Miracle-dz/UniFAR-FTUs huggingface dataset:
High-level Power Modeling, Estimation, And Optimization

In the past, the major concern of the VLSI designers werearea, performance, cost, and reliability.In recent years,however, this has changed and, increasingly, power is beinggiven comparable weight to area and speed.This is mainlydue to the remarkable success of personal computing devicesand wireless communication systems, which demandhigh-speed computation and complex functionality with lowpower consumption.In addition, there exists a strong pressurefor manufacturers of high-end products to keep powerunder control.The main driving factors for lower powerdissipation in these products are the costs associated withpackaging and cooling, and circuit reliability.Tools for the automatic design of low-power VLSI systemshave thus become mandatory.More specifically, followinga natural trend, interests of researchers have latelyshifted to the investigation of high-level power modeling,estimation, synthesis, and optimization techniques that accountfor power dissipation as the primary cost factor.This paper provides a non-exhaustive survey of the mostsuccessful and innovative ideas in this area that have appearedin the literature in the last few years.
Vehicular networking and channel modeling: A new Markovian approach

Vehicular networking is rapidly growing in the last years, due to its ability of enhancing users everyday-life, in terms of comfort, security and QoS. New services are being implemented and the research activity on the topic is embracing different OSI layers, like the network and application ones. Many efforts have been also given at the PHY layer. In this paper we focus our attention on a new approach for modeling the wireless channel of VANETs communications. In the literature many channel models have been proposed, but most of them work at the bit level or they investigate only some aspects of channel interaction. In this work we provide a high level IEEE802.11p channel model based on Discrete Time Markov Chain (DTMC) modeling, useful in every simulation context. The proposed model is called Markovian Vehicular Channel Model (MVCM) and it is based on the concept of Packet Error Rate (PER) discretization: we do not consider the performance analysis at the bit level, but we derive the proposed model by computing the PER, associated to different observation times. The effectiveness of the proposed idea has been evaluated through a deep campaign of simulations.
Connection admission control for hard real-time communication in ATM networks

Connection Admission Control (CAC) as needed in ATM networks to provide Quality of Service (QoS) guarantees real-time connections. In this paper, we present a CAC scheme based on (1) a bit-stream traffic model to describe traffic generation patterns of CBR/VBR connections and traffic distortions within a network, and (2) worst-case queueing analysis to obtain hard cell queueing delay bounds. The proposed CAC scheme can be used for the establishment of hard real-time connections in ATM networks with conventional static priority FIFO queueing switches. The effectiveness of the scheme is illustrated by applying it to an ATM-based Real-Time Plant Control Network (RTPCN) currently under development by the Mitsubishi Electric Corporation. The CAC scheme presented in the paper can also be extended to set up soft real-time connections in ATM networks.
Static Name Control for FreshML

FreshML extends ML with constructs for declaring and manipulating abstract syntax trees that involve names and statically scoped binders. It is impure: name generation is an observable side effect. In practice, this means that FreshML allows writing programs that create fresh names and unintentionally fail to bind them. Following in the steps of early work by Pitts and Gabbay, this paper defines Pure FreshML, a subset of FreshML equipped with a static proof system that guarantees purity. Pure FreshML relies on a rich binding specification language, on user-provided assertions, expressed in a logic that allows reasoning about values and about the names that they contain, and on a conservative, automatic decision procedure for this logic. It is argued that pure FreshML can express non-trivial syntax-manipulating algorithms.
Singing Voice Separation and Vocal F0 Estimation Based on Mutual Combination of Robust Principal Component Analysis and Subharmonic Summation

This paper presents a new method of singing voice analysis that performs mutually-dependent singing voice separation and vocal fundamental frequency (F0) estimation. Vocal F0 estimation is considered to become easier if singing voices can be separated from a music audio signal, and vocal F0 contours are useful for singing voice separation. This calls for an approach that improves the performance of each of these tasks by using the results of the other. The proposed method first performs robust principal component analysis (RPCA) for roughly extracting singing voices from a target music audio signal. The F0 contour of the main melody is then estimated from the separated singing voices by finding the optimal temporal path over an F0 saliency spectrogram. Finally, the singing voices are separated again more accurately by combining a conventional time-frequency mask given by RPCA with another mask that passes only the harmonic structures of the estimated F0s. Experimental results showed that the proposed method significantly improved the performances of both singing voice separation and vocal F0 estimation. The proposed method also outperformed all the other methods of singing voice separation submitted to an international music analysis competition called MIREX 2014.
Finite Model Reasoning in Description Logics

