Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving Dependency Ambiguity of Subordinate Clauses using Support Vector Machines

— In this paper, we propose a method of resolving dependency ambiguities of Korean subordinate clauses based on Support Vector Machines (SVMs). Dependency analysis of clauses is well known to be one of the most difficult tasks in parsing sentences, especially in Korean. In order to solve this problem, we assume that the dependency relation of Korean subordinate clauses is the dependency relation among verb phrase, verb and endings in the clauses. As a result, this problem is represented as a binary classification task. In order to apply SVMs to this problem, we selected two kinds of features: static and dynamic features. The experimental results on STEP2000 corpus show that our system achieves the accuracy of 73.5%.
Estimation of suspended sediment concentration and yield using linear models, random forests and quantile regression forests

For sediment yield estimation, intermittent measurements of suspended sediment concentration (SSC) have to be interpolated to derive a continuous sedigraph. Traditionally, sediment rating curves (SRCs) based on univariate linear regression of discharge and SSC (or the logarithms thereof) are used but alternative approaches (e.g. fuzzy logic, artificial neural networks, etc.) exist. This paper presents a comparison of the applicability of traditional SRCs, generalized linear models (GLMs) and non‐parametric regression using Random Forests (RF) and Quantile Regression Forests (QRF) applied to a dataset of SSC obtained for four subcatchments (0·08, 41, 145 and 445 km2) in the Central Spanish Pyrenees. The observed SSCs are highly variable and range over six orders of magnitude. For these data, traditional SRCs performed inadequately due to the over‐simplification of relating SSC solely to discharge. Instead, the multitude of acting processes required more flexibility to model these nonlinear relationships. Thus, alternative advanced machine learning techniques that have been successfully applied in other disciplines were tested. GLMs provide the option of including other relevant process variables (e.g. rainfall intensities and temporal information) but require the selection of the most appropriate predictors. For the given datasets, the investigated variable selection methods produced inconsistent results. All proposed GLMs showed an inferior performance, whereas RF and QRF proved to be very robust and performed favourably for reproducing sediment dynamics. QRF additionally provides estimates on the accuracy of the predictions and thus allows the assessment of uncertainties in the estimated sediment yield that is not commonly found in other methods. The capabilities of RF and QRF concerning the interpretation of predictor effects are also outlined. Copyright © 2008 John Wiley & Sons, Ltd.
Spectrophotometric Determination of Cardiovascular Drugs

Simple, sensitive, accurate and precise spectrophotometric methods for quantitative determination of cardiovascular drugs viz., Dobutamine Hydrochloride (DOB), Ramipril (RAM), Telmisartan (TEL), Verapamil Hydrochloride (VER) were developed. The method of each drug depends upon oxidation of drugs by Ce (IV) (Excess) and estimating the amount of un reacted Ce (IV) by amaranth dye at 523nm. The calibration curves obeyed Beer’s law over the concentration range of 1.6-12μg ml -1 (DOB), 8-56 μg ml -1 (RAM), 2-14 μg ml -1 (TEL) & 2-12 μg ml -1 (VER). The method has been validated in terms of guidelines of ICH and has been applied to analysis of pharmaceuticals.
Locus Ceruleus Degeneration Promotes Alzheimer Pathogenesis in Amyloid Precursor Protein 23 Transgenic Mice

Locus ceruleus (LC) degeneration and loss of cortical noradrenergic innervation occur early in Alzheimer’s disease (AD). Although this has been known for several decades, the contribution of LC degeneration to AD pathogenesis remains unclear. We induced LC degeneration with N-(2-chloroethyl)-N-ethyl-bromo-benzylamine (dsp4) in amyloid precursor protein 23 (APP23) transgenic mice with a low amyloid load. Then 6 months later the LC projection areas showed a robust elevation of glial inflammation along with augmented amyloid plaque deposits. Moreover, neurodegeneration and neuronal loss significantly increased. Importantly, the paraventricular thalamus, a nonprojection area, remained unaffected. Radial arm maze and social partner recognition tests revealed increased memory deficits while high-resolution magnetic resonance imaging-guided micro-positron emission tomography demonstrated reduced cerebral glucose metabolism, disturbed neuronal integrity, and attenuated acetylcholinesterase activity. Nontransgenic mice with LC degeneration were devoid of these alterations. Our data demonstrate that the degeneration of LC affects morphology, metabolism, and function of amyloid plaque-containing higher brain regions in APP23 mice. We postulate that LC degeneration substantially contributes to AD development.
The Impact of Class Size and Number of Students on Outcomes in Higher Education.

