Miracle-dz/UniFAR-FTUs huggingface dataset:
3DNet: Large-scale object class recognition from CAD models

3D object and object class recognition gained momentum with the arrival of low-cost RGB-D sensors and enables robotics tasks not feasible years ago. Scaling object class recognition to hundreds of classes still requires extensive time and many objects for learning. To overcome the training issue, we introduce a methodology for learning 3D descriptors from synthetic CAD-models and classification of never-before-seen objects at the first glance, where classification rates and speed are suited for robotics tasks. We provide this in 3DNet (3d-net.org), a free resource for object class recognition and 6DOF pose estimation from point cloud data. 3DNet provides a large-scale hierarchical CAD-model databases with increasing numbers of classes and difficulty with 10, 50, 100 and 200 object classes together with evaluation datasets that contain thousands of scenes captured with a RGB-D sensor. 3DNet further provides an open-source framework based on the Point Cloud Library (PCL) for testing new descriptors and benchmarking of state-of-the-art descriptors together with pose estimation procedures to enable robotics tasks such as search and grasping.
Geodesics and spanning trees for Euclidean first-passage percolation

The metric D α (q, q') on the set Q of particle locations of a homogeneous Poisson process on R d , defined as the infimum of (Σ i |q i -q i+1 | α ) 1/α over sequences in Q starting with q and ending with q' (where |.| denotes Euclidean distance) has nontrivial geodesics when a > 1. The cases 1 < α < ∞ are the Euclidean first-passage percolation (FPP) models introduced earlier by the authors, while the geodesics in the case α = ∞ are exactly the paths from the Euclidean minimal spanning trees/forests of Aldous and Steele. We compare and contrast results and conjectures for these two situations. New results for 1 < α < ∞ (and any d) include inequalities on the fluctuation exponents for the metric (X ≤ 1/2) and for the geodesies (ξ ≤ 3/4) in strong enough versions to yield conclusions not yet obtained for lattice FPP: almost surely, every semiinfinite geodesic has an asymptotic direction and every direction has a semiinfinite geodesic (from every q). For d = 2 and 2 < α < ∞ further results follow concerning spanning trees of semiinfinite geodesics and related random surfaces.
A novel method of automatically generating texture atlas for triangular meshes

Texture Atlas is a kind of large image consisting of many sub-images, which are usually used to store surface texture in realistic rendering. In order to reach a higher capacity rate for the atlas, a novel method of automatically generating texture atlas for triangular meshes is presented. Each triangular is rotated until its longest edge is in horizontal direction, so that the area of its bounding box is effectively reduced. According to the order of the area descending, each triangle bounding box is packed into atlas space through the collision test. The experimental results show that our approach has the advantage of storing texture without deformation, and can substantially increase the capacity rate of atlas without increase of the running time.
Selecting Best Practices for Effort Estimation

Effort estimation often requires generalizing from a small number of historical projects. Generalization from such limited experience is an inherently underconstrained problem. Hence, the learned effort models can exhibit large deviations that prevent standard statistical methods (e.g., t-tests) from distinguishing the performance of alternative effort-estimation methods. The COSEEKMO effort-modeling workbench applies a set of heuristic rejection rules to comparatively assess results from alternative models. Using these rules, and despite the presence of large deviations, COSEEKMO can rank alternative methods for generating effort models. Based on our experiments with COSEEKMO, we advise a new view on supposed "best practices" in model-based effort estimation: 1) Each such practice should be viewed as a candidate technique which may or may not be useful in a particular domain, and 2) tools like COSEEKMO should be used to help analysts explore and select the best method for a particular domain
Factors Predicting Reversion from Mild Cognitive Impairment to Normal Cognitive Functioning: A Population-Based Study

