Miracle-dz/UniFAR-FTUs huggingface dataset:
Word Spotting in Scanned Images of Printed Devanagri Documents

In this paper, we propose a keyword retrieval system for locating words in printed Devanagari document images. Government has initiated various schemes to scan and digitally preserve such documents for future use. Such scanned images of documents are now available to users. Even though the documents are available in their digital format, it is still difficult to search for a single word or phrase as they are scanned images. Traditional optical character recognition techniques (OCR) and other text retrieval systems fail on such type of document images due to various types of noises. In such situations word spotting shall be a major help to users to automatically search for a particular word/phrase in millions of such document images. An attempt is made here to design and implement a word spotting technique for printed Devanagari documents. Based on the word spotting technology, a collection of document images is converted into a collection of word images by word segmentation, and a number of profilebased features are extracted to represent word images. Dynamic Time Warping(DTW) is applied for image comparisons. Imageto-image matching is done by calculating similarities between a query word image and each word image in the collection, and consequently, a ranked result is returned in descending order of the similarities. The system supports GUI. The optimal performance of the system is validated.
Design of an Optically Controlled MR-Compatible Active Needle

An active needle is proposed for the development of magnetic resonance imaging (MRI)-guided percutaneous procedures. The needle uses a low-transition-temperature shape memory alloy (LT SMA) wire actuator to produce bending in the distal section of the needle. Actuation is achieved with internal optical heating using laser light transported via optical fibers and side coupled to the LT SMA. A prototype, with a size equivalent to a standard 16-gauge biopsy needle, exhibits significant bending, with a tip deflection of more than 14° in air and 5° in hard tissue. A single-ended optical sensor with a gold-coated tip is developed to measure the curvature independently of temperature. The experimental results in tissue phantoms show that human tissue causes fast heat dissipation from the wire actuator; however, the active needle can compensate for typical targeting errors during prostate biopsy.
Survey of Scalable String Similarity Joins

Similarity Join is an important operation in data integration and cleansing, record linkage, data deduplication and pattern matching. It finds similar sting pairs from two collections of strings. Number of approaches have been proposed as well as compared for string similarity joins. The rising era of big data demands for scalable algorithms to support large scale string similarity joins. In this paper we study the string similarity joins, their use. Further we look at three different techniques for scalable string similarity join using MapReduce, which areParallel set-similarity join, MGJoin and MassJoin. Finally, we try to compare them based on some common characteristics. Keywords— Similarity Join, MapReduce
Functional profiling of microarray experiments using text-mining derived bioentities

MOTIVATION The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.
A continuous regression function for the Delaunay calibration method

Abstract The Delaunay tessellation and topological regression is a local simplex method for multivariate calibration. The method, developed within computational geometry, has potential for applications in online analytical chemistry and process monitoring. This study proposes a novel approach to perform prediction and extrapolation using Delaunay calibration method. The main property of the proposed extension is the continuity of the estimated regression function also outside the calibration domain. To support the presentation, an application in estimating the aromatic composition in Light Cycle Oil by Near Infrared spectroscopy is discussed.
Signal transduction by the α6β4 integrin: distinct β4 subunit sites mediate recruitment of Shc/Grb2 and association with the cytoskeleton of hemidesmosomes

The EMBO Journal , 14 , 4470–4481, 1995 The α6β4 integrin is a major receptor for the basement membrane component laminin 5. Ligation of the α6β4 integrin induces tyrosine phosphorylation of the β4 cyto plasmic domain, followed by recruitement of the adaptor protein Shc and activation of mitogen‐activated protein (MAP) kinase cascades (Mainiero et al ., 1995, 1997). In addition to its signaling function, the cytoplasmic domain of β4 plays a crucial role in the assembly of hemidesmosomes (Spinardi et al . , 1993; Murgia et …
Energy and macronutrient intakes of professional football (soccer) players.

OBJECTIVE: To examine the dietary habits of professional soccer players at two Scottish Premier League clubs during the competitive season. METHODS: A study of the dietary intake of 51 professional soccer players with two different clubs was carried out by the seven day weighed intake method. RESULTS: Physical characteristics of the two groups of players were similar, with only small differences in age and body mass but no difference in height and body fat. Mean (SD) daily energy intake for club A was 11.0 (2.6) MJ, and for club B 12.8 (2.2) MJ. The higher energy intake at club B was largely accounted for by a higher (P < 0.005) fat intake (118 v 93 g d-1): there was no difference in the absolute amounts of protein, carbohydrate, or alcohol consumed. When expressed as a fraction of total energy intake, mean protein intake was higher (P < 0.05) and fat intake lower (P < 0.01) at club A. CONCLUSIONS: The mean energy intake of these players was not high compared with athletes in endurance sports. Fractional contribution of the macronutrients to total energy intake was broadly similar to that of the general population.
Predicting staff retention from employee motivation and job satisfaction

