Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing acoustic similarities between emotions in speech: an acoustic map of emotions

In this paper, we introduce a visual analysis method to assess the discriminability and confusiability between emotions according to automatic emotion classifiers. The degree of acoustic similarities between emotions can be defined in terms of distances that are based on pair-wise emotion discrimination experiments. By employing Multidimensional Scaling, the discriminability between emotions can then be visualized in a two-dimensional plot that is relatively easy to interpret. This map of emotions is compared to the well-known Feeltrace two-dimensional mapping of emotions. While there is correlation with the arousal dimension of Feeltrace, it appears that the valence dimension is difficult to relate to the acoustic map.
An Efficient Algorithm for Detecting Closed Frequent Subgraphs in Biological Networks

In this paper, aimed at the problem of detecting closed frequent subgraphs in biological networks, an improved FP-growth algorithm MaxFP is presented, which is based on the simplification model appropriate to biological networks. The defects of the algorithm based on item-set mining are analyzed when it is applied to biological networks, and which is overcome in MaxFP. In addition, MaxFP also takes the biological network characteristics into account. Experiment results show that MaxFP runs faster than the algorithms based on Apriori, and MaxFP not only detects maximal frequent subgraphs, but also finds more frequent subgraphs having biological meaning. The results got by performing Apriori based algorithms many times can be got by performing MaxFP once.
Compiling Communication-Efficient Programs for Massively Parallel Machines

A method of generating parallel target code with explicit communication for massively parallel distributed-memory machines is presented. The source programs are shared-memory parallel programs with explicit control structures. The method extracts syntactic reference patterns from a program with shared address space, selects appropriate communication routines, places these routines in appropriate locations in the target program text and sets up correct conditions for invoking these routines. An explicit communication metric is used to guide the selection of data layout strategies. >
Robust Shape Clustering : Computing 1-medians on Riemannian Manifolds

Propelled by advances in medical imaging technology, clinicians and researchers are generating vast amounts of complex 2D and 3D shape data describing the brain, the heart, and other critical organs in both diseased and normal patients. Such shape data is often modelled as points on manifolds. Thus, characterizing such data requires us to extend statistical notions of centrality to manifold-valued data. In previous work [2, 6, 13], the notion of centrality of empirical data was defined via the Fréchet mean [7], which was first developed for manifold-valued data by Karcher [8]. Although the mean is an obvious central representative, one of its major drawbacks is its lack of robustness, i.e. sensitivity to outliers.
Documentation of dark areas of large historical buildings by a formation of unmanned aerial vehicles using model predictive control

A system designed for a unique multi-robot application of closely flying formations of Unmanned Aerial Vehicles (UAVs) in indoor areas is described in this paper. The proposed solution is aimed as a tool for historians and restorers working in large historical buildings such as churches to provide an access to areas that are difficult to reach by humans. In these objects, it is impossible to keep a large scaffolding for a long time due to regular services, which is necessary for studying a long-term influence of restorations works, and some parts of the churches were even not reached by people for decades and need to be inspected. To provide the same documentation and inspection techniques that are used by the experts in lower easily accessible parts of the buildings, we employ a formation of autonomous UAVs, where one of the robots is equipped by a visual sensor and the others by source of light, which provides the required flexibility for control of lightening. The described system in its full complexity has been implemented with achieved robustness and reliability required by deployment in real missions. The technology demonstration has been provided with real UAVs in historical objects to help restorers and conservationists with achieved valuable results used in plans of restoration works. In these missions, UAVs were autonomously hovering at designated locations to be able to demonstrate usefulness of such robotic lightening approach.
MSE Estimates for Multitaper Spectral Estimation and Off-Grid Compressive Sensing

