Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable Visualization of Semantic Nets using Power-Law Graphs

Scalability and performance implications of semantic net visualization techniq ues are open research challenges. This paper focuses on developing a visualization technique that mitigates these challeng es. We present a novel approach that exploits the underlying concept of power-law degree distribution as many realistic semantic nets seems to possess a power law degree distribution and present a small world phenomenon. The core concept is to partition the node set of a graph into power and non-power nodes and to apply a modified force-directed method that emphasizes the power nodes whic h results in establishing local neighborhood clusters among power nodes. We also made refinements in conventional force-directe d method by tuning the temperature cooling mechanism in order to resolve 'local-minima' problem. To avoid cluttered view, we applied semantic filtration on nodes, ensuring zero loss of semantics. Results show that our technique handles very large scale semantic nets with a substantial performance improvement while producing aesthetically pleasant layouts. A visualization tool, NavigOWL, is developed by using this technique which has been ported as a plug-in for Protege, a famous ontology editor.
A new low-power pMOS poly-Si inverter for AMDs

A new low-power inverter using only p-type poly-Si thin-film transistors for the driving circuits of active matrix liquid crystal displays and active matrix organic light-emitting diodes is proposed and fabricated. The proposed pMOS inverter using capacitive coupling and bootstrapping successfully eliminated the troublesome through current and exhibited a wide output swing from V/sub DD/ to V/sub SS/ without additional signals.
The Orbit and Pulsation Periods of the γ Doradus Variable HR 6844 (V2502 Ophiuchi)

We obtained spectroscopic and photometric observations of the γ Doradus variable HR 6844 (=V2502 Ophiuchi). Radial velocities show that this star is a single-lined binary with a period of 4.4852 days. The primary is an F1 V star, while the secondary is likely an M dwarf. Velocity residuals to a circular orbit have a period of 1.3071 days and an amplitude of ∼3 km s-1. Three periods of light variation were detected, 1.30702, 1.4350, and 0.62286 days. The first period is essentially identical to that found in the radial velocities and has the largest amplitude, a peak-to-peak value of 0.067 mag in B. The photometric check star, 73 Oph (=HR 6795), has light variations with a period of 0.61439 in B. Although the star is a close visual binary, the light variations are ascribed to the primary, making it most likely a newly discovered γ Doradus variable.
A bimodal sound source model for vehicle tracking in traffic monitoring

The paper addresses road traffic monitoring using a compact microphone array. More precisely, estimation of both speed and wheelbase distance of detected vehicles is performed. The detection algorithm is based on the comparison between theoretical and measured correlation time series using the two dimensional Bravais-Pearson correlation coefficient. The tracking step is conducted with a particle filter specifically designed to model the position-variant bimodal sound source nature of the vehicles, i.e. taking into account the sound emitted by both vehicle axles. Sensitivity and performance studies using simulations and real measurements show that the bimodal approach reduces the tracking failure risk in harsh conditions when vehicles are tracked, at the same time, in opposite directions.
Scope resolution of logical connectives in NL constraints

Natural Language Constraints have a vital role in Business Organization. The main problem is scope ambiguity when these NL constraints are translated into formal languages. Human beings can understand the context in which these constraints are defined but it is most difficult for a machine to understand the exact meanings of these constraints in their context and this leads to crash the Business System. Therefore before translating these business constraints to OCL, the scope ambiguities should be resolved for correct translation of NL to OCL. For this purpose a new technique is proposed for handling the scope of logical operators used in NL constraints by using the Markov Logic. The subject and scope knowledge and Markov logic integrates into natural language processing. The subject knowledge has been deployed as context knowledge and scope knowledge was acquired from the business constraints. Markov logic was applied to NL constraints for selecting the most possible meaning of an ambiguous NL constraint based on the context. The presented work shows that by handling the identified cases of scope ambiguities of logical operators, we can take correct translation of business constraints into formal specifications.
A Magnetic Ranging-Aided Dead-Reckoning Positioning System for Pedestrian Applications

This paper investigates the applicability of a developed Magnetic Positioning System (MPS) as a support for a dead-reckoning inertial navigation system (DR-INS) for pedestrian applications. The integrated system combines the complementary properties of the separate systems, operating over long periods of time and in cluttered indoor areas with partial nonline-of-sight conditions. The obtained results show that the proposed approach can effectively improve the coverage area of the MPS and the operation time with bounded errors of the DR-INS. In particular, a solution that provides bounded position errors of 1–2 m over significantly long periods of time up to 45 min, in realistic indoor environments, is demonstrated. Moreover, system applicability is also shown in those scenarios where arbitrary orientations of the MPS mobile node are considered and an MPS position estimate is not available due to less than three distance measurements.
HMGA2 expression in uterine leiomyomata and myometrium: Quantitative analysis and tissue culture studies

