Miracle-dz/UniFAR-FTUs huggingface dataset:
Reactive power control in three-phase grid-connected current source boost inverter

Reactive power control and consequently voltage regulation in a micro-grid is one of the main control requirements, particularly when the micro-grid operates in an islanding mode. In this paper, the capability of a single-stage boost inverter in providing reactive power is investigated. The presented boost inverter utilizes the current-source topology and applies a modified space vector pulse-width-modulation (SVPWM) switching technique, here called phasor pulse-width-modulation (PPWM). It is demonstrated that the injected active and reactive power can be controlled through two modulation indices introduced in the PPWM switching algorithm. The capability of reactive power generation using a three-phase current source boost inverter (CSBI) was experimentally verified and the results are presented in this paper.
Hardware-software run-time systems and robotics: a case study

We present a sample implementation of a run time scheduler, split between hardware and software, controlling a real time robotics application. The hardware part of the run time scheduler, implemented as a finite state machine (FSM), schedules the tasks for the application and can be readily extended to include additional tasks in hardware or in software. The software part executes tasks based on which tasks are ready to execute as indicated by the FSM. We have successfully implemented the scheduler on a working prototype which shows the feasibility of our approach.
On Providing Minimum Rate Guarantees over the InternetWu-chang Fengy

A large number of Internet applications are sensitive to overload conditions in the network. While these applications have been designed to adapt somewhat to the varying conditions in the Internet, they can beneet greatly from an increased level of predictability in network services. We propose minor extensions to the packet queueing and discard mechanisms used in routers, coupled with simple control mechanisms at the source that enable the network to guarantee minimal levels of throughput to diierent sessions while sharing the residual network capacity in a cooperative manner. The service realized by the proposed mechanisms is an interpretation of the controlled-load service being standardized by the ietf. Although controlled-load service can be used in conjunction with any transport protocol, our focus in this paper is on understanding its interaction with tcp. Speciically, we study the dynamics of tcp traac in an integrated services network that simultaneously supports both best-eeort and controlled-load sessions. In light of this study, we propose and experiment with several variations to tcp's control mechanisms with the objective of ne-tuning them for an integrated services environment. We then investigate the eeect of network transients, such as changes in traac load and in service levels, on the performance of controlled-load as well as best-eeort connections. To capture the evolution of integrated services in the Internet, we also consider situations where only a selective set of routers are capable of providing service diierentiation between best-eeort and controlled-load traac. Finally, we show how the service mechanisms proposed here can be embedded within more elaborate packet and link scheduling frameworks in a fully-evolved integrated services Internet.
Na+ activation of the muscarinic K+ channel by a G-protein-independent mechanism

Muscarinic potassium channels (KACh) are composed of two subunits, GIRK1 and GIRK4 (or CIR), and are directly gated by G proteins. We have identified a novel gating mechanism of KACh, independent of G-protein activation. This mechanism involved functional modification of KACh which required hydrolysis of physiological levels of intracellular ATP and was manifested by an increase in the channel mean open time. The ATP-modified channels could in turn be gated by intracellular Na+, starting at approximately 3 mM with an EC50 of approximately 40 mM. The Na(+)-gating of KACh was operative both in native atrial cells and in a heterologous system expressing recombinant channel subunits. Block of the Na+/K+ pump (e.g., by cardiac glycosides) caused significant activation of KACh in atrial cells, with a time course similar to that of Na+ accumulation and in a manner indistinguishable from that of Na(+)-mediated activation of the channel, suggesting that cardiac glycosides activated KACh by increasing intracellular Na+ levels. These results demonstrate for the first time a direct effect of cardiac glycosides on atrial myocytes involving ion channels which are critical in the regulation of cardiac rhythm.
Combining process splitting and merging transformations for Polyhedral Process Networks

We use the polyhedral process network (PPN) model of computation to program and map streaming media applications onto embedded Multi-Processor Systems on Chip (MPSoCs) platforms. In previous works, it has been shown how to apply different process network transformations in isolation. In this work, we present a holistic approach combining the process splitting and merging transformations and show that it is necessary to use both transformations in combination to achieve the best performance results, which cannot be achieved using only one transformation. We solve the problem of ordering both transformation and, in addition, relieve the designer from the task to select the processes on which the transformation should be applied. Thus, our approach combines both transformations exploiting the data-level parallelism available in a PPN as much as possible, even in cases where the parallelism is restricted by topological cycles and stateful processes in the PPN.
Classification of acoustic physiological signals based on deep learning neural networks with augmented features

Digital signal processing techniques have been applied to analyze physiological signals for decades. Recent progresses in other fields, such as computer vision and machine learning, are attracting people to utilize such technologies for analyzing physiological signals. In this paper, recurrent neural network, often used in deep learning for time series signals, is applied to detect anomalies in heart sound. We successfully detected anomalies with 80% accuracy when augmenting the signals with other features.
Towards a City's Systems Integration Model for Smart City Development: A Conceptualization

