Miracle-dz/UniFAR-FTUs huggingface dataset:
Markerless Augmented Reality with Light Source Estimation for Direct Illumination

We present a markerless augmented reality system with intuitive positioning and realistic direct lighting of virtual objects. Our approach exploits a two camera system consisting of a TV-camera and a fish-eye camera. The TVcamera captures the video for the augmentation while the fish-eye camera observes the upper hemisphere to track the light sources. Accordingly, direct lighting can be used to render virtual objects. Additionally, we propose an easy method to place virtual objects in the scene and to compute the shadows of these objects. The proposed tracking methods overcome the limitations of many systems that need markers in the scene for augmentation or need additional equipment in the scene to reconstruct illumination. Our approach will keep the augmented scene unaffected.
HPRD: a high performance RDF database

In this paper, a high performance storage system for RDF documents is introduced. The system employs optimised index structures for RDF data and efficient RDF query evaluation. The index scheme consists of three types of indices. Triple index manages basic RDF triples by dividing original RDF graph into several sub-graphs. Path index manages frequent RDF path patterns for long path query performance enhancement. Context index is optional for context oriented RDF data and temporal RDF data. In this paper, we describe the organisation of index structures, which shows the process of evaluating queries based on the index structures, and provide a performance comparison with exist RDF database through several benchmark experiments.
Community Forest Management in Southern Malawi: Solution or Part of the Problem?

We investigated performance of a committee-led community natural resources management (CNRM) model in managing common-pool eucalyptus and miombo forest resources in southern Malawi. We argue that CNRM policies that ignore internal power relations attract unintended consequences that undermine achievement of conservation and social goals. Both CNRM concept and implementation created new elites (forest committees) who largely operated as corrupt, unaccountable “village bureaucracies,” alienating communities from CNRM. Widespread forest degradation and institutional breakdown ensued. Community management became committee management, and part of the problem. Rare “success” was associated with idiosyncratic leadership qualities of village heads, suggesting need for enhancing roles and leadership skills of traditional leaders in balancing the exercise of power among CNRM stakeholders, and for broad-based community empowerment so that members can demand accountability from local leaders. Eucalyptus was perceived to have higher exchange value and to be managed better than miombo, suggesting the need for separate incentives structures and institutional arrangements.
A study of fitness functions for data classification using grammatical evolution

Data classification is a well studied area with various techniques such as support vector machines, decision trees, neural networks and evolutionary algorithms, amongst others successfully applied to this domain. The research presented in this paper forms part of an initiative aimed at evaluating grammatical evolution, a recent variation of genetic programming, for data classification. The paper reports on a study conducted to compare six different measures, namely, accuracy, true positive rate, false positive rate, precision, F-score and Matthew's correlation coefficient, as fitness functions for grammatical evolution. The performance of grammatical evolution using the six measures as a fitness function is evaluated for multi-class data classification. The study has shown that the accuracy and F-score are effective as fitness functions outperforming all other measures. In some instances accuracy produced better results than F-score. Future work will examine the correlation between the characteristics of the data set and the best performing measure.
The Uniform Minimum-Ones 2SAT Problem and its Application to Haplotype Classification

Analyzing genomic data for finding those gene variations which are responsible for hereditary diseases is one of the great challenges in modern bioinformatics. In many living beings (including the human), every gene is present in two copies, inherited from the two parents, the so-called haplotypes . In this paper, we propose a simple combinatorial model for classifying the set of haplotypes in a population according to their responsibility for a certain genetic disease. This model is based on the minimum-ones 2SAT problem with uniform clauses. The minimum-ones 2SAT problem asks for a satisfying assignment to a satisfiable formula in 2CNF which sets a minimum number of variables to true. This problem is well-known to be -hard, even in the case where all clauses are uniform, i.e. , do not contain a positive and a negative literal. We analyze the approximability and present the first non-trivial exact algorithm for the uniform minimum-ones 2SAT problem with a running time of (1.21061 n ) on a 2SAT formula with n variables. We also show that the problem is fixed-parameter tractable by showing that our algorithm can be adapted to verify in (2 k ) time whether an assignment with at most k true variables exists.
Image de-noising using a fast non-local averaging algorithm

Recently the non local (NL) means algorithm was introduced in order to suppress additive Gaussian noise in images. Although its very good performances for Gaussian noise, the NL-means method has two disadvantages. Its computational complexity is very large and the impulse rejection is poor. In this paper, we propose a simplified version of the NL-means algorithm with a much smaller computational complexity and better behavior in mixed (Gaussian and impulsive) noise. Experimental results obtained with our proposed method and several other algorithms are also presented.
papago: A Machine Translation Service with Word Sense Disambiguation and Currency Conversion

