Previous works show that the probabilistic Latent Semantic Analysis (pLSA) model is one of the best generative models for scene categorization and can obtain an acceptable classification accuracy. However, this method uses a certain number of topics to construct the final image representation. In such a way, it restricts the image description to one level of visual detail and cannot generate a higher accuracy rate. In order to solve this problem, we propose a novel generative model, which is referred to as multi-scale multi-level probabilistic Latent Semantic Analysis model (msml-pLSA). This method consists of two parts: multi-scale part, which extracts visual details from the image of diverse resolutions, and multi-level part, which concentrates multiple levels of topic representation to model scene. The msml-pLSA model allows for the description of fine and coarse local image detail in one framework. The proposed method is evaluated on the well-known scene classification dataset with 15 scene categories, and experimental results show that the proposed msml-pLSA model can improve the classification accuracy compared with the typical classification methods.

In this paper, two techniques for implementing a low-power pipelined analog-to-digital converter (ADC) are proposed. First, the time-interleaved correlated double sampling (CDS) technique is proposed to compensate the finite gain error of operational amplifiers in switched-capacitor circuits without a half-rate front-end sample-and-hold amplifier (SHA). Therefore, low-gain amplifiers and the SHA-less architecture can be used to effectively reduce power consumption of a pipelined ADC. Second, the back-end pipelined stages of a pipelined ADC are implemented using a low-power time-interleaved successive approximation (SA) ADC rather than operational amplifiers to further reduce the power consumption of the proposed pipelined ADC. A 9-bit, 100-MS/s hybrid pipelined-SA ADC is implemented in the TSMC 0.13 µm triple-well 1P8M CMOS process. The ADC achieves a spurious free dynamic range (SFDR) of 62.15 dB and a signal-to-noise distortion ratio (SNDR) of 50.85-dB for 2-MHz input frequency at a 100-MS/s sampling rate. The power consumption is 21.2 mW from a 1.2 V supply. The core area of the ADC is 1.6 mm2.

In Video-on-Demand (VoD) services, the playback continuity is one of the most crucial factors for end-user to judge service quality. It is even more significant than the actual video image quality since new generation VoD users commonly have heterogeneous requirements on service according to their context. Moreover, managing dynamic situations in VoD service is always a challenge, especially in the unpredictable user preferences and network conditions. In this paper, i) Autonomous Decentralized VoD System (ADVODS) has been proposed to satisfy different service quality demands of users and, ii) the Autonomous Node Allocation Technology (ANAT) is proposed for assuring service continuity. With the help of autonomous nodes and mobile agents, ANAT can applies different backup policies to users with different Service Level Agreements (SLA), and dynamically update the backup schema to adapt the changing situations such as various service time or congestion events. Drawing on the evaluation results this paper shows that proposed system architecture has a better performance on streaming service provision and continuity.

In this paper we first demonstrate that effective selection functions in power analysis attacks change depending on circuit architectures of a block cipher. We then conclude that the most resistant architecture on its own, in the case of the loop architecture, has two data registers have separate roles: one for storing the plaintext and ciphertext, and the other for storing intermediate values. There, the pre-whitening operation is placed at the output of the former register. The architecture allows the narrowest range of selection functions and thereby has resistance against ordinary CPA. Thus, we can easily defend against attacks by ordinary CPA at the architectural level, whereas we cannot against DPA. Secondly, we propose a new technique called "self-templates" in order to raise the accuracy of evaluation of DPA-based attacks. Self-templates enable to differentiate meaningful selection functions for DPA-based attacks without any strong assumption as in the template attack. We also present the results of attacks to an AES co-processor on an ASIC and demonstrate the effectiveness of the proposed technique.

