We report a real time method to monitor the chemical reaction in microdroplets, which contain an organic dye, 5(6)-carboxynaphthofluorescein and a CdSe/ZnS quantum dot using fluorescence spectra. Especially, the relationship between the droplet size and the reaction rate of the two reagents was investigated by changing an injection speed.

In this study, flexible organic solar cells (OSCs) employing a solution-processed hole-transporting layer (HTL) and low temperature annealing active layer have been fabricated. Vanadium oxide (V$_{2}$O$_{5})$, poly(3,4-ethylene dioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), V$_{2}$O$_{5}$/PEDOT:PSS or PEDOT:PSS/V$_{2}$O$_{5}$ is used as the HTL. Poly(3-hexythiophene) (P3HT):[6,6]-phenyl C61-butyric acid methyl ester (PCBM) is used as the active layer. HTL and active layer are all formed by a spin coating method on polyethylene terephthalate (PET) substrates. The OSC configuration has been optimized in the study to be PET/ITO/V$_{2}$O$_{5}$/PEDOT:PSS/P3HT:PCBM/LiF/Al. Based on a low annealing temperature of 90$^{circ}$C for P3HT:PCBM and parameters optimization of solution-processed V$_{2}$O$_{5}$/PEDOT:PSS, the OSC demonstrates a current density (JSC) and power conversion efficiency (PCE) of 6.08, mA/cm$^{2}$ and 1.57%, while an OSC without the HTL has PCE around 0.06%. The V$_{2}$O$_{5}$/PEDOT:PSS stacked HTL provides not only a stepwise hole-transporting energy diagram configuration but a smooth film surface for coating P3HT:PCBM active layer, which subsequently increases charge carrier transporting capability and extracts holes from the active layer to the anode.

We show that, in practice, a network adversary can achieve decidedly non-negligible advantage in attacking provable key-protection properties; e.g., the “existential key recovery” security and “multi-key hiding” property of typical nonce-based symmetric encryption schemes whenever these schemes are implemented with standard block ciphers. We also show that if a probabilistic encryption scheme uses certain standard block ciphers (e.g., two-key 3DES), then enforcing the security bounds necessary to protect against network adversary attacks will render the scheme impractical for network applications that share group keys amongst many peers. The attacks presented here have three noteworthy implications. First, they help identify key-protection properties that separate the notion of indistinguishability from random bits (IND$) from the strictly weaker notion of indistinguishability of ciphertexts (IND); also, they help establish new relationships among these properties. Second, they show that nonce-based symmetric encryption schemes are typically weaker than probabilistic ones. Third, they illustrate the need to account for the Internet-level growth of adversary capabilities when establishing the useful lifetime of standard block-cipher parameters.

Most existing deterministic multithreading systems are costly on pipeline parallel programs due to load imbalance. In this letter, we propose a Load-Balanced Deterministic Runtime (LBDR) for pipeline parallelism. LBDR deterministically takes some tokens from non-synchronization-intensive threads to synchronization-intensive threads. Experimental results show that LBDR outperforms the state-of-the-art design by an average of 22.5%.

Since it is difficult to understand or predict research trends, we proposed methodologies for understanding and predicting research trends in the sciences, focusing on the structures of grants in the Japan Society for the Promotion of Science (JSPS), a Japanese funding agency. Grant applications are suitable for predicting research trends because these are research plans for the future, different from papers, which report research outcomes in the past. We investigated research trends in science focusing on research histories identified in grant application data of JSPS. Then we proposed a model for predicting research trends, assuming that breakthrough research encourages researchers to change from their current research field to an entirely new research field. Using breakthrough research, we aim to obtain higher precision in the prediction results. In our experimental results, we found that research fields in Informatics correlate well with actual scientific research trends. We also demonstrated that our prediction models are effective in actively interacting research areas, which include Informatics and Social Sciences.

