Miracle-dz/UniFAR-FTUs huggingface dataset:
RoboCup-97: The First Robot World Cup Soccer Games and Conferences

RoboCup-97, The First Robot World Cup Soccer Games and Conferences, was held at the Fifteenth International Joint Conference on Artificial Intelligence. There were two leagues: (1) real robot and (2) simulation. Ten teams participated in the real-robot league and 29 teams in the simulation league. Over 150 researchers attended the technical workshop. The world champions are CMUNITED (Carnegie Mellon University) for the small-size league, DREAMTEAM (University of Southern California) and TRACKIES (Osaka University, Japan) for the middle-size league, and AT-HUMBOLDT (Humboldt University) for the simulation league. The Scientific Challenge Award was given to Sean Luke (University of Maryland) for his genetic programming- based simulation team LUKE, and the Engineering Challenge Awards were given to UTTORI UNITED (Utsunomiya University, Toyo University, and Riken, Japan) and RMIT (Royal Melbourne Institute of Technology, Australia) for designing novel omnidirectional driving mechanisms. Over 5000 spectators and 70 international media covered the competition worldwide. RoboCup-98, the Second Robot World Cup Soccer, was held in conjunction with the Third International Conference on Multiagent Systems in Paris, France, in July 1998.
Dry Eye Disease in Patients with Functioning Filtering Blebs after Trabeculectomy

Purpose The aim of this study was to analyze dry eye disease (DED) in patients with functioning filtering blebs and to explore the relationship between the morphology of filtering blebs and ocular surface instability. Methods This was a cross-sectional, case-comparison study. Seventy glaucomatous patients (70 eyes) with functioning blebs who had undergone trabeculectomy more than 6 months prior (study group) and 35 control subjects (35 eyes) (control group) were included. All subjects completed an ocular symptom questionnaire that referred to the Shihpai Eye Study. Evaluation of meibomian gland obstruction, a tear film break-up time test (TFBUT), fluorescein corneal staining and a Schirmer’s tear test were then performed. Filtering bleb morphology was analyzed using Wuerzburg bleb classification scoring criteria in the study group. The presence of DED was defined as the concomitant presence of TFBUT <10 seconds and the presence of superficial punctate keratitis. Results The patients with functioning blebs presented higher corneal staining scores (P = 0.012) and lower TFBUT values (P = 0.043) than the control group. DED was present in 28/70 patients in the study group and 6/35 patients in the control group (P = 0.018). More patients in the study group complained of dryness (P = 0.001), a gritty or sandy sensation (P < 0.001) and redness (P = 0.048). In the study group, the patients with DED were significantly different from the patients without DED in both TFBUT (P < 0.001) and corneal staining (P < 0.001). More patients in the DED group were likely to report dryness (P = 0.013) and watery or teary eyes (P = 0.012). The differences in meibomian gland obstruction scores between the study and the control group, the DED and the non-DED group were not significant (P = 0.105 and P = 0.077, respectively). The values for microcysts and bleb heights were significantly higher in the DED group (P = 0.040 and P = 0.011, respectively). A Spearman’s rank correlation showed that microcysts were positively correlated with corneal staining (r = 0.270, P = 0.024). Bleb height was negatively correlated with TFBUT (r = -0.299, P = 0.012) and positively correlated with corneal staining (r = 0.275, P = 0.021). The relationships between DED and microcysts and between DED and bleb height were significant (r = 0.247, P = 0.039 and r = 0.307, P = 0.010, respectively). Conclusion DED is relatively common in patients with functioning filtering blebs following trabeculectomy. In DED patients, dryness and watery are common symptoms. Microcysts and bleb height are related to ocular surface instability and DED.
Impact of Technology Enhanced Language Learning (TELL) in promoting ESL learners’ reading comprehensibility and skills: students’ and teachers’ perceptions

The paper documents on the learners’ and teachers’ attitudes, preferences and priorities in technological implementation in the ESL reading context of Bangladesh. The research is conducted among 3 Government-based Bangla Medium Schools and 1 NGO-based English Version School in Dhaka city. The specified schools were chosen by the researcher based on their availability of technological applications and its usage in language classrooms. The qualitative and quantitative data of the research showed relevance with that of former study by Patel(2014), Parvin(2014) etc. in favor of technological modes. The study reflects that technology plays a pivotal role in producing Krashen’s(1991) low affective filter in pedagogical reading environment and, thus, promoting the learners’ reading comprehensibility. However, the current research also provides more in-depth notion of the variation of learners’ and teachers’ opinion on the impact of technology in development of academic reading skills and sub skills, like skimming, scanning etc. This appears to be an unexplored and often neglected area in the domain of language learning and instruction giving for most Bangladeshi pedagogical settings. Again, the study also provides subjective and objective ideas about the possible limitations that tend to crop up in technologically advanced reading classes in an ESL context like Bangladesh. TELL IN PROMOTING ESL LEARNERS’ READING SKILLS 4
Eleven years of malaria surveillance in a Sudanese village highlights unexpected variation in individual disease susceptibility and outbreak severity