Abstract This study investigated the role of employee motivation and job satisfaction as predictors of staff retention in a foreign exchange bank. Participants were 341 employees of a South African foreign exchange bank division (female = 62.8%; black = 31.1%; managers = 37%, mean years of experience = 10 years). The employees completed the following self-report measures: Work Preference Inventory, Job Satisfaction Survey, and Employee Retention Questionnaire. Structural equation modelling was applied in the analysis to test the prediction effect of employee motivation and job satisfaction on staff retention. The findings of the model fit revealed that the model (employee motivation and employee job satisfaction) explained an estimated 46% of the variance in the employee retention construct. The job satisfaction construct in the model explained an estimated 66% of the variance in the employee retention construct; while the employee motivation construct explained only 8% of the variance. Organisational talent management should seek to identify employee motivation and job satisfaction interventions that might help to retain talented staff.
Unsupervised categorical shape reconstruction through manifolds

We tackle a new challenge of unsupervised categorical 3D reconstruction using images from different instances without any manually assigned key point correspondence. We take advantage of the observations that objects are generally captured from ground-level viewpoints, and that images transform smoothly between some characteristic viewpoints despite the difference among instances. To estimate 3D models of a category, we first embed the images into a manifold to cluster viewpoints into degenerate and intermediate viewpoints. Then, we select adequate triplets of images that capture similarly shaped objects by aligning manifolds of the different viewpoint clusters. To establish correspondence between the images, we prepare finer clusters from the original manifold, and obtain a common set of features that are at locations consistent with the average flow between neighboring clusters. Under the assumption of orthographical projection, camera parameters are estimated using the correspondence among views. Finally, visual hull for each image triplet is calculated using the silhouettes. Our method is capable of automatically reconstructing an approximate categorical model even without supervision.
Pandora: A Reasoning Toolbox using Natural Deduction Style

Pandora is a tool for supporting the learning of first order natural deduction. It includes a help window, an interactive context sensitive tutorial known as the “e-tutor” and facilities to save, reload and export to LATEX. Every attempt to apply a natural deduction rule is met with either success or a helpful error message, providing the student with instant feedback. Detailed electronic logs of student usage are recorded for evaluation purposes. This paper describes the basic functionality, the e-tutor, our experiences of using the tool in teaching and our future plans.
Literature Review of Student Self-assessment and Its Effects on the Second Language Writing

This paper is a detailed review of the theories and previous studies that investigate self-assessment and second language writing. After the introduction of the definition of self-assessment, a review of the validity and reliability of self-assessment will be presented, followed by its potential benefits to students, teachers and the conventions of testing. The previous studies on the effects of self-assessment on second language writing are reviewed at the end of this
FOCAS AUTOMATIC CATALOG MATCHING ALGORITHMS

This paper describes efficient algorithms that automatically take two or more catalogs of objects with instrumental coordinates and magnitudes and matches them. The challenges are that the instrumental coordinates may be only partially overlapping, at a different scale, rotated, or even inverted (flipped). The object magnitudes may be derived from different passbands so that the relative magnitudes of the objects differ. Also, the catalog may not contain all the same objects to to differences in separating close objects or to partial overlap between images. Finally, the catalog positions and magnitudes are subject to noise in the images from which they were derived. The algorithms are applicable to any automated cataloging system. However, the implementation described here is part of the Faint Object Classification and Analysis System (FOCAS). FOCAS automatically produces catalogs of objects from digital images. The algorithms described here first take a subsample of the brightest objects from the catalog, and other catalogs. Then all the objects in the catalogs are matched based on the transformed reference coordinates.
VERB NUMBERS = COMPUTATIONAL VERBS + NUMBERS

In this paper the concept of (computational) verb number and arithmetical operations of verb numbers are presented. A verb number is a kind of special computational verb, which is derived from structures of (host) verb+(real, interval, fuzzy) number. From the linguistic point of view, a verb number is a computational verb with contexts defined by (real, interval, fuzzy) numbers. Verb numbers can be classified into three basic types based on the outer systems of host verbs. The arithmetic for verb numbers and its rules are presented and proved. If host computational verbs degrade to BE, then verb numbers collapse to real numbers, interval numbers, fuzzy numbers (sets) or other numbers. The set of all verb numbers can be a metric space. The distance between verb numbers can be defined based on the collapses of verb numbers. The cases when verb numbers collapse to triangular fuzzy numbers, trapezoidal fuzzy numbers and interval numbers are presented and proved. The method of constructing verb numbers from fuzzy numbers is presented. c ©2002 Yang’s Scientific Research Institute, LLC. All rights reserved.
A Quantitative Comparative Study of Prosodic and Discourse Units, the Case of French and Taiwan Mandarin

