Miracle-dz/UniFAR-FTUs huggingface dataset:
Risikofaktoren für die Kälbersterblichkeit beeinflussen den Nachweis von Antikörpern gegen die Erreger der enzootischen Bronchopneumonie

Zusammenfassung Gegenstand und Ziel Atemwegs- und Lungenerkrankungen sind eine häufige Ursache für Kälberverluste. Ziel dieser Arbeit war, das Management der Kälberhaltung in Milchviehbetrieben zu beschreiben und dabei nach Beziehungen zwischen dem Auftreten der enzootischen Bronchopneumonie (EBP) und der Kälbersterblichkeit sowie Beziehungen zu Managementfaktoren zu suchen. Material und Methoden In 153 Betrieben, die zwischen November 2006 und Juli 2007 auf freiwilliger Basis an der Studie teilnahmen, wurde das Management der Kälberhaltung im Rahmen einer Bestandsvisitation und Betriebsleiterbefragung erfasst und zu der aus der Datenbank HI-Tier ermittelten Kälbersterblichkeitsrate des Referenzjahres 2006 in Beziehung gesetzt. Pro Betrieb wurden Serumproben einer Stichprobe von 7 Tieren ab dem 6. Lebensmonat auf Antikörper gegen das bovine respiratorische Synzytialvirus (BRSV-Ak) und das Parainfluenzavirus Typ 3 (PIV3-Ak) untersucht und die Betriebe entsprechend dem Anteil der Kälber mit BRSV-Ak bzw. PIV3-Ak (≤ 20 % oder > 20 %) in 2 Klassen eingeteilt. Ergebnisse Eine positive Beziehung zur Kälbersterblichkeit zeigten die Betriebsleiterangaben zum betriebsüblichen Zeitpunkt der Erstkolostrumgabe und zur Wichtigkeit von Bronchopneumonien im Krankheitsgeschehen des Betriebs. BRSV-Ak waren häufiger in Betrieben nachweisbar, deren Betriebsleiter angaben, dass die erstmalige Kolostrumgabe üblicherweise später als 4 Stunden nach der Geburt erfolgte, die Geburtsüberwachung nur selten stattfand und die die Staubbelastung im Kälberstall als hoch einschätzten. PIV3-Ak traten in den Beständen häufiger auf, in denen die Kalbungen noch in Anbindehaltung stattfanden. Schlussfolgerung und klinische Relevanz Die Ergebnisse weisen darauf hin, dass sich Abläufe im Kälbermanagement direkt zur und nach der Geburt auf die Kälbersterblichkeit und die Nachweishäufigkeit von BRSV-Ak bzw. PIV3-Ak auswirken können. Einflüsse der Geburtsüberwachung und des Zeitpunkts der Kolostrumgabe sowie der Staubbelastung sollten bei künftigen Studien zur Häufigkeit der EBP Berücksichtigung finden und in die tierärztliche Ursachenanalyse von Bestandsproblemen mit EBP einbezogen werden.
C-Rank:A Credibility Evaluation Method for Deep Web Records

How to identify and evaluate information credibility ranking has become an increasing important problem.To address the issue,an effective credibility evaluation method called C-Rank to compute trust values of records in Deep Web databases is proposed,which constructs an S-R credibility graph for each record.The graph contains 2 types of vertices and 3 types of edges.Firstly,each vertex's local trust value is computed by using out-degrees based on the idea of trust propagation.Then,the weight of record vertex is computed by using its in-degree and adjacent site vertices'local trust values.Lastly,the global trust value of the S-R credibility graph is computed,which denotes the record's credibility in the whole Web.Experiment results show C-Rank can evaluate credibility rankings of records appropriately and discriminate false information effectively.This method is generally applicable to all domains of Deep Web.
Log-Gabor and 2D semi-supervised discriminant analysis based face image retrieval