We obtain estimates for the mean squared error (MSE) for the multitaper spectral estimator and certain compressive acquisition methods for multi-band signals. We confirm a fact discovered by Thomson [Spectrum estimation and harmonic analysis, Proc. IEEE, 1982]: assuming bandwidth <inline-formula> <tex-math notation="LaTeX">$W$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> time domain observations, the average of the square of the first <inline-formula> <tex-math notation="LaTeX">$K=\lfloor 2NW\rfloor$ </tex-math></inline-formula> Slepian functions approaches, as <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> grows, an ideal bandpass kernel for the interval <inline-formula> <tex-math notation="LaTeX">$[ -W,W]$ </tex-math></inline-formula>. We provide an analytic proof of this fact and measure the corresponding rate of convergence in <inline-formula> <tex-math notation="LaTeX">$L^{1}$ </tex-math></inline-formula> norm. This validates a heuristic approximation used to control the MSE of the multitaper estimator. The estimates have also consequences for the method of compressive acquisition of multi-band signals introduced by Davenport and Wakin, giving MSE approximation bounds for the dictionary formed by modulation of the critical number of prolates.
Exact and Numerical Solutions for Coupled Nonlinear Klein-Gordon-Schrödinger Equations

In this paper we give a derivation of the exact solution for coupled nonlinear KleinGordon-Schrödinger equation by the ansatz method. We present a numerical solution by implicit finite difference scheme which is fourth order accurate in space and second order in time. We discuss the accuracy and stability of the scheme. Numerical results are given to show that this method is quite accurate.
Instruction Shuffle: Achieving MIMD-like Performance on SIMD Architectures

SIMD architectures are less efficient for applications with the diverse control-flow behavior, which can be mainly attributed to the requirement of the identical control-flow. In this paper, we propose a novel instruction shuffle scheme that features an efficient control-flow handling mechanism. The cornerstones are composed of a shuffle source instruction buffer array and an instruction shuffle unit. The shuffle unit can concurrently deliver instructions of multiple distinct control-flows from the instruction buffer array to eligible SIMD lanes. Our instruction shuffle scheme combines the best attributes of both the SIMD and MIMD execution paradigms. Experimental results show that, an average performance improvement of 86% can be achieved, at a cost of only 5.8% area overhead.
Collecting Usage Data for Software Development: Selection Framework for Technological Approaches

Software development methods are shifting towards faster deployments and closer to the end users. Their ever tighter engagement of end-users also requires new technologies for gathering feedback from those users. At the same time, widespread Internet connectivity of different application envi- ronments is enabling the collection of this post-deployment data also from sources other than traditional web and mobile software. However, the sheer number of different alternatives of collecting technologies makes the selection a complicated process in itself. In this paper, we describe the process of data-driven software development and study the challenges organizations face when they want to start guiding their development towards it. From these challenges, we extract evaluation criteria for technological approaches to usage data collecting. We list such approaches and evaluate them using the extracted criteria. Using a design science approach, we refine the evaluation criteria to a selection framework that can help practitioners in finding a suitable technological approach for automated collecting of usage data. I. INTRODUCTION
Performance and Modeling of Si-Nanocrystal Double-Layer Memory Devices With High- $k$ Control Dielectrics

In this paper, memory devices integrating a double layer of silicon nanocrystals (Si-ncs) as a trapping medium and a HfAlO-based control dielectrics are presented. We will show that the use of two stacked Si-nc layers significantly improves the memory window compared with the single Si-nc layer devices, without introducing anomalies on the charging dynamics. Then, we also evaluate the potential use of a hybrid Si-nc double-layer/SiN layer charge trapping stack. These devices show a good memory window in a Fowler-Nordheim (FN)/FN mode and a good retention (>; 3 V after ten years) with small activation energy (0.35 eV up to 200 °C), thus showing promise for future high-temperature memory applications. A model implying valence-band electron tunneling and a floating-gate-like approximation is used to explain the memory window improvement of the Si-nc double-layer memory devices.
Secretory effects of ATP on nontransformed dog pancreatic duct epithelial cells.