Studies of spontaneous conversational speech grounded on large and richly annotated corpora are still rare due to the scarcity of such resources. Comparative studies based on such resources are even more rarely found because of the extra-need of comparability in terms of content, genre and speaking style. The present paper presents our efforts for establishing such a dataset for two typologically diverse languages: French and Taiwan Mandarin. To the primary data, we added morphosyntactic, chunking, prosodic and discourse annotation in order to be able to carry out quantitative comparative studies of the syntax-discourse-prosody interfaces. We introduced our work on the data creation itself as well as some preliminary results of the boundary alignment between prosodic and discourse units and how POS and chunks are distributed on these boundaries.
SemText: A semantically enriched information retrieval system for biology

SemText draws upon a number of core technologies from the NaCTeM text mining tool kit to enhance automated detection and mark-up of biologically important terms appearing in text, such as gene/protein names. One of these tools is AcroMine which disambiguates acronyms based upon the context in which they appear. This functionality plays a key role in searching large document collections by allowing users to expand their queries and to include synonymous acronyms without losing the specificity of the original query.
Functional Renormalization Group Equations, Asymptotic Safety, and Quantum Einstein Gravity

These lecture notes provide a pedagogical introduction to a specific continuum implementation of the Wilsonian renormalization group, the effective average action. Its general properties and, in particular, its functional renormalization group equation are explained in a simple scalar setting. The approach is then applied to Quantum Einstein Gravity (QEG). The possibility of constructing a fundamental theory of quantum gravity in the framework of Asymptotic Safety is discussed and the supporting evidence is summarized.
Noiseless and vibration-free Ionic Propulsion technology for indoor surveillance blimps

We present in this paper a novel indoor blimp that is propelled by a propulsion technology that uses no moving mechanical parts and thus is noiseless and vibration free. In our prior work reported at IEEE/ASME AIM 2007, we demonstrated several prototype propulsive units (with asymmetric capacitor configurations) that lift themselves into air. Using these basic propulsive units (“Ionic Flyers”), we have recently developed an indoor flying blimp that has a propulsion system with no moving mechanical parts and thus generates no noise or vibration - the Ionic Propulsion Blimp. The key to successfully create this novel indoor flying system is the development of a power generation system that includes an 11.1V battery which is capable of generating ∼20kV DC voltage continuously over time for a load in the MΩ range. The architecture of this ionic power system will be presented. A detailed parametric analysis and an optimal design methodology of the Ionic Flyer are also discussed. Initial experimental results of the Ionic Propulsion Blimp are also summarized in this paper.
Edge Detection for Retinal Image Using Superimposing Concept and Curvelet Transform

Retinal image analysis plays vital role in many applications, such as finding out ocular fund us and early stage detection of some disease. Even though there is more advanced technologies for human recognition process this retinal image analysis concentrates on the human iris authentication purpose. Since both the similar person can’t have the same retinal blood vessels. As per this paper concern in extracting of retinal blood vessels from the retina images as well as finding out disease affected area in the retina image to do this process the methodologies implemented are multi structure elements makes the edge detection effectively. Hence morphology operators using multi structure elements method are used to find out the ridges. Afterwards morphological operators by reconstruction eliminate the ridges which are not belonging to the blood vessels. The algorithm used here is back propagation (BPA) which helps to find out the real retinal blood vessels from the image. The researchers also have more reputed works on this area to produce better result for blood vessel detection.
Sill Image Object Categorization Using 2D Objects Models

This paper proposes a novel recognition scheme for semantic labeling of 2D objects present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to associate the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Experiments show that such a system can achieve recognition rate up to 70.4%.
Gender and generational differences in first outward- and first inward-moves: An event-history analysis of rural migrants in China

Focusing on the onset of circularity, this paper examines the first outward-moves and first inward-moves of rural–urban migrants in China. Using event-history analysis, we investigate the impacts of time-varying individual and household characteristics on the mobility of 787 rural workers from six villages in Anhui Province, based on a longitudinal study of 150 households for the period 1980 to 2009. The findings show that the probability of initiating the first outward-move and first inward-move is affected by age, gender, education, decade, and life-cycle and household-arrangement factors such as the location of dependent children, spouse, and elderly parents. New-generation migrants are more likely to move outward and spend longer time outside the home location than their predecessors. Gender differences persist; women continue to be less likely to move outward and more likely to return, and their mobility patterns are much more sensitive to caregiving needs than men. These results suggest that migrants’ circularity will persist and that China’s urbanization policy should consider multi-locality as a central component of migration.
Modifying the IEEE 802.11 MAC to improve performance of multiple broadcasting of multimedia data in wireless ad-hoc networks