This paper proposes a novel image classification scheme for cloth pattern recognition. The rotation and scale invariant delta-HOG (DHOG)-based descriptor and the entire recognition process using random ferns with this descriptor are proposed independent from pose and scale changes. These methods consider maximun orientation and various radii of a circular patch window for fast and efficient classification even when cloth patches are rotated and the scale is changed. It exhibits good performance in cloth pattern recognition experiments. It found a greater number of similar cloth patches than dense-SIFT in 20 tests out of a total of 36 query tests. In addition, the proposed method is much faster than dense-SIFT in both training and testing; its time consumption is decreased by 57.7% in training and 41.4% in testing. The proposed method, therefore, is expected to contribute to real-time cloth searching service applications that update vast numbers of cloth images posted on the Internet.

A cloud system is defined as a large scale computer system that contains running high performance computers and responds to a large number of incoming tasks over the Internet. In this paper, we consider the problem to schedule computational jobs efficiently regarding system resource constraint and introduce a cuckoo search (CS) algorithm. Experimental results show that CS outperforms the genetic algorithm in terms of fitness value.

Coarse-grained Reconfigurable Architecture (CGRA) is a promising mobile computing platform that provides both high performance and high energy efficiency. In an application, loop nests are usually mapped onto CGRA for further acceleration, so optimizing the mapping is an important goal for design of CGRAs. Moreover, obviously almost all of mobile devices are powered by batteries, how to reduce energy consumption also becomes one of primary concerns in using CGRAs. This paper makes three contributions: a) Proposing an energy consumption model for CGRA; b) Formulating loop nests mapping problem to minimize the battery charge loss; c) Extract an efficient heuristic algorithm called BPMap. Experiment results on most kernels of the benchmarks and real-life applications show that our methods can improve the performance of the kernels and lower the energy consumption.

In this paper, we present a new method for diagnosis of stochastic discrete event system. The method is based on anomaly detection for sequences. We call the method sequence profiling (SP). SP does not require any system models and any system-specific knowledge. The only information necessary for SP is event logs from the target system. Using event logs from the system in the normal situation, N-gram models are learned, where the N-gram model is used as approximation of the system behavior. Based on the N-gram model, the diagnoser estimates what kind of faults has occurred in the system, or may conclude that no faults occurs. Effectiveness of the proposed method is demonstrated by application to diagnosis of a multi-processor system.

In recent 3GPP (3rd Generation Partnership Project) standardization meetings, D2D (Device-to-Device) discovery has been a major issue to support commercial/social services and public safety in disaster environment, and TDM (Time Division Multiplexing) based discovery channel structure is mainly considered to prevent mutual interference between D2D and cellular traffic. In this structure, D2D discovery among the same cell UEs (User Equipment) has no problem because they have the same timing source. However, LTE (Long Term Evolution) assumes an asynchronous network where two adjacent eNBs (evolved Node B) have a symbol-level timing offset. For that reason, asynchronous interference among discovery signals can appear in inter-cell D2D discovery. Therefore, channel re-use scheduling was studied previously in which neighboring cells do not use the same portion of the extended discovery channel and other non-neighboring cells re-use it. However, it still shows interference problems in small cell networks which cause substantial cellular traffic loss. Therefore, in this paper, we propose a novel discovery channel scheduling in which eNBs time-align their discovery channels from each other by sample-level. In the proposed scheme, serving eNB requests cell edge UEs to estimate NTD (Network Time Difference) between serving eNB and neighboring eNB. Then, considering multiple NTDs, eNB adjusts the sample position of its discovery channel based on a novel decision rule. We verify that the proposed scheme can match the discovery performance of a synchronous network with less cellular uplink loss.

In this paper, we consider a decentralized failure diagnosis problem for discrete event systems. For a conjunctively codiagnosable system, there exists a conjunctive decentralized diagnoser that can detect the occurrence of any failure within a uniformly bounded number of steps. We present a method for synthesizing such a conjunctive decentralized diagnoser as an online diagnoser.

