Today, computer vision is used in different applications for intelligent transportation systems like: traffic surveillance, driver assistance, law enforcement etc. Amongst these applications, we are concentrating on speed measurement for law enforcement. In law enforcement applications, the presence of the license plate in the scene is a presupposition and metric parameters like vehicle's speed are to be estimated with a high degree of precision. The novelty of this paper is to propose a new precise, practical and fast procedure, with hierarchical architecture, to estimate the homraphic transform of the license plate and using this transform to estimate the vehicle's speed. The proposed method uses the RANSAC algorithm to improve the robustness of the estimation. Hence, it is possible to replace the peripheral equipment with vision based systems, or in conjunction with these peripherals, it is possible to improve the accuracy and reliability of the system. Results of experiments on different datasets, with different specifications, show that the proposed method can be used in law enforcement applications to measure the vehicle's speed.

In this study, Si(100) surface flattening process was investigated utilizing sacrificial oxidation method to improve Metal--Insulator--Semiconductor (MIS) diode characteristics. By etching of the 100,nm-thick sacrificial oxide formed by thermal oxidation at 1100$^{circ}$C, the surface roughness of Si substrate was reduced. The obtained Root-Mean-Square (RMS) roughness was decreased from 0.15,nm (as-cleaned) to 0.07,nm in the case of sacrificial oxide formed by wet oxidation, while it was 0.10,nm in the case of dry oxidation. Furthermore, time-dependent dielectric breakdown (TDDB) characteristic of Al/SiO$_{2}$(10,nm)/p-Si(100) MIS diode structures was found to be improved by the reduction of Si surface RMS roughness.

As data volumes explode, data storage costs become a large fraction of total IT costs. We can reduce the costs substantially by using compression. However, it is generally known that database compression is not suitable for write-intensive workloads. In this paper, we provide a comprehensive solution to improve the performance of compressed databases for write-intensive OLTP workloads. We find that storing data too densely in compressed pages incurs many future page splits, which require exclusive locks. In order to avoid lock contention, we reduce page splits by sacrificing a couple of percent of space savings. We reserve enough space in each compressed page for future updates of records and prevent page merges that are prone to incur page splits in the near future. The experimental results using TPC-C benchmark and MySQL/InnoDB show that our method gives 1.5 times higher throughput with 33% space savings compared with the uncompressed counterpart and 1.8 times higher throughput with only 1% more space compared with the state-of-the-art compression method developed by Facebook.

A new artificial fish swarm algorithm (AFSA) for solving the multiple knapsack problem (MKP) is introduced in this paper. In the proposed AFSA, artificial fish (AF) individuals are only allowed to search the region near constraint boundaries of the problem to be solved. For this purpose, several behaviors to be performed by AF individuals, including escaping behavior, randomly moving behavior, preying behavior and following behavior, were specially designed. Exhaustive experiments were implemented in order to investigate the proposed AFSA's performance. The results demonstrated the proposed AFSA has the ability of finding high-quality solutions with very fast speed, as compared with some other versions of AFSA based on different constraint-handling methods. This study is also meaningful for solving other constrained problems.

We investigated subjects' gaze movement when reading E-books and compared it with that when reading traditional paper books. By examining the eye motion associated with the reader encountering new lines and new pages during reading, we found that each new line was completed with one saccade in both E-books and paper books, but E-books and paper books differed in saccade patterns when the reader encountered a new page. In E-books, a regular eye movement such as steady gaze to the next page's start position was repeated. In contrast, in paper books, there is no regularity in eye movement during this transition. It was shown that reading behavior is variable and depends on the individual.

In this letter, we propose an improvement on a knapsack probabilistic encryption scheme [B. Wang, Q. Wu, Y. Hu, Information Sciences 177 (2007)], which was shown vulnerable to attacks due to Youssef [A.M. Youssef, Information Sciences 179 (2009)] and Lee [M.S. Lee, Information Sciences 222 (2013)], respectively. The modified encryption scheme is secure against Youssef's and Lee's attacks only at the costs of slightly compromising the efficiency of the original proposal.