In this paper, we introduce papago - a translator for mobile device which is equipped with new features that can provide convenience for users. The first feature is word sense disambiguation based on user feedback. By using the feature, users can select one among multiple meanings of a homograph and obtain the corrected translation with the user-selected sense. The second feature is the instant currency conversion of money expressions contained in a translation result with current exchange rate. Users can be quickly and precisely provided the amount of money converted as local currency when they travel abroad.
Statistical multiple perception model 3 . 1 . Classification and regression model

More and more efforts have been made for the research of emotional speech recently. Although we may, sometimes be able to make a definite perceptual decision on emotion state, emotion is actually a kind of cline in a large vector space. Different emotions can be thought of as zones along an emotional vector. To resolve the ambiguity of emotion perception, the authors make an array of perception experiments. Furthermore, the paper creates a statistical model to simulate emotion perception and finds that there is an underlying consistency in the patterns of responses. The results show important cues on how to do multiple perception of the emotional speech.
Data Placement Based on Toleration on Twice Failures Array Codes in RAID

This paper presents an extension of the double erasure-correcting EVENODD for tolerating disk failure in highly available data storage system, which called the V codes. The V-Codes have a simple geometrical structure, namely, they can correct any double column erasure errors. In addition, the parity symbols are evenly distributed among all the columns, thus the bottleneck effects of repeated write operation are naturally overcome. We provide detailed V code's decoding algorithms for correcting various double node failures with a geometrical structure. The complexity of encoding and decoding, the small write performance of three types of codes, are compared and analyzed, thus the V code is practically very meaningful for storage systems that need higher reliability
Ethylene-orchestrated circuitry coordinates a seedling’s response to soil cover and etiolated growth

Significance Seedlings’ ability to both adapt to their soil environment and acquire photoautotrophic capacity under various buried conditions is a life-or-death issue for terrestrial flowering plants. By designing and utilizing a standardized real-soil assay, we identify the key features of germinating seedlings’ soil response and deduce that the gaseous phytohormone ethylene acts as the primary regulator of soil-induced plant morphogenetic changes. Moreover, our study illustrates that an EIN3/EIL1-conducted PIF3–ERF1 molecular circuitry enables seedlings to synchronize the rate of protochlorophyllide biosynthesis with upward growth, a mechanism critical to the prevention of photooxidative damage during seedlings’ initial transition from dark to light in natural conditions. The early life of terrestrial seed plants often starts under the soil in subterranean darkness. Over time and through adaptation, plants have evolved an elaborate etiolation process that enables seedlings to emerge from soil and acquire autotrophic ability. This process, however, requires seedlings to be able to sense the soil condition and relay this information accordingly to modulate both the seedlings’ growth and the formation of photosynthetic apparatus. The mechanism by which soil overlay drives morphogenetic changes in plants, however, remains poorly understood, particularly with regard to the means by which the cellular processes of different organs are coordinated in response to disparate soil conditions. Here, we illustrate that the soil overlay quantitatively activates seedlings’ ethylene production, and an EIN3/EIN3-like 1–dependent ethylene-response cascade is required for seedlings to successfully emerge from the soil. Under soil, an ERF1 pathway is activated in the hypocotyl to slow down cell elongation, whereas a PIF3 pathway is activated in the cotyledon to control the preassembly of photosynthetic machinery. Moreover, this latter PIF3 pathway appears to be coupled to the ERF1-regulated upward-growth rate. The coupling of these two pathways facilitates the synchronized progression of etioplast maturation and hypocotyl growth, which, in turn, ultimately enables seedlings to maintain the amount of protochlorophyllide required for rapid acquisition of photoautotrophic capacity without suffering from photooxidative damage during the dark-to-light transition. Our findings illustrate the existence of a genetic signaling pathway driving soil-induced plant morphogenesis and define the specific role of ethylene in orchestrating organ-specific soil responses in Arabidopsis seedlings.
Rover Configuration for Exploring Lunar Craters

Configuration of locomotion for planetary rovers is motivated by increased interest in exploring lunar polar craters. Current rover designs cannot achieve the ascent or descent required by steep, unconsolidated lunar slopes. New designs must provide locomotive capability for steep climbing, techniques for controlling slip, and safely navigating down and along steep slopes. We propose a locomotion system designed to show unprecedented capabilities in steep terrain through a track-based system featuring a low center of gravity and an actuated, omni-directional plowing device. Experimental results show unprecedented locomotion in steep terrain, capable of controlled ascent on 35◦ slopes, controlled descent and point turning on 38◦ slopes. For descent, the use of a plow is shown to reduce slip twenty-fold in linear descent, and threefold in point turns.
Trends in the Development of Machinery and Associated Technology ” TMT 2011 , Prague , Czech Republic , 12-18 September 2011 THE WELD PROFILE EFFECT ON STRESS CONCENTRATION FACTORS IN WELDMENTS