Context-aware applications are a key aspect of pervasive computing. The core issue of context-aware application development is how to make the application behave suitably according to the changing context without coupling such context dependencies in the program. Several programming paradigms and languages have been proposed to facilitate the development, but they are either lack of sufficient flexibility or somewhat complex for programming and deploying. A reference programming model is proposed in this paper to make up inadequacy of those approaches. In the model, virtual tables constructed by system and maintained by space manager connect knowledge of both developer and space manager while separating dependency between context and application logic from base program. Hierarchy and architecture of the model are presented, and implementation suggestions are also discussed. Validation and evaluation show that the programming model is lightweight and easy to be implemented and deployed. Moreover, the model brings better flexibility for developing context-aware applications.

A sanitizable signature scheme is a signature scheme which, after the signer generates a valid signature of a message, allows a specific entity (sanitizer) to modify the message for hiding several parts. Existing sanitizable signature schemes require the message to be divided into pre-defined blocks before signing so that each block can be sanitized independently. However, there are cases where the parts of the message which are needed to be sanitized can not be determined in the time of signing. Thus, it is difficult to decide the partition of the blocks in such cases. Since the length of the signature is usually proportional to the number of blocks, signing every bit independently will make the signature too long. In this paper, we propose a solution by introducing a new concept called sequential bitwise sanitizable signature schemes, where any sequence of bits of the signed document can be made sanitizable without pre-defining them, and without increasing the length of signature. We also show that a one-way permutation suffices to get a secure construction, which is theoretically interesting in its own right, since all the other existing schemes are constructed using stronger assumptions.

This paper presents an architecture and a circuit design of readout address compression for a high-speed 3-D range-finding image sensor using the light-section method. We utilize a kind of variable-length code which is modified to suit the 3-D range-finder. The best compression rate by the proposed compression technique is 33.3%. The worst compression and the average compression rate is 56.4% and 42.4%, respectively, when we simulated the effectivity by using the example of measured sheet scans. We also show the measurement result of the fabricated image sensor with the address compression.

This paper discusses speaker verification (SV) using Gaussian mixture models (GMMs), where only utterances of enrolled speakers are required. Such an SV system can be realized using artificially generated cohorts instead of real cohorts from speaker databases. This paper presents a rational approach to set GMM parameters for artificial cohorts based on statistics of GMM parameters for real cohorts. Equal error rates for the proposed method are about 10% less than those for the previous method, where GMM parameters for artificial cohorts were set in an ad hoc manner.

This paper presents an unsupervised learning-based method for selection of feature points and object category classification without previous setting of the number of categories. Our method consists of the following procedures: 1)detection of feature points and description of features using a Scale-Invariant Feature Transform (SIFT), 2)selection of target feature points using One Class-Support Vector Machines (OC-SVMs), 3)generation of visual words of all SIFT descriptors and histograms in each image of selected feature points using Self-Organizing Maps (SOMs), 4)formation of labels using Adaptive Resonance Theory-2 (ART-2), and 5)creation and classification of categories on a category map of Counter Propagation Networks (CPNs) for visualizing spatial relations between categories. Classification results of static images using a Caltech-256 object category dataset and dynamic images using time-series images obtained using a robot according to movements respectively demonstrate that our method can visualize spatial relations of categories while maintaining time-series characteristics. Moreover, we emphasize the effectiveness of our method for category classification of appearance changes of objects.

This paper proposes a new kind of communication system for air traffic control over the oceans; it is particularly effective at handling high air traffic loads due to many oceanic flights. In this system, each aircraft position report is sent to its relevant ground station by forwardly relaying them via a multi hop ad-hoc network that is formed by the aircraft between this aircraft and the ground station. In addition, an effective multiple access scheme with optimal values is also proposed. This scheme enables the various aircraft involved in relaying the signal to operate autonomously in a flight-route airspace. Furthermore, two useful schemes are proposed for efficient timeslot reuse and timeslot assignment in cases of low aircraft densities: the position aided timeslot reuse (PATR) and distance based timeslot assignment (DBTA), respectively. Finally, another scheme is proposed to improve the achievable relayed packet rate under low aircraft densities, which is called interference-based node selection (IB-NS). In all, the proposed system combined with those three schemes show the availability to utilize this system for air traffic control communications, specifically on high traffic ocean routes.