An analysis is presented of continuous data collected over 11 years based on 1902600 person/days of observation on the malaria experience of the people of Daraweesh, a village in eastern Sudan. Malaria transmission is hypo-endemic: the acquisition of clinical immunity with age is not as obvious as in more holo-endemic areas and malaria remained a problem in all age groups throughout the study. However, this population, who are of Fulani origin, showed a distinctly variable level of disease susceptibility. Thirty-two percent of the village never reported malaria symptoms or required malaria treatment while others experienced up to 8 clinical episodes over the 11 years of observation. Malaria incidence was clearly influenced by drought but much less obviously by rainfall. To what extent outbreak patterns are explicable in terms of anopheline factors, and to human immune factors, remains an interesting question for malaria modelling in this, and in other low transmission zones, such as the burgeoning urban areas of modern Africa.
Natural Spatial Language Generation for Indoor Robot Zhiyu

This paper proposes a spatial language generation system to find short, accurate and human-like descriptions for robots to communicate with a human user about the location of an object. The research focuses on building static spatial descriptions which use reference objects and directions to describe spatial relations. The system generates a natural spatial description in three steps. In the first step, it collects the sensory information and robot state to extract an environment model. Then, it builds a grounding model that describes the location of the target object, based on landmarks in the scene. After that it will generate the natural language description by imitating a human’s talking style. A corpus of 149 spatial language commands for an indoor environment fetch task is used to train the system. An early-stage experiment was conducted and the results illustrate good potential for further development. Keywords-spatial language; language generation; robotics
Acanthamoeba spp. in Contact Lenses from Healthy Individuals from Madrid, Spain

Purpose Acanthamoeba keratitis (AK) is a painful and potentially blinding corneal infection caused by Acanthamoeba spp. In Madrid, environmental studies have demonstrated a high presence of these free-living amoebae in tap water. Since most of AK cases occur in contact lenses (CL) wearers with inadequate hygiene habits, the presence of Acanthamoeba in discarded CL has been studied and compared with other common etiological agents of keratitis, such as Pseudomonas aeruginosa and Staphylococcus aureus. Methods One hundred and seventy-seven healthy individuals from Madrid contributed their discarded CL and answered a questionnaire on hygiene habits. DNA was extracted from the CL solution and analyzed by real-time PCR for Acanthamoeba, Pseudomonas aeruginosa and Staphylococcus aureus. These CL and their solutions were also cultured on non-nutrient agar to isolate Acanthamoeba. Results Among the 177 samples, Acanthamoeba DNA was detected in 87 (49.2%), P. aeruginosa DNA in 14 (7.9%) and S. aureus DNA in 19 (10.7%). Cultivable amoebae, however, were observed in only one sample (0.6%). This isolate was genotyped as T4. The habits reported by this CL owner included some recognized risk factors for AK, but in this study only the practice of “not cleaning the CL case” presented some statistical significant association with Acanthamoeba DNA presence. Detection of the investigated bacterial DNA did not demonstrate statistical significant association with the studied practices, but the presence of P. aeruginosa revealed a possible inhibition of Acanthamoeba in these samples. Conclusions The PCR results suggest a high presence of Acanthamoeba spp. in healthy CL wearers from Madrid, but we can assume that CL solutions are properly disinfecting the CL since only 1.1% of the positive PCR samples correspond to viable amoebae and, after four years, only one participant reported stronger ocular problems. Nevertheless, more studies are necessary to corroborate this hypothesis.
Barbell lifting wavelet transform for highly scalable video coding

This paper proposes a generic lifting technology (Barbell Lifting), where each predicting or updating signal is generated with a Barbell function instead of always a sample from single direction or bi-direction, to incorporate various motion alignment methods into temporal wavelet transform. The proposed lifting technology embraces fractional pixel motion alignment, variable block size motion alignment and overlapped block motion alignment into a framework. It also guarantees the perfect reconstruction in various Barbell functions even with fractional precision. Furthermore, the proposed lifting technology also solves several problems that extensively exist in the current 3D wavelet coding schemes, such as many-to-one mapping for the area with covered scenes, non-referred pixels for the area with uncovered scenes, ambiguities of inversed mapping in the updating stage. Replacing the conventional lifting with the proposed Barbell lifting, the 3D wavelet coding scheme achieves a high coding efficiency.
An Early Warning System for Turkey: The Forecasting Of Economic Crisis by Using the Artificial Neural Networks

