Miracle-dz/UniFAR-FTUs huggingface dataset:
Path generation for scanning large-size equipment using industrial robot

In manufacturing industry or equipment painting fields, the equipment may have minor shape changes. In order to obtain a better fabrication or painting results, it is required to get an accurate on-site 3D data of the equipment rapidly. A new path generating method on industrial robot with 3D scanner is proposed in this paper. The main idea of the method is to obtain a coarse model of the equipment from the CAD and translate it into the robot coordinate system. Then the model is segmented into flatness zones. Meaningful zone information and collision detection are used to generate the scanning path which could be used by the robots directly. The simulation and the on-site experiment results show its effectiveness and feasibility using the ABB's 5400 robot and TOF depth camera.
Multi-Aspect, Robust, and Memory Exclusive Guest OS Fingerprinting

Precise fingerprinting of an operating system (OS) is critical to many security and forensics applications in the cloud, such as virtual machine (VM) introspection, penetration testing, guest OS administration, kernel dump analysis, and memory forensics. The existing OS fingerprinting techniques primarily inspect network packets or CPU states, and they all fall short in precision and usability. As the physical memory of a VM always exists in all these applications, in this article, we present OS-SOMMELIER+, a multi-aspect, memory exclusive approach for precise and robust guest OS fingerprinting in the cloud. It works as follows: given a physical memory dump of a guest OS, OS-SOMMELIER+ first uses a code hash based approach from kernel code aspect to determine the guest OS version. If code hash approach fails, OS-SOMMELIER+ then uses a kernel data signature based approach from kernel data aspect to determine the version. We have implemented a prototype system, and tested it with a number of Linux kernels. Our evaluation results show that the code hash approach is faster but can only fingerprint the known kernels, and data signature approach complements the code signature approach and can fingerprint even unknown kernels.
Slice culture of the olfactory bulb of Xenopus laevis tadpoles.

We report on the development of a slice culture of amphibian brain tissue. In particular, we cultured slices from Xenopus laevis tadpoles that contain the olfactory mucosae, the olfactory nerves, the olfactory bulb and the telencephalon. During 6 days in roller tubes the slices flattened, starting from 250 microm and decreasing to approximately 40 microm, corresponding to about three cell layers. Dendritic processes could be followed over distances as long as 200 microm. Neurons in the cultured slice could be recorded using the patch clamp technique and simultaneously imaged using an inverted laser scanning microscope. We characterized the main neuron types of the olfactory bulb, i.e. mitral cells and granule cells, by correlating their typical morphological features in the acute slice with the electrophysiological properties in both the acute slice and slice culture. This correlation allowed unambiguous identification of mitral cells and granule cells in the slice culture.
Development of a blood pressure monitoring system for home health application

A wireless physiological parameter monitoring system is presented in this paper for home health application. This system includes real time continuous collection and evaluation of physiological parameters like blood pressure, pulse rate and fall of an elderly at home. A reliable wireless personal area network like bluetooth has been used for this purpose. The hardware design of this system consists of sensors, PIC microcontroller, bluetooth module and mobile phone/laptop. This system provides safe and accurate monitoring. It also gives the freedom of movement.
PITM: Passive indoor object tracking with Markov probability estimation in wireless sensor networks

Exploiting Radio Signal Strength Indicator (RSSI) estimation method to conduct indoor localization in wireless sensor networks offers a new approach to serve object tracking and improve the tracking precision. When the object is closer the line-of-sight link between the transmitter and the receiver, it is more likely to arouse the attenuation or amplification of the RSSI signal. In this paper, the exponential model is used to analyze the fluctuation of the measured RSSI with the nodes, TT - CC2430, in the indoor environment. The indoor object tracking scenario is investigated through a Markov analytical model. The analysis based on Markov probability estimation lays a theoretical foundation on the object tracking process. Furthermore, PITM scheme is presented for object tracking based on the analytical results. The soundness of the analytical approach and the tracking accuracy of the PITM scheme are verified through extensive simulation, which also guides the design of more sophisticated indoor object tracking schemes.
Z-MERT: A Fully Configurable Open Source Tool for Minimum Error Rate Training of Machine Translation Systems