Smart city development is a response to address the issues of urbanization and need for flexibility and agility in delivering services to citizens. City as a complex system of systems needs to be efficient, inter-operable, and integrated. Thus, similar to systems integration in enterprises, integration of city systems provides flexibility and access to real-time information for creation and delivery of efficient services. In addition, Business Process Change is essential for systems integration in smart city development. Similar to business process change in the private enterprises, there are a number of challenging dimensions in smart city development. This conceptualization research considers a city as a large-scale enterprise and attempts to design a business process centric model for city's systems integration.
The Fundamental Capacity-Delay Tradeoff in Large Mobile Ad Hoc Networks

There has been recent interest within the networking research community to understand how mobility can improve the capacity of mobile ad hoc networks. Of particular interest is the achievable capacity under delay constraints. In this paper, we establish the following upper bound on the optimal capacity-delay tradeoff in mobile ad hoc networks for an i.i. d. mobility model. For a mobile ad hoc network with n nodes, if the per-bit-averaged mean delay is bounded by D̄, then the per-node capacity λ is upper bounded by λ ≤ O( D̄n log 3 n). By studying the condition under which the upper bound is tight, we are able to identify the optimal values of several key scheduling parameters. We then develop a new scheme that can achieve a capacity-delay tradeoff close to the upper bound up to a logarithmic factor. Our new scheme achieves a larger per-node capacity than the schemes reported in previous works. In particular, when the delay is bounded by a constant, our scheme achieves a per-node capacity of Θ(n/ logn). This indicates that, for the i.i. d. mobility model, mobility results in a larger capacity than that of static networks even with constant delays. Finally, the insight drawn from the upper bound allows us to identify limiting factors in existing schemes. These results present a relatively complete picture of the achievable capacity-delay tradeoffs under different settings.
Engaged or Disengaged? Examining the Relationship Between Electoral Ambivalence and Indicators of Political Engagement in the 2012 U.S. Election

ABSTRACT This study uses uncertainty theories to examine the relationship between presidential electoral ambivalence and three political belief variables: internal efficacy, skepticism, and apathy. We propose that the relationship between ambivalence, which is an indicator of uncertainty, and information-seeking intentions should be mediated by our political belief variables. Our proposed model suggests that presidential electoral ambivalence is characteristic of a disengaged citizenry, with ambivalence correlating with lower levels of internal efficacy and skepticism in a cross-sectional analysis. We also found ambivalence associated with higher levels of apathy in this same analysis. Moreover, we found an over-time indirect effect of ambivalence on information seeking through internal efficacy.
HOW FINANCIAL DEVELOPMENT CAUSED ECONOMIC GROWTH IN APEC COUNTRIES : FINANCIAL INTEGRATION WITH FDI OR PRIVATIZATION WITHOUT FDI

Politicians fashionably argue in favour of financial development to promote economic growth following the seminal study of King and Levine (1993a and 1993b). Financial development, however, could come through alternative channels that are sometimes not compatible in small, open economics. A relatively popular channel promotes privatization of domestic financial intermediaries but with restrictions on foreign ownership. The other competing channel works through foreign direct investment (FDI) requiring foreign ownership of national assets. Until the last decade of globalization, from the 1960s through the early 1990s, in many Asia-Pacific Economic Cooperation (APEC) economies and especially in East Asia, privatization of national banks went hand in hand with barriers against FDI. The recent trend in globalization creates a political tension between those who welcome and the others who oppose FDI. This paper evaluates the relative contribution of those two alternative channels of financial development to economic growth. The model of analysis builds on King and Levine (1993b) but restricts its attention to small open economies of APEC. Contrary to the previous findings, privatization of the domestic financial sector alone turns out to have a negative impact on the growth of productivity and a weakly negative impact on the growth rate of per capita income. This discrepancy could possibly be rationalized by a special characteristic of the APEC sample where endogenous credit rationing by privatized banks could have lowered the relative proportion of entrepreneurs in the economy for reasons presented in Stiglitz and Weiss (1981). In this environment, FDI could serve as a catalyst to increase entrepreneurial access to international credit, which in turn could raise productivity by
Speech recognition in noisy environments using a switching linear dynamic model for feature enhancement

The performance of automatic speech recognition systems strongly decreases whenever the speech signal is disturbed by background noise. We aim to improve noise robustness focus-ing on all major levels of speech recognition: feature extraction, feature enhancement, and speech modeling. Different auditory modeling concepts, speech enhancement techniques, training strategies, and model architectures are implemented in an in-car digit and spelling recognition task. We prove that joint speech and noise modeling with a global Switching Linear Dynamic Model (SLDM) capturing the dynamics of speech, and a Linear Dynamic Model (LDM) for noise, prevails over state-of-the-art speech enhancement techniques. Furthermore we show that the baseline recognizer of the Interspeech Consonant Challenge 2008 can be outperformed by SLDM feature enhancement for almost all of the noisy testsets.
A theoretical and experimental analysis of linear combiners for multiple classifier systems

