Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning from wrong and creative algorithm design

We all are aware of the relevance of examining a task from diverse angles. We also are aware of the potential relevance of learning from one's mistakes. Yet computer science (CS) textbooks and teaching materials fall short in embedding these two notions. In this paper, we present an approach of elaborating divergent thinking in algorithm design, while capitalizing on erroneous solutions. Using a collected set of non-routine algorithmic tasks, we developed and applied a scheme of class activities, in which initial faulty solutions (due to novice tendencies) are carefully examined, and their falsifying inputs and characteristics are used for creative reasoning that yields fruitful outcomes. We present and illustrate our activities, refer to their cognitive aspects, and describe our experience with applying them in (an Introduction-to-Algorithms) class.
Authorable Dense Crowd Simulation based on Smoothed Particle Hydrodynamics

The control of dense crowd is a time-consuming and challenging task. There are always conflicts between detailed movements and the control of large-scale crowd. To solve this problem, we suggest the smoothed particle hydrodynamics (SPH) technique to express continuous flow with two authorable interfaces. To reflect the connectivity that occurs in a crowd, we use an authorable sociogram model. And we present a new type of shape map to produce various shapes of crowd in real time under interactive control.
Modeling Viral Genome Fitness Evolution Associated with Serial Bottleneck Events: Evidence of Stationary States of Fitness

ABSTRACT Evolution of fitness values upon replication of viral populations is strongly influenced by the size of the virus population that participates in the infections. While large population passages often result in fitness gains, repeated plaque-to-plaque transfers result in average fitness losses. Here we develop a numerical model that describes fitness evolution of viral clones subjected to serial bottleneck events. The model predicts a biphasic evolution of fitness values in that a period of exponential decrease is followed by a stationary state in which fitness values display large fluctuations around an average constant value. This biphasic evolution is in agreement with experimental results of serial plaque-to-plaque transfers carried out with foot-and-mouth disease virus (FMDV) in cell culture. The existence of a stationary phase of fitness values has been further documented by serial plaque-to-plaque transfers of FMDV clones that had reached very low relative fitness values. The statistical properties of the stationary state depend on several parameters of the model, such as the probability of advantageous versus deleterious mutations, initial fitness, and the number of replication rounds. In particular, the size of the bottleneck is critical for determining the trend of fitness evolution.
Improved Maximum Likelihood Estimation of Target Position in Wireless Sensor Networks using Particle Swarm Optimization

Estimation of target position from multi-frame binary data provided by a wireless sensor network (WSN) can be done by optimizing a complex multimodal likelihood function. Deterministic quasi Newton-Raphson (QNR) schemes with line search are typically used for optimization in maximum likelihood estimation. However, these methods often find a local minimum, which leads to large estimation errors. This paper presents an approach that employs particle swarm optimization (PSO) techniques for global optimization of the likelihood function. Simulation results comparing the performance of a maximum likelihood target position estimation scheme employing QNR and PSO algorithms are presented. It is seen that the PSO algorithm provides significantly higher position estimation accuracy throughout the sensor field
A scalable algorithm for clustering sequential data

In recent years, we have seen an enormous growth in the amount of available commercial and scientific data. Data from domains such as protein sequences, retail transactions, intrusion detection, and Web-logs have an inherent sequential nature. Clustering of such data sets is useful for various purposes. For example, clustering of sequences from commercial data sets may help marketer identify different customer groups based upon their purchasing patterns. Grouping protein sequences that share similar structure helps in identifying sequences with similar functionality. Over the years, many methods have been developed for clustering objects according to their similarity. However these methods tend to have a computational complexity that is at least quadratic on the number of sequences. In this paper we present an entirely different approach to sequence clustering that does not require an all-against-all analysis and uses a near-linear complexity K-means based clustering algorithm. Our experiments using data sets derived from sequences of purchasing transactions and protein sequences show that this approach is scalable and leads to reasonably good clusters.
An update on a systematic review of the use of geriatric assessment for older adults in oncology.

