Miracle-dz/UniFAR-FTUs huggingface dataset:
Large Bandwidth Digital Phase Shifters With All-Pass, High-Pass, and Low-Pass Networks

Large bandwidth phase shifters using a combination of an all-pass network (APN), a high-pass network (HPN), and a low-pass networks (LPN) are presented. An exact equiripple phase-shift response is first derived for an infinite series of an APN using phase superposition. However, the realization is impractical and the topology is modified by truncating the series of the APN. A pair of properly designed HPN and LPN is added to compensate for the phase error introduced by the truncation. To verify the topology, phase-shifting networks of 90° and 180° with a bandwidth from less than 100 MHz to more than 2 GHz are designed and measured. A frequency ratio of 35 and 25 has been achieved by the 90° and 180° phase-shifting networks, respectively.
Suppression of auditory nerve activity by stimulation of efferent fibers to cochlea.

THE OBSERVATION that prompts this communication is illustrated in Fig. 1 which shows electrophysiological responses obtained from the round window membrane of the cochlea of a cat. In the upper row (click alone) the electrical events that customarily follow click stimulation are to be seen. The major deflections recordable under these conditions are labelled according to a current convention on the trace labelled C. M is the aural microphonic response, derived in all likelihood from the hair cells in the cochlea; NI and NIX are considered to be the signs of neural events. Since Nl is the first, or earliest, neural event known to occur in the auditory system, it has generally been agreed that NI is the sign of the discharge of the afferent fibers of the auditory nerve (1). A change in its magnitude is ordinarily taken to mean that a corresponding change has occurred in the amount of excitation produced by the sound stimulation. In the second row of Fig. 1, clicks identical to those in the first row were presented; while these were delivered to the ear, however, electrical shocks were being applied to the floor of the medulla. As can be seen, the effect of these shocks is to produce partial or complete suppression of both NI and NI1, with little or no change in the magnitude of M. This change is reversible, for when the shocks were discontinued, the normal click response returned. As will be developed below, this observation means that nerve impulses aroused in the medulla by the electrical stimulation pass out to the cochlea where, through a physiological interaction, they suppress the expected auditory nerve inflow.
Using Video Tutorials to Reduce Cognitive Load and Frustration for Early Learners of 3D Maya: A Comparative Case Study Discussion on Knowledge Visualisation Modes

This study investigates the reduction in frustration experienced by early learners of 3D Maya by reducing the cognitive load of the learning materials. It compares the relative efficacy of the traditional front-of-class demonstration with printable text and image, and narrated video format -- with the main focus on the latter. It found that participants preferred the video tutorial over other formats and reported higher satisfaction with the overall learning experience. This was due to the reduced cognitive load of the video tutorial when compared to the other formats.
High performance bulk mode gallium nitride resonators and filters

In this paper, measurements and characterization results of several micromechanical bulk-mode resonators and filters fabricated from single crystalline gallium nitride are presented. A 167.6 MHz length-extensional mode resonator is demonstrated that exhibits an unloaded quality factor of 1370 and motional impedance of 485 Ω at atmospheric pressure and 300 K. The ƒ×Q values of the resonators presented in this work measured under ambient conditions are significantly higher than prior work and prove that GaN is a suitable material as a micromechanical resonating element for high-power applications. The relevant material properties of GaN are also characterized.
Cristin Bigan : Signal Dependent KL Transform for ECG Signals Representation 9 2

Abstract: The general transform processes are all members of the signal independent, or fixed, class of transforms. All such transforms have a predefined transform vectors which do not change. The advantage of such transforms besides fast algorithms, is the selection of a transform according to its specific properties in relation to a signal of known characteristics. In many instances, however, the characteristics of the signal may be complex, or even unknown. In such cases selection of an unsuitable transform with give poor results. Signals may also contain components suited to different transforms. A signal comprising pure tones plus Dirac functions, for example, will not be efficiently processed by a Fourier transform, which cannot express Dirac functions easily. The statistically best block transform (in terms of decorrelation of the signal samples, and energy repacking) is, a signal dependent one, the Karhunen Loeve Transform (KLT) used here for large databases of ECG compression and representation.
Nonsmooth control design of mechanical systems with friction in the sense of Filippov

Utilizing the notion of Filippov solution, a sliding mode control law is derived for generic second order nonlinear mechanical system with friction. The control law is designed with some tunable parameters and optional functions. The asymptotically stability of the closed-loop system is proved by the concept of the solution, nonsmooth analysis and nonsmooth Lyapunov stability theory. By some numerical examples, the correctness of the control law is illuminated. Finally, the validity of the controller design is verified by a simulation example for a flight simulation table system with Stricbeck friction model.
Learning Static Parallel Portfolios of Algorithms

