MemSafe: ensuring the spatial and temporal memory safety of C at runtime

Memory access violations are a leading source of unreliability in C programs. As evidence of this problem, a variety of methods exist that retrofit C with software checks to detect memory errors at runtime. However, these methods generally suffer from one or more drawbacks including the inability to detect all errors, the use of incompatible metadata, the need for manual code modifications, and high runtime overheads. This paper presents a compiler analysis and transformation for ensuring the memory safety of C called MemSafe. MemSafe makes several novel contributions that improve upon previous work and lower the cost of safety. These include (i) a method for modeling temporal errors as spatial errors, (ii) a metadata representation that combines features of both object‐based and pointer‐based approaches, and (iii) a dataflow representation that simplifies optimizations for removing unneeded checks. MemSafe is capable of detecting real errors with lower overheads than previous efforts. Experimental results show that MemSafe detects all memory errors in six programs with known violations as well as two large and widely used open source applications. Finally, MemSafe ensures complete safety with an average overhead of 88% on 30 programs commonly used for evaluating the performance of error detection tools. Copyright © 2012 John Wiley & Sons, Ltd.     

A sinusoidal family of unitary transforms

A new family of unitary transforms is introduced. It is shown that the well-known discrete Fourier, cosine, sine, and the Karhunen-Loeve (KL) (for first-order stationary Markov processes) transforms are members of this family. All the member transforms of this family are sinusoidal sequences that are asymptotically equivalent. For finite-length data, these transforms provide different approximations to the KL transform of the said data. From the theory of these transforms some well-known facts about orthogonal transforms are easily explained and some widely misunderstood concepts are brought to light. For example, the near-optimal behavior of the even discrete cosine transform to the KL transform of first-order Markov processes is explained and, at the same time, it is shown that this transform is not always such a good (or near-optimal) approximation to the above-mentioned KL transform. It is also shown that each member of the sinusoidal family is the KL transform of a unique, first-order, non-stationary (in general), Markov process. Asymptotic equivalence and other interesting properties of these transforms can be studied by analyzing the underlying Markov processes.     

A thermogravimetric study of the oxidation of CuFeO2

The oxidation kinetics of CuFeO₂ have been studied between 500 and 1000° C under various oxygen partial pressures using thermogravimetric analysis (TGA). The oxidation rate was found to increase as the oxygen partial pressure was increased, and for a given partial pressure of oxygen it was found to be maximum at 700° C. The enthalpy and activation energy for the oxidation of CuFeO₂ were calculated to be 26.6±2 and 18±2 kcal mol^–1 respectively. The oxidation of CuFeO₂ resulted in the formation of CuFe₂O₄ and CuO, and the rate of reaction followed an S-type curve as found in the pearlitic transformation in steels.     

Ecofriendly approach for detection of phenols in water using laccase from different fungi

Laccase-initiated oxidative coupling reactions of phenol and its derivatives with 4-aminoantipyrene using air as an oxidant has been investigated. The oxidation reaction of phenols and 4-aminoantipyrene is getting a lot of attention due to environmental concerns. Oxidation of simple phenol and 4-aminoantipyrene as a benchmark reaction enabled us to rank the relative oxidation ability of various laccases. Among the laccases tested, laccase from Pycnoporus cinnabarinus successfully yielded 72% antipyrilquinoneimine dye. The present method can also be used to determine p-substituted phenols and chlorophenols. In this work, the influence of mediators on laccase activity has also been studied.     

