Improvement of lubrication and cooling in grinding

The presence of air boundary layer around a grinding wheel impedes the proper entry of cutting fluid into grinding zone and thereby lubrication and cooling are hampered. It leads to the thermal damage to the workpiece and rapid wheel wear. This experimental work is aimed at increasing the lubrication and cooling effects in grinding by a novel method of using scraper board. The experiments are conducted, using the scraper board, to find the critical region where the air pressure is zero. The coolant jet has then impinged into the grinding zone which is maintained within the critical region. The requirement of specific energy, surface texture, and mechanical properties of the ground surface are analyzed and compared with the traditional grinding and the grinding at various positions of scraper board. Results show that the grinding ratio improved by 35.6and 119%, surface roughness decreased by 36 and 54.2%, while the requirement of specific energy is reduced by 50.8 and 57.3% when scraper board is positioned at the critical distance in comparison to the 57.5° position and no scraper board, respectively. The results indicate that the introduction of fluid in the present method can improve the process efficiency and the product quality effectively.     

Cancer predisposition, radiosensitivity and the risk of radiation-induced cancers. IV. Prediction of risks in relatives of cancer-predisposed individuals

Individuals carrying cancer-predisposing germline mutations are known to be at a higher risk for cancers than those who do not carry them. This is also true of their biological relatives because they have a higher probability of being carriers of such mutant genes than unrelated individuals in the population. Further, there are now sufficient grounds for assuming that cancer-predisposed individuals may also be at a higher risk for cancers induced by ionizing radiation. In our earlier work, we examined the impact of this heterogeneity (with respect to cancer predisposition and radiosensitivity differentials) on risks of radiation-induced cancer at the population level. This paper is focused on the question of risks of radiation-induced cancer in relatives of cancer-predisposed individuals. Using an autosomal dominant model of cancer predisposition and radiosensitivity developed earlier and applying it to breast cancer risks associated with mutations in the BRCA1 gene, we show that: (1) The risk ratio (i.e. the ratio of risk of radiation-induced cancer in relatives to that in unrelated individuals) in the population increases with the degree of biological relatedness of the relative, being higher for close than for distant relatives; incomplete penetrance of the mutant gene "dilutes" this risk ratio. (2) The proportion of excess radiation-induced cancers in relatives (i.e. the attributable fraction) is higher than in unrelated individuals. (3) In relatives, the proportion of excess cancers due to radiosensitivity differentials alone depends on the strength of predisposition, the radiosensitivity differentials assumed, the radiation dose, the proportion of cancers due to predisposition, the mutant gene frequency and the penetrance of the mutant gene. This is in contrast to the situation for unrelated individuals, for whom the above-mentioned proportion is dependent on the first three but not on the last three of these factors. Further, even when the proportion of excess cancers is small, most of it is due to radiosensitivity differential alone both in unrelated individuals and in relatives. (4) For values of predisposition strength and radiosensitivity differential <10, even when the estimated frequency of a mutant BRCA1 gene is 0.0047 and the proportion of breast cancers due to these mutations is 38% (as is the case for Ashkenazi Jewish women under age 30), the increase in breast cancer risks is only marginal even for first-degree relatives. (5) These findings support the conclusion that increases in radiation risks to relatives (compared to those in unrelated individuals), to be detectable epidemiologically, will occur only when the mutant alleles are common and the strength of predisposition and radiosensitivity differentials are conjointly dramatic.     

Thin film evaporation in microchannels with interfacial slip

We investigate the role of interfacial slip on evaporation of a thin liquid film in a microfluidic channel. The effective slip mechanism is attributed to the formation of a depleted layer adhering to the substrate–fluid interface, either in a continuum or in a rarefied gas regime, as a consequence of intricate hydrophobic interactions in the narrow confinement. We appeal to the fundamental principles of conservation in relating the evaporation mechanisms with fluid flow and heat transfer over interfacial scales. We obtain semi-analytical solutions of the pertinent governing equations, with coupled heat and mass transfer boundary conditions at the liquid–vapor interface. We observe that a general consequence of interfacial slip is to elongate the liquid film, thereby leading to a film thickening effect. Thicker liquid films, in turn, result in lower heat transfer rates from the wall to liquid film, and consequently lower mass transfer rates from the liquid film to the vapor phase. Nevertheless, the total mass of evaporation (or equivalently, the net heat transfer) turns out to be higher in case of interfacial slip due to the longer film length. We also develop significant physical insights on the implications of the relative thickness of the depleted layer with reference to characteristic length scales of the microfluidic channel on the evaporation process, under combined influences of the capillary pressure, disjoining pressure, and the driving temperature differential for the interfacial transport.     

Selection of industrial robots using compromise ranking and outranking methods

Selection of a robot for a specific industrial application is one of the most challenging problems in real time manufacturing environment. It has become more and more complicated due to increase in complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. At present, different types of industrial robots with diverse capabilities, features, facilities and specifications are available in the market. Manufacturing environment, product design, production system and cost involved are some of the most influencing factors that directly affect the robot selection decision. The decision maker needs to identify and select the best suited robot in order to achieve the desired output with minimum cost and specific application ability. This paper attempts to solve the robot selection problem using two most appropriate multi-criteria decision-making (MCDM) methods and compares their relative performance for a given industrial application. The first MCDM approach is ‘VIsekriterijumsko KOmpromisno Rangiranje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. Two real time examples are cited in order to demonstrate and validate the applicability and potentiality of both these MCDM methods. It is observed that the relative rankings of the alternative robots as obtained using these two MCDM methods match quite well with those as derived by the past researchers.     

