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Byline: Rishu. Bansal, Sushant. Bhuyan, Rajiv. Gupta, Arun. Garg, Atma. Bansal The introduction of air into cerebral venous or arterial circulation known as cerebral air embolism (CAE) is a rare [...]

By studying the behavior of several programs that crash due to memory errors, we observed that locating the errors can be challenging because significant propagation of corrupt memory values can occur prior to the point of the crash. In this article, we present an automated approach for locating memory errors in the presence of memory corruption propagation. Our approach leverages the information revealed by a program crash: when a crash occurs, this reveals a subset of the memory corruption that exists in the execution. By suppressing (nullifying) the effect of this known corruption during execution, the crash is avoided and any remaining (hidden) corruption may then be exposed by subsequent crashes. The newly exposed corruption can then be suppressed in turn. By iterating this process until no further crashes occur, the first point of memory corruption--and the likely root cause of the program failure--can be identified. However, this iterative approach may terminate prematurely, since programs may not crash even when memory corruption is present during execution. To address this, we show how crashes can be exposed in an execution by manipulating the relative ordering of particular variables within memory. By revealing crashes through this variable re-ordering, the effectiveness and applicability of the execution suppression approach can be improved. We describe a set of experiments illustrating the effectiveness of our approach in consistently and precisely identifying the first points of memory corruption in executions that fail due to memory errors. We also discuss a baseline software implementation of execution suppression that incurs an average overhead of 7.2x, and describe how to reduce this overhead to 1.8x through hardware support. Categories and Subject Descriptors: D.2.4 [Software Engineering]: Software/Program Verification--Reliability; D.2.5 [Software Engineering]: Testing and Debugging--Debugging aids; D.3.4 [Programming Languages]: Processors--Debuggers General Terms: Algorithms, Experimentation, Performance, Reliability, Verification Additional Key Words and Phrases: Execution suppression, fault localization, hardware support, memory corruption propagation, memory errors, variable re-ordering DOI = 10.1145/1745312.1745314

Byline: Ketankumar. Rupala, Varun. Mittal, Rajiv. Gupta, Rajiv. Yadav Pheochromocytoma has atypical presentation in 9%–10% of patients. Atypical presentations include myocardial infarction, renal failure, and rarely cerebrovascular events. Various etiologies [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jss.2006.06.007 Byline: Yongjing Lin (a), Youtao Zhang (b), Rajiv Gupta (c) Keywords: Path matching; Sequitur compression; Control flow trace Abstract: A control flow trace captures the complete sequence of dynamically executed basic blocks and function calls. It is usually of very large size and therefore commonly stored in compressed format. On the other hand, control flow traces are frequently queried to assist program analysis and optimization, e.g. finding frequently executed subpaths that may be optimized. In this paper, we identify path interruption and path context problems in querying an intraprocedural path over control flow traces. While algorithms that perform pattern matching on compressed strings have been proposed, solving new challenges requires the extension of traditional algorithms. We design and evaluate four path matching schemes including those that match in the compressed data directly and those that match after decompression. In addition, simple indices are also designed to improve matching performance. Our experimental results show that these schemes are practical and can be adapted to environments with different hardware settings and path matching requests. Author Affiliation: (a) Computer Science Department, University of Texas at Dallas, Richardson, TX 75083, United States (b) Computer Science Department, University of Pittsburgh, Pittsburgh, PA 15260, United States (c) Computer Science Department, University of Arizona, Tucson, AZ 85721, United States Article History: Received 23 May 2005; Revised 23 May 2006; Accepted 2 June 2006

Over the years, many methods have been developed to predict the concrete strength. In recent years, artificial neural networks (ANNs) have been applied to many civil engineering problems with some degree of success. In the present paper, ANN is used as an attempt to obtain more accurate concrete strength prediction based on parameters like concrete mix design, size and shape of specimen, curing technique and period, environmental conditions, etc. A total of 864 concrete specimens were cast for compressive strength measurement and verification through the ANN model. The back propagation-learning algorithm is employed to train the network for extracting knowledge from training examples. The predicted strengths found by employing ANN are compared with the actual values. The results indicate that ANN is a useful technique for predicting the concrete strength. Further, an effort to build an expert system for the problem is described in this paper. To overcome the bottleneck of intricate knowledge acquisition, an expert system is used as a mechanism to transfer engineering experience into usable knowledge through rule-based knowledge representation techniques. CE Database subject headings: Concrete; Neural networks; Expert systems; Algorithms; Artificial intelligence; Compressive strength.

