Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Charging Strategies for Electric Vehicles in PowerMatcher-Driven Smart Energy Grids

A crucial challenge in future smart energy grids is the large-scale coordination of distributed energy demand and generation. The well-known PowerMatcher is a promising approach that integrates demand and supply flexibility in the operation of the electricity system through dynamic pricing and a hierarchical bidding coordination scheme. However, as the PowerMatcher focuses on short-term coordination of demand and supply, it cannot fully exploit the flexibility of e.g. electric vehicles over longer periods of time. In this paper, we propose an extension of the PowerMatcher comprising a planning module, which provides coordinated predictions of demand/price over longer times as input to the users for determining their short-term bids. The optimal short-term bidding strategy minimizing a user's costs is then formulated as a Stochastic Dynamic Programming (SDP) problem. We derive an analytic solution for this SDP problem leading to a simple short-term bidding strategy. Numerical results using real-world data show a substantial performance improvement compared to the standard PowerMatcher, without significant additional complexity.
Placement and placement driven technology mapping for FPGA synthesis

Because of the more restrictive placement and routing constraints in Xilinx FPGA designs, conventional physical design tools for general placement and routing architectures usually do not work well for FPGA designs. Moreover, to generate high quality circuits which are easy to place and route, it is important to consider the specific physical design constraints during the technology mapping process. The authors first present a performance driven placement algorithm specifically developed for the Xilinx FPGAs. They then present a new placement driven technology mapping algorithm which uses placement information to guide the mapping process. <<ETX>>
HTSC and FH_HTSC: XOR-based codes to reduce access latency in distributed storage systems

A massive distributed storage system is the foundation for big data operations. Access latency performance is a key metric in distributed storage systems since it greatly impacts user experience while existing codes mainly focus on improving performance such as storage overhead and repair cost. By generating parity nodes from parity nodes, in this paper we design new XOR-based erasure codes hierarchical tree structure code (HTSC) and high failure tolerant HTSC (FH_HTSC) to reduce access latency in distributed storage systems. By comparing with other popular and representative codes, we show that, under the same repair cost, HTSC and FH.HTSC codes can reduce access latency while maintaining favorable performance in other metrics. In particular, under the same repair cost, FH.HTSC can achieve lower access latency, higher or equal failure tolerance and lower computation cost compared with the representative codes while enjoying similar storage overhead. Accordingly, FH.HTSC is a superior choice for applications requiring low access latency and outstanding failure tolerance capability at the same time.
Effect of Airflow Rate on Vibration Response Imaging in Normal Lungs

Background: Evaluating the effect of airflow rate on amplitude of lung sound energy and regional distribution of lung sounds may assist in the interpretation of computerized acoustic measurements. Objectives: The aim of this study was to assess the effect of airflow rate on Vibration Response Imaging (VRI) measurement in healthy lungs. Methods: Lung sounds were recorded from 20 healthy adults in the frequency range of 150-250 Hz using 40 piezoelectric sensors positioned on the posterior chest wall. During the recordings, subjects were breathing at airflow rates ranging between 0.3 and 1.7L/s. Online visual feedback was provided using a pneumotach mouthpiece. Results: Amplitude of lung sound energy significantly increased with increasing airflow rate (p<0.00001, Friedman test). A strong relationship (R2=0.95) was obtained between amplitude of lung sound energy at peak inspiration and airflow rate raised to the third power. This correlation did not significantly affect normalized lung sound distribution maps at peak inspiration, especially when airflow was higher than 1.0L/s. Acoustic maps obtained at airflow rates below 0.7L/s differed from those recorded above 1.0L/s (p<0.05, Wilcoxon matched-paired signed-ranks test). Conclusion: These findings may be of importance when comparing healthy and diseased lungs or when monitoring changes in lung sounds during treatment follow-up.
The Laboratory Diagnosis and Follow Up of Strongyloidiasis: A Systematic Review