Z-MERT: A Fully Configurable Open Source Tool for Minimum Error Rate Training of Machine Translation Systems We introduce Z-MERT, a software tool for minimum error rate training of machine translation systems (Och, 2003). In addition to being an open source tool that is extremely easy to compile and run, Z-MERT is also agnostic regarding the evaluation metric, fully configurable, and requires no modification to work with any decoder. We describe Z-MERT and review its features, and report the results of a series of experiments that examine the tool's runtime. We establish that Z-MERT is extremely efficient, making it well-suited for time-sensitive pipelines. The experiments also provide an insight into the tool's runtime in terms of several variables (size of the development set, size of produced N-best lists, etc).
Formal representation of conflict zones in XACML access control systems

In this work we propose a new approach for handling the problem of detection and resolution of conflicts/anomalies between XACML (eXtensible Access Control Markup Language) policies. We give more attention to the mathematical formalism of the problem. We introduce the notion of the canonical representation of the query space. This is a partition of the query space formed by authorization classes. Each authorization class regroups queries that are intercepted by the same policies. This classification provides a natural way to handle interferences between policy targets (in other words conflicts /anomalies). Then we bring the study of the problem from the whole query space to elements of its canonical representation. After, we study the impact of adding and deleting policies from the policy repository on the canonical representation. This is important when this canonical representation is integrated as a part of a Framework for conflict detection and resolution in XACML access control systems.
Discovering Light Verb Constructions and their Translations from Parallel Corpora without Word Alignment

We propose a method for joint unsupervised discovery of multiword expressions (MWEs) and their translations from parallel corpora. First, we apply independent monolingual MWE extraction in source and target languages simultaneously. Then, we calculate translation probability, association score and distributional similarity of co-occurring pairs. Finally, we rank all translations of a given MWE using a linear combination of these features. Preliminary experiments on light verb constructions show promising results.
An Approach to Regression Test Selection Based on Hierarchical Slicing Technique

Regression testing is an important stage of software maintenance. Regression test selection is a key technique to test case reuse. Program slicing is one of these commonly used regression test selection techniques. The proposed slicing techniques for regression test selection are primarily for procedural program. Hierarchy slice, which is used for object-oriented programs according to the logical hierarchy of program, is able to compute slice step by step based on hierarchical slicing criterion. Compared to traditional slicing, hierarchical slicing technique can produce more precise slice especially for object-oriented program. This paper applies hierarchical slicing technique to regression test selection in order to improve the precision of regression test selection and address the problem of level. The approach computes hierarchy slice on the modified parts of program, then selects test cases from different levels in terms of test case coverage. This approach can select test cases from high level to low level of program. The initial experimental results present the effectiveness of applying hierarchical slicing in regression test selection.
High-Mobility Stable 4H-SiC MOSFETs Using a Thin PSG Interfacial Passivation Layer

Phosphorous from P<sub>2</sub>O<sub>5</sub> is more effective than nitrogen for passivating the 4H-SiC/SiO<sub>2</sub> interface. The peak value of the field-effect mobility for 4H-SiC metal-oxide-semiconductor field-effect transistors (MOSFETs) after phosphorus passivation is approximately 80 cm<sup>2</sup>/V·s. However, P<sub>2</sub>O<sub>5</sub> converts the SiO<sub>2</sub> layer to phosphosilicate glass (PSG)-a polar material that introduces voltage instabilities which negate the benefits of lower interface trap density and higher mobility. We report a significant improvement in voltage stability with mobilities as high as 72 cm<sup>2</sup>/V·s for MOSFETs fabricated with a thin PSG gate layer ( ~ 10 nm) capped with a deposited oxide.
Cosmological implications of APM 08279+5255, an old quasar at z= 3.91

