Miracle-dz/UniFAR-FTUs huggingface dataset:
A lightweight early arbitration method for low-latency asynchronous 2D-mesh NoC's

A new asynchronous low-latency interconnection network is introduced for a 2D mesh topology. The network-on-chip, named AEoLiAN, contains a fast lightweight monitoring network to notify the routers of incoming traffic, thereby allowing arbitration and channel allocation to be initiated in advance. In contrast, several recent synchronous early arbitration methods require significant resource overhead, including use of hybrid networks, or wide monitoring channels and additional VCs. The proposed approach has much smaller overhead, allowing a finer-grain router-by-router early arbitration, with monitoring and data advancing independently at different speeds. The new router was implemented in 45nm technology using a standard cell library. It had 52% lower area than a similar lightweight synchronous switch, xpipesLite, with no early arbitration capability. Network-level simulations were then performed on 6 diverse synthetic benchmarks in an 8×8 2D mesh network topology, and the performance of the new network was compared to an asynchronous baseline. Considerable improvements in system latency over all benchmarks for moderate traffic were obtained, ranging from 34.4-37.9%. Interestingly, the proposed acceleration technique also enabled throughput gains, ranging from 14.7-27.1% for the top 5 benchmarks. In addition, a zero-load end-to-end latency of only 4.9ns was observed, for the longest network path through 15 routers and 14 hops.
UTILIZATION OF PARALLELIZATION ALGORITHMS IN INSAR/PS-INSAR PROCESSING

GermanAerospaceCenter(DLR),Oberpfaﬁenhofen,82234Wessling,Germany,Email: bert.kampes@dlr.deABSTRACTThisstudydescribesamethodforInSAR/PS-InSARprocessing using parallelization algorithms. TheInSAR/PS-InSARprocessingchainisanalyzedfromtheaspectofthecomputationalload,whichresultsinaspeciﬂcparallelizationmodel. Thetheoreticalcon-ceptfortheportingofDelftObject-orientedRadarInterferometricSoftware(Doris)intoaparallelcom-putationalenvironmentisdescribed. Thefeaturesofthepresentedparallelizationmodelincludee–-cientinterprocessorcommunicationsutilizedbyMPI(MultiPassageInterface)anda\chained"datadis-tributioncapability. AnexampleofthemappingprocessisillustratedforthecaseofsimpleInSARprocessing.Keywords:InSAR,PS-InSAR,parallelization,Dorissoftware.1. INTRODUCTIONClassicalInSARprocessingisknowntobecompu-tationallylaborious.Althoughmanyaspectsofthedataprocessingchainarealreadywellknown,thereisaneedformoree–cientmethodsthatprovidere-sultsinlessertime. Especiallytheadventofradartime-seriesanalysis,[1],neededforprecisepin-pointdeformationmeasurements,isadrivingforceforim-provementsinprocessingtechnology,duetotheverylargequantitiesofdataandintermediateproducts.Improvementsinprocessingspeedcanbeobtainedbyastrictinitialselectionofpotentiallyusefulre-°ections,butthiswillalsolimitpotentialalternativeapplications. A-posterioriimplementationofsmallcorrectionstotheprocessingchain,aswellasstor-ageofvariance-covarianceinformationrequireskeep-ingasmuchinformationathandaspossible.Thispaperdiscussespossibleimprovementsintheprocessingchainbymeansofacombinedparalleliza-tionanddistributionalgorithm. Theprocessingchainisanalyzedfromtheaspectofthecomputa-tionalload.Consequently,theanalysisresultedwiththespeciﬂcparallelizationmodeloftheInSARap-plicationspace. Thedevelopedmodeleﬁectivelymakesuseofthein-herentlyspatiallylocalizednatureofmostprocessingstepsoftheinterferogramproductionalgorithmtoformulatethedivisionoflabor,bothspatiallyacrosstheinputdataandtemporallyalongthepipelineofalgorithmtasks. Thisformulationcanbeusedtosplittheloadamongallavailableprocessingunits,byeitherusingmultiplethreadsofexecutiononamulti-processorconﬂguration,orbyamessagepassingin-terfacetechnique(MPI),[2],tocoordinatemultipleprocessesdistributedacrossaclusterofcomputers.Subsequently,theconceptfortheparallelizationofDoris(DelftObject-orientedRadarInterferometricSoftware),[3],isdevelopedandpresented.Asacasestudy,theMatlab/Octavedevelopmentenvironmentisusedforthepreliminaryevaluationoftheperformanceofthepresentedparallelizationmodel.ThepaperproceedsinSection2withadiscussionontheInSAR/PS-InSARprocessingalgorithmsandintroducestheprocessingandperformancecubesasthemeanfortheperformanceevaluationofthepro-ductionchainwithinthesingle/multi-processoren-vironment.Section3introducestheconceptfortheparallelizationoftheDorissoftwaretogetherwithbasicsofimplementedinterprocessorcommunicationmodel(MPI-MessagePassingInterface),[2],anddatadistributionmodel.Section4discussesthere-sultsofnumericalexperimentsperformedusingthepreviouslydiscussedmodelwithintheMatlabenvi-ronment.Finally,section5outlinestheperspectivesoffutureworkandpresentstheconclusions.
An application of constraint-based task specification and estimation for sensor-based robot systems