Estimating the packet loss ratio of TCP transfers is essential for passively measuring Quality of Service (QoS) on the Internet traffic. However, only a few studies have been conducted on this issue. The Benko-Veres algorithm is one technique for estimating the packet loss ratio of two networks separated by a measurement point. However, this study shows that it leads to an estimation error of a few hundred percent in the particular environment where the packet loss probabilities between the two networks are asymmetrical. We propose a passive method for packet loss estimation that offers improved estimation accuracy by introducing classification conditions for the TCP retransmission timeout. An experiment shows that our proposed algorithm suppressed the maximum estimation error to less than 15%.

In this letter, we propose a novel search approach to blur kernel estimation for defocused image restoration. An adaptive binary search on consensus is the main contribution of our research. It is based on binary search and random sample consensus set (RANSAC). Moreover an evaluating function which uses a histogram of gradient distribution is proposed for assessing restored images. Simulations on an image benchmark dataset shows that the proposed algorithm can estimate, on average, the blur kernels 15.14% more accurately than other defocused image restoration algorithms.

In this paper, we have addressed the problem of ordering transactions in network-on-chips (NoCs) for post-silicon validation. The main idea is to extract the order of the transactions from the local partial orders in each NoC tile based on a set of “happened-before” rules, assuming transactions do not have a timestamp. The assumption is based on the fact that implementation and usage of a global time as timestamp in such systems may not be practical or efficient. When a new transaction is received in a tile, we send special messages to the neighboring tiles to inform them regarding the new transaction. The process of sending those special messages continues recursively in all the tiles that receive them until another such special message is detected. This way, we relate local orders of different tiles with each other. We show that our method can reconstruct the correct transaction orders when communication delays are deterministic. We have shown the effectiveness of our method by correctly ordering the transaction in NoCs with mesh and torus topologies with different sizes from 5*5 to 9*9. Also, we have implemented the proposed method in hardware to show its feasibility.

In camera-based object recognition and classification, surface color is one of the most important characteristics. However, apparent object color may differ significantly according to the illumination and surface conditions. Such a variation can be an obstacle in utilizing color features. Geusebroek et al.'s color invariants can be a powerful tool for characterizing the object color regardless of illumination and surface conditions. In this work, we analyze the estimation process of the color invariants from RGB images, and propose a novel invariant feature of color based on the elementary invariants to meet the circular continuity residing in the mapping between colors and their invariants. Experiments show that the use of the proposed invariant in combination with luminance, contributes to improve the retrieval performances of partial object image matching under varying illumination conditions.

We propose a new coding scheme for lossless bit rate reduction of the MPEG Surround module in unified speech and audio coding (USAC). The proposed scheme is based on context-adaptive arithmetic coding for efficient bit stream composition of spatial parameters. Experiments show that it achieves the significant lossless bit reduction of 9.93% to 12.14% for spatial parameters and 8.64% to 8.96% for the overall MPEG Surround bit streams compared to the original scheme. The proposed scheme, which is not currently included in USAC, can be used for the improved coding efficiency of MPEG Surround in USAC, where the saved bits can be utilized by the other modules in USAC.

Multimedia transactions between vehicles are expected to become a promising application in VANETs but security is a fundamental issue that must be resolved before such transactions can become practical and trusted. Existing certificate-based digital signature schemes are ineffective for ensuring the security of multimedia transactions in VANETs. This ineffectiveness exists because there is no guarantee that (1) vehicles can download the latest certificate revocation lists or that (2) vehicles can complete a multimedia transaction before leaving their communication range. These two problems result, respectively, from a lack of infrastructure and from the inconsistent connectivity inherent in VANETs. In this paper, we propose a digital signature approach that combines a certificateless signature scheme and short-lived public keys to alleviate these problems. We then propose a security protocol that uses the proposed signature approach for multimedia transactions between vehicles. The proposed protocol enables vehicles to trade in multimedia resources without an online trust authority. We provide an analytical approach to optimizing the security of the proposed protocol. The security and performance of our protocol are evaluated via simulation and theoretical analysis. Based on these evaluations, we contend that the proposed protocol is practical for multimedia transactions in VANETs in terms of security and performance.