Extracellular triphosphate nucleotides, such as ATP, may regulate various cellular functions through specific cell surface receptors. We examine in this report the different secretory effects of ATP and analogs on nontransformed dog pancreatic duct epithelial cells (PDEC). We observed that 1) ATP, UTP, adenosine 5'- O-(3-thiotriphosphate), and, to a lesser extent, β,γ-methylene-ATP, but not adenosine, stimulated125I-efflux from PDEC, suggesting a primary role for P2Y2 receptors, 2) ATP-stimulated125I-efflux was inhibited by 5-nitro-2-(3-phenylpropylamino)benzoic acid, diphenylamine-2-carboxylate, and DIDS, suggesting mediation through Ca2+-activated Cl- channels, 3) ATP stimulated an86Rb+efflux sensitive to BaCl2 and charybdotoxin, thus likely occurring through Ca2+-activated K+ channels, 4) serosal or luminal addition of UTP activated apical Cl-conductance and basolateral K+conductance when nystatin-permeabilized PDEC were studied in an Ussing chamber, suggesting the expression of P2Y2 receptors on both sides of the cell, 5) ATP stimulated mucin secretion, and 6) ATP increases intracellular Ca2+ concentration ([Ca2+]i). In conclusion, ATP and UTP interact with P2Y2 receptors on nontransformed PDEC to increase [Ca2+]i, stimulate mucin secretion, and activate ion conductances; these findings have implications for pancreatic exocrine function in both health and disease, such as cystic fibrosis.
Motion compensation of wavelet coefficients for very low bit rate video coding

We construct a new algorithm for motion compensation of wavelet coefficients. The new approach outperforms standard block matching techniques both in terms of higher PSNR, and better perceptual quality. The algorithm works directly in the wavelet coefficients domain and has been successfully used for wavelet based very low bit rate video coding.
Hybrid Modulation Concept for Five-Level Active-Neutral-Point-Clamped Converter

In this letter, a hybrid modulation concept consisting of three-level space vector modulation (3L-SVM) and phase-shifted pulse width modulation (PS-PWM) is proposed for five-level active-neutral-point-clamped (5L-ANPC) converter. Under this concept, a simpler 3L-SVM plus PS-PWM scheme is applied to realize 5L modulation, instead of using complex 5L-SVM. The control of neutral voltage, flying capacitor voltage, and the improved dc voltage utilization are all implemented. With the help of the proposed concept, well-developed 3L-SVM schemes can be directly applied to the 5L-ANPC converter, which significantly simplify the gating signal generation. This concept can also be applied to other hybrid clamped 5L converters with two dc-link capacitors. It provides a unique solution, which utilize lower level SVM scheme to control higher level multilevel converters.
PARIS: Flexible Plan Adaptation by Abstraction and Refinement

Paris (Plan Abstraction and Refinement in an Integrated System) [4, 2] is a domain independent case-based planning system which allows the flexible reuse of planning cases by abstraction and refinement. This approach is mainly inspired by the observation that reuse of plans must not be restricted to a single description level. In domains with a high variation in the problems, the reuse of past solutions must be achieved at various levels of abstraction.
A Maximum Likelihood Approach to Least Absolute Deviation Regression

Least absolute deviation (LAD) regression is an important tool used in numerous applications throughout science and engineering, mainly due to the intrinsic robust characteristics of LAD. In this paper, we show that the optimization needed to solve the LAD regression problem can be viewed as a sequence of maximum likelihood estimates (MLE) of location. The derived algorithm reduces to an iterative procedure where a simple coordinate transformation is applied during each iteration to direct the optimization procedure along edge lines of the cost surface, followed by an MLE of location which is executed by a weighted median operation. Requiring weighted medians only, the new algorithm can be easily modularized for hardware implementation, as opposed to most of the other existing LAD methods which require complicated operations such as matrix entry manipulations. One exception is Wesolowsky's direct descent algorithm, which among the top algorithms is also based on weighted median operations. Simulation shows that the new algorithm is superior in speed to Wesolowsky's algorithm, which is simple in structure as well. The new algorithm provides a better tradeoff solution between convergence speed and implementation complexity.
Volumetric heat kernel signatures