We present an approach for improving the performance of combinatorial optimization algorithms by generating an optimal Parallel Portfolio of Algorithms (PPA). A PPA is a collection of diverse algorithms for solving a single problem, all running concurrently on a single processor until a solution is produced. The performance of the portfolio may be controlled by assigning different shares of processor time to each algorithm. We present a method for finding a static PPA, in which the share of processor time allocated to each algorithm is fixed. The schedule is shown to be optimal with respect to a given training set of instances. We draw bounds on the performance of the PPA over random instances and evaluate the performance empirically on a collection of 23 state-of-the-art SAT algorithms. The results show significant performance gains (up to a factor of 2) over the fastest individual algorithm in a realistic setting.
Delayed Hypersensitivity Reaction: An Increasingly Recognized Complication of Metal-on-Metal Total Disc Replacement

We report the case of a 32-year-old woman who presented with pain recurrence 20 months after she underwent a C5C6 metal-on-metal total replacement. Plan radiographs demonstrated a modification of the shape of the vertebral bodies making the prosthesis more protruding. Then, infection has been ruled out and patch testing revealed a strongly positive reaction for chromium and cobalt. The prosthesis has been removed and a fusion achieved using a cage filled with bone graft. She has been immediately and fully relieved from her pain. We report the radiological signs that enabled early diagnosis and treatment allowing favorable outcome.
Experiences with a Research Product: A Robot Avatar for Chronically Ill Adolescents

This chapter discusses challenges related to studying the use and usefulness of research products (robust, high fidelity prototypes placed in real use contexts for research purposes). Methods and methodologies for studying use and usefulness of such research products embedded in users’ everyday lives are still lacking and need to be better established. By presenting a case of such research product in use, a robot avatar, we wish to illustrate how new knowledge of relevance for both designers and users can be gained. The robot avatar was designed to represent chronically ill adolescents at school, improving his/hers learning opportunities, as well as helping maintain social connections with peers. The chapter shows how methods were adapted and tools designed to work with this user group and learn about the role of avatars in education and reduction of social isolation. The value of using the avatar, and similar research products, is considered.
Reconnaissance-Attack Parsing

In this paper wc will describe an approach to parsing one major component of which is a stragegy called RECONNAISSANCEATTACK. Under this strategy, no structure building is attempted until after completion of a preliminary phase designed to exploit low-level information to the fullest possible extent. This first pass then defines a set of constraints that restrict the set of available options when structure building proper begins. R-A parsing is in principle compatible with a variety of different views regarding the nature of syntactic representation, though it fits more comfortably with some than with others--a point to which we shall return.
Implementation of virtual network management system with SLA on NetFPGA

With the increase in the bandwidth needs of network service, the customer requirements for Quality of Service (QoS) are also higher. Although the QoS guarantees can be offered by signing the Service Level Agreement (SLA), the costs of infrastructures are increased as well. This paper proposes a shortest path algorithm based on SLA, combined with the resource allocation for virtual networks (VNs). It can help service providers to enhance the achievement of overall SLA contracts in the case of lack of resources. This architecture was also implemented on NetFPGA platforms applied with the concept of OpenFlow to meet the demands of network performance and flexibility. Finally, the experimental results show that the proposed algorithm can dynamically provide the better path to reach the SLA achievement rates.
Distance Bounding Facing Both Mafia and Distance Frauds

Contactless technologies such as radio-frequency identification, near field communication, and sensor networks are vulnerable to mafia and distance fraud. These types of fraud are aimed at successfully passing an authentication protocol by cheating on the actual distance between the prover and the verifier. Distance-bounding protocols have been designed to cope with these security issues, but none of them properly resist these two types of fraud without requiring additional memory and computation. The situation is even worse considering that just a few distance-bounding protocols are able to deal with the inherent background noise on the communication channels. This paper introduces a noise-resilient distance-bounding protocol that resists both mafia and distance fraud. The security of the protocol is analyzed against known attacks and illustrated by experimental results. The results demonstrate the significant advantage of the introduced lightweight design over previous proposals.
The neurobiological basis of inter-individual variability in visual perception

