Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-dimensional datapath regularity extraction

This paper presents a new method to automatically extract regular structures from logic netlists containing datapath circuitry. The goal of datapath extraction is the exploitation of structural regularity to efficiently obtain regular placements which are typically more compact. Datapaths constitute increasingly sizeable parts of ever more and larger circuits, hence flexible technology-independent layout tools, unlike state of the art datapath compilers, will become critical in the design flow. Our method transforms a circuit’s existing functional hierarchy, if any, into a 2-dimensional hierarchy that is more suitable for subsequent cell-placement, thereby also automating the currently mostly handcrafted task of selective partial hierarchy flattening. Once the two-dimensional structure is known, the remaining placement task is greatly reduced to arranging just one row and one column of the discovered matrix-like structure, allowing for much larger circuits to be placed in one go. Experiments show superior extraction results compared to existing approaches.
Vectorialisation of Raster Colour Images

Vector representation of digital images offer a number of advantages over the more common raster representation, such as scalability and resolution independence. Many efforts have been addressed to scalable raster representations for photographic imagery for portable applications. However, they lack the flexibility and simplicity of vector representation. Vector graphics is a new and little explored alternative to the more common raster representation. This paper is devoted to outline our experience in the field of vectorialisation of photographic raster images and to highlight ongoing research.
Spin-Torque-Nano-Oscillator based neuromorphic computing assisted by laser

In spintronic-based neuromorphic computing systems (NCSs), the switching of magnetic moment in a magnetic tunnel junction (MTJ) or magnetic oscillation in spin torque nano-oscillator (STNO) is used to mimic biological neuron firing. Although using STNO reduces the power consumption significantly, still there is a huge gap between the power consumption of spintronic-based NCS and brain due to the high bias current. In this paper, the power consumption of the proposed STNO-based NCS is reduced by thermally assisting the STNO oscillation through a microwatt nanosecond laser pulse. The experimental results show the power consumption of STNOs in NCS reduces by 56% by heating them up to 10000B0;C. The total power consumption of the proposed laser assisted oscillation-based NCS (LAO-NCS) is reduced by 46% at 100°C compared with a typical STNO-based NCS at room temperature.
A study of haptic linear and pie menus in a 3D fish tank VR environment

New pop-up menu styles such as pie menus and marking menus have proven to be measurably faster and more accurate in mouse and pen-based interfaces. These characteristics suggest that they may also be useful for 3D haptically enhanced environments. This paper reports on our development and evaluation of a pie menu style and two types of linear menu styles. All utilize force to aid the user in option selection and activation. Our evaluation results show that selection using the pie menu is considerably faster and more accurate than both types of linear menu. Selection using push-through or exceed border methods was found to be superior to conventional button selection. We conclude that pop-up pie menus, with the right combination of selection method and assistive forces, can provide an excellent solution to providing menu choices in 3D haptic environments and that considering speed accuracy tradeoffs is important in making design decisions.
Diagnosis of Dilated Cardiomyopathy: Patient Reaction and Adaptation—Case Study and Review of the Literature

Objective. Heart failure remains a major cause of morbidity and mortality. Given that heart failure generally has a chronic course, it is important to appreciate the impact it can have on the quality of life of patients and also their partners or family carers. Method. Questionnaires were given to a patient newly diagnosed with dilated cardiomyopathy, during his hospital admission, as well as after discharge. The responses are summarised and explored in the discussion section, where we used review of the literature to discuss the implications of a new diagnosis of heart failure. Results. The patient's responses to the questionnaires suggest certain anxieties that are part of his adaptation to the diagnosis of heart failure. Conclusion. Depression is a common comorbid condition in patients with heart failure. Various tools can be used to screen for depression in patients with heart failure. Both pharmacological and nonpharmacological options are available. Rapid evaluation of ongoing problems and active participation by a psychiatrist can ensure that the patient receives the best possible clinical care.
Simulation of semiconductor bulk trap influence on the electrical characteristics of the n-channel power VDMOS transistor

In this paper the impact of traps generated in semiconductor bulk due to High Electric Field Stress (HEFS) or irradiation of n-channel power VDMOSFET are presented. The influence of semiconductor bulk traps is expected, due to the fact that the current mainly flows vertically through the n-epitaxial layer and n+ substrate to drain contact. For the reverse engineering of the process flow and the simulation of electrical characteristics of power VDMOS transistor, Technology Computer-Aided Design (TCAD) software package tools from Silvaco are used. Taking the advantage of simulation, the influences of donor (DT) and acceptor (AT) traps generated in the semiconductor bulk on the electrical characteristics are separately analysed and discussed.
A Brief and Preliminary Look at SNPs Data for some Bering-Chukchi-Beaufort Seas Bowhead Whales

We present preliminary analyses of 18 single nucleotide polymorphism markers (SNPs) for 106 bowhead whales from Barrow and St. Lawrence Island. We find no evidence for disequilibrium, population substructure, or genetic variation associated with temporal spacing of whales in the migration. Introduction We present here a preliminary examination of a small dataset of single nucleotide polymorphism markers (SNPs) obtained from samples from 126 bowhead whales (Balaena mysticetus) from the Bering-Chukchi-Beaufort Seas region. These data were developed by Morin et al. (2007), using the methods of Morin and McCarthy (2007). Primary analyses of these data are given by Morin et al. (2007); we offer only some preliminary secondary examinations here. The main goal of our paper is to provide a first look at one analysis not provided by those authors related to a temporal lag autocorrelation feature found in microsatellite analysis of fall Barrow samples (Jorde et al., 2007; Givens and Ozaksoy, 2006; Givens et al. 2007). We also confirm some basic findings of Morin et al. (2007) using a slightly different set of samples and SNP loci. We analyzed data for 18 SNP loci from 106 bowhead whales. The samples were collected from three sites: Barrow and the villages of Savoonga and Gambell on St. Lawrence Island (SLI). The Barrow data were all collected during the spring migration period. The Savoonga and Gambell data came from whales sampled during both the fall and spring migrations, as well as from baleen samples and whale skulls obtained from villagers and discards from historical aboriginal hunts. Some adjustments were made to the raw data prior to analysis. In the original dataset there were 126 whales typed on 19 loci. First, 16 individuals were deleted from the dataset because they were found to be duplicates of whales already in the dataset. Second, two fetuses from Barrow and 2 fetuses from Savoonga were deleted because data from their mothers were already in the dataset. Third, one locus (Bmys402M56) was deleted from the data set because it was sex-linked. Table 1 shows the numbers of whales analyzed using the 18 remaining SNPs loci. 1 Dept. of Statistics, Colorado State University, Fort Collins CO 80523. 2 Southwest Fisheries Science Center, 8604 La Jolla Shores Dr., La Jolla CA 92037. 3 North Slope Borough Dept. of Wildlife Management, PO Box 69, Barrow AK 99723.
Stock Market Reactions to Brexit: Case of Selected CEE and SEE Stock Markets

The debate on the UK leaving the European Union is still hot and ongoing today due to many economic, political, social, and other consequences on many different countries over the world. This paper focuses on the reactions of selected Central and Eastern European (CEE) and South and Eastern European (SEE) stock markets to the Brexit vote on 23 June 2016. Using daily data for the time span from January 2010 until July 2016 and the event study methodology (ESM), the return and volatility series are being tested for significant reactions to the Brexit event. The results indicate mixed results regarding the abnormal cumulative return series, but the volatility series were found to be significantly affected by the mentioned event. This is important for international investors and gives information on the reaction of mentioned markets to big political and economic events in order to tailor international portfolios in a way to hedge from risk.
Border Ranks of Monomials

Young flattenings, introduced by Landsberg and Ottaviani, give determinantal equations for secant varieties and provide lower bounds for border ranks of tensors. We find special monomial-optimal Young flattenings that provide the best possible lower bound for all monomials up to degree 6. For degree 7 and higher these flattenings no longer suffice for all monomials. To overcome this problem we introduce partial Young flattenings and use them to give a lower bound on the border rank of monomials which agrees with Landsberg and Teitler's upper bound.
GRAPH DATA ANALYSIS

We explore the generalization of scattering transforms from traditional signals to graph data, analogous to the generalization of ConvNets in geometric deep learning, and the utility of extracted graph features in graph data analysis. In particular, we focus on the capacity of these features to retain informative variability and relations in the data (e.g., between individual graphs, or in aggregate). We demonstrate the application of our geometric scattering features in graph classification of social network data, and in data exploration of biochemistry data.
Price Discrimination and Market Power in Export Markets: The Case of the Ceramic Tile Industry

This paper combines the pricing-to-market equation and the residual demand elasticity equation to measure the extent of competition in the export markets of ceramic tiles, which has been dominated by Italian and Spanish producers since the late eighties. The findings show that the tile exporters enjoyed substantial market power over the period 1988–1998, and limited evidence that the export market has become more competitive over time.
Improved Trip Planning by Learning from Travelers' Choices

We analyze the work of urban trip planners and the relevance of trips they recommend upon user queries. We propose to improve the planner recommendations by learning from choices made by travelers who use the transportation network on the daily basis. We analyze individual travelers' trips and convert them into pair-wise preferences for traveling from a given origin to a destination at a given time point. To address the sparse and noisy character of raw trip data, we model passenger preferences with a number of smoothed time-dependent latent variables, which are used to learn a ranking function for trips. This function can be used to re-rank the top planner's recommendations. Results of tests for cities of Nancy, France and Adelaide, Australia show a considerable increase of the recommendation relevance.
“Time is bandwidth”? Narrowing the gap between subjective time perception and Quality of Experience

Over the last couple of years, the scope of Quality of Experience (QoE) research has been constantly extended, most recently to the field of Web QoE in the context of HTTP-based applications. In this paper, we address the question whether it is sufficient to reduce typical Web QoE assessment scenarios to the temporal aspects of waiting for task completion, which would allow to attribute the resulting logarithmic laws to well-known psychological insights on human time perception. We demonstrate that while this attribution is valid for simple waiting tasks which are typical for simple data services like e.g. file downloads, the case of interactive web browsing is much more complex. We show that this is not only because technical issues prevent bandwidth and download time from being directly correlated with each other in a simple manner, but also because user perceived web page load times strongly deviate from technical page load times. Consequently, existing approaches towards assessment and modeling of web browsing QoE have to be critically reviewed and redesigned.
Local Selective Voting

We propose a technique of localized selective voting of weak classifiers. This technique identifies local regions having similar characteristics and then uses the selective votes of each local expert to describe the relationship between the data characteristics and the target class. The algorithms that are locally used for building the ensemble are tested in the local set and if they have statistically worse accuracy than the most accurate algorithm, they do not participate to the final decision of the ensemble. Our experiment for several UCI datasets shows that the proposed combining method outperforms other combining methods we tried as well as any base classifier.
Efficient Implementation of WiMAX Physical Layer on Multi-core Architectures with Dynamically Reconfigurable Processors

Wireless internet access technologies have significant market potential, especially the WiMAX protocol which can offer data rate of tens of Mbps. A significant demand for embedded high performance WiMAX solutions is forcing designers to seek single-chip multiprocessor or multi-core systems that offer competitive advantages in terms of all performance metrics, such as speed, power and area. Through the provision of a degree of flexibility similar to that of a DSP and performance and power consumption advantages approaching that of an ASIC, emerging dynamically reconfigurable processors are proving to be strong candidates for future high performance multi-core processor systems. This paper presents several new single-chip multi-core architectures, based on newly emerging dynamically reconfigurable processor cores, for the WiMAX physical layer. A simulation platform is proposed in order to explore and implement various multi-core solutions combining different memory architectures and task partitioning schemes. The paper describes the architectures, the simulation environment, several task partitioning methods and demonstrates that up to 4.9x speedup can be achieved by employing five dynamically reconfigurable processor cores each having individual local memory units.
Concurrent Constraint Logic Programming On Massively Parallel SIMD Computers

With the advent of cost-eeective massively parallel computers, researchers conjecture that the future constraint logic programming system is composed of a massively parallel constraint solver as the back-end with a concurrent inference engine as the front-end 7]. This paper represents an attempt to build a constraint logic programming system on a massively parallel SIMD computer. A concurrent constraint logic programming language called Firebird is presented in this paper. Firebird can handle nite domain constraints and supports both concurrency and data-parallelism. As a result, it is suitable for both multiprocessors and SIMD computers. Concurrency arises from the stream and-parallelism of committed-choice logic programming languages. In a nondeterministic derivation step, one of the domain variables is selected to create a choice point. All possible alternatives are attempted in parallel. Data-parallelism is exploited in the resulting or-parallel execution. Firebird is currently being implemented on a DECmpp 12000 Sx-100 1 massively parallel computer. On nding all the solutions to the 8-queens problem, Firebird on a MasPar MP-2 is about 20 times faster than CHIP 8] on a DECstation 3100.
Can we use Existing Pedagogical Specifications to Design Mixed Reality Learning Games