Background Strongyloidiasis is frequently under diagnosed since many infections remain asymptomatic and conventional diagnostic tests based on parasitological examination are not sufficiently sensitive. Serology is useful but is still only available in reference laboratories. The need for improved diagnostic tests in terms of sensitivity and specificity is clear, particularly in immunocompromised patients or candidates to immunosuppressive treatments. This review aims to evaluate both conventional and novel techniques for the diagnosis of strongyloidiasis as well as available cure markers for this parasitic infection. Methodology/Principal Findings The search strategy was based on the data-base sources MEDLINE, Cochrane Library Register for systematic review, EmBase, Global Health and LILACS and was limited in the search string to articles published from 1960 to August 2012 and to English, Spanish, French, Portuguese and German languages. Case reports, case series and animal studies were excluded. 2003 potentially relevant citations were selected for retrieval, of which 1649 were selected for review of the abstract. 143 were eligible for final inclusion. Conclusions Sensitivity of microscopic-based techniques is not good enough, particularly in chronic infections. Furthermore, techniques such as Baermann or agar plate culture are cumbersome and time-consuming and several specimens should be collected on different days to improve the detection rate. Serology is a useful tool but it might overestimate the prevalence of disease due to cross-reactivity with other nematode infections and its difficulty distinguishing recent from past (and cured) infections. To evaluate treatment efficacy is still a major concern because direct parasitological methods might overestimate it and the serology has not yet been well evaluated; even if there is a decline in antibody titres after treatment, it is slow and it needs to be done at 6 to 12 months after treatment which can cause a substantial loss to follow-up in a clinical trial.
Spatial Query Processing Based on Minimum Bounding in Wireless Sensor Networks

Sensors are deployed to gather physical, environmental data in sensor networks. Depend- ing on scenarios, it is often assumed that it is difficult for batteries to be recharged or exchanged in sensors. Thus, sensors should be able to process users' queries in an energy-efficient manner. This pa- per proposes a spatial query processing scheme- Minimum Bounding Area Based Scheme. This scheme has a purpose to decrease the number of outgoing messages during query processing. To do that, each sensor has to maintain some partial information locally about the locations of descendent nodes. In the initial setup phase, the routing path is established. Each child node delivers to its parent node the location information including itself and all of its descendent nodes. A parent node has to maintain several minimum bounding boxes per child node. This scheme can reduce unnecessary message propagations for query processing. Finally, the experimental results show the effectiveness of the pro- posed scheme.
Hybrid Routing Approach for Heterogeneous Wireless Sensor Networks Using Fuzzy Logic Technique

Wireless Sensor Networks are composed of thousands of sensor nodes, with restricted energy that cooperates to accomplish a sensing task. The homogeneous sensor nodes have same capacity in term of sensing, computation, communication, and power. The different application leads different types of sensor network in real life so the heterogeneous sensors exist. This leads to the researcher to develop the new concept for data acquisition. The Region-based Clustering Approach is used for deployment of different types of nodes in different regions according to their energy level to provide efficient utilization of total coverage area. The proposed Hybrid Routing Protocol is used for some nodes to transmit data directly to base station, while some uses clustering technique to send data to base station. The proposed protocol uses the fuzzy level information for cluster head selection to minimize the selection process time and re-election process of cluster head. This reduces the overall consumption of energy and improves the lifetime of the network.
Detecting word substitutions: PMI vs. HMM

Those who want to conceal the content of their communications can do so by replacing words that might trigger attention. For example, instead of writing "The bomb is in position", a terrorist may chose to write "The flower is in position. " The substituted sentence would sound a bit "odd" for a human reader and it has been shown in prior research that such oddity is detectable by text mining approaches. However, the importance of each component in the suggested oddity detection approach has not been thoroughly investigated. Also, the approach has not been compared with such an obvious candidate for the task as Hidden Markov Models (HMM). In this work, we explore further oddity detection algorithms reported earlier, specifically those based on pointwise mutual information (PMI) and Hidden Markov Models (HMM).
Adaptive Analytical Simplified Constant Modulus Algorithm: A BSS algorithm for MIMO systems with time-varying environments

An adaptive Analytical Simplified Constant Modulus Algorithm (adaptive-ASCMA) which accomplishes blind source separation and carrier phase recovery is proposed. This algorithm is applied on Multiple Input Multiple Output (MIMO) communication systems and uses some analytical methods to minimize the Simplified Constant Modulus (SCM) cost function. A study was done to find the subspace containing the solution of the minimization problem. With comparable computational complexities, the adaptive ASCMA accomplishes better performances in Bit Error Rate (BER) and Signal to Interference and Noise Ratio (SINR) terms than the adaptive-ACMA with time varying environment.
1 FRACTIONAL-ORDER CONTROL OF COOPERATIVE ROBOTS

In this paper it is studied the implementation of fractional-order algorithms in the position/force control of two cooperating robotic manipulators. The system performance is analyzed in the time and frequency domains. We analyze and compare different control methodologies such as the integer and the fractional-order PID presenting the simulation results assessing the performance of the proposed fractional-order algorithms.
Emotional intelligence and subjective well-being: Altruistic behavior as a mediator

