Miracle-dz/UniFAR-FTUs huggingface dataset:
Force-enabled TouchPad in Cars: Improving Target Selection using Absolute Input

Current automotive interfaces rely heavily on touchscreen interfaces which leverage simple and intuitive direct touch interaction. Since input and output are co-located, displays have to be positioned within hand's reach. When the display is outside the reach envelope, a touchpad has been used as a control device. Current implementation of touchpads in cars rely on a relative input method that requires a visual cursor and is known to cause distraction from primary driving task. Newer touchpads with force sensing ability are getting introduced in notebook computers. We propose to use a force-enabled touchpad with absolute mapping for target selection. We performed a controlled experiment as a first step towards assessing whether absolute mapped force input target selection performance can be comparable to direct touch input. Results show that target selection performance is not significantly different from direct touch input making a case for force-enabled touchpad usage in scenarios where the display is outside the reach envelope.
Compensation of Calculations Duration on Converters Output Voltage in Digitally Controled Converters Based on Law of Conservation of Energy - Project "Bumblebee"

In the paper an example of implementation of new, original DC/DC converter controlling concept is presented. It is designed to be used in regulators with DSP processors. Control device keeps energy accumulated in converter at steady level, and in this way indirectly forces required value of output voltage. To check the possibility of using this method in real life devices, regulators algorithm was analyzed with particular attention set on numerical complexity and duration of necessary calculations. Reference was a fixed-point 32-bit DSP processor designed for energy-electronics applications. Way of compensating influence of processors calculations duration on behavior of converter is also presented. Results of conducted research and analysis confirm possibility and attractiveness of using the method to control DC/DC converters.
Target selection for AI companions in FPS games

Non-player Characters (NPCs) that accompany the player enable a single player to participate in team-based experiences, improving immersion and allowing for more complex gameplay. In this context, an Artificial Intelligence (AI) teammate should make good combat decisions, supporting the player and optimizing combat resolution. Here we investigate the target selection problem, which consists of picking the optimal enemy as a target in a modern war game. We look at how the companion’s different strategies can influence the outcome of combat, and by analyzing a variety of non-trivial First Person Shooter (FPS) scenarios show that an intuitively simple approach has good mathematical justification, improves over other common strategies typically found in games, and can even achieve results similar to much more expensive look-up tree approaches. This work has applications in practical game design, verifying that simple, computationally efficient target selection can make an excellent target selection heuristic.
On the Complexity of a Matching Problem with Asymmetric Weights

We present complexity results regarding a matching-type problem related to structural controllability of dynamical systems modelled on graphs. Controllability of a dynamical system is the ability to choose certain inputs in order to drive the system from any given state to any desired state; a graph is said to be structurally controllable if it represents the structure of a controllable system. We define the Orientation Control Matching problem (OCM) to be the problem of orienting an undirected graph in a manner that maximizes its structural controllability. A generalized version, the Asymmetric Orientation Control Matching problem (AOCM), allows for asymmetric weights on the possible directions of each edge. These problems are closely related to 2-matchings, disjoint path covers, and disjoint cycle covers. We prove using reductions that OCM is polynomially solvable, while AOCM is much harder; we show that it is NP-complete as well as APX-hard.
Computation of atomic fibers of Z-linear maps

For given matrix $A\in\Z^{d\times n}$, the set $P_{b}=\{z:Az=b,z\in\Z^n_+\}$ describes the preimage or fiber of $b\in\Z^d$ under the $\Z$-linear map $f_A:\Z^n_+\rightarrow\Z^d$, $x\mapsto Ax$. The fiber $P_{b}$ is called atomic, if $P_{b}=P_{b_1}+P_{b_2}$ implies $b=b_1$ or $b=b_2$. In this paper we present a novel algorithm to compute such atomic fibers. An algorithmic solution to appearing subproblems, computational examples and applications are included as well.
Scalable parallelization of skyline computation for multi-core processors

The skyline is an important query operator for multi-criteria decision making. It reduces a dataset to only those points that offer optimal trade-offs of dimensions. In general, it is very expensive to compute. Recently, multicore CPU algorithms have been proposed to accelerate the computation of the skyline. However, they do not sufficiently minimize dominance tests and so are not competitive with state-of-the-art sequential algorithms. In this paper, we introduce a novel multicore skyline algorithm, Hybrid, which processes points in blocks. It maintains a shared, global skyline among all threads, which is used to minimize dominance tests while maintaining high throughput. The algorithm uses an efficiently-updatable data structure over the shared, global skyline, based on point-based partitioning. Also, we release a large benchmark of optimized skyline algorithms, with which we demonstrate on challenging workloads a 100-fold speedup over state-of-the-art multicore algorithms and a 10-fold speedup with 16 cores over state-of-the-art sequential algorithms.
Thermodynamic instability of siRNA duplex is a prerequisite for dependable prediction of siRNA activities

