Empirical models for net-length probability distribution and applications

In this paper, we propose a novel, empirical, and parameterizable model for estimating the probability distribution of wire length for each net in a placed netlist. The model is simple and fast to compute. We did extensive experimentation with state-of-the-art commercial (Cadence) and academic (Parquet and Labyrinth) tools and validated our model. Our distribution model was around three times more accurate than assuming half-perimeter bounding box as the fixed net-length estimate. Since the model is parameterizable it can be easily tailored for different routing tools and benchmarks. This model would be very useful in defining a full fledged probabilistic design automation methodology in which various design metrics are optimized from a probabilistic point of view. We also discuss the application of our model in a novel probabilistic approach to the buffer insertion problem.     

Scene Graph and Frame Update Algorithms for Smooth and Scalable 3D Visualization of Simulated Construction Operations

One of the prime reasons inhibiting the widespread use of discrete-event simulation in construction planning is the absence of appropriate visual communication tools. Visualizing modeled operations in 3D is arguably the best form of communicating the logic and the inner working of simulation models and can be of immense help in establishing the credibility of analyses. New software development technologies emerge at incredible rates that allow engineers and scientists to create novel, domain-specific applications. The authors capitalized on a computer graphics technology based on the concept of the scene graph to design and implement a general-purpose 3D visualization system that is simulation and CAD-software independent. This system, the Dynamic Construction Visualizer, enables realistic visualization of modeled construction operations and the resulting products and can be used in conjunction with a wide variety of simulation tools. This paper describes the scene graph architecture and the frame updating algorithms used in designing the Dynamic Construction Visualizer.     

Some investigations on fuzzy P + fuzzy I + fuzzy D controller for non-stationary process

The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller whose gain changes continuously with output of the process under control. Two non-stationary processes, whose characteristics change with time, are considered for simulation study. Simulation is performed using software LabVIEW TM . The set-point tracking response of parallel FP+FI+FD is compared with conventional parallel proportional plus integral plus derivative (PID) controller, tuned with the Ziegler-Nichols (Z-N) tuning technique. Simulation results show that conventional PID controller fails to track the set-point and becomes unstable as the process changes its characteristic with time. But the parallel FP+FI+FD controller shows considerably much better set-point tracking response and does not deviate from steady state. Also, a huge spike is observed in the output of PID controller as the reference set-point and process parameters are changed, while the FP+FI+FD controller gives spike free control signal.     

A free space frequency‐time‐domain technique for electromagnetic characterization of materials using reflection‐based measurement

In this report, a free space frequency‐time‐domain technique is presented for characterizing the electrical properties and thickness of the sample using multiple reflections and fabry‐perot resonance phenomenon. The retrieval of constitutive electromagnetic parameters of the sample has been carried out by comparing the measured reflection coefficient data from the sample at two different incident angles. The relative permittivity as well as relative permeability along with the thickness of different samples viz., beryllia, silicon, and plexiglass have been evaluated with high accuracy in the frequency range 1 to 15 GHz. The method is also experimentally validated by successfully reconstructing the unknown material properties of two different samples. The unique advantage of this method lies in non‐requirement of any prior knowledge of the sample's thickness for measuring the complex relative dielectric constant as well as relative permeability of the sample. To determine the electromagnetic properties of the sample, the sole knowledge of reflection coefficient data are needed. Moreover, the method does not involve any additional measurement for the reference calibration. The simple, cost‐effective proposed scheme is quite useful in many applications like accurate determination of signal strength in indoor wireless communication, through wall imaging, food industry, and so on.     