BACKGROUND Our previous systematic review of geriatric assessment (GA) in oncology included a literature search up to November 2010. However, the quickly evolving field warranted an update. Aims of this review: (i) provide an overview of all GA instruments developed and/or in use in the oncology setting; (ii) evaluate effectiveness of GA in predicting/modifying outcomes (e.g. treatment decision impact, treatment toxicity, mortality, use of care). MATERIALS AND METHODS Systematic review of literature published between November 2010 and 10 August 2012. English, Dutch, French and German-language articles reporting cross-sectional or longitudinal, intervention or observational studies of GA instruments were included. DATA SOURCES MEDLINE, EMBASE, PsycINFO, CINAHL and Cochrane Library. Two researchers independently reviewed abstracts, abstracted data and assessed the quality using standardized forms. A meta-analysis method of combining proportions was used for the outcome impact of GA on treatment modification with studies included in this update combined with those included in our previous systematic review on the use of GA. RESULTS Thirty-five manuscripts reporting 34 studies were identified. Quality of most studies was moderate to good. Eighteen studies were prospective, 11 cross-sectional and 5 retrospective. Three studies examined treatment decision-making impact and found decisions changed for fewer than half of assessed patients (weighted percent modification is 23.2% with 95% confidence interval (20.3% to 26.1%). Seven studies reported conflicting findings regarding predictive ability of GA for treatment toxicity/complications. Eleven studies examined GA predictions of mortality, and reported that instrumental activities of daily living, poor performance status and more numerous GA deficits were associated with increased mortality risk. Other outcomes could not be meta-analyzed. CONCLUSION Consistent with our previous review, several domains of GA are associated with adverse outcomes. However, further research examining effectiveness of GA on treatment decisions and oncologic outcomes is needed.
Extracting Human Body based on Background Estimation in Modified HLS Color Space

— The ability to recognize humans and their activities by computer vision is a very important task, with many potential application. Study of human motion analysis is related to several research areas of computer vision such as the motion capture, detection, tracking and segmentation of people. In this paper, we describe a segmentation method for extracting human body contour in modified HLS color space. To estimate a background, the modified HLS color space is proposed, and the background features are estimated by using the HLS color components. Here, the large amount of human dataset, which was collected from DV cameras, is pre-processed. The human body and its contour is successfully extracted from the image sequences.
MT3S: Mobile Turkish Scene Text-to-Speech System for the Visually Impaired

Reading text is one of the essential needs of the visually impaired people. We developed a mobile system that can read Turkish scene and book text, using a fast gradient-based multi-scale text detection algorithm for real-time operation and Tesseract OCR engine for character recognition. We evaluated the OCR accuracy and running time of our system on a new, publicly available mobile Turkish scene text dataset we constructed and also compared with state-of-the-art systems. Our system proved to be much faster, able to run on a mobile device, with OCR accuracy comparable to the state-of-the-art.
Parent scaffolding of young children’s use of touch screen tablets

ABSTRACT Parents play a key role in supporting young children’s interactions with tablets (e.g. iPads). Little is known about the types of scaffolding parents provide during tablet activities and how these relate to child age, SES, and home use. Fifty-five parent–child dyads (M child age = 3.49 years) were videoed as they played on an iPad. All parent utterances were coded into three types of scaffolding behaviours (cognitive, affective, technical scaffolding; CATs). Home tablet use and family demographics were reported via a parent questionnaire. Parents used CATs strategies to support their children’s learning. Parents most frequently used cognitive scaffolding and least frequently technical scaffolding. SES was not related to the number of tablets at home. The negative association found between technical scaffolding and child age suggests that younger children require more scaffolding by parents. Coaching parents in using scaffolding strategies during joint-tablet activities has the potential to support early learning.
Enhancing the Collective Knowledge for the Engineering of Ontologies in Open and Socially Constructed Learning Spaces

The aim of this paper is to present a novel technological approach for enhancing the collective knowledge of communities of learners on the engineering of ontologies within a collaborative, open and socially constructed environment. The pro- posed technology aims at shaping information spaces into ontologies in a collaborative, communicative and learner-centered way during the ontology development life-cycle. The paper conjectures that such a collaborative environment can yield educational benefits, thus there is need to follow principles that apply in the Computer Supported Collaborative Learning (CSCL) paradigm. This work is mainly based on a collabora- tive and human-centered ontology engineering methodology and on a meta-ontology framework for developing ontologies, namely HCOME and HCOME-3O respectively. The integration of key technologies such as Semantic Wiki and Argumentation models with Ontology Engineering methodologies and tools serve as an enabler of learning spaces construction for different domain-specific information spaces in open settings. Inside these learning spaces innovative conceptualizations (both domain and devel- opment) are conceived, described by intertwined ontological meta-models following the HCOME-3O specifications for future reference and tutoring support. Such learn- ing spaces support two types of ontology engineering courses: a) courses related to the know-how of shaping information spaces into ontologies (namely, the development knowledge) and b) courses related to the analysis of the domain itself (namely, the do- main knowledge). The paper reports on the evaluation of the approach within a CSCL setting in Ontology Engineering, using the integrated set of tools and the framework that have been developed for the collaborative engineering of ontologies.
Outdoor map building based on odometry and RTK-GPS positioning fusion