This paper shows the application of a systematic approach for constraint-based task specification for sensor-based robot systems to a laser tracing example. This approach integrates both task specification and estimation of geometric uncertainty in a unified framework. The framework consists of an application independent control and estimation scheme. An automatic derivation of controller and estimator equations is achieved, based on a geometric task model that is obtained using a systematic task modeling procedure. The paper details the systematic modeling procedure for the laser tracing task and elaborates on the task specific choice of two types of task coordinates: feature coordinates, defined with respect to object and feature frames, which facilitate the task specification, and uncertainty coordinates to model geometric uncertainty. Furthermore, the control and estimation scheme for this specific task is studied. Simulation and real world experimental results are presented for the laser tracing example.
MaTrust: An Effective Multi-Aspect Trust Inference Model

Trust is a fundamental concept in many real-world applications such as e-commerce and peer-to-peer networks. In these applications, users can generate local opinions about the counterparts based on direct experiences, and these opinions can then be aggregated to build trust among unknown users. The mechanism to build new trust relationships based on existing ones is referred to as trust inference. State-of-the-art trust inference approaches employ the transitivity property of trust by propagating trust along connected users. In this paper, we propose a novel trust inference model (MaTrust) by exploring an equally important property of trust, i.e., the multi-aspect property. MaTrust directly characterizes multiple latent factors for each trustor and trustee from the locally-generated trust relationships. Furthermore, it can naturally incorporate prior knowledge as specified factors. These factors in turn serve as the basis to infer the unseen trustworthiness scores. Experimental evaluations on real data sets show that the proposed MaTrust significantly outperforms several benchmark trust inference models in both effectiveness and efficiency.
A Factor Analysis of Trade Integration: The Case of Asian and Oceanic Economies

We study trade integration among 15 selected Asian and Oceanic economies using factor models. The principal component approach is employed to extract the common factor that drives trade integration from bilateral trade integration series. It is found that the estimated common trade integration factor has strong seasonal and deterministic components. In accordance with theory, the common trade integration factor is significantly associated with the economic growth and the trade barriers of the 15 economies. However, we find no evidence that the common trade integration factor is affected by foreign direct investment. The basic model is extended to incorporate an ASEAN factor that affects trade integration among the ASEAN economies in our sample.
The nom Profit-Maximizing Operating System