We developed a simple algorithm, i-Score (inhibitory-Score), to predict active siRNAs by applying a linear regression model to 2431 siRNAs. Our algorithm is exclusively comprised of nucleotide (nt) preferences at each position, and no other parameters are taken into account. Using a validation dataset comprised of 419 siRNAs, we found that the prediction accuracy of i-Score is as good as those of s-Biopredsi, ThermoComposition21 and DSIR, which employ a neural network model or more parameters in a linear regression model. Reynolds and Katoh also predict active siRNAs efficiently, but the numbers of siRNAs predicted to be active are less than one-eighth of that of i-Score. We additionally found that exclusion of thermostable siRNAs, whose whole stacking energy (ΔG) is less than −34.6 kcal/mol, improves the prediction accuracy in i-Score, s-Biopredsi, ThermoComposition21 and DSIR. We also developed a universal target vector, pSELL, with which we can assay an siRNA activity of any sequence in either the sense or antisense direction. We assayed 86 siRNAs in HEK293 cells using pSELL, and validated applicability of i-Score and the whole ΔG value in designing siRNAs.
In praise of vagueness: re-visioning the relationship between theory and practice in the teaching of Fine Art from a cross-cultural perspective

ABSTRACT The emphasis on textual or oral supplements grounded in objective metacognitive analysis, and drawing on theoretical ideas and concepts, is now an acknowledged part of Fine Art pedagogy. But many involved in art education would agree that there is often a problem finding a good ‘fit’ between the theoretical and the practical. I draw on my experience as an artist and a teacher of Fine Art in the Republic of Korea in order to suggest how a positive evaluation of ‘vagueness’ within the cognitive style displayed by Korean students as part-and-parcel of their cultural mindset signals the fact that they are familiar with a analogical cognitive style in which ‘the incoherence associable with images and metaphors are carried over into the more formal elements of thought’ [Hall, David L. , and Roger T. Ames. 1995. Anticipating China: Thinking Through the Narratives of Chinese and Western Culture. Albany: State University of New York: 124]. I relate this to the research of Barbara Stafford on analogy and suggest that developing a methodology capable of addressing the benefits of this looser, ‘vaguer’, cognitive style can strengthen Fine Art pedagogy by incorporating the analogical language of images.
Genome-Wide Association for Smoking Cessation Success in a Trial of Precessation Nicotine Replacement

Abilities to successfully quit smoking display substantial evidence for heritability in classic and molecular genetic studies. Genomewide association (GWA) studies have demonstrated single-nucleotide polymorphisms (SNPs) and haplotypes that distinguish successful quitters from individuals who were unable to quit smoking in clinical trial participants and in community samples. Many of the subjects in these clinical trial samples were aided by nicotine replacement therapy (NRT). We now report novel GWA results from participants in a clinical trial that sought dose/response relationships for “precessation” NRT. In this trial, 369 European-American smokers were randomized to 21 or 42 mg NRT, initiated 2 wks before target quit dates. Ten-week continuous smoking abstinence was assessed on the basis of self-reports and carbon monoxide levels. SNP genotyping used Affymetrix 6.0 arrays. GWA results for smoking cessation success provided no P value that reached “genome-wide” significance. Compared with chance, these results do identify (a) more clustering of nominally positive results within small genomic regions, (b) more overlap between these genomic regions and those identified in six prior successful smoking cessation GWA studies and (c) sets of genes that fall into gene ontology categories that appear to be biologically relevant. The 1,000 SNPs with the strongest associations form a plausible Bayesian network; no such network is formed by randomly selected sets of SNPs. The data provide independent support, based on individual genotyping, for many loci previously nominated on the basis of data from genotyping in pooled DNA samples. These results provide further support for the idea that aid for smoking cessation may be personalized on the basis of genetic predictors of outcome.
Dynamic Load Balancing of Unstructured Computations in Decision Tree Classifiers

One of the important problems in data mining is discovering classification models from datasets. Application domains include retail target marketing, fraud detection, and design of telecommunication service plans. Highly parallel algorithms for constructing classification decision trees are desirable for dealing with large data sets. Algorithms for building classification decision trees have a natural concurrency, but are difficult to parallelize due to the inherent dynamic nature of the computation. In this short paper, we present parallel formulations of classification decision tree learning algorithm based on induction. We describe two basic parallel formulations, Synchronous Tree Construction Approach and Partitioned Tree Construction Approach. We propose a hybrid method that employs the good features of these methods. Our experimental results of the hybrid method on an IBM SP-2 demonstrate excellent speedups.
Speech recognition with factorial-HMM syllabic acoustic models