Introduction Mild cognitive impairment (MCI) is associated with an increased risk of developing dementia. However, many individuals diagnosed with MCI are found to have reverted to normal cognition on follow-up. This study investigated factors predicting or associated with reversion from MCI to normal cognition. Methods Our analyses considered 223 participants (48.9% male) aged 71–89 years, drawn from the prospective, population-based Sydney Memory and Ageing Study. All were diagnosed with MCI at baseline and subsequently classified with either normal cognition or repeat diagnosis of MCI after two years (a further 11 participants who progressed from MCI to dementia were excluded). Associations with reversion were investigated for (1) baseline factors that included diagnostic features, personality, neuroimaging, sociodemographics, lifestyle, and physical and mental health; (2) longitudinal change in potentially modifiable factors. Results There were 66 reverters to normal cognition and 157 non-reverters (stable MCI). Regression analyses identified diagnostic features as most predictive of prognosis, with reversion less likely in participants with multiple-domain MCI (p = 0.011), a moderately or severely impaired cognitive domain (p = 0.002 and p = 0.006), or an informant-based memory complaint (p = 0.031). Reversion was also less likely for participants with arthritis (p = 0.037), but more likely for participants with higher complex mental activity (p = 0.003), greater openness to experience (p = 0.041), better vision (p = 0.014), better smelling ability (p = 0.040), or larger combined volume of the left hippocampus and left amygdala (p<0.040). Reversion was also associated with a larger drop in diastolic blood pressure between baseline and follow-up (p = 0.026). Discussion Numerous factors are associated with reversion from MCI to normal cognition. Assessing these factors could facilitate more accurate prognosis of individuals with MCI. Participation in cognitively enriching activities and efforts to lower blood pressure might promote reversion.
An Extended EOQ Model in Production-Recycling System

In this paper, we develop an extended EOQ model with used products recycling and finished products producing to satisfy the fixed demands. This model involves the repair and the continuous collection of used products and allows multiple production lot-sizes problems. Based on the present model, we present a joint policy associating with the collection of used products and the production of finished products under the minimization of total costs of the inventory system, and we deduce simultaneously the optimal economic order quantity of finished products and the optimal inventory level of repairable products models. Finally, we give several numerical examples to illustrate the validity of the models.
Metaphor and ideology: Conceptual structure and conceptual content in Spanish political discourse

This article presents the results of the analysis of a number of linguistic metaphors found in a corpus of opinion articles published in the Spanish newspaper El País. The authors included in the corpus, who tend towards the left of the political spectrum, use metaphor to express moral judgements on the actions and decisions of the conservative, centre-right People’s party (Partido Popular or PP), which governs Spain with an overall majority. With the aim of describing this discourse, we have undertaken a qualitative analysis with a conceptual framework deriving from CDA and cognitive linguistics. First, therefore, we have made use of the methodology developed by Steen and the Pragglejaz group to extract the discourse units that could be considered as the lexical expression of an underlying mapping between domains, that is, the metaphors; second, according to the descriptions of Talmy, Croft, Sweetser, Sullivan, and Dancygier and Sweetser, we have verified that the different types of grammatical structure in which the lexical items appeared also indicated the existence of a metaphorical thought process; and third, in the words of van Dijk, we have studied the ideological semantics underlying conceptual structures and conceptual content. As we have demonstrated, all the samples of linguistic metaphors found led readers to construct the same interpretation of the meaning: The Spanish People’s party government is the past, a past that provokes rejection and which was thought to be definitively ended.
ZCS and TCS learning classifier system controllers on real robots

To date there has only been one implementation of Holland's Learning Classifier System (LCS) on real robots. In this paper the use of Wilson's ZCS system is described for an obstacle avoidance task. Although the task is simple it does present some advances and change of emphasis over the previous LCS robotic implementation. The controller model is "event" based. Instead of the robot being assigned fixed length actions, continuous actions are taken. These actions are taken until an "event" occurs. An event can be thought of as a change of state. This division of the world into states is usually part of the problem description, and to do this automatically is currently one of the challenges facing machine learning. The paper then introduces TCS, a form of ZCS that attempts to address this issue. LCS have the ability to generalise over the state action-space. In TCS this generalisation ability can also be used to determine the extent of this space. TCS also implements components from SMDP reinforcement learning theory to weight the influence of time on the reward functions of the LCS. A simple light-seeking task on the robot platform using TCS is presented which demonstrates desirable adaptive characteristics for the use of LCS on real robots.
Face authentication by using elastic graph matching and support vector machines

A novel method for enhancing the performance of elastic graph matching in face authentication is proposed. The starting point is to weigh the local matching errors at the nodes of an elastic graph according to their discriminatory power. We propose a novel approach to discriminant analysis that re-formulates Fisher's linear discriminant ratio to a quadratic optimization problem subject to inequality constraints by combining statistical pattern recognition and support vector machines. The method is applied to frontal face authentication on the M2VTS database.
Performance prediction based on knowledge of prior product versions