In this paper, a theoretical and experimental analysis of linear combiners for multiple classifier systems is presented. Although linear combiners are the most frequently used combining rules, many important issues related to their operation for pattern classification tasks lack a theoretical basis. After a critical review of the framework developed in works by Turner and Ghosh [1996], [1999] on which our analysis is based, we focus on the simplest and most widely used implementation of linear combiners, which consists of assigning a nonnegative weight to each individual classifier. Moreover, we consider the ideal performance of this combining rule, i.e., that achievable when the optimal values of the weights are used. We do not consider the problem of weights estimation, which has been addressed in the literature. Our theoretical analysis shows how the performance of linear combiners, in terms of misclassification probability, depends on the performance of individual classifiers, and on the correlation between their outputs. In particular, we evaluate the ideal performance improvement that can be achieved using the weighted average over the simple average combining rule and investigate in what way it depends on the individual classifiers. Experimental results on real data sets show that the behavior of linear combiners agrees with the predictions of our analytical model. Finally, we discuss the contribution to the state of the art and the practical relevance of our theoretical and experimental analysis of linear combiners for multiple classifier systems.
Anti-arrhythmic effects of hypercalcemia in hyperkalemic, Langendorff-perfused mouse hearts

The present study examined the ventricular arrhythmic and electrophysiological properties during hyperkalemia (6.3 mM [K+] vs. 4 mM in normokalemia) and anti-arrhythmic effects of hypercalcemia (2.2 mM [Ca2+]) in Langendorff-perfused mouse hearts. Monophasic action potential recordings were obtained from the left ventricle during right ventricular pacing. Hyperkalemia increased the proportion of hearts showing provoked ventricular tachycardia (VT) from 0 to 6 of 7 hearts during programmed electrical stimulation (Fisher's exact test, P<0.05). It shortened the epicardial action potential durations (APDx) at 90, 70, 50 and 30% repolarization and ventricular effective refractory periods (VERPs) (analysis of variance, P<0.05) without altering activation latencies. Endocardial APDx and VERPs were unaltered. Consequently, ∆APDx (endocardial APDx-epicardial APDx) was increased, VERP/latency ratio was decreased and critical intervals for reexcitation (APD90-VERP) were unchanged. Hypercalcemia treatment exerted anti-arrhythmic effects during hyperkalemia, reducing the proportion of hearts showing VT to 1 of 7 hearts. It increased epicardial VERPs without further altering the remaining parameters, returning VERP/latency ratio to normokalemic values and also decreased the critical intervals. In conclusion, hyperkalemia exerted pro-arrhythmic effects by shortening APDs and VERPs. Hypercalcemia exerted anti-arrhythmic effects by reversing VERP changes, which scaled the VERP/latency ratio and critical intervals.
Flexible multi-mode embedded floating-point unit for field programmable gate arrays

Performance of Field Programmable Gate Arrays (FPGAs) used for floating-point applications is poor due to the complexity of floating-point arithmetic. Implementing floating-point units on FPGAs consume a large amount of resources. This makes FPGAs less attractive for use in floating-point intensive applications. Therefore, there is a need for embedded floating-point units (FPUs) in FPGAs. However, if unutilized, embedded FPUs waste space on the FPGA die. To overcome this issue, we propose a flexible multi-mode embedded FPU for FPGAs that can be configured to perform a wide range of operations. The floating-point adder and multiplier in our embedded FPU can each be configured to perform one double-precision operation or two single-precision operations in parallel. To increase flexibility further, access to the large integer multiplier, adder and shifters in the FPU is provided. Benchmark circuits were implemented on both a standard Xilinx Virtex-II FPGA and on our FPGA with embedded FPU blocks. The results using our embedded FPUs showed a mean area improvement of 5.2 times and a mean delay improvement of 5.8 times for the double-precision benchmarks, and a mean area improvement of 4.4 times and a mean delay improvement of 4.2 times for the single-precision benchmarks.
The mind-window: brain activity visualization using tablet-based AR and EEG for multiple users