In the near future, cloud providers will sell their users virtual machines with CPU, memory, network, and storage resources whose prices constantly change according to market-driven supply and demand conditions. Running traditional operating systems in these virtual machines is a poor fit: traditional operating systems are not aware of changing resource prices and their sole aim is to maximize performance with no consideration of costs. Consequently, they yield low profits. We present nom, a profit-maximizing operating system designed for cloud computing platforms with dynamic resource prices. Applications running on nom aim to maximize profits by optimizing simultaneously for performance and resource costs. The nom kernel provides them with direct access to the underlying hardware and full control over their private software stacks. Since nom applications know there is no single ``best'' software stack, they adapt their stacks' behavior on the fly according to the current price of available resources and their private utility from them, which differs between applications. We show that in addition to achieving up to 3.9x better throughput and up to 9.1x better latency, nom applications yield up to 11.1x higher profits when compared with the same applications running on Linux and OSv.
Real-Time landslide monitoring using single-frequency PPP: Proof of concept

Strong need for a sophisticated landslide monitoring and alerting system has grown especially in mountainous regions. Traditionally, monitoring is performed using time-domain reflectometry by geodesists. Since a few years the Global Positioning System (GPS) dual-frequency Real-Time Kinematic (RTK) approach is widely used for monitoring landslides. However, it should be noted that the setup and the support of dual-frequency RTK is cost intensive. In order to reduce the costs of a GPS-based landslide monitoring system, one could use single-frequency low-cost receivers for RTK or try to utilize a Precise Point Positioning (PPP) approach. A landslide monitoring system using both single-frequency RTK and PPP is developed by Graz University of Technology and TeleConsult Austria GmbH within the GeoWSN project. This paper describes the general structure of a GPS-based landslide monitoring system and discusses aspects of the used PPP approach.
Operationalising the capability approach: developing culturally relevant indicators of indigenous wellbeing – an Australian example

Abstract The tension that exists between the worldviews of Indigenous peoples and government reporting frameworks is what Taylor has termed ‘the recognition or translation space’. The meaningful operation of the ‘recognition space’ hinges on four key points – firstly, why measure wellbeing, secondly, how wellbeing is conceptualised, thirdly, by what process the wellbeing measures are decided, and finally, who makes those decisions. Sen’s capability approach is concerned with development as a process of expanding people’s freedoms to live the life they have reason to value. It is in this spirit of freedom that Sen has not prescribed a fixed list of functioning and capabilities. The open-ended nature of this approach, in letting the identification of important capabilities be dependent on specific contexts and people’s own values, aligns with the United Nations Declaration on the Rights of Indigenous peoples which asserts that Indigenous people must be agents of their own development. This paper contributes to the understanding of what a good life means by augmenting the capability approach to incorporate Indigenous worldviews. Through participatory research methodologies we define and select indicators of wellbeing which are grounded in the lived experiences of the Yawuru people in Broome, Western Australia.
The Effect of Bangerter Occlusion Foils on Blepharospasm and Hemifacial Spasm in Occlusion-Positive and Occlusion-Negative Patients

Objective: To test the hypothesis that occlusion-positive (OP) patients with blepharospasm (BEB) or hemifacial spasm (HFS) will benefit from a Bangerter occlusion foil (BOF), compared to occlusion-negative (ON) patients. OP/ON was based on immediate improvement in spasm with placement of a hand in front of either eye. Design: Prospective non-randomised single-centre pilot study. Participants: Fifteen-patients (6 BEB, 9 HFS). Methods: Patients were identified as OP or ON and wore highest-density BOF tolerable over one spectacle lens for 1 month. Outcomes were assessed at 1 month. Main Outcome Measures: Validated quality-of-life questionnaire (CDQ-24), scores of blink-rate and spasm severity assessed by two observers from video-recordings. Results: OP group had mean improvement in all scores. There was no change or worsening of scores in the ON group. In both BEB and HFS, more OP patients reported subjective benefit from wearing a foil (2 of 4 BEB, and 2 of 2 HFS) compared to the ON group (0 of 2 BEB, and 1 of 7 HFS). Conclusion: OP patients with BEB and HFS are more likely to experience improvement in spasms from wearing a BOF compared to ON patients. The occlusion test should be considered on all patients with BEB or HFS.
Self-Organizing Maps Approach to Object Localization in Sonar Imagery

The Self-Organizing Map is well-known as the unsupervised classification method. It is employed as classifier in various applications such as image segmentation. The main purpose of this paper is to identify and detect an object of interest on side scan sonar image. This work is performed by two steps. The first one is to split an image into regions of uniform texture using the Gray Level Co-occurrence Matrix Method (GLCM) which is widely used in texture segmentation application. The last one address the unsupervised learning method based on the Artificial Neural Networks (Self-Organizing Map or SOM) used for determining the comparative model of object of interest from an image. To increase the performance of SOM, we propose a penalty function based on data histogram visualization. After a brief review of both techniques (GLCM and SOM), we present our method and some results from several experiments on the real world data set.
Automatic 3D modeling of archaeological objects

A wide-spread use of 3D models in archeology application requires low cost equipment and technically simple modeling procedures. In this context methods for automatic 3D modeling based on fully automatic techniques for 3D views registration will play a central role. This paper proposes a very robust procedure which does not require special equipment or skill in order to make 3D models. The results of this paper, originally conceived to address the costs issues of heritage's modeling, can be profitably exploited also in other modeling applications.
Robust stabilization control of unknown small-scale helicopters

In this paper, we address the attitude and vertical stabilization problem for small-scale helicopters. An emergency controller that would successfully stabilize the helicopter in a safe flight mode when a pilot/autopilot fails to control it, owing to unexpected reasons, is of outmost importance in flight control systems. In this direction, we propose a low complexity nonlinear control scheme that drives the angles and the vertical speed to zero with prescribed transient and steady state response, without incorporating any knowledge of the dynamic model parameters in the control design. The stereographic coordinates were employed to model the attitude state of the helicopter in an attempt to guarantee the safe stabilization for every possible initial orientation without introducing any representation singularities as in the Euler angles representation or increasing complexity as in conventional four element quaternions. Moreover, the transient and steady state performance of the proposed scheme is a priori determined even in the presence of external disturbances. Furthermore, the overall control scheme can be easily implemented on embedded flight systems equipped with low-cost sensors. Finally, simulation and experimental results on a realistic platform verify the efficacy of the proposed method.
Speciation as automatic categorical modularization

Many natural and artificial systems use a modular approach to reduce the complexity of a set of subtasks while solving the overall problem satisfactorily. There are two distinct ways to do this. In functional modularization, the components perform very different tasks, such as subroutines of a large software project. In categorical modularization, the components perform different versions of basically the same task, such as antibodies in the immune system. This second aspect is the more natural for acquiring strategies in games of conflict, An evolutionary learning system is presented which follows this second approach to automatically create a repertoire of specialist strategies for a game-playing system. This relieves the human effort of deciding how to divide and specialize. The genetic algorithm speciation method used is one based on fitness sharing. The learning task is to play the iterated prisoner's dilemma. The learning system outperforms the tit-for-tat strategy against unseen test opponents. It learns using a "black box" simulation, with minimal prior knowledge of the learning task.
Texture synthesis via a noncausal nonparametric multiscale Markov random field

Our noncausal, nonparametric, multiscale, Markov random field (MRF) model is capable of synthesizing and capturing the characteristics of a wide variety of textures, from the highly structured to the stochastic. We use a multiscale synthesis algorithm incorporating local annealing to obtain larger realizations of texture visually indistinguishable from the training texture.
Indoor localization on depth data and digital-piano decoder algorithm (D-PDA)

In this paper, we focus on the need for indoor localization in disaster situations with power cut off or damaged. Indoor localization is always a problem in the field of the rescue robot. This paper proposes an idea based on depth data from Kinect and Digital-Piano Decoder Algorithm. The depth data can help get the location of the marker in relative robot coordinates and the D-PDA help decode the geographic location of the marker. Then we make the coordinate transformation to get the robot's location. A stable, accurate Digital-Piano code (D-P code) is presented and the corresponding Digital-Piano Decoder Algorithm (D-PDA) will be elaborated.
CESADS - Centralised ESTRACK Status and Diagnostic System