Approaches in Automatic Speech Recognition based on classic acoustic models seem not to exploit all the information lying in a speech signal; furthermore decoding procedures have real time constraints preventing the system to achieve optimal alignment between acoustic models and signal. In this paper, we present an approach to speech recognition in which Factorial Hidden Markov Models (FHMM) are used as syllabic acoustic models. An alignment algorithm is used for unit decoding. As applicative domain we choose numbers (range 0-999,999) uttered in Italian. Syllabic accuracy in our model is 84.81%, correctness on numbers is 77.74%. Aim of the experiment is to show that the performances of FHMMs lie in the ability to retrieve the presence of two different temporal dynamics in a speech segments: the former with a quasi-segmental timing, the latter presenting a quasi-syllabic trend. Moreover, we evaluate a unit decoding process based on a dynamic programming algorithm in order to exploit the acoustic models performances at best.
A graph based framework for the implementation of visual environments

We propose an architecture for storing visual expressions within an environment which supports various forms of visual expression editing, like syntax directed editing, free editing, and layout editing. The proposed architecture is based on two related graph data structures: an abstract syntax graph represents the logical structure of a visual expression in terms of its visual language syntax; a spatial relations graph represents the pictorial structure of a visual expression with graphical objects as nodes and spatial relations as edges. We explain the distinction between the two ways of structuring in detail, we show how coupled graph grammars can be used to define, build and relate the two structures, and we explain how an editor for a visual language can be defined on top of these data structures. We use the visual language Message Sequence Charts (MSC) as a running example.
Family-based association study of ZNF533, DOCK4 and IMMP2L gene polymorphisms linked to autism in a northeastern Chinese Han population

Objective: A study in a Caucasian population has identified two single-nucleotide polymorphisms (SNPs) in ZNF533, one in DOCK4, and two in IMMP2L, which were all significantly associated with autism. They are located in AUTS1 and AUTS5, which have been identified as autism susceptibility loci in several genome-wide screens. The present study aimed to investigate whether ZNF533, DOCK4, and IMMP2L genes are also associated with autism in a northeastern Chinese Han population. Methods: We performed a similar association study using families with three individuals (one autistic child and two unaffected parents). A family-based transmission disequilibrium test (TDT) was used to analyze the results. Results: There were significant associations between autism and the two SNPs of ZNF533 gene (rs11885327: χ2=4.5200, P=0.0335; rs1964081: χ2=4.2610, P=0.0390) and the SNP of DOCK4 gene (rs2217262: χ2=5.3430, P=0.0208). Conclusions: Our data suggest that ZNF533 and DOCK4 genes are linked to a predisposition to autism in the northeastern Chinese Han population.
HIGH RESOLUTION STUDIES OF PROTOSTELLAR CONDENSATIONS IN NGC 2024

We present interferometric 3 mm continuum and C 34 S(2 1) line observations towards the star forming NGC2024(south) molecular cloud core. The continuum of the prominentdustcoresFIR5andFIR6isspatiallyresolved.FIR5 separates into a binary or disk-envelope system. Weexplorethephysicalcharacteristicsofthecoresbymeans of a radiative transfer modelling in spherical symmetry. So- lutions with low bolometric luminosities (Lbol 1 4L) and massive envelopes (Menv a few 10M) t the long wavelength spectral energy distributions best. Dust compo- sitions allowing for thick ice coatings provide better agree- ment with the dynamical mass estimates derived from the kine- matics of the surrounding gas clumps. The ambiguity of the models is severely conned by a recent 350 m flux den- sity limit from the Heinrich-Hertz-Telescope (Menv > 5M, Lbol < 30 80L). In all cases, the mass of the envelope exceeds limits on the mass of any embedded central object by order(s) of magnitude. The observations are suggestive of pro- tostellar objects in their earliest phase of formation, with the bulk of their mass still to be accreted. The C 34 S line emission arises from two clump ensembles near to, and likely associated with these dense cores - however, the cores proper still escape detection in their molecular emis- sion. This striking anti-correspondence is suggestive of freeze- out of elements onto the surface of dust grains.
Intracavity parametric fluorescence in diode lasers

Self-pumped parametric fluorescence was observed in GaAs/AlGaAs Bragg reflection waveguide lasers with χ<sup>(2)</sup> phase-matched cavities. With a 967 nm pump, signal and idler around 2300 nm and 1700 nm were measured respectively, with record conversion efficiency of 4176 ± 817 %W<sup>−1</sup> cm<sup>−2</sup>.
The Fear Factor is a Main Thing: How Radio Influences Anxiety and Political Attitudes

