An image appearance model called iCAM06 was designed for high dynamic range (HDR) image rendering. The dynamic range of an HDR image needs to be mapped on output devices, which is called tone compression or tone mapping. The iCAM06, the representative HDR rendering algorithm, uses tone compression for image reproduction on the low dynamic range of output devices. However, color saturation reduction occurs during its tone compression process. We propose a saturation correction method using the inverse compensation in order to recover the saturation reduction in the iCAM06. Experimental results show that the proposed method has better performance than the iCAM06 from the viewpoint of saturation accuracy and rendering preference.

We determine the autocorrelations of the quaternary sequence over F4 and its modified version introduced by Du et al. [X.N. Du et al., Linear complexity of quaternary sequences generated using generalized cyclotomic classes modulo 2p, IEICE Trans. Fundamentals, vol.E94-A, no.5, pp.1214–1217, 2011]. Furthermore, we reveal a drawback in the paper aforementioned and remark that the proof in the paper by Kim et al. can be simplified.

Modern web applications incorporate many programmatic frameworks and APIs that are often pushed to the client-side with most of the application logic while contents are the result of mashing up several resources from different origins. Such applications are threatened by attackers that often attempts to inject directly, or by leveraging a stepstone website, script codes that perform malicious operations. Web scripting based malware proliferation is being more and more industrialized with the drawbacks and advantages that characterize such approach: on one hand, we are witnessing a lot of samples that exhibit the same characteristics which make these easy to detect, while on the other hand, professional developers are continuously developing new attack techniques. While obfuscation is still a debated issue within the community, it becomes clear that, with new schemes being designed, this issue cannot be ignored anymore. Because many proposed countermeasures confess that they perform better on unobfuscated contents, we propose a 2-stage technique that first relieve the burden of obfuscation by emulating the deobfuscation stage before performing a static abstraction of the analyzed sample's functionalities in order to reveal its intent. We support our proposal with evidence from applying our technique to real-life examples and provide discussion on performance in terms of time, as well as possible other applications of proposed techniques in the areas of web crawling and script classification. Additionally, we claim that such approach can be generalized to other scripting languages similar to JavaScript.

In this letter, a two-stage TOA estimation scheme is proposed for positioning in OFDM-based WLAN systems under indoor environments. The estimation scheme consists of coarse estimation and fine estimation. The presented scheme effectively exploits the preamble of the OFDM-based WLAN for accurate estimation. The simulation results exhibit that the performance of the proposed approach is comparable to that of super-resolution estimation even with lower computational complexity.

In this paper, the Getis statistic is applied to ALOS- PALSAR (Advanced Land Ovserving Satellite-Phased Array L-band Synthetic Aperture Radar) images for assessing the building damage caused by the Wenchuan earthquake in 2008. As a proposed image analysis, a simulated building image using mapping and projection algorithm is first presented for analysis of the Getis statistic. The results show the high accuracy of the assessment of the proposed approach. The Getis statistic is then applied to two ALOS-PALSAR images acquired before and after the Wenchuan earthquake to assess the level of building damage. Results of the Getis statistic show that the damage level is approximately 81%.

The air traffic situational awareness is an essential factor for flight safety and efficiency. Today, pilots have only two methods for situational awareness, through visual acquisition or with traffic information via voice messages from Air Traffic Controllers. These methods have limitations in reducing aircraft separation because of their delay in acquiring traffic. To improve the acquisition of traffic information, airborne surveillance with ADS-B/TIS-B has been proposed. This paper reports on the prototype TIS-B system developed by ENRI and on the results of evaluations with flight testing.

This letter considers a sum-rate maximization problem with user scheduling wherein each user has a minimum-rate requirement in multiple-input-multiple-output broadcast channel. The multiuser strategy used in the user scheduling is a joint transceiver scheme with block diagonal geometric mean decomposition. Since optimum solution to the user scheduling problem generally requires exhaustive search, we propose a suboptimum user scheduling algorithm with each user's minimum-rate requirement as the main constraint. In order to satisfy maximum sum-rate and minimum-rate constraints simultaneously, we additionally consider power allocation for scheduled users. Simulation results show that the proposed user scheduling algorithm, together with the user power allocation, achieves sum-rate close to the exhaustive search, while also guarantees minimum-rate requirement of each user.

We propose a data transmission method for resonant wireless power transmission systems. In order to transmit data, we use the coils originally designed for power transmission, no additional antennas are required. We focus on uplink data transmission and adopt the load modulation technique. This configuration yields mid-range data transmission without transmitting power. In addition, the proposal enables simultaneous power feeding and uplink data transmission. We make a prototype demonstrating resonant wireless power transmission and measure its S-parameter under some load conditions. The results confirm the potential of load modulation in supporting uplink data transmission. Additionally, the results are elucidated by analyzing an equivalent circuit. Measured S-parameter and equivalent circuit response are found to be similar.

