Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing Multi-dimensional and Uni-dimensional Computer Adaptive Strategies in Psychological and Health Assessment

This study aimed to compare the efficiencies of multi-dimensional CAT versus uni-dimensional CAT based on the multi-dimensional graded response model and provide information about the optimal size of the item pool. Item selection and ability estimation methods based on multi-dimensional graded response models were developed and two studies, one based on simulated data, the other based on real data, were conducted. Five design factors were manipulated: correlation between dimensions, item pool size, test length, ability level, and number of estimated dimensions. A modest effect due to the correlation between dimensions on the outcome measures was observed, although the effect was found primarily for correlations of 0 versus 0.4. Based on a comparison of the correlation condition equal to zero with correlation conditions greater than zero, the multi-dimensional CAT was more efficient than the uni-dimensional CAT. As expected, ability level had an impact on the outcome measures. A multi-dimensional CAT provided more accurate estimates for those examinees with average true ability values than those with true ability values in the extreme range. The multi-dimensional CAT was over-estimated for examinees with negative true ability values and under-estimated for examinees with positive true ability values. This is consistent with Bayesian estimation methods which "shrink" estimates toward the mean of the prior distribution. As the number of estimated dimensions increased, more accurate estimates were achieved. This supports the idea that the ability of one dimension can be used to augment the information available to estimate ability in another dimension. Finally, larger item pools and longer tests yielded more accurate and reliable ability estimation, although greater difference in efficiency was realized when comparing shorter tests and smaller item pools.Information on the optimal item pool size was provided by plotting the outcome measures versus the item pool size. The plots indicated that, for short tests, the optimal item pool size was 20 items; for longer test, the optimal item pool size was 50 items. However, if item exposure control or content balancing were an issue, a larger item pool would be needed to achieve the same efficiency in ability estimates.
Finite time stability analysis for nonlinear fractional order differential systems

The finite time stability of nonlinear fractional order differential systems is investigated in this paper. Two versions of finite time stability of Lyapunov theorem for nonlinear fractional order differential systems are proposed. Based on the fractional order extension of Lyapunov method, the finite time stability problem is studied for nonlinear fractional order differential systems, and several stability results are obtained. Via the fractional Lyapunov method by the class-K functions, some sufficient conditions of finite time stability for nonlinear fractional order differential systems are presented. The main results improve the existing results on the finite time stability of general dynamic systems. An illustrative example is provided to illustrate the main results.
Making AC-3 an Optimal Algorithm

The AC-3 algorithm is a basic and widely used arc consistency enforcing algorithm in Constraint Satisfaction Problems (CSP). Its strength lies in that it is simple, empirically efficient and extensible. However its worst case time complexity was not considered optimal since the first complexity result for AC-3 [Mackworth and Freuder, 1985] with the bound O(ed3), where e is the number of constraints and d the size of the largest domain. In this paper, we show suprisingly that AC-3 achieves the optimal worst case time complexity with O(ed2). The result is applied to obtain a path consistency algorithm which has the same time and space complexity as the best known theoretical results. Our experimental results show that the new approach to AC-3 is comparable to the traditional AC-3 implementation for simpler problems where AC-3 is more efficient than other algorithms and significantly faster on hard instances.
Exploring Registered Psychiatric Nurses' Responses towards Service Users with a Diagnosis of Borderline Personality Disorder

This study explored registered psychiatric nurses' (RPNs') interactions and level of empathy towards service users with a diagnosis of borderline personality disorder (BPD). A qualitative approach was used, and 17 RPNs were interviewed using a semistructured interview schedule incorporating the “staff-patient interaction response scale” (SPIRS). Four themes emerged following data analysis: “challenging and difficult,” “manipulative, destructive and threatening behaviour,” “preying on the vulnerable resulting in splitting staff and other service users,” and “boundaries and structure. ” Additionally, low levels of empathy were evident in the majority of participants' responses to the SPIRS. The findings provide further insight on nurses' empathy responses and views on caring for service users with BPD and further evidence for the need for training and education for nurses in the care of service users diagnosed with BPD.
Managing Process Model Complexity Via Abstract Syntax Modifications

As a result of the growing adoption of Business Process Management (BPM) technology, different stakeholders need to understand and agree upon the process models that are used to configure BPM systems. However, BPM users have problems dealing with the complexity of such models. Therefore, the challenge is to improve the comprehension of process models. While a substantial amount of literature is devoted to this topic, there is no overview of the various mechanisms that exist to deal with managing complexity in (large) process models. As a result, it is hard to obtain an insight into the degree of support offered for complexity reducing mechanisms by state-of-the-art languages and tools. This paper focuses on complexity reduction mechanisms that affect the abstract syntax of a process model, i.e., the formal structure of process model elements and their interrelationships. These mechanisms are captured as patterns so that they can be described in their most general form, in a language- and tool-independent manner. The paper concludes with a comparative overview of the degree of support for these patterns offered by state-of-the-art languages and tools, and with an evaluation of the patterns from a usability perspective, as perceived by BPM practitioners.
The VACCINE Framework for Building DLP Systems