The high mobility group gene, HMGA2, is frequently expressed in uterine leiomyomata (UL) with chromosomal rearrangements of 12q15. In contrast, HMGA2 expression has not been detected in karyotypically normal UL or in myometrium, but has been detected in these tissues after culture. To characterize further the expression pattern of HMGA2, we assessed HMGA2 expression by RT‐PCR followed by Southern blot hybridization, and by real‐time PCR in three tissue panels: (1) primary myometrial cultures, (2) uncultured tissue from 15 karyotypically normal samples consisting of eleven 46,XX UL and four matched myometrial specimens, and (3) uncultured tissue from ten UL with 12q15 rearrangements and three matched myometrial specimens. HMGA2 expression was detected in all samples from the three panels. The level of HMGA2 expression in karyotypically normal UL was similar to the level of expression in myometrium; however, it was significantly less than the level measured in UL with 12q15 rearrangements. This expression analysis by use of detection methods of different sensitivities underscores the importance of studies of HMGA2 expression in uncultured tissues and of careful interpretation of results from experiments on cultured cells. Moreover, detection of HMGA2 expression in myometrium and in UL without 12q15 rearrangements, tissues previously thought not to express HMGA2, suggests that HMGA2 expression is required in normal adult myometrial physiology. © 2003 Wiley‐Liss, Inc.
In-situ TEM study of carbon nanomaterials and thermoelectric nanomaterials

Graphene nanoribbons (GNRs) are quasi one dimensional structures which have unique transport properties, and have a potential to open a bandgap at small ribbon widths. They have been extensively studied in recent years due to their high potential for future electronic and spintronic device applications. The edge structures including the edge roughness and chirality dramatically affect the transport, electronic, and magnetic properties of GNRs, and are of the critical importance. We have developed an efficient way of modifying the edges structures, to produce atomically smooth zigzag and armchair edges by using insitu TEM with a controlled bias. This work provides us with many opportunities for both fundamental studies and for future applications. I also report the use of either furnace heating or Joule heating to pacify the exposed graphene edges by loop formation in the graphitic nanoribbons. The edge energy minimization process involves the formation of loops between adjacent graphene layers. An estimation of the temperature during in-situ Joule heating is also reported based on the melting and evaporation of Pt nanoparticles. In this thesis work, I have also investigated the morphological and electronic properties of GNRs grown by chemical vapor deposition. Our results suggest that the GNRs have a surprisingly high crystallinity and a clean surface. Both folded and open edges are observed in GNRs. Atomic resolution scanning tunneling microscopy (STM) images were obtained on the folded layer and the bottom layer of the GNR, which enables clear identification of the chirality for both layers. We have also studied the electronic properties of the GNRs using low temperature scanning tunneling spectroscopy (STS). Our findings suggest that edges states exist at GNR edges which are dependent on the chiral angles of the GNRs. Thesis Supervisor: Mildred S. Dresselhaus Title: Institute Professor of Electrical Engineering and Physics
Experimental analysis of drainage and water storage of litter layers

Abstract. Many hydrological studies of forested ecosystems focus on the study of the forest canopy and have partitioned gross precipitation into throughfall and stemflow. However, the presence of forest litter can alter the quantities of water available for soil infiltration and runoff. Little information exists regarding the value of storage and drainage parameters for litter layers. Vegetation parameters of this kind are required in physically-based and lumped conceptual models to quatify the availabilty and distribution of water. Using a rainfall simulator and laboratory conditions two main objectives were investigated using layers of recently seneced poplar leaves, fresh grass or woodchips: 1) Effect of rain intensity on storage. With this respect we found that: maximum storage (Cmax), defined as the detention of water immediately before rainfall cessation, increased with rainfall intensity. The magnitude of the increment was up to 0.5 mm kg−1 m−2 between the lowest (9.8 mm h−1) and highest (70.9 mm h−1) rainfall intensities for poplar leaves. Minimum storage (Cmin), defined as the detention of water after drainage ceased, was not influenced by rainfall intensity. Repeated wetting-draining cycles or layer thickness have no effect on Cmax or Cmin. 2) The evaluation of drainage coefficient for the Rutter model. This model was found accurate to predict storage and drainage in the case of poplar leaves, was less accurate for fresh grass and resulted in overestimations for woodchips. Additionally, the effect of an underlaying soil matrix on lateral movement of water and storage of poplar leaves was studied. Results indicated that the soil matrix have no effect on Cmax or Cmin of the litter layer. Lateral movement of water in the poplar layer was observed at intermediate rainfall intensities (30.2 and 40.4 mm h−1), but not a the lowest or highest rates.
A novel flocking inspired algorithm for self-organization and control in heterogeneous wireless networks