The existence of old high-redshift objects provides an important tool for constraining the expanding age of the Universe and the formation epoch of the first objects. In a recent paper, Hasinger, Schartel & Komossa reported the discovery of the quasar APM 08279 + 5255 at redshift z= 3.91 with an extremely high iron abundance, and estimated age of 2–3 Gyr. By assuming the lower limit for this age estimate and the latest measurements of the Hubble parameter as given by the HST key project, we study some cosmological implications from the existence of this object. In particular, we derive new limits on the dark matter and vacuum energy contribution. Our analysis is also extended to quintessence scenarios in which the dark energy is parametrized by a smooth component with an equation of state px=ωxρx (−1 ≤ωx < 0). For flat models with a relic cosmological constant we show that the vacuum energy density parameter is constrained to be ΩΛ≥ 0.78, a result that is marginally compatible with recent observations from type Ia supernovae (SNe Ia) and cosmic microwave background (CMB). For quintessence scenarios the same analysis restricts the cosmic parameter to ωx≤−0.22. Limits on a possible first epoch of quasar formation are also briefly discussed. The existence of this object pushes the formation era back to extremely high redshifts.
The impacts of restricting housing supply on house prices and affordability: final report

The research explores the underlying causes of the English housing affordability crisis. The report finds causal evidence that regulatory constraints have had a serious negative long-run impact on housing affordability and have increase house price volatility. The report goes on to propose the alternative solution of providing greater incentives to Local Planning Authorities to better incentivise residential development.
Opportunistic Reasoning for the Semantic Web: Adapting Reasoning to the Environment

Despite the efforts devoted so far, the Semantic Web vision appears to be an eluding target. We propose a paradigm shift for the Semantic Web centred around the pragmatics of developing Semantic Web applications in order to overcome the bootstrapping problem it suffers from. This paradigm is based on the vision of the Semantic Web as the result emerging from the integration and collaboration of a plethora of Semantic Web applications, rather that as a global entity. On the basis of this assumption we describe and propose Opportunistic Reasoning as a general purpose reasoning model suitable for the development of reasonably scalable Semantic Web applications.
Data Transmission in the Presence of Limited Channel State Information Feedback

Foreword Modern wireless systems include key technologies such as multiuser diversity, adaptive transmission, multiple-input multiple-output (MIMO) processing and cooperative data communication networks. Common for all these technologies is that the feedback of channel state information (CSI) is necessary, as it is exploited for adapting the transmission parameters, scheduling, etc. The CSI is normally obtained by direct estimation of the channel coefficients at the receiver and somehow informing the transmitter about the obtained complex fading coefficients. The more information available at the transmitter, the better performance can be achieved. However, depending on the channel characteristics, number of transmit/receive antennas, etc., the rate of the feedback information may be so high that it will consume much of the capacity in the reverse link, making the whole system impractical. Therefore, it has often been questioned whether the improved system performance due to CSI feedback is worth the additional feedback rate and the increased implementation complexity. Thus, different CSI feedback compression techniques have been of interest during the last two decades. In the thesis, we consider two different approaches, namely, quantized CSI feedback and automatic repeat request (ARQ), providing the imperfect channel quality information at the transmitter. Implementing a quantized CSI feedback scheme, the receiver provides the transmitter with some rough measure of the channel gain before transmission, and the transmitter adjusts its transmission parameters according to this imperfect information. Rough CSI is normally produced by channel gain quantization at the receiver where the set of all possible channel gains is partitioned into a number of non-overlapping regions. The instantaneous channel gain being in a region, its representing symbol is sent back and the transmitter selects the codewords transmission parameters such that the system performance is optimized. The ARQ, on the other hand, is a well-known approach applied in today's networks to increase the transmission reliability in the absence of the transmitter CSI. From an information-theoretic point of view, the ARQ systems can be viewed as channels with sequential feedback where the transmitter CSI is refined in the retransmissions based on the message decoding status. In a general ARQ approach, the transmitter considers some initial transmission rate and power with no pre-knowledge about the channel quality. Then, with the help of ARQ, the decoding status at the receiver will be reported back to the transmitter via one bit feedback. Based on the received feedback, it is decided by the transmitter whether to retransmit the …
Fully Bayesian Source Separation of Astrophysical Images Modelled by Mixture of Gaussians