Multimedia applications over wireless networks have dramatically increased over the past years. Numerous new devices and applications that distribute audio and video over wireless networks are introduced every day and all of them demands a reliable and efficient wireless standard. Either operating as independent ad-hoc networks or as terminal parts of wired networks or the internet, wireless networks are frequently facing the need to broadcast multimedia data from multiple sources to multiple users. IEEE 802.11 standard (Wi-Fi) is the primary technology in wireless networking today. However, it has some inherited problems when it comes to broadcasting caused mainly by the lack of an acknowledgment mechanism. These problems do not allow the standard to take full advantage of the bandwidth offered by its latest amendments. In this paper two independent modifications of the medium access control (MAC) mechanism of the standard, are proposed along with the expanded use of the CTS-to-Self protection mechanism. The main objective of this study is to explore the ability of the modified MAC mechanisms to improve broadcasting performance while are operating in conjunction with a regular wireless network, and also to define the cases were the use of CTS-to-Self-protection mechanism can improve the overall performance of the network. The results show that the overall performance can be improved using these alternative MAC methods. Also, the cases where the CTS-to-Self technique can additionally contribute to the network performance are defined and analyzed.
Super-resolution reconstruction based on structure tensor's eigenvalue and classification dictionary

Super-resolution provides effective prior information for the single-frame super resolution reconstruction. It's difficult to recover fine grained details via a general dictionary, trained through the diversified training samples, due to the negli-gence of structural characteristics. Thus, the dictionary whic-h is adaptive to local structures is needed. Considering the eigenvalues of structure tensor are convenient to distinguish the edge regions and the smooth regions, we construct a sca-lar texture feature descriptor to present texture information of image. It is employed for clustering low and high resolution patches in the training stage and for model selection in the reconstruction stage. Tight sub-dictionary is learned for each cluster. For a given test image patch, the corresponding sub-dictionary is adaptively selected, and then super-resolution reconstruction of this image is completed. Com-pared with the recently proposed dictionary learning met-hods for image super-resolution reconstruction, the algorit-hm preserves more details and ensures the quality of the reconstructed image.
Progressive Occlusion of Enterprise Stent-Assisted Coiling of Ruptured Wide-Necked Intracranial Aneurysms and Related Factors on Angiographic Follow-Up: A Single-Center Experience with 468 Patients

This study was designed to assess the effect of the Enterprise stent on progressive occlusion of wide-necked aneurysms and to evaluate the association between dubious factors and progressive occlusion, which is a consecutive, retrospective, single-center study. Data from 468 patients with 495 wide-necked aneurysms, who had undergone Enterprise stent-assisted coiling (SAC) were reviewed, and the clinical outcomes and the angiographic results were analyzed. A 14-month clinical follow-up was achieved in 421 of the 468 patients (90.0%), showing modified Rankin Scale (mRS) 0–1 in 364 (86.4%), mRS 2 in 17 (4.1%), mRS 3 in 17 (4.1%), mRS 4–5 in 9 (2.1%), and mRS 6 in 14 (3.3%) patients. Overall, the morbidity and mortality were 10.2% and 3.3%, respectively. Initial angiographic results showed Raymond scale (RS)1 in 273 (55.2%), RS2 in 194 (39.2%), and RS3 in 28 (5.6%) patients. Eight-month angiographic follow-up was available in 394 of 495 patients (79.6%), and RS1 was seen in 315 (79.9%), RS2 in 65 (16.5%) and RS3 in 14 (3.6%) cases. At the end of the follow-up, 115 of the 165 (69.7%) patients with initial RS2 and RS3 showed progressive occlusion. Statistical analysis showed no significant difference between progressive occlusion and age (p = 0.654), sex (p = 0.016), aneurysm diameter (p = 0.010), neck size (p = 0.124), dome-to neck ratio (DNR) (p = 0.018) and location (p = 0.001) at the time of follow-up. SAC using Enterprise stent is not only feasible for wide-necked aneurysms, but can achieve a high rate of progressive occlusion with good clinical outcomes at medium-term follow-up. Patient age and aneurysm neck size showed no associated with progressive occlusion at follow-up, while sex, aneurysm diameter, DNR and location were significantly associated with progressive occlusion.