Investigations on the extrusion defect – Axial hole or funnel

Axial hole or funnel is a common extrusion defect observed during a direct extrusion process. Though a common defect, the parameters that influence the nature and formation of this defect have not been studied and reported. Further, the die design requirement to avoid the defect has also been not yet established. In this regard, finite element analysis has been carried out to investigate the effect of important extrusion parameters such as extrusion ratio (R), extrusion die angle (θ), deformation zone height (h), friction (μ) and constitutive material behaviour on the defect formation and its characteristic. The conditions under which the defect can be avoided have been established. Physical modeling experiments using plasticine were carried out to validate the numerical modeling results.     

Study of Damage and Fracture Toughness Due to Influence of Creep and Fatigue of Commercially Pure Copper by Monotonic and Cyclic Indentation

Fracture toughness is the ability of a component containing a flow to resist fracture. In the current study, the Ball indentation (BI) test technique, which is well acknowledged as an alternative approach to evaluate mechanical properties of materials due to its semi-nondestructive, fast, and high accurate qualities is used to estimate damage and the fracture toughness for copper samples subjected to varying levels of creep and fatigue. The indentation fracture toughness shows the degradation of Cu samples when they are subjected to different creep conditions. Axial fatigue cycling increases the strength at the mid-gauge section compared to other regions of the samples due to initial strain hardening. The advancement of indentation depth with indentation fatigue cycles experiences transient stage, i.e., jump in indentation depth has been observed, which may be an indication of failure and followed by a steady state with almost constant depth propagation with indentation cycles.     

Exploratory mining in cube space

Data Mining has evolved as a new discipline at the intersection of several existing areas, including Database Systems, Machine Learning, Optimization, and Statistics. An important question is whether the field has matured to the point where it has originated substantial new problems and techniques that distinguish it from its parent disciplines. In this paper, we discuss a class of new problems and techniques that show great promise for exploratory mining, while synthesizing and generalizing ideas from the parent disciplines. While the class of problems we discuss is broad, there is a common underlying objective—to look beyond a single data-mining step (e.g., data summarization or model construction) and address the combined process of data selection and transformation, parameter and algorithm selection, and model construction. The fundamental difficulty lies in the large space of alternative choices at each step, and good solutions must provide a natural framework for managing this complexity. We regard this as a grand challenge for Data Mining, and see the ideas discussed here as promising initial steps towards a rigorous exploratory framework that supports the entire process. Bee-Chung Chen is supported by a Microsoft Research graduate fellowship.     

Classification and Uncertainty Visualization of Dendritic Spines from Optical Microscopy Imaging

Neuronal dendrites and their spines affect the connectivity of neural networks, and play a significant role in many neurological conditions. Neuronal function is observed to be closely correlated with the appearance, disappearance and morphology of the spines. Automatic 3‐D reconstruction of neurons from light microscopy images, followed by the identification, classification and visualization of dendritic spines is therefore essential for studying neuronal physiology and biophysical properties. In this paper, we present a method to reconstruct dendrites using a surface representation of the dendrite. The 1‐D skeleton of the dendritic surface is then extracted by a medial geodesic function that is robust and topologically correct. This is followed by a Bayesian identification and classification of the spines. The dendrite and spines are visualized in a manner that displays the spines' types and the inherent uncertainty in identification and classification. We also describe a user study conducted to validate the accuracy of the classification and the efficacy of the visualization.     

Refining the In-Parameter-Order Strategy for Constructing Covering Arrays

Covering arrays are structures for well-representing extremely large input spaces and are used to efficiently implement blackbox testing for software and hardware. This paper proposes refinements over the In-Parameter-Order strategy (for arbitrary t). When constructing homogeneous-alphabet covering arrays, these refinements reduce runtime in nearly all cases by a factor of more than 5 and in some cases by factors as large as 280. This trend is increasing with the number of columns in the covering array. Moreover, the resulting covering arrays are about 5 % smaller. Consequently, this new algorithm has constructed many covering arrays that are the smallest in the literature. A heuristic variant of the algorithm sometimes produces comparably sized covering arrays while running significantly faster.     