Invariant shape descriptors are instrumental in numerous shape analysis tasks including deformable shape comparison, registration, classification, and retrieval. Most existing constructions model a 3D shape as a two-dimensional surface describing the shape boundary, typically represented as a triangular mesh or a point cloud. Using intrinsic properties of the surface, invariant descriptors can be designed. One such example is the recently introduced heat kernel signature, based on the Laplace-Beltrami operator of the surface. In many applications, however, a volumetric shape model is more natural and convenient. Moreover, modeling shape deformations as approximate isometries of the volume of an object, rather than its boundary, better captures natural behavior of non-rigid deformations in many cases. Here, we extend the idea of heat kernel signature to robust isometry-invariant volumetric descriptors, and show their utility in shape retrieval. The proposed approach achieves state-of-the-art results on the SHREC 2010 large-scale shape retrieval benchmark.
Analysis of Decision Making Operation In Cognitive Radio Using Fuzzy Logic System

Introduction of flexibility and intelligence in the wireless devices and applications have introduced the concept of Cognitive Radio. This research objective has inspired various research activities on going which included the decision making aspects. In this paper, a decision making process in cognitive radio is analyzed using fuzzy logic system, in which secondary user can use the spectrum effectively. We have selected three descriptive factors for choosing the proper secondary unlicensed user – velocity of the secondary user, spectrum to be utilized by secondary user and distance of the secondary user from primary user. The efficiency of the decision making process in cognitive radios is analyzed. Based on linguistic knowledge 27 rules are set up. The output of the fuzzy logic system gives the probability of the decision based on the three descriptive factors. We show how fuzzy logic system can be used for decision making operation in cognitive radio.
Dynamic robot scheduling using a genetic algorithm

This paper describes a genetic algorithm that was developed for optimizing plans in a robotic competition. The algorithm was used both as a static planner, making plans before matches, and as a dynamic replanner during matches, a task with much stricter demands of efficiency. The genetic algorithm was hybridized with a local search technique, which experiments proved essential to finding good solutions in this complex task. To enable rapid response under environmental changes, a heuristic for immediate response and a contingency planning module were also implemented. Experiments proved that the algorithm was able to generate good plans, and continuously modify them in light of a rapidly changing environment.
The integration of storm water flooding and thermal stress potential in Tainan (Taiwan) and Groningen (Netherlands)

Stormwater flooding and thermal stresses of citizens are two important phenomena for most of the dense urban area. Due to the climate change, these two phenomena will occur more frequently and cause serious problems. Therefore, the sectors for public health and disaster management should be able to assess the vulnerability to stormwater flooding and thermal stress. To achieve this goal, two cities in different climate regions and with different urban context have been selected as the pilot areas, i.eY. , Tainan, Taiwan and Groningen, Netherlands. Stormwater flooding and thermal stress maps will be produced for both cities for further comparison. The flooding map indicates vulnerable low lying areas, where the thermal stress map indicates high Physiological Equivalent Temperature (PET) values (thermal comfort) in open areas without shading. The combined map indicates the problem areas of flooding and thermal stress and can be used by urban planners and other stakeholders to improve the living environment.
Sarcolemmal-restricted localization of functional ClC-1 channels in mouse skeletal muscle

Skeletal muscle fibers exhibit a high resting chloride conductance primarily determined by ClC-1 chloride channels that stabilize the resting membrane potential during repetitive stimulation. Although the importance of ClC-1 channel activity in maintaining normal muscle excitability is well appreciated, the subcellular location of this conductance remains highly controversial. Using a three-pronged multidisciplinary approach, we determined the location of functional ClC-1 channels in adult mouse skeletal muscle. First, formamide-induced detubulation of single flexor digitorum brevis (FDB) muscle fibers from 15–16-day-old mice did not significantly alter macroscopic ClC-1 current magnitude (at −140 mV; −39.0 ± 4.5 and −42.3 ± 5.0 nA, respectively), deactivation kinetics, or voltage dependence of channel activation (V1/2 was −61.0 ± 1.7 and −64.5 ± 2.8 mV; k was 20.5 ± 0.8 and 22.8 ± 1.2 mV, respectively), despite a 33% reduction in cell capacitance (from 465 ± 36 to 312 ± 23 pF). In paired whole cell voltage clamp experiments, where ClC-1 activity was measured before and after detubulation in the same fiber, no reduction in ClC-1 activity was observed, despite an ∼40 and 60% reduction in membrane capacitance in FDB fibers from 15–16-day-old and adult mice, respectively. Second, using immunofluorescence and confocal microscopy, native ClC-1 channels in adult mouse FDB fibers were localized within the sarcolemma, 90° out of phase with double rows of dihydropyridine receptor immunostaining of the T-tubule system. Third, adenoviral-mediated expression of green fluorescent protein–tagged ClC-1 channels in adult skeletal muscle of a mouse model of myotonic dystrophy type 1 resulted in a significant reduction in myotonia and localization of channels to the sarcolemma. Collectively, these results demonstrate that the majority of functional ClC-1 channels localize to the sarcolemma and provide essential insight into the basis of myofiber excitability in normal and diseased skeletal muscle.
Toward Monitoring Fault-Tolerant Embedded Systems (Extended Abstract)