Face recognition methods are easily affected by variances of lighting and expression,and there are often only part of sample faces labeled in large image database.To address the two problems,this paper presented a face image retrieval method using multi-channel Log-Gabor wavelet based semi-supervised manifold learning algorithm.Firstly,used Log-Gabor to filter the face image to obtain feature matrix.Then proposed two-dimension semi-supervised manifold learning algorithm to extract the discriminative submanifolds.As the proposed method operated on Log-Gabor feature matrix directly,small sample problem was overcome.Furthermore,by making use of labeled and unlabeled information,preserved the local manifold structure of image data.So enhanced the similarity of feature matching.Experimental results on CMU PIE and AR databases show that the proposed approach is effective and superior to others.
UNIVERSIDADE FEDERAL DE SANTA CATARINA CURSO DE BACHARELADO EM CI ˆ ENCIA DA COMPUTAC ¸ ˜ AO

The market of embedded systems is increasingly growing. Nowadays, it is almost impossible not to find electronic equipment that use control systems to implement its functions. Given this market growth, its applications have become more and more complex. In view of this, the need to utilize File Systems to consistently store a large quantity of data is increasing. This study, following the Application Oriented System Design methodology, focus on the modeling of necessary abstractions in such a way that the operational system EPOS provides support to files systems in such an environment. A file system created in the RAM of the system was implemented to validate the proposed modeling.
Distribute with Proficient Revocation of Data Stored in Clouds

Access control is processed on centralized form with key distributed center (KDC). Because of this data are affected if any one of the key gets attacks. To recover the data from the overall damage from attacks, providing attributes for the data in decentralized approach. Due to this attribute based access control for data in cloud storage. Secure the data storage in clouds, decentralized access control approach is introduced. Access control provides authentication for the user, in which only valid users are able to decrypt the stored information. User authentication and access control scheme are introduced in decentralized, which prevent replay attacks and supports modification on data stored in the cloud. Access control in clouds is gaining attention because it is important that only authorized users have to access to valid service. A huge amount of information is being stored in the cloud, and much of this is sensitive information. Clouds are being store sensitive information about patients to enable access to medical professionals, hospital staff, researchers, and policy makers. Decentralized approach and provides authentication without disclosing the identity of the users.
Facial landmark tracking on a mobile device

Face recognition is an important research topic in computer vision and biometrics and has become an important component in society. Face recognition is used in crime fighting and person identification at airports. With the increasing interest in applications of face recognition, the need for real-time face recognition has arisen. In order to perform face recognition, the facial features (e.g. eyes, nose, mouth) have to be localised. Usually, this is done by ’detection’ in each individual frame. This is an inefficient method for dynamic footage, since the location information of facial features from previous frames is not used. A more efficient method is ’tracking’. This paper is about the feasibility of facial feature localisation in dynamic footage using video tracking algorithms. This research is conducted with the aim of improving the speed of a 2D face recognition system on a smartphone. A C++ framework is realised in order to compare 4 video tracking algorithms and 2 widely used facial landmark localisation software libraries. The region-of-interest of the different video tracking algorithms is set automatically. A database is composed to evaluate the different algorithms on accuracy, precision, robustness and speed. With an ideal landmark detector, 2 of the 4 video tracking algorithms are able to outperform a state-of-the-art facial landmark localisation method on precision and accuracy.
Curve and surface framing for scientific visualization and domain dependent navigation

