Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hierarchical Skeleton-Based Shape

[ç $ÍÒ ¢v; êuÙ è AÃ3 A Hierarchical Skeleton-Based Shape Description Jong-Seung Park Duk-Ho Chang Visual Information Team, ETRI, 161 Kajong-Dong, Yusong-Gu, Taejon, 305-350, South Korea park@etri.re. kr dhchang@etri.re. kr Abstract Skeleton representation is a natural way of shape description for deformable objects. Also the shape can be reconstructed from the skeleton representation by taking an inverse skeleton transform. This paper proposes a skeleton tree structure for e cient shape representation. In our proposed skeleton tree structure, the sensitivity to boundary noise is reduced by employing a hierarchical tree representation. High-level nodes describe parts of coarse trunk of the object and low-level nodes describe ne details. Each low-level node re nes the shape of the parent node. Most of the noise disturbances are limited to the bottom levels.
Robust adaptive neural control of SISO nonlinear systems with unknown dead-zone and completely unknown control gain

In this paper, robust adaptive neural tracking control is developed for a class of uncertain SISO nonlinear systems in a Brunovsky form with unknown nonlinear dead-zone and unknown control gain & its sign. The design is based on the principle of sliding mode control and the use of Nussbaum-type function in solving the problem of the completely unknown function control gain. A novel description of general nonlinear dead-zone, which makes the control system design possible, is introduced by using the mean value theorem. The approach removes the condition of the equal slope with defined region for the dead-zone. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation for the upper bound of the optimal approximation error and the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded
Fully Bottom-Up Blob Extraction in Building Facades

A fully bottom-up algorithm for extracting blobs in building facades is proposed. Prototype discovery, hypothesis testing and verification are used to identify missing blobs or split the agglomerated ones, when repeated patterns are present in the facade. A novel similarity measure is used for assessing the similarity of subpatterns. The proposed algorithm can detect 80% of the 3589 hand segmented components in 300 images.
Crossing Boundaries – an interdisciplinary journal

Due to the bandwidth constraint and dynamic topology of Mobile Ad hoc NETworks (MANET), supporting Quality of Service (QoS) in MANETs is a challenging task. A lot of research has been done on supporting QoS in the Internet and other network architectures, but most of them are not suitable in the MANET environment. In this paper, we review the current research on QoS support in MANETs, which includes QoS models, resource reservation signaling, QoS routing, and QoS Medium Access Control (MAC). The purpose of this paper is twofold. The first is to describe a whole picture of QoS support in MANETs; the other is to present the challenges and stimulate more research interests in this area.
An iintegrated algorithmic and software solution for biological rhythms analysis: Application to long-term data series

Here we introduce an algorithmic tool to extract significant information out of the long-term physiological monitoring data following an originally designed methodology that is implemented as an integrative software solution. The algorithm consists of several consecutive steps including elimination of outlier measurements, filtering out high-frequency noise, detection of the long-term trend and an enhanced elicitation and analysis procedure of the rhythms based on the spectral analysis of the fluctuations around the detected trend. The designed solutions are especially suited to operate with non-equidistant data series that are common in ambulatory monitoring data due to the limited control over the measurement procedures and elimination of unreliable measurements. The potential application area includes not only the analysis of biological data series but also extends to astronomical, climatological, hydrological, meteorological and other data series. The integrated solution providing the universal analysis algorithm for data sets from different sources is especially interesting for elicitation of various cross-modulation effects like governing of physiological rhythms by astronomic cycles.
Registration of Noisy Point Clouds Using Virtual Interest Points

A new method is presented for robustly and efficiently registering two noisy point clouds. The registration is driven by establishing correspondences of virtual interest points, which do not exist in the original point cloud data, and redefined by the intersection of parametric surfaces extracted from the data. Parametric surfaces, such as planes, exist in abundance in both natural and artificial scenes, and can lead to regions in the data of relatively low noise. This in turn leads to repeatable virtual interest points, with stable locations across overlapping images. Experiments were run using virtual interest points defined by the intersection of three implicit planes, applied to data sets of four environments comprising100 point clouds. The proposed method outperformed the Iterative Closest Point, Generalized Iterative Closest Point, and a 2.5D SIFT-based RANSAC method in registering overlapping images with a higher success rate, and more efficiently.
Football player tracking from multiple views - using a novel background segmentation algorithm and multiple hypothesis tracking