An economic crisis is typically a rare kind of an event but it impedes monetary stability, fiscal stability, financial stability, price stability, and sustainable economic development when it appears. Economic crises have huge adverse effects on economic and social system. This study uses an artificial neural network learning paradigm to predict economic crisis events for early warning aims. This paradigm is being preferred due to its flexible modeling capacity and can be applied easily to any time series since it does not require prior conditions such as stationary or normal distribution. The present article analyzes economic crises occurred in Turkey for the period 1990-2011. The main question addressed in this paper is whether currency crises can be estimated by using artificial neural networks.
Anticipation and attention for robust object recognition with RGBD-data in an industrial application scenario

An extension based on attention and anticipation of a robot vision pipeline for object recognition in RGBD images from low-cost sensors like MS Kinect or ASUS Xtion is presented. This work originated in research on an industrial application scenario, namely shipping-container unloading, but it is applicable to advanced manipulation tasks in unstructured environments in general where the perception must be very robust while being as fast as possible. For these scenarios, we build on our previous work that proved to be competitive in cluttered scenes in table-top scenarios and which forms the backbone of our RGBD object recognition. It is further enhanced by two main contributions. First, a simple but very effective form of anticipation as top-down expectations of the evolution of the scene due to the actions of the robot is used to speed up the processing. Second, attention is used as a mechanism for further speed-up by focusing processing only on certain regions of interest of the scene based also on an anticipation mechanism. The method is analyzed in experiments using real-world data from an industrial demonstration set-up.
Abduction over Unbounded Domains via ASP

It is known that abduction can be embedded into Answer Set programming (ASP). This enables sophisticated answer set solvers to be applied to abduction problems. However this approach does not scale to abduction over infinite domains, nor to unbounded abduction of individual existence, due to well-known un-decidability results. The approaches to open abduction usually rely on 3-valued semantics to overcome technical difficulties, but this approach changes the underlying semantics and prevents the application of ASP solvers. In this paper we apply the theory of finitary programs to prove that for an expressive and very interesting class of domain theories, ASP-based abduction with unbounded domains can effectively be computed. We also prove that each observable has a finite set of finite explanations representative of all the observable's infinitely many explanations. Moreover, the set of representative explanations can be computed with standard ASP engines.
Compression of View Dependent Displacement Maps

Texture is important to enhance realism in surface representations for computer graphics and vision. View dependent displacement mapping (VDM) is proposed recently to give the effects of shadow, occlusion and silhouette, since traditional texture mapping can not produce all of these effects. Also, VDM can be viewed as a data structure to encode the texture geometry and exploit the modern graphics processing unit (GPU) to do interactive rendering. One drawback of the VDM approach is large memory consumption. Singular value decomposition (SVD) based compression has been proposed to alleviate this issue. In this paper , we present a method that combines k-means clustering and non-negative matrix factorization. Experimental evaluations show that the performance of our approach surpasses prior SVD-based method.
A crowd flow estimation method based on dynamic texture and GRNN

To overcome the deficiencies of the existing methods used in the estimation of the crowd flow with high-density and multi-motion direction, a crowd flow estimation method based on dynamic texture and generalized regression neural network (GRNN) is presented in this paper. The method firstly extracts the dynamic texture features through optical flow, performs the moving crowd segmentation by the dynamic texture features and level set algorithm to achieve ROIs, and then the regression analysis based on GRNN between ROI features and crowd flow is adopted to achieve the real-time crowd flow estimation results in the crowd scene. Experimental results show that the proposed crowd flow estimation algorithm is more suitable than the existing methods to the crowd flow estimation applications with low complexity, high accuracy and high real-time requirements.
ClusterCluster: Parallel Markov Chain Monte Carlo for Dirichlet Process Mixtures

The Dirichlet process (DP) is a fundamental mathematical tool for Bayesian nonparametric modeling, and is widely used in tasks such as density estimation, natural language processing, and time series modeling. Although MCMC inference methods for the DP often provide a gold standard in terms asymptotic accuracy, they can be computationally expensive and are not obviously parallelizable. We propose a reparameterization of the Dirichlet process that induces conditional independencies between the atoms that form the random measure. This conditional independence enables many of the Markov chain transition operators for DP inference to be simulated in parallel across multiple cores. Applied to mixture modeling, our approach enables the Dirichlet process to simultaneously learn clusters that describe the data and superclusters that define the granularity of parallelization. Unlike previous approaches, our technique does not require alteration of the model and leaves the true posterior distribution invariant. It also naturally lends itself to a distributed software implementation in terms of Map-Reduce, which we test in cluster configurations of over 50 machines and 100 cores. We present experiments exploring the parallel efficiency and convergence properties of our approach on both synthetic and real-world data, including runs on 1MM data vectors in 256 dimensions.
ASSESSMENT OF TEACHERS’ PERCEPTIONS ON SCHOOL ENVIRONMENT: THE CASE OF PREPARATORY SCHOOLS IN NORTH GONDAR ADMINISTRATIVE ZONE.