Performance estimation is traditionally carried out when measurement from a product can be obtained. In many cases there is, however, a need to start to make predictions earlier in a development project, when for example different architectures are compared. In this paper, two methods for subjective predictions of performance are investigated. With one of the methods experts estimate the relative resource usage of software tasks without using any knowledge of earlier versions of the product, and with the other method experts use their experience and knowledge of earlier versions of the system. With both methods there are rather large differences between different individual predictions, but the median of the prediction error indicates that the second method is worth further investigations.
Reducing barriers how the Jews of Djerba are using tourism to assert their place in the modern nation state of Tunisia

ABSTRACT The Island of Djerba is one of Tunisia’s most important tourist venues. Once a year, it becomes the host site for the only Jewish pilgrimage in the entire Islamic world, an event that takes place at the synagogue of El Ghriba, itself the oldest synagogue in North Africa. The Jewish community in Djerba is today confronted not only by the challenges of declining numbers due to outmigration and an aging population, but also by issues arising from a lack of political representation. The result has been a rise in forecasts about a continued decline in community numbers and a corresponding attrition in the number of people making the pilgrimage to El Ghriba. At the same time, with the increase in Jihadist threats since the attack against the synagogue in 2002 and the revolution of 2011, the importance of ensuring that the pilgrimage to El Ghriba can continue to occur has become an issue of national concern. The pilgrimage is now launched every year under the auspices of officials of the State, such as President Marzouki and and different Ministers of Tourism and takes place under heavy military and police protection. Both the pilgrimage itself and the community now seem to be invested with a new role intrinsic to the overall economic and security status of the country. This article proposes an analysis of the different strategies employed by the Jewish community to use tourism to reassert its role as a full and active citizen of Tunisia, while at the same time maintaining the vitality of the pilgrimage to El Ghriba.
Evaluating the Performance of Reverse Encryption Algorithm (REA) on the Databases

Database encryption is a well established technology for protecting sensitive data. Unfortunately, the integration of existing encryption techniques with database systems causes undesirable performance degradation. It is a crucial technique in the security mechanisms of database. In this paper we propose a new encryption algorithm, which we call Reverse Encryption Algorithm (REA). Our new encryption algorithm REA is simple and yet leads to a cipher. It has achieved security requirements and is fast enough for most applications. REA algorithm is limiting the added time cost for encryption and decryption to don't degrade the performance of a database system. Also, we evaluate the performance of the proposed encryption algorithm REA and compare with the most common encryption algorithms. The performance measure of encryption schemes will be conducted in terms of encryption / decryption time. Experiment results show that our new algorithm outperforms other algorithms at encryption and decryption time.
Modelling User Interfaces for Special Needs

Computers offer valuable assistance to people with physical disabilities. However designing human-computer interfaces for these users is complicated. The range of abilities is more diverse than for able-bodied users, which makes analytical modelling harder. Practical user trials are also difficult and time consuming. We are developing a simulator to help with the design and evaluation of assistive interfaces. It can predict the likely interaction patterns when undertaking a task using a variety of input devices, and estimate the time to complete the task in the presence of different disabilities and for different levels of skill. The simulator is developed according to the concept of Model Human Processor. It consists of a Perception model, a Cognitive model and a Motor-Behaviour Model. In this paper, we have discussed the modelling of visual impairments in the perception model of our simulator. We describe the functions used to model different visual impairments and present demonstrations of their execution.
Big data analytics for health systems

The speedily growing field of big data analytics has started to play a pivot role in the advancement of healthcare practices and research. It has provided tools to mount up, manage, analyze, and incorporate large volumes of unrelated, structured, and unstructured data produced by current healthcare systems. Big data analytics is a useful technique that is useful to provide better analysis of disease. However, the acceptance rate and research development in this space is still delayed by some fundamental problems inbuilt within the big data standard. Current research which focuses on utilization of huge volume of medical data while combining multidimensional data from different sources is discussed. Some areas of research within this field which have the ability to provide significant impact on healthcare delivery are also examined.
A Realistic Battlefield Model for the Evaluation of MANET

Often quoted MANET applications include battlefield and disaster relief. Most research into MANET routing solutions is done using simulations that contain models of the physical space in which the MANET operates, the number of nodes deployed and the movement patterns and communications requirements of the nodes. This paper presents a specific example model of a battlefield based on a real building and current military tactics, and compares the performance of three protocols (AODV, DSDV and DSR) in this model with a random model similar to those used in most publications.
Multi-Genomic Algorithms