In this work, our aim is to develop an automated system which provides data useful for football game analysis. Information from multiple cameras is used to perform player detection, classification and tracking. A background segmentation approach, which operates with the invariant Gaussian colour model and uses temporal information, is used to achieve more accurate results. Information derived and matched from all cameras is then used to perform tracking, using an advanced Multiple Hypothesis Tracking algorithm.
A STUDY ON EFFECTIVE DIELECTRIC CONSTANTS OF NON-SPHERICAL SNOWFLAKE AND MELTING HYDROMETEORS

The bright band, a layer of enhanced radar echo associated with melting hydrometeors, is often observed in stratiform rain. The microphysical properties of melting hydrometeors and their scattering and propagation effects have long been studied not only because of their importance in accurately estimating parameters of the precipitation from spaceborne radar and radiometers but also as a result of their negative influence on earthsatellite communication systems caused by attenuation and depolarization of radio signals. To characterize the properties of the melting layer a number of observations of the radar bright band have been made by both groundbased weather radars and multi-frequency airborne radars. However, one of the impediments to the study of the radar signature of the melting layer is the determination of effective dielectric constants of melting hydrometeors. Although a number of mixing formulas are available to compute the effective dielectric constants, their results vary to a great extent when water is involved in the mixture, such as in the case of melting snow[1][2]. It is also physically unclear as to how to select among these various formulas. Furthermore, questions remain as to whether these mixing formulas can be applied to computations of radar polarimetric parameters from non-spherical melting particles.
Research on Vector Sensor Direction Finding Technology in Intensive Coherent Interference

Passive direction finding is the main capability of AUVs. Methods of direction finding based on single vector are reviewed in this paper. Coherent interference of AUVs itself is very hard for acoustic direction finding system and traditional noise control method can overcomes strong interference but forms blind spots in the interference direction. In order to achieve the total space DOA estimation, time reversal passive shield and focus (TRPSF) method is brought out in this paper, which sets the zero point at the position of strong interference. AUVs can not only overcome strong interference at a certain place of its stern by TRPSF technology, but also refocus the signal energy in its original area. The using of TRPSF can effectively estimate target azimuth angle. Simulations results prove its feasibility and practicality.
Infinitesimal Flexibility of Higher Order for a Planar Parallel Manipulator

The problems around rigidity and exibility of geometrical structures have a long history in mathematics. Recently obtained results like the proof of the \Bellows Conjecture" have brought them back into the center of mathematical interest. However, innnitesimal exibility | usually of order one | has also been studied in kinematics for a long time. In particular in the eld of robotics the singularity analysis of parallel manipulators is of high actuality. The objective of this paper is to bridge the gap between rigidity theory and kinemat-ics. On the one hand the deenition and basic properties of higher-order innnitesimal exibility are presented to kinematicians. On the other hand it is shown that for a particular planar parallel manipulator standard results from kinematics enable to characterize in a geometric way all cases of higher-order innnitesimal exibility.
Cautious particle swarm

Behavior and search performance of the proposed cautious particle swarm, in which the particles are cautious about imitating the best successful one, are investigated with a question: ldquoIs it really the best strategy for a group that every individual in which obediently imitates the top one? rdquo Their neutral or disobedient attitudes to the global best are expressed by replacing the conventional uniform distribution for random numbers with either of the two probability distributions: slided uniform distribution and asymmetrical normal distribution. Empirical analyses on the behavior of such a single particle in one-dimensional search space have aroused an expectation that appropriate cautiousness balance may accomplish both exploration-oriented search for avoiding local minima and exploitation-oriented search for finding the global optimum near the global best. For discussion on the optimization performance of the cautious particle swarm, experiments in typical test functions were performed. The experimental results have presented an acceptable parameter range of obedience for appropriate cautiousness.
Forensic detection of Gaussian low-pass filtering in digital images

Gaussian low-pass filtering is a common post-process operation which is exploited to blur and conceal these discontinuities at the border of tampered objects introduced by copy & paste operation, making the tampered image more realistic. In this paper, a novel approach for detecting Gaussian low-pass filtering in digital images is proposed based on the frequency residual function which presents different attribute in median-high frequency domain between the original image and the filtered image. A Gaussian low-pass filter bank is utilized to obtain a series of frequency residual functions and a bandwidth feature vector is proposed to identify the filtered image with the Support Vector Machine (SVM). Excellent experimental results verify the effectiveness of our proposed approach.
PROTEIN STRUCTURE: INSIGHTS FROM GRAPH THEORY

