Miracle-dz/UniFAR-FTUs huggingface dataset:
Solar Cycle Variability of Nonmigrating Tides in the 5.3 and 15 μm Infrared Cooling of the Thermosphere (100–150 km) from SABER

This paper discusses the solar cycle variation of the DE3 and DE2 nonmigrating tides in the nitric oxide (NO) 5.3 μm and carbon dioxide (CO2) 15 μm infrared cooling between 100 and 150 km altitude and ±40° latitude. Tidal diagnostics of SABER NO and CO2 cooling rate data (2002–2013) indicate DE3 (DE2) amplitudes during solar maximum are on the order of 1 (0.5) nW/m3 in NO near 125 km, and on the order of 60 (30) nW/m3 in CO2 at 100 km, which translates into roughly 15–30% relative to the monthly zonal mean. The NO cooling shows a pronounced (factor of 10) solar cycle dependence (lower during solar minimum) while the CO2 cooling does not vary much from solar min to solar max. Photochemical modeling reproduces the observed solar cycle variability and allows one to delineate the physical reasons for the observed solar flux dependence of the tides in the infrared cooling, particularly in terms of warmer/colder background temperature versus smaller/larger tidal temperatures during solar max/min, in addition to cooling rate variations due to vertical tidal advection and tidal density variations. Our results suggest that (i) tides caused by tropospheric weather impose a substantial—and in the NO 5.3 μm case solar cycle dependent—modulation of the infrared cooling, mainly due to tidal temperature, and (ii) observed tides in the infrared cooling are a suitable proxy for tidal activity including its solar cycle dependence in a part of Earth's atmosphere where direct global temperature observations are lacking.
Multivariate Probabilistic Monocular 3 D Object Detection

In the main paper, we show how learned covariances behave on the KITTI dataset [1]. To show the scalability of our method, we further show how learned covariances behave on the Waymo Open dataset [7] in Fig. 1. We can see predicted covariances are negative and their magnitudes increase with the increase of the distance. This shows our model can also predict covariances as expected effectively on the much more diverse and challenging Waymo Open dataset [7]. We also show predicted uncertainties in Fig. 2. We can see predicted uncertainties are larger for distant small objects. Moreover, we notice that the magnitudes of covariances and uncertainties on the Waymo Open dataset [7] are larger than those on the KITTI dataset [1]. We assume this is because Waymo [7] is much more diverse and challenging than KITTI [1].
Eurographics/ Acm Siggraph Symposium on Computer Animation (2006) Automatic Splicing for Hand and Body Animations

We propose a solution to a new problem in animation research: how to use human motion capture data to create character motion with detailed hand gesticulation without the need for the simultaneous capture of hands and the full-body. Occlusion and a difference in scale make it difficult to capture both the detail of the hand movement and unrestricted full-body motion at the same time. With our method, the two can be captured separately and spliced together seamlessly with little or no user input required. The algorithm relies on a novel distance metric derived from research on gestures and uses a two-pass dynamic time warping algorithm to find correspondence between the hand and full-body motions. In addition, we provide a method for supplying user input, useful to animators who want more control over the integrated animation. We show the power of our technique with a variety of common and highly specialized gesticulation examples.
Discontinuation of Statins in Routine Care Settings

BACKGROUND Systematic data on discontinuation of statins in routine practice of medicine are limited. OBJECTIVE To investigate the reasons for statin discontinuation and the role of statin-related events (clinical events or symptoms believed to have been caused by statins) in routine care settings. DESIGN A retrospective cohort study. SETTING Practices affiliated with Brigham and Women's Hospital and Massachusetts General Hospital in Boston. PATIENTS Adults who received a statin prescription between 1 January 2000 and 31 December 2008. MEASUREMENTS Information on reasons for statin discontinuations was obtained from a combination of structured electronic medical record entries and analysis of electronic provider notes by validated software. RESULTS Statins were discontinued at least temporarily for 57 292 of 107 835 patients. Statin-related events were documented for 18 778 (17.4%) patients. Of these, 11 124 had statins discontinued at least temporarily; 6579 were rechallenged with a statin over the subsequent 12 months. Most patients who were rechallenged (92.2%) were still taking a statin 12 months after the statin-related event. Among the 2721 patients who were rechallenged with the same statin to which they had a statin-related event, 1295 were receiving the same statin 12 months later, and 996 of them were receiving the same or a higher dose. LIMITATIONS Statin discontinuations and statin-related events were assessed in practices affiliated with 2 academic medical centers. Utilization of secondary data could have led to missing or misinterpreted data. Natural-language-processing tools used to compensate for the low (30%) proportion of reasons for statin discontinuation documented in structured electronic medical record fields are not perfectly accurate. CONCLUSION Statin-related events are commonly reported and often lead to statin discontinuation. However, most patients who are rechallenged can tolerate statins long-term. This suggests that many of the statin-related events may have other causes, are tolerable, or may be specific to individual statins rather than the entire drug class. PRIMARY FUNDING SOURCE National Library of Medicine, Diabetes Action Research and Education Foundation, and Chinese National Key Program of Clinical Science.
Removal of salt and pepper noise using Advanced Modified Decision based Unsymmetric Trimmed Median Filter

