Miracle-dz/UniFAR-FTUs huggingface dataset:
UvA-DARE ( Digital Academic Repository ) Hooked : A Game for Discovering What Makes Music

Although there has been some empirical research on earworms, songs that become caught and replayed in one’s memory over and over again, there has been surprisingly little empirical research on the more general concept of the musical hook, the most salient moment in a piece of music, or the even more general concept of what may make music ‘catchy’. Almost by definition, people like catchy music, and thus this question is a natural candidate for approaching with ‘gamification’. We present the design of Hooked, a game we are using to study musical catchiness, as well as the theories underlying its design and the results of a pilot study we undertook to check its scientific validity. We found significant di↵erences in time to recall pieces of music across di↵erent segments, identified parameters for making recall tasks more or less challenging, and found that players are not as reliable as one might expect at predicting their own recall performance.
Fast communication A frequency-domain double-talk detector based on a normalized cross-correlation vector

A key component for hands-free, full-duplex, communication technology is the echo canceler. An echo canceler consists primarily ofan adaptive 4lter and a control device called the double-talk detector. We derive a test statistic based on a normalized cross-correlation vector for the multichannel frequency-domain adaptive algorithm. The advantages ofthis approach are: low computational complexity, simplicity ofimplementation, and better perf ormance than the classical Geigel algorithm. 2001 Elsevier Science B.V. All rights reserved.
AIS Electronic

Knowing about communication of specific issues in social media has become increasingly important for the reactive and proactive stakeholder-communication of enterprises. Tools have been designed to monitor social media sites and to aggregate data of discussions in social media. However, these tools do not consider the dynamics of discussions and are not able to reflect sentiments within these discussions. In our contribution, we address these aspects by analyzing a data set of around 730,000 Tweets published in a time frame of 19 weeks. Within this data set, we analyzed those Tweets dealing with the corporate crisis of Toyota in 2010. We classified sentiments by using a linguistic approach. In this context, we identified and investigated specific stages of communication (“quiet stages” and “peaks”). Additionally, our study concentrates on the sentiments found in Tweets of the ten most active participants of the discussion.
Birkbeck ePrints: an open access repository of the research output of Birkbeck College

—This paper proposes an approach that integrates technical concerns with user perceptual considerations for intelligent decision making in the construction of tailor-made multimedia communication protocols. Thus, the proposed approach, based on multicriteria decision making (MDM), incorporates not only classical networking considerations, but, indeed, user preferences as well. Furthermore, in keeping with the task-dependent nature consistently identiﬁed in multimedia scenarios, the suggested communication protocols also take into account the type of multimedia application that they are transporting. Lastly, this approach also opens the possibility for such protocols to dynamically adapt based on a changing operating environment and user’s preferences.
Type-Safe Communication in Java with Session Types

This paper demonstrates the impact of integrating session types for communication behaviour into object-oriented languages, through their implementation in a distributed Java. Session types abstract a potentially unbounded structured sequence of communications in an easy-to-read type syntax, and guarantee the absence of communication errors through static type-checking. The introduction of session types not only contributes to clear and statically correct communication programs, but also enables the efficient, transparent delegation of an ongoing conversation and leads to the potential for significant performance improvement. To our knowledge, this is the first practical implementation of higher-order session types (delegation) with subtyping for an object-oriented language. The use of session types enables the decoupling of communication abstraction from its implementation mediated by type information: the runtime can encapsulate low-level communication mechanisms for their effective exploitation, with minimal overhead. The benchmark results show our implementation outperforms RMI, the standard API for typed inter-process communication.
Three-dimensional scene flow

Just as optical flow is the two-dimensional motion of points in an image, scene flow is the three-dimensional motion of points in the world. The fundamental difficulty with optical flow is that only the normal flow can be computed directly from the image measurements, without some form of smoothing or regularization. In this paper, we begin by showing that the same fundamental limitation applies to scene flow; however, many cameras are used to image the scene. There are then two choices when computing scene flow: 1) perform the regularization in the images or 2) perform the regularization on the surface of the object in the scene. In this paper, we choose to compute scene flow using regularization in the images. We describe three algorithms, the first two for computing scene flow from optical flows and the third for constraining scene structure from the inconsistencies in multiple optical flows.
The Hedge Algorithm for Metasearch at TREC 2007

Aslam, Pavlu, and Savell [3] introduced the Hedge algorithm for metasearch which effectively combines the ranked lists of documents returned by multiple retrieval systems in response to a given query. It has been demonstrated that the Hedge algorithm is an effective technique for metasearch, often significantly exceeding the performance of standard metasearch and IR techniques over small TREC collections. In this work, we explore the effectiveness of Hedge as an automatic metasearch engine over the much larger GOV2 collection on about 1700 topics as part of the Million Query Track of TREC 2007.
The Eclectic Quadrant of Rule Based System Verification : Work Grounded in Verification of Fuzzy Rule Bases Acknowledgement