We address the problem of source separation in the presence of prior information. We develop a fully Bayesian source separation technique that assumes a very flexible model for the sources, namely the Gaussian mixture model with an unknown number of factors, and utilize Markov chain Monte Carlo techniques for model parameter estimation. The development of this methodology is motivated by the need to bring an efficient solution to the separation of components in the microwave radiation maps to be obtained by the satellite mission Planck which has the objective of uncovering cosmic microwave background radiation. The proposed algorithm successfully incorporates a rich variety of prior information available to us in this problem in contrast to most of the previous work which assumes completely blind separation of the sources. We report results on realistic simulations of expected Planck maps and on WMAP 5th year results. The technique suggested is easily applicable to other source separation applications by modifying some of the priors.
Anti-α4 Integrin Antibody Blocks Monocyte/Macrophage Traffic to the Heart and Decreases Cardiac Pathology in a SIV Infection Model of AIDS

Background Cardiovascular disease (CVD), myocarditis and fibrosis are comorbidities of HIV+ individuals on durable antiretroviral therapy (ART). Although mechanisms for these vary, monocytes/macrophages are increasingly demonstrated to be key players. Methods and Results We directly blocked monocyte/macrophage traffic to the heart in an SIV model of AIDS using an anti-alpha-4 integrin antibody (natalizumab). Nineteen Rhesus macaques were SIVmac251 infected and CD8-lymphocyte depleted for the development of rapid AIDS. Ten animals received natalizumab once a week, for 3 weeks, and were sacrificed 1 week later. Six animals began treatment at the time of infection (early) and the remaining 4 began treatment 28 days post-infection (late), a time point we have previously established when significant cardiac inflammation occurs. Nine animals were untreated controls; of these, 3 were sacrificed early and 6 were sacrificed late. At necropsy, we found decreased SIV-associated cardiac pathology in late natalizumab-treated animals, compared to untreated controls. Early and late treatment resulted in significant reductions in numbers of CD163+ and CD68+ macrophages in cardiac tissues, compared to untreated controls, and a trend in decreasing numbers of newly recruited MAC387+ and BrdU+ (recruited) monocytes/macrophages. In late treated animals, decreased macrophage numbers in cardiac tissues correlated with decreased fibrosis. Early and late treatment resulted in decreased cardiomyocyte damage. Conclusions These data demonstrate a role for macrophages in the development of cardiac inflammation and fibrosis, and suggest that blocking monocyte/macrophage traffic to the heart can alleviate HIV- and SIV-associated myocarditis and fibrosis. They underscore the importance of targeting macrophage activation and traffic as an adjunctive therapy in HIV infection.
Safe and robust robot maneuvers based on reach control

In this paper, we investigate the synthesis of piecewise affine feedback controllers to address the problem of safe and robust controller design in robotics based on high-level controls specifications. The methodology is based on formulating the problem as a collection of reach control problems on a polytopic state space. Reach control has so far only been developed in theory and has not been tested experimentally on a real system before. Using a quadrocopter as our experimental platform, we show that these theoretical tools can achieve fast, albeit safe and robust maneuvers. In contrast to most traditional control techniques, the reach control approach does not require a predefined open-loop reference trajectory or spacial path. Experimental results on a quadrocopter show the effectiveness and robustness of this control approach. In a proof-of-concept demonstration, the reach controller is implemented in one translational direction while the other degrees of freedom are stabilized by separate controllers.
Controlling the complexity of grouped items in colour interfaces