In this poster we introduce a novel approach, called the "Mind-Window", for real-time visualization of brain activity. The Mind-Window enables one or multiple users to visualize the brain activity of another person as if her skull was transparent. Our approach relies on the use of multiple tablet PCs that the observers can move around the head of the observed person wearing an EEG cap. A 3D virtual brain model is superimposed onto the head of the observed person using augmented reality by tracking a 3D marker placed on top of the head. The EEG cap records the electrical fields emitted by the brain, and they are processed in real-time to update the display of the virtual brain model. Several visualization techniques are proposed such as an interactive cutting plane which can be manipulated with touch-based inputs on the tablet. The Mind-Window could be used for various application purposes such as for Education as teaching tool to learn brain anatomy/activity and EEG features, e.g., electrodes localization, electrical patterns, etc.
Wrench Capabilities of Planar Parallel Manipulators and their Effects Under Redundancy

where J is referred to as the Jacobian matrix. In addition, an extended problem can be formulated as the analysis of the maximum twist or wrench that the end-effector can perform in the twist or wrench spaces, respectively. The knowledge of maximum twist and wrench capabilities is an important tool for achieving the optimum design of manipulators. For instance, by being able to graphically visualize the twist and wrench capabilities, comparisons between different design parameters, such as the actuator torque capabilities and the dimensions of the links, can be explored. Also, the performance of an existing manipulator can be improved by identifying the optimal capabilities based on the configuration of the branches and the pose of the end-effector. This work focuses on the wrench capabilities of planar parallel manipulators (PPMs), the geometric interpretation of their wrench polytopes, the derivation of wrench performance indices, and how the inclusion of redundancy affects the performance of parallel manipulators (PMs). The wrench capability analysis of a manipulator depends on its design, posture, and actuator torque capabilities.
Recognising the Capacities of Dynamic Reconfiguration for the QoS Assurance of Running Systems in Concurrent and Parallel Environments

Recognizing the impact of reconfiguration on the QoS of running systems is especially necessary for choosing an appropriate approach to dealing with dynamic evolution of mission-critical or non-stop business systems. The rationale is that the impaired QoS caused by inappropriate use of dynamic approaches is unacceptable for such running systems. To predict in advance the impact, the challenge is two-fold. First, a unified benchmark is necessary to expose QoS problems of existing dynamic approaches. Second, an abstract representation is necessary to provide a basis for modeling and comparing the QoS of existing and new dynamic reconfiguration approaches. Our previous work [8] has successfully evaluated the QoS assurance capabilities of existing dynamic approaches and provided guidance of appropriate use of particular approaches. This paper reinvestigates our evaluations, extending them into concurrent and parallel environments by abstracting hardware and software conditions to design an evaluation context. We report the new evaluation results and conclude with updated impact analysis and guidance.
Context Generalization for Information Extraction from the Web

Many online data sources, such as product catalogs, on-line directories, etc. are available on the web. Extracting information from such sources is a hard task since these sources are designed to be presented to human users. Many researchers have tackled the problem of building wrappers for such sources. The state of the art approach is to use machine learning techniques based on fully labeled example pages. In this paper we propose and study an approach based on example instances. This allows the user to build a wrapper using only a handful of examples of the whole source allowing to take into account structural differences. The patterns obtained allow to extract the instances of the relation described by the examples and contained in the same data source.
Coinitial semantics for redecoration of triangular matrices

Infinite triangular matrices and, in particular, the redecoration operation on them, were studied by Matthes and Picard. In their work, redecoration is characterized as the cobind operation of what the authors call a "weak constructive comonad". In this work, we identify weak constructive comonads as an instance of the more general notion of relative comonad. Afterwards, building upon the work by Matthes and Picard, we give a category-theoretic characterisation of infinite triangular matrices---equiped with the canonical bisimulation relation and a compatible comonadic cobind operation---as the terminal object in some category.
Workload characterization model for tasks with variable execution demand

The analysis of real-time properties of an embedded system usually relies on the worst-case execution times (WCET) of the tasks to be executed. In contrast to that, in real world applications the running time of tasks may vary from execution to execution, e.g. in multimedia applications. The traditional worst-case analysis of the system then returns overly pessimistic estimates of the system performance. In this paper we propose a new effective method to characterize tasks with variable execution requirements, which leads to tighter worst-case bounds on system performance and better use of available resources. We show the applicability of our approach by a detailed study of a multimedia application.
Response of a Channel with alternate bars to a decrease in supply of mixed‐size bed load: A Flume Experiment

The response of a channel with a topography and modeled bed material size typical of gravel bed rivers to reductions in sediment supply was investigated in a laboratory flume filled and fed with a sand-gravel mixture. After a series of quasi-stationary alternate bars were formed under equilibrium sediment transport, feed rate was reduced in two steps to one third and one tenth the initial rate as discharge was held constant. The primary response following both reductions was an increase in bed surface particle size as a corridor of intensive bed load transport contracted and local transport rates decreased. After the first feed rate reduction, the channel incised by twice the mean water depth, on average, and caused distal bar surfaces to emerge as terracelike features. Bar roughness decreased, and mean boundary shear stress exerted on bed surface particles increased. Little incision occurred after the second feed rate reduction.