Game-based learning is one efficient pedagogical concept that uses game principles to incite learners to engage into learning activities. Learning games are commonly known as digital environments. In the mean time, new technologies have been increasingly developed, thus providing new perspectives in game-based learning, particularly, mixed reality technologies that merge both real and digital worlds. For instance, they are widely used in mobile learning or learning with tangible interfaces. For the latter, mixed reality technologies make collaboration easier and provide better feedback to users. We present in the paper a brief study on the state of the art of mixed reality technologies. While the technologies have been experimented in educational settings or in games, they are used only in few learning games. Some research efforts have proven positive outcomes of the latter in learning even they are not widely applicable. Based upon the contributions of mixed reality in learning games, we point out that means employed by designers are as crucial as the pedagogical objectives. Therefore, they have to be taken into account during the design process. Our research efforts aim at providing tools and methods to support the design of mixed reality learning games (MRLG). One of the first steps during the instructional design is to write the learning scenario. However, there is no universal method to be used in the design process. Thus, in the second section of this paper, we analyze the ability of existing pedagogical specifications to model mixed reality learning games scenarios. In this view, we compare IMS-LD, LDL and ISiS, which all intend to assist pedagogical designer and teachers in the design of new pedagogical activities and in the formalization of existing ones. Design process of MRLG includes game elements and mixed reality technologies design, particularly in the pedagogical scenario writing. Meanwhile, the specifications mentioned earlier do not fulfil our needs: they all allow a representation of a pedagogical scenario in a workflow, but in our case, a more detailed description of the workflow is needed. The specifications are not suitable to describe the used technologies or the way they are used. Regarding the fun factors, none of the formalisms includes the description of rules and neither game principles nor game objectives. The last part of the paper discuss different proposals: an extension of a pedagogical specification, a combination of existing specification with a task model for more detailed description, and a new pedagogical specification for mixed reality learning games.
DUAL-LATTICE-BASED SIMULATIONS OF COUPLED FRACTURE-FLOW IN REINFORCED CONCRETE

Although reinforced concrete design typically allows for non-critical cracking of the concrete, such cracking is known to increase the effective permeability of concrete, which can promote various forms of structural deterioration. Numerical modeling offers opportunities for the study of these durability problems. In particular, lattice models are attractive for this purpose. The present work describes the fundamental concept and related recent developments of a dual-lattice model for coupled fracture-flow analyses of cementitious materials. The capabilities of this model are demonstrated by simulating water absorption in cracked reinforced concrete, the experiment of which was performed by Zhang et al. [24]. Comments are provided regarding more realistic simulations of reinforced concrete durability problems and potential future developments of this model.
Supporting creative collaboration in globally distributed companies

Creative ways of working with whiteboards and sticky notes are growing in popularity even in global companies. However, digital tools for enabling these ways of working, especially for geographically distributed teams, have still not been adopted in these companies. We present Tele-Board, a web-based digital whiteboard and sticky note system and describe how it was used in a large company at three locations. From system log data and interviews recorded after three months of use, we found that idea generation and feedback collection can be facilitated if a system offers real-time synchronous editing as well as asynchronous input. Interestingly, the users who were not located at the company's headquarters regarded the tool as very beneficial and used it more than their colleagues at the headquarters. We provide a detailed analysis of the study and important points for fostering the adoption of creative tools in large companies.
Power Spectrum Estimation via Modified Indirect Dominant Mode Rejection ∗

It is well known that under low sample support of the correlation matrix, low rank solutions of the Minimum Variance Distortionless Response (MVDR) problem can yield better performance than the full rank solution. A new adaptive approach, Indirect Dominant Mode Rejection (IDMR), was introduced in previous work to solve the MVDR optimization problem. In this paper we extend IDMR beamformers from the signal arrival directions to the entire spatial spectrum. We also introduce several modifications, which bring more robustness to basic IDMR. These include root-music, forward/backward averaging of the sample correlation matrix and power window. The MVDR beamformer is scaled to satisfy the unity gain constraint, while the power window technique determines the scaling factor based on the fact that it is the power arriving from the look-direction. MUSIC is used to provide the power window technique an initial estimate of these powers.
Quantifying Input Uncertainty via Simulation Confidence Intervals

We consider the problem of deriving confidence intervals for the mean response of a system that is represented by a stochastic simulation whose parametric input models have been estimated from “real-world” data. As opposed to standard simulation confidence intervals, we provide confidence intervals that account for uncertainty about the input model parameters; our method is appropriate when enough simulation effort can be expended to make simulation-estimation error relatively small. To achieve this we introduce metamodel-assisted bootstrapping that propagates input variability through to the simulation response via an equation-based model rather than by simulating. We develop a metamodel strategy and associated experiment design method that avoid the need for low-order approximation to the response and that minimizes the impact of intrinsic (simulation) error on confidence level accuracy. Asymptotic analysis and empirical tests over a wide range of simulation effort show that confidence intervals obtaine.