Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing Popularity Dynamics of User-generated Videos: A Category-based Study of YouTube

Understanding the growth pattern of content popularity has become a subject of immense interest to Internet service providers, content makers and on-line advertisers. This understanding is also important for the sustainable development of content distribution systems. As an approach to comprehend the characteristics of this growth pattern, a significant amount of research has been done in analyzing the popularity growth patterns of YouTube videos. Unfortunately, no work has been done that intensively investigates the popularity patterns of YouTube videos based on video object category. In this thesis, an in-depth analysis of the popularity pattern of YouTube videos is performed, considering the categories of videos. Metadata and request patterns were collected by employing category-specific YouTube crawlers. The request patterns were observed for a period of five months. Results confirm that the time varying popularity of different YouTube categories are conspicuously different, in spite of having sets of categories with very similar viewing patterns. In particular, News and Sports exhibit similar growth curves, as do Music and Film. While for some categories views at early ages can be used to predict future popularity, for some others predicting future popularity is a challenging task and require more sophisticated techniques, e.g., time-series clustering. The outcomes of these analyses are instrumental towards designing a reliable workload generator, which can be further used to evaluate different caching policies for YouTube and similar sites. In this thesis, workload generators for four of the YouTube categories are developed. Performance of these workload generators suggest that a complete category-specific workload generator can be developed using time-series clustering. Patterns of users’ interaction with YouTube videos are also analyzed from a dataset collected in a local network. This shows the possible ways of improving the performance of Peer-to-Peer video distribution technique along with a new video recommendation method.
Onlinegestützte Suche nach innovativen Anwendern in direkten und analogen Anwendermärkten

Unternehmen, die Produkte der nachsten Generation entwickeln, stehen oft vor folgendem Problem: Orientieren sie ihre Entwicklung zu stark an den heutigen Kunden und Anwendern, resultieren oft nur kleine Innovationen (inkrementale Innovation). Losen Sie sich hingegen von diesen Anwendern, erhoht sich die Gefahr einer Entwicklung am Markt vorbei. Das sog. Lead User Verfahren stellt einen Ausweg aus diesem Dilemma dar, da sich die Entwicklungsarbeit hier an Anwendern orientiert, die hinsichtlich marktlicher wie technischer Trends Vorreiter-Status in ihrer Branche haben. Die mit Lead Usern gemeinsam entwickelten Produktkonzepte konnen dann mit Hilfe der klassischen, testenden Marktforschung auf deren Vermarktungspotential bei der eigenen Kundschaft uberpruft werden. Erste Projekterfahrungen mit dem Lead User Verfahren zeigen, dass insbesondere die beiden ersten Projektphasen einen hohen und konzentrierten Mitarbeitereinsatz erfordern, da diese sehr rechercheintensiv sind. Der erforderliche Arbeitsaufwand kann jedoch durch Nutzung heute weitgehend allgemein zuganglicher online-Medien effizient gestaltet werden. Anhand eines Beispiels aus der Medizintechnik werden die fur ein Lead User Projekt typischen Fragestellungen und Aktivitaten illustriert und die Nutzung der online-Medien sowie deren Nutzen diskutiert.
Durcheinander – Understanding Clustering via Interactive Sonification

With Durcheinander we present a system to help understand Agglomerative Clustering processes as they appear in various datamining tasks. Durcheinander consists of a toy dataset represented by several small objects on a tabletop surface. A computer vision systems tracks their position and computes a cluster dendrogram which is sonified every time a substantial change in this dendrogram takes place. Durcheinander may be used to answer questions concerning the behavior of clustering algorithms under various conditions. We propose its usage as a didactical and explo- rative platform for single- and multi-user operation.
User interaction and performance evaluation in content-based visual information retrieval

Cette these donne une vue detaillee sur la recherche d'informations visuelles basee sur le contenu, un secteur d'etude actif dans le domaine de la vision par ordinateur. Les principaux objectifs de cette investigation sont la recherche d'images ou d'autres documents visuels dans les archives, basee sur le contenu visuel uniquement, et, en general, sans l'usage d'annotations textuelles. Les deux themes principaux sont l'interaction avec l'utilisateur et l'evaluation de performance. L'interaction avec l'utilisateur, et l'apprentissage a long terme en particulier, s'est revelee etre la cle pour obtenir de bonnes performances. L'interaction de differentes methodes ameliore les resultats des recherches de maniere significative. L'evaluation des resultats de recherche a ete largement negligee dans la recherche. Ceci est pourtant extremement important puisque seule une evaluation correcte permet de montrer les progres que certaines techniques peuvent apporter. Un benchmark completement automatise et base sur des tests effectues par de vrais utilisateurs est mis en oeuvre sur la base de langage de communication MRML.
PPA ou PPP: parite de pouvoir d'achat ou parite de pouvoir de production?

