17431951
Analyzing Performance of Web-Based Metrics for Evaluating Reliability and Maintainability of Hypermedia Applications
This paper has been designed to identify the Web metrics for evaluating the reliability and maintainability of hypermedia applications. In the age of information and communication technology (ICT), Web and the Internet, have brought significant changes in information technology (IT) and their related scenarios. Therefore in this paper an attempt has been made to trace out the Web-based measurements towards the creation of efficient Web centric applications. The dramatic increase in Web site development and their relative usage has led to the need of Web-based metrics. These metrics will accurately assess the efforts in the Web-based applications. Here we promote the simple, but elegant approaches to estimate the efforts needed for designing Web-based applications with the help of user behavior model graph (UBMG), Web page replacement algorithms, and RS Web Application Effort Assessment (RSWAEA) method. Effort assessment of hyperdocuments is crucial for Web-based systems, where outages can result in loss of revenue and dissatisfied customers. Here we advocate a simple, but elegant approach for effort estimation for Web applications from an empirical point of view. The proposed methods and models have been designed after carrying out an empirical study with the students of an advanced university class and Web designers that used various client-server based Web technologies. Our first aim was to compare the relative importance of each Web-based metric and method. Second, we also implemented the quality of the designs obtained based by constructing the User Behavior Model Graphs (UBMGs) to capture the reliability of Web-based applications. Thirdly, we use Web page replacement algorithms for increasing the Web site usability index, maintainability, reliability, and ranking. The results obtained from the above Web-based metrics can help us to analytically identify the effort assessment and failure points in Web-based systems and makes the evaluation of reliability of these systems simple.
15134584
Replication of Biomolecular Techniques for Implementing Intelligent Systems
In this paper, it has been shown that computational jobs, such as encoding of input data and AND, OR operation, can work on the computers (by using computer databases and algorithms for the purpose of speeding up and enhancing biological research). By combining more complex functions, more complex molecular programs for gene analysis can be constructed. It is expected an in vivo (i.e. inside cellular life forms) computer will be realized from this technology, which detects the cell state through gene expression patterns, and controls the cell conditions with output RNA (ribose nucleic acid). The replication of biomolecular techniques based upon DNA (deoxyribose nucleic acid) architecture has been proposed. It may provide a powerful tool for both research and clinical applications. To develop functional supra-molecular systems, where sequence-programmable and evolvable molecular systems have been constructed as cell-free chemical systems using biomolecules such as DNA and proteins based on the integration of electronics, computer science, IT (information technology), mathematical and statistical tools. This paper is organised into four parts: part I describes the functioning and encoding processes of DNA computers, which are implemented using a traveling salesman problem (as in artificial intelligent systems) and single shortest path routing approach (as in computer networks) using object-oriented approach of software development, part II presents database integration with DNA using client-server technologies of Web design, part III discusses the implications of DNA for computer and network security, and part IV investigates and shows the results with the use of above mentioned approaches.
205912378
The architecture of Efficient Multi-Core Processors: A Holistic Approach
Abstract The most straightforward methodology for designing a multi-core architecture is to replicate an off-the-shelf core design multiple times, and then connect the cores together using an interconnect mechanism. However, this methodology is “multi-core oblivious” as subsystems are designed/optimized unaware of the overall chip-multiprocessing system they would become parts of. The chapter demonstrates that this methodology is inefficient in terms of area/power. It recommends a holistic approach where the subsystems are designed from the ground up to be effective components of a complete system. The inefficiency in “multi-core oblivious” designs comes from many sources. Having multiple replicated cores results in an inability to adapt to the demands of execution workloads, and results in either underutilization or overutilization of processor resources. Single-ISA (instruction-set architecture) heterogeneous multi-core architectures host cores of varying power/performance characteristics on the die, but all cores are capable of running the same ISA. Such a processor can result in significant power savings and performance improvements if the applications are mapped to cores judiciously. The paper also presents holistic design methodologies for such architectures. Another source of inefficiency is blind replication of over-provisioned hardware structures. Conjoined-core chip multiprocessing allows adjacent cores of a multi-core architecture to share some resources. This can result in significant area savings with little performance degradation. Yet another source of inefficiency is the interconnect. The interconnection overheads can be very significant for a “multi-core oblivious” multi-core design—especially as the number of cores increases and the pipelines get deeper. The paper demonstrates the need to co-design the cores, the memory and the interconnection to address the inefficiency problem, and also makes several suggestions regarding co-design.
