This paper describes diffusion of electric vehicles and novel social infrastructure from the viewpoint of systems innovation theory considering both human society aspects and elemental technological aspects. Firstly, fundamentals of the systems innovation theory and the platform theory are mentioned. Secondly, discussion on mobility from the viewpoint of the human-society layer and discussion of electrical vehicles from the viewpoint of the elemental techniques are carried out. Thirdly, based on those, R & D, measures are argued such as establishment of the ubiquitous noncontact feeding and authentication payment system is important. Finally, it is also insisted that after the establishment of this system the super smart grid with temporal and spatial control including demand itself with the low social cost will be expected.

In this letter, we propose an improved anchor shot detection (ASD) method in order to effectively retrieve anchor shots from news video. The face location and dissimilarity of icon region are used to reduce false alarms in the proposed method. According to the results of the experiment on several types of news video, the proposed method obtained high anchor detection results compared with previous methods.

Wireless mesh networks have been extensively studied as expandable, flexible, and inexpensive access networks to the Internet. This paper focuses on one composed of multiple access points (APs) connected through multihop wireless communications mainly by the wireless distribution system (WDS). For scalability, the proper partition of APs into multiple WDS clusters is essential, because the number of APs in one cluster is limited due to the increasing radio interference and control packets. In this paper, we formulate this WDS clustering problem and prove the NP-completeness of its decision version through reduction from a known NP-complete problem. Then, we propose its heuristic algorithm, using a greedy method and a variable depth search method, to satisfy the complex constraints while optimizing the cost function. We verify the effectiveness of our algorithm through extensive simulations, where the results confirm its superiority to the existing algorithm in terms of throughput.

This paper proposes a technique for detecting the occurrences of refactoring from source code revisions. In a real software development process, a refactoring operation may sometimes be performed together with other modifications at the same revision. This means that detecting refactorings from the differences between two versions stored in a software version archive is not usually an easy process. In order to detect these impure refactorings, we model the detection within a graph search. Our technique considers a version of a program as a state and a refactoring as a transition between two states. It then searches for the path that approaches from the initial to the final state. To improve the efficiency of the search, we use the source code differences between the current and the final state for choosing the candidates of refactoring to be applied next and estimating the heuristic distance to the final state. Through case studies, we show that our approach is feasible to detect combinations of refactorings.

Topological structure of peer-to-peer (P2P) networks affects their operating performance. Thus, various models have been proposed to construct an efficient topology for the P2P networks. However, due to the simultaneous failures of peers and other disastrous events, it is difficult to maintain the originally designed topological structure that provides the network with some performance benefits. For this reason, in this paper we propose a simple local rewiring method that changes the network topology to have small diameter as well as highly clustered structure. Moreover, the presented evaluation study shows how these topological properties are involved with the performance of P2P networks.

Due to the distributed nature, mobile ad-hoc networks (MANETs) are vulnerable to various attacks, resulting in distrusted communications. To achieve trusted communications, it is important to build trusted routes in routing algorithms in a self-organizing and decentralized fashion. This paper proposes a trusted routing to locate and to preserve trusted routes in MANETs. Instead of using a hard security mechanism, we employ a new dynamic trust mechanism based on multiple constraints and collaborative filtering. The dynamic trust mechanism can effectively evaluate the trust and obtain the precise trust value among nodes, and can also be integrated into existing routing protocols for MANETs, such as ad hoc on-demand distance vector routing (AODV) and dynamic source routing (DSR). As an example, we present a trusted routing protocol, based on dynamic trust mechanism, by extending DSR, in which a node makes a routing decision based on the trust values on its neighboring nodes, and finally, establish a trusted route through the trust values of the nodes along the route in MANETs. The effectiveness of our approach is validated through extensive simulations.

This paper proposes a sensing system for a behavior detection system using an ultrasonic oscillosensor and an air pressure sensor. The ultrasonic oscillosensor sensor has a cylindrical tank filled with water. It detects the vibration of the target object from the signal reflected from the water surface. This sensor can detect a biological vibration by setting to the bottom bed frame. The air pressure sensor consists of a polypropylene sheet and an air pressure sensor, and detects the pressure information by setting under the bed's mattress. An increase (decrease) in the load placed on the bed is detected by the increase (decrease) in the pressure of the air held in the tube attached to the sheet. We propose a behavior detection system using both sensors, complementally. The system recognizes three states (nobody in bed, keeping quiet in bed, moving in bed) using both sensors, and we detect the behavior before getting out of bed by recognized these states. Fuzzy logic plays a primary role in the system. As the fundamental experiment, we applied the system to five healthy volunteers, the system successfully recognized three states, and detected the behavior before getting out of bed. As the clinical experiment, we applied the system to four elderly patients with dementia, the system exactly detected the behavior before getting out of the bed with enough time for medical care support.

