Miracle-dz/UniFAR-FTUs huggingface dataset:
Augmented Groove: Collaborative Jamming in Augmented Reality

Augmented Groove is a musical interface that explores use of augmented reality, 3D interfaces, and physical, tangible interaction for conducting multimedia musical performance. Users can play music together, with or without traditional music instruments, simply by picking and manipulating physical cards on a table. The physical movements of the cards are mapped to changes in musical elements such as timbre, pitch, rhythm, distortion, and reverb. At the same time, users wearing lightweight head-mounted displays can see 3D virtual images attached to the cards. The shapes, color, and dynamics of the virtual images reflect aspects of the music. In this augmented reality environment, users can see the physical world, virtual objects, and each other, so several users can gather around the mixing table and “jam” together, passing sequences to each other in the same manner in which we pass everyday objects from person to person. In a sense, the music becomes a physical, tangible object, something that can be touched and seen as part of the physical environment.
A social network-based recommender system

For more than a decade, recommender systems have been proposed as a key tool to overcome information overload, and many algorithms and systems have been developed. Despite all these efforts, recommender systems still face many challenges—such as improving prediction accuracy, data sparsity, and cold-start issues. On the other hand, the recent emergence of online social networks provides us with an unprecedented large amount of information regarding user behavior and friend interactions. Especially, homophily effects among friends have demonstrated their importance to product marketing, and marketing strategies that utilize homophily have achieved great success. However, such information has not yet been considered in recommender systems. In this dissertation we propose a new paradigm of recommender systems which can significantly improve performance by utilizing information in social networks. In particular, we address the following challenging issues in building a social network-based recommender system. 1) We investigate the existence of homophily among friends in rating items using statistical analyses on a dataset crawled from a real online social network, Yelp.com. 2) To understand the role of social relationships in a social network-based recommender system, we develop a Bayesian network-based recommender system (SNRS-BN) based on a simplified homogeneous social network, and study the performance of SNRS-BN under different types of social relationships. 3) We develop a social network-based recommender system (SNRS) which utilizes more information in social network, including user preferences, an item's likability, and homophily effects among friends, to provide better recommendations. An iterative classification has been adopted in this system to incorporate homophily even from friends at multiple hops away. The performance improvements of SNRS are validated through experiments on the Yelp dataset in terms of both prediction accuracy and coverage over traditional recommender systems. 4) To overcome the problems of heterogeneities in social networks, we propose to select relevant friends for inference based on the semantics in fine-grained user ratings on their buying decisions. An experiment is carried out in a graduate student class to validate performance improvements from such semantic filtering. 5) We discuss the trust issues caused by malicious users and users with unreliable domain knowledge in SNRS. In particular, for the case of users with unreliable domain knowledge, we propose to estimate homophily more robustly by relaxing the item category information according to item taxonomy. Future work in this direction will be desirable.
A Hybrid Web Personalization Model Based on Site Connectivity

Web usage mining has been used effectively as an underlying mechanism for Web personalization and recommender systems. A variety of recommendation frameworks have been proposed, including some based on non-sequential models, such as association rules and clusters, and some based on sequential models, such as sequential or navigational patterns. Our recent studies have suggested that the structural characteristics of Web sites, such as the site topology and the degree of connectivity, have a significant impact on the relative performance of recommendation models based on association rules, contiguous and non-contiguous sequential patterns. In this paper, we present a framework for a hybrid Web personalization system that can intelligently switch among different recommendation models, based on the degree of connectivity and the current location of the user within the site. We have conducted a detailed evaluation based on real Web usage data from three sites with different structural characteristics. Our results show that the hybrid system selects less constrained models such as frequent itemsets when the user is navigating portions of the site with a higher degree of connectivity, while sequential recommendation models are chosen for deeper navigational depths and lower degrees of connectivity. The comparative evaluation also indicates that the overall performance of hybrid system in terms of precision and coverage is better than the recommendation systems based on any of the individual models.
Analyzing 2D Structure Images of Piezoelectric Ceramics Using ImageJ

An image analysis processing method for the measurement of structure of piezoelectric ceramics from 2D SEM images using ImageJ program is studied. Lots of parameter of structure was mentioned in ImageJ, however in this study, we concentrate on studying the particle size distribution and shape analyzing. The results show that the developed method can be used as a practical tool to estimate the physic structure of materials.
Scalable sensor localization algorithms for wireless sensor networks

An adaptive rule-based algorithm, SpaseLoc, is described to solve localization problems for ad hoc wireless sensor networks. A large problem is solved as a sequence of very small subproblems, each of which is solved by semidefinite programming relaxation of geometric optimization model. The subproblems are generated according to a set of sensor/anchor selection rules and a priority list. Computational results compared with existing approaches show that the SpaseLoc algorithm scales well and provides excellent, positioning accuracy. A dynamic version of the SpaseLoc method is developed for estimating proving sensors locations in a real-time environment. The method uses dynamic distance measurement updates among sensors, and utilizes SpaseLoc for static sensor localization. Further computational results are presented, along with an application to bus transit systems. Ways to deploy sensor localization algorithms in clustered distributed environments are also studied, permitting application to arbitrarily large networks. In addition, we extend the algorithm to solving sensor localizations in 3D space. A preprocessor is developed to enable SpaseLoc: for localization of networks without absolute position information. * *Joint research conducted in the Dept of Management Science and Engineering, Stanford University.
Dagstuhl-Workshop MBEES: Modellbasierte Entwicklung eingebetteter Systeme I, Schloss Dagstuhl, Germany, 10.-14. Januar 2005, Tagungsband Modellbasierte Entwicklung eingebetteter Systeme

Advanced mechatronic systems of the future are expected to behave more intelligently than today by building communities of autonomous agents which exploit local and global networking to enhance their behavior and to realize otherwise not possible functionality. While engineering of mechatronic systems and software engineering for embedded systems, multi-agent systems, and distributed systems are established areas, no solution for the systematic development of the outlined future generation of intelligent, distributed, embedded systems exists today. This is not simply a matter of composing the solutions developed for each of these area as some of their requirements are in conflict: E.g., flexibility and autonomy are to some extent at odds with predictability and safety. We propose to address this challenge by a modeldriven development approach which includes several advanced analysis and synthesis techniques. A restricted high level UML model serves as a basis for rigorous validation and verification to address the correctness and safety issues. Analyzing the high level models rather than the code is justified by synthesis techniques, which guarantee that all properties of the high level models also hold for the implementation.
About the Processing of Division Queries Addressed to Possibilistic Databases

When identifying found bodies at the scene of a large-scale disaster, a technique for fast and cheap identification is very useful. Many techniques have been proposed in the past for this purpose. The method developed here allows flexible matching of ante mortem and post mortem pictures taken of the human ear and faces a challenge left unhandled before: the low quality control on the pictures of missing persons. As these pictures can be unsharp and out of profile, the comparison becomes more difficult and a flexible approach is required.
HLFSD: Delivering Email to Your $HOME: Delivering Email to Your $HOME

We consider the problem of enabling users to access their mailbox files from any host on our local network, and not only on one designated "home machine". We require a solution which will not introduce any new single points of failure, force us to modify mail transfer agents and user agents, or require changes to the operating system kernels. In other words, minimize the amount of work needed by system-administrators and users. Our solution is to deliver mail into the users' home directories, which are exported via NFS[20, 25] to all of the machines on our network. We wrote a small user-level NFS server implementing a single symbolic link that references the home directory of a user, either the one who accessed it, or by name, with a fallback reference in case of failures. This enables electronic mail to be delivered directly into the user's home directory, which is already accessible from any machine on the network. Although we have used our server primarily for mail delivery redirection, it can be used to redirect spooled faxes, access to /tmp, etc.
COMPUTING RESOURCES IN FLEXIBLE RADIO ENVIRONMENTS

The present invention provides a method of manufacturing an optical fiber preform having the steps of disposing a rod member made of a silica-based material within a cavity of a mold, followed by loading a molding material within the mold cavity, and applying pressure to the mold from the outside to form a porous layer on the surface of the rod member and, thus, to obtain a porous preform, wherein at least one end portion of the rod member extends outside the mold cavity in the step of applying pressure to the mold. The particular method permits manufacturing a high quality porous preform free from splits or cracks, making it possible to obtain a high quality optical fiber preform free from residual bubbles.
Reactive Collision Avoidance of UAVs with Stereovision Camera Sensors using UKF

Abstract An effective reactive collision avoidance algorithm is presented in this paper for Unmanned Ariel Vehicles(UAVs) based on stereovision sensing of the obstacles. Vision sensors detection range is limited and state measurements are noisy. Unscented Kalman Filter(UKF) based sensor state estimation is proposed to extract the accurate information from the sensors through a geometrical formulation. This formulation is capable of estimating the range information of the obstacle. The first order differential of the nonlinear sensor dynamics is used to compute obstacle's velocity estimate. In the case of imminent collision, UAV is guided towards an 'Aiming point' which is computed for point obstacle with safety ball and using the collision cone approach. The velocity vector of the UAV is steered away towards this point by using 'Differential Geometry Guidance'(DGG). Simulations show that this guidance strategy is quite effective in avoiding popup obstacles within a very short time and hence can be useful for reactive collision avoidance.
The grammar and processing of order and dependency : a categorial approach