Conventional Data Leakage Prevention (DLP) systems suffer from the following major drawback: Privacy policies that define what constitutes data leakage cannot be seamlessly defined and enforced across heterogeneous forms of communication. Administrators have the dual burden of: (1) manually self-interpreting policies from handbooks to specify rules (which is error-prone); (2) extracting relevant information flows from heterogeneous communication protocols and enforcing policies to determine which flows should be admissible. To address these issues, we present the Verifiable and ACtionable Contextual Integrity Norms Engine (VACCINE), a framework for building adaptable and modular DLP systems. VACCINE relies on (1) the theory of contextual integrity to provide an abstraction layer suitable for specifying reusable protocol-agnostic leakage prevention rules and (2) programming language techniques to check these rules against correctness properties and to enforce them faithfully within a DLP system implementation. We applied VACCINE to the Family Educational Rights and Privacy Act and Enron Corporation privacy regulations. We show that by using contextual integrity in conjunction with verification techniques, we can effectively create reusable privacy rules with specific correctness guarantees, and check the integrity of information flows against these rules. Our experiments in emulated enterprise settings indicate that VACCINE improves over current DLP system design approaches and can be deployed in enterprises involving tens of thousands of actors.
Nonspecific Esterase Patterns of Rattus norvegicus (Berkenhout, 1769) in Western Turkey

Nonspecific esterases in the muscle, heart, kidney and liver tissues of wild rats (Rattus norvegicus) were examined by horizontal starch gel electrophoresis. Zymogram bands corresponding to Es-10 and Es-4 in the muscle, heart, kidney and liver homogenates, Es-3 and Es-17 in the kidney and liver, Es-18 in the liver tissue, Es-15 in kidney and liver, Es-2 in the muscle and heart, Es-16 in the heart tissue were detected. These findings showed that nonspecific esterases are very polymorphic and tissue-specific, and are not of taxonomic importance for the populations of Rattus norvegicus.
Robust randomized model predictive control for energy balance in smart thermal grids

This paper presents a stochastic model predictive control approach for a thermal grid with uncertainties in the consumer demand profiles. This approach leads to a finite-horizon chance-constrained mixed-integer linear optimization problem at each sampling time, which is in general non-convex and hard to solve. Earlier approaches for such problems are either suboptimal ad-hoc methodologies, or computationally intractable formulations. We provide a unified framework to deal with production planning problems for uncertain systems, while providing a-priori probabilistic certificates for the robustness properties of the resulting solutions. Our methodology is based on solving a random convex optimization problem to compute the uncertainty bounds using the so-called scenario approach and then, solving a robust mixed-integer optimization problem with the computed randomized uncertainty bounds at each sampling time. Using a tractable approximation of uncertainty bounds, the proposed problem formulation retains the complexity of the problem without chance constraints. In the presented thermal grid application this implies that a robust mixed-integer program is solved to provide a day-ahead prediction for the thermal energy production plan in the grid. The performance of the proposed methodology is illustrated using Monte Carlo simulations and employing two different problem formulations: optimization over input sequences (open-loop MPC) and optimization over affine feedback policies (closed-loop MPC).
Channel characteristics of the generalized alpha-mu multipath fading model

In this paper, we consider a relatively new small scale multipath fading model, namely; the α−μ fading distribution. We derive expressions for the amount of fading and the average channel capacity for this channel model and show the generalized attribute of this fading model. The obtained expressions for the performance metrics reduce to other expressions for other channel models as special cases. Numerical results for the obtained expressions are provided and some conclusions are also drawn.
PDM : Programmable Monitoring For Distributed Applications

We have constructed PDM, a Programmable, Distributed Monitoring system for building performance monitoring/analysis, steering, and adaptive systems for larg escale, parallel applications. PDM takes advantage of mobile languages to reduce monitoring overheads and offers new monitoring capabilities. PDM monitoring code is currently written in Tcl. PDM is capable of decomposing and distributing the monitoring code to the nodes in the system where the performance data is generated, thereby reducing the amount of network traffic required to collect monitoring information. Furthermore, PDM scripts can monitor and bound their own resource usage, further reducing monitoring overheads.
Ultrasound-Guided Caudal Epidural Injection Technique