Flight-critical systems for aircraft and spacecraft must be ultra-reliable and so are designed to be fault-tolerant. For embedded control systems and data buses, a primary means for achieving fault-tolerance is hardware replication to provide redundancy so that the system can survive random hardware faults of individual components. Nevertheless, a system may fail to meet its reliability requirements for one of three reasons: (1) the system suffers an unexpectedly high number of hardware faults, (2) hardware faults lead to unexpected system-level failures, or (3) software or design bugs result in systematic faults. Indeed, failures may result from a combination of these reasons (e.g., an unanticipated hardware faults triggers the execution of fault-management software that is incorrectly designed, leading to system failure). A monitor [1], [2] is a runtime verification mechanism that observes the behavior of a system and detects if it is consistent with its specified correct behavior. Ultrareliable systems stand to benefit from runtime monitors, if monitors can be constructed to increase their reliability. However, ultra-reliable systems, which are often distributed, real-time, fault-tolerant systems, have largely been ignored by the monitoring community. The challenges associated with monitoring this class of systems include the following: • How to ensure the monitor does not interfere with the monitored system delivering its services and meeting its real-time deadlines. • How to ensure the monitoring infrastructure does not reduce the reliability of the monitored system. • How to monitor a fault-tolerant system, since faulttolerant systems are distributed to provide replication. • How to monitor for faults. We propose these are all important open research questions. In this extended abstract, we motivate the need for runtime monitoring for ultra-reliable systems. We motivate this need by first presenting an example of a
Habituation of Predator Inspection and Boldness in the Guppy (Poecilia reticulata)

This study examined habituation of the predator inspection behavior in the guppy ( Poecilia reticu- lata ) and its relationship with boldness (open field locomotion). Two different strategies were discovered: (1) initial inspection of a predator-like fish, correlated with boldness; (2) subsequent surveillance, governed by a random underlying process and unrelated to boldness. The surveillance inspection is probably linked with anti-predator vigilance. Possible implications to between-population variation in inspection behavior are dis- cussed.
Normal-Metal Hot-Electron Nanobolometer With Johnson Noise Thermometry Readout

The sensitivity of a THz hot-electron nanobolometer (nano-HEB) made from a normal metal is analyzed. Johnson Noise Thermometry (JNT) is employed as a readout technique. In contrast to its superconducting Transition-Edge Sensor (TES) counterpart, the normal-metal nano-HEB can operate at any cryogenic temperature depending on the required radiation background limited Noise Equivalent Power (NEP). It does not require bias lines; 100s of nano-HEBs can be read by a single low-noise X-band amplifier via a filter bank channelizer. The modeling predicts that even with the sensitivity penalty due to the amplifier noise, an NEP ~ 10-20-10-19W/Hz1/2 can be expected at 50-100 mK in 10-20 nm thin titanium (Ti) normal metal HEBs with niobium (Nb) contacts. This NEP is fairly constant over a range of readout frequencies ~ 10 GHz. Although materials with weaker electron-phonon coupling (bismuth, graphene) do not improve the minimum achievable NEP, they can be considered if a larger than 10 GHz readout bandwidth is required.