered PDMS substrates, due to covalent bonding, anchoring effects of polymer chains as well as high affinity of N atoms to Pd species. Our process was also successfully applied to the electroless plating of microstructured PDMS substrates.

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.

In 2017, Shirase proposed a variant of Elliptic Curve Method combined with Complex Multiplication method for generating certain special kinds of elliptic curves. His algorithm can efficiently factorize a given composite integer when it has a prime factor p of the form 4p=1+Dv2 for some integer v, where -D is an auxiliary input integer called a discriminant. However, there is a disadvantage that the previous method works only for restricted cases where the class polynomial associated to -D has degree at most two. In this paper, we propose a generalization of the previous algorithm to the cases of class polynomials having arbitrary degrees, which enlarges the class of composite integers factorizable by our algorithm. We also extend the algorithm to more various cases where we have 4p=t2+Dv2 and p+1-t is a smooth integer.

Pose estimation is a basic requirement for the autonomous behavior of robots. In this article we present a robust and fast visual odometry method to obtain camera poses by using RGB-D images. We first propose a motion estimation method based on sparse geometric constraint and derive the analytic Jacobian of the geometric cost function to improve the convergence performance, then we use our motion estimation method to replace the tracking thread in ORB-SLAM for improving its runtime performance. Experimental results show that our method is twice faster than ORB-SLAM while keeping the similar accuracy.

Fail-Stop Signature (FSS) scheme is a signature scheme which satisfies unforgeability even against a forger with super-polynomial computational power (i.e. even against a forger who can compute acceptable signatures) and non-repudiability against a malicious signer with probabilistic polynomial time computational power (i.e. a PPT malicious signer). In this paper, under some settings, the equivalence relation has been derived between a set of security properties when single FSS scheme is used singly and a security property called Universally Composable (UC) security when plural FSS schemes are concurrently used. Here, UC security is a security property guaranteeing that even when plural schemes are concurrently used, security properties of each scheme (for single scheme usage) are preserved. The above main settings are as follows. Firstly, H-EUC (Externalized UC) security is introduced instead of “conventional” UC security, where a new helper functionality H is constructed appropriately. It is because that we can derive “conventional” UC security cannot hold for FSS schemes when malicious parties (e.g. a forger and a malicious signer) have super-polynomial computational power. In the environment where the above helper functionality H is used, all parties are PPT, but only a forger may compute acceptable signatures by obtaining some additional information from H. Secondly, the definition of unforgeability (in a set of security properties for single FSS scheme usage) is revised to match the above environment. The above equivalence relation derived under the above settings guarantees that even when plural FSS schemes are concurrently used, those security properties for single scheme usage are preserved, provided that some conditions hold. In particular, the equivalence relation in this paper has originality in terms of guaranteeing that unforgeability is preserved even against a forger who is PPT but may compute acceptable signatures. Furthermore, it has been firstly proved in this paper that H-EUC security holds for an existing instantiation of an FSS scheme by Mashatan et al. From this, it can be said that the equivalence relation shown in this paper is practical.

Traffic matrix (TM) estimation has been extensively studied for decades. Although conventional estimation techniques assume that traffic volumes are unchanged between origins and destinations, packets are often lost on a path due to traffic burstiness, silent failures, etc. Counting every path at every link, we could easily get the traffic volumes with their change, but this approach significantly increases the measurement cost since counters are usually implemented using expensive memory structures like a SRAM. This paper proposes a mathematical model to estimate TMs including volume changes. The method is established on a Boolean fault localization technique; the technique requires fewer counters as it simply determines whether each link is lossy. This paper extends the Boolean technique so as to deal with traffic volumes with error bounds that requires only a few counters. In our method, the estimation errors can be controlled through parameter settings, while the minimum-cost counter placement is determined with submodular optimization. Numerical experiments are conducted with real network datasets to evaluate our method.

Data replication in cloud storage systems brings a lot of benefits, such as fault tolerance, data availability, data locality and load balancing both from reliability and performance perspectives. However, each time a datanode fails, data blocks stored on the failed datanode must be restored to maintain replication level. This may be a large burden for the system in which resources are highly utilized with users' application workloads. Although there have been many proposals for replication, the approach of re-replication has not been properly addressed yet. In this paper, we present a deferred re-replication algorithm to dynamically shift the re-replication workload based on current resource utilization status of the system. As workload pattern varies depending on the time of the day, simulation results from synthetic workload demonstrate a large opportunity for minimizing impacts on users' application workloads with the simple algorithm that adjusts re-replication based on current resource utilization. Our approach can reduce performance impacts on users' application workloads while ensuring the same reliability level as default HDFS can provide.

As an optimal combinatorial object, cyclic perfect Mendelsohn difference family (CPMDF) was introduced by Fuji-Hara and Miao to construct optimal optical orthogonal codes. In this paper, we propose a direct construction of disjoint CPMDFs from the Zeng-Cai-Tang-Yang cyclotomy. Compared with a recent work of Fan, Cai, and Tang, our construction doesn't need to depend on a cyclic difference matrix. Furthermore, strictly optimal frequency-hopping sequences (FHSs) are a kind of optimal FHSs which has optimal Hamming auto-correlation for any correlation window. As an application of our disjoint CPMDFs, we present more flexible combinatorial constructions of strictly optimal FHSs, which interpret the previous construction proposed by Cai, Zhou, Yang, and Tang.

Surface light field advances conventional light field rendering techniques by utilizing geometry information. Using surface light field, real-world objects with complex appearance could be faithfully represented. This capability could play an important role in many VR/AR applications. However, an accurate geometric model is needed for surface light field sampling and processing, which limits its wide usage since many objects of interests are difficult to reconstruct with their usually very complex appearances. We propose a novel two-step optimization framework to reduce the dependency of accurate geometry. The key insight is to treat surface light field sampling as a multi-view multi-texture optimization problem. Our approach can deal with both model inaccuracy and image to model misalignment, making it possible to create high-fidelity surface light field models without using high-precision special hardware.

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.

As energy efficiency has become a major design constraint or objective, heterogeneous manycore architectures have emerged as mainstream target platforms not only in server systems but also in embedded systems. Manycore accelerators such as GPUs are getting also popular in embedded domains, as well as the heterogeneous CPU cores. However, as the number of cores in an embedded GPU is far less than that of a server GPU, it is important to utilize both heterogeneous multi-core CPUs and GPUs to achieve the desired throughput with the minimal energy consumption. In this paper, we present a case study of mapping LBP-based face detection onto a recent CPU-GPU heterogeneous embedded platform, which exploits both task parallelism and data parallelism to achieve maximal energy efficiency with a real-time constraint. We first present the parallelization technique of each task for the GPU execution, then we propose performance and energy models for both task-parallel and data-parallel executions on heterogeneous processors, which are used in design space exploration for the optimal mapping. The design space is huge since not only processor heterogeneity such as CPU-GPU and big.LITTLE, but also various data partitioning ratios for the data-parallel execution on these heterogeneous processors are considered. In our case study of LBP face detection on Exynos 5422, the estimation error of the proposed performance and energy models were on average -2.19% and -3.67% respectively. By systematically finding the optimal mappings with the proposed models, we could achieve 28.6% less energy consumption compared to the manual mapping, while still meeting the real-time constraint.

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.

F.P. Preparata et al. have proposed a fault diagnosis model to find all faulty units in the multicomputer system by using outcomes which each unit tests some other units. In this paper, for probabilistic diagnosis models, we show an efficient diagnosis algorithm to obtain a posteriori probability that each of units is faulty given the test outcomes. Furthermore, we propose a method to analyze the diagnostic error probability of this algorithm.