In this paper, we present a cognitive relay network with two primary transceivers that communicate via several distributed relay terminals. Spectrum sensing is deployed at the relays to sense the absence/presence of the primary transceivers based on energy detection. The primary network utilizes a two-step two-way amplify-and-forward (AF) scheme by using the cognitive radio (CR) terminals as its relay nodes when the primary network is not in operation, in contrast, the CRs communicate with their own base station (BS). In the first relaying step, the primary transceivers send their signal to the CRs/relays. Distributed beamforming is then performed in the second relaying step. Our aim is to set the beamforming weights so as to minimize the total power dissipated in the relay network while satisfying a target signal-to-noise ratio (SNR) at the primary transceivers and at the cognitive BS. This is achieved by solving an optimization problem that we formulate as a nonconvex quadratically constrained quadratic program (QCQP). This problem is solved efficiently by semidefinite relaxation (SDR) and Lagrangian duality. Simulation results are provided to demonstrate the superiority of our proposed technique, compared to classical beamforming techniques, in terms of power reduction.

In this paper, we evaluate the downlink performance of Transparent mode (T-mode) and Non-Transparent mode (NT-mode) in a two-hop cellular system based on IEEE 802.16j. In particular, we evaluate the performance in terms of the system capacity, optimal resource allocation, and outage probability using Monte Carlo simulation with various system parameters such as different Frequency Reuse Factors (FRFs) and the distance between Base Station (BS) and Relay Station (RS). To analyze the Signal to Interference and Noise Ratio (SINR) of the access and relay links, an SINR model is introduced for cellular multihop systems considering intra- and inter-cell interferences. Then, we present a method of optimal resource allocation for the Access Zone (AZ) and Relay Zone (RZ) to maximize the system capacity. Consequently, the simulation results provide an insight into choosing the appropriate RS position and optimal resource allocation. Through numerical examples, it is found that the FRFs of two and three are good choices to achieve the highest capacity with low outage in T- and NT-modes, respectively.

In non-cooperative scenarios, the estimation of direct sequence spread spectrum (DS-SS) signals has to be done in a blind manner. In this letter, we consider the spreading sequence estimation problem for DS-SS signals. First, the maximum likelihood estimate (MLE) of spreading sequence is derived, then a semidefinite relaxation (SDR) approach is proposed to cope with the exponential complexity of performing MLE. Simulation results demonstrate that the proposed approach provides significant performance improvements compared to existing methods, especially in the case of low numbers of data samples and low signal-to-noise ratio (SNR) situations.

The multiple-access channel (MAC) becomes very popular in various communication systems, because multi-terminal communication systems have been widely used in practical systems, e.g., mobile phones and P2P, etc. For some MACs, it is known that feedback can enlarge the capacity region, where the capacity region is the set of rate pairs such that the error probability can be made arbitrarily small for sufficiently large block length. The capacity region for general MACs, which are not required to satisfy ergodicity and stationarity with perfect feedback was first shown by Tatikonda and Mitter without the proof, where perfect feedback means that the channel output is perfectly fed back to senders. In this paper, we generalize Tatikonda and Mitter's result to the case of deterministic feedback, where the values of deterministic functions of past channel outputs is fed back to senders. We show that the capacity region for general MACs with deterministic feedback can be represented by the information-spectrum formula introduced by Han and Verdu, and directed information introduced by Massey. We also investigate the compound MAC problem, the ε-coding problem, the strong converse property and the cost constraint problem for general MACs with deterministic feedback.

Authenticated encryption schemes are very useful for private and authenticated communication. In 2010, Rasslan and Youssef showed that the Hwang et al.'s authenticated encryption scheme is not secure by presenting a message forgery attack. However, Rasslan and Youssef did not give how to solve the security issue. In this letter, we give an improvement of the Hwang et al.'s scheme. The improved scheme not only solves the security issue of the original scheme, but also maintains its efficiency.

For amplify-and-forward (AF) relaying with imperfect channel estimation, we present the average symbol error rate (SER) and the diversity and multiplexing tradeoff (DMT) analysis for both opportunistic relaying (OPR) and all-participate relaying (APR) schemes. SER comparisons show that when the channel estimation quality order is no larger than 1, OPR will perform worse than APR in high SNR region. Moreover, small channel estimation quality orders will also lead to significant DMT loss.