Curves and surfaces are two of the most fundamental types of objects in computer graphics. Most existing systems use only the 3D positions of the curves and surfaces, and the 3D normal directions of the surfaces, in the visualization process. In this dissertation, we attach moving coordinate frames to curves and surfaces, and explore several applications of these frames in computer graphics and scientific visualization. Curves in space are difficult to perceive and analyze, especially when they are densely clustered, as is typical in computational fluid dynamics and volume deformation applications. Coordinate frames are useful for exposing the similarities and differences between curves. They are also useful for constructing ribbons, tubes and smooth camera orientations along curves. In many 3D systems, users interactively move the camera around the objects with a mouse or other device. But all the camera control is done independently of the properties of the objects being viewed, as if the user is flying freely in space. This type of domain-independent navigation is frequently inappropriate in visualization applications and is sometimes quite difficult for the user to control. Another productive approach is to look at domain-specific constraints and thus to create a new class of navigation strategies. Based on attached frames on surfaces, we can constrain the camera gaze direction to be always parallel (or at a fixed angle) to the surface normal. Then users will get a feeling of driving on the object instead of flying through the space. The user's mental model of the environment being visualized can be greatly enhanced by the use of these constraints in the interactive interface. Many of our research ideas have been implemented in Mesh View, an interactive system for viewing and manipulating geometric objects. It contains a general purpose C++ library for nD geometry and supports a winged-edge based data structure. Dozens of examples of scientifically interesting surfaces have been constructed and included with the system.
Clothing Color and Pattern Recognition for Impaired people

In the study of Human-computer-interaction (HCI) the design and use of technology using digitalized computer systems mainly focusing on the particular interfaces between people and computers. There is an ongoing research that taking place till today using Human-computer-interactions especially on visually impaired people. This system mainly introduces the thematic study on "Blind and visually impaired people Human computer and access to Graphics" represents a current research study towards solution for impaired people and brings together a new researchers and practitioners. Here, we are approaching one of the methods which can be useful for the visually impaired people in the form of recognising the clothing patterns. Choosing clothing pattern is one of the challenging tasks for visually impaired people. We matured a camera-based model to notice the clothing patterns. The clothing patterns are categories as five types like (plaid, striped, pattern less, horizontal-vertical, irregular etc) and it identifies 11 clothing colors. The system mainly integrates with the microphone, camera, Bluetooth, earpiece for audio signal. The output of our system is given by audio signal. To recognize clothing patterns, we propose a Hough line Transformation for the detection of pattern and canny detection for detection of edges in the clothing pattern. we proposed the CCNY Clothing Pattern dataset and other different pattern datasets to our method. Using various other performances our method is under the study. In this project we are using OpenCV library for capture the images. Thought such a system would support more independence in blind person's daily life.
Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology

It is a pleasure to welcome you to Santa Fe for UIST 2004, the Seventeenth Annual ACM Symposium on User Interface Software and Technology. This year's symposium continues the UIST tradition of being the premier forum for presentation of research innovations in the software and technology of human-computer interfaces. UIST brings together researchers and practitioners from diverse areas that include traditional graphical and web user interfaces, tangible and ubiquitous computing, virtual and augmented reality, multimedia, new input and output devices, and CSCW. The intimate size, the single track, and comfortable surroundings make this symposium an ideal opportunity to exchange research results and implementation experience. The call for papers attracted 118 full paper submissions and 52 TechNote submissions from Asia, Europe, North and South America, and the South Pacific. The program committee accepted 24 full papers (20%) and 12 TechNotes (23%) that cover a variety of exciting topics, including augmented reality, design tools, toolkits, pen and tactile input, and ambient interfaces. In addition, the program includes a keynote speech by Mary Czerwisnki on using theory as a basis for human-computer interaction research and two invited surveys by Saul Greenberg and Joseph Kaye on Physical User Interfaces and Olfactory Displays, respectively. Posters, demos, and our second annual doctoral symposium round out our program; UIST attendees receive a separate document that contains the accepted submissions for those categories. The UIST proceedings are in color for the first time ever and we hope that they will serve as a valuable reference for user interface researchers and practitioners. We have supplemented the proceedings with a DVD containing videos for almost all of the papers, TechNotes, posters, and demonstrations.
Akıllı telefon ve giyilebilir cihazlarla aktivite tanıma: Klasik yaklaşımlar, yeni çözümler

