Miracle-dz/UniFAR-FTUs huggingface dataset:
Stabilization of a Rigid Body Payload with Multiple Cooperative Quadrotors

This paper presents the full dynamics and control of arbitrary number of quadrotor unmanned aerial vehicles (UAV) transporting a rigid body. The rigid body is connected to the quadrotors via flexible cables where each flexible cable is modeled as a system of arbitrary number of serially connected links. It is shown that a coordinate-free form of equations of motion can be derived for the complete model without any simplicity assumptions that commonly appear in other literature, according to Lagrangian mechanics on a manifold. A geometric nonlinear controller is presented to transport the rigid body to a fixed desired position while aligning all of the links along the vertical direction. A rigorous mathematical stability proof is given and the desirable features of the proposed controller are illustrated by numerical examples and experimental results.
Laser-based gap finding approach to mobile robot navigation

In this paper, a real-time laser based gap finding obstacle avoidance algorithm is presented. This algorithm layers on top of a global planner to maintain the overall goal of a given task. In the presence of an unknown obstacle, the algorithm computes a trajectory toward a gap that is wide enough and is closest to the path pre-planned by the global planner. In order to achieve this result, a four-stage process is executed sequentially namely: data classification, obstacle detection, collision avoidance, and online trajectory generation. During these stages, the algorithm classifies the environment into free space and obstacle regions, adjusts the vehicle velocity as a function of surrounding obstacles proximity, makes a decision to avoid the obstacles and then execute a new trajectory. This trajectory can either be an offset from the original path or a normal path to the best gap depending on the size of the free space, width of the robot and the allowable clearance from obstacles. Experiments show that this approach can avoid obstacles efficiently and effectively achieve the overall goal.
The fourth moment method

Higher moment analysis has typically been used to upper bound certain functions. In this paper, we introduce a new combinatorial method to lower bound the expectation of the absolute value of a random variable X by the expectation of a quartic in X. In the special case where we are looking at the absolute value of a (weighted) sum of {-1,+1} unbiased random variables, we achieve tight bounds, using only a fourth moment, for the total discrepancy of a set system. Because the fourth moment depends only on 4-wise independence, our bounds will hold over polynomially sized distributions, and so these bounds will be directly applicable in removing randomness to obtain NC algorithms. We obtain the first NC algorithms for the problems of total discrepancy, maximum acyclic subgraph, tournament ranking, the Gale--Berlekamp switching game, and edge discrepancy. We show that for most of these applications it is truly necessary to consider a fourth moment by exhibiting a 3-wise independent distribution which does not achieve the required bounds. Our method is strong enough to give a new combinatorial bound on tournament ranking.
Effect Estimation Method of Parallel Computing Based on Dynamic Generation of Equivalent Transformation Rules Dynamic Generation of Equivalent Transformation Rules

Recent studies in parallel computing have mainly focused on physically producing multiple computing sites for computational speed-up and not considered theories and methodologies, which are the essence of parallel computing, and correctness as well. It means that the studies have mostly considered cost-effectiveness, that is, how many computing sites are produced determines how much computing speed improves. This study proposes an algorithm to estimate the effectiveness of parallel computing based on the model with established theories and methodologies, which are the essence of parallel computing, and with assured correctness, instead of exploring such cost-effectiveness. Moreover, we will demonstrate the effectiveness of the proposed method by applying it to one of constraint satisfaction problems, Pic-a-Pix Puzzle, and comparing sequential computing time with estimated parallel computing time based on the dynamic generation of equivalent transformation (ET) rules.
Error Diagnosis and Data Profiling with Data X-Ray

The problem of identifying and repairing data errors has been an area of persistent focus in data management research. However, while traditional data cleaning techniques can be effective at identifying several data discrepancies, they disregard the fact that many errors are systematic, inherent to the process that produces the data, and thus will keep occurring unless the root cause is identified and corrected. In this demonstration, we will present a large-scale diagnostic framework called DataXRay. Like a medical X-ray that aids the diagnosis of medical conditions by revealing problems underneath the surface, DataXRay reveals hidden connections and common properties among data errors. Thus, in contrast to traditional cleaning methods, which treat the symptoms, our system investigates the underlying conditions that cause the errors. The core of DataXRay combines an intuitive and principled cost model derived by Bayesian analysis, and an efficient, highly-parallelizable diagnostic algorithm that discovers common properties among erroneous data elements in a top-down fashion. Our system has a simple interface that allows users to load different datasets, to interactively adjust key diagnostic parameters, to explore the derived diagnoses, and to compare with solutions produced by alternative algorithms. Through this demonstration, participants will understand (1) the characteristics of good diagnoses, (2) how and why errors occur in real-world datasets, and (3) the distinctions with other related problems and approaches.
Use-case driven service modelling with XML-based tailoring for SOA