In this paper, we study the decentralized coverage control problem for an environment using a group of autonomous mobile robots with nonholonomic kinematic and dynamic constraints. In comparison with standard coverage control procedures, we develop a combined controller for Voronoi-based coverage approach in which kinematic and dynamic constraints of the actual mobile sensing robots are incorporated into the controller design. Furthermore, a collision avoidance component is added in the kinematic controller in order to guarantee a collision free coverage of the area. The convergence of the network to the optimal sensing configuration is proven with a Lyapunov-type analysis. Numerical simulations are provided approving the effectiveness of the proposed method through several experimental scenarios.

Subspace learning based face recognition methods have attracted considerable interest in recent years, including Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA), and some extensions for 2D analysis. However, a disadvantage of all these approaches is that they perform subspace analysis directly on the reshaped vector or matrix of pixel-level intensity, which is usually unstable under illumination or pose variance. In this paper, we propose to represent a face image as a local descriptor tensor, which is a combination of the descriptor of local regions (K*K-pixel patch) in the image, and is more efficient than the popular Bag-Of-Feature (BOF) model for local descriptor combination. Furthermore, we propose to use a multilinear subspace learning algorithm (Supervised Neighborhood Embedding-SNE) for discriminant feature extraction from the local descriptor tensor of face images, which can preserve local sample structure in feature space. We validate our proposed algorithm on Benchmark database Yale and PIE, and experimental results show recognition rate with our method can be greatly improved compared conventional subspace analysis methods especially for small training sample number.

Owing to the high expressiveness of regular expression, it is frequently used in searching and manipulation of text based data. Regular expression is highly applicable in processing Latin alphabet based text, but the same cannot be said for Hangeul*, the writing system for Korean language. Although Hangeul possesses alphabetic features within the script, expressiveness of regular expression pattern using Hangeul is hindered by the absence of syllable decomposition. Without decomposition support in regular expression, searching through Hangeul text is limited to string literal matching. Literal matching has made enumeration of syllable candidates in regular expression pattern definition indispensable, albeit impractical, especially for a large set of syllable candidates. Although the existing implementation of canonical decomposition in Unicode standard does reduce a pre-composed Hangeul syllable into smaller unit of consonant-vowel or consonant-vowel-consonant letters, it still leaves quite a number of the individual letters in compounded form. We have observed that there is a necessity to further reduce the compounded letters into unit of basic letters to properly represent the Korean script in regular expression. We look at how the new canonical decomposition technique proposed by Kim can help in handling Hangeul in regular expression. In this paper, we examine several of the performance indicators of full decomposition of Hangeul syllable to better understand the overhead that might incur, if a full decomposition were to be implemented in a regular expression engine. For efficiency considerations, we propose a semi decomposition technique alongside with a notation for defining Hangeul syllables. The semi decomposition functions as an enhancement to the existing regular expression syntax by taking in some of the special constructs and features of the Korean language. This proposed technique intends to allow an end user to have a greater freedom to define regular expression syntax for Hangeul.

Undeniable signatures, introduced by Chaum and van Antwerpen, require a verifier to interact with the signer to verify a signature, and hence allow the signer to control the verifiability of his signatures. Convertible undeniable signatures, introduced by Boyar, Chaum, Damgård, and Pedersen, furthermore allow the signer to convert signatures to publicly verifiable ones by publicizing a verification token, either for individual signatures or for all signatures universally. In addition, the original definition allows the signer to delegate the ability to prove validity and convert signatures to a semi-trusted third party by providing a verification key. While this functionality is implemented by the early convertible undeniable signature schemes, most recent schemes do not consider this form of delegation despite its practical appeal. In this paper we present an updated definition and security model for schemes allowing delegation, and furthermore highlight a new essential security property, token soundness, which is not formally treated in the previous security models for convertible undeniable signatures. We then propose a new convertible undeniable signature scheme. The scheme allows delegation of verification and is provably secure in the standard model assuming the computational co-Diffie-Hellman problem, a closely related problem, and the decisional linear problem are hard. Furthermore, unlike the recently proposed schemes by Phong et al. and Huang et al., our scheme provably fulfills all security requirements while providing short signatures.