Energy conservation inside the buildings is of utmost importance. To reduce the heating and cooling loads inside the energy-efficient buildings, solar entry regulation as per season can be attained with the use of specific sunshades. Although various static sunshades have been developed depending upon solar geometry, the efficiency with respect to control of solar entry inside the building is a major concern over the seasonal classification for a particular geographic location. The proposed work aims at the design development of a new static sunshade depending on solar angles, whose efficiency has been experimentally verified using a small-scale modeling technique. Three experimental models of insulating material were prepared with varying aspect ratio of windows and static sunshades. Sunlit area, which in turn controls the temperature inside the models, has been made the criteria for deciding the effectiveness of the proposed sunshade over existing horizontal sunshade. The proposed technique can be applied at any geographic location over the world for which sunshade can be designed as per the climatic requirements of the place. CE Database subject headings: Energy conservation; Buildings; Temperature; Cooling.

Dynamic slicing algorithms are used to narrow the attention of the user or an algorithm to a relevant subset of executed program statements. Although dynamic slicing was first introduced to aid in user level debugging, increasingly applications aimed at improving software quality, reliability, security, and performance are finding opportunities to make automated use of dynamic slicing. In this paper we present the design and evaluation of three precise dynamic data slicing algorithms called the full preprocessing (FP), no preprocessing (NP) and limited preprocessing (LP) algorithms. The algorithms differ in the relative timing of constructing the dynamic data dependence graph and its traversal for computing requested dynamic data slices. Our experiments show that the LP algorithm is a fast and practical precise data slicing algorithm. In fact we show that while precise data slices can be orders of magnitude smaller than imprecise dynamic data slices, for small number of data slicing requests, the LP algorithm is faster than an imprecise dynamic data slicing algorithm proposed by Agrawal and Horgan. Categories and Subject Descriptors: D.3.4 [Programming Languages]: Processors--Debuggers; D.2.5 [Software Engineering]: Testing and Debugging--Debugging aids, testing tools, tracing General Terms: Algorithms, Measurement, Performance Additional Key Words and Phrases: Program slicing, data dependences, pointer references, debugging

Technological and industrial developmental project activities disturb the natural ecosystem and have multiple direct and indirect environmental consequences. The disposal of waste material, being a prominent activity that accompanies any industrial development, is a problem of ever-increasing concern. Therefore it is of immense importance to establish appropriate sites for waste disposal facilities such as landfills. To select an appropriate landfill site with minimal environmental damage, an environmental impact assessment (EIA) is necessary. Available methods to carry out an EIA are insufficient for cumulative assessment and inappropriate to make the final decision regarding the selection of a landfilling site, nor do they take uncertainty and future impacts into account. The present work implements fuzzy logic, which takes uncertainty into account in assessing the environmental impact of landfill siting and considers future impacts in terms of frequency of occurrence. A new approach that considers numeric values of the weights in terms of fuzzy membership is examined, the potential applicability of the method is tested, and results are compared with those of other common existing methods. DOI: 10.1061/(ASCE)0733-9488(2003)129:3(121) CE Database subject headings: Environmental impacts; Landfills; Fuzzy sets; Uncertainty.

Compiler algorithms that accommodate compiled applications in multitasking environments are examined. It is assumed that the underlying network is an all-optical Time-Division Multiplexing (TDM) network.

Linear graph theory used for pipe network analysis is to make the method systematic. A numerical method that uses linear graph theory is presented for the steady-state analysis of flow and pressure in a pipe network including its hydraulic components (pumps, valves, junctions, etc.). The proposed method differs from other linear graph methods in terms of the linear graph and the selection of its tree. The solution algorithm uses a function that depends on a power law to update the pipe flows in successive iterations. The exponents of this function are chosen to obtain a fast convergence rate even for large errors in the assumption of initial pipe flows. The convergence rate of the proposed method is validated using an error function and is compared to those of other methods. Some typical networks are analyzed to check the reliability of the proposed method. The results demonstrate the superior conditioning of the proposed method.