Son yıllarda özellikle akıllı telefonların ve giyilebilir cihazların gelişmesiyle birlikte aktivite tanıma alanındaki çalışmalar hız kazanmıştır. Aktiviteler temel olarak yürüme, koşma gibi basit aktiviteler ve yemek yeme, uyuma, diş fırçalama gibi karışık aktiviteler olmak üzere ikiye ayrılmaktadır. Bu derleme çalışmasında aktivite tanıma konusu ile ilgili makaleler değerlendirilmiş ve aktivite tanımada kullanılan sensörler, aktivite çeşitleri, uygulama alanları, aktivite tanıma için kullanılan cihazlar, veri toplama işlemi, eğitim yöntemleri, sınıflandırma algoritmaları ve kaynak tüketimi konuları detaylı olarak incelenmiştir. Yapılmış çalışmaların mevcut durumu ortaya konmuş ve kullanılan farklı yöntemler karşılaştırılmıştır. Daha sonra açık veri setleri paylaşılmış ve literatürdeki derin öğrenme yöntemleri kullanan yenilikçi çözümlerden bahsedilmiştir. Son olarak, bu alanda hala açık olan noktalardan bahsedilmiş ve ileride çalışma yapılabilecek konular önerilmiştir. In recent years, the research on activity recognition has gained speed especially with the development of smart phones and wearable devices. Activities could be categorized into two main groups. simple activities such as walking, running and complex activities such as eating, sleeping, brushing teeth. In this survey paper, articles about activity recognition are examined thoroughly. Sensors and devices used in activity recognition, types of daily activities, application areas, data collection process, training methods, classification algorithms and resource consumption are mentioned in details. The state of the art is elaborated and the existing methods are compared to each other. Later, open data sets are mentioned and studies offering innovative solutions using latest approaches such as deep learning methods are introduced. Finally, still open issues on this area are presented and future work has been discussed.
World wide web: online core concept thesaucratic database development to improve information seeking

Information seeking by undergraduate and postgraduate students who are either new to academic research or are from a non-English speaking background is sometimes fraught with difficulties and obstacles for the unwary. Because of personal habits in a home or personal setting Computer users often resort to using the www and Google® to find academic materials. Whilst this is not necessarily an unwise method of finding academic information, those users still experience similar problems because they are related to the establishment of effective search terms. Rootza®TM is an information seeking tool I developed in an attempt to make online searching easier for either the novice or non-novice information seeker. Rootza was researched, developed and experiments conducted with student participants as a PhD project. Rootza's core function is to teach information seekers The Big 61 steps of information seeking as well as the 6 elements that form the basis for the evaluation of online materials acceptable to academic standards. The resulting research and statistical analysis shows a marked improvement in the online information seeking skills for the students who participated in the experiment. This data suggests that the online core concept thesaucratic database which informs the user of the steps of information seeking and the elements which constitute online academically acceptable information does indeed assist students and information seekers.
A feasibility study on estimation of tissue mixture contributions in 3D arterial spin labeling sequence

Arterial spin labeling (ASL) provides a noninvasive measurement of cerebral blood flow (CBF). Due to relatively low spatial resolution, the accuracy of CBF measurement is affected by the partial volume (PV) effect. To obtain accurate CBF estimation, the contribution of each tissue type in the mixture is desirable. In general, this can be obtained according to the registration of ASL and structural image in current ASL studies. This approach can obtain probability of each tissue type inside each voxel, but it also introduces error, which include error of registration algorithm and imaging itself error in scanning of ASL and structural image. Therefore, estimation of mixture percentage directly from ASL data is greatly needed. Under the assumption that ASL signal followed the Gaussian distribution and each tissue type is independent, a maximum a posteriori expectation-maximization (MAP-EM) approach was formulated to estimate the contribution of each tissue type to the observed perfusion signal at each voxel. Considering the sensitivity of MAP-EM to the initialization, an approximately accurate initialization was obtain using 3D Fuzzy c-means method. Our preliminary results demonstrated that the GM and WM pattern across the perfusion image can be sufficiently visualized by the voxel-wise tissue mixtures, which may be promising for the diagnosis of various brain diseases.
Motion Modeling of Crawling Robot Based on Layer Controlled Hybrid Petri Net