This thesis presents accounts of a range of linguistic phenomena in an extended categorial framework, and develops proposals for processing grammars set within this framework. Linguistic phenomena whose treatment we address include word order, grammatical relations and obliqueness, extraction and island constraints, and binding. The work is set within a exible categorial framework which is a version of the Lambek calculus (Lambek, 1958) extended by the inclusion of additional type-forming operators whose logical behaviour allows for the characterization of some aspect of linguistic phenomena. We begin with the treatment of extraction phenomena and island constraints. An account is developed in which there are many interrelated notions of boundary, and where the sensitivity of any syntactic process to a particular class of boundaries can be addressed within the grammar. We next present a new categorial treatment of word order which factors apart the specication of the order of a head's complements from the position of the head relative to them. This move has the advantage of allowing the incorporation of a treatment of grammatical relations and obliqueness, as well as providing for the treatment of Verb Second phenomena in Germanic languages. A categorial treatment of binding is then presented which integrates the preceding proposals of the thesis, handling command constraints on binding in terms of relative obliqueness and locality constraints using the account of linguistic boundaries. Attention is given to the treatment of long distance re exivization in Icelandic, a phenomenon of interest because of its unusual locality behaviour. Finally, a method is developed for parsing Lambek calculus grammars which avoids the e ciency problems presented by the occurrence of multiple equivalent proofs. The method involves developing a notion of normal form proof and adapting the parsing method to ensure that only normal form proofs are constructed. iii
Design considerations of an interactive robotic agent for public libraries

The role of public libraries has long been recognized, rendering them a timeless offered form of public service. Users of a public library should have easy access to catalogs and full text of printed and electronic versions of books, magazines, and periodicals, as well as to multimedia databases. Every day, most public libraries are in service for several hours, thus computer-based library service applications provide a valuable service supplement. In this study, a robotic agent which guides users in libraries is proposed. The robotic agent is equipped with sound acquisition and reproduction chains and is capable of understanding some specific commands and guiding the users. The agent is currently able to understand commands and respond in English. Therefore, it may be useful for public libraries visited or remotely used by foreign, English speaking, users. Future work consists of the implementation of language packages for Turkish and the evaluation of field tests that will be held at the library and documentation center of Trakya University, Edirne, Turkey.
A Textbook of Neuroanatomy

Preface. 1. Introduction to the Nervous System. 2. Development of the Nervous System. 3. Histophysiology of the Nervous Sytem. 4. Neurotransmitter Substances. 5. Spinal Cord. 6. Gross Anatomy of the Brain. 7. The Meninges and Cerebrospinal Fluid. 8. Vascular Supply of the Central Nervous System. 9. The Autonomic Nervous System. 10. The Ascending Sensory Pathways. 11. The Motor Cortex and Descending Motor Pathways. 12. The Basal Ganglia. 13. The Cerebellum. 14. The Reticular Formation. 15. The Cranial Nerves. 16. The Visual System. 17. The Auditory System. 18. The Vestibular System. 19. The Olfactory System. 20. The Limbic System. 21. The Hypothalamus. 22. The Thalamus. 23. The Cerebral Cortex. Index
Automatic Adaptation of Sound Analysis and Synthesis

In Time-Frequency Analysis, adaptivity is the possibility to conceive representations and operators whose characteristics can be modeled according to their input. In this work, we look for methods providing for a local variation of the time-frequency resolution for sound analysis and re-synthesis. The first and fundamental objective is thus the formal definition of mathematical models whose interpretation leads to theoretical and algorithmic methods for adaptive sound analysis. The second objective is to make the adaptation automatic; we establish criteria to define the best local time-frequency resolution, with the optimization of appropriate sparsity measures. To be able to exploit adaptivity in spectral sound processing, we then introduce efficient re-synthesis methods based on analyses with varying resolution, designed to preserve and improve the existing sound transformation techniques. Our main assumption is that algorithms based on adaptive representations will help to establish a generalization and simplification for the application of signal processing methods that today still require expert knowledge. In particular, the need to provide manual low level configuration is a major limitation for the use of advanced signal processing methods by large communities. The possibility to dispose of an automatic time-frequency resolution drastically limits the parameters to set, without affecting, and even ameliorating, the treatment quality: the result is an improvement of the user experience, even with high-quality sound processing techniques, like transposition and time-stretch.
Reinforcement learning with dynamic covering of state-action space: partitioning Q-learning

