Determination of ranged sets of design specifications by incorporating design-space heterogeneity

Setting design specifications (targets) is a critical task in the early stages of the design process. Flexible targets can accommodate uncertainty and changes in design by postponing design commitments and preserving design freedom. In this article, a new method is developed for obtaining a ranged set of design specifications that meets design criteria whilst incorporating design-space heterogeneity; meaning some areas in the design attribute space are more achievable than the others. The proposed method has two notable features. First, a quantization algorithm based on rough-set theory is used to decompose a design attribute space into sub-regions on the basis of how well they meet design criteria. Second, a new design-flexibility measure is used as a metric to select the most desired ‘target region’ on the bases of both the size of the region and the influence of potential design alternatives on overall achievability. The proposed approach enhances the capacity of a design system to adapt to evolving design knowledge, as well as to unexpected changes. The proposed method is demonstrated by a numerical example and the design of a domestic blender.     

Power aware channel width tapering of serially connected MOSFETs

This paper reviews a transistor channel width tapering scheme called Hill Tapering for FET chains with specific emphasis on power dissipation and layout area of the tapered chains. The Hill Tapering scheme results in the lowest power dissipation and physical area compared to any of the existing tapering schemes like linear, exponential or optimal tapering. It also offers high speed operation. This tapering scheme is general and suits domino logic circuit designs. SPICE simulation results have shown that up to 81% power dissipation reduction could be achieved by using this tapering scheme.     

Study of relaxations in poly(methyl methacrylate)–magneto electrets by thermally stimulated depolarization current and surface‐charge‐decay mechanisms

The effect of the forming temperature and the magnetic field was investigated for the charge retention and stability of poly(methyl methacrylate) (PMMA)–magneto electret (ME) samples with thermally stimulated discharge currents (TSDCs) and a surface‐charge‐decay mechanism. The measurements were performed on a pristine PMMA sample with a thickness of 20 mm. The comparative studies of charge decay with TSDC indicated a strong resemblance between the results of the two techniques of MEs of PMMA and were characterized by two TSDC peaks, that is, an α peak at 110°C and a ρ peak at 160°C. The low‐temperature peak (i.e., the α peak) was associated with dipolar relaxation, and the high‐temperature peak (i.e., the ρ peak) was attributed to the self‐motion of space charges in PMMA. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011.     

Weather-Induced Degradation of Plastic Pipes

A number of plastic materials, such as unplasticized poly(viny1 chloride) (uPVC), acrylonitrile-butadiene-styrene (ABS), high-density polyethylene (HDPE), poly-(vinylidene fluoride) (PVDF), and chlorinated poly(viny1 chloride) (cPVC), are available for numerous applications. uPVC and HDPE pipes are used in pressurized piping systems in Saudi Arabia for industrial, agricultural, domestic, and general-purpose applications. Some studies have been carried out to investigate the causes of failure in plastic pipes, which is very high in the area. In this chapter an overview of the failure of plastic pipes is presented, with emphasis given to failure of pipes due to severe weather conditions in Saudi Arabia.     

Properties of chemically treated natural amorphous silica fibers as polyurethane reinforcement

A novel kind of short natural fiber obtained from mineral resources, which consists mainly of pure amorphous SiO₂, was chemically modified with aminosilane to improve its interfacial adhesion in polyurethane composites. The effect of the treatment as well as the aspect ratio of the fibers on the mechanical properties of the composite were evaluated and compared with properties obtained with glass fibers composites, which are commonly used in industry. The results obtained show that these natural fibers are potential candidates for the substitution of glass fibers as a reinforcement phase in polymer composites, since the mechanical properties obtained were in all cases equal or superior to the ones obtained with commercial glass fibers. POLYM. COMPOS. 27:582–590, 2006. © 2006 Society of Plastics Engineers.     

No evidence for an ischemic penumbra in massive experimental intracerebral hemorrhage