On examine dans cette etude les differents types de deflateurs qui sont utilises pour comparer les estimations des volumes de revenue et de la production nationale de divers pays. On y met de l'avant la these selon laquelle ces deflateurs doivent etre adaptes au concept specifique de revenu a l'etude. Si le concept de possibilite de depenser est utilise, on doit faire appel a un deflateur de pouvoir d'achat. Si un concept base sur la production est utilise, c'est alors un deflateur de pouvoir de production qui est de mise. Cette etude affirme que la pratique actuelle produit un deflateur hybride qui ne reussit pas a atteindre les deux objectifs lorsque les revirements des termes de l'echange sont importants et propose une solution.
Evaluación del impacto del término “MOOC” vs “elearning” en la literatura científica y de divulgación

Resumen: Dado el impacto educativo y social alcanzando por los Massive Open Online Courses y su perspectiva de crecimiento inmediato, se desarrolla un estudio bibliometrico acerca de la evolucion de este termino en la literatura cientifica y de divulgacion en contraste con el termino eLearning. A partir de los registros obtenidos en las bases de datos Google, Google Scholar, Web of Science, Scopus, Dialnet, Worldcat y EBSCO, se analizan la tendencia temporal en cuanto a la cantidad de registros en ambos terminos y su prospectiva, los principales indices bibliometricos y de exito de las publicaciones seleccionadas y los grafos de relaciones a partir de la co-ocurrencia de palabras clave. En la discusion se muestra como, mientras que el crecimiento e impacto del eLearning en la literatura se ha estancado en los ultimos anos, los Massive Open Online Courses estan en pleno auge, tanto a nivel cientifico como de divulgacion Palabras clave: MOOCs, eLearning, estudio bibliometrico, evaluacion, analisis de redes
Open-ended Spoken Language Technology: Studies on Spoken Dialogue Systems and Spoken Document Retrieval Systems

Spoken language is one of the most natural communication tools; therefore, technologies for handling spoken language by using computers have been attracting much attention. One example of such technology is a speech interface used as a powerful man-machine interface, and another is a speech mining system used as a rich information extraction tool. With advances in speech recognition techniques, some systems have reached the level of practicality, and there is a growing demand for applying spoken language technologies anywhere for any purpose. However, most spoken language systems, especially application systems such as spoken dialogue and spoken document retrieval systems, still depend on limited domain knowledge, and what the system can interpret is severely limited. Since spoken language is so familiar in our daily lives, users often expect spoken language systems to understand everything the users can. Therefore, there is a large gap between what current systems can handle and what users expect. It is important to narrow this gap in spoken language technologies to benefit a wide range of users. Our ultimate goal is to develop open-ended spoken language technologies, which can handle a broad range of utterances by freely extending their knowledge resources. For achieving this goal, we tackled two technical problems; (i) spoken language analysis with little or no domain knowledge as a basis for handling arbitrary topics and (ii) integration of knowledge on an arbitrary number of domains. For spoken language systems, speech recognition errors are inevitable and need to be considered in each layer of a system. Therefore, to solve these problems, we investigated two target systems, spoken dialogue and spoken document retrieval. A spoken dialogue system is a computer system that can understand and respond to a user’s spoken requests. We consider it as a representative system that treats speech as a man-machine interface. A spoken document retrieval system can find specific recordings from input queries. We consider it as a representative system that treats speech as an information source. We developed open-ended technologies for both systems by solving problems (i) and (ii).
Computer-Assisted Image Analysis Cytology

Inevitably, reading is one of the requirements to be undergone. To improve the performance and quality, someone needs to have something new every day. It will suggest you to have more inspirations, then. However, the needs of inspirations will make you searching for some sources. Even from the other people experience, internet, and many books. Books and internet are the recommended media to help you improving your quality and performance.
La cibermetría en la recuperación de información en el Web

The exponential growth of web and distributed data characteristics, high volatility, unstructured data, redundant and highly heterogeneous, have introduced new problems in information retrieval processes. Therefore it is necessary to open new avenue of research that allow us to obtain good levels of accuracy. The papers are based on exploiting the hypertext features of the site is reaching great fame. The cybermetrics is providing many options for working with links and is offering some interesting options at this time, and much of the techniques used in the same may be useful in the processes of information retrieval on the web.
Handbook of neural activity measurement