The first step of any optimization process consists in choosing the Decision Variables (DV) and its relationships that model the problem, system or object to optimize. Many problems cannot be represented by a unique, exhaustive model which would ensure a global best result: in those cases, the model (DV and relationships) choice matters on the quality of the results.
Memory-based and on-line processing of metaphoric sarcasm

Metaphoric statements such as “He certainly is Romeo to her Juliet” can be uttered not only as a metaphor but used sarcastically to make a commentary on the metaphor. So how does one determine the intent of the speaker who utters such a statement? Evidence is reviewed about the constraints that are available for use by someone who reads or hears such a statement and an experiment is described which indicates that at least some of these constraints work on-line, that is during the moment-to-moment processing of the statement as it is encountered.
A multiple case study of teachers’ visions and reflective practice

Abstract Researchers have found that teachers’ visions of what they hope to instill in their students beyond curricular objectives are integral to their instruction and to larger decisions such as their career paths. The purpose of this research was to examine 10 in-service teachers, who taught in different geographic locations across the United States, their visions, and the ways in which these visions influenced their reflective curricular decisions and instructional actions. The researchers describe salient dimensions of visions, the actions teachers reported to enact visions, and the distance and tensions in enacting visions. Researchers used grounded theory and constant comparative analysis to analyze interviews, questionnaires, and artifacts. Findings explore the relationship between teachers’ visions and reflective practice as well as the alignment of instructional practices teachers report in supporting their respective visions. Implications for future research, theory, and practice are discussed.
Model Based Modified K-Means Clustering for Microarray Data

Large amount of gene expression data obtained from Microarray technologies should be analyzed and interpreted in appropriate manner for the benefit of researchers. Using microarray techniques one can monitor the expressions levels of thousands of genes simultaneously. One challenging problem in gene expression analysis is to define the number of clusters. This can be done by some efficient clustering techniques; the Model Based Modified k-means method introduced in this paper could find the exact number of clusters and overcome the problems in the existing k-means clustering technique. Our experimental results show the efficiency of our method by calculating and comparing the sum of squares with different k values.
Diagnostic accuracy of rectal mucosa biopsy testing for chronic wasting disease within white-tailed deer (Odocoileus virginianus) herds in North America

An effective live animal diagnostic test is needed to assist in the control of chronic wasting disease (CWD), which has spread through captive and wild herds of white-tailed deer (Odocoileus virginianus) in Canada and the United States. In the present study, the diagnostic accuracy of rectal mucosa biopsy sample testing was determined in white-tailed deer from 4 CWD-infected captive herds. Specifically, the current study compared the immunohistochemical detection of disease-associated prion protein in postmortem rectal mucosa biopsy samples to the CWD status of each deer as determined by immunodiagnostic evaluations of the brainstem at the obex, the medial retropharyngeal lymph node, and the palatine tonsil. The effects of age, sex, genotype, and disease progression were also evaluated. Diagnostic sensitivity on rectal biopsy samples for CWD in white-tailed deer ranged from 63% to 100%; the pooled estimate of sensitivity was 68% with 95% confidence limits (95% CLs) of 49% and 82%. However, diagnostic sensitivity was dependent on genotype at prion protein gene (PRNP) codon 96 and on disease progression as assessed by obex grade. Diagnostic sensitivity was 76% (95% CLs: 49%, 91%) for 96GG deer but only 42% (95% CLs: 13%, 79%) for 96GS deer. Furthermore, diagnostic sensitivity was only 36% for deer in the earliest stage of disease (obex grade 0) but was 100% for deer in the last 2 stages of preclinical disease (obex grades 3 and 4). The overall diagnostic specificity was 99.8%. Selective use of antemortem rectal biopsy sample testing would provide valuable information during disease investigations of CWD-suspect deer herds.
When Team Members Perceive Task Interdependence Differently: Exploring Centrality Asymmetry and Team Success

In this article, we examine the construct of perceived task interdependence and propose that there is variation in how members perceive interdependence with one another, even within the same team. In particular, we introduce centrality asymmetry—the extent to which members differ in their perceptions of how central they are in the team’s task interdependence network relative to how central other members see them. Using field data (interviews, team surveys, and executive ratings) from 2,222 members across 319 teams in a large corporation, we test hypotheses regarding the relationship between centrality asymmetry and team success. We find that teams with more centrality asymmetry are less successful, above and beyond the level of perceived task interdependence centrality and variation in perceived task interdependence centrality on the team. We discuss the implications of our findings for future theory and research on task interdependence in teams.