The assessment of beneficial effects of weld geometry modification methods is considered in this paper. Since all these methods significantly increaese weld toe radius, its influence on stress concentration factors is analised. The dependance of theoretical stress concentration factors vs. weld toe radius was determined by using both finite element analisys and photoelasicity method for various types of welded joints. Ratio of coresponding values of fatigue stress concentration factors of aswelded and improved joint, determined by using empirical formulas including also hardness in heat affected zone, gives magnitude of beneficial effects of mentioned weld improvement methods. The results obtained by these calculations for one type of welded joints are compared with experimental results reported in literature.
Linear-programming decoding of Tanner codes with local-optimality certificates

Given a channel observation y and a codeword x, we are interested in a one-sided error test that answers the questions: is x optimal with respect to y? is it unique? A positive answer for such a test is called a certificate for the optimality of a codeword. We present new certificates that are based on combinatorial characterization for local-optimality of a codeword in irregular Tanner codes. The certificate is based on weighted normalized trees in computation trees of the Tanner graph. These trees may have any finite height h (even greater than the girth of the Tanner graph). In addition, the degrees of local-code nodes are not restricted to two (i.e., skinny trees). We prove that local-optimality in this new characterization implies ML-optimality and LP-optimality, and show that a certificate can be computed efficiently. We apply the new local-optimality characterization to regular Tanner codes, and prove lower bounds on the noise thresholds of LP-decoding in MBIOS channels. When the noise is below these lower bounds, the probability that LP-decoding fails decays doubly exponentially in the girth of the Tanner graph.
Piezoelectric Vibration-Type Tactile Sensor with Wide Measurement Range Using Elasticity and Viscosity Change

We propose a new tactile sensor utilizing piezoelectric vibration. This tactile sensor has a high sensitivity, wide measurement range, pressure resistance, flexibility, and self-sensing function. This tactile sensor comprises two piezoelectric materials. One is used for the vibration of the sensor element and the other is used for the measurement of the change in mechanical impedance induced by an external force. We achieved the wide measurement range by implementing two ideas. One was to apply the external force to the sensor element through an elastic body and the other was to use two or more modes of vibration. Moreover, for the elastic body, it is preferable to use a material whose elasticity and viscosity are easily changed by an external force, such as a gel. In this study, first, this tactile sensor was analyzed, and then its characteristics were derived. The analytical results qualitatively corresponded to the experimental results. Next, a prototype tactile sensor was fabricated and evaluated. The evaluation results showed that this tactile sensor can measure a pressure of 2.5 Pa or less and a pressure of 10 kPa or more and its pressure resistance is 1 MPa or more
Effects of Audio Compression in Automatic Detection of Voice Pathologies

This paper investigates the performance of an automatic system for voice pathology detection when the voice samples have been compressed in MP3 format and different binary rates (160, 96, 64, 48, 24, and 8 kb/s). The detectors employ cepstral and noise measurements, along with their derivatives, to characterize the voice signals. The classification is performed using Gaussian mixtures models and support vector machines. The results between the different proposed detectors are compared by means of detector error tradeoff (DET) and receiver operating characteristic (ROC) curves, concluding that there are no significant differences in the performance of the detector when the binary rates of the compressed data are above 64 kb/s. This has useful applications in telemedicine, reducing the storage space of voice recordings or transmitting them over narrow-band communications channels.
Filtering operation in cross-document linking

In this paper a filtering operation for cross-document connections is presented. Different texts could be connected to each other if they refer to the same entity. Linking different documents only in terms of overlap leads to too many False Positives. The method proposed in this paper has as start point Centering Theory (CT). A list of Principal Centers (Cp) is created for each sentence in the document. This list filters the results in cross-document linking. A bigraph representation is proposed to highlight the connections between texts. A score for classifying the topics is also presented. The score is calculated based on entities occurrence frequency in the whole document. Such an approach eliminated some of the False Positive results (Fps).
Random-walk based analysis of virtual backbone in manets

Service discovery architectures and cluster-assisted routing protocols in mobile ad-hoc networks (MANETs) heavily rely on formation and maintenance of a virtual backbone (VB). We present a novel analytic model for VB stability in MANETs. The model employs the dynamics of node movements, where link creation/failure is modeled via a random walk with probabilistic state-transition matrix. The backbone formation algorithm gives preference to the nodes with the smaller number of link changes and the higher degree. Therefore, the link arrivals and departures approximate the probability (and thus the expected time) for a mobile node to leave, join, or remain in the backbone, i.e., the stability of a dynamic structure of VB nodes.
Assessment of residual gastric volume and thirst in patients who drink before gastroscopy.

