NIDA technical review: nitrite inhalants

Nitrite inhalants are commonly abused substances in the US and Europe. "Nitrite inhalants and AIDS" was a popular topic in the early 1980s when the cause of AIDS was not known. With the discovery of HIV, concern about nitrite use wained. However, nitrite inhalant use is associated with behavioral relapse and HIV transmission among gay men, with decreased lymphocyte counts and natural killer cell activity in laboratory studies, and remains a candidate "cofactor" in the pathogenesis of AIDS-related Karposi sarcoma. Discouraging nitrite use continues to be a worthwhile public health goal. Participants recommend specific research efforts.     

Recognition of handwritten Chinese characters by critical region analysis

The problem of recognizing offline handwritten Chinese characters has been investigated extensively. One difficulty is due to the existence of characters with very similar shapes. In this paper, we propose a “critical region analysis” technique which highlights the critical regions that distinguish one character from another similar character. The critical regions are identified automatically based on the output of the Fisher's discriminant. Additional features are extracted from these regions and contribute to the recognition process. By incorporating this technique into the character recognition system, a record high recognition rate of 99.53% on the ETL-9B database is obtained.     

Scheduling jobs with equal processing times subject to machine eligibility constraints

We consider the problem of nonpreemptively scheduling a set of n jobs with equal processing times on m parallel machines so as to minimize the makespan. Each job has a prespecified set of machines on which it can be processed, called its eligible set. We consider the most general case of machine eligibility constraints as well as special cases of nested and inclusive eligible sets. Both online and offline models are considered. For offline problems we develop optimal algorithms that run in polynomial time, while for online problems we focus on the development of optimal algorithms of a new and more elaborate structure as well as approximation algorithms with good competitive ratios.     

Rule acquisition and attribute reduction in real decision formal contexts

Formal Concept Analysis of real set formal contexts is a generalization of classical formal contexts. By dividing the attributes into condition attributes and decision attributes, the notion of real decision formal contexts is introduced. Based on an implication mapping, problems of rule acquisition and attribute reduction of real decision formal contexts are examined. The extraction of “if–then” rules from the real decision formal contexts, and the approach to attribute reduction of the real decision formal contexts are discussed. By the proposed approach, attributes which are non-essential to the maximal s rules or l rules (to be defined later in the text) can be removed. Furthermore, discernibility matrices and discernibility functions for computing the attribute reducts of the real decision formal contexts are constructed to determine all attribute reducts of the real set formal contexts without affecting the results of the acquired maximal s rules or l rules.     

Data race: tame the beast

Data races hamper parallel programming and threaten the reliability of future software. This paper proposes the data race prevention scheme View-Oriented Data race Prevention (VODAP), which can prevent data races in the View-Oriented Parallel Programming (VOPP) model. VOPP is a novel shared-memory data-centric parallel programming model, which uses views to bundle mutual exclusion with data access. We have implemented the data race prevention scheme with a memory protection mechanism. Experimental results show that the extra overhead of memory protection is trivial in our applications. The performance is evaluated and compared with modern programming models such as OpenMP and Cilk.     

Access and service convergence over the mobile internet – A survey

Next generation heterogeneous wireless networks are expected to interwork with Internet Protocol (IP)-based infrastructures. Conventional network services operate like silos in that a specific set of services are offered over a specific type of access network. It is desirable for users to be able to roam between fixed and mobile networks that employ different access technologies. Therefore, mobility management with quality of service (QoS) support is of particular importance and one of the driving forces of convergence. Since service providers often provide more than one service to their subscribers, it is important to facilitate convergence of network charging architecture through a common charging framework. One of the main issues of IP-based convergence is security and privacy. This requires coordination of different security policies in diverse networks that have different security levels and capabilities. The business case for migration to an IP-based platform motivates operators to deliver more powerful services for customers as well as a better user experience. This paper provides an overview of converged mobile Internet architectures and their implications on QoS, charging/billing and security, as well as emerging business models for telecommunication services.     

Kernel Width Optimization for Faulty RBF Neural Networks with Multi-node Open Fault

Many researches have been devoted to select the kernel parameters, including the centers, kernel width and weights, for fault-free radial basis function (RBF) neural networks. However, most are concerned with the centers and weights identification, and fewer focus on the kernel width selection. Moreover, to our knowledge, almost no literature has proposed the effective and applied method to select the optimal kernel width for faulty RBF neural networks. As is known that the node faults inevitably take place in real applications, which results in a great many of faulty networks, it will take a lot of time to calculate the mean prediction error (MPE) for the traditional method, i.e., the test set method. Thus, the letter derives a formula to estimate the MPE of each candidate width value and then use it to select the optimal one with the lowest MPE value for faulty RBF neural networks with multi-node open fault. Simulation results show that the chosen optimal kernel width by our proposed MPE formula is very close to the actual one by the conventional method. Moreover, our proposed MPE formula outperforms other selection methods used for fault-free neural networks.     

A Monte Carlo Simulation approach for the modeling of free-molecule squeeze-film damping of flexible microresonators

Squeeze-film damping on microresonators is a significant damping source even when the surrounding gas is highly rarefied. This article presents a general modeling approach based on Monte Carlo (MC) simulations for the prediction of squeeze-film damping on resonators in the free-molecule regime. The generality of the approach is demonstrated in its capability of simulating resonators of any shape and with any accommodation coefficient. The approach is validated using both the analytical results of the free-space damping and the experimental data of the squeeze-film damping on a clamped–clamped plate resonator oscillating at its first flexure mode. The effect of oscillation modes on the quality factor of the resonator has also been studied and semi-analytical approximate models for the squeeze-film damping with diffuse collisions have been developed.     

On the security of a visual cryptography scheme for color images

Hou [Visual cryptography for color images, Pattern Recognition 36 (2003) 1619-1629] proposed a four-share visual cryptography scheme for color images. The scheme splits a dithered eight-color secret image into four shares: the black mask and other three shares. It was claimed that without knowing the black mask, no information about the secret image can be obtained even if all the other three shares are known. In this paper, we show that this may be true for a few specific two-color secret images only. In all other cases, however, security cannot be guaranteed. We show that an attacker can compromise a randomly chosen two-color secret image from any two of the other three shares with probability by completely recovering the shape and pattern of the secret image. The advantage will increase to if all the three shares are known. If the secret image has three or four colors, we show that the attacker can compromise it with probability and , respectively. Finally, we show that our technique can be extended to compromising secret images with more than four colors.