OBJECTIVES: To determine the effect of massive intracerebral hemorrhage (ICH) on regional cerebral blood flow (rCBF) and metabolism, and to test the hypothesis that there is persistent ischemia in the perihematoma region after ICH. BACKGROUND: Cerebral ischemia is postulated to be one of the mechanisms of neural injury after ICH. Presumably the hematoma induces ischemia by mechanical compression of the surrounding microvasculature. METHODS: The authors induced ICH in eight anesthetized mongrel dogs by autologous blood injection (7.5 mL) under arterial pressure in the deep white matter adjacent to the left basal ganglia. They measured serial rCBF using radiolabeled microspheres in regions around and distant to the hematoma, as well as cerebral oxygen extraction, oxygen consumption (CMRO2), glucose utilization, and lactate production by serial sampling of cerebral venous blood from the sagittal sinus. Mean arterial pressure (MAP) and intracranial pressure (ICP) were monitored continuously. All measurements were recorded at 0.5, 1.0, 2.0, 3.5, and 5.0 hours after induction of ICH and compared with prehematoma values. Evans Blue dye was injected at the end of the experiment, and intensity of staining was compared with three control animals. RESULTS: Compared with prehematoma ICP (12.5+/-2.0 mm Hg, mean+/-standard error), significant elevation in ICP was observed after ICH peaking at 5 hours (34.4+/-5.2 mm Hg). Compared with prehematoma MAP (125.8+/-7.0 mm Hg), significant elevation in MAP was observed at 120 minutes after onset of hematoma (139.1+/-4.6 mm Hg), with return to the prehematoma value by 5 hours. There were no significant changes observed in cerebral oxygen extraction (51.4+/-4.3% versus 44.8+/-4.9%) and CMRO2 (1.8+/-0.3 versus 1.64+/-0.2 mL O2/100 g/min) at 5 hours posthematoma (or any other posthematoma measurement) compared with prehematoma values. There were no significant differences observed in rCBF in the perihematoma gray (18.2+/-0.9 mL/100 g/min versus 20.1+/-1.5 mL/100 g/min) or white matter (15.6+/-1.4 mL/100 g/min versus 15.3+/-1.1 mL/100 g/min) at 5 hours posthematoma (or any other posthematoma measurement) compared with prehematoma values. No changes were observed in cerebral glucose utilization, lactate production, and rCBF in other regions after introduction of ICH. Permeability of the blood-brain barrier was more prominent in the ipsilateral hemisphere in animals with ICH compared with control animals. CONCLUSIONS: Despite a prominent increase in ICP and MAP after ICH, the authors found no evidence to support the presence of an ischemic penumbra in the first 5 hours after ICH. Thus, other mechanisms for acute neural injury and late rCBF changes after ICH must be investigated.     

Dynamic S-Box Generation Using Novel Chaotic Map with Nonlinearity Tweaking

A substitution box (S-Box) is a crucial component of contemporary cryptosystems that provide data protection in block ciphers. At the moment, chaotic maps are being created and extensively used to generate these S-Boxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical attempts. In this paper, the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking approach. The projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their working makes both of these dynamic in nature. The tweak approach employs cubic polynomials while permuting the values of an initial S-Box to enhance its cryptographic fort. Values of the parameters are provided using the cipher key and a small variation in values of these parameters results in a completely different unique S-Box. Comparative analysis and exploration confirmed that the projected chaotic map exhibits a significant amount of chaotic complexity. The security assessment in terms of bijectivity, nonlinearity, bits independence, strict avalanche, linear approximation probability, and differential probability criteria are utilized to critically investigate the effectiveness of the proposed S-Box against several assaults. The proposed S-Box’s cryptographic performance is comparable to those of recently projected S-Boxes for its adaption in real-world security applications. The comparative scrutiny pacifies the genuine potential of the proposed S-Box in terms of its applicability for data security.     

A Framework of Deep Learning and Selection-Based Breast Cancer Detection from Histopathology Images

Breast cancer (BC) is a most spreading and deadly cancerous malady which is mostly diagnosed in middle-aged women worldwide and effecting beyond a half-million people every year. The BC positive newly diagnosed cases in 2018 reached 2.1 million around the world with a death rate of 11.6% of total cases. Early diagnosis and detection of breast cancer disease with proper treatment may reduce the number of deaths. The gold standard for BC detection is biopsy analysis which needs an expert for correct diagnosis. Manual diagnosis of BC is a complex and challenging task. This work proposed a deep learning-based (DL) solution for the early detection of this deadly disease from histopathology images. To evaluate the robustness of the proposed method a large publically available breast histopathology image database containing a total of 277524 histopathology images is utilized. The proposed automatic diagnosis of BC detection and classification mainly involves three steps. Initially, a DL model is proposed for feature extraction. Secondly, the extracted feature vector (FV) is passed to the proposed novel feature selection (FS) framework for the best FS. Finally, for the classification of BC into invasive ductal carcinoma (IDC) and normal class different machine learning (ML) algorithms are used. Experimental outcomes of the proposed methodology achieved the highest accuracy of 92.7% which shows that the proposed technique can successfully be implemented for BC detection to aid the pathologists in the early and accurate diagnosis of BC.     

Self-embedding framework for tamper detection and restoration of color images

Multimedia Tools and Applications - The present era is paving huge expansion to the transmission of digital data in fields like health, military intelligence, scientific research, and publication...