Efficient algorithm for glitch power reduction [CMOS logiccircuits]

An efficient algorithm is proposed for reducing glitch power dissipation in CMOS logic circuits. The proposed algorithm takes a path balancing approach that is achieved using gate sizing and buffer insertion methods. The gate sizing technique reduces not only glitches but also the effective circuit capacitance. After gate sizing, buffers are inserted into the remaining unbalanced paths which have not been subjected to gate sizing. ILP has been employed to determine the location of inserted buffers. The proposed algorithm has been tested on LGSynth91 benchmark circuits. Experimental results show that 61.5% of glitches are reduced on average     

Reconstruction of dynamic 3D scene based on visual hull and view morphing

In this paper, we propose a new method that processes multiple synchronized video sequences and generates 3D rendering of dynamic objects in the video. It exploits an efficient image‐based reconstruction scheme that constructs and shades 3D models of objects from silhouette images by combining image‐based visual hull and view morphing. The proposed hybrid method improves the speed and the quality of the previous visual hull sampling methods. We designed and implemented a system based on this method which is relatively low cost and does not require any special hardware or specific environment. Copyright © 2003 John Wiley & Sons, Ltd.     

Machine Learning Identifies Robust Matrisome Markers and Regulatory Mechanisms in Cancer

The expression and regulation of matrisome genes—the ensemble of extracellular matrix, ECM, ECM-associated proteins and regulators as well as cytokines, chemokines and growth factors—is of paramount importance for many biological processes and signals within the tumor microenvironment. The availability of large and diverse multi-omics data enables mapping and understanding of the regulatory circuitry governing the tumor matrisome to an unprecedented level, though such a volume of information requires robust approaches to data analysis and integration. In this study, we show that combining Pan-Cancer expression data from The Cancer Genome Atlas (TCGA) with genomics, epigenomics and microenvironmental features from TCGA and other sources enables the identification of “landmark” matrisome genes and machine learning-based reconstruction of their regulatory networks in 74 clinical and molecular subtypes of human cancers and approx. 6700 patients. These results, enriched for prognostic genes and cross-validated markers at the protein level, unravel the role of genetic and epigenetic programs in governing the tumor matrisome and allow the prioritization of tumor-specific matrisome genes (and their regulators) for the development of novel therapeutic approaches.     

Effect of pressure and impurities on oxidation in supercritical CO2

Both indirect‐ and direct‐fired supercritical CO₂ cycles for high‐efficiency power generation are expected to have impurities that may greatly alter the compatibility of Fe‐ and Ni‐based structural alloys in these environments. Recent work has attempted to quantify reaction rates at 750°C in simulated laboratory environments with controlled impurity levels at ambient pressure, as well as under supercritical conditions (30 MPa). With low impurity levels in research and industrial‐grade CO ₂, pressure appeared to have only a limited effect on oxide thickness and internal oxidation and reaction products were similar to those formed in laboratory air. However, a direct‐fired simulation at 750°C/30 MPa in CO ₂ + 1%O ₂ + 0.25%H ₂O has found an increased mass gain and characterization after 2,500‐hr exposures have found thicker reaction products, especially for Fe‐based alloys. At these impurity levels, pressure may have a significant effect on the role of impurities.     

Gameful Experience Questionnaire (GAMEFULQUEST): an instrument for measuring the perceived gamefulness of system use

User Modeling and User-Adapted Interaction - In this paper, we present the development and validation of an instrument for measuring users’ gameful experience while using a service. Either...     

Parental worry about indoor air quality and student symptom reporting in primary schools with or without indoor air quality problems

Poor indoor air quality (IAQ) in schools is related to increased symptom reporting in students. We investigated whether parental worry about school IAQ influences this association. Data came from survey collected from five Finnish primary schools with observed IAQ problems and five control schools. Parents (n = 1868) of primary school students reported worry about IAQ in schools and symptoms of their children. Associations between observed IAQ problems, worry, and five symptom scores (ie, respiratory, lower respiratory, eye, skin, and general symptoms) were analyzed using multivariate logistic regression and mediation analysis. Parents were on average more worried in schools with observed IAQ problems. Observed IAQ problems were strongly associated with increased worry and all symptoms under study (unadjusted ORs ranged between 1.48 [95% CI 1.48‐2.16] and 2.70 [95% CI 1.52‐5.17]). Parental worry was associated with all symptoms (unadjusted ORs ranged between 2.49 [95% CI 1.75‐3.60] and 4.92 [95% CI 2.77‐9.40]). Mediation analyses suggested that parental worry might partially explain the association between observed IAQ problems and symptom reporting (proportion mediated ranged between 67% and 84% for the different symptoms). However, prospective studies are needed to assess causal relationships between observed IAQ problems, worry, and symptom reporting in schools.     

Fuzzy feed rate and cutting speed optimization in turning

There are several methods of monitoring metal cutting processes. In this study, the combination of various methods in order to define an overall “cutting state” of a turning process is discussed along with an application to use these methods for adaptive fuzzy feed rate and cutting speed optimising control. For this purpose, different methods of monitoring individual cutting phenomena such as chip length and vibration level are aggregated and the combination of this information is considered to be the cutting state of the process. Expert data has been collected from a series of experiments concerning the apparent state of these phenomena as well as required control action. An adaptive optimizing fuzzy controller has been designed based on the concept of the cutting state and collected expert rules. The automatically classified cutting state as well as the control action based on this state is compared to expert data. There are notable differences which are analysed and solutions and further research are suggested based on the points requiring further improvement.     

Regeneration and Recycling of Aqueous Periodate Solution in Dialdehyde Cellulose Production

Abstract

The regeneration of aqueous iodate solution from the regioselective periodate oxidation of softwood cellulose pulp to dialdehyde cellulose using hypochlorite as a secondary oxidant was studied. The influence of oxidation time on the pulp dissolution and regeneration efficacy was examined in particular. In addition, the recycling of regenerated periodate solution back to oxidation was clarified. The solutions from the 10 and 15 min oxidations were regenerated with 100% conversion efficacy when 1.2–1.4 times the stoichiometric amounts of hypochlorite were used. However, the regeneration efficacy decreased when the reaction time in the oxidation increased to 30 min because the content of soluble impurities, which consumed the hypochlorite in the side-reactions, increased significantly as the oxidation reaction proceeded. The regenerated solutions possessed good oxidation performance, showing that periodate was successfully regenerated using hypochlorite and supporting the assumption that periodate can be effectively recycled in the process when short oxidation times are used.     

The effect of the stabilization period on the economic lot scheduling problem

The Economic Lot Scheduling Problem (ELSP) is the problem of scheduling production of several items in a single facility, so that demands are met without stockouts or backorders, and the long run average inventory carrying and setup costs are minimized. One of the general assumptions in the ELSP is that the yield rates of a given manufacturing process are constant, or 100%, after setup. However, this assumption may not be true for certain manufacturing processes, in which the yield rates are quite low just after setup, and then increase over time. This period is called a stabilization period and yield rates gradually increase during this period until they reach the target rates, which are set empirically or strategically. The purpose of this paper is to clarify the effect of the stabilization period by applying the stabilization period concept to the ELSP, which has been widely applied to many production systems. In this paper, the problem is tackled in three stages: Firstly, we formulate a model and develop an algorithm, which provides a lower bound for a minimum cost. Secondly, we develop a heuristic procedure using the time-varying lot size approach. Finally, we solve a special case of the ELSP to find an upper bound using the common cycle approach.