Visual perception is the conscious experience that is unique to each individual. However, conventional neuroscience studies tend to focus on the commonality in visual perception across different individuals and fail to address the key properties of any conscious experience - its individuality and subjectivity. In my thesis, I investigated the neurobiological basis of perceptual variability across healthy human adults, through a combined approach of psychophysics, in-vivo MR imaging, in-vitro histological imaging, and computational modeling. I found that perception of local and global visual features, as assessed respectively from visual discrimination of local feature details and visual illusion induced by global feature contexts, exhibits a ten-fold inter-individual variability that correlates with the morphology of primary visual cortex. Specifically, an increase in the surface area of primary visual cortex is associated with a shift in the scope of visual feature perception from global-context-oriented to local-detail-oriented, where individuals with smaller visual cortical surface area experience stronger visual illusion and individuals with larger visual cortical surface area perform more accurate visual discrimination. Intriguingly, an increase in the thickness of primary visual cortex has the opposite impact, where visual discrimination is less accurate at visual field locations corresponding to thicker parts of primary visual cortex. The functional impact that visual cortical anatomy exerts on visual feature perception is recapitulated in visual neural selectivity. I found that in individuals with larger surface area of primary visual cortex, visual cortical neurons exhibit higher selectivity and respond to a smaller, localised visual field range. By contrast, at thicker parts of primary visual cortex, visual cortical neurons exhibit lower selectivity and respond to a larger, globalised visual field range. The opposite functional impacts exhibited by the two morphological dimensions, the surface area and the thickness, of primary visual cortex can nonetheless be unified under the framework of intracortical scaling. I found that the scaling of intracortical connectivity with visual cortical morphology shifts the scope of both visual feature perception and visual neural selectivity between global- and local-oriented. Together these findings revealed that the individuality in visual feature perception arises neurobiologically from the variability in visual cortical morphology, through the mediation of intracortical connectivity and visual neural selectivity.
High throughput pipelined FPGA implementation of the new SHA-3 cryptographic hash algorithm

In this paper a two-staged pipelined architecture of the new SHA-3 (Keccak) algorithm is presented. The core can operate on both one-block and multi-block messages, realizing all possible modes of Keccak. Special effort has been paid and different design alternatives have been studied to derive efficient FPGA implementations in terms of throughput and throughput/area metrics. The proposed core has been implemented in Xilinx Virtex-5, Virtex-6, and Virtex-7 FPGA technologies and achieves significant improvements compared to existing FPGA implementations. Specifically, for Virtex-5 the proposed architecture achieves better throughput and throughput/area results from 45.8% to 248× and from 8.9% up to 17.9×, respectively. Regarding Virtex-6, the improvements in throughput and throughput/area are from 47.2% up to 18.1× and from 8% up to 27.3×, respectively.
Assessment of Motion Devices Used for Spatial Orientation Research and Training

Abstract : There are many unresolved issues related to motion-based simulators including: 1) should they even be used, 2) if so, what drive configurations might be preferred and to what aspects of flight should they be applied, 3) what motion cities and artifacts are critical, 4) what drive algorithm or set of drive algorithms best utilizes the motion capabilities of a given configuration to emulate critical aircraft motion cities while producing minimal artifacts, and 5) how can pitot-driven algorithms be made more effective at teaching recovery from the perceptual conflicts of spatial disorientation? None of these questions are answered by this paper. What the paper does contain is a description of the capability of a computer simulation of motion simulators that can be used to help quantitatively address these questions. A sample aircraft maneuver is evaluated for several variants of drive configuration and drive algorithm to illustrate the measures for quantitative comparison of motion systems and the level of effort and input data required to make the comparison. The paper indicates the status of an ongoing effort to develop a modeling tool for use by the spatial orientation and flight simulation communities to gain further understanding of the role of motion simulators.
Norms for the Icelandic version of the ACE-III : effects of age and education

Recently the much researched and validated cognitive test battery for dementia screening, Addenbrooke's cognitive examination (ACE-III) was translated into Icelandic. The aim of the study was to collect Icelandic norms for the elderly on the Icelandic version of the ACE (t-ACE) and evaluate whether age or education stratified cut-off scores should be used. The t-ACE was administered to 80 (46 women) cognitively healthy 65-85 year old volunteers with an average of 12.7 years of schooling. The results revealed little difference in performance between age groups. Participants with higher education did perform significantly better on the t-ACE with an average of 95.9 points compared to 90.2 and 90.6 points for those with secondary or elementary education. Furthermore, the correlation between years of schooling and t-ACE score was R = 0.54. The normative data were comparable to what had been seen in other countries and the Icelandic translation of the test appears to be adequate. The performance on the t-ACE was strongly influenced by the individual's education level, indicating that education stratified cut-off scores might be necessary.
Power Reduction using Approximation Function

This paper combines two different styles of asynchronous circuitry used in de-synchronization flow. We offer 20% power savings using approximation functions over previously known architecture while preserving the ability to measure the speed of the circuit at fabrication time or run time. The overhead introduced by additional circuitry is minimal when compared with the baseline dual-rail design.
A comparative study of segment representation for biomedical named entity recognition