Numerous studies have investigated the impact of class size on student outcomes. This analysis contributes to this discussion by examining the impact of class size on student outcomes in higher education. Additionally, this paper investigates the importance of student load (total number of students taught across all courses) in educational outcomes. We find that both class size and student load negatively impact student assessments of courses and instructors. Large classes and heavy student loads appear to prompt faculty to alter their courses in ways deleterious to students.
Resource contention detection and management for consolidated workloads

Public and private cloud computing environments typically employ virtualization methods to consolidate application workloads onto shared servers. Modern servers typically have one or more sockets each with one or more computing cores, a multi-level caching hierarchy, a memory subsystem, and an interconnect to the memory of other sockets. While resource management methods may manage application performance by controlling the sharing of processing time and input-output rates, there is generally no management of contention for virtualization kernel resources or for the memory hierarchy and subsystems. Yet such contention can have a significant impact on application performance. Hardware platform specific counters have been proposed for detecting such contention. We show that such counters are not always sufficient for detecting contention. We propose a software probe based approach for detecting contention for shared platform resources and demonstrate its effectiveness. We show that the probe imposes a low overhead and is remarkably effective at detecting performance degradations due to inter-VM interference over a wide variety of workload scenarios. Our approach supports the management of workload placement on shared servers and pools of shared servers.
Towards Trustworthy Virtualisation Environments : Xen Library OS Security Service Infrastructure

New cost effective commodity PC hardware now includes fully virtualisable processors and the Trusted Computing Group’s trusted platform module (TPM). T his provides the opportunity to combine virtualisation, trusted computing and open source softwar e development to tackle the security challenges modern computing faces. We believe that leveraging this tec hnology to partition critical operating system services and applications into small modules with stric tly controlled interactions is a good way to improve trustworthiness. To support the development of small applications running in Xe domains we built a library OS. We ported the GNU cross-development tool chain and standard C l ibraries to the small operating system kernel included with the Xen distribution, and wrote an inte r-domain communications (IDC) library for communications between Xen domains. To confirm the usabilit y of our library OS we ported a software TPM to run on it as a typical application. We evaluated the per formance of our IDC system and showed that it has good performance for the applications we envisag e. We have shown that a lightweight library OS offers a convenie nt and practical way of reducing the trusted computing base of applications by running secur ity sensitive components in separate Xen domains.
Shot noise process and pricing of extreme insurance claims in an economic environment

We consider the classical Compound Poisson model of insurance risk for extreme events, with the additional economic assumption of a positive interest rate. We note a duality result relating the accumulated aggregate claims and the shot noise process so we apply the piecewise deterministic Markov processes theory. It is assumed that the claim arrival process follows the Poisson process and the claim sizes are assumed to be Loggamma, Frechet and truncated Gumbel to deal with large losses in practice. In order to obtain an arbitrage-free premium, we use an equivalent martingale probability measure obtained via the Esscher transform. In the cases of Loggamma and Frechet distributions for claim sizes, which allow us to derive the explicit forms for the insurance premium calculations, we find that the arbitrage-free premiums can only be obtained by levying the loading in terms of claim arrival rate, not in terms of claim size measure. It is due to the non- existence of the Laplace transforms of Loggamma and Frechet distributions for claim sizes after changing measure. We find that if claim size follows a truncated Gumbel distribution, the security loading can be levied either in terms of claim arrival rate or in terms of claim size measure (or both). However it is not possible for us to obtain the explicit form for the insurance premium calculation. Using the analytical/explicit forms for three dierent claim size distributions, we also provide the several numerical examples.
Intrusion tolerant serializability for transaction-based SAN environments

The serializability of transactions is among the properties that should be implemented in order to ensure the correct processing in transaction-based environments. When the system is compromised, the serializability in addition to the relevant properties of transaction-based environments may be affected. Ensuring the serializability of transactions in compromised systems is among the needs in order to enable the processing of interrelated transactions and avoiding blocking situations with the inability of committing transactions or some available sub-transactions. In this context, this paper proposes an approach to ensure an intrusion tolerant serializability in a compromised transaction-based environment. This approach is built on a new concept that is based on the definition and the use of virtual nodes instead of the detected malicious nodes. These virtual entities ensures the processing of transactions and sub transactions in a secure manner even if the running environment is compromised. They ensure the continuous running of transactions without experimenting the blocking of interleaved transactions and therefore to ensure the serializability even if the monitored system is compromised. A serial schedule graph is also generated and used by the Central Security Node in order to make decisions concerning the nodes and the set of data and transactions that are threatened by a malicious activity by attaching to each component a set of security parameters. The behavior of the proposed intrusion tolerant serializability scheme in addition to its efficiency is illustrated through a case study describing a SAN system that ensures the monitoring of cars activity and generates infractions and warning messages on road in order to prevent the occurrence of car accidents.
An asynchronous and secure ascending peer-to-peer auction