Byline: Yeeshu. Sudan, Arun. Garg, Rajiv. Gupta, Atma. Bansal Sir, A 14-year-old boy presented with altered sensorium, slurred speech, seizures, and weakness of all four limbs for the last 2 [...]

An important challenge in industrial metrology is to provide rapid measurement of critical three-dimensional (3-D) internal object geometry for either inspecting high volume parts or controlling a machining process. Existing metrological techniques are typically too slow to meet this need or can not measure small features with high precision. In this paper, we present a new method that achieves fast, accurate, internal 3-D geometry measurement based on 3-D reconstruction from a few X-ray views of a part. Our approach utilizes an accurate camera model for the X-ray sensor, calibration using in situ ground truth and geometry-guided X-ray feature extraction to achieve this goal and has been fully implemented in a prototype 3-D measurement system. We describe a novel application of the system to CAD-based verification of drilled hole positioning. Experimental results are given to illustrate the precision of the system and 3-D measurement on real industrial parts. Index Terms - CAD-based measurement, inspection, 3-D metrology, X-ray imaging.

The high cost and growing importance of interprocedural data flow analysis have led to an increased interest in demand-driven algorithms. In this article, we present a general framework for developing […]

Modeling and analyzing pushbroom sensors commonly used in satellite imagery is difficult and computationally intensive due to the motion of an orbiting satellite with respect to the rotating earth, and the nonlinearity of the mathematical model involving orbital dynamics. In this paper, a simplified model of a pushbroom sensor (the linear-pushbroom model) is introduced. It has the advantage of computational simplicity while at the same time giving very accurate results compared with the full orbiting pushbroom model. Besides remote sensing, the linear pushbroom model is also useful in many other imaging applications. Simple noniterative methods are given for solving the major standard photogrammetric problems for the linear pushbroom model: computation of the model parameters from ground-control points; determination of relative model parameters from image correspondences between two images; and scene reconstruction given image correspondences and ground-control points. The linear pushbroom model leads to theoretical insights that are approximately valid for the full model as well. The epipolar geometry of linear pushbroom cameras in investigated and shown to be totally different from that of a perspective camera. Nevertheless, a matrix analogous to the fundamental matrix of perspective cameras is shown to exist for linear pushbroom sensors. From this it is shown that a scene is determined up to an affine transformation from two views with linear pushbroom cameras. Index Terms - Pushbroom sensor, fundamental matrix, satellite cameras, photogrammetry.

A compiler-assisted approach is developed for fault detection by utilizing the idle time slots to conduct duplicated computations in distributed-memory systems. The fault is detected by duplicating the execution of statement instances on two processors and comparing the results from these executions. A loop transformation framework is developed to transform a regular loop into duplicate computations. This approach needs no specialized hardware, checking is concurrent with execution of the programs, resulting in increased efficiency. Its implementation is automatic without users involvement.

Classical data flow problems such as reaching available and busy expressions and definitions use a novel technique to calculate rapid data flow problems in parallel. This method analyzes data flow within linear paths, independent paths and paths that occur within the loop of a control flow graph. A directed acyclic graph (DAG) characterizes this technique, which transforms a cyclic flow graph's cyclic structures to acyclic structures.

Proposed approaches for the reduction of overhead costs generated by static decomposition and self-scheduling loops are suited to most shared memory multiprocessor machines such as the Alliant FX/8 and the RP3. Methods for detecting static loop decompositions, synchronization reduction, run-time scheduling and communication costs are also proposed. Results show that performance can be influenced by overhead cost accounting in connection with parallel applications.

Byline: Reena. Singh, Neetu. Gautam, Anurag. Mishra, Rajiv. Gupta Heavy metals are natural constituents of the earth's crust, but indiscriminate human activities have drastically altered their geochemical cycles and biochemical [...]