In this paper we describe a method of managing the complexity that arises when automatically colouring a realistic GUI interface. This complexity primarily comes from two sources, from the number of items to be coloured - which in interfaces of realistic complexity grows very quickly - and from the interactions between both the items' colours themselves and their background colour. Attempting to satisfy the relationships between the colours of items in an interface, their backgrounds, whether items may be coloured identically or must be distinct, and all the while creating a colour scheme that is harmonious requires multiple constraints be satisfied simultaneously. The addition of visually related groups of screen elements complicates this optimisation. The use of spring-based algorithms will allow groups to have their own local colour schemes (sub-schemes) while still satisfying the need for overall colour harmony.
CD4 Receptor is a Key Determinant of Divergent HIV-1 Sensing by Plasmacytoid Dendritic Cells

Plasmacytoid dendritic cells (pDC) are innate immune cells that sense viral nucleic acids through endosomal Toll-like receptor (TLR) 7/9 to produce type I interferon (IFN) and to differentiate into potent antigen presenting cells (APC). Engagement of TLR7/9 in early endosomes appears to trigger the IRF7 pathway for IFN production whereas engagement in lysosomes seems to trigger the NF-κB pathway for maturation into APC. We showed previously that HIV-1 (HIV) localizes predominantly to early endosomes, not lysosomes, and mainly stimulate IRF7 rather than NF-κB signaling pathways in pDC. This divergent signaling may contribute to disease progression through production of pro-apoptotic and pro-inflammatory IFN and inadequate maturation of pDCs. We now demonstrate that HIV virions may be re-directed to lysosomes for NF-κB signaling by either pseudotyping HIV with influenza hemagglutinin envelope or modification of CD4 mediated-intracellular trafficking. These data suggest that HIV envelope-CD4 receptor interactions drive pDC activation toward an immature IFN producing phenotype rather than differentiation into a mature dendritic cell phenotype.
Improved Fast Two Cycle by using KFCM Clustering for Image Segmentation

Among available level set based methods in image segmentation, Fast Two Cycle (FTC) model is efficient and also the fastest one. But its efficiency is highly dependent to contour initialization. This paper tries to improve this method by using a kernel-based fuzzy c-means (KFCM) clustering algorithm. The proposed approach consists of two successive stages for image segmentation. Firstly, the KFCM is used to cluster the input image. Then ROI's fuzzy membership matrix is used for next stage as an initial contour. Eventually, FTC model is utilized to segment the image by curve evolution based on level set. As a result, two benefits are provided for image segmentation in addition of advantages of FTC model. They are independency of curve initialization and reduction of user intervention. Experimental results show promising outputs in segmentation of different kinds of image including medical data imagery, natural scene and synthetic data.
Vehicular platooning experiments with LEGO MINDSTORMS NXT

The paper reports on experimenting with a popular introductory robotics toolkit LEGO® MINDSTORMS® NXT that was aimed at demonstrating a few algorithms for distributed control of a long platoon of autonomous vehicles. The configuration used in this report measures the distance to the vehicle ahead and the velocity of the vehicle itself. The acquired technical experience with this platform is shared in the report, including recommendation towards improvements.
A New Method for Trajectory Control of Mobile Robots Using Artificial Neural Networks

An approach based on neural networks to the navigation control of mobile robots is presented in this paper. The problem of driving a mobile robot to a goal in an unknown environment is formulated as a neural control problem in which local information are used to make steering and velocity decisions while the robot is moving. The artificial neural network maps the input signals representing the mobile robot state space determined by sensor readings to the output signals representing mobile robot action space. We propose a direct and effective method using sensory data in order to design the artificial neural network. Simulation results show that the technique proposed here has provided satisfactory results. Key-Words: Mobile robots, neural networks, system identification, intelligent systems, motion planning, feedforward networks.