Graphical and computer-aided approaches to plan experiments

Design of experiments is a quality technology to achieve product excellence, that is to achieve high quality at low cost. It is a tool to optimize product and process designs, to accelerate the development cycle, to reduce development costs, to improve the transition of products from R & D to manufacturing and to troubleshoot manufacturing problems effectively. It has been successfully, but sporadically, used in the United States. More recently, it has been identified as a major technological reason for the success of Japan in producing high-quality products at low cost. In the United States, the need for increased competitiveness and the emphasis on quality improvement demands a widespread use of design of experiments by engineers, scientists and quality professionals. In the past, such widespread use has been hampered by a lack of proper training and a lack of availability of tools to easily implement design of experiments in industry. Three steps are essential, and are being taken, to change this situation dramatically. First, simple graphical methods, to design and analyse experiments, need to be developed, particularly when the necessary microcomputer resources are not available. Secondly, engineers, scientists and quality professionals must have access to microcomputer-based software for design and analysis of experiments.¹ Availability of such software would allow users to concentrate on the important scientific and engineering aspects of the problem by computerizing the necessary statistical expertise. Finally, since a majority of the current workforce is expected to be working in the year 2000, a massive training effort, based upon simple graphical methods and appropriate computer software, is necessary.² The purpose of this paper is to describe a methodology based upon a new graphical method called interaction graphs and other previously known techniques, to simplify the correct design of practically important fractional factorial experiments. The essential problem in designing a fractional factorial experiment is first stated. The interaction graph for a 16-trial fractional factorial design is given to illustrate how the graphical procedure can be easily used to design a two-level fractional factorial experiment. Other previously known techniques are described to easily modify the two-level fractional factorial designs to create mixed multi-level designs. Interaction graphs for other practically useful fractional factorial designs are provided. A computer package called CADE (computer aided design of experiments), which automatically generates the appropriate fractional factorial designs based upon user specifications of factors, levels and interactions and conducts complete analyses of the designed experiments is briefly described.¹ Finally, the graphical method is compared with other available methods for designing fractional factorial experiments.     

刻蚀实现双重图形的前景

双重图形需要更新更苛刻的刻蚀能力，要求低于1.5nm CD均匀性、图形收缩和原位多层刻蚀。     

A High Throughput Configurable SDR Detector for Multi-user MIMO Wireless Systems

Spatial division multiplexing (SDM) in MIMO technology significantly increases the spectral efficiency, and hence capacity, of a wireless communication system: it is a core component of the next generation wireless systems, e.g. WiMAX, 3GPP LTE and other OFDM-based communication schemes. Moreover, spatial division multiple access (SDMA) is one of the widely used techniques for sharing the wireless medium between different mobile devices. Sphere detection is a prominent method of simplifying the detection complexity in both SDM and SDMA systems while maintaining BER performance comparable with the optimum maximum-likelihood (ML) detection. On the other hand, with different standards supporting different system parameters, it is crucial for both base station and handset devices to be configurable and seamlessly switch between different modes without the need for separate dedicated hardware units. This challenge emphasizes the need for SDR designs that target the handset devices. In this paper, we propose the architecture and FPGA realization of a configurable sort-free sphere detector, Flex-Sphere, that supports 4, 16, 64-QAM modulations as well as a combination of 2, 3 and 4 antenna/user configuration for handsets. The detector provides a data rate of up to 857.1 Mbps that fits well within the requirements of any of the next generation wireless standards. The algorithmic optimizations employed to produce an FPGA friendly realization are discussed.     

Structural and thermal characterization of CaO–MgO–SiO2–P2O5–CaF2 glasses

The influence of varying the CaO/MgO ratio on the structure and thermal properties of CaO–MgO–SiO₂–P₂O₅–CaF₂ glasses was studied in a series of eight glass compositions in the glass forming region of diopside (CaMgSi₂O₆)–fluorapatite [Ca₅(PO₄)₃F]–wollastonite (CaSiO₃) ternary system. The melt-quenched glasses were characterized for their structure by infrared spectroscopy (FTIR) and magic angle spinning (MAS)-nuclear magnetic resonance (NMR) spectroscopy. Silicon is predominantly present as Q² (Si) species, while phosphorus tends to coordinate in orthophosphate environment. The sintering and crystallization parameters of the glasses were obtained from differential thermal analysis (DTA) while crystalline phase fractions in the sintered glass–ceramics were analyzed by X-ray diffraction adjoined with Rietveld refinement. Diopside, fluorapatite, wollastonite and pseudowollastonite crystallized as the main crystalline phases in all the glass–ceramics with their content varying with respect to variation in CaO/MgO ratio in glasses. The implications of structure and sintering behaviour of glasses on their bioactivity were discussed.