Biomedical Named Entity Recognition (Bio-NER) is an important subtask of Biomedical Text Mining (BioTM), where the performance of further tasks, such as relation extraction, protein-protein interaction and hypothesis generation depend on the performance of Bio-NER. Bio-NER involves determining the biomedical named entities, such as DNA, RNA, cell types, gene and protein present in the biomedical research articles. Annotating the dataset for training the classifier to recognize and classify named entities is the crucial task in BioNER. Segment representation (SR) is an efficient way of annotating Biomedical Named Entities (BioNEs) within a sentence to differentiate them from non-BioNEs. In this paper, we have used Support Vector Machines (SVMs) and Conditional Random fields (CRFs) to train different BioNER models with the benchmark JNLPBA 2004 and i2b2 2010 shared task dataset using different SRs. The performance of SR models shows that more complex the model worse performance of f-score.
Development of teaching in order to improve learning and support students' motivation

In general it is easily understood that good motivation of students supports their willingness to study, which of course supports their learning. Based on that, it is seen important to consider also motivational issues in planning the use of different teaching methods and in developing the learning environments. This paper presents different ways to improve teaching methods in order to better support the learning of individual students and at the same time increase their motivation towards the central learning objectives. Development of those teaching methods was partly based on the students’ feedback during the course. It was clearly noticed that some teaching methods, such targeted exercises, improved learning and understanding. Also an increase in the motivation was seen, which comes probably from the feeling of success, but the separation of the all facts affecting in motivation was not possible to understand thoroughly due to the complex nature of motivation. However the linking between motivation and successful studying was noticed. It was seen, for example that student with weakest motivation had more problems in their time management, too. It could be concluded that it is more important to start the development of teaching from the supporting of the motivation, because good motivation is the first requirement for effective studying and learning.
Machine Learning for Shallow Inter pretation of UserUtterancesin Spoken DialogueSystems PiroskaLendvai ILK ResearchGroup Tilburg University

We investigateto whatextentautomatic learningtechniquescanbeusedfor shallow interpretationof userutterancesin spoken dialoguesystems.This taskinvolvesdialogueact classification,shallow understandingand problemdetection simultaneously . For this purpose we train both a rule-induction and a memory-basedlearningalgorithm on a largesetof surfacefeaturesobtainedby affordablemeansfrom anannotatedcorpusof human-machinedialogues.Using a pseudo-e xhausti ve search,the parametersof both algorithmsareoptimized. Theshallow interpretationtaskturnsout to be a difficult one, partly sincethere are94 typesof useranswers.The best overall accuracy (exactmatch)obtained was 73.5%, which is a significant improvementover the baseline. The best averageprecisionandrecallfor dialogue actclassificationwas91.2%,for classifying slot types86.8%andfor detecting communicationproblems91.0%.
Effect of network topology on the controllability of voter model dynamics using biased nodes

This paper examines the effects of biased nodes on the voter model dynamics where each node is characterized by binary states si = ±1. For a fully connected graph, the master equation is shown to have the form of the Fokker-Planck equation, and necessary and sufficient conditions for the existence of a polynomial solution are investigated. Numerical simulations and analytical results are studied for a complete graph and the Erdös-Rényi network to reveal several interesting characteristics of the dynamical system. One of the key findings is that the equilibrium probability density of the network can be controlled by selecting the size of the influence groups. Population size, relative size of the biased groups, initial conditions and network parameters such as connection probabilities are discussed and their effects on the equilibrium probability density and time to convergence are investigated and reported.
Work stealing for time-constrained octree exploration: application to real-time 3D modeling

This paper introduces a dynamic work balancing algorithm, based on work stealing, for time-constrained parallel octree carving. The performance of the algorithm is proved and confirmed by experimental results where the algorithm is applied to a real-time 3D modeling from multiple video streams. Compared to classical work stealing, the proposed algorithm enforces a relaxed width first octree carving that enables to stop computations at anytime while ensuring a balanced carving.
Regression Analysis for Energy and Lifetime Prediction in Large Wireless Sensor Networks

Wireless communication technologies are used to collect information from sensitive, hostile and inaccessible environments. They are used in both military and civil applications that include environmental, medical, military and industrial fields. Routing data to a processing center or a base station requires mechanisms for energy conservation at the end of the prolonged lifetime of the network. The simulation in this case is very constrained by the high density of the network. Existing tools cannot simulate large networks with millions of sensors. In this paper, we propose a new method using statistical regression analysis in order to predict the energy consumption and the lifetime of a wireless sensor network with hundreds or thousands of sensors by simulating smaller networks. We have validated the proposed method using a Revised LEACH protocol. Indeed, this method can be used for other protocols and other kind of simulations with the purpose of evaluating a specific parameter.