In this paper we are presenting a novel approach for removal of salt and pepper noise from the high density salt & pepper noisy images, using Iterative Modified Decision based Unsymmetric Trimmed Median Filter. The existing MDBUTMF is unable to restore the original image from the noisy one if noise density is more than 70%. The performance of the proposed method is analyzed by using various qualities of metrics, such as Mean Square Error (MSE) and Peak Signal to Noise ratio (PSNR). Simulation results clearly show that the proposed method is out performs both in qualitative as well quantitative fidelity criteria, when it is compared with MDBUTMF.
Semantic Enrichment of a Multilingual Archive with Linked Open Data

We first performed Named-Entity Recognition (NER) on this collection in order to extract meaningful concepts. A second step involved a new approach to Entity Linking with gazetteers (Shen et al., 2014) in order to disambiguate them with DBpedia URIs (Bizer et al., 2009). For instance, http://dbpedia.org/resource/Christiaan_Huygens includes the alternative label “Christian Huyghens” (French spelling) but excludes information about the Belgian painter Leon Huygens (which has his own
IT project prioritization

Tullow Oil, a London-based independent oil and gas exploration and production company, regularly wins awards for its innovative approach to problem solving. Its business culture is based on investing in the best people and then trusting them to work together to keep Tullow on the leading edge of the industry. Tullow’s CIO recently challenged his team to develop an approach to devolve control of IT project prioritization to non-IT leaders within the company. This article explains the approach developed and how it is working to keep the business’s IT strategy aligned with Tullow’s entrepreneurial spirit and commitment to collaborative decision making.
Graph Regularized Non-Negative Matrix Factorization for Image Retrieval

This paper presents a novel matrix factorization method for effectively performing the image retrieval in large image databases. Non-negative Matrix Factorization (NMF) provides a parts-based representation of data by finding two non-negative matrices whose product can well approximate the original data matrix. Although it has been applied successfully for several applications, simply using NMF for image retrieval provides low performance results which results from the fact that NMF fails to consider the geometric structure that is contained within the data. To solve the above problem, we encode the geometrical information contained in the data by constructing a nearest neighbor graph and perform matrix factorization based on this graph structure. In this work, 500 images from Corel dataset have been taken into consideration. We compared NMF and GNMF based method in the context of image retrieval. Experimental results demonstrate the effectiveness and robustness of GNMF based approach.
Platforms, Communities, and Business Ecosystems: Lessons Learned about Technology Entrepreneurship in an Interconnected World

Technology entrepreneurs are increasingly building businesses that are deliberately anchored in platforms, communities, and business ecosystems. Nonetheless, actionable, evidence-based advice for technology entrepreneurs is scarce. Platforms, communities, and ecosystems are active areas of management research, but until recently, each has been studied in separate research programs, with results published in different venues, and often examined from the perspectives of incumbent managers or policy makers rather than entrepreneurs and new entrants. This article re-examines these phenomena from the perspective of technology entrepreneurs facing strategic choices about interconnected systems of platforms, communities, and business ecosystems, and decisions about the nature and extent of participation. It brings together insights from a wide range of published sources. For entrepreneurs, it provides an accessible introduction to what can be a complex topic, identifies a set of practical considerations to be accounted for in decision-making, and offers a guide for further reading. For researchers and graduate students seeking practical and high-impact research problems, it provides an entry point to the research literature and identifies gaps in the current body of knowledge, especially regarding the system-level interactions between subsystems. I get by with a little help from my friends. Lennon–McCartney The Beatles (1967)
Learning Language from Perceptual Context