In recent years, auctions have become a very popular price discovery mechanism. Among them, second-price auctions are of theoretical importance, as they have the simple dominant strategy of bidding ones true valuation. Sellers, however, are reluctant to do so, as a malicious auctioneer could take advantage of this knowledge. Several distributed auction mechanisms have been suggested that make it possible to determine the auction outcome without revealing the winner's valuation of the good; however, they are only suitable for sealed-bid auction.This paper suggests a distributed mechanism for ascending second price auctions. The auction protocol has the ability to preserve the privacy of the winning bidder's true valuation or highest bid, respectively, with a high probability. The auction protocol is based on a high number of auctioneers that are distributed to several groups. A bidder generates an encrypted chain of monotonously increasing bidding steps, where each bidding step can be decrypted by a different auctioneer group reducing the possibilities of manipulation for malicious auctioneers. Another fundamental advantage of this secure approach is that bidders need not be online except for submitting their bid chain to the auctioneers.
Definitions of engagement in human-agent interaction

We give an overview of engagement in human-agent interaction. We discuss the different definitions of engagement in human and social science, specify how they relate to certain other concepts, and give an overview of the high level behaviour that is often associated with engagement. This work serves to position our future research on engagement in human-agent interaction.
Sequential and parallel algorithms for mixed packing and covering

We describe sequential and parallel algorithms that approximately solve linear programs with no negative coefficients (aka mixed packing and covering problems). For explicitly given problems, our fastest sequential algorithm returns a solution satisfying all constraints within a 1/spl plusmn//spl epsi/ factor in O(mdlog(m)//spl epsi//sup 2/) time, where m is the number of constraints and d is the maximum number of constraints any variable appears in. Our parallel algorithm runs in time polylogarithmic in the input size times /spl epsi//sup -4/ and uses a total number of operations comparable to the sequential algorithm. The main contribution is that the algorithms solve mixed packing and covering problems (in contrast to pure packing or pure covering problems, which have only "/spl les/" or only "/spl ges/" inequalities, but not both) and run in time independent of the so-called width of the problem.
Adaptive Evolutionary Artificial Neural Networks for Pattern Classification

This paper presents a new evolutionary approach called the hybrid evolutionary artificial neural network (HEANN) for simultaneously evolving an artificial neural networks (ANNs) topology and weights. Evolutionary algorithms (EAs) with strong global search capabilities are likely to provide the most promising region. However, they are less efficient in fine-tuning the search space locally. HEANN emphasizes the balancing of the global search and local search for the evolutionary process by adapting the mutation probability and the step size of the weight perturbation. This is distinguishable from most previous studies that incorporate EA to search for network topology and gradient learning for weight updating. Four benchmark functions were used to test the evolutionary framework of HEANN. In addition, HEANN was tested on seven classification benchmark problems from the UCI machine learning repository. Experimental results show the superior performance of HEANN in fine-tuning the network complexity within a small number of generations while preserving the generalization capability compared with other algorithms.
An Evolutionary Algorithm for Uncertain Optimization Problems

In order to model uncertain optimization problems, fuzzy expected value programming and chance-constrained programming are formulated. Firstly, the method of fuzzy simulation is used to generate training samples for neural network, and the neural network is embedded into PSO to design a hybrid intelligent algorithm. Then, the death penalty function is adopted to deal with the constraints. Finally, some numerical examples are provided to illustrate the feasibility and effectiveness of the algorithm. Keywords-Uncertain optimization; Neural network; Fuzzy simulation; Particle swarm optimization
The Effect of Reading Motivations of 6th, 7th and 8th Grade Students on Reading Attitudes: A Structural Equation Modeling

Article History: Received 14.12. 2017 Received in revised form 13.02. 2018 Accepted 20.02. 2018 Available online 27.03. 2018 In this study, it was aimed to analyze the reading motivations of 6th, 7th and 8th graders on reading attitudes through structural equation modeling, as well as their reading attitudes and motivations in terms of different variables. In the research carried out by the relational and descriptive scanning model, the study group formed by simple random sampling consisted of 349 6th, 7th and 8th grade students. The Survey of Adolescent Reading Attitudes (SARA) developed by Baştuğ and Keskin (2013) and the Motivations for Reading Questionnaire (MRQ) adapted to Turkish by Durmuş (2014) were used in the collection of the data. As a result of the research, it has been found that hypothesis model is valid and reading motivation directly and significantly affects the reading attitude, but it does not have a direct effect on the reading attitude. In addition, 50% of the reading attitude has been explained by reading motivation. However, it has been determined that reading motivations and attitudes of 6th, 7th, and 8th graders are different in terms of gender and class level variables. © 2018 IOJES. All rights reserved
History on the implementation and compilation of Prolog