A key problem in service-oriented computing is how to extract business requirements and build solutions with available services. The manual process of eliciting business requirements from use cases and scenarios is time consuming. This paper proposes a semi-automatic way of deriving service models from business use cases using XML-based use-case tailoring. By matching the required capability of each use case to the available capabilities provided by services, the optimal set of use cases is realised by the appropriate set of services. We rewrite use cases in XML to achieve the clear separation of any semantic parts of use-case descriptions from visual representations. The resulting use cases are subsequently tailored into well-defined business functionalities, which are built as services according to service orientation principles. Finally, we analyse and discuss validation results of a case study to illustrate how the proposed approach works.
EPiCS: Evolution Phenomenology in Component-intensive Software

This paper briefly justifies and outlines initial plans for an empirical investigation into the evolution of component-intensive software systems. Questions to be addressed include whether the findings and observations of traditional software evolution studies garnered over the last 30 years or so, and most recently as part of the FEAST projects, apply to and are relevant in the context of component-intensive software. The goal of the suggested investigation is to contribute towards disciplined planning and management of long-term evolution of component-intensive software. In submitting this paper to the WESS 2001 workshop, the authors are presenting initial plans to obtain early exposure of the ideas and constructive criticisms from the empirical studies community.
Wisteria: Nurturing Scalable Data Cleaning Infrastructure

Analysts report spending upwards of 80% of their time on problems in data cleaning. The data cleaning process is inherently iterative, with evolving cleaning workflows that start with basic exploratory data analysis on small samples of dirty data, then refine analysis with more sophisticated/expensive cleaning operators (e.g., crowdsourcing), and finally apply the insights to a full dataset. While an analyst often knows at a logical level what operations need to be done, they often have to manage a large search space of physical operators and parameters. We present Wisteria, a system designed to support the iterative development and optimization of data cleaning workflows, especially ones that utilize the crowd. Wisteria separates logical operations from physical implementations, and driven by analyst feedback, suggests optimizations and/or replacements to the analyst's choice of physical implementation. We highlight research challenges in sampling, in-flight operator replacement, and crowdsourcing. We overview the system architecture and these techniques, then provide a demonstration designed to showcase how Wisteria can improve iterative data analysis and cleaning. The code is available at: http://www.sampleclean. org.
A case study of aerosol scavenging in a biomass burning plume over eastern Canada during the 2011 BORTAS field experiment

Abstract. We present measurements of a long-range smoke transport event recorded on 20–21 July 2011 over Halifax, Nova Scotia, Canada, during the Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS-B) campaign. Ground-based Fourier transform spectrometers and photometers detected air masses associated with large wildland fires burning in eastern Manitoba and western Ontario. We investigate a plume with high trace gas amounts but low amounts of particles that preceded and overlapped at the Halifax site with a second plume with high trace gas loadings and significant amounts of particulate material. We show that the first plume experienced a meteorological scavenging event, but the second plume had not been similarly scavenged. This points to the necessity to account carefully for the plume history when considering long-range transport since simultaneous or near-simultaneous times of arrival are not necessarily indicative of either similar trajectories or meteorological history. We investigate the origin of the scavenged plume, and the possibility of an aerosol wet deposition event occurring in the plume ~ 24 h prior to the measurements over Halifax. The region of lofting and scavenging is only monitored on an intermittent basis by the present observing network, and thus we must consider many different pieces of evidence in an effort to understand the early dynamics of the plume. Through this discussion we also demonstrate the value of having many simultaneous remote-sensing measurements in order to understand the physical and chemical behaviour of biomass burning plumes.
Workshop summary

I present a general overview of the results discussed during the Cracow 1997 workshop on “Relativistic Jets in AGNs”. My emphasis will be on showing the signiﬁcant progress made in several areas over the last few years, pointing out what I feel are some of the more important issues still facing us today
Milky Way demographics with the VVV Survey III. Evidence for a Great Dark Lane in the 157 Million Star Bulge Color-Magnitude Diagram