Neuroscientists employ many different techniques to observe the activity of the brain, from single-channel recording to functional imaging (fMRI). Many practical books explain how to use these techniques, but in order to extract meaningful information from the results it is necessary to understand the physical and mathematical principles underlying each measurement. This book covers an exhaustive range of techniques, with each chapter focusing on one in particular. Each author, a leading expert, explains exactly which quantity is being measured, the underlying principles at work, and most importantly the precise relationship between the signals measured and neural activity. The book is an important reference for neuroscientists who use these techniques in their own experimental protocols and need to interpret their results precisely; for computational neuroscientists who use such experimental results in their models; and for scientists who want to develop new measurement techniques or enhance existing ones.
Rotating objects using quaternions

Last year may go down in history as The Year of the Hardware Acceleration. Much of the work rasterizing and texture-mapping polygons was off-loaded to dedicated hardware. As a result, we game developers now have a lot of CPU cycles to spare for physics simulation and other features. Some of those extra cycles can be applied to tasks such as smoothing rotations and animations, thanks to quaternions.
A Tutorial Introduction to PVS

This document provides an introductory example, a tutorial, and a compact reference to the PVS veri cation system. It is intended to provide enough information to get you started using PVS, and to help you appreciate the capabilities of the system and the purposes for which it is suitable. Dave Stringer-Calvert provided valuable comments on earlier versions of this tutorial, and also checked the speci cations and proofs appearing here. Preparation of this tutorial was partially funded by NASA Langley Research Center under Contract NAS1-18969, and by the Advanced Research Projects Agency through NASA Ames Research Center NASA-NAG-2-891 (Arpa order A721) to Stanford Unversity.
Three-Dimensional Data Recovery Using Image-Based Modeling

Extraction of a three-dimensional model from a set of two-dimensional projections is a well-known problem of contemporary computer science. Termed image-based modeling, solutions to this problem have a number of practical applications ranging from virtual tours and image recognition to generation of physical models from image data. However, this problem remains the subject of active research as it has not yet been solved in the general case. Although this general case has proven very challenging, there are certain special cases where a satisfactory solution can be achieved with minimal human intervention. The following report describes our approach to a general solution to the problem of inferring geometric information from a photographic image. A detailed description of our algorithm and the method of implementation are provided along with sample results demonstrating the capabilities of this approach.
Machine learning and statistics: a matter of perspective

Information has become an important commercial commodity–indeed, possibly the most important product of the future. While we have well-developed technologies to store data, the analysis to extract information is time-consuming and requires skilled human intervention. Machine learning algorithms augment statistical analysis by providing mechanisms that automate the information discovery process. These algorithms also tend to be more accessible to end-users and domain experts. The two analysis methods are converging, and the fields have much to offer each other.
Enhetlighet och/eller profilering i det svenska högskolelandskapet?

Genom hogskolereformen 1977 fordes nastan all postgymnasial utbildning in i en enhetlig sammanhallen hogskoleorganisation. Den enhetliga strukturen svarade val mot datidens socioekonomiska och utbildningspolitiska stra-vanden om okad tillganglighet till hogre utbildning och minskning av de status-skillnader som tidigare funnits mellan olika typer av postgymnasiala utbildningar. Genom en serie senare reformeringar har larosatena numera en betydande autonomi for att mota de krav som i dag stalls pa dem att profilera sig och konkurrera och/eller samverka med varandra for att darigenom kunna havda sig och Sverige pa den internationella kunskapsmarknaden. Dessa profilerings- och konkurrenskrav rim-mar dock daligt med den strukturella enhetligheten fran 1977, som formellt fort-farande galler.
Cache Optimizations for the Lattice Boltzmann Method in 2D

The lattice Boltzmann Method (LBM) has, in recent years, gained wide acceptance as an efficient alternative to simulate flows in complex geometries as opposed to using algorithms that numerically solve the Navier-Stokes equation. The lattice Boltzmann method divides space into a regular grid, where each grid site determines the local behavior of the fluid. For algorithms working on regular grids, execution speed is often limited by access to the main memory. However, the speed of computer processors is currently increasing much faster than this memory latency decreases. Thus, modern computer architectures employ memory hierarchies based on caches that are 30 to 40 times faster than the main memory, to mitigate this effect. It has been shown that many algorithms working on regular grids can be optimized in terms of spatial and temporal locality, to efficiently use these memory hierarchies. This thesis will investigate the transferability of these techniques to the lattice Boltzmann method using the C++ programming language and it will provide quantitative values for the gain in performance.
Multi-sensor architecture for human-centered smart environments, A

In a multi-sensory environment, supported with embedded computer technology, the system can capture and interpret what the users are doing and assist or collaborate with the users in real-time. Such an environment should be aware of users intentions, tasks and feelings, and allow people to interact with the environment in a natural way: by moving, pointing and gesturing. In this paper we propose an architecture for such a smart environment consisting of three modules.
Parsing Sanskrit texts: Some relation specific issues