Co-channel interference (CCI) is becoming a challenging factor that causes performance degradation in modern communication systems. The receiver equipped with multiple antennas can suppress such interference by exploiting spatial correlation. However, it is difficult to estimate the spatial covariance matrix (SCM) of CCI accurately with limited number of known symbols. To address this problem, this paper first proposes an improved SCM estimation method by shrinking the variance of eigenvalues. In addition, based on breadth-first tree search schemes and improved channel updating, a low complexity iterative detector is presented with channel preprocessing, which not only considers the existence of CCI but also reduces the computational complexity in terms of visited nodes in a search tree. Furthermore, by scaling the extrinsic soft information which is fed back to the input of detector, the detection performance loss due to max-log approximation is compensated. Simulation results show that the proposed iterative receiver provides improved signal to interference ratio (SIR) gain with low complexity, which demonstrate the proposed scheme is attractive in practical implementation.

In a multi-cell MIMO system, the rate of edge users is limited by the inter-cell co-channel interference. The CoMP scheme which includes Joint Process (JP) and Coordinated Scheduling/Beamforming (CS/CB) was developed to reduce the inter-cell interference and enhance the edge rate. Because CS/CB can alleviate the overhead of network, it gains attention recently. In this paper, a modified zero forcing beamforming (ZFBF) is applied to downlink transmission in a two-cell MIMO system. In order to enhance system sum rate, a novel coordinated user scheduling algorithm is proposed. Firstly, we select users with high correlation among cross-channels as candidates, and then group users from candidates with high orthogonality among direct-channels, and match user groups in different cells as the final scheduling group pair. Simulations show that the proposed algorithm can achieve a higher system sum rate with low complexity than traditional scheduling algorithms.

We consider user selection schemes for multi-user MIMO systems with linear precoding. In this work, we apply two user selection schemes based on the orthogonality between the propagation channel of MSs. Indoor transmission experiments are carried out under several scenarios and the performances of user selection schemes are evaluated. It is shown that the transmission performance is improved and the user selection schemes are remarkably affected by the path loss between MSs.

Video Up-scaling is a hotspot in TV display area; as an important brunch of Video Up-scaling, Texture-Based Video Up-scaling (TBVU) method shows great potential of hardware implementation. Coarse-grained Reconfigurable Architecture (CGRA) is a very promising processor; it is a parallel computing platform which provides high performance of hardware, high flexibility of software, and dynamical reconfiguration ability. In this paper we propose an implementation of TBVU on CGRA. We fully exploit the characters of TBVU and utilize several techniques to reduce memory I/O operation and total execution time. Experimental results show that our work can greatly reduce the I/O operation and the execution time compared with the non-optimized ones. We also compare our work with other platforms and find great advantage in execution time and resource utilization rate.

A processing system with multiple field programmable gate array (FPGA) cards is described. Each FPGA card can interconnect using six I/O (up, down, left, right, front, and back) terminals. The communication network among FPGAs is scalable according to user design. When the system operates multi-dimensional applications, transmission efficiency among FPGA improved through user-adjusted dimensionality and network topologies for different applications. We provide a fast and flexible circuit configuration method for FPGAs of a multi-dimensional FPGA array. To demonstrate the effectiveness of the proposed method, we assess performance and power consumption of a circuit that calculated 3D Poisson equations using the finite difference method.

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.

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.

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.

Speeded up robust features (SURF) can detect/describe scale- and rotation-invariant features at high speed by relying on integral images for image convolutions. However, the time taken for matching SURF descriptors is still long, and this has been an obstacle for use in real-time applications. In addition, the matching time further increases in proportion to the number of features and the dimensionality of the descriptor. Therefore, we propose a fast matching method that rearranges the elements of SURF descriptors based on their entropies, divides SURF descriptors into sub-descriptors, and sequentially and analytically matches them to each other. Our results show that the matching time could be reduced by about 75% at the expense of a small drop in accuracy.