This paper presents CESADS, a knowledge-based Monitoring and Diagnostic system targeted at preventing space link losses in satellite control missions. CESADS integrates fuzzy knowledge and rules. It is composed of a Server and four clients, for knowledge acquisition, space link assessment and monitoring, reporting and management. An Operational Prototype was developed for the European Space Tracking Network of the European Space Agency, using Kiruna ground-station to demonstrate CESADS concept and philosophy.
A chaos model of subharmonic oscillations in current mode PWM boost converters

Chaos concepts formulated in a discrete form were applied to examine instability conditions in a current mode PWM boost converter under open and closed outer-loop conditions. A simple expression for the maximum duty cycle for subharmonic-free operation was developed and applied to asses the effects of the outer loop on subharmonic oscillations in the converter under study.
ContentPlace: social-aware data dissemination in opportunistic networks

This paper deals with data dissemination in resource-constrained opportunistic networks, i.e., multi-hop ad hoc networks in which simultaneous paths between endpoints are not available, in general, for end-to-end communication. One of the main challenges is to make content available in those regions of the network where interested users are present, without overusing available resources (e.g., by avoiding flooding). These regions should be identified dynamically, only by exploiting local information exchanged by nodes upon encountering other peers. To this end, exploiting information about social users' behaviour turns out to be very efficient. In this paper we propose and evaluate ContentPlace, a system that exploits dynamically learnt information about users' social relationships to decide where to place data objects in order to optimise content availability. We define a number of social-oriented policies in the general ContentPlace framework, and compare them also with other reference policies proposed in the literature.
Synthesis of Co–TiO2 nanostructured photocatalytic coatings for MDF substrates

This paper describes for the first time the development of novel photocatalytic coatings specifically for medium-density fibreboard (MDF) substrates. Anatase nanostructures were manufactured using a sol–gel synthesis route and subsequently heat-treated to form micro-sized agglomerates. In this study titanium dioxide particles were doped with cobalt in order to reduce the band gap and promote photocatalysis in the visible wavelength range. These agglomerates were then bound to MDF using a polyurethane-based binder. The subsequent coatings were tested under white, green and ultraviolet light using ink intelligent photoactive dyes in a gaseous environment and methylene blue indicator in an aqueous environment. Manufactured particles were also compared to the commercially available products P25 and Kronoclean 7000. The physical and chemical properties of the manufactured particles and substrates were evaluated using electron microscopy, X-ray diffraction and Raman spectroscopy. This work demonstrates the perf.
Entropy-constrained dense disparity map estimation algorithm for stereoscopic images

This paper deals with the stereo matching problem to estimate a dense disparity map. Traditionally a matching metric such as mean square error distortion is adopted to select the best matches associated with disparities. However several disparities related to a given pixel may satisfy the distortion criterion although quite often the choice that is made does not necessarily meet the coding objective. An entropy-constrained disparity optimization approach is developed where the traditional matching metric is replaced by a joint entropy-distortion metric so that the selected disparities reduce not only the reconstructed image distortion but also the entropy disparity. The algorithm sequentially builds a tree avoiding a full search and ensuring good rate-distortion performance. At each tree depth, the M-best retained paths are extended to build new paths to which are assigned entropy-distortion metrics. Simulations show that our algorithm provides better results than dynamic programming algorithm.
Advances in Nonlinear Predictive Control : A Survey on Stability and Optimality

Some recent advances in stability and optimality for the nonlinear receding horizon control (NRHC) or the nonlinear model predictive control (NMPC) are assessed. The NRHCs with terminal conditions are surveyed in terms of a terminal state equality constraint, a termi- nal cost, and a terminal constraint set. Other NRHCs without terminal conditions are surveyed in terms of a control Lyapunov function (CLF) and cost monotonicity. Additional approaches such as output feedback, fuzzy, and neural network are introduced. This paper excludes the results for linear receding horizon controls and concentrates only on the analytical results of NRHCs, not including applications of NRHCs. Stability and optimality are focused on rather than robustness.