This paper presents a new model and algorithm for slef-organization and control of a class of next generation communication networks: hierarchical heterogeneous wireless networks (HHWNs), under real world physical constraints. A nature inspired flocking algorithm (FA) is investigated in this context. Our model is based on the control framework at the physical layer presented previously by the authors, where network robustness is characterized in terms of the system's potential energy, and control mechanisms are designed to minimize potential energy for optimized network performance. We first focus on the modeling of HHWNs under real world physical constraints. Second, we propose a new FA for self-organization and control of the backbone nodes in an HHWN by collecting local information from end users. Our algorithm is examined in our built simulation platform that supports various dynamic scenarios. Experimental results demonstrate that FA outperforms current algorithms for the self-organization and optimization of HHWN under real world physical constraints.
A type-preserving compiler in Haskell

There has been a lot of interest of late for programming languages that incorporate features from dependent type systems and proof assistants, in order to capture important invariants of the program in the types. This allows type-based program verification and is a promising compromise between plain old types and full blown Hoare logic proofs. The introduction of GADTs in GHC (and more recently type families) made such dependent typing available in an industry-quality implementation, making it possible to consider its use in large scale programs. We have undertaken the construction of a complete compiler for System F, whose main property is that the GHC type checker verifies mechanically that each phase of the compiler properly preserves types. Our particular focus is on "types rather than proofs": reasonably few annotations that do not overwhelm the actual code. We believe it should be possible to write such a type-preserving compiler with an amount of extra code comparable to what is necessary for typical typed intermediate languages, but with the advantage of static checking. We will show in this paper the remaining hurdles to reach this goal.
Image Enhancement Using Fuzzy Technique

— Image enhancement means to enrich the perception of images for human viewers. It can reduce impulsive noise, sharpen the edges with the help of different image enhancement techniques. Fuzzy techniques can manage the uncertainty and imperfection of an image which can be represented as a fuzzy set. Fuzzy logic can be used to process human knowledge in the form of fuzzy if-then rules. The accumulation of all these approaches come up to the theory of fuzzy image processing, which is divided into 3 phases: Image fuzzification, membership values modification, and image defuzzification. In most cases, images available are not in fine quality. In this paper an image enhancement technique based on fuzzy logic is discussed and then implemented in MATLAB 7.14. 0 (R2012a).
Transfer Ensemble Model for Customer Churn Prediction with Imbalanced Class Distribution

Customer churn prediction is an important issue in customer relationship management. The class distribution of customer data is often imbalanced, which may affect the performance of churn prediction model greatly. This paper combines transfer learning and multiple classifiers ensemble, and proposes a transfer ensemble model for imbalanced data (TEMID). This method focuses on using transfer learning and sampling to enlarge the available training set and balance it respectively. What's more, it also uses multiple classifiers ensemble method to implement the classification. The performance of TEMID and some existing transfer learning algorithms are compared in two class imbalanced datasets. The results show that the TEMID methods can actually improve the performance of the customer churn prediction.
Application of operator-scaling anisotropic random fields to binary mixtures

In modern technical applications various multiphase mixtures are used to meet demanding mechanical, chemical and electrical requirements. To understand their structural properties as continuous macroscopic materials, it is important to capture the microstructure of these mixtures. Due to their vast range of applications multicomponent systems are subjected to microstructural changes such as phase separation and coarsening. Therefore the ultimate microstructural arrangement depends on the system's configuration and on exterior driving forces. In addition to this, random physical imperfections within the material and random noise in the exterior thermodynamic fields influence in essence the microstructural evolution. Since all physical processes are subjected to a certain degree of random inhomogeneity under realistic conditions, the influence of random phenomena cannot be neglected in modern physical models. An advanced mathematical description and an implementation of these stochastic processes are required to adapt simulation results based on deterministic mathematical models to experimental observations. In our contribution we will present an operator-scaling anisotropic random field embedded in the Cahn–Hilliard phase-field model to describe the phase evolution in a binary mixture. The arising nonlinear diffusion equation will be solved numerically in the innovative framework of the isogeometric finite element method. To illustrate the flexibility and versatility of our approach, numerical and experimental results for a eutectic Sn-Pb alloy are contraposed. This is the first time that the microstructural evolution in a multicomponent system has been associated with operator-scaling anisotropic random fields. Due to its enormous potential as an essential ingredient in stochastic mathematical and physical modeling it is only a matter of time until these processes will become prevalent in engineering applications.
A thermoviscoelastic analysis of process-induced internal stresses in thermoplastic matrix composites

A numerical tool for predicting the evolution of internal and residual stresses during the processing of thermoplastic matrix composites has been developed. Based on a finite element formulation, the model accounts for the anisotropy, viscoelasticity and heterogeneity of the materials and represents mechanisms of both stress generation and stress relaxation. The viscoelastic properties are described by a linear thermoviscoelastic formulation. The model allows the buildup of stresses during processing to be monitored, in particular when the material is cooling through its transition temperatures, and enables the prediction of stress release and the resulting part warpage on demolding. Its use is demonstrated for unidirectional and crossply polyetherimide/glass fiber (PEI/GF) laminates processed by compression molding, and the influence of cooling conditions on stress levels is shown.
Study on Effect of Composite Particles in Polishing Process and Its Mechanism