62589113
Linear model hashing and batch RANSAC for rapid and accurate object recognition
This paper proposes a joint feature-based model indexing and geometric constraint based alignment pipeline for efficient and accurate recognition of 3D objects from a large model database. Traditional approaches either first prune the model database using indexing without geometric alignment or directly perform recognition based alignment. The indexing based pruning methods without geometric constraints can miss the correct models under imperfections such as noise, clutter and obscurations. Alignment based verification methods have to linearly verify each model in the database and hence do not scale up. The proposed techniques use spin images as semi-local shape descriptors and locality-sensitive hashing (LSH) to index into a joint spin image database for all the models. The indexed models represented in the pruned set are further pruned using progressively complex geometric constraints. A simple geometric configuration of multiple spin images, for instance a doublet, is first used to check for geometric consistency. Subsequently, full Euclidean geometric constraints are applied using RANSAC-based techniques on the pruned spin images and the models to verify specific object identity. As a result, the combined indexing and geometric alignment based pipeline is able to focus on matching the most promising models, and generate far less pose hypotheses while maintaining the same level of performance as the sequential alignment based recognition. Furthermore, compared to geometric indexing techniques like geometric hashing, the construction time and storage complexity for the proposed technique remains linear in the number of features rather than higher order polynomial. Experiments on a 56 3D model database show promising results.
26613232
Learning Actions Using Robust String Kernels
This paper presents an action analysis method based on robust string matching using dynamic programming. Similar to matching text sequences, atomic actions based on semantic and structural features are first detected and coded as spatio-temporal characters or symbols. These symbols are subsequently concatenated to form a unique set of strings for each action. A similarity metric using longest common subsequence algorithm is employed to robustly match action strings with variable length. A dynamic programming method with polynomial computational complexity and linear space complexity is implemented. An effective learning scheme based on similarity metric embedding is developed to deal with matching strings of variable length. Our proposed method works with limited amount of training data and exhibits desirable generalization property. Moreover, it can be naturally extended to detect compound behaviors and events. Experimental evaluation on our own and a commonly used data set demonstrates that our method allows for large pose and appearance changes, is robust to background clutter, and can accommodate spatio-temporal behavior variations amongst different subjects while achieving high discriminability between different behaviors.
46163853
Enhancement of adhesion strength of Cu layer with low dielectric constant SiC: H liners in Cu interconnects
Abstract One of the primary candidates for the liner/etch stop layer in damascene process is silicon nitride (Si 3 N 4 ). However, silicon nitride has a high dielectric constant of 7.0. To reduce the effective dielectric constant in Copper (Cu) damascene structure, dielectric SiC:H (prepared by plasma enhanced chemical vapor deposition (PECVD) using trimethylsilane source) as the Cu diffusion barrier was studied. The dielectric constant of SiC:H used is 4.2. A systematic study was made on the properties of liner material and electro-chemically plated (ECP) Cu to enhance the adhesion strength in Cu/low-dielectric constant ( k ) multilevel interconnects. Though the effects of as Si 3 N 4 the liner have been much studied in the past, less is known about the relation between adhesion strength of ECP Cu layer and physical vapor deposited (PVD) Cu seeds, with seed thickness below 1000 A. The annealing of Cu seed layer was carried out at 200 °C in N 2 ambient for 30 min was carried out to study the impact on adhesion strength and the microstructure evolution on the adhesion between ECP Cu and its barrier layer. In the study, our claim that SiC:H barrier/etch stop layer is essential for replacing conventional Si 3 N 4 layer in enhancing adhesion strength and interfacial bonding between Cu/dielectric interconnects.
5884426
Validation of an optical flow method for tag displacement estimation
Presents a validation study of an optical-flow method for the rapid estimation of myocardial displacement in magnetic resonance tagged cardiac images. This registration and change visualization (RCV) software uses a hierarchical estimation technique to compute the flow field that describes the warping of an image of one cardiac phase into alignment with the next. This method overcomes the requirement of constant pixel intensity in standard optical-flow methods by preprocessing the input images to reduce any intensity bias which results from the reduction in stripe contrast throughout the cardiac cycle. To validate the method, SPAMM-tagged images were acquired of a silicon gel phantom with simulated rotational motion. The pixel displacement was estimated with the RCV method and the error in pixel tracking was <4% 1000 ms after application of the tags, and after 30/spl deg/ of rotation. An additional study was performed using a SPAMM-tagged multiphase slice of a canine left ventricle. The true displacement was determined using a previously validated active contour model (snakes). The error between methods was 6.7% at end systole. The RCV method has the advantage of tracking all pixels in the image in a substantially shorter period than the snakes method.