For the basic Description Logics reasoning with respect to finite models amounts to reasoning with respect to arbitrary ones, but finiteness of the domain needs to be considered if expressivity is increased and the finite model property fails. Procedures for reasoning with respect to arbitrary models in very expressive Description Logics have been developed, but these are not directly applicable in the finite case. We first show that we can nevertheless capture a restricted form of finiteness and represent finite modeling structures such as lists and trees, while still reasoning with respect to arbitrary models. The main result of this paper is a procedure to reason with respect to finite models in an expressive Description Logic equipped with inverse roles, cardinality constraints, and in which arbitrary inclusions between concepts can be specified without any restriction. This provides the necessary expressivity to go beyond most semantic and object-oriented Database models, and capture several useful extensions.
SATenstein: Automatically Building Local Search SAT Solvers from Components

Designing high-performance algorithms for computationally hard problems is a difficult and often time-consuming task. In this work, we demonstrate that this task can be automated in the context of stochastic local search (SLS) solvers for the propositional satisfiability problem (SAT). We first introduce a generalised, highly parameterised solver framework, dubbed SATenstein, that includes components gleaned from or inspired by existing high-performance SLS algorithms for SAT. The parameters of SATenstein control the selection of components used in any specific instantiation and the behaviour of these components. SATenstein can be configured to instantiate a broad range of existing high-performance SLS-based SAT solvers, and also billions of novel algorithms. We used an automated algorithm configuration procedure to find instantiations of SATenstein that perform well on several well-known, challenging distributions of SAT instances. Overall, we consistently obtained significant improvements over the previously best-performing SLS algorithms, despite expending minimal manual effort.
Test Case Generation Using Model Checking for Software Components Deployed into New  Environments

In this paper, we show how to generate test cases for a componentdeployed into a new software environment. This problem is importantfor software engineers who need to deploy a component into a newenvironment. Most existing model based testing approaches generatemodels from high level specifications. This leaves a semantic gapbetween the high level specification and the actualimplementation. Furthermore, the high level specification often needsto be manually translated into a model, which is a time consuming anderror prone process. We propose generating themodel automatically by abstracting the source code of the componentusing an under-approximating predicate abstraction scheme and leaving theenvironment concrete. Test cases are generated by iterativelyexecuting the entire system and storing the border states between thecomponent and the environment. A model checker is used in the componentto explore non-deterministic behaviors of the component due to theconcurrency or data abstraction. The environment is symbolicallysimulated to detect refinement conditions. Assuming the run timeenvironment is able to do symbolic execution and that the run timeenvironment has a single unique response to a given input, we provethat our approach can generate test cases that have complete coverageof the component when the proposed algorithm terminates. When thealgorithm does not terminate, the abstract-concrete model can berefined iteratively to generate additional test cases. Test casesgenerated from this abstract-concrete model can be used to check whethera new environment is compatible with the existing component.
Bootstrapping grounded symbols by minimal autonomous robots

In this paper an experiment is presented in which two mobile robots develop a shared lexicon of which the meanings are grounded in the real world. The robots start without a lexicon nor shared meanings and play language games in which they generate new meanings and negotiate words for these meanings. The experiment tries to find the minimal conditions under which verbal communication may begin to evolve. The robots are autonomous in terms of computing and cognition, but they are otherwise far simpler than most, if not all animals. It is demonstrated that a lexicon nevertheless can be made to emerge even though there are strong limits on the size and stability of this lexicon.
Impact of Season Variation on Semen Quality: A Comprehensive Retrospective Analysis of Data From Patients at an Eastern Iranian Tertiary Care Fertility Center Over a Decade

Seasonal changes are assumed to affect various sperm characteristics based on photoperiods, temperature, and air pollution. According to the literature, most studies were performed on populations of Western countries, and there are limited studies performed in the Middle East with variable results. This study evaluated the seasonality of sperm characteristics among men of reproductive age in an andrology center in Kerman, Iran, where the seasonal temperature varies significantly, with average temperatures ranging from 50 °F (10 °C) to 75.2 °F (24 °C). We retrospectively evaluated the sperm analysis test record. Sperm samples were obtained from 2,948 men during 10 years, excluding those with azoospermia. Samples were assessed for volume, concentration, motility, and morphology according to the World Health Organization (WHO) criteria. We performed a comprehensive comparative literature review of the studies investigating the association between seasonal variation and sperm quality. The mean semen volume was higher in the summer compared with other seasons (p = .04). The mean percentage of sperm motility was higher in the spring and less in winter (p = .03). Sperm morphology-related parameters, measured by the percent of normal morphology, were significantly better in winter (p = .03). Our findings suggest seasonality of sperm characteristics among men of fertility age. Semen volume, motility, and morphology were affected by the photoperiod of reproductive seasons. Results might support the influential role of seasonal variations in the possibility of fertility, especially among those using assisted reproductive technologies and those with oligospermia.
Controlled Trial of Captopril in Chronic Heart Failure: A Rest and Exercise Hemodynamic Study