The subset sum problem, which is often called as the knapsack problem, is known as an NP-hard problem, and there are several cryptosystems based on the problem. Assuming an oracle for shortest vector problem of lattice, the low-density attack algorithm by Lagarias and Odlyzko and its variants solve the subset sum problem efficiently, when the “density” of the given problem is smaller than some threshold. When we define the density in the context of knapsack-type cryptosystems, weights are usually assumed to be chosen uniformly at random from the same interval. In this paper, we focus on general subset sum problems, where this assumption may not hold. We assume that weights are chosen from different intervals, and make analysis of the effect on the success probability of above algorithms both theoretically and experimentally. Possible application of our result in the context of knapsack cryptosystems is the security analysis when we reduce the data size of public keys.

In this letter, we investigate the performance impact of disjoint multiple paths on SCTP in the connected MANET under emergency situations. Disjoint multiple paths allow multi-homing of SCTP to be fully utilized in MANETs, but it may cause inappropriate SACK handling. Through simulations, we evaluate the impact in terms of throughput and energy efficiency.

This paper addresses stereo matching under scenarios of smooth region and obviously slant plane. We explore the flexible handling of color disparity, spatial relation and the reliability of matching pixels in support windows. Building upon these key ingredients, a robust stereo matching algorithm using local plane fitting by Confidence-based Support Window (CSW) is presented. For each CSW, only these pixels with high confidence are employed to estimate optimal disparity plane. Considering that RANSAC has shown to be robust in suppressing the disturbance resulting from outliers, we employ it to solve local plane fitting problem. Compared with the state of the art local methods in the computer vision community, our approach achieves the better performance and time efficiency on the Middlebury benchmark.

This paper proposes 7T SRAM which realizes block-level simultaneous copying feature. The proposed SRAM can be used for data transfer between local memories such as checkpoint data storage and transactional memory. The 1-Mb SRAM is comprised of 32-kb blocks, in which 16-kb data can be copied in 33.3 ns at 1.2 V. The proposed scheme reduces energy consumption in copying by 92.7% compared to the conventional read-modify-write manner. By applying the proposed scheme to transactional memory, the number of write back cycles is possibly reduced by 98.7% compared with the conventional memory system.

We propose a robust and efficient algorithm called ROCKET for clustering large-scale transaction databases. ROCKET is a divisive hierarchical algorithm that makes the most of recent hardware architecture. ROCKET handles the cases with the small and the large number of similar transaction pairs separately and efficiently. Through experiments, we show that ROCKET achieves high-quality clustering with a dramatic performance improvement.

Flash SSDs are being incorporated in many enterprise storage platforms recently and expected to play a notable role for IO-intensive applications. However, the IO characteristics of flash SSDs are very different from those of hard disks. Since existent storage subsystems are designed on the basis of characteristics of hard disks, the IO performance of flash SSDs may not be obtained as expected. This paper provides an evaluation of flash SSDs in transaction processing systems with TPC-C benchmark. We present performance results with various configurations and describe our observations of the IO behaviors at different levels along the IO path, which helps to understand the performance of flash-based transaction processing systems and provides certain references to build flash-based systems for IO-intensive applications.

In this paper, we emphasize the need for data cleansing when clustering large-scale transaction databases and propose a new data cleansing method that improves clustering quality and performance. We evaluate our data cleansing method through a series of experiments. As a result, the clustering quality and performance were significantly improved by up to 165% and 330%, respectively.

This paper presents a fast and systematic architecture exploration method that realizes an efficient IEEE 802.11e based hardware/software co-design Medium Access Control (MAC) system architecture, which can achieve near theoretical MAC throughput for burst data transmission while complying with strict channel access time requirements. Our design approach uses SystemC based Transaction Level Modeling (TLM) framework to integrate reconfigurable general purpose computing and communication resources into the application model for rapid evaluation of core parameters, system performance, and application specific optimizations. As a result, a MAC system architecture that achieves a simulated MAC throughput of more than 100 Mbps when transmitted at 260 Mbps of Physical Layer (PHY) data rate is obtained. This result is verified with X-X-IMPLEMENTATION on a Xilinx Field-Programmable Gate Array (FPGA) board.