School environment variables were found to impact students’ learning and achievement both positively and negatively. These variables include teachers’ satisfaction, their relationship with students, teachers’ influence on the school, collegiality, principal leadership, students’ discipline as well as teachers’ personal character such as gender, marital status and seniority. The purpose of this research was to examine the levels of teacher’s perception on their personal and school environment factors in the preparatory schools of north Gondar zone. The research used descriptive survey design. From the 29 preparatory schools, 18 schools were selected for the research purposes. From each school, 5 senior teachers (90 teachers in total) were selected using stratified random sampling. Data was collected with questionnaire developed by the researchers and data was analyzed using descriptive (mean and median), and inferential (ANOVA) statistics. Findings showed that teachers experienced unfavorable school environment leading to low satisfaction, poor teacher student relationship, limited teachers influence, lack of collegiality, poor principal leadership and student’s indiscipline. There were no significant differences regarding job satisfaction by gender; however female teachers had relatively higher satisfaction scores than males. There was no significant difference between married and single teachers on their perceptions regarding school and personal variables. However, teachers with lower seniority had higher scores on open environment/climate, job satisfaction, and teacher student relationships. These findings have implications for School Improvement Program (SIP).
Determination of the Visual Field of Persons in a Scene

The determination of the visual field for several persons in a scene is an important problem with many applications in human behavior understanding for security and customized marketing. One such application, addressed in this paper, is to catch the visual field of persons in a scene. We obtained the head pose in the image sequence manually in order to determine exactly the visual field of persons in the monitored scene. We use knowledge about the human vision, trigonometrical relations to calculate the length and the height of the visual field and quaternion approach for doing several changes of reference marks. We demonstrate this technique using a data set of videos taken by surveillance cameras on shops.
3D Facial Landmark Localisation by Matching Simple Descriptors

We present our graph matching approach for 3D facial feature localisation. The work here uses a basic graph model (three vertices and three arcs) to locate the inner eye corners and the nose tip simultaneously. We intend to extend this to a larger set of the eleven features that exist in our ground truth of the face recognition grand challenge (FRGC) database. We apply the structural matching algorithm "relaxation by elimination" using a simple "distance to local plane" node property and a "Euclidean distance" arc property. After the graph matching process has eliminated unlikely candidates, the most likely feature combination (left eye, right eye and nose tip) is selected, by exhaustive search, as the minimum mahalanobis distance over a six dimensional space, corresponding to three node variables and three arc variables. Our results on the 3D FRGC database are presented and discussed.
A Hybrid Model for Ranking Cloud Services

In this paper we analyse the typical inter-cloud scenario, with particular reference to the negotiation of a CSA (Cloud Service Agreement). Thereafter, the roles of the main players - customers, providers, brokers, and auditors -- are taken into account along with reciprocal trust relationships. On this basis, we propose a hybrid model for ranking cloud services. By means of the proposed model we take into account QoS measurements performed by independent Brokers plus certifications made by Auditors. Furthermore, in addition to objective QoS measures, the described model represents an attempt to integrate a reputation system which involves the community of Cloud users in a typical inter-cloud scenario. Indeed, they are supposed to interact with brokers in order to release feedbacks based on their direct experience, and send opinion (recommendations) to potential Cloud customers.
Temporal Dependencies with OrderConstraintsJef WijsenDecember

We propose a temporal dependency, called trend dependency (TD), which captures a signi cant family of data evolution regularities. A simple example of such regularity might be: \Salaries of employees do not decrease. " TDs compare attributes over time using operators of f<;=;>; ; ; 6=g. We de ne a satis ability problem that is the dual of the logical implication problem for TDs, and we investigate the computational complexity of both problems. We provide an axiomatization of logical implication. As TDs allow expressing meaningful trends, \mining" them from existing databases is interesting. For the purpose of TD mining, TD satisfaction is characterized by the common notions of support and con dence. We study the problem TDMINE: Given a temporal database, mine the TDs that conform to a given template and whose support and con dence exceed certain threshold values. The complexity of TDMINE is studied, as well as algorithms to solve it. A comparison with related work is provided at the end of the paper. We show that TDs can express several temporal dependencies found in the literature.