An adjustable X-ray collimator is disclosed which has two web assemblies. Each web assembly has a pair of spaced and connected webs which form a continuous loop reaved over a pair of rollers. The assemblies are positioned near and parallel with one another with the axes of the rollers on one assembly being perpendicular to the other so that one assembly defines the sides and the other assembly the ends of a rectangular X-ray beam opening. The size of the opening is adjusted by rotating the rollers so as to move the interconnected webs to adjust the amount of space between ends of the webs.
A Consent-based Workflow System for Healthcare Systems

In this paper, we describe a new framework for healthcare systems where patients are able to control the disclosure of their medical data. In our framework, the patient's consent has a pivotal role in granting or removing access rights to subjects accessing patient's medical data. Depending on the context in which the access is being executed, different consent policies can be applied. Context is expressed in terms of workflows. The execution of a task in a given workflow carries the necessary information to infer whether the consent can be implicitly retrieved or should be explicitly requested from a patient. However, patients are always able to enforce their own decisions and withdraw consent if necessary. Additionally, the use of workflows enables us to apply the need-to-know principle. Even when the patient's consent is obtained, a subject should access medical data only if it is required by the actual situation. For example, if the subject is assigned to the execution of a medical diagnosis workflow requiring access to the patient's medical record. We also provide a complex medical case study to highlight the design principles behind our framework. Finally, the implementation of the framework is outlined.
A comparison of automated keyphrase extraction techniquesand of automatic evaluation vs. human evaluation

Keyphrases are added to documents to help identify the areas of interest they contain. However, in a significant proportion of papers author selected keyphrases are not appropriate for the document they accompany: for instance, they can be classificatory rather than explanatory, or they are not updated when the focus of the paper changes. As such, automated methods for improving the use of keyphrases are needed, and various methods have been published. However, each method was evaluated using a different corpus, typically one relevant to the field of study of the method’s authors. This not only makes it difficult to incorporate the useful elements of algorithms in future work, but also makes comparing the results of each method inefficient and ineffective. This paper describes the work undertaken to compare five methods across a common baseline of corpora. The methods chosen were Term Frequency, Inverse Document Frequency, the C-Value, the NC-Value, and a Synonym based approach. These methods were analysed to evaluate performance and quality of results, and to provide a future benchmark. It is shown that Term Frequency and Inverse Document Frequency were the best algorithms, with the Synonym approach following them. Following these findings, a study was undertaken into the value of using human evaluators to judge the outputs. The Synonym method was compared to the original author keyphrases of the Reuters’ News Corpus. The findings show that authors of Reuters’ news articles provide good keyphrases but that more often than not they do not provide any keyphrases.
Real-time multiple object tracking

Multiple object tracking consists of detecting and identifying objects in video. In some applications, such as robotics and surveillance, it is desired that the tracking is performed in real-time. This poses a challenge in that it requires the algorithm to run as fast as the frame-rate of the video. Today’s top performing tracking methods run at only a few frames per second, and can thus not be used in real-time. Further, when determining the speed of the tracker, it is common to not include the time it takes to detect objects. We argue that this way of measuring speed is not relevant for robotics or embedded systems, where the detecting of objects is done on the same machine as the tracking. We propose that one way of running a method in real-time is to not look at every frame, but skip frames to make the video have the same frame-rate as the tracking method. However, we believe that this will lead to decreased performance. In this project, we implement a multiple object tracker, following the tracking-by-detection paradigm, as an extension of an existing method. It works by modelling the movement of objects by solving the filtering problem, and associating detections with predicted new locations in new frames using the Hungarian algorithm. Three different similarity measures are used, which use the location and shape of the bounding boxes. Compared to other trackers on the MOTChallenge leaderboard, our method, referred to as C++SORT, is the fastest non-anonymous submission, while also achieving decent score on other metrics. By running our model on the Okutama-Action dataset, sampled at different frame-rates, we show that the performance is greatly reduced when running the model – including detecting objects – in real-time. In most metrics, the score is reduced by 50%, but in certain cases as much as 90%. We argue that this indicates that other, slower methods could not be used for tracking in real-time, but that more research is required specifically on this.