Prolog, abbreviation for PROgrammation en LOGique, was designed in 1972 by Philippe Roussel, Alain Colmerauer at the University of AixMarseille and Robert Kowalski at the University of Edinburgh [1]. Since 1972, Prolog has been one of the most popular logical programming language based on Horn clause logic. Intrigued by the interesting history of Prolog, I decided to learn the nature of the design and implementation of Prolog interpreter/compiler. Warren Abstract Machine (WAM) has become the de facto standard for designing Prolog system since 1983 when it was first invented by Warren. GNU Prolog is a mordern free Prolog system based on WAM and is the first Prolog system which really complicant to ISO starndard for Prolog by 2000. Besides GNU Prolog, there have been lots of other free and comercial Prolog systems since the brith of Prolog in 1972.
On demographic transition, structural change, and economic growth and stagnation

The paper analyzes an economy with an agrarian and an industrial sector. Demand is determined by Engel's Law. Population growth follows a non‐linear income dependent path according to the theory of demographic transition. In case of decreasing returns to scale in the agrarian sector the existence of a stable low‐income equilibrium with high population growth can be shown. If this equilibrium is globally unstable, the system evolves towards a steady‐state of perpetual economic growth and low population growth. The path of demographic transition coincides with a path of structural change from an economy specialized in agriculture to a fully industrialized economy. The introduction of an income dependent savings rate allows the interpretation of the low‐income equilibrium as a limit cycle and, therefore, the explanation of high fluctuations in population growth and per capita income in least developed economies.
Intrinsic Functional-Connectivity Networks for Diagnosis: Just Beautiful Pictures?

Resting-state functional connectivity has become a topic of enormous interest in the Neuroscience community in the last decade. Because resting-state data (1) harbor important information that often is diagnostically relevant and (2) are easy to acquire, there has been a rapid increase in the development of a variety of network analytic techniques for diagnostic applications, stimulating methodological research in general. While we are among those who welcome the increased interest in the resting state and multivariate analytic tools, we would like to draw attention to some entrenched practices that undermine the scientific quality of diagnostic functional-connectivity research, but whose correction is relatively easy to accomplish. With the current commentary we also hope to benefit the field at large and contribute to a healthy debate about research goals and best practices.
Overview of Robot-Aided Gait Biofeedback and Assessment

Robot-assisted gait training can increase the duration and number of training sessions, whilst reducing the number of therapists required per patient. However, robotic training without therapists lacks feedback required for patient assessment. In this paper, we present results from the literature and our research in order to provide an overview of novel human-centered strategies that enable the robot to support biofeedback and assessment of motor functions. The combination of robot-aided training with robot-aided assessment has a high potential to make future gait therapy easier and increase comfort and efficiency. Broad clinical testing is still required to prove this assumption
An Eight-Element 2–16-GHz Programmable Phased Array Receiver With One, Two, or Four Simultaneous Beams in SiGe BiCMOS

This paper presents an eight-element 2-16-GHz programmable phased array (PPA) receiver in a 0.13-μm SiGe BiCMOS with the reconfigurable number of beams and with the digital beamforming (DBF) capabilities. The eight-element chip can be configured for one, two, or four simultaneous beams or as an element-level DBF receiver. This is achieved using reconfigurable input switching and output combining networks with wideband active switches and combiners. The phased array channel results in a 5-b performance at 3-14 GHz (rms error <;5°) and a 4-b performance at 2-16 GHz (rms error <;8.5°). Each channel also contains a 3-b variable gain amplifier with 8-dB gain control at 2-16 GHz. The chip results in an 8-12-dB gain at 2-16 GHz (depending on the PPA mode), a noise figure (NF) of 12 dB, and an input P1 dB of -20 dBm per channel when all channels are activated. The chip consumes 250 mW per channel, which is competitive knowing its bandwidth and linearity. The DBF function also results in a wideband response with a gain and an NF of 15-16 and 12-13 dB, respectively, and high linearity (input P1 dB = -16 dBm) at 2-16 GHz. The programmable phased array receiver allows a single chip to be used over S-, C-, X-, and Ku-bands for a variety of applications such as satellite communications and point-to-point links. This results in faster and lower-cost phased array development since the same chip and its field-programmable gate array control can be reused from system to system, but with different antenna and grid spacing. The PPA removes the need to develop a different chip for every application and allows the development of phased arrays at commercial scales.
Automated inter-domain security policy generation

Collaborative work needs a flexible secured networking management tool, as virtual teams can be formed and disbanded rapidly. Building a multi-domains security policy is a challenge as far as each domain has to kept total control over its policy. One favorite tool to manage domains is policy based. The hierarchical organization of the policy based management fits the intra-domain one but fail when extended to the inter-domain scope. We present an inter-domain security policies based on the coalition concept and policy abstractions. Such abstractions enable policy designers to focus on communication end-points. However, devices standing on these communications have to be configured. We introduce a method that automatically computes policy required for theses intermediate devices.