In this paper, mixed slurries containing silica abrasives and polystyrene (PS) polymer particles in deionized water at pH 10.5 have been evaluated for silicon wafer polishing. By applying the theory of electric double layer model, the effect of the particle interactions in mixed slurry is investigated. Zeta potential measurements and TEM images have been used to show the formation of composite particles. The polishing mechanism with composite particles slurries is discussed. Polishing experiments with the mixed slurries formed by coating smaller (~30nm) abrasives onto softer and larger (~2000nm) polymer particles have shown the superior characteristic with higher removal rate and high surface quality.
Use of Inductive Logic Programming to Learn Principles of Protein Structure

Inductive Logic Programming (ILP) has been applied to learn rules which characterise protein folds. Several representations for the background set have been explored and the results have been interpreted in their biological context. In this paper, we present new results obtained with a background set containing information about protein topology. The new rules are more descriptive than the previous ones, i.e. where previous rules represented local motifs, often associated with functional regions, the new rules represent more complete descriptions, often similar to the descriptions found in SCOP. Cross-validation experiments were conducted for the 20 most populated folds. The overall cross-validated accuracy was found to be 75.1 ± 1.6 % for the more limited background knowledge, and 82.1± 1.4 % whith additional information.
Performance and Design Issues for High Strength Steel in Structures

Steel has been used in a very large number of structures for almost 150 years, and the material has undergone major changes over that period. For many years the primary grades were carbon-manganese steel with low strength and high deformability. However, structural systems have evolved greatly, with taller buildings and longer span structures of all kinds. Along with new directions in architectural expression, engineering modeling and design techniques have been affected by computational equipment, and fabrication and erection changes have followed suit. As these advances have taken place, significant demands for higher performing materials have evolved, to the extent that ultra high strength steels with yield stress levels of 700 MPa and much higher are now being considered. The paper examines these developments, including very recent findings from a variety of sources, and looks to the practical uses of the high strengths. The discussion focuses on performance needs, steel products, fabrication options and realistic economies of scale. It is clear that high strength by itself is not a solution, and numerous options need to be evaluated before selecting systems and materials.
Prospective study of Type 2 diabetes mellitus, anti‐diabetic drugs and risk of prostate cancer

Type 2 diabetes mellitus (T2DM) has consistently been associated with decreased risk of prostate cancer; however, if this decrease is related to the use of anti‐diabetic drugs is unknown. We prospectively studied men in the comparison cohort in the Prostate Cancer data Base Sweden 3.0, with data on T2DM, use of metformin, sulfonylurea and insulin retrieved from national health care registers and demographic databases. Cox proportional hazards regression models were used to compute hazard ratios (HR) and 95% confidence intervals (CI) of prostate cancer, adjusted for confounders. The study consisted of 612,846 men, mean age 72 years (standard deviation; SD = 9 years), out of whom 25,882 men were diagnosed with prostate cancer during follow up, mean time of 5 years (SD = 3 years). Men with more than 1 year's duration of T2DM had a decreased risk of prostate cancer compared to men without T2DM (HR = 0.85, 95% CI = 0.82–0.88) but among men with T2DM, those on metformin had no decrease (HR = 0.96, 95% CI = 0.77–1.19), whereas men on insulin (89%) or sulfonylurea (11%) had a decreased risk (HR = 0.73, 95% CI = 0.55–0.98), compared to men with T2DM not on anti‐diabetic drugs. Men with less than 1 year's duration of T2DM had no decrease in prostate cancer risk (HR = 1.11, 95% CI = 0.95–1.31). Our results gave no support to the hypothesis that metformin protects against prostate cancer as recently proposed. However, our data gave some support to an inverse association between T2DM severity and prostate cancer risk.
Impact of Space-Time Multiplexing Granularity on Provisioning in On-Demand Data Centers: Opportunities and Challenges

On-demand data centers efﬁciently host multiple applications on shared hardware by dynamically provisioning resources in response to workload variations. In this paper, we use real-world e-commerce workloads to demonstrate that the efﬁciency of such dynamic provisioning is critically dependent on the granularity of reallocation. Speciﬁcally, we show that the ability to allocate fractional server resources at time-scales of seconds can improve the multiplexing beneﬁts by a factor of three. Using these results, we argue that existing techniques for dedicated hosting are highly sub-optimal. We argue for a new hosting platform architecture, based on virtual machine monitors, that can perform ﬁne-grain resource multiplexing along the space and time dimensions while retaining the isolation and security beneﬁts of dedicated hosting platforms.