Although an increasing number of studies shed light on the relationship between emotional intelligence and subjective well-being, little is yet known of the mediating effect of altruistic behavior in this relationship. We examined the relationships among emotional intelligence, altruistic behavior, and subjective well-being. Using structural equation modeling, we conducted an empirical test based on survey data obtained from 412 undergraduates in 2 South China universities. The results showed that emotional intelligence and altruistic behavior led to subjective well-being. In addition, altruistic behavior partially mediated the relationship between emotional intelligence and subjective well-being. Our findings support the application of an altruistic behavior perspective to gaining a better understanding of the mechanism by which emotional intelligence influences subjective well-being.
Weak Harnack inequality for fully nonlinear uniformly elliptic PDE with unbounded ingredients

The weak Harnack inequality for Lp-viscosity solutions is shown for fully nonlinear, second order uniformly elliptic partial differential equations with unbounded coefficients and inhomogeneous terms. This result extends those of Trudinger for strong solutions [21] and Fok for Lp-viscosity solutions [13]. The proof is a modification of that of Caffarelli [5, 6]. We apply the weak Harnack inequality to obtain the strong maximum principle, boundary weak Harnack inequality, global Cα estimates for solutions of fully nonlinear equations, strong solvability of extremal equations with unbounded coefficients, and Aleksandrov-Bakelman-Pucci maximum principle in unbounded domains.
Choices, Choices: Task Selection Preference During Concurrent Multitasking

With the ever-increasing stream of information we are expected to deal with on a moment-to-moment basis, human multitasking behavior has become an important part of modern society. Multitasking can occur on many different timescales. Our interest is in concurrent multitasking: attempting to fulfill multiple goals in parallel. There have been many investigations to determine whether concurrent multitasking is good or bad. However, there is no definite answer to this question. Instead, it seems to depend very much on the tasks that are performed concurrently, as well as the amount of experience one has with the tasks. For instance, studies into driving behavior have shown that purely cognitive tasks can have a negative impact on driving performance (Horrey & Wickens, 2006). On the other hand, some studies have shown that perfect multitasking is possible (Schumacher et al., 2001). Early attempts to explain the results of multitasking studies revolved around multiple resource theories. These postulate that the cognitive system can be divided up into several resources. Once the capacity of a resource is exceeded, it can create interference during multitasking. While able to offer explanations for multitasking observations, these theories cannot produce detailed models that can be used to predict behavior in new situations. However, with the development of cognitive architectures, our ability to predict multitasking behavior has greatly increased.
Effect of inhaled nitric oxide on raised pulmonary vascular resistance in children with congenital heart disease.

OBJECTIVE--To study the short-term effects of inhaled nitric oxide in infants and young children with congenital heart disease. SETTING--A supraregional referral centre for children with congenital heart disease. PATIENTS AND METHODS--22 infants and children aged 3-32 months (median age 5 months) with congenital heart disease undergoing preoperative cardiac catheterisation. All but one infant had intracardiac shunt lesions and 13 had increased pulmonary vascular resistance. During catheterisation the patients inhaled nitric oxide in a concentration of 40 parts per million in room air. Pulmonary and systemic haemodynamic variables were evaluated by means of measured oxygen consumption and the Fick principle before and after 10 minutes' exposure to nitric oxide. RESULTS--Inhaled nitric oxide did not affect the systemic circulation. There was a significant reduction in the pulmonary vascular resistance, but only in the 13 infants with pulmonary hypertension, in whom pulmonary vascular resistance was reduced by 34% from 8.6 (4.6) mm Hg.min.m2.l-1 (mean (SD)) to 5.7 (3.5) mm Hg.min.m2.l-1. The pulmonary circulation in infants with normal pulmonary vascular resistance was not affected. No statistically significant increase in methaemoglobin was seen, though there were large individual differences. No other side effects were seen. CONCLUSION--The present study shows that in infants with congenital heart disease inhaled nitric oxide reduced pathologically increased pulmonary vascular resistance without affecting systemic circulation and without important side effects with brief exposure.
Effective energy function for proteins in solution

A Gaussian solvent‐exclusion model for the solvation free energy is developed. It is based on theoretical considerations and parametrized with experimental data. When combined with the CHARMM 19 polar hydrogen energy function, it provides an effective energy function (EEF1) for proteins in solution. The solvation model assumes that the solvation free energy of a protein molecule is a sum of group contributions, which are determined from values for small model compounds. For charged groups, the self‐energy contribution is accounted for primarily by the exclusion model. Ionic side‐chains are neutralized, and a distance‐dependent dielectric constant is used to approximate the charge–charge interactions in solution. The resulting EEF1 is subjected to a number of tests. Molecular dynamics simulations at room temperature of several proteins in their native conformation are performed, and stable trajectories are obtained. The deviations from the experimental structures are similar to those observed in explicit water simulations. The calculated enthalpy of unfolding of a polyalanine helix is found to be in good agreement with experimental data. Results reported elsewhere show that EEF1 clearly distinguishes correctly from incorrectly folded proteins, both in static energy evaluations and in molecular dynamics simulations and that unfolding pathways obtained by high‐temperature molecular dynamics simulations agree with those obtained by explicit water simulations. Thus, this energy function appears to provide a realistic first approximation to the effective energy hypersurface of proteins. Proteins 1999;35:133–152. © 1999 Wiley‐Liss, Inc.
ARM Based Implementation of Text-to-Speech (TTS) for Real Time Embedded System