BACKGROUND: Before endoscopy patients undergo an uncomfortable fluid fast to reduce the risk of gastric acid aspiration and to ensure good endoscopic views are obtained. However, fluids rapidly leave the stomach and thus a long fluid fast before endoscopy may not be required. AIMS: The object of this study was to establish whether drinking before endoscopy is safe and relieves patients' symptoms of thirst. PATIENTS AND METHODS: 88 patients with American Society of Anaesthesiologists classification of physical status grades I and II were recruited in a controlled randomised single blind trial. The volume and pH of gastric aspirate obtained at gastroscopy was assessed in patients who drank 330 ml of water a minimum 90 minutes before their endoscopy and compared with values in patients who starved overnight. RESULTS: 44 patients who drank ('drinkers') 330 ml of water a mean 117 minutes before their morning gastroscopy had a similar volume and pH of gastric aspirate compared with 44 patients starved overnight ('starvers'); median volume 12.5 ml versus 10 ml, median pH 2.0 versus 2.0; 'drinkers' versus 'starvers' (NS). Before endoscopy patients were asked to score their thirst and hunger ratings as either none, mild, moderate or severe. Ratings for moderate and severe thirst were grouped together for analysis. The percentage of drinkers compared with starvers in each group with no thirst, mild thirst, and moderate severe thirst was 63%, 46%, and 37% respectively (chi 2 test for trend p < 0.05). Hunger ratings were similar in the two groups. CONCLUSIONS: It is safe for elective day cases to drink a significant volume of water two hours before endoscopy and this alleviates symptoms of thirst.
Designing Knowledge-Assisted Visual Analytics Systems for Organizational Environments

We present research focused on designing knowledge-assisted visual analytics systems for workers in organizational environments. We focus on business analysts and asset managers, who work collaboratively to analyze information and make decisions. Through extensive investigations in two organizational environments, we found that these knowledge workers struggle with managing and analyzing information from multiple perspectives. Their current tools lack support for aggregating, organizing, and sharing such information. To address their needs, we characterized their analytic workflows, extracted specific key knowledge actions for each task commonly found in these workflows, and designed and evaluated two visual analytics systems that support and encapsulate these knowledge actions. We provide design guidelines that should be used when designing knowledge-assisted visual analytics systems, and illustrate their effectiveness with two systems built by following them.
Estimation of infinite dilution activity coefficients of organic compounds in water with neural classifiers

A new approach is presented for the development of quantitative structure–property relations (QSPR) based on the extraction of relevant molecular features with self-organizing maps and the use of a modified fuzzy-ARTMAP classifier for variable prediction. The present methodology is demonstrated for the development of a QSPR for the aqueous-phase infinite dilution activity coefficient γ∞, based on a data set of 325 diverse organic compounds. The QSPR was developed using a set of 11 molecular descriptors (four connectivities vχ1–4, Coulomb self-similarity measure, electron–nuclear attraction, dipole moment, sum of atomic numbers, number of filled levels, average polarizability, and nuclear–nuclear repulsion). The final set of molecular descriptors was selected from an initial pool of 23 topological and quantum chemical descriptors, including six molecular quantum similarity measures, by means of a topological analysis of self-organization of the data set. Additional interpolated information to enhance the training of the neural system was obtained from the self-organization analysis. The resulting fuzzy-ARTMAP–based QSPRs performed with errors that were on the average seven times smaller compared to previous published models. The use of only four molecular quantum similarity measures proved to be sufficient for building a lnγ∞ fuzzy-ARTMAP–based QSPR with reasonable accuracy. © 2004 American Institute of Chemical Engineers AIChE J, 50:1315–1343, 2004
Credit report accuracy and access to credit

Data that credit-reporting agencies maintain on consumers' credit-related experiences play a central role in U.S. credit markets. Analysts widely agree that the data enable these markets to function more efficiently and at lower cost than would otherwise be possible. Despite the great benefits of the current system, however, some analysts have raised concerns about the accuracy, timeliness, completeness, and consistency of consumer credit records and about the effects of data problems on the availability and cost of credit. ; In this article, the authors expand on the available research by quantifying the effects of credit record limitations on the access to credit. Using the credit records of a nationally representative sample of individuals, the authors examine the possible effects of data problems on consumers by estimating the changes in consumers' credit history scores that would result from "correcting" the problems in their credit records. Moreover, the authors report results for consumer groups segmented by strength of credit history (credit history score range), depth of credit history (number of credit accounts in a credit record), and selected demographic characteristics.