Abstract We investigate how being exposed to media influences levels of anxiety and political attitudes in conflict-affected areas. Exploiting exogenous variation in signal strength of a radio station in South Sudan’s Western Equatoria State, we compare original qualitative and quantitative data from areas with differing radio coverage. Civilians living in areas with more exposure to radio are more afraid of attacks by the Lord’s Resistance Army (LRA). This anxiety means civilians rely more on a civilian militia, the arrow boys, and less on the state army. Hence media, through fear, can contribute to changing social and political structures.
Smart Parking with Reservation in Cloud Based Environment

In many cites, car drivers search for a parking slot during the peak hours or in traffic congestion. This paper presence an efficient method to check the availability of the parking slot and to reserve a slot. Existing work focuses on availability of the parking slot only. However drivers in this fast paced world can't judge whether a parking slot is available on-demand. To overcome this disadvantage, smart parking with reservation option using cloud based environment is proposed. This make the drivers easier to park the vehicles and also overcome traffic congestion. Drivers can initiate request using reservation app in the android mobile to determine the availability of the parking slot. If the slot is available a driver can reserve a slot through online payment system. The propose system also enables drivers to cancel the reserved parking slot. Amount will be refunded after cancellation charges. Thus a low cost prototype for smart parking with reservation is proposed using sensor, Arduino and android in cloud platform.
A proposal for design and implementation of an hybrid navigation system based on open data, augmented reality and big data: Applications for the smart cities

Indoor positioning and navigation systems have attributes which make their use inadvisable in certain applications. Our main purpose is to investigate these issues in order to improve accessibility in Smart Cities. In the last decade, there are increasing efforts to develop a sustainable and precise indoor navigation system to be used in any situation. There are interesting proposals but they suffer from various constraints (accuracy, cost, complexity, etc), so the use of hybrid and targeted solutions is mandatory. In an effort to address these problems, in this study we will develop an affordable and accurate indoor location system. Firstly, we will use geodata from the the Open Data initiative of the Spanish Conference of University Rectors. After studying its data model, we will create new methods to automatically derive new geometric layers, useful for accessibility studies. Then, all relevant information will be published via standard protocols and web services. In the second phase of this project, we will design an indoor positioning network (Bluetooth, WiFi, etc) based on indoor mapping. Finally, this positioning and navigation system will be used for performing different mobility experiments from the Smart Cities perspective.
Invariant Facial Features Under Pose Variations for Face Recognition

Pose variation is one of the major challenges in face recognition. In this paper, two global invariant facial features are proposed: (1) horizontal facial feature; (2) vertical facial feature. The paper proves that the proposed two facial features are invariant under pose variations. Cosine-face, extracted by performing a method based on a combination of discrete cosine transform (DCT) and principal component analysis (PCA), is used as the basic feature in face recognition application. By integrating proposed invariant features and cosine-face, unified facial features are obtained to represent each face image. Experimental results on Cambridge ORL face database show that substantial improvements are obtained by using our proposed global invariant features
Web Services Security: a preliminary study using Casper and FDR

Web Services is an important new XML-based architecture in which security is increasingly important. The WS-Security specification defines mechanisms for securing the SOAP messages. We show how those messages can be mapped to Casper notation and therefore be analysed with FDR. We show two attacks on proposed protocols and lastly discuss informally some ramifications of the use of the WS-Security specification.
Function and evolution of a Lotus japonicus AP2/ERF family transcription factor that is required for development of infection threads

Abstract Legume-rhizobium symbiosis is achieved by two major events evolutionarily acquired: root hair infection and organogenesis. Infection thread (IT) development is a distinct element for rhizobial infection. Through ITs, rhizobia are efficiently transported from infection foci on root hairs to dividing meristematic cortical cells. To unveil this process, we performed genetic screening using Lotus japonicus MG-20 and isolated symbiotic mutant lines affecting nodulation, root hair morphology, and IT development. Map-based cloning identified an AP2/ERF transcription factor gene orthologous to Medicago truncatula ERN1. LjERN1 was activated in response to rhizobial infection and depended on CYCLOPS and NSP2. Legumes conserve an ERN1 homolog, ERN2, that functions redundantly with ERN1 in M. truncatula. Phylogenetic analysis showed that the lineages of ERN1 and ERN2 genes originated from a gene duplication event in the common ancestor of legume plants. However, genomic analysis suggested the lack of ERN2 gene in the L. japonicus genome, consistent with Ljern1 mutants exhibited a root hair phenotype that is observed in ern1/ern2 double mutants in M. truncatula. Molecular evolutionary analysis suggested that the nonsynonymous/synonymous rate ratios of legume ERN1 genes was almost identical to that of non-legume plants, whereas the ERN2 genes experienced a relaxed selective constraint.