Although many studies have shown acute hemodynamic improvement in patients with congestive heart failure treated with vasodilating drugs, long-term controlled studies with both hemodynamic and exercise capacity measurements are not available. We studied the converting-enzyme inhibitor captopril in 16 ambulatory patients in New York Heart Association functional class II-IV heart failure who were clinically stable on digoxin and diuretics. The acute response to open-label captopril was quantified by blood pool scintigraphy, right-heart catheterization at rest and during exercise, and measurements of exercise capacity. The patients were then randomized to maintenance therapy with captopril or matching placebo and were restudied after 3 months. The two groups were similar in their clinical characteristics and pretreatment rest and exercise hemodynamic measurements. Both displayed similar acute beneficial responses to captopril at rest, with a mean reduction in left ventricular filling pressure from 24 9 to 14 6 mm Hg (p < 0.001) and increases in cardiac index, from 2.1 0.5 to 2.5 + 0.61/min/m2 (p < 0.01), and stroke index, from 25 8 to 34 + 8 mI/M2 (p < 0.001). Directionally similar hemodynamic improvement was noted during exercise.After 3 months, these beneficial hemodynamic changes were sustained only in the patients randomized to captopril. Concomitantly, the captopril patients increased their exercise capacity as measured by the duration of bicycle exercise (9.0 2.2 vs 11.7 1.4 min, p < 0.01), maximal work load (360 80 vs 460 50 kpm/min, p < 0.005) and oxygen consumption (12.9 2.3 vs 15 + 1.8 ml/kg/min). The placebo group showed either no change or a worsening over the 3 months compared to their pretreatment measurements.These findings demonstrate that captopril is an effective adjunctive agent for the treatment of chronic heart failure and that it produces long-term hemodynamic improvement together with an increase in exercise capacity.
Research on Forecast Model of the Air-conditioning System in Data Center Based on Neural Network

This paper introduces the relevant information about data center. The concept of data center is increasingly popular. This paper summarizes the domestic and foreign scholars research about the current situation of optimization and energy-saving about the air-conditioning system in data center and most scholars still come to stay in the study of the optimization of the equipment and control some equipment in order to achieve the purpose of energy optimization, but there is almost no research on predictive control. This topic applied predictive control to the entire air conditioning system. And it introduced the basic principles of predictive control, the policy-related knowledge of forecast model and data collection strategy. This paper introduces emphatically the BP neural network algorithm principle and application. By determining the amount of inputs and outputs and using BP neural network established the forecast model of the air conditioning system in data center. Eventually the model achieved the expected forecast results with MATLAB simulation and test.
Posterolateral Disc Prolapse in Flexion Initiated by Lateral Inner Annular Failure: An Investigation of the Herniation Pathway

Study Design. Structural investigation of mechanically induced herniations in ovine lumbar motion segments. Objective. This new study addresses the question of whether there are regions other than the posterior and posterolateral aspects that are implicated in the initiation of disc disruption and herniation. Summary of Background Data. Flexion in combination with compressive loading will induce disc herniations in healthy motion segments in vitro. Although it is widely accepted that the posterior and posterolateral regions of the disc are the primary sites of herniation much less is known as to whether other regions of the disc might be involved in the herniation process. Methods. Healthy ovine lumbar motion segments (n = 14) were flexed 10° and compressed at a rate of 40 mm/min up to point of failure. The discs were macroscopically analyzed using progressive transverse sectioning to obtain a more global picture of internal disc disruption and herniation. Results. A high prevalence of disruption in the lateral annulus was found associated with circumferential tracking of nucleus between the annular layers toward the posterolateral and posterior regions. In all tests this lateral disruption did not cause any discernible external change in the lateral disc periphery after the removal of load. After imposing the predetermined flexion the applied compression also induced a forward anterior shear of the superior vertebra of approximately equal magnitude to the axial compressive displacement. Conclusion. The vulnerability of the lateral annulus to disruption is thought to arise from the overloading of its differentially recruited oblique/counteroblique fiber sets, this in turn generated by anterior shear developed in the flexed, compressed motion segment. This lateral annular disruption, followed by circumferential tracking of nuclear material and resulting in either contained or uncontained extrusions in the posterior or posterolateral annulus, highlights the complexity of the herniation process. Level of Evidence: N/A
A Survey of Agent-based Personalized Semantic information retrieval