In this paper, we used a research approach based on grounded theory in order to classify methods proposed in literature that try to extend the verification of classical rule bases to the case of fuzzy knowledge modeling. Within this area of verification we identify two dual lines of thought respectively leading to what is termed respectively static and dynamic anomaly detection methods. The major outcome of the confrontation of both approaches is that their results, most often stated in terms of necessary and/or sufficient conditions are difficult to reconcile. This paper addresses precisely this issue by the construction of a theoretical framework, which enables to effectively evaluate the results of both static and dynamic verification theories. Things essentially go wrong when in the quest for a good affinity, matching or similarity measure, one neglects to take into account the effect of the implication operator, an issue that rises above and beyond the fuzzy setting that initiated the research. The findings can easily be generalized to verification issues in any knowledge coding setting.
Fast Dimensional Analysis for Root Cause Investigation in a Large-Scale Service Environment

Root cause analysis in a large-scale production environment is challenging due to the complexity and scale of the services running across global data centers. It is often difficult to review the logs jointly for understanding production issues given the distributed nature of the system. Additionally, there could easily be millions of entities, each described by hundreds of features. In this paper we present a fast dimensional analysis framework that automates the root cause analysis on structured logs with improved scalability. We first explore item-sets, i.e. combinations of feature values, that could identify groups of samples with sufficient support for the target failures using the Apriori algorithm and a subsequent improvement, FP-Growth. These algorithms were designed for frequent item-set mining and association rule learning over transactional databases. After applying them on structured logs, we select the item-sets that are most unique to the target failures based on lift. We propose pre-processing steps with the use of a large-scale real-time database and post-processing techniques and parallelism to further speed up the analysis and improve interpretability, and demonstrate that such optimization is necessary for handling large- scale production datasets. We have successfully rolled out this approach for root cause investigation purposes within Facebook's infrastructure. We also present the setup and results from multiple production use cases in this paper.
A Two-stage Online Handwritten Chinese Character Segmentation Algorithm Based on Dynamic Programming

In this paper, an online handwritten Chinese character segmentation method is proposed. It is based on a dynamic programming algorithm, which uses geometrical features extracted from the handwritten strokes. The algorithm is carried out in two stages: pre-segmentation and recognition-based segmentation. The experimental results on 2363 sentences, representing nearly 70,000 characters and more than 370,000 strokes, show that the pre-segmentation stage keeps incorrect segmentation rate below 1% with an over-segmentation rate limited to 11%. The final correct segmentation rate is about 88%, without using any language model, indicating the effectiveness of proposed approach.
A Ubiquitous Interactive Computing Model applied to the Natural and Cultural Heritage of the Montsec Area –

2 Presentation: The Computerization and networking of All Things – Friedemann Mattern, Manuel Ortega Cantero and Jesús Lorés Vidal 3 The Vision and Technical Foundations of Ubiquitous Computing – Friedemann Mattern We illustrate the vision of Mark Weiser, the visionary behind ubiquitous computing, and describe its technical foundation and current trends. We also give a brief overview of its implications for privacy and outline possible applications. 7 The Dreaming – Jakub Wejchert Vision and underlying motivation can play an important role in research – yet these aspects are often overlooked. Using the disappearing computer initiative as a starting point, this article describes how the germ of a vision was used as the basis for a call for research proposals in the area. 12 Where Computation and Artefacts Meet – Hans-Werner Gellersen Ubiquitous computing is a vision in search of a fundamentally new quality of computer use, approached by deep interconnection of computation with the designed environments of modern life. 17 AULA: A Ubiquitous Language Teaching System – Manuel Ortega Cantero, Maximiliano Paredes Velasco, Miguel Ángel Redondo Duque, Pedro Pablo Sánchez Villalón, Crescencio Bravo Santos, José Bravo Rodríguez A ubiquitous system being developed with the aim of studying ways and means of bringing new technologies into the classroom. 23 A Ubiquitous Interactive Computing Model applied to the Natural and Cultural Heritage of the Montsec Area – Montserrat Sendín, Jesús Lorés, Carles Aguiló, Alexandra Balaguer The mountains of Montsec is an area of outstanding geological, historical, paleontological and scenic wealth. It is regarded as a truly natural laboratory. The application of the model presented here will help to conserve and make people more aware of the park’s natural resources and cultural heritage, by turning the area into an “interactive space”. 27 Pervasive and Mobile Computing Middleware – Klaus Rindtorff, Martin Welsch Internet access is no longer primarily a domain of browsers based on desktop PCs. The number of non-PC mobile access devices is fast outgrowing that of traditional PC based access devices. How can existing content as well as new services be delivered to all kinds of mobile Internet devices? 32 A World Model for Location-Aware Systems – Matthias Grossmann, Alexander Leonhardi, Bernhard Mitschang, Kurt Rothermel Advanced location-aware applications require a detailed model of the real world. We describe the characteristics of the Augmented World Model and the architecture of the Nexus platform. 36 A Comparative Study of Communication Infrastructures for the Implementation of Ubiquitous Computing – Pablo Haya, Xavier Alamán and Germán Montoro This article focuses on communication networks that could be used in a ubiquitous computing environment. These networks are heterogeneous due to the variety of device types that can be connected and the different kinds of traffic that can be transmitted. Ubiquitous Computing Guest Editors: Friedemann Mattern, Manuel Ortega Cantero and Jesús Lorés Vidal
Joint Estimation of Correspondence and Motion Using Global Rigidity and Local Descriptors

In this thesis we present a new approach to the modeling of the correspondence problem for rigid and Lambertian objects within a Structure from Motion framework. Our goal is to solve for correspondences and camera motion altogether, using only a pair of images with no additional information. The approach presented takes as input sets of point coordinates, specifically a set of points in the first image, each with a set of correspondence candidates in the second image presenting the same intensity value. With this data, we estimate motion between both cameras and select a number of most likely candidates for each point in the first image (which, in particular, can be the case of 1-to-1 correspondence). To fulfill this goal, our work merges information from brightness cues available in image points extracted using local descriptor algorithms with a model that constrains point trajectories due to the rigidity of the object. The use of both these constraints allows us to formulate the estimation of correspondences, motion and depth within a single optimization problem. We describe the set of possible motions as a Stiefel manifold, whose properties allow us to solve the optimization problem by minimizing a cost function over a two-parameter search grid The resulting algorithm — Correspondence Estimation using Rigidity and local Descriptors, or CERD — has polynomial complexity, therefore bypassing the combinatorial explosion typically associated with the correspondence problem, and has optimal properties when the camera parameters are known. Our experiments with synthetic and real data show that CERD is able to accurately estimate correspondence and motion, being able to cope with a large number of outliers and light occlusion. Additionally, it’s ability to be coupled with any feature extraction algorithm (e.g., SIFT) allows for extra versatility and broadens it’s applicability to a wide range of scenarios.
Terms of use : Click here A survey on smart grid communication system

APSIPA Transactions on Signal and Information Processing / Volume 4 / 2015 / e5 DOI: 10.1017/ATSIP.2015. 9, Published online: 03 August 2015 Link to this article: http://journals.cambridge. org/abstract_S2048770315000098 How to cite this article: Miles H.F. Wen, Ka-Cheong Leung, Victor O.K. Li, Xingze He and C. -C. Jay Kuo (2015). A survey on smart grid communication system. APSIPA Transactions on Signal and Information Processing, 4, e5 doi:10.1017/ATSIP.2015. 9 Request Permissions : Click here
Video summarization using reinforcement learning in eigenspace

We propose video summarization using reinforcement learning. The importance score of each frame in a video is calculated from the user's actions in handling similar previous frames; if such frames were watched rather than skipped, a high score is assigned. To calculate the score, instead of using raw feature vectors extracted from images, we use feature vectors projected on eigenspace: as a result, we can deal with the features comprehensively. We also give an algorithm that uses the reinforcement learning method to create a personalized video summary. The summarization algorithm is applied to a soccer video to confirm its effectiveness.
Prehistoric evolution of the dualistic structure mixed rice and millet farming in China

Compared with the monistic structure of crop agriculture in Southwest Asia and Mesoamerica, agriculture in ancient China reflects the characteristics of a dualistic structure with millet in the north and rice in the south. It is argued that the rice and millet farming modes were mutually exchanged during their development and formed a vast region of mixed farming. However, the time and place of its origin, the routes of dissemination, and the development patterns and possible influence factors of mixed farming remain unclear. This study systematically collected information from 804 sites with millet and rice records and detailed floatation results from 78 mixed farming sites in prehistoric China. Three north–south communication corridors are identified between the upper, middle and lower Yellow and Yangtze River Valleys that began around 5500 BP, 8400 BP and 4600 BP, respectively. Cultural communication accompanied by human migration and the unique natural environment of loess and East Asia monsoons facilitated the interaction between millet and rice farming through these corridors. As a comprehensive reflection of the interaction between millet and rice farming, the crop structure of the four core mixed farming regions is in a continual process of adjustment, with the selection of foxtail millet in the southward spread of millet agriculture and temperate Oryza japonica in the northern spread of rice agriculture.
Institute of Physics Publishing Journal of Optics A: Pure and Applied Optics Conical Diffraction Asymptotics: Fine Structure of Poggendorff Rings and Axial Spike