From the Department of Physical Medicine & Rehabilitation, Chang Gung Memorial Hospital, Linkou and Chang Gung University College of Medicine, Tao-Yuan County, Taiwan (CPCC, SFTT); Defense and Veterans Brain Injury Center, Richmond, Virginia (HLL); Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, Virginia (HLL); and John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii (HLL).
Soft computing models to predict daily temperature of Dhaka

Soft computing forecasting tools play an important role to forecast many complicated systems. In this paper, an effort has been made to use soft computing approaches to predict Dhaka daily temperatures for the period of 28 February 1945 to 27 August 2006. We have selected the fuzzy neuro model, the neuro genetic algorithm model as soft computing techniques. To compare results, a popular time series statistical technique, namely autoregressive moving average model is selected and based on error analysis, a suitable model to predict temperature for Dhaka city is proposed. The performance comparisons of different models due to root mean square error, correlation coefficient and coefficient of determination between observed and predicted temperatures indicate that the neuro genetic algorithm model predicts temperatures with maximum accuracy, followed by the fuzzy neuro model. Our believe findings of this paper will be useful for those who are interested about Bangladeshi important atmospheric parameter, namely temperature.
Not-a-Bot: Improving Service Availability in the Face of Botnet Attacks

A large fraction of email spam, distributed denial-of-service (DDoS) attacks, and click-fraud on web advertisements are caused by traffic sent from compromised machines that form botnets. This paper posits that by identifying human-generated traffic as such, one can service it with improved reliability or higher priority, mitigating the effects of botnet attacks. The key challenge is to identify human-generated traffic in the absence of strong unique identities. We develop NAB ("Not-A-Bot"), a system to approximately identify and certify human-generated activity. NAB uses a small trusted software component called an attester, which runs on the client machine with an untrusted OS and applications. The attester tags each request with an attestation if the request is made within a small amount of time of legitimate keyboard or mouse activity. The remote entity serving the request sends tshe request and attestation to a verifier, which checks the attestation and implements an application-specific policy for attested requests. Our implementation of the attester is within the Xen hypervisor. By analyzing traces of keyboard and mouse activity from 328 users at Intel, together with adversarial traces of spam, DDoS, and click-fraud activity, we estimate that NAB reduces the amount of spam that currently passes through a tuned spam filter by more than 92%, while not flagging any legitimate email as spam. NAB delivers similar benefits to legitimate requests under DDoS and click-fraud attacks.
C-Reactive Protein Modifies the Relationship Between Blood Pressure and Microalbuminuria

Abstract—C-reactive protein (CRP) and microalbuminuria reflect intimately related components of the atherosclerotic disease process. Epidemiological studies found only modest associations between CRP and microalbuminuria. Blood pressure, one of the components of the metabolic syndrome in the general population, is the main determinant of microalbuminuria in diabetes and hypertension. We questioned whether CRP modifies the relationship of blood pressure and other cardiovascular risk factors with microalbuminuria in a cross-sectional study in 8592 inhabitants from Groningen, The Netherlands. The crude data showed an increase in the prevalence of microalbuminuria with increasing CRP quartiles (4.8, 9.6, 14.5, and 18.6%, P <0.0001). On stratification for cardiovascular risk factors, the data revealed a significant and positive interaction between mean arterial pressure (MAP) and quartiles of CRP with respect to the risk of microalbuminuria (Wald statistic 9.2, P =0.03). In subjects with a MAP <90 mm Hg, a nonsignificant trend in the association between CRP quartiles and microalbuminuria was found (prevalence: 3.9%, 5.8%, 6.6%, 8.7%; P =0.11). This trend was much steeper and significant in subjects with an MAP >90 mm Hg (prevalence: 6.7%, 13.6%, 20.4%, 25.1%; P <0.0001). Controlling for other risk factors in multivariate analyses, the positive interaction persisted (P =0.0004). No significant interactions between other risk factors and CRP with respect to the risk of microalbuminuria were encountered. Thus, CRP modifies the relation between blood pressure and microalbuminuria.
Characterization of a Live-Attenuated Retroviral Vaccine Demonstrates Protection via Immune Mechanisms

ABSTRACT Live-attenuated retroviruses have been shown to be effective retroviral vaccines, but currently little is known regarding the mechanisms of protection. In the present studies, we used Friend virus as a model to analyze characteristics of a live-attenuated vaccine in protection against virus-induced disease. Highly susceptible mice were immunized with nonpathogenic Friend murine leukemia helper virus (F-MuLV), which replicates poorly in adult mice. Further attenuation of the vaccine virus was achieved by crossing the Fv-1 genetic resistance barrier. The minimum dose of vaccine virus required to protect 100% of the mice against challenge with pathogenic Friend virus complex was determined to be 103 focus-forming units of attenuated virus. Live vaccine virus was necessary for induction of immunity, since inactivated F-MuLV did not induce protection. To determine whether immune cells mediated protection, spleen cells from vaccinated donor mice were adoptively transferred into syngeneic recipients. The results indicated that immune mechanisms rather than viral interference mediated protection.
First Results on Detecting Term Evolutions