Recently, Jin, Wen, and Du proposed an identity-based signcryption scheme in the standard model. In this letter, we show that their scheme does not have the indistinguishability against adaptive chosen ciphertext attacks and existential unforgeability against adaptive chosen messages attacks.

A hash chain H for a hash function hash(·) is a sequence of hash values ⟨ xn, xn-1,..., x0 ⟩, where x0 is a secret value, xi is generated by xi = hash(xi-1) for 1 ≤ i ≤ n, and xn is a public value. Hash values of H are disclosed gradually from xn-1 to x0. The correctness of a disclosed hash value xi can be verified by checking the equation xn =? hashn-i(xi). To speed up the verification, Fischlin introduced a check-bit scheme at CT-RSA 2004. The basic idea of the check-bit scheme is to output some extra information cb, called a check-bit vector, in addition to the public value xn, which allows each verifier to perform only a fraction of the original work according to his or her own security level. We revisit the Fischlin's check-bit scheme and show that the length of the check-bit vector cb can be reduced nearly by half. The reduced length of cb is close to the theoretic lower bound.

An improvement of estimating sound power spectra located in a particular 2-dimensional area is proposed. We previously proposed a conventional method that estimates sound power spectra using multiple fixed beamformings in order to emphasize speech located in a particular 2-dimensional area. However, the method has one drawback that the number of areas where the active sound sources are located must be restricted. This restriction makes the method less effective when many noise source located in different areas are simultaneously active. In this paper, we reveal the cause of this restriction and determine the maximum number of areas for which the method is able to simultaneously estimate sound power spectra. Then we also introduce a procedure for investigating areas that include active sound sources to reduce the number of unknown power spectra to be estimated. The effectiveness of the proposed method is examined by experimental evaluation applied to sounds recorded in a practical environment.

Those host-based intrusion detection models like VPStatic first construct a model of acceptable behaviors for each monitored program via static analysis, and then perform intrusion detection by comparing them with programs' runtime behaviors. These models usually share the highly desirable feature that they do not produce false alarms but face the conflicts between accuracy and efficiency. For instance, the high accuracy of the VPStatic model is at the cost of high space complexity. In this paper, we use a statically-constructed state transition table (STT), which records expected transitions among system calls as well as their stack states (return address lists), as a behavior model to perform context-sensitive intrusion detection. According to our analysis, our STT model improves the space efficiency of the VPStatic model without decreasing its high precision and time efficiency. Experiments show that for three test programs, memory uses of our STT models are all much less than half of the VPStatic models'. Thereby, we alleviate the conflicts between the accuracy and the efficiency.

Accelerator cores in low-power embedded processors have on-chip multiple memory modules to increase the data access speed and to enable parallel data access. When large functional units such as multipliers and dividers are used for addressing, a large power and chip area are consumed. Therefore, recent low-power processors use small functional units such as adders and counters to reduce the power and area. Such small functional units make it difficult to implement complex addressing patterns without duplicating data among multiple memory modules. The data duplication wastes the memory capacity and increases the data transfer time significantly. This paper proposes a method to reduce the memory duplication for window-based image processing, which is widely used in many applications. Evaluations using an accelerator core show that the proposed method reduces the data amount and data transfer time by more than 50%.

In OFDM systems, in-phase and quadrature (I/Q) imbalances generated in the analog front-end introduce inter-channel interference and, consequently, error performance degradation. This letter provides an exact expression involving the two-dimensional (2-D) Gaussian Q-function for the error probability of an arbitrary 2-D modulated OFDM signal with I/Q imbalances. The effects of I/Q imbalances on the distribution of an AWGN and the error performance are analyzed.