GPU-based Acceleration of System-level Design Tasks

Many system-level design tasks (e.g., high-level timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-hard). As a result, they involve high running times even for mid-sized problems. In this paper we explore the possibility of using commodity graphics processing units (GPUs) to accelerate such tasks that commonly arise in the electronic design automation (EDA) domain. We demonstrate this idea via two detailed case studies. The first explores the possibility of using GPUs to speedup standard schedulability analysis problems. The second proposes a GPU-based engine for a general hardware/software design space exploration problem. Not only do these problems commonly arise in the embedded systems domain, their computational kernels turn out to be variants of a combinatorial optimization problem—viz., the knapsack problem—that lies at the heart of several EDA applications. Experimental results show that our GPU-based implementations offer very attractive speedups for the computational kernels (up to 100×), and speedups of up to 17× for the full problem. In contrast to ASIC/FPGA-based accelerators—given that even low-end desktop and notebook computers are now equipped with GPUs—our solution involves no extra hardware cost. Although recent research has shown the benefits of using GPUs for a variety of non-graphics applications (e.g., in databases and bioinformatics), harnessing the parallelism of GPUs to accelerate problems from the EDA domain has not been sufficiently explored so far. We believe that our results and the generality of the core problem that we address will motivate researchers from this community to explore the possibility of using GPUs for a wider variety of problems from the EDA domain.     

An experimental analysis of electrostatically vibrated array of polysilicon cantilevers

Micromechanical cantilevers are one of the most fundamental and widely studied structures in micro-electromechanical systems. Dynamic response of such cantilevers has long been an interesting subject to researchers and different analytical and experimental approaches have been reported to determine it. Theoretical estimation of different damping mechanisms have been reported over years which are relevant particularly in studying the dynamics of the micro-mechanical structures. Most properties and functionalities of the MEMS devices are invariably dependant on the dynamic response of the devices, which in turn depends on the quality factor of the devices or in other words the overall damping present in the system. This paper presents a thorough experimental analysis of vibration characteristics of micro-mechanical cantilevers of different dimensions. Arrays of polysilicon micro-cantilevers of different dimensions have been designed and fabricated using surface micromachining process. The beams are resonated by electrostatic actuation and their vibration characteristics have been observed using Laser Doppler Vibrometer. Also a thorough analysis of modal behaviour of the beams is presented using analytical approach and finite element method based simulation. Different damping mechanisms have been critically reviewed and a semi-analytical estimation of the overall damping is presented. The results are compared with experimental values.     

Bayesian binary kernel probit model for microarray based cancer classification and gene selection

With the arrival of gene expression microarrays a new challenge has opened up for identification or classification of cancer tissues. Due to the large number of genes providing valuable information simultaneously compared to very few available tissue samples the cancer staging or classification becomes very tricky.In this paper we introduce a hierarchical Bayesian probit model for two class cancer classification. Instead of assuming a linear structure for the function that relates the gene expressions with the cancer types we only assume that the relationship is explained by an unknown function which belongs to an abstract functional space like the reproducing kernel Hilbert space. Our formulation automatically reduces the dimension of the problem from the large number of covariates or genes to a small sample size. We incorporate a Bayesian gene selection scheme with the automatic dimension reduction to adaptively select important genes and classify cancer types under an unified model. Our model is highly flexible in terms of explaining the relationship between the cancer types and gene expression measurements and picking up the differentially expressed genes. The proposed model is successfully tested on three simulated data sets and three publicly available leukemia cancer, colon cancer, and prostate cancer real life data sets.     

A layered algorithm for quantifier elimination from linear modular constraints

Linear equalities, disequalities and inequalities on fixed-width bit-vectors, collectively called linear modular constraints, form an important fragment of the theory of fixed-width bit-vectors. We present a practically efficient and bit-precise algorithm for quantifier elimination from conjunctions of linear modular constraints. Our algorithm uses a layered approach, whereby sound but incomplete and cheaper layers are invoked first, and expensive but complete layers are called only when required. We then extend this algorithm to work with arbitrary Boolean combinations of linear modular constraints as well. Experiments on an extensive set of benchmarks demonstrate that our techniques significantly outperform alternative quantifier elimination techniques based on bit-blasting and linear integer arithmetic.     

Effect of ohmic contacts on buffer leakage of GaN transistors

The effect of ohmic contacts on the buffer leakage of GaN transistors is presented. The buffer leakage for AlGaN/GaN high-electron mobility transistors and GaN MESFETs grown on the same underlying buffer was observed to be different. Controlled experiments show that the increased buffer leakage is due to the nature of the alloyed ohmic contacts and can be minimized if they are screened by the Si doping or by the two-dimensional electron gas.