Building a sentential parser following a dependency framework needs a well defined set of relations. In case of Sanskrit, various texts on Śābdabodha theories discuss such relations. These relations are critically examined from the point of view of feasibility of building a rule based parser. We propose an intermediate parse with nice computational properties of a tree structure and then propose another layer to make this tree structure more useful for information retrieval and user understanding.
Solving Combinatorial Optimization Problems Using Genetic Algorithms and Ant Colony Optimization

Emergency departments have repeating 24-hour cycles of non-stationary Poisson arrivals and high levels of service time variation. The problem is to find a shift schedule that considers queuing effects and minimizes average patient waiting time and maximizes physicians’ shift preference subject to constraints on shift start times, shift durations and total physician hours available per day. An approach that utilizes a genetic algorithm and discrete event simulation to solve the physician scheduling problem in a hospital is proposed. The approach is tested on real world datasets for physician schedules.
Creating and validating a large image database for METTREC

The National Institute of Standards and Technology (NIST) is in the process of setting up a new series of conferences named the Metadata Text Retrieval Conferences (METTREC). It will focus on evaluating document conversion using optical character recognition (OCR), and information retrieval (IR) technologies. Evaluations will be designed to investigate the impact of machine recognition errors upon information retrieval and to determine what interfaces are appropriate to integrate the two technologies. To implement this conference, we require databases that can be used for conference evaluations and has chosen the Federal Register to be the initial document source. It is a large, complete set of documents containing metadata that will allow quantitative evaluation of recognition and retrieval technologies. This paper describes the activities associated with scanning the Federal Register and validating the document images within the database. The process of image validation includes translating filenames, assuring image integrity, and verifying correct page sequences. In order to reduce the cost of validation, we minimized human resource expenditure by exploiting OCR and high-speed visual adjudication from images by an operator. This process minimizes the expensive handling of paper to validate document image collections.
End-to-end Network Monitoring Infrastructure

The capability of dynamically monitoring the performance of the communication infrastructure is one of the emerging requirements for a Grid. We claim that such a capability is in fact orthogonal to the more popular collection of data for scheduling and diagnosis, which needs large storage and indexing capabilities, but may disregard real-time performance issues. We discuss such claim analyzing the gLite NPM architecture, and we describe a novel network monitoring infrastructure specifically designed for demand driven monitoring, named gd2, that can be potentially integrated in the gLite framework. We describe a Java implementation of gd2 on a virtual testbed.
Learning How to Manage Projects: exploring the situational context

This paper presents an account of how project management practitioners learn, how they determine what they want to learn, and suggests some future directions for their knowledge journey. Two similar teaching approaches will be discussed that are currently used at undergraduate and post graduate level in an Australian University. The approaches used to embed the formal concepts taught in class include field work and reflective practice. This will provide a view of the formal structure in which learning takes place and the informal way that explicit knowledge is converted to tacit knowledge. A formative research study into project management research directions undertaken in 2003 provides a framework for the knowledge required by practitioners to further the discipline of project management.
Handbook of Granular Computing

Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest in the topic as it begins to play a key role in bioinformatics, e-commerce, machine learning, security, data mining and wireless mobile computing when it comes to the issues of effectiveness, robustness and uncertainty. The Handbook of Granular Computing offers a comprehensive reference source for the granular computing community, edited by and with contributions from leading experts in the field. Includes chapters covering the foundations of granular computing, interval analysis and fuzzy set theory; hybrid methods and models of granular computing; and applications and case studies. Divided into 5 sections: Preliminaries, Fundamentals, Methodology and Algorithms, Development of Hybrid Models and Applications and Case Studies. Presents the flow of ideas in a systematic, well-organized manner, starting with the concepts and motivation and proceeding to detailed design that materializes in specific algorithms, applications and case studies. Provides the reader with a self-contained reference that includes all pre-requisite knowledge, augmented with step-by-step explanations of more advanced concepts. The Handbook of Granular Computing represents a significant and valuable contribution to the literature and will appeal to a broad audience including researchers, students and practitioners in the fields of Computational Intelligence, pattern recognition, fuzzy sets and neural networks, system modelling, operations research and bioinformatics.
A Novel Index to Compare the Representation Quality of Objects Approximated with Spheres

Practical collision detection problems require very fast algorithms. The quality of the object representation plays a key role in the efficiency of these algorithms. In this paper a new index is presented which makes it possible to compare in terms of quality of representation different algorithms that approximate an object by means of spheres. Comparative results with other indexes are provided.