The new generation of IR surveys are revealing and quantifying Galactic features, providing an improved 3-D interpretation of our own Galaxy. We present an analysis of the global distribution of dust clouds in the bulge using the near-IR photometry of 157 million stars from the VVV Survey. We investigate the color magnitude diagram of the Milky Way bulge which shows a red giant clump of core He burning stars that is split in two color components, with a mean color difference of (Z-Ks)=0.55 magnitudes equivalent to A_V=2.0 magnitudes. We conclude that there is an optically thick dust lane at intermediate latitudes above and below the plane, that runs across several square degrees from l=-10 deg to l=+10 deg. We call this feature the "Great Dark Lane". Although its exact distance is uncertain, it is located in front of the bulge. The evidence for a large-scale great dark lane within the Galactic bulge is important in order to constrain models of the barred Milky Way bulge and to compare our galaxy with external barred galaxies, where these kinds of features are prominent. We discuss two other potential implications of the presence of the Great Dark Lane for microlensing and bulge stellar populations studies.
I/O-Optimal Distribution Sweeping on Private-Cache Chip Multiprocessors

The parallel external memory (PEM) model has been used as a basis for the design and analysis of a wide range of algorithms for private-cache multi-core architectures. As a tool for developing geometric algorithms in this model, a parallel version of the I/O-efficient distribution sweeping framework was introduced recently, and a number of algorithms for problems on axis-aligned objects were obtained using this framework. The obtained algorithms were efficient but not optimal. In this paper, we improve the framework to obtain algorithms with the optimal I/O complexity of $O(sort {P}(N) + K/PB)$ for a number of problems on axis-aligned objects, $P$ denotes the number of cores/processors, $B$ denotes the number of elements that fit in a cache line, $N$ and $K$ denote the sizes of the input and output, respectively, and $sort {P}(N)$ denotes the I/O complexity of sorting $N$ items using $P$ processors in the PEM model. To obtain the above improvement, we present a new one-dimensional batched range counting algorithm on a sorted list of ranges and points that achieves an I/O complexity of $O((N + K)/PB)$, where $K$ is the sum of the counts of all the ranges. The key to achieving efficient load balancing among the processors in this algorithm is a new method to count the output without enumerating it, which might be of independent interest.
Predictive ADAS: A predictive trajectory guidance scheme for advanced driver assistance in public traffic

In recent years, semi-autonomous vehicle control solutions have been aggressively developed in the form of various advanced driver assistance systems. It is expected that these developments will facilitate the eventual customer acceptance of fully autonomous vehicles. In this paper, we present a configuration of a nonlinear model predictive control scheme for predictive driver assistance. The human driver's steering and acceleration inputs to the vehicle are first interpreted into the driver-desired vehicle responses. These are then configured to be tracked by a coordination of the predictive and the lower level control systems as long as safe motion is predicted for these driver inputs. As soon as a violation of motion constraints is predicted from the driver inputs, the control scheme augments the driver inputs with active steering, brake and/or engine interventions so that the constraints of the vehicle dynamics, road boundaries and dynamic objects are respected. The performance of this proposed scheme is illustrated and discussed considering closed-loop-simulations of some typical driving events in public traffic.
Supporting viewpoints in Metaview

Metaview is a me&system that can generate automatically a variety of environments to support software engineering activities, such as requirement analysis and design. One of the strengths of Metaview is its capability to define and enforce constraints binding the software specification being developed. In this paper we show how we can use this capability to support and integrate various viewpoints, with the emphasis put on conflict detection and resolution.
Volumes of Nonnegative Polynomials, Sums of Squares and Powers of Linear Forms

We study the quantitative relationship between the cones of nonnegative polynomials, cones of sums of squares and cones of sums of powers of linear forms. We derive bounds on the volumes (raised to the power reciprocal to the ambient dimension) of compact sections of the three cones. We show that the bounds are asymptotically exact if the degree is fixed and number of variables tends to infinity. When the degree is larger than two it follows that there are significantly more non-negative polynomials than sums of squares and there are significantly more sums of squares than sums of powers of linear forms. Moreover, we quantify the exact discrepancy between the cones; from our bounds it follows that the discrepancy grows as the number of variables increases.
High-efficiency, long-term cardiac expression of foreign genes in living mouse embryos and neonates.

