Miracle-dz/UniFAR-FTUs huggingface dataset:
Steady-state and transient-state analyses of TCP and TCP-friendly rate control mechanism using a control theoretic approach

In recent years, various real-time applications in the Internet have been emerging with rapid increase of the network bandwidth. A real-time application traditionally uses either UDP (User Datagram Protocol) or TCP (Transmission Control Protocol) as its transport layer protocol. However, using either UDP or TCP is insufficient for most real-time applications because of lacking a smooth rate control mechanism or suffering a significant transfer delay. In the literature, several transport-layer communication protocols for real-time applications have been proposed. In this paper, among these transport-layer communication protocols, we focus on TFRC (TCP-Friendly Rate Control). Steady state performances of TCP and TFRC connections such as throughput and fairness have been throughly investigated by many researchers using simulation experiments. However, transient state properties of TCP and TFRC connections such as stability and responsiveness have not been investigated. In this paper, we therefore analyze both steady state and transient state performances of TCP and TFRC connections using a control theoretic approach. We frist model TFRC and TCP connections with different propagation delays and the active queue management mechanism of RED (Random Early Detection) router as independent discrete-time systems. By combining these discrete-time systems, we analyze steady state performance of TCP and TFRC connections such as throughput, transfer delay, and packet loss probability. We also analyze transient state performance of TCP and TFRC connections using linearization of discrete-time systems around their equilibrium points.
A 40-nm CMOS E-Band 4-Way Power Amplifier With Neutralized Bootstrapped Cascode Amplifier and Optimum Passive Circuits

This paper reports a fully integrated 40-nm CMOS power amplifier (PA) for E-band applications. A neutralized bootstrapped cascode amplifier (NBCA) topology is proposed to enhance the power gain and output power at millimeter wave (mm-Wave) frequencies while maintaining the stability. A broadband 4-way differential parallel-series power combiner is employed to further increase the output power. Besides, both interstage and input passive networks are optimized to improve the bandwidth and common-mode stability. Occupying 0.25 mm2, the proposed PA achieves a measured output power of 22.6 dBm with 19.3% peak power-added efficiency (PAEMAX). The 2-stage PA has a measured power gain of 25.3 dB.
Wide bandwidth low complexity isolated current sensor to be employed in a 10 kW/500 kHz three-phase unity power factor PWM rectifier system

A current sensor employing a Hall-based field sensing ASIC in combination with a current transformer is proposed. The sensor is characterized by a measuring range of /spl plusmn/50 A, an upper bandwidth limit of 20 MHz and high dV/dt-immunity up to 10 kV//spl mu/s. The sensor functional principle and dimensioning are discussed in detail. Parameters determining the sensor bandwidth are clarified, the theoretical considerations are verified by experiments. Finally, measures for further increasing the sensor bandwidth are proposed.
Level-Ups: Motorized Stilts that Simulate Stair Steps in Virtual Reality

We present "Level-Ups", computer-controlled stilts that allow virtual reality users to experience walking up and down steps. Each Level-Up unit is a self-contained device worn like a boot. Its main functional element is a vertical actuation mechanism mounted to the bottom of the boot that extends vertically. Unlike traditional solutions that are integrated with locomotion devices, Level-Ups allow users to walk around freely ("real-walking"). We present Level-Ups in a demo environment based on a head-mounted display, optical motion capture, and integrated with two different game engines. In a user study, participants rated the realism of stepping onto objects 6.0 out of 7.0 when wearing Level-Ups compared to 3.5 without.
Targeting breast cancer stem cells by dendritic cell vaccination in humanized mice with breast tumor: preliminary results

Background Breast cancer (BC) is one of the leading cancers in women. Recent progress has enabled BC to be cured with high efficiency. However, late detection or metastatic disease often renders the disease untreatable. Additionally, relapse is the main cause of death in BC patients. Breast cancer stem cells (BCSCs) are considered to cause the development of BC and are thought to be responsible for metastasis and relapse. This study aimed to target BCSCs using dendritic cells (DCs) to treat tumor-bearing humanized mice models. Materials and methods NOD/SCID mice were used to produce the humanized mice by transplantation of human hematopoietic stem cells. Human BCSCs were injected into the mammary fat pad to produce BC humanized mice. Both hematopoietic stem cells and DCs were isolated from the human umbilical cord blood, and immature DCs were produced from cultured mononuclear cells. DCs were matured by BCSC-derived antigen incubation for 48 hours. Mature DCs were vaccinated to BC humanized mice with a dose of 106 cells/mice, and the survival percentage was monitored in both treated and untreated groups. Results The results showed that DC vaccination could target BCSCs and reduce the tumor size and prolong survival. Conclusion These results suggested that targeting BCSCs with DCs is a promising therapy for BC.
A Force Field Method Based Multi-Robot Collaboration

A force field (F2) based multi-robot collaboration method is presented in this paper. In this method, a virtual force field is generated for every moving robot and continuously changing based on the robot status including its traveling speed, dimension, priority, location and environment, etc. The interactions among robots' force fields and obstacles provide a natural way for collision avoidance and collaboration while robots are on their way to goals. In this paper, the definition of reaction force direction is modified to reduce robot orientation oscillations which occur when a robot approaches obstacles or other robots. Then the influence of task priority on motion planning and the problem of deadlock in multi-robot cases are discussed. Simulations in a real indoor environment were carried out and demonstrated the feasibility and effectiveness of this method
Ranking ontologies in the Ontology Building Competition BOC 2014

Due to the constantly increasing amount of ontologies available, the need for tools supporting ontology evaluation and ranking is crucial. In this paper, we present a Web tool for evaluating and ranking ontologies. The ontologies are evaluated against various structural and semantic metrics. We describe the metrics developed for the ranking system and present the system's results in the context of the Ontology Building Competition 2014 - a learning environment for developing ