Miracle-dz/UniFAR-FTUs huggingface dataset:
Interference suppression in DMT receivers using windowing

A new receiver structure for improving the performance of conventional discrete multitone (DMT) based digital subscriber line (DSL) transceivers is described. In this method, the conventional demodulator consisting of a FFT followed by a scalar frequency-domain equalizer is augmented by an additional data-path utilizing windowing. Time-limited receiver windowing is done independently for each symbol over the orthogonality interval while the transmitter is unchanged. Windowing can be carried out efficiently in the time or frequency domain. A decision feedback equalizer is used to cancel the resulting inter-bin-interference. Computer simulation results are presented for ADSL with realistic interference conditions which show that this method is most effective against narrowband interference and other impairments which lead to diminished inter-bin orthogonality. The overall technique is also applicable to other multi-carrier modems such as VDSL and wireless OFDM.
Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis

Tensor decomposition is a powerful computational tool for multiway data analysis. Many popular tensor decomposition approaches---such as the Tucker decomposition and CANDECOMP/PARAFAC (CP)---amount to multi-linear factorization. They are insufficient to model (i) complex interactions between data entities, (ii) various data types (e.g. missing data and binary data), and (iii) noisy observations and outliers. To address these issues, we propose tensor-variate latent nonparametric Bayesian models, coupled with efficient inference methods, for multiway data analysis. We name these models InfTucker. Using these InfTucker, we conduct Tucker decomposition in an infinite feature space. Unlike classical tensor decomposition models, our new approaches handle both continuous and binary data in a probabilistic framework. Unlike previous Bayesian models on matrices and tensors, our models are based on latent Gaussian or $t$ processes with nonlinear covariance functions. To efficiently learn the InfTucker from data, we develop a variational inference technique on tensors. Compared with classical implementation, the new technique reduces both time and space complexities by several orders of magnitude. Our experimental results on chemometrics and social network datasets demonstrate that our new models achieved significantly higher prediction accuracy than the most state-of-art tensor decomposition
Feature‐Driven Visual Analytics of Chaotic Parameter‐Dependent Movement

Analyzing movements in their spatial and temporal context is a complex task. We are additionally interested in understanding the movements’ dependency on parameters that govern the processes behind the movement. We propose a visual analytics approach combining analytic, visual, and interactive means to deal with the added complexity. The key idea is to perform an analytical extraction of features that capture distinct movement characteristics. Different parameter configurations and extracted features are then visualized in a compact fashion to facilitate an overview of the data. Interaction enables the user to access details about features, to compare features, and to relate features back to the original movement. We instantiate our approach with a repository of more than twenty accepted and novel features to help analysts in gaining insight into simulations of chaotic behavior of thousands of entities over thousands of data points. Domain experts applied our solution successfully to study dynamic groups in such movements in relation to thousands of parameter configurations.
Equivalency? An Analysis of the AACS General Cosmetic Surgery Fellowship Through the Lens of the ACGME 6 Core Competencies

The American Academy of Cosmetic Surgeons (AACS) and American Board of Cosmetic Surgery (ABCS) have developed a 1-year fellowship program in cosmetic surgery with a pathway for board certification. However, attempts by ABCS physicians to advertise as “board certified cosmetic surgeons” have been met with resistance in some states, claiming that this training is not equivalent in scope, content, and duration to training accredited by the Accreditation Council of Graduate Medical Education (ACGME). This has led us to examine the AACS Cosmetic Surgery Fellowship through the lens of the ACGME 6 core competencies and milestones. We conclude that the AACS General Cosmetic Surgery Fellowship meets the ACGME core competencies. Medical knowledge and patient care are the competencies in which it is easiest to demonstrate equivalency to training accredited by the ACGME. Professionalism, systems-based practice, interpersonal communication skills, and practice-based learning are met, although they are more challenging to document. This problem is no different from that faced by ACGME-accredited residency programs and fellowships, who have also found it difficult to measure the competencies independently of one another in a meaningful way.
Microcomputations as Micropayments in Web-based Services

In this article, we propose a new micropayment model for nonspecialized commodity web-services based on microcomputations. In our model, a user that wishes to access online content (offered by a website) does not need to register or pay to access the website; instead, he will accept to run microcomputations on behalf of the service provider in exchange for access to the content. These microcomputations can, for example, support ongoing computing projects that have clear social benefits (e.g., projects relating to medical research) or can contribute towards commercial computing projects. We analyze the security and privacy of our proposal and we show that it preserves the privacy of users. We argue that this micropayment model is economically and technically viable and that it can be integrated in existing distributed computing frameworks (e.g., the BOINC platform). In this respect, we implement a prototype of a system based on our model and we deploy our prototype on Amazon Mechanical Turk to evaluate its performance and usability given a large number of users. Our results show that our proposed scheme does not affect the browsing experience of users and is likely to be used by a non-trivial proportion of users. Finally, we empirically show that our scheme incurs comparable bandwidth and CPU consumption to the resource usage incurred by online advertisements featured in popular websites.
A novel approach for optimal allocation of fault current limiter in distribution system via combination of particle swarm optimization algorithm and genetic algorithm (PSOGA)

Nowadays, power systems expansions are undeniable due to increase in power demands. This fact has caused the increase in short circuit level of power networks. So that, The occurrence of short circuit in such networks results in a large short circuit current throughout the system, which may exceed the rating of existing circuit breakers and damage power system equipments. There are some approaches to reduce and suppress this fault current such as power network reinforcement, equipment rating update, utilization of fault current limiter (FCLs) in power system and etc. Because of difficulty and non economic justification in some cases of power network reinforcement, the utilization of FCLs is effective way to limit and suppress fault currents. FCLs utilization have many benefits, such as power network reliability improvement, voltage stability and short circuit current limitation. But this effectiveness depends on rating, number and installation location of FCLs. In this paper, the authors providing a heuristic optimization algorithm that combined particle swarm optimization algorithm (PSO) and genetic algorithm (GA) so that has more effectiveness rather than both of PSO and GA to determine the optimal rating, number and location of FCLs to improve the power network reliability and fault current reduction. IEEE 30 bus system and IEEE 34 node system are considered to evaluate the effectiveness and feasibility of the proposed method. The objective functions considered for the optimal allocation are reliability of power system, economical impact and short circuit current reduction.
Smart Power technologies on SOI

This paper gives a summary on SOI based Smart Power technologies. The benefit of SOI is explained by reviewing the basic power device concepts. SOI enables full dielectric isolation of devices. In power applications this can be used to build products with improved EMC, improved robustness. Another dominant aspect is that devices can be biased above the supply voltage or below the ground voltage, without suffering from electrical overstress or the trigger of parasitic transistors. It also enables the integration of minority carrier devices into an integrated circuit. NXP uses those benefits in the SOI based technologies, like A-BCD (for medium voltages) and EZ HV (for high voltages). Other semiconductor manufacturers use the SOI for similar reasons, or extend the voltage range of their baseline technology. Main drawback of SOI is the relative high price of the starting material.
The Utility of the SAT ® I and SAT II for Admissions Decisions in California and the Nation

Researchers are encouraged to freely express their professional judgment. Therefore, points of view or opinions stated in College Board Reports do not necessarily represent official College Board position or policy. The College Board is a national nonprofit membership association dedicated to preparing, inspiring, and connecting students to college and opportunity. Founded in 1900, the association is composed of more than 4,200 schools, colleges, universities, and other educational organizations. Each year, the College Board serves over three million students and their parents, 22,000 high schools, and 3,500 colleges through major programs and services in college admissions, guidance, assessment, financial aid, enrollment , and teaching and learning. Among its best-known programs are the SAT ® , the PSAT/NMSQT ® , and the Advanced Placement Program ® (AP ®). The College Board is committed to the principles of equity and excellence, and that commitment is embodied in all of its programs, services, activities, and concerns.
Blind Channel Estimation for SIMO OFDM Systems without Cyclic Prefix

In sacrificing the bandwidth efficiency, the insertion of cyclic prefix (CP) is used in OFDM system to combat ISI and allow for a simple one-tap equalization scheme. In this paper, the OFDM system without CP equipped with multiple antennas at the receiver is studied. Without ignoring the ISI components, the subspace channel estimation and MMSE equalizers are proposed. Besides, due to the block Toeplitz structure of channel matrix, the block matrix scheme is developed to increase several times of sample vectors, which results in better performance of subspace channel estimation in a finite sample scenario. The computational complexity of the proposed method increases slightly over the conventional subspace method. Computer simulations are given to verity the effectiveness of the proposed methods
Political Participation in Hong Kong: The Roles of News Media and Online Alternative Media

Different types of media use exert distinctive influences over political participation of various forms. Drawing on the O-S-R-O-R (Orientation–Stimulus–Reasoning–Orientation–Response) model of political communication effects, this study proposes a theoretical model to connect traditional news media use and online alternative media use to both institutional and noninstitutional forms of political participation. The framework integrates internal efficacy and political satisfaction as mediators to explain the indirect processes from media use to political participation. Findings from a survey of representative Hong Kong adults suggest that news media use and alternative media use can influence political participation in different ways. Specifically, traditional news media play the role of an efficacy facilitator to boost institutional and noninstitutional political participation, whereas online alternative media mainly serve as a political dissatisfaction amplifier to fuel citizens’ noninstitutional political participation, such as protest participation.
Sm/Lsm Genes Provide a Glimpse into the Early Evolution of the Spliceosome

The spliceosome, a sophisticated molecular machine involved in the removal of intervening sequences from the coding sections of eukaryotic genes, appeared and subsequently evolved rapidly during the early stages of eukaryotic evolution. The last eukaryotic common ancestor (LECA) had both complex spliceosomal machinery and some spliceosomal introns, yet little is known about the early stages of evolution of the spliceosomal apparatus. The Sm/Lsm family of proteins has been suggested as one of the earliest components of the emerging spliceosome and hence provides a first in-depth glimpse into the evolving spliceosomal apparatus. An analysis of 335 Sm and Sm-like genes from 80 species across all three kingdoms of life reveals two significant observations. First, the eukaryotic Sm/Lsm family underwent two rapid waves of duplication with subsequent divergence resulting in 14 distinct genes. Each wave resulted in a more sophisticated spliceosome, reflecting a possible jump in the complexity of the evolving eukaryotic cell. Second, an unusually high degree of conservation in intron positions is observed within individual orthologous Sm/Lsm genes and between some of the Sm/Lsm paralogs. This suggests that functional spliceosomal introns existed before the emergence of the complete Sm/Lsm family of proteins; hence, spliceosomal machinery with considerably fewer components than today's spliceosome was already functional.
Eliminating NULLs with Subsumption and Complementation

In a data integration process, an important step after schema matching and duplicate detection is data fusion. It is concerned with the combination or merging of different representations of one real-world object into a single, consistent representation. In order to solve potential data conflicts, many different conflict resolution strategies can be applied. In particular, some representations might contain missing values (NULL-values) where others provide a non-NULL-value. A common strategy to handle such NULL-values, is to replace them with the existing values from other representations. Thus, the conciseness of the representation is increased without losing information. Two examples for relational operators that implement such a strategy are minimum union and complement union and their unary building blocks subsumption and complementation. In this paper, we define and motivate the use of these operators in data integration, consider them as database primitives, and show how to perform optimization of query plans in presence of subsumption and complementation with rule-based plan transformations. 1 Data Fusion as Part of Data Integration Data integration can be seen as a three-step process consisting of schema matching, duplicate detection and data fusion. Schema matching is concerned with the resolution of schematic conflicts, for instance through schema matching and schema mapping techniques. Next, duplicate detection is concerned with resolving conflicts at object level, in particular detecting two (or more! ) representations of same real-world objects, called duplicates. For instance, considering two data sources describing persons, schema matching determines that the concatenation of the attributes firstname and lastname in Source 1 is semantically equivalent to the attribute name in Source 2. Duplicate detection then recognizes that the entry John M. Smith in Source 1 represents the same person as the entry J. M. Smith in Source 2. This article focuses on the step that succeeds both schema matching and duplicate detection, namely data fusion. This final step combines different representations of the same real-world object (previously identified Copyright 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering
A high efficiency Hardware Trojan detection technique based on fast SEM imaging

In the semiconductor market where more and more companies become fabless, malicious integrated circuits' modifications are seen as possible threats. Those Hardware Trojans can have various effects and can be implemented by different entities with different means. This article includes the integration of an almost automatic Hardware Trojan detection. The latter is based on a visual inspection implemented within the integrated circuit life cycle. The proposed detection methodology is quite efficient regarding tools, user experience and time needed. A single layer of the chip is accessed and then imaged with a Scanning Electron Microscope (SEM). The acquisition of several hundred images at high magnification is automated as does the images registration. Then depending on the reference availability, one can check if any supplementary gates have been inserted in the design using a golden reference or a graphic/text design file. Depending on the reference, either basic image processing is used to compare the chip extracted image with a golden model or some pattern recognition can be used to retrieve the number of occurrences of each standard cell. The depicted methodology aims to detect any gate modification, substitution, removal or addition and so far require an invasive approach and a reference.
Augmented reality in surgery.

OBJECTIVE To evaluate the history and current knowledge of computer-augmented reality in the field of surgery and its potential goals in education, surgeon training, and patient treatment. DATA SOURCES National Library of Medicine's database and additional library searches. STUDY SELECTION Only articles suited to surgical sciences with a well-defined aim of study, methodology, and precise description of outcome were included. DATA SYNTHESIS Augmented reality is an effective tool in executing surgical procedures requiring low-performance surgical dexterity; it remains a science determined mainly by stereotactic registration and ergonomics. Strong evidence was found that it is an effective teaching tool for training residents. Weaker evidence was found to suggest a significant influence on surgical outcome, both morbidity and mortality. No evidence of cost-effectiveness was found. CONCLUSIONS Augmented reality is a new approach in executing detailed surgical operations. Although its application is in a preliminary stage, further research is needed to evaluate its long-term clinical impact on patients, surgeons, and hospital administrators. Its widespread use and the universal transfer of such technology remains limited until there is a better understanding of registration and ergonomics.
A method of capturing the Public Mood Levels in emergency based on internet comments

The Web has become an excellent source for gathering and realizing public voice. This paper discusses a method for exploring the public mood levels at the time of posting. Based on the corpus aggregating Internet comments about the emergency during given time intervals, our method can capture the public mood levels in emergency. And then, we define two parameters, Public Mood Level Index and Public Mood Related Strength Index, to express public mood levels evolution characteristic. To this end, we take a first step toward applying these parameters on decision-making in emergency response. Experimental results show our method is feasible.
Performance Analysis of UWB Timing Acquisition Schemes Based on RSS Measurements

The paper focuses on the performance analysis of the timing acquisition scheme based on received signal strength (RSS) measurements for ultra-wideband (UWB) communication systems. To our knowledge, few paper discusses the performance of the timing acquisition scheme based on RSS measurements for UWB in details. The timing acquisition scheme based on RSS measurements has many advantages, such as low cost, high speed and robustness. However, low transmission power limitation and complicated indoor multipath propagation environments make it difficult to measure accurate RSS at the receiver and affect the accuracy of the time delay offset estimation for the local template signals. In addition, the time variation of the indoor channel state can form a multiple-to-one mapping relation between the RSS measurements and the distance, which largely limits the method application. In the paper, we analyze the accuracy of time delay offset estimation for this method by deriving the Cramer-Rao lower bound (CRLB). The number results show that the accuracy of the timing acquisition method based on RSS measurements suffers from both the UWB signal transmission speed and the varying distance between the transmitter and receiver. It is noted that though the accuracy of the method can hardly fulfil the fine timing acquisition requirement for UWB systems, it will largely reduce the coarse timing acquisition time and improve the performance for UWB timing acquisition systems if combined with other timing acquisition ones
Bullying Victimisation and Risk of Psychotic Phenomena

• Users may freely distribute the URL that is used to identify this publication. • Users may download and/or print one copy of the publication from the University of Birmingham research portal for the purpose of private study or non-commercial research. • User may use extracts from the document in line with the concept of ‘fair dealing’ under the Copyright, Designs and Patents Act 1988 (? ) • Users may not further distribute the material nor use it for the purposes of commercial gain.
Algorithms for Propositional KB Approximation

One of the obstacles to the effective compilation of propositional knowledge bases (KBs) using Hom approximations, as introduced by (Selman & Kautz 1991), is the lack of computationally feasible methods for generating Hom bounds. In this paper new algorithms for generating Hom Greatest Lower Bounds (GLB) that can apply to large size KBs, are presented. The approach is extended through a more general target language: the renamable Hom class. The conditions under which a renamable Hom formula is a renamable Hom GLB of a KB are established and algorithms for computing it are derived. These algorithms can be used in the other approaches based on computation of Hom or renamable lower bounds as (Boufkhad et al. 1997). The efficiency of these algorithms and the tightness with respect to the KB in terms of number of models of the bounds, are experimentally evaluated. The renamable Hom GLB proves to be closer to the KB than the Horn GLB.
Spectral Decomposition of Option Prices in Fast Mean-Reverting Stochastic Volatility Models

Using spectral decomposition techniques and singular perturbation theory, we develop a systematic method to approximate the prices of a variety of European and path-dependent options in a fast mean-reverting stochastic volatility setting. Our method is shown to be equivalent to those developed in [J.-P. Fouque, G. Papanicolaou, and R. Sircar, Derivatives in Financial Markets with Stochastic Volatility, Cambridge University Press, Cambridge, UK, 2000] but has the advantage of being able to price options for which the methods of [J.-P. Fouque, G. Papanicolaou, and R. Sircar, Derivatives in Financial Markets with Stochastic Volatility, Cambridge University Press, Cambridge, UK, 2000] are unsuitable. In particular, we are able to price double-barrier options. To our knowledge, this is the first time that double-barrier options have been priced in a stochastic volatility setting in which the Brownian motions driving the stock and volatility are correlated.