The security of P2P networks depends on building trust management among peers. However, current trust management models focus on preventing untrustworthy resources from spreading by malicious providers, but have few effects on reducing denial-of-service attacks of malicious consumers and free riding of selfish peers. Pointing to these problems, a bi-evaluation trust management model, called BiTrust, is proposed. In this model, the trustworthiness of a peer is divided into service and request trustworthiness. Service trustworthiness shows the resources reliability of providers, and request trustworthiness is used to deal with requests from consumers, which can keep away malicious consumers and encourage selfish peers to share resources. A generic method for evaluating service and request trustworthiness is described. Furthermore, the implementation strategies of the model are also depicted in this paper. The following analysis and simulation show that BiTrust is more effective on enhancing high-quality resources sharing among peers and more advanced in successful exchanges rate.

This paper proposes an efficient fingerprint recognition algorithm combining phase-based image matching and feature-based matching. In our previous work, we have already proposed an efficient fingerprint recognition algorithm using Phase-Only Correlation (POC), and developed commercial fingerprint verification units for access control applications. The use of Fourier phase information of fingerprint images makes it possible to achieve robust recognition for weakly impressed, low-quality fingerprint images. This paper presents an idea of improving the performance of POC-based fingerprint matching by combining it with feature-based matching, where feature-based matching is introduced in order to improve recognition efficiency for images with nonlinear distortion. Experimental evaluation using two different types of fingerprint image databases demonstrates efficient recognition performance of the combination of the POC-based algorithm and the feature-based algorithm.

In this paper we propose a file replication scheme inspired by a thermal diffusion phenomenon for storage load balancing in unstructured peer-to-peer (P2P) file sharing networks. The proposed scheme is designed such that the storage utilization ratios of peers will be uniform, in the same way that the temperature in a field becomes uniform in a thermal diffusion phenomenon. The proposed scheme creates replicas of files in peers probabilistically, where the probability is controlled by using parameters that can be used to find the trade-off between storage load balancing and search performance in unstructured P2P file sharing networks. First, we show through theoretical analysis that the statistical behavior of the storage load balancing controlled by the proposed scheme has an analogy with the thermal diffusion phenomenon. We then show through simulation that the proposed scheme not only has superior performance with respect to balancing the storage load among peers (the primary objective of the present proposal) but also allows the performance trade-off to be widely found. Finally, we qualitatively discuss a guideline for setting the parameter values in order to widely find the performance trade-off from the simulation results.

Given a question and a set of its candidate answers, the task of answer validation (AV) aims to return a Boolean value indicating whether a given candidate answer is the correct answer to the question. Unlike previous works, this paper presents an unsupervised model, called the U-model, for AV. This approach regards AV as a classification task and investigates how effectively using redundancy of the Web into the proposed architecture. Experimental results with TREC factoid test sets and Chinese test sets indicate that the proposed U-model with redundancy information is very effective for AV. For example, the top@1/mrr@5 scores on the TREC05, and 06 tracks are 40.1/51.5% and 35.8/47.3%, respectively. Furthermore, a cross-model comparison experiment demonstrates that the U-model is the best among the redundancy-based models considered. Even compared with a syntax-based approach, a supervised machine learning approach and a pattern-based approach, the U-model performs much better.

A technique for reducing the footprints of HMM-based speech synthesis systems by tying all covariance matrices of state distributions is described. HMM-based speech synthesis systems usually leave smaller footprints than unit-selection synthesis systems because they store statistics rather than speech waveforms. However, further reduction is essential to put them on embedded devices, which have limited memory. In accordance with the empirical knowledge that covariance matrices have a smaller impact on the quality of synthesized speech than mean vectors, we propose a technique for clustering mean vectors while tying all covariance matrices. Subjective listening test results showed that the proposed technique can shrink the footprints of an HMM-based speech synthesis system while retaining the quality of the synthesized speech.