In order to describe static characteristics and dynamic behavior of the crawling robot on the aircraft surface which is a complex hybrid motor system as a combination of discrete event and continuous events,the layer controlled hybrid Petri nets is proposed.The definition of constituent elements of the Petri net is given based on the crawling robot movement mechanism and then established single axis layer controlled hybrid Petri net and dual axis layer controlled hybrid Petri net of crawling robot,the model of which could receive the upper trajectory commands and outputs crawling action sequences.Experiments show that:the implementation of creeping control on simulate cabin of the aircraft based on the model was safe and reliable,so the correctness and practicability of the model is verified.
Multi-level Kapur’s thresholding using whale optimization and social group optimization for brain MRI image segmentation

Abstract Image thresholding is the vital part for segmentation of a region in image. A fresh technique of multilevel thresholding based on the whale optimizer and social group optimizer are in fact recommended in this particular paper. New Optimization techniques inspired are actually affected as a result of the interpersonal as well as the backpacking behaviour of all of the whales. The process of multi-level thresholding problem is applied through the Kapur’s entropy and metaheuristic algorithms. The suggested strategy is tried on brain MRI test image set. The suggested methods are next in contrast with particle swarm optimization (PSO) and differential evaluation (DE) constructed multilevel thresholding techniques and other optimization techniques in the literature. The segmentation really calculated with evaluation measures like Sensitivity, Specificity, and Dice Score (DS).
Child language acquisition: Why universal grammar doesn’t help

In many different domains of language acquisition, there exists an apparent learnability problem to which innate knowledge of some aspect of universal grammar (UG) has been proposed as a solution. The present article reviews these proposals in the core domains of (i) identifying syntactic categories, (ii) acquiring basic morphosyntax, (iii) structure dependence, (iv) subjacency, and (v) the binding principles. We conclude that, in each of these domains, the innate UG-specified knowledge posited does not, in fact, simplify the task facing the learner.
Join in Peer-to-Peer Systems: The Steady State Statistics Service Approach

This diploma thesis introduces the Steady-State-Statistics-Service (4S). 4S is a decentralised service which collects approximate statistical information about a Peer-to-Peer (P2P) system and propagates this information into a P2P system. An example application illustrates how 4S can be used in order to insert peers into a P2P system. Two Join-Algorithms are introduced: Number Join and Depth Join. Both Algorithms deterministically insert new peers into a P2P system in which the peers are guided towards “sparse areas”. A framework for the simulation of algorithms is drawn up on the basis of an Event-Driven-Simulation. The framework allows for an easy integration of additional applications. The modular construction makes a simple exchange of modules possible, thereby making the simulation suitable for other situations. Simulations using realistic data show that insertion-operations based on 4S lead to a balanced P2P system. In this system the join algorithms transfer an imbalanced peer into a balanced P2P system. 4S can be described as a basic tool of a P2P system which in particular can be used by different applications.
Distributed load balancing

Distribution of resources has significant advantages, but requires algorithms which can manage this distribution correctly with minimal overhead. One of the greatest difficulties is ensuring that the load produced by this distribution is well balanced. We consider this challenge in several application areas. Within storage systems, we consider modified leashing algorithms that allow load distributions to be greatly improved in multiple contexts. Within networked systems, we construct peer-to-peer systems and supervised peer-to-peer systems that support communication and distributed object allocation while maintaining an equitable distribution of resources. Our systems are based on uniform participants as well as participants which vary in storage capacity or available bandwidth.
Optimizing Time-Efficient Use of Computer-Aided Detection in Computed Tomographic Colonography (Virtual Colonoscopy)

Poster: "ECR 2011 / C-2335 / Optimizing Time-Efficient Use of Computer-Aided Detection in Computed Tomographic Colonography (Virtual Colonoscopy)" by: "A. Dachman1, I. Trilisky1, I. Sethi1, J. Hoffmeister2, R. Van Uitert2, M. W. Vannier1, S. Periaswamy2; 1Chicago, IL/US, 2Nashua, NH/US"