The archival of content like publications or web pages is just the first step toward “full” content preservation. It also has to be guaranteed that content can be found and interpreted in the long run. The correspondence between the terminology used for querying and the one used in content objects to be retrieved, is a crucial prerequisite for effective retrieval technology. However, as terminology evolves over time, a growing gap opens between older documents in (longterm) archives and the active language used for querying such archives. Thus, technologies for detecting and systematically handling terminology evolution are required to ensure “semantic” accessibility of archived content in the long run. The core of our approach is to derive mappings between terminologies originating from different times by the fusion of term concept graphs. To verify the suitability of our approach, we present first results of experiments conducted on The Times archive that covers 200 years of documents. In addition, we discuss how our approach can be applied to web archives and the challenges that arise from this.
Interface agents: A review of the field

This paper reviews the origins of interface agents, discusses challenges that exist within the interface agent field and presents a survey of current attempts to find solutions to these challenges. A history of agent systems from their birth in the 1960’s to the current day is described, along with the issues they try to address. A taxonomy of interface agent systems is presented, and today’s agent systems categorized accordingly. Lastly, an analysis of the machine learning and user modelling techniques used by today’s agents is presented.
On the Applicability of Speaker Diarization to Audio Concept Detection for Multimedia Retrieval

Recently, audio concepts emerged as a useful building block in multimodal video retrieval systems. Information like "this file contains laughter", "this file contains engine sounds" or "this file contains slow music" can significantly improve purely visual based retrieval. The weak point of current approaches to audio concept detection is that they heavily rely on human annotators. In most approaches, audio material is manually inspected to identify relevant concepts. Then instances that contain examples of relevant concepts are selected -- again manually -- and used to train concept detectors. This approach comes with two major disadvantages: (1) it leads to rather abstract audio concepts that hardly cover the audio domain at hand and (2) the way human annotators identify audio concepts likely differs from the way a computer algorithm clusters audio data -- introducing additional noise in training data. This paper explores whether unsupervized audio segementation systems can be used to identify useful audio concepts by analyzing training data automatically and whether these audio concepts can be used for multimedia document classification and retrieval. A modified version of the ICSI (International Computer Science Institute) speaker diarization system finds segments in an audio track that have similar perceptual properties and groups these segments. This article provides an in-depth analysis on the statistic properties of similar acoustic segments identified by the diarization system in a predefined document set and the theoretical fitness of this approach to discern one document class from another.
Fast Rates for Regularized Objectives

We study convergence properties of empirical minimization of a stochastic strongly convex objective, where the stochastic component is linear. We show that the value attained by the empirical minimizer converges to the optimal value with rate 1/n. The result applies, in particular, to the SVM objective. Thus, we obtain a rate of 1/n on the convergence of the SVM objective (with fixed regularization parameter) to its infinite data limit. We demonstrate how this is essential for obtaining certain type of oracle inequalities for SVMs. The results extend also to approximate minimization as well as to strong convexity with respect to an arbitrary norm, and so also to objectives regularized using other lp norms.
A New Approach of Complier Design in Context of Lexical Analyzer and Parser Generation for NextGen Languages

A compiler translates and/or compiles a program written in a suitable source language into an equivalent target language through a number of stages. Starting with recognition of token through target code generation provide a basis for communication interface between a user and a processor in significant amount of time. A new approach GLAP model for design and time complexity analysis of lexical analyzer is proposed in this paper. In the model different steps of tokenizer (generation of tokens) through lexemes, and better input system implementation have been introduced. Disk access and state machine driven Lex are also reflected in the model towards its complete utility. The model also introduces generation of parser. Implementation of symbol table and its interface using stack is another innovation of the model in acceptance with both theoretically and in implementation widely. General Terms Compiler, Language Processor.
Transparent Rate Mode Bilateral Teleoperation Control

Transparent teleoperation under rate mode has proven to be difficult in terms of stability, performance and implementation. This is mainly due to the need for an exchange of derivative and integral of measured positions and forces which make transparent rate mode controllers prone to noise and abrupt contact force changes. Moreover, the performance of controllers declines in the presence of communication delays. This paper proposes two control architectures based on the use of local force feedback (LFF) and environment impedance reflection (EIR). The LFF controllers eliminate a force channel while preserving transparency under ideal conditions. In the EIR controller, the identified impedance of the environment is employed in the master controller to predict the slave position and contact force derivatives. The stability robustness and performance of these controllers are evaluated and compared to those of a benchmark controller under different operational conditions, such as noise and delay, using analytical methods and experimental results.