Energy efficient routing is one of the key design issues to prolong the lifetime of wireless sensor networks (WSNs) since sensor nodes can not be easily re-charged once they are deployed. During routing process, the routes with only few hops or with too many hops are not energy efficient. Hop-based routing algorithms can largely improve the energy efficiency of multi-hop routing in WSNs because they can determine the optimal hop number as well as the corresponding intermediate nodes during multi-hop routing process under medium or high density network. In this paper, we not only focus on studying the relationship between energy consumption and hop number from theoretical point of view but also provide a practical selection criterion of the sub-optimal hop number under practical sensor network so as to minimize the energy consumption. We extend the theoretical deduction of optimal hop number and propose our Hop-based Energy Aware Routing (HEAR) algorithm which is totally distributed and localized. Simulation results show that our HEAR algorithm can reduce the average energy consumption about 10 times compared to the direct transmission algorithm and 2 to 10 times than other algorithms like LEACH and HEED under various network topologies.

In this paper, we propose a novel stochastic gradient algorithm for efficient adaptive filtering. The basic idea is to sparsify the initial error vector and maximize the benefits from the sparsification under computational constraints. To this end, we formulate the task of algorithm-design as a constrained optimization problem and derive its (non-trivial) closed-form solution. The computational constraints are formed by focusing on the fact that the energy of the sparsified error vector concentrates at the first few components. The numerical examples demonstrate that the proposed algorithm achieves the convergence as fast as the computationally expensive method based on the optimization without the computational constraints.

A 0.9-V 12-bit 40-MSPS pipeline ADC with I/Q amplifier sharing technique is presented for wireless receivers. To achieve high linearity even at 0.9-V supply, the clock signals to sampling switches are boosted over 0.9 V in conversion stages. The clock-boosting circuit for lifting these clocks is shared between I-ch ADC and Q-ch ADC, reducing the area penalty. Low supply voltage narrows the available output range of the operational amplifier. A pseudo-differential (PD) amplifier with two-gain-stage common-mode feedback (CMFB) is proposed in views of its wide output range and power efficiency. This ADC is fabricated in 90-nm CMOS technology. At 40 MS/s, the measured SNDR is 59.3 dB and the corresponding effective number of bits (ENOB) is 9.6. Until Nyquist frequency, the ENOB is kept over 9.3. The ADC dissipates 17.3 mW/ch, whose performances are suitable for ADCs for mobile wireless systems such as WLAN/WiMAX.

To detect the natural clusters for irregularly shaped data distribution is a difficult task in pattern recognition. In this study, we propose an efficient clustering algorithm for irregularly shaped clusters based on the advantages of spectral clustering and Affinity Propagation (AP) algorithm. We give a new similarity measure based on neighborhood dispersion analysis. The proposed algorithm is a simple but effective method. The experimental results on several data sets show that the algorithm can detect the natural clusters of input data sets, and the clustering results agree well with that of human judgment.

This paper proposes a topic-independent method for automatically scoring essay content. Unlike conventional topic-dependent methods, it predicts the human-assigned score of a given essay without training essays written to the same topic as the target essay. To achieve this, this paper introduces a new measure called MIDF that measures how important and relevant a word is in a given essay. The proposed method predicts the score relying on the distribution of MIDF. Surprisingly, experiments show that the proposed method achieves an accuracy of 0.848 and performs as well as or even better than conventional topic-dependent methods.

Digital fingerprinting is used to trace back illegal users, where unique ID known as digital fingerprints is embedded into a content before distribution. On the generation of such fingerprints, one of the important properties is collusion-resistance. Binary codes for fingerprinting with a code length of theoretically minimum order were proposed by Tardos, and the related works mainly focused on the reduction of the code length were presented. In this paper, we present a concrete and systematic construction of the Tardos's fingerprinting code using a chaotic map. Using a statistical model for correlation scores, the actual number of true-positive and false-positive detection is measured. The collusion-resistance of the generated fingerprinting codes is evaluated by a computer simulation.

Privacy preserving association rule mining algorithms have been designed for discovering the relations between variables in data while maintaining the data privacy. In this article we revise one of the recently introduced schemes for association rule mining using fake transactions (fs). In particular, our analysis shows that the fs scheme has exhaustive storage and high computation requirements for guaranteeing a reasonable level of privacy. We introduce a realistic definition of privacy that benefits from the average case privacy and motivates the study of a weakness in the structure of fs by fake transactions filtering. In order to overcome this problem, we improve the fs scheme by presenting a hybrid scheme that considers both privacy and resources as two concurrent guidelines. Analytical and empirical results show the efficiency and applicability of our proposed scheme.

This paper proposes a hardware-based parallel pattern matching engine using a memory-based bit-split string matcher architecture. The proposed bit-split string matcher separates the transition table from the state table, so that state transitions towards the initial state are not stored. Therefore, total memory requirements can be minimized.