The paraxial propagation of a beam incident along an optic axis of a biaxial crystal slab is studied in detail. Analytical descriptions are given for the Poggendorff bright and dark rings (associated with the conical singularity of the dispersion surface), and the axial spike (associated with the toroidal ring in the dispersion surface). The rings and spike depend on distance from the crystal. In sharpest focus, the rings are close and asymmetrical, and the spike is faint. Further away, the rings separate, they develop weak diffraction oscillations, and the spike grows in intensity. Eventually the oscillations disappear and the rings become symmetrical, and the axial spike dominates. The images depend on the profile of the incident beam; explicit formulae are given for a Gaussian beam and a coherently illuminated pinhole. Geometrical optics (extended to complex rays for the Gaussian beam) can describe some aspects of the images, in particular the Poggendorf dark ring, which arises from antifocusing and for which an explicit description is given.
Pathways to resilience in semi-arid economies (PRISE) CARIAA consortium report February 2014 - November 2018

PRISE (www.prise.odi.org) (2014–2018) was funded through the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA) programme, launched by the International Development Research Centre (IDRC) and the Department for International Development (DFID) in 2013, to fund adaptation research on three ‘hotspots’ of climate vulnerability: glacier-fed rivers, mega-deltas, and semi-arid lands (de Souza et al., 2015). ‘Hotspots’ are defined as areas where a strong climate signal coincides with a large concentration of poor, vulnerable or marginalised people. PRISE developed projects in seven countries with semi-arid regions: Senegal, Burkina Faso, Kenya, Tanzania (until 2015), Pakistan and Tajikistan and Kyrgyzstan (since 2016). CARIAA is also rooted in progressive research for development principles, including knowledge co-creation (Harvey et al., 2017) and transdisciplinarity (Cundill et al., 2018), and this is reflected in the approaches and methodology employed by PRISE.
Distributed Sensor Systems

Nowadays many surveillance systems are composed of several sensors to improve information one can obtained from a target. Depending on constellation of sensors and target, the performance of detection, localization, recognition, and tracking is improved dramatically. In particular a sensor network with distributed transmit and receive nodes can increase the probability to survive if any individual sensor node fails and the vulnerability against any electronic or physical attack is reduced [1]. Networks of homogeneous sensors even promote new processing concepts like multiple-input multiple-output (MIMO) or compressive sensing for data fusion and parameter estimation. The objective of this lecture is to establish fundamental understanding of multi sensor systems to stimulate new concepts, theories, and applications in this area, and to provide a background to the following lectures of this series.
Towards Cloud-Native, Machine Learning Based Detection of Crop Disease with Imaging Spectroscopy

Developing actionable early detection and warning systems for agricultural stakeholders is crucial to reduce the annual $200B USD losses and environmental impacts associated with crop diseases. Agricultural stakeholders primarily rely on labor-intensive, expensive scouting and molecular testing to detect disease. Spectroscopic imagery (SI) can improve plant disease management by offering decision-makers accurate risk maps derived from Machine Learning (ML) models. However, training and deploying ML requires significant computation and storage capabilities. This challenge will become even greater as global scale data from the forthcoming Surface Biology & Geology (SBG) satellite becomes available. This work presents a cloud-hosted architecture to streamline plant disease detection with SI from NASA’s AVIRIS-NG platform, using grapevine leafroll associated virus complex 3 (GLRaV-3) as a model system. Here, we showcase a pipeline for processing SI to produce plant disease detection models and demonstrate that the underlying principles of a cloud-based disease detection system easily accommodate model improvements and shifting data modalities. Our goal is to make the insights derived from SI available to agricultural stakeholders via a platform designed with their needs and values in mind. The key outcome of this work is an innovative, responsive system foundation that can empower agricultural stakeholders to make data-driven plant disease management decisions, while serving as a framework for others pursuing use-inspired application development for agriculture to follow that ensures social impact and reproducibility while preserving stakeholder privacy. Key Points Cloud-based plant disease detection system, easily accommodates newly developed and/or improved models, as well as diverse data modalities. Empower agricultural stakeholders to use hyperspectral data for decision support while preserving stakeholder data privacy. Outline framework for researchers interested in designing geospatial/remote sensing applications for agricultural stakeholders to follow.