Miracle-dz/UniFAR-FTUs huggingface dataset:
Thatcher's Britain : the politics and social upheaval of the Thatcher era

It will, in May 2009, be thirty years since Margaret Thatcher entered Downing Street. Thatcher was the longest serving prime minister of the twentieth-century and her period in government coincided with extraordinary changes in British society and in Britain's place in the world. Thatcher's image permeates, not just discussion of recent British history, but also films and novels -- there has even been a musical based on her career. Curiously, the emphasis on Thatcher as a kind of cultural icon has often gone with a declining interest in the details of what her government did. This book tells the story of Thatcherism for a generation with no personal memories of the 1980s -- as well as for those who want to revisit the polemics of their youth. It aims to describe Thatcherism in a way that is both detached and engaging. Most of all, it seeks to rescue Margaret Thatcher from being seen as John the Baptist for Tony Blair. It stresses that Thatcherism was not a timeless phenomenon that can be traced back into the nineteenth century or transported forward into the twenty-first.It was rooted in the 1970s and 1980s -- a time when the Soviet empire seemed to be expanding and when the British economy seemed to be on its deathbed. Anyone who wants a flavour of the times should recall that Margaret Thatcher received her first ever letter from Ronald Reagan on the day that Saigon fell to the Viet Cong.
English-Korean patent system: fromTo-EK/PAT

This paper addresses a method for customizing an En glish-Korean machine translation system from genera l domain to patent domain. The customizing method includes the followings: (1) extracting and constructing large bilingual termin ology and the patent-specific translation patterns, (2) adapting the probabilitie s of POS tagger trained from general domain to the pat nt domain, (3) syntactically analyzing long and complex sentences by recognizing coordinate structures, and (4) selecting a proper target word using patentspecific bilingual dictionary and collocation knowl edge extracted from patent corpus. The translation accuracy of the customized EnglishKorean patent translation system is 82.43% on the a verage in 5 patent categories (machinery, electronics, chemistry, medicine and co mputer) according to the evaluation of 7 profession al patent translators. A patent MT system for electronics domain was installed and started an on-line MT service in IPAC (Internationa l P tent Assistance Center) under MOCIE (Ministry of Commerce, Industry and Ene rgy) in Korea. In 2007, KIPO (Korean Intellectual P roperty Office) is expected to launch its English-Korean MT service fo r whole patent domain.
Hybridized Oscillating Search Algorithm for Unsupervised Feature Selection

In feature selection, a search problem of finding a subset of features from a given set of measurement s has been of interest for a long time. However, unsupervised met hods are scarce. An unsupervised criterion, based o n SVD-entropy (Singular Value Decomposition), selects a feature a ccording to its contribution to the entropy (CE) ca lculated on a leave-one-out basis. Based on this criterion, this paper proposes a Hybridized Oscillating Search feat ur selection method (HOS) which does not follow a pre defined di rection of search (forward or backward). It is a ra ndomized search method which begins with a random subset of feature s. The proposed HOS method makes use of a sequentia l f ature selection method called Simple Ranking based on CE to get the initial feature subset. Repeated modific at on of the subset is achieved through up and down swings which form the oscillating cycles. The up swing adds goo d features to the current subset while the down swing removes wor st features from the current subset. After each osc illating cycle, the subset is evaluated by comparing its predictive accuracy with known classification. Common indices like Rand Index and Jaccard Coefficient are used for this pur pose. If the last oscillating cycle did not find a better subset, then the process ends with the current subset.
System Design for Heterogeneity: The Virtual Machine Services Test Case

Power and energy constraints are forcing architects to propose heterogeneous parallel systems. Unfortunately, tuning or customizing parallel hardware for a particular application compromises application portability. This paper focuses on the class of heterogeneous systems that combine general-purpose big and small cores for portability. This paper identifies key software characteristics and a framework for exploiting them to improve performance, power, and energy on big/small multicores: (1) parallelism, (2) asynchrony, (3) criticality, and (4) hardware sensitivity. We choose Virtual Machine (VM) services executing managed languages as our workload. They are pervasive (e.g., JavaScript, PHP, Java, and C#), dominate power and energy constrained platforms, such as the phone and tablet, do not compromise application portability, and use a lot of energy. VM services interpret, compile, profile, schedule, and manage memory while executing applications. Fortunately, VM services are often parallel, asynchronous, not on the application’s critical path, and are power and energy efficient on small cores. This paper demonstrates (a) that VM services consume a lot of power and energy, almost 40% in modern systems; (b) how to exploit unique combinations of the four characteristics in VM services to lower power, improve performance, and improve performance per energy (PPE); and (c) that using big cores for application threads together with tuned small low-power cores for VM services can substantially lower power and improve performance per energy (PPE). These results suggest that other system services, additional architecture tuning or customization, and software/hardware co-design are fruitful future directions for improving PPE and meeting power constraints.
Compositional separate modular static analysis of programs by abstract interpretation

The purpose of this paper is to present four ba­ sic methods for compositional separate modular static analy­ sis of programs by abstract interpretation: • Simplification-based separate analysis; • Worst-case separate analysis; • Separate analysis with (user-provided) interfaces; • Symbolic relational separate analysis; as well as a fifth category which is essentially obtained by composition of the above separate local analyses and global analysis methods. Keywords—Abstract interpretation, Static program analy­ sis, Global analysis, Whole program analysis, Separate analysis, Modular analysis, Component analysis, Composi­ tion of analyses.
An Efficient Gray-level Clustering Algorithm for Image Segmentation

Gray-level clustering is an important procedure in image processing, which reduces the gray-level of an image. In order to display an image with high gray level in a screen with lower gray level, a good gray-level clustering algorithm is necessary to complete this job. Based on the mean value and standard deviation of histogram within a sub-interval, a novel recursive algorithm for solving the gray-level reduction is proposed in this paper. It divides the sub-interval recursively until the difference between original image and clustered image within a given threshold. Experiments are carried out for some samples with high gray level to demonstrate the computational advantage of the proposed method.
Illuminant color estimation for real-world mixed-illuminant scenes

We present a physics-based approach for illuminant color estimation of arbitrary images, which is explicitly designed for handling images with multiple illuminants. The majority of techniques that extract the illuminant color assume that the illumination is constant across the scene. This, however, is not often the case. We propose an illuminant-color estimation method which is based on robust local illuminant estimates. There are no assumptions on the number or type of illuminants. An illuminant color estimate is obtained independently from distinct image mini-regions. From these mini-regions a robust local illumination color is computed by consensus. These local estimates are then used in deriving the chromaticity of the dominant illuminants. Experiments on an established benchmark database of real-world images show that our technique performs comparably to uniform-illuminant estimation methods. Furthermore, extensive tests on real-world images show that we can reliably process mixed illuminant scenes.
Zernike moments and svm for shape classification in very high resolution satellite images

In this paper, a Zernike moments-based descriptor is used as a measure of shape information for the detection of buildings from Very High Spatial Resolution (VHSR) satellite images. The proposed approach comprises three steps. First, the image is segmented into homogeneous objects based on the spectral and spatial information. MeanShift segmentation method is used for this end. Second, a Zernike feature vector is computed for each segment. Finally, a Support Vector Machines (SVM)-based classification using the feature vectors as inputs is performed. Experimental results and comparison with Environment for Visualizing Images (ENVI) commercial package confirm the effectiveness of the proposed approach.
Bioelectrical Impedance Vector Analysis (BIVA) in Slovak population: application in a clinical sample

The purpose of this study is to provide new data on body composition in the Slovak population, particularly impedance vector components according to sex and age, relevant for bioelectrical impedance vector analysis (BIVA) in a clinical sample. The reference sample consisted of 1543 apparently healthy individuals (1007 females and 536 males), aged from 18 to 92 years and of 60 patients with Parkinson’s disease (PD) (26 females and 34 males), aged from 40 to 81 years. Bioelectrical parameters of resistance (R) and reactance (Xc) were measured with a monofrequency analyser (BIA 101). BIVA was used to analyse tissue electric properties in control subjects and patients with PD. The mean vector position differed significantly between PD patients and healthy controls in males of age subgroups 60–69 years and 70–79 years, respectively. These results were conterminous with significant Hotelling’s T2-test; 60–69 y T2=7.8, P=0.024 and 70–79 y T2=7.6, P=0.026. In the RXc-score graph three patients had values outside the 95% ellipse. Altered tissue electric properties were present in 23.5% of males and 15.4% of females. Distribution of impedance vector components in different age categories of healthy Slovak subjects are relevant to comparative population studies and to clinical practice.
Biochemical Characteristics of New Delhi Metallo-β-Lactamase-1 Show Unexpected Difference to Other MBLs

New Delhi metallo-β-lactamase (NDM-1) is a new metallo-β-lactamase (MBL) that has recently emerged as a global threat because it confers bacteria with resistance to almost all clinically used β-lactam antibiotics. To determine the molecular basis of this threat, NDM-1 was purified from Escherichia coli TransB (DE3) carrying cloned blaNDM-1 gene by an anion-exchange chromatography step followed by a gel permeation chromatography step. The purified enzyme was stable even in extremely alkaline buffer (pH 11) and reached its highest activity at a low temperature (15°C), which was different from other MBLs. The 50% inhibition concentration of EDTA against NDM-1 was 412 nM, which showed that NDM-1 was more susceptible to EDTA than other MBLs. The effects of zinc on NDM-1 differed between cephem and carbapenem complexes, but inhibition at high Zn2+ concentration was observed for all of tested β-lactam compounds.
INFERNECE GENERATION SKILL AND TEXT COMPREHENSION

________________ One of the most common findings of recent reading research is that drawing inferences is an essential part of the comprehension process, even among young children (Anderson & Pearson, 1984). Dole et al (1991) argues that inference is at the heart of comprehension process. As they construct their own models of meaning for a given text, readers and listeners alike use inferencing extensively to fill in details omitted in text and to elaborate what they read. The important point is that even the simplest of texts require inferencing. Despite persistent, well-meaning positions that argue for delaying inferential activities until literal comprehension is mastered (e.g., you need to get the facts straight before you can reason beyond the text), both basic and applied reading research supports a strong emphasis on inferential strategies from the beginning of instruction. The present paper has explored the factors affecting the generation of inferences by readers as well as the reasons for their inference failure. Some instructional techniques and strategies for the development of inferential skill is provided.
The Remote Rendering Pipeline - Managing Geometry and Bandwidth in Distributed Virtual Environments

The contribution of this thesis is at the place where interactive 3-D computer graphics and distributed systems meet. Virtual Environments are concerned with the convincing simulation of a virtual world. One of the most promising aspects of this approach lies in its potential as a way of bringing people together, as a virtual meeting place. To overcome current restrictions in network performance and bandwidth, techniques that have already been used for improving the rendering performance for virtual reality applications can be adopted and enhanced. In this context, we develop the concept of the Remote Rendering Pipeline, that extends the traditional rendering pipeline for interactive graphics to include the network transmission of geometry data. By optimizing the steps of the Remote Rendering Pipeline, and combining these improvements, a system that is better prepared to deal with complex and interesting virtual worlds emerges. After a discussion of the state of the art in the fields of interactive 3-D graphics and distributed virtual environments, the Remote Rendering Pipeline is introduced, a conceptual model of rendering in distributed systems. Its elements are discussed in the following chapters: the demanddriven geometry transmission protocol, a strategy for managing partially replicated geometry databases for virtual environments; an octree-based level of detail generator; smooth levels of detail, a novel data structure for incremental encoding and transmission of polygonal objects; and a modeling and rendering toolkit for directed cyclic graphs allowing a compact representation of a large class of natural phenomena.
Despeckling of interferometrie SAR data

This paper presents speckle noise removal from synthetic aperture radar data. A novelty in this paper is removing of speckle noise using complex valued SAR data using optimal dual based l1 analysis approach. Paper presents complex valued computation of optimal dual frame l1 analysis using quasi Newton approach. Complex valued regularization is performed using single polarized SAR image and interferometric pair. It was shown that quasi Newton complex valued estimation of single SAR image does not influence on phase, but changes only amplitude part of complex valued SAR data. The proposed method well suppresses speckle noise from single look SAR images was achieves good results compared with the state of the art methods.
ACHIEVING PREDICTABLE AND SCALABLE PERFORMANCE WITH BCS-MPI

Demand for increasingly-higher computing capability is driving a similar growth in compute cluster sizes, soon to be reaching tens of thousands of processors. This growth is not matched however by system software, which has remained largely unchanged from the advent of clusters. The failure of system software to scale and develop in the same rate as the underlying hardware constrains the productivity of these machines by severely limiting their utilization, reliability, and responsiveness. The traditional approach to system software, namely, the use of loosely-coupled independent daemons on each node, is inadequate for the management of large-scale clusters, a problem which is inherently tightly-coupled and requires a high degree of synchronization. One model for large-scale system software is Buffered Coscheduling (BCS), wherein synchronization and scalability are obtained by means of global scheduling of all system activities and collective network operations. BCS represents a new methodology for the design of system software as a single, parallel program using traditional parallel constructs. As such, system software can be made orders of magnitude more scalable, simple, and easy to debug than the existing distributed solutions. The most important aspect of the BCS model and the overlying system software is the buffering and scheduling of all communication, resulting in highly controllable and deterministic system behavior. This chapter describes in detail the implementation of BCS-MPI, an MPI library designed after this model, and shows that the benefits of determinism need not come at a significant performance cost. Furthermore, BCS-MPI comes with a sophisticated monitoring and debugging subsystem that simplifies the analysis of system and application performance, and is covered in detail in this chapter.
Speedup of Distributed Programson a Network of Shared

This paper presents an alternative to process migration , called competition, to speed up distributed programs in the background on a network of processors. Competition protocols are transparent operating system facilities that involve creating multiple instances (called clones) p 1 , p 2 , etc. of a process P on diier-ent processors, and making clones \compete", i.e., attempting to guarantee that the output of the clone that is farthest \ahead" is fed to the rest of the computation , and that the entire application's performance tracks that of the clone which is farthest ahead. We show that competition protocols ooer performance beneets that are as good as or better than migration protocols for distributed programs under comparable assumptions. We also demonstrate that competition protocols ooer even more speedup for distributed programs than for sequential programs.
2 Retrieval as a Self-limiting Process : Part II

A cross much of the history of systematic research on human memory, three stages critical to the memory process have been postulated: trace formation , trace storage, and trace utilization or retrieval (see, e.g., Melton, 1963). It was not, however, until Tulving and Pearlstone's (1966) seminal study that the fundamental importance of retrieval processes in human memory—and the need to distinguish the conditions affecting storage from those affecting retrieval—became clear. By providing cues to participants during the recall of items from categorized lists, Tulving and Pearlstone were able to demonstrate that what is stored or available in memory cannot be indexed in a precise or reliable way by what is recallable or accessible at a given point in time. Prior to the Tulving and Pearlstone (1966) study, a typical paradigm used by researchers to investigate both storage and retrieval processes was to ask participants to recall all the items they could following the presentation of different types of lists, and it was simply assumed that what was recalled reflected what information had been successfully stored and, furthermore, how that information was organized in memory. Items on a list that are semantically related tend to be recalled together, for example, even if they are presented at disparate positions in the list, which was taken as evidence that interitem associations formed at the time of storage then guided the retrieval process at the time of recall. In other words, the retrieval process underlying recall was thought to be self-propagating: The recall of one item triggers the recall of a next, associated item, which triggers the recall of yet another item, and so forth. Such a self-propagating property was— and still is, to a large extent—intrinsic to associative and organizational theories of the recall process. In J. R. Anderson's (1972) model of recall, for example, it was assumed that to-be-learned items, such as a list of randomly presented words, are associated with each other at the time of study and that a participant's later recall of the list is guided and sustained by such interitem associations. In other words, the items
Sliding mode control system design using parallel feedforward compensator

In this paper, the design method of sliding mode control (SMC) system for single-input single-output (SISO) linear system is discussed. First, we consider the similarity between the design method of sliding mode hyper plane using the strict positive realness and the characteristics of zeros of feedback system and the design method of simple adaptive control. Based on such a consideration, we propose the new design method of SMC system using parallel dynamic compensator. As a result, SMC system can be constructed only with the derivative of output signal for controlled plant. Furthermore, the sliding mode servo control (SMSC) system design based on proposed scheme is also discussed. The performance of proposed SMC system and SMSC system are confirmed through the experiments and numerical example, respectively.
Apparatus for Histological Validation of In Vivo and Ex Vivo Magnetic Resonance Imaging of the Human Prostate

This article describes apparatus to aid histological validation of magnetic resonance imaging studies of the human prostate. The apparatus includes a 3D-printed patient-specific mold that facilitates aligned in vivo and ex vivo imaging, in situ tissue fixation, and tissue sectioning with minimal organ deformation. The mold and a dedicated container include MRI-visible landmarks to enable consistent tissue positioning and minimize image registration complexity. The inclusion of high spatial resolution ex vivo imaging aids in registration of in vivo MRI and histopathology data.
On the Use of Homogenous Sets of Subjects in Deceptive Language Analysis

Recent studies on deceptive language suggest that machine learning algorithms can be employed with good results for classification of texts as truthful or untruthful. However, the models presented so far do not attempt to take advantage of the differences between subjects. In this paper, models have been trained in order to classify statements issued in Court as false or not-false, not only taking into consideration the whole corpus, but also by identifying more homogenous subsets of producers of deceptive language. The results suggest that the models are effective in recognizing false statements, and their performance can be improved if subsets of homogeneous data are provided.
Real-time analysis and visualization of online social media dynamics

Social network emanates from socially interacting entities that are represented as nodes with identical properties. These nodes are interconnected through different forms of relationship among them. Social network analysis (SNA) establishes interactions and defines the relationships on basis of theoretical foundation of networks and graphs. Social media involves in exploring several ways people share ideas and information through mobile devices, e-mail, posts, microblogging etc. Connection among users gets strengthened as they like, dislike, follow, tweet, tag, or comment over the shared idea. Various network parameters are employed to analyze the real time datasets generated from online social media such as Twitter via application programming interfaces.
Recent advances in Operational Phytoplankton Monitoring System Alg@line

Alg@line is a forerunner in the field of monitoring research using commercial ferries. In 1992 the Finnish Institute of Marine Research started systematic measurements on board ferry Finnjet, crossing the Baltic Sea Proper, using unattended recording and sampling system. Alg@line co-operation project nowadays uses several approaches to integrate operationally ecological and environmental information of the Baltic Sea such as chlorophyll-a and turbidity observations with flow through systems and MODIS satellite monitoring for the water quality.