Most current natural language processing (NLP) systems are built using statistical learning algorithms trained on large annotated corpora which can be expensive and time-consuming to collect. In contrast, humans can learn language through exposure to linguistic input in the context of a rich, relevant, perceptual environment. If a machine learning system can acquire language in a similar manner without explicit human supervision, then it can leverage the large amount of available text that refers to observed world states (e.g. sportscasts, instruction manuals, weather forecasts, etc.) Thus, my research focuses on how to build systems that use both text and the perceptual context in which it is used in order to learn a language. I will first present a system we completed that can describe events in RoboCup 2D simulation games by learning only from sample language commentaries paired with traces of simulated activities without any language-specific prior knowledge. By applying an EM-like algorithm, the system was able to simultaneously learn a grounded language model as well as align the ambiguous training data. Human evaluations of the generated commentaries indicate they are of reasonable quality and in some cases even on par with those produced by humans. For future work, I am proposing to solve the more complex task of learning how to give and receive navigation instructions in a virtual environment. In this setting, each instruction corresponds to a navigation plan that is not directly observable. Since an exponential number of plans can all lead to the same observed actions, we have to learn from compact representations of all valid plans rather than enumerating all possible meanings as we did in the sportscasting task. Initially, the system will passively observe a human giving instruction to another human, and try to learn the correspondences between the instructions and the intended plan. After the system has a decent understanding of the language, it can then participate in the interactions to learn more directly by playing either the role of the instructor or the follower.
DSM in practice: iterative water-filling implemented on ADSL modems

Dynamic spectrum management (DSM) is a new technique for multiuser power allocation and/or detection in digital subscriber line (DSL) networks. In DSM, transmit spectra are adapted based on the direct and crosstalk channels seen by the modems within a network. This allows binder bit rate performance maximisation. At the Alcatel Research and Innovation labs, we have recently developed a DSM testbed which allows the performance of DSM algorithms to be evaluated in practice. The paper describes the development of this DSM testbed. With this testbed we have evaluated the performance of a DSM algorithm known as iterative water-filling. It has been demonstrated that iterative water-filling can yield data-rate gains of up to 500% in the real world. Practical issues on the implementation of iterative water-filling are also discussed.
T he D istributed C omputing C olumn

In this issue of the distributed computing column, Michel Raynal and Gadi Tauben-feld revisit a classical question: what can we accomplish in shared memory systems that are anonymous and symmetric? The article is a nice introductory presentation of symmetry and anonymity. It di ﬀ erentiates symmetry and anonymity in the context of processors, and looks at both process and memory anonymity. The article uses two fundamental problems to illustrate: mutual exclusion and consensus. In each case, it illustrates what can be accomplished, giving a good illustration of both what is feasible and the limitations in symmetric and anonymous systems. This new distributed computing column is a great way to start the new year, looking back at a classic problem!
Learned deconvolution using physics priors for structured light-sheet microscopy

SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9SS, UK Robinson Research Institute, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, The University of Adelaide, Adelaide, SA, Australia Institute for Photonics and Advanced Sensing, The University of Adelaide, Adelaide, SA, Australia Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia Department of Physics, College of Science, Yonsei University, Seoul 03722, South Korea
Image Restoration Using Gaussian Particle Filters

Sequential Monte Carlo method has received intense attention among the literature due to its promising applicability to non-linear and non-Gaussian problems. However, while adopting the standard particle filtering method to the area of image restoration, two main drawbacks are found. Firstly, the computational complexity, which mainly comes from a procedure called resample (in a serial implementation), of particle filters would render it too resource-requiring for image restoration. Secondly, the sample impoverishment introduced by resample can affect the filter's performance. In this paper, we adopt a new type of particle filters which do not require resample to the area of image restoration-the Gaussian Particle Filters (GPF). Simulation results are presented to show the GPF's better performances over conventional particle filters. Keywords: particle filter, Gaussian particle filter, resample, sample impoverishment
Two-Hop MIMO Relaying Systems Using Random Unitary Beamforming in Gaussian Broadcast Channels

In this paper we propose the multi-user MIMO (MU-MIMO) with the fixed relay station (RS) transmissions scheme where the base station (BS) and the fixed RS are equipped with multiple antennas and the multiple users are equipped with a single antenna. Since the MU-MIMO can improve the sum capacity significantly by transmitting the data streams to multiple users simultaneously without much link gain while the fixed relay station can improve the link gain but loses the spectral efficiency due to the half-duplex transmission, our proposed scheme can compensate each of the drawbacks and can improve both the sum rate and the link gain. We adopt the practical random unitary beamforming (RUB) precoding method for MU-MIMO and the simple amplify-and-forward protocol for the operation of the relay station. Based on our proposed RUB based MU-MIMO with fixed RS, the sum capacity is upper bounded by the channels between the BS and the RS, not by the channels between the RS and the users. We also show from our extensive simulations that our proposed scheme has lower complexity compartively and provides the performance commensurate with the schemes presented in the literature in terms of the sum-rate for the large user scenario.
Clustering and classification

At a moderately advanced level, this book seeks to cover the areas of clustering and related methods of data analysis where major advances are being made. Topics include: hierarchical clustering, variable selection and weighting, additive trees and other network models, relevance of neural network models to clustering, the role of computational complexity in cluster analysis, latent class approaches to cluster analysis, theory and method with applications of a hierarchical classes model in psychology and psychopathology, combinatorial data analysis, clusterwise aggregation of relations, review of the Japanese-language results on clustering, review of the Russian-language results on clustering and multidimensional scaling, practical advances, and significance tests.
Monitoring a progressive collapse test of a spherical lattice shell using high‐speed videogrammetry

The monitoring of a progressive collapse test of a structure model has always been a technical issue in civil engineering. This paper proposes a novel videogrammetric approach to monitor a single‐layer lattice shell, which consists of three main parts: A videogrammetry system with six high‐speed cameras is established to measure the morphological changes of the lattice shell. A specific artificial target is designed and experimentally tested to obtain the location of every node centre on the lattice shell. The 3D displacements of the node centres can be calculated by surface fitting and local coordinate transformation.
Automatized tracking of free-ranging wild song birds using the Encounternet

Understanding the ecology and evolution of animals requires fundamental insights into the decision making of individuals. Animal populations are characterized by individuals usually moving in space and time to explore and exploit resources, find partners, or escape predators. Thus many decisions they make have a spatial component, potentially affecting reproduction and survival. Decisions where to move when has implications for access to information about the environment and for encountering predators, potential mates and competitors and thus for the social dynamics. Yet, despite a profound understanding on selection pressures on animals, we still have very little information about individual spatial activities as it is very difficult to track free ranging animals over a prolonged period of time. Even though GPS devices can provide high accuracy tracking data, they are limited to larger animals. Also novel light-weight GPS tags are limited for continuous tracking, due to their (still) low battery life time (Wikelski et al. 2007). For small animals, radio-tracking has been a successful alternative as light weight senders can last for several weeks. Yet, radio tracking usually requires a person to follow a given individual and mark its locations at regular time intervals which is a time consuming expedition specifically for mobile small animals, such as songbirds (Naef-Daenzer 1994; Naguib et al. 2001; Amrhein et al. 2004; Roth et al. 2009).
More Efficient Secure Function Evaluation Using Tiny Trusted Third Parties

We investigate the use of trustworthy devices, which function as trusted third parties (TTPs), to solve general two-party Secure Function Evaluation (SFE) problems. We assume that a really trustworthy TTP device will have very limited protected memory and computation environment—a tiny TTP. This precludes trivial solutions like "just run the function in the TTP". Traditional scrambled circuit evaluation approaches to SFE have a very high overhead in using indirectly-addressed arrays—every array access’s cost is linear in the array size. The main gain in our approach is that array access can be provided with much smaller overhead— O( p N logN). This expands the horizon of problems which can be efficiently solved using SFE. Additionally, our technique provides a simple way to deploy arbitrary programs on tiny TTPs. In our prototype, we use a larger (and expensive) device, the IBM 4758 secure coprocessor, but we also speculate on the design of future tiny devices that could greatly improve the current prototype’s efficiency by being optimized for the operations prevalent in our algorithms. We have prototyped a compiler for the secure function definition language (SFDL) developed in the Fairplay project. Our compiler produces an arithmetic circuit, augmented with array access gateswhich provide more efficient secure access to arrays. We then have a circuit interpreter in the 4758 to evaluate such a circuit on given inputs. It does this gate by gate, requiring very little protected space. We report on the performance of this prototype, which confirms our approach’s strength in handling indirectly-addressed arrays.
AIS Electronic

Consumerization of IT (CoIT) is a key trend affecting society at large, including organizations of all kinds. A consensus about the defining aspects of CoIT has not yet been reached. Some refer to CoIT as employees bringing their own devices and technologies to work, while others highlight different aspects. While the debate about the nature and consequences of CoIT is still ongoing, many definitions have already been proposed. In this paper, we review these definitions and what is known about CoIT thus far. To guide future empirical research in this emerging area, we also review several established theories that have not yet been applied to CoIT but in our opinion have the potential to shed a deeper understanding on CoIT and its consequences. We discuss which elements of the reviewed theories are particularly relevant for understanding CoIT and thereby provide targeted guidance for future empirical research employing these theories. Overall, our paper may provide a useful starting point for addressing the lack of theorization in the emerging CoIT literature stream and stimulate discussion about theorizing CoIT.
Grouth Cycles in a Discrete, Nonlinear Model

This paper develops a discrete, nonlinear growth cycle model for a macroeconomy. The nonlinearities, which correspond to empirical relationships between profitability and capacity utilization in the postwar U.S economy, can produce stable, periodic and chaotic behavior. These behaviors are established_analytically, and further investigated through simulation. Data from the simulations are used to show that chaotic attractors can produce time series which are useful representations of business cycles.