The Aim of personalized search is to provide users with information tailored to their individual contexts. Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. Current Web search engines are built to serve all users, independent of the special needs of any individual user. Personalization of Web search is to carry out retrieval for each user incorporating his/her interests. The Semantic Web and Multi-Agent are effective means for constructing information retrieval systems.Despite a great deal of research, a number of challenges still exist before making Semantic Web and agent-based computing a widely accepted in information retrieval practice. The goal of this survey is study of the main concepts, existing methods, and practices of this area.
Object-based data compression for massive multichannel audio

A new data compression scheme is considered for multichannel audio signal that typically represents a dense sound field. The technique exploits similarities between channels by jointly encoding "objects" extracted from them. For this purpose, dominant energy sources are identified in the spatio-temporal domain, separated from channel data, and encoded jointly, with taking care of appropriate temporal and spectral alignment between channels. The remaining residual signal is encoded in each channel. Experimental results show a significant efficiency increase w.r. t. encoding individual channels without extracting objects. Applications include 3D audio and offline Wave Field Synthesis systems.
Diagnostic Accuracy of PCR in gambiense Sleeping Sickness Diagnosis, Staging and Post-Treatment Follow-Up: A 2-year Longitudinal Study

Background The polymerase chain reaction (PCR) has been proposed for diagnosis, staging and post-treatment follow-up of sleeping sickness but no large-scale clinical evaluations of its diagnostic accuracy have taken place yet. Methodology/Principal Findings An 18S ribosomal RNA gene targeting PCR was performed on blood and cerebrospinal fluid (CSF) of 360 T. brucei gambiense sleeping sickness patients and on blood of 129 endemic controls from the Democratic Republic of Congo. Sensitivity and specificity (with 95% confidence intervals) of PCR for diagnosis, disease staging and treatment failure over 2 years follow-up post-treatment were determined. Reference standard tests were trypanosome detection for diagnosis and trypanosome detection and/or increased white blood cell concentration in CSF for staging and detection of treatment failure. PCR on blood showed a sensitivity of 88.4% (84.4–92.5%) and a specificity of 99.2% (97.7–100%) for diagnosis, while for disease staging the sensitivity and specificity of PCR on cerebrospinal fluid were 88.4% (84.8–91.9%) and 82.9% (71.2–94.6%), respectively. During follow-up after treatment, PCR on blood had low sensitivity to detect treatment failure. In cerebrospinal fluid, PCR positivity vanished slowly and was observed until the end of the 2 year follow-up in around 20% of successfully treated patients. Conclusions/Significance For T.b. gambiense sleeping sickness diagnosis and staging, PCR performed better than, or similar to, the current parasite detection techniques but it cannot be used for post-treatment follow-up. Continued PCR positivity in one out of five cured patients points to persistence of living or dead parasites or their DNA after successful treatment and may necessitate the revision of some paradigms about the pathophysiology of sleeping sickness.
Object-oriented Reactive Programming is Not Reactive Object-oriented Programming

According to chapter 3 of Abelson & Sussman [1], there are two fundamentally different ways to organise large systems: according to the objects that live in the system, or according to the streams of values that flow through the system. Even though the notions of “object” and “stream” have meanwhile taken many incarnations, the dichotomy still exists in modern programming languages. Marrying reactive programming and OOP is a research endeavour to come up with a unified model that embraces both styles of thinking. We identify two opposing research tracks towards the marriage. Existing work focuses on OO reactive programming, i.e., it uses object technology to compose reactions. Our work explores the converse: in the paper, we present the ROAM (Reactive Objects in AmbientTalk) model which is an experimental framework that explores objects as streams of reactive state.
Superlinear Convergence and Implicit Filtering

In this paper we show how the implicit filtering algorithm can be coupled with the BFGS quasi-Newton update to obtain a superlinearly convergent iteration if the noise in the objective function decays sufficiently rapidly as the optimal point is approached. In this way we give insight into the observations of good performance in practice of quasi-Newton methods when they are coupled with implicit filtering. We also report on numerical experiments that show how an implementation of implicit filtering that exploits these new results can improve the performance of the algorithm.
Effect Analysis of Design Variables on the Disc in a Double-Eccentric Butterfly Valve

We have performed a shape optimization of the disc in an industrial double-eccentric butterfly valve using the effect analysis of design variables to enhance the valve performance. For the optimization, we select three performance quantities such as pressure drop, maximum stress, and mass (weight) as the responses and three dimensions regarding the disc shape as the design variables. Subsequently, we compose a layout of orthogonal array (L16) by performing numerical simulations on the flow and structure using a commercial package, ANSYS v13.0, and then make an effect analysis of the design variables on the responses using the design of experiments. Finally, we formulate a multiobjective function consisting of the three responses and then propose an optimal combination of the design variables to maximize the valve performance. Simulation results show that the disc thickness makes the most significant effect on the performance and the optimal design provides better performance than the initial design.