The final objective of the authors is to realize mobile robot navigation in walkway of outdoor environment. The path along the walkway which is measured correctly together with landmarks must be given in the framework in this paper. The robot identifies its position by means of odometry, DGPS and laser range finder (LRF) during the motion along the path. This work contributes to the map building of landmarks along the walkway. To make the map, RTK-GPS, odometry and LRF are used for the sensory devices and Kalman smoothing technique is also incorporated to interpolate trajectory of the scanning LRF equipment between the two point that RTK-GPS measurement took place. The scanning by LRF is performed to acquire the 3-D shape of objects along the walkway. The trajectory presumed properly and well organized shapes of the objects are reconstructed.
Representing, analyzing, and synthesizing biochemical pathways

This article describes computational problems that arise in representing knowledge about the metabolism in electronic form, in analyzing that knowledge to gain deeper insights into complexities of the metabolism, and in applying that knowledge to biology, biotechnology, and health care. These problems push the limits of existing techniques for knowledge representation, planning, integration of heterogeneous databases, qualitative reasoning, knowledge acquisition and machine learning. This article surveys several recent and ongoing efforts to solve these problems, including the EcoCyc project, a collaborative effort of the Marine Biological Laboratory, SRI International, and the National Library of Medicine. <<ETX>>
Inferring Coronal Structure from X-Ray Light Curves and Doppler Shifts: A Chandra Study of AB Doradus

The Chandra X-Ray Observatory continuously monitored the single cool star AB Dor for a period lasting 88 ks (1.98Prot) in 2002 December with the Low-Energy Transmission Grating HRC-S. The X-ray light curve shows rotational modulation with three peaks that repeat in two consecutive rotation cycles. These peaks may indicate the presence of compact emitting regions in the quiescent corona. Centroid shifts as a function of phase in the strongest line profile, O VIII λ18. 97, indicate Doppler rotational velocities with a semiamplitude of 30 ± 10 km s-1. By taking these diagnostics into account along with constraints on the rotational broadening of line profiles (provided by archival Chandra High-Energy Transmission Grating Fe XVII and Far Ultraviolet Spectroscopic Explorer Fe XVIII profiles), we can construct a simple model of the X-ray corona that requires two components. One of these components is responsible for 80% of the X-ray emission and arises from the pole and/or a homogeneously distributed corona. The second component consists of two or three compact active regions that cause modulation in the light curve and contribute to the O VIII centroid shifts. These compact regions account for 16% of the emission and are located near the stellar surface with heights of less than 0.3R*. At least one of the compact active regions is located in the partially obscured hemisphere of the inclined star, while another of the active regions may be located at 40°. High-quality X-ray data such as these can test the models of the coronal magnetic field configuration as inferred from magnetic Zeeman Doppler imaging.
A Dynamic Mesh Display Representation for the Holodeck Ray Cache System

This report presents a dynamic mesh representation that is designed to display the results of interactively sampling a 3D environment. The mesh generator takes samples comprising a world space location, RGB color value, and sampled ray direction, and assembles them into a 3D triangle mesh. From this representation a complete image can be constructed and displayed, both from the initial view, and from subsequent views as the user moves through the environment. The representation exploits the fact that from a fixed vantage point there is a one-to-one mapping between visible world space points and their projection onto a sphere centered at that viewpoint. A Delaunay triangulation constructed on the sphere provides the mesh topology and the the vertex coordinates are derived from the input samples. The resulting mesh is used as the 2.5D display representation. The mesh is dynamic and ephemeral: it is updated as samples are added and deleted, and reconstructed after significant viewpoint changes. The dynamic mesh representation is described in the context of an interactive rendering system based on the "holodeck", a 4-dimensional ray-caching data structure. In the holodeck system, a display driver makes requests for ray samples based on the user''s current view. The display driver must then quickly construct a coherent image based on these samples. This report introduces the dynamic mesh representation as a solution to the reconstruction problem, describes its implementation, and presents the results of utilizing this representation in the holodeck environment.
EXPLORATION IN COMPETITIVE NONRENEWABLE RESOURCE MARKETS: AN EXTENSION OF PINDYCK'S PERFECT FORESIGHT MODEL

be an increasing function of that discovery rate. This meansthat continuous, rather than pulsed, exploration is apotentially optimal policy. If the initial reserves availableto each producing agent are small, early optimal explorationmay be large enough to increase reserves and decrease unitproduction cost enough to cause price to drop over a period oftime. Eventually, discovery becomes so costly that theresource is economically (if not actually physically) depletedand price rises. The price path produced by this optimisingbehaviour has a "U" shape, rather than being monotonicallyincreasing.Pindyck's model, despite its success at demonstrating thepossibility of nonmonotonic price paths, is unnatural in thatunit production cost depends only on the amount of reservesconcurrently available to the producing agent rather than
Structured Vectorial Semantics for Broad-coverage Parsing