Measuring the relational similarity between word pairs is important in numerous natural language processing tasks such as solving word analogy questions, classifying noun-modifier relations and disambiguating word senses. We propose a supervised classification method to measure the similarity between semantic relations that exist between words in two word pairs. First, each pair of words is represented by a vector of automatically extracted lexical patterns. Then a binary Support Vector Machine is trained to recognize word pairs with similar semantic relations to a given word pair. To train and evaluate the proposed method, we use a benchmark dataset that contains 374 SAT multiple-choice word-analogy questions. To represent the relations that exist between two word pairs, we experiment with 11 different feature functions, including both symmetric and asymmetric feature functions. Our experimental results show that the proposed method outperforms several previously proposed relational similarity measures on this benchmark dataset, achieving an SAT score of 46.9.

This paper introduces a new dynamic 3D mesh representation that provides 3D animation support of progressive display and drastically reduces the amount of storage space required for 3D animation. The primary purpose of progressive display is to allow viewers to get animation as quickly as possible, rather than having to wait until all data has been downloaded. In other words, this method allows for the simultaneous transmission and playing of 3D animation. Experiments show that coarser 3D animation could be reconstructed with as little as 150 KB of data transferred. Using the sustained transmission of refined operators, viewers feel that resolution approaches that of the original animation. The methods used in this study are based on a compression technique commonly used in 3D animation - clustered principle component analysis, using the linearly independent rules of principle components, so that animation can be stored using smaller amounts of data. This method can be coupled with streaming technology to reconstruct animation through iterative updating. Each principle component is a portion of the streaming data to be stored and transmitted after compression, as well as a refined operator during the animation update process. This paper considers errors and rate-distortion optimization, and introduces weighted progressive transmitting (WPT), using refined sequences from optimized principle components, so that each refinement yields an increase in quality. In other words, with identical data size, this method allows each principle component to reduce allowable error and provide the highest quality 3D animation.

This paper proposes likelihood smoothing techniques to improve decision tree-based acoustic models, where decision trees are used as replacements for Gaussian mixture models to compute the observation likelihoods for a given HMM state in a speech recognition system. Decision trees have a number of advantageous properties, such as not imposing restrictions on the number or types of features, and automatically performing feature selection. This paper describes basic configurations of decision tree-based acoustic models and proposes two methods to improve the robustness of the basic model: DT mixture models and soft decisions for continuous features. Experimental results for the Aurora 2 speech database show that a system using decision trees offers state-of-the-art performance, even without taking advantage of its full potential and soft decisions improve the performance of DT-based acoustic models with 16.8% relative error rate reduction over hard decisions.

We propose two types of autonomic and distributed cooperative behaviors of peers for peer-to-peer (P2P) file-sharing networks. Cooperative behaviors of peers are mediated by query trails, and allows the exploration of better trade-off points between file search and storage load balancing performance. Query trails represent previous successful search paths and indicate which peers contributed to previous file searches and were at the same time exposed to the storage load. The first type of cooperative behavior is to determine the locations of replicas of files through the medium of query trails. Placement of replicas of files on strong query trails contributes to improvement of search performance, but a heavy load is generated due to writing files in storage to peers on the strong query trails. Therefore, we attempt to achieve storage load balancing between peers, while avoiding significant degradation of the search performance by creating replicas of files in peers adjacent to peers on strong query trails. The second type of cooperative behavior is to determine whether peers provide requested files through the medium of query trails. Provision of files by peers holding requested files on strong query trails contributes to better search performance, but such provision of files generates a heavy load for reading files from storage to peers on the strong query trails. Therefore, we attempt to achieve storage load balancing while making only small sacrifices in search performance by having peers on strong query trails refuse to provide files. Simulation results show that the first type of cooperative behavior provides equal or improved ability to explore trade-off points between storage load balancing and search performance in a static and nearly homogeneous P2P environment, without the need for fine tuning parameter values, compared to replication methods that require fine tuning of their parameters values. In addition, the combination of the second type and the first type of cooperative behavior yields better storage load balancing performance with little degradation of search performance. Moreover, even in a dynamic and heterogeneous P2P environment, the two types of cooperative behaviors yield good ability to explore trade-off points between storage load balancing and search performance.

Weight perturbation learning was proposed as a learning rule in which perturbation is added to the variable parameters of learning machines. The generalization performance of weight perturbation learning was analyzed by statistical mechanical methods and was found to have the same asymptotic generalization property as perceptron learning. In this paper we consider the difference between perceptron learning and AdaTron learning, both of which are well-known learning rules. By applying this difference to weight perturbation learning, we propose adaptive weight perturbation learning. The generalization performance of the proposed rule is analyzed by statistical mechanical methods, and it is shown that the proposed learning rule has an outstanding asymptotic property equivalent to that of AdaTron learning.

In this letter, we propose an effective method to retrieve images from a 2D shape image database using discrete shock graphs combined with an adaptive selection algorithm. Experimental results show that our method is more accurate and fast than conventional approaches and reduces computational complexity.