Altered fingerprints: analysis and detection

The widespread deployment of Automated Fingerprint Identification Systems (AFIS) in law enforcement and border control applications has heightened the need for ensuring that these systems are not compromised. While several issues related to fingerprint system security have been investigated, including the use of fake fingerprints for masquerading identity, the problem of fingerprint alteration or obfuscation has received very little attention. Fingerprint obfuscation refers to the deliberate alteration of the fingerprint pattern by an individual for the purpose of masking his identity. Several cases of fingerprint obfuscation have been reported in the press. Fingerprint image quality assessment software (e.g., NFIQ) cannot always detect altered fingerprints since the implicit image quality due to alteration may not change significantly. The main contributions of this paper are: 1) compiling case studies of incidents where individuals were found to have altered their fingerprints for circumventing AFIS, 2) investigating the impact of fingerprint alteration on the accuracy of a commercial fingerprint matcher, 3) classifying the alterations into three major categories and suggesting possible countermeasures, 4) developing a technique to automatically detect altered fingerprints based on analyzing orientation field and minutiae distribution, and 5) evaluating the proposed technique and the NFIQ algorithm on a large database of altered fingerprints provided by a law enforcement agency. Experimental results show the feasibility of the proposed approach in detecting altered fingerprints and highlight the need to further pursue this problem.     

Enhancing electronic medical record retrieval through semantic query expansion

There are currently many active movements towards computerizing patient healthcare information. As Electronic Medical Record (EMR) systems are being increasingly adopted in healthcare facilities, however, there is a big challenge in effectively utilizing this massive information source. It is very time-consuming for healthcare providers to dig into the voluminous medical records of a patient to find the few that are indeed relevant to the patient’s current problem. Due to the complex semantic relationships among medical concepts and use of many synonyms, antonyms, and hypernym/hyponym, simple word-based information retrieval does not produce satisfactory results. In this paper, we propose an EMR retrieval system that leverages semantic query expansion to retrieve medical records that are relevant to the patient’s current symptom/problem. The proposed framework integrates various technologies, including information retrieval, domain ontologies, automatic semantic relationship learning, as well as a body of domain knowledge elicited from healthcare experts. Knowledge of semantic relationships among medical concepts, such as symptoms, exams and tests, diagnoses, and treatments, as well as knowledge of synonyms and hypernym/hyponyms, is used to expand and enhance initial queries posed by a user. We have implemented a preliminary prototype and conducted a pilot testing using sample nursing notes drawn from the EMR system of a community health center.     

面向驾驶员的个性化健康导航

为了减少因驾驶员的生理和心理健康状况变化引发的交通事故,实现对驾驶员健康状态的自动监测和实时优化,提出以控制论的基本理论为基础的驾驶员健康状态闭环反馈系统框架.首先基于驾驶员日志建立个性化健康模型;然后结合各种传感器实时采集的驾驶员、车辆和道路环境等多模态数据,对驾驶员当前健康状态进行估计;最后针对预设健康目标,为驾驶员提供可执行的行为建议,实现对驾驶员健康状态的导航优化.在最关键的实时监测环节,提出基于注意力的卷积神经网络(convolutional neural network,CNN)-长短期记忆网络(long short term memory,LSTM)的多模态融合模型,实现对驾驶员压力、情绪和疲劳3个方面的健康状态估计.在私有数据集和公开数据集上分别开展的实验验证均获得高于90％的检测准确率.实验结果表明,提出的模型和方法可以实时准确监测驾驶员的压力、情绪和疲劳状态,为实现驾驶员的个性化健康导航系统提供有力支撑.     

General Health in Organizations: Relative Relevance of Emotional Intelligence, Trust, and Organizational Support.

This study examined the predictive ability of emotional intelligence (EI), trust, and organizational support in general health. The sample consisted of 250 middle-level executives from 2-wheeler manufacturing organizations. Results suggest that the dimension of EI termed positive attitude about life predicted both factors of general health positively: (a) sense of accomplishment and contribution and (b) botheration-free existence. Organizational support predicted sense of accomplishment and contribution, whereas vertical trust predicted botheration-free existence, accompanied by the assertiveness and positive self-concept dimension of EI. The implications of the results are discussed in terms of promoting the general health of employees through training on EI skills and through the creation of an atmosphere of trust and recognition within the organization. (PsycINFO Database Record (c) 2010 APA, all rights reserved)