Since decades, real time hardware implementation of Text-To-Speech system has been drawing attention of the research community due to its various real time applications. These include reading aids for the blind, talking aid for the vocally handicapped and training aids and other commercial applications. All these applications demand the real time embedded platform to meet the real time specifications such as speed, power, space requirements etc. In this context the embedded processor ARM (Advanced RISC Machine), has been chosen as hardware platform to implement Text-To-Speech conversion. This conversion needs algorithms to perform various operations like parts of speech tagging, phrase marking, word to phoneme conversion and clustergen synthesis. These algorithms are coded and developed in C using eclipse IDE and finally implemented on commercially available ARM9 microcontroller (AT91SAM9263EJ-S). Experiments have been performed on ARM microcontroller using test cases. It has been observed that the performance of the ARM based implementation is very close to x86 implementation.
Estimating the Number of Clusters Based on Sequential Clustering Algorithms

The main goal of clustering algorithms is to organize a given set of data patterns into groups (clusters) and their main strategy is to group patterns based on their similarity. However, some clustering algorithms also require as an input parameter, the number of clusters the induced clustering should have, or then, a threshold value used for limiting for the number of induced clusters. Both, the number of cluster as well a threshold value are often unknown, however it is well-known that results of clustering tasks can be very sensitive to them. This work presents a method for empirically estimating both values. The method is based on multiple runs of sequential clustering algorithms, by using increasing threshold values. Results from experiments conducted using several data domains from two repositories, the UCI and the Keel, as well as a few artificially created data, are presented and a comparative analysis is carried out, as evidence of the good estimates on both values given by the method.
On the trade-off between throughput maximization and energy consumption minimization in IEEE 802.11 WLANs

Understanding and optimizing the energy consumption of wireless devices is critical to maximize the network lifetime and to provide guidelines for the design of new protocols and interfaces. In this work, we first provide an accurate analysis of the energy performance of an IEEE 802.11 WLAN, and then we derive the configuration to optimize it. We further analyze the impact of the energy configuration of the stations on the throughput performance, and we discuss under which circumstances throughput and energy efficiency can be both jointly maximized and where they constitute different challenges. Our findings are that, although an energy-optimized configuration typically yields gains in terms of throughput as compared against the default configuration, it comes with a reduction in performance as compared against the maximum-bandwidth configuration, a reduction that depends on the energy parameters of the wireless interface.
Optimal Scheduling and Beamforming in Relay Networks With Energy Harvesting Constraints

In this paper, multiple relays capable of harvesting energy from radio-frequency (RF) signals are employed to collaboratively forward data from a source transmitter to its destined receiver. Due to the relays' inability to harvest energy and transmit data simultaneously, the source needs to optimally schedule the relays' energy harvesting (EH) and data transmission. Considering different channel conditions and energy constraints, the relays need to optimally design a beamforming vector that specifies each relay a power amplifier coefficient to forward the source signal and suppress the noise. By joint EH scheduling and beamforming, we maximize the overall throughput formulated in a nonconvex problem. We first propose a centralized scheme that achieves the optimal throughput by exploiting the monotonicity in the problem structure. We further propose a distributed suboptimal scheme in a game theoretic approach, which requires the source and the relays to iteratively update EH scheduling and beamforming vector, respectively. We show that the suboptimal scheme has a threshold-based structure for the relays' power control depending on the source-relay channel conditions. Numerical results show near-optimal performance of the distributed scheme compared with the centralized optimal scheme.
Why we need a different view of software architecture

The definition and understanding of software architectures and architecture views still shows considerable disagreement in the software engineering community. The paper argues that the problems we face exist because our understanding is based on specious analogies with traditionally engineered artefacts. A review of the history of ideas shows the evolution of this understanding. A detailed examination is then presented of the differences that exist between the nature of the systems, the content of their large-scale representations, and how they are used in practice in the respective disciplines. These differences seriously undermine the analogies used to develop our understanding and this is discussed in terms of software engineering as a whole.