This paper proposes a novel structured vectorial semantic framework, incorporating cognitively-motivated ‘gist’ semantics as selectional restrictions in interactive vectorial-semantic parsing. Applying vectorial semantic techniques (in particular, relational clustering over dependent headwords) in this extended framework has a predictable positive impact on parsing accuracy. The vectorial representation is conducive to a fast implementation of necessary parser operations, despite the fact that vectorial semantic techniques have dense relations to propagate through the parse chart.
Genomic overview of mRNA 5′-leader trans-splicing in the ascidian Ciona intestinalis

Although spliced leader (SL) trans-splicing in the chordates was discovered in the tunicate Ciona intestinalis there has been no genomic overview analysis of the extent of trans-splicing or the make-up of the trans-spliced and non-trans-spliced gene populations of this model organism. Here we report such an analysis for Ciona based on the oligo-capping full-length cDNA approach. We randomly sampled 2078 5′-full-length ESTs representing 668 genes, or 4.2% of the entire genome. Our results indicate that Ciona contains a single major SL, which is efficiently trans-spliced to mRNAs transcribed from a specific set of genes representing ∼50% of the total number of expressed genes, and that individual trans-spliced mRNA species are, on average, 2–3-fold less abundant than non-trans-spliced mRNA species. Our results also identify a relationship between trans-splicing status and gene functional classification; ribosomal protein genes fall predominantly into the non-trans-spliced category. In addition, our data provide the first evidence for the occurrence of polycistronic transcription in Ciona. An interesting feature of the Ciona polycistronic transcription units is that the great majority entirely lack intercistronic sequences.
Correlates of sexual behaviour of rural college youth in Maharashtra, India

Abstract. Although premarital sex relationships are widely discouraged in India, some youth do form such relationships. It is important to understand the nature and extent of youth sexual behaviour and examine the relationship between individual characteristics, knowledge and attitude towards reproductive health issues and sexual behaviour. In order to study the sexual behaviour of rural youth, quantitative data have been collected among 1500 students (800 male and 700 female) and qualitative data through 4 focus group discussions & 4 in-depth interviews, in the age group 15-24 years in Thane district of Maharashtra during 2005. Chi-square test and regression analysis was performed using the sexual experience (penetrative and non-penetrative sex) as the dependent variable to find out the association and relationship with individual characteristics (age, education, working status, peer interaction, erotic exposure, and habits), knowledge and attitude towards reproductive health issues. Boys and girls lacked scientific information and misconceptions are widespread on various reproductive health issues. Boys had more liberal attitudes towards premarital sex as compared to the girls. Proportion of students with any sexual experience (penetrative and non-penetrative sex) was much higher in boys (29.8%) compared to girls (4.9%). Around 11 percent boys and 1 percent girls who reported penetrative sex (vaginal, /oral / anal), around half of them did not use condom. Homosexual experience was reported by 11 percent boys and 3 percent girls. AIDS awareness was observed high (89% & 87 % respectively among boys and girls). However the knowledge of sexually transmitted diseases was limited. Exposure to alcohol, drugs, pornographic films, having more frequent interaction with peers and working status of the students were positively related with penetrative and non-penetrative sex relationships for both boys and girls. Over 83 percent youth expressed a need for interactive communication on reproductive health issues be available in their colleges. The rural youth engaged in penetrative sex and use condom inconsistently are at risk of STIs and HIV transmission to their partners. Findings underscore the need for sexual and reproductive health interventions to target not only young people but also their peers. Key words: Sexual behaviour, rural youth, reproductive health, youth sexuality, sexual health
WiCKEd: a tool for writing in the context of knowledge

This paper introduces WiCKEd, a prototype tool to assist document authoring in a Semantic Web context. The tool builds on Semantic Web technologies and addresses the issues of creating and reusing knowledge-rich documents. WiCKEd allows new content to be created by pulling together relevant and contextual knowledge held in existing background documents, retaining explicit links to these knowledge sources. The consistency and coherence of authored documents are improved because they explicitly assimilate and link to relevant background knowledge instances as well as exposing them for further reuse.
Compact Model for Dual Gate Graphene Field-Effect Transistor

An improvised compact model for analysis of dual gate Graphene transistor is developed which describes the current-voltage relationship of Graphene FET. The compact model presented in this paper extends to the prior models by taking into consideration the difference in the mobilities of holes and electrons in the Graphene channel which incorporates a change in carrier density and mobility in GFET. Also, the effect of top gate and bottom gate capacitances have been considered while forming the equations for Graphene channel potential which shows the effect of back gate modulation on GFET operation. The model also captures the effect of back gate modulation and gate bias dependence on the Dirac point. Parameter variation analyses is done using the developed compact model using closed form equations and the simulation results show an increase in current due to the effective mobility considered in this model and the Dirac point can be controlled using the back gate bias. The transconductance is found to be least at the Dirac point of operation due to charge neutralization.