High-precision identification of contextual information in location-aware engineering applications

This paper presents research that investigated algorithms for high-precision identification of contextual information in location-aware engineering applications. The primary contribution of the presented work is the design and implementation of a dynamic user-viewpoint tracking scheme in which mobile users’ spatial context is defined not only by their position (i.e., location), but also by their three-dimensional head orientation (i.e., line of sight). This allows the identification of objects and artifacts visible in a mobile user’s field of view with much higher accuracy than was possible by tracking position alone. For outdoor applications, a georeferencing based algorithm has been developed using the Global Positioning System (GPS) and magnetic orientation tracking devices [5] to track a user’s dynamic viewpoint. For indoor applications, this study explored the applicability of wireless technologies, in particular Indoor GPS, for dynamic user position tracking in situations where GPS is unavailable. The objectives of this paper are to describe the details of the three-stage-algorithm that has been designed and implemented, and to demonstrate the extent to which positioning technologies such as GPS and Indoor GPS can be used together with high-precision orientation trackers to accurately interpret the fully-qualified spatial context of a mobile user in challenging environments such as those found on construction sites. The obtained results highlight the potential of using location-aware technologies for rapidly identifying and retrieving contextual information in engineering applications.     

Influence of dietary iron deficiency on acute metal intoxication

The frequent difficulties encountered in the diagnosis of pediatric sarcomas, caused by the lack of observable differentiation at the light microscopic level, has led to the routine use of immunohistochemistry in pediatric surgical pathology. To a large degree the advent of this staining technique has led to the correct assessment of many perplexing lesions that previously would have been given inconclusive diagnoses. However, with increased usage and testing, it has become apparent that there are few, if any, "magic bullets" in immunohistochemistry for pediatric pathologists. Thus, it behooves diagnosticians to be careful in the usage of this technique, to be aware of possible discrepancies in its results, and to remember the ancillary nature of its application. The following article will review selected markers commonly used in pediatric surgical pathology, from both previous reports and the author's perspective, and will briefly consider several new phenotypic markers which have potential utility with childhood sarcomas.     

CAMO: A context-aware movie ontology generated from LOD and movie databases

Multimedia Tools and Applications - An ontology is a formal representation of domain knowledge as a set of concepts and their relationships in structured format. Besides various applications,...     

Studies of nanocomposites based on carbon nanomaterials and RTV silicone rubber

The mechanical and electrical properties were investigated for nanocomposites based on carbon nanotubes (CNTs) and conductive carbon black (CB). Solution room‐temperature‐vulcanized silicone rubber was used as a matrix. Vulcanizates based on CNTs and CB was prepared by solution mixing. With the addition of 2 phr of CNTs to the rubber matrix, the Young's modulus increased by 272% and reached as high as ～706% at 8 phr, whereas the modulus increased only 125% for CB specimens at 10 phr. Similarly, the electrical properties at 5 phr content of CNT were ～0.7 kΩ against ～0.9 kΩ at 20 phr CB. The Kraus plot from equilibrium swelling tests shows that the high properties for CNT specimens are due to high polymer–filler interfacial interactions, the small particle size that improves the distribution of the filler in a highly exfoliated state, and high electrical connective networks among the filler particles. These improvements can especially influence medical products such as feeding tubes, seals and gaskets, catheters, respiratory masks and artificial muscles. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44407.     

SPARCL: an effective and efficient algorithm for mining arbitrary shape-based clusters

Clustering is one of the fundamental data mining tasks. Many different clustering paradigms have been developed over the years, which include partitional, hierarchical, mixture model based, density-based, spectral, subspace, and so on. The focus of this paper is on full-dimensional, arbitrary shaped clusters. Existing methods for this problem suffer either in terms of the memory or time complexity (quadratic or even cubic). This shortcoming has restricted these algorithms to datasets of moderate sizes. In this paper we propose SPARCL, a simple and scalable algorithm for finding clusters with arbitrary shapes and sizes, and it has linear space and time complexity. SPARCL consists of two stages—the first stage runs a carefully initialized version of the Kmeans algorithm to generate many small seed clusters. The second stage iteratively merges the generated clusters to obtain the final shape-based clusters. Experiments were conducted on a variety of datasets to highlight the effectiveness, efficiency, and scalability of our approach. On the large datasets SPARCL is an order of magnitude faster than the best existing approaches.