BACKGROUND The development of improved strategies for efficient and reproducible in vivo gene transfer into the murine heart will ultimately allow the intersection of somatic and germline gene transfer strategies to study complex features of cardiac biology and diseases. METHODS AND RESULTS For embryonic gene transfer, an adenovirus vector expressing beta-galactosidase was injected in utero into the ventricular cavity of living embryos via microsurgical approaches. The injected embryos were developed to term, and efficient expression of the transgene was detected in all cell types in the heart. For postnatal cardiac gene transfer, adenovirus was injected into the cardiac ventricle of neonatal mice, resulting in efficient expression of the transgene in the outer layer of the myocardium as well as cardiomyocytes in the middle and inner layers of the cardiac wall. Mice examined after 3 weeks displayed a pattern of expression that completely mimicked the pattern seen after 3 days, and gene expression was also found after 6 months. The infected myocytes can be identified by coinfection of an adenovirus expressing green fluorescent protein without affecting their normal physiological function. CONCLUSIONS We have developed a new strategy to achieve efficient and long-term foreign gene expression in both embryonic and postnatal mouse myocardium via direct intracardiac injection of recombinant adenovirus. The strategy should allow the functional assessment of the expression of dominantly acting exogenous genes, overexpression of wild-type genes, and Cre recombinase-mediated gene ablations at the single-cell level in the context of the intact adult mouse myocardium.
Blind and semi-blind maximum likelihood methods for FIR multichannel identification

We investigate maximum likelihood (ML) methods for blind and semi-blind estimation of multiple FIR channels. Two blind deterministic ML (DML) strategies are presented. In the first one, we propose to modify the iterative quadratic ML (IQML) algorithm in order to "denoise" it and hence obtain consistent channel estimates. The second strategy, called pseudo-quadratic ML (PQML), is naturally asymptotically denoised. Links between these two approaches are established and their global convergence is proved. Furthermore, we propose semi-blind ML techniques combining PQML with two different training sequence estimation methods and compare their performance. These semi-blind techniques, exploiting the presence of known symbols, outperform their blind version. They also allow channel estimation in situations where blind and training sequence methods fail separately. Simulations are presented to demonstrate the performance of all the proposed algorithms, and comparisons between them are discussed in a blind and/or semi-blind context.
BlindHelper: A Pedestrian Navigation System for Blinds and Visually Impaired

Notably valuable efforts have focused in helping people with special needs. Daily routine which is trivial for most of us is a real survival problem for groups of people with special needs and abilities, especially in a society with the bad habit to push to the side such people. This paper is focused on the problem of pedestrian navigation of visually impaired people. BlindHelper primarily enhances the ability of a visually impaired person to navigate efficiently to desired destinations without the aid of guides. Moreover it can provide multiple other uses during outdoor navigation such as dialing a call and notifying the current location in case of an emergency situation. The proposed system has been implemented as a smartphone application which interacts with a small embedded system responsible for reading simple user controls, high-accuracy GPS tracking of pedestrian mobility in real time, and identifying traffic light status and near-field obstacles along the route. This information is communicated to the smartphone application which in turn issues voice navigation instructions or undertakes further actions to help the user.
Algebraic Fault Attack on the SHA-256 Compression Function

The cryptographic hash function SHA-256 is one member of the SHA-2 hash family, which was proposed in 2000 and was standardized by NIST in 2002 as a successor of SHA-1. Although the differential fault attack on SHA-1compression function has been proposed, it seems hard to be directly adapted to SHA-256. In this paper, an efficient algebraic fault attack on SHA-256 compression function is proposed under the word-oriented random fault model. During the attack, an automatic tool STP is exploited, which constructs binary expressions for the word-based operations in SHA-256 compression function and then invokes a SAT solver to solve the equations. The simulation of the new attack needs about 65 fault injections to recover the chaining value and the input message block with about 200 seconds on average. Moreover, based on the attack on SHA-256 compression function, an almost universal forgery attack on HMAC-SHA-256 is presented. Our algebraic fault analysis is generic, automatic and can be applied to other ARX-based primitives.
Add-Drop Filter Based on Wavelength-Dependent Light Interlink between Lithium-Niobate Microwaveguide Chip and Microfiber Knot Ring

In this paper, we experimentally demonstrate an add-drop filter based on wavelength-dependent light coupling between a lithium-niobate (LN) microwaveguide chip and a microfiber knot ring (MKR). The MKR was fabricated from a standard single-mode fiber, and the LN microwaveguide chip works as a robust substrate to support the MKR. The guided light can be transmitted through add and drop functionality and the behaviors of the add-drop filter can be clearly observed. Furthermore, its performance dependence on the MKR diameter is also studied experimentally. The approach, using a LN microwaveguide chip as a platform to couple and integrate the MKR, may enable us to realize an optical interlink between the microstructured chip and the micro/nano fiber-optic device.
Recent CLEO-c results

Recent CLEO‐c results on open and closed charm physics at center‐of‐mass energy of 3773 MeV (ψ(3770) resonance), 4170 MeV and 3686 MeV (ψ(2S) peak) are reviewed. Measurements of absolute hadronic branching ratios of D0, D+ and Ds+ mesons as well as charmonium spectroscopy are discussed. An outlook and future prospects for the experiment at CESR is also presented.