The sequence and structure of a large body of proteins are becoming increasingly available. It is desirable to explore mathematical tools for ecient extraction of information from such sources. The principles of graph theory, which was earlier applied in elds such as electrical engineering and computer networks are now being adopted to investigate protein structure, folding, stability, function and dynamics. This review deals with a brief account of relevant graphs and graph theoretic concepts. The concepts of protein graph construction are discussed. The manner in which graphs are analyzed and parameters relevant to protein structure are extracted, are explained. The structural and biological information derived from protein structures using these methods is presented.
Content linking for UGC based on Word Embedding model

There are huge amounts of User Generated Contents (UGCs) consisting of authors' articles of different themes and readers' comments in social networks every day. Generally, an article often gives rise to thousands of readers' comments, which are related to specific points of the originally published article or previous comments. Hence it has suggested the urgent need for automated methods to implement the content linking task, which can also help other related applications, such as information retrieval, summarization and content management. So far content linking is still a relatively new issue. Because of the unsatisfactory of traditional ways based on feature extraction, we look forward to using deeper textual semantic analysis. The Word Embedding model based on deep learning has performed well in Natural Language Processing (NLP), especially in mining deep semantic information recently. Therefore, we study further on the Word Embedding model trained by different neural network models from which we can learn the structure, principles and training ways of the neural network based language models in more depth to complete deep semantic feature extraction. With the aid of the semantic features, we expect to put forward a new method for content linking between comments and their original articles in social networks, and finally verify the validity of the proposed method through experiments and comparison with traditional ways based on feature extraction.
Functional Mri: Pitfalls in Fmri Quantification Processing

Background The use of MRI for performing non-invasive assessment has grown dramatically over the past two decades. Functional MRI (fMRI) is now a critical tool in basic neuroscience, and is gradually being used in the clinical arena as well. One of the reasons that fMRI has been slow to be utilized clinically, however, is that it is quite prone to confounding artifacts that can be particularly problematic in clinical cases. This means that clinicians need to be conversant with the sorts of artifact that can corrupt fMRI data, with ways in which the risk of these artifacts being present can be reduced, and with some of the correction procedures that can be applied to reduce their effect.
Group key establishment for secure multicasting in IoT-enabled Wireless Sensor Networks

Wireless Sensor Network (WSN) is a fundamental technology of the Internet of Things (IoT). Group communications in the form of broadcasting and multicasting incur efficient message deliveries among resource-constrained sensors in IoT-enabled WSNs. Secure and efficient key management is significant to protect the authenticity, integrity, and confidentiality of multicast messages. This paper develops two group key establishment protocols for secure multicast communications among resource-constrained devices in IoT. The applicability of the two protocols are analyzed and justified by performance and security analysis.
The Attention Study : A Study on the Presence of Selective Attention in Firearms Officers

Perception, or the acquisition of information through the senses, has been a focus of philosophy and psychology for millennia. Phenomenological philosophers recognized that we were not simply passive absorbers of information but actively interact with our environment to perceive, process, and interpret this information. The philosophers’ perspective simply expressed is that there is no such thing as an objective reality. The very act of perceiving is dependent upon the direction and quality of the senses of the perceiver, and this varies on an individual level based on the nutrition, fatigue, experience, interest, etc., of the observer. Further, they questioned whether the very act of observing changed in some fashion the elements of what was being observed. If that were true, it would further distort the reality of that which is being observed. For instance, a cell under a microscope is neither seen nor functions as it would among other cells in a body. The very act of observing changes the dynamics of that which is observed. Subsequently, there was and is no such thing as a pure, objective reality. Similarly, there is no such thing as a pure, objective viewer.
Calibration of optical tweezers with positional detection in the back focal plane

We explain and demonstrate a new method of force and position calibrations for optical tweezers with back-focal-plane photodetection. The method combines power spectral measurements of thermal motion and the response to a sinusoidal motion of a translation stage. It consequently does not use the drag coefficient of the trapped object as an input. Thus, neither the viscosity, nor the size of the trapped object, nor its distance to nearby surfaces needs to be known. The method requires only a low level of instrumentation and can be applied in situ in all spatial dimensions. It is both accurate and precise: true values are returned, with small error bars. We tested this experimentally, near and far from surfaces in the lateral directions. Both position and force calibrations were accurate to within 3%. To calibrate, we moved the sample with a piezoelectric translation stage, but the laser beam could be moved instead, e.g., by acousto-optic deflectors. Near surfaces, this precision requires an improved formula for the hydrodynamical interaction between an infinite plane and a microsphere in nonconstant motion parallel to it. We give such a formula.
Intelligent denoising technique for spatial video denoising for real-time applications

With the wide spread of video usage in many fields of our lives, it becomes very important to develop new techniques for video denoising. Spatial video denoising using wavelet transform has been the focus of the current researches as it requires less computation and more suitable for real-time applications. Two specific techniques for spatial video denoising using wavelet transform are considered in this work: 2D Discrete Wavelet Transform (2D DWT) and 2D Dual Tree Complex Wavelet Transform (2D DTCWT). Each of these techniques has its advantages and disadvantages. The first technique gives less quality at high levels of noise but consumes less time while the second gives high quality video while consuming long. In this work, we introduce an intelligent denoising system that makes a tradeoff between the quality of the denoised video and the time required for denoising. The system first estimates the noise level in the video frame then accordingly chooses the proper of the two denoising techniques to apply on the frame. The simulation results show that the proposed system is more suitable for real-time applications where the time is critical while giving high quality videos especially at low to moderate levels of noise.
Biometrics based Asymmetric Cryptosystem Design Using Modified Fuzzy Vault Scheme

We propose a novel biometrics cryptosystem where one can send and receive secure information using just the fingerprints. This cryptosystem is a judicious blend of the asymmetric cryptosystem like RSA and the symmetric fuzzy vault scheme having the advantages of both the aforementioned crypto systems. We have proposed a modification of the fuzzy vault scheme to make it more robust against variations in the values of biometric features. Finally, we propose the use of invariant features as a key to producing a hierarchical security system where the same key (fingerprint) can be used to generate encrypted messages at different levels of security
Software Analytics for Mobile Applications--Insights & Lessons Learned

Mobile applications, known as apps, are software systems running on handheld devices, such as smartphones and tablet PCs. The market of apps has rapidly expanded in the past few years into a multi-billion dollar business. Being a new phenomenon, it is unclear whether approaches to maintain and comprehend traditional software systems can be ported to the context of apps. We present a novel approach to comprehend apps from a structural and historical perspective, leveraging three factors for the analysis: source code, usage of third-party APIs, and historical data. We implemented our approach in a web-based software analytics platform named SAMOA. We detail our approach and the supporting tool, and present a number of findings obtained while investigating a corpus of mobile applications. Our findings reveal that apps differ significantly from traditional software systems in a number of ways, which calls for the development of novel approaches to maintain and comprehend them.
Rituximab consolidation after high-dose chemotherapy and autologous blood stem cell transplantation in follicular and mantle cell lymphoma: a prospective, multicenter phase II study.

BACKGROUND Patients with follicular (FL) or mantle cell lymphoma (MCL) are incurable with conventional therapy. We investigated the safety and efficacy of rituximab consolidation after autologous stem cell transplantation (ASCT) in order to prevent relapse by clearance of minimal residual disease (MRD). METHODS Rituximab was given approximately 8 weeks after CD34+ cell enriched ASCT at 375 mg/m2, weekly for 4 weeks. Monitoring of MRD was performed by repetitive PCR analyses. RESULTS Thirty-one patients were included; one died early after ASCT before rituximab administration. Thirty patients (20 FL, 10 MCL) were evaluable after rituximab consolidation, and 27 of these were assessable for MRD detection. Rituximab consolidation post-ASCT was safe, the most common toxicity being infection. At a median follow-up of 42 months (range 13-96) after ASCT, 25 patients were censored with an actuarial event-free survival (EFS) of 81% at 4 and 5 years. Four patients (two FL, two MCL) relapsed, and one additional MCL patient died unexpectedly in complete remission. PCR-negativity was observed in 22% of the patients before ASCT, 53% post-ASCT (P=0.0547), 72% after rituximab (P=0.0018) and 100% at 6 months post-transplant (P < 0.001). CONCLUSIONS One single course of rituximab consolidation given after ASCT is safe, may help to eliminate MRD and may translate into improved EFS in both FL and MCL patients.
ObjectRunner

We present in this paper ObjectRunner, a system for extracting, integrating and querying structured data from the Web. Our system harvests real-world items from template-based HTML pages (the so-called structured Web). It illustrates a two-phase querying of the Web, in which an intentional description of the targeted data is first provided, in a flexible and widely applicable manner. ObjectRunner follows then a lightweight, best-effort approach, leveraging both the input description and the source structure. This process is domain-independent, in the sense that it applies to any relation, either flat or nested, describing real-world items. We advocate via our prototype that fully automatic extraction and integration of structured data can be done fast and effectively, when the redundancy of the Web meets knowledge over the to-be-extracted data. We present the technical details and the overall platform through several application scenarios on real-life Web sources.