Theorem Proving Guided Development of Formal Assertions in a Resource-Constrained Scheduler for High-Level Synthesis

This paper presents a formal specification and a proof of correctness for the widely-used Force-Directed List Scheduling (FDLS) algorithm for resource-constrained scheduling of data flow graphs in high-level synthesis systems. The proof effort is conducted using a higher-order logic theorem prover. During the proof effort many interesting properties of the FDLS algorithm are discovered. These properties are formally stated and proved in a higher-order logic theorem proving environment. These properties constitute a detailed set of formal assertions and invariants that should hold at various steps in the FDLS algorithm. They are then inserted as programming assertions in the implementation of the FDLS algorithm in a production-strength high-level synthesis system. When turned on, the programming assertions (1) certify whether a specific run of the FDLS algorithm produced correct schedules and, (2) in the event of failure, help discover and isolate programming errors in the FDLS implementation.We present a detailed example and several experiments to demonstrate the effectiveness of these assertions in discovering and isolating errors. Based on this experience, we discuss the role of the formal theorem proving exercise in developing a useful set of assertions for embedding in the scheduler code and argue that in the absence of such a formal proof checking effort, discovering such a useful set of assertions would have been an arduous if not impossible task.     

Quality aspects for component‐based systems: A metrics based approach

In component‐based development, software systems are built by assembling components already developed and prepared for integration. To estimate the quality of components, complexity, reusability, dependability, and maintainability are the key aspects. The quality of an individual component influences the quality of the overall system. Therefore, there is a strong need to select the best quality component, both from functional and nonfunctional aspects. The present paper produces a critical analysis of metrics for various quality aspects for components and component‐based systems. These aspects include four main quality factors: complexity, dependency, reusability, and maintainability. A systematic study is applied to find as much literature as possible. A total of 49 papers were found suitable after a defined search criteria. The analysis provided in this paper has a different objective as we focused on efficiency and practical ability of the proposed approach in the selected papers. The various key attributes from these two are defined. Each paper is evaluated based on the various key parameters viz. metrics definition, implementation technique, validation, usability, data source, comparative analysis, practicability, and extendibility. The paper critically examines various quality aspects and their metrics for component‐based systems. In some papers, authors have also compared the results with other techniques. For characteristics like complexity and dependency, most of the proposed metrics are analytical. Soft computing and evolutionary approaches are either not being used or much less explored so far for these aspects, which may be the future concern for the researchers. In addition, hybrid approaches like neuro‐fuzzy, neuro‐genetic, etc., may also be examined for evaluation of these aspects. However, to conclude that one particular technique is better than others may not be appropriate. It may be true for one characteristic by considering different set of inputs and dataset but may not be true for the same with different inputs. The intension in the proposed work is to give a score for each metric proposed by the researchers based on the selected parameters, but certainly not to criticize any research contribution by authors. Copyright © 2012 John Wiley & Sons, Ltd.     

A multi-step linearization technique for a class of boundary value problems in non-linear mechanics

Non-linear finite element analyses of structures (such as beams) involve construction of weak solutions for the governing equations. While a weak approach weakens the differentiability requirements of the so-called shape functions, the governing equations are only satisfied in an integral sense and not point-wise, or, even path-wise. Moreover, use of a finite mesh leads to a stiffening of the numerical model. While strong solutions obtained through some of the existing mesh-free collocation methods overcomes some of these lacunae to an extent, the quality of the numerical solutions would be considerably improved if the computational algorithm were able to faithfully reproduce (or approximate or preserve) certain geometrical features of the response surfaces or manifolds. This paper takes the first step towards realizing this objective and proposes a multi-step transversal linearization (MTL) technique for a class of non-linear boundary value problems, which are treated as conditionally dynamical systems. Numerical explorations are performed, to a limited extent, through applications to large deflection analyses of planar beams with or without plastic deformations.     

Nanoclays for polymer nanocomposites, paints, inks, greases and cosmetics formulations, drug delivery vehicle and waste water treatment

An overview of nanoclays or organically modified layered silicates (organoclays) is presented with emphasis placed on the use of nanoclays as the reinforcement phase in polymer matrices for preparation of polymer/layered silicates nanocomposites, rheological modifier for paints, inks and greases, drug delivery vehicle for controlled release of therapeutic agents, and nanoclays for industrial waste water as well as potable water treatment to make further step into green environment. A little amount of nanoclay can alter the entire properties of polymers, paints, inks and greases to a great extent by dispersing 1nm thick layered silicate throughout the matrices. The flexibility of interlayer spacing of layered silicates accommodates therapeutic agents which can later on be released to damaged cell. Because the release of drugs in drug-intercalated layered materials is controllable, these new materials have a great potential as a delivery host in the pharmaceutical field. The problem of clean water can be solved by treating industrial and municipal waste water with organoclays in combination with other sorbents like activated carbon and alum. Organoclays have proven to be superior to any other water treatment technology in applications where the water to be treated contains substantial amounts of oil and grease or humic acid.     

Multidroplet Impact Model for Prediction of Residual Stresses in Water Jet Peening of Materials

In this article, a multidroplet impact model, proposed for predicting residual stresses induced on materials subjected to water jet peening, is presented. This approach considers the impact pressure distribution due to high-velocity droplets impinging on the material surface instead of stationary pressure distribution for prediction of residual stresses on water jet-peened surfaces. It makes use of Reichardt's theory for predicting the velocity distribution of droplets and liquid impact theory for predicting the impact pressure and duration of impact of high-velocity droplets. For predicting residual stresses on the surface and subsurface of material subjected to water jet peening, finite element modeling approach was adopted by using transient elastoplastic finite element analysis by considering an impingement of a set of droplets in succession to one another over a certain time period after which this pressure is released. The effectiveness of the proposed approach was demonstrated bv comparing the predicted residual stresses with those predicted by using the single set of droplets approach proposed by Rajesh et al. [6]. Finally, the practical relevance of the proposed approach was shown by comparing the predicted results with the experimental results obtained by water peening of 6063-T6 aluminium alloy.     

Efficient clustering algorithms for self-organizing wireless sensor networks

Self-organization of wireless sensor networks, which involves network decomposition into connected clusters, is a challenging task because of the limited bandwidth and energy resources available in these networks. In this paper, we make contributions towards improving the efficiency of self-organization in wireless sensor networks. We first present a novel approach for message-efficient clustering, in which nodes allocate local “growth budgets” to neighbors. We introduce two algorithms that make use of this approach. We analyze the message complexity of these algorithms and provide performance results from simulations. The algorithms produce clusters of bounded size and low diameter, using significantly fewer messages than the earlier, commonly used, Expanding Ring approach. Next, we present a new randomized methodology for designing the timers of cluster initiators. This methodology provides a probabilistic guarantee that initiators will not interfere with each other. We derive an upper bound on the expected time for network decomposition that is logarithmic in the number of nodes in the network. We also present a variant that optimistically allows more concurrency among initiators and significantly reduces the network decomposition time. However, it produces slightly more clusters than the first method. Extensive simulations over different topologies confirm the analytical results and demonstrate that our proposed methodology scales to large networks.     

Instrumental Learning Within the Rat Spinal Cord: Localization of the Essential Neural Circuit.

Following spinal transection of the upper thoracic spinal cord, male Sprague-Dawley rats given legshock whenever a hindlimb is extended learn to maintain the leg in a flexed position. The region of the cord that mediates this instrumental learning was isolated using neuroanatomical tracing, localized infusion of lidocaine, and surgical transections. DiI and Fluoro-Gold microinjection at the site of shock application labeled motor neuron bodies of lamina IX in the lower lumbar region. Local application of the Na++ channel blocker lidocaine disrupted learning when it was applied over a region extending from the lower lumbar (L3) to upper sacral (S2) cord. The drug had no effect rostral or caudal to this region. Surgical transections as low as L4 had no effect on learning. Learning also survived a dual transection at L4 and S3, but not L4 and S2. The results suggest that the essential neural circuit lies between L4 and S3. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Lessons and Challenges from Mining Retail E-Commerce Data

The architecture of Blue Martini Software's e-commerce suite has supported data collection, data transformation, and data mining since its inception. With clickstreams being collected at the application-server layer, high-level events being logged, and data automatically transformed into a data warehouse using meta-data, common problems plaguing data mining using weblogs (e.g., sessionization and conflating multi-sourced data) were obviated, thus allowing us to concentrate on actual data mining goals. The paper briefly reviews the architecture and discusses many lessons learned over the last four years and the challenges that still need to be addressed. The lessons and challenges are presented across two dimensions: business-level vs. technical, and throughout the data mining lifecycle stages of data collection, data warehouse construction, business intelligence, and deployment. The lessons and challenges are also widely applicable to data mining domains outside retail e-commerce.     

First and second law investigations of a new solar‐assisted thermodynamic cycle for triple effect refrigeration

This investigation is persuaded for the first and second law analyses of a new solar‐driven triple‐effect refrigeration cycle using Duratherm 600 oil (Duratherm Extended Life Fluid, NY, USA) as the heat transfer fluid is performed. The proposed cycle is an integration of ejector, absorption, and cascaded refrigeration cycles that could produce refrigeration output of different magnitude at different temperature simultaneously. Both exergy destruction and losses in each component and hence in the overall system are determined to identify the causes and locations of the thermodynamic imperfection. The effects of some influenced parameters such as hot oil outlet temperature, refrigerant turbine inlet pressure, and the evaporator temperature of ejector and cascaded refrigeration cycle have been observed on the first and second law performances. It is found that maximum irreversibility occurs in central receiver as 52.5% and the second largest irreversibility of 25% occurs in heliostat field. The second law efficiency of the solar driven triple effect refrigeration cycle is 2%, which is much lower than its first law efficiency of 11.5%. Analysis clearly shows that performance evaluation based on the first law analysis is inadequate and hence, more meaningful evaluation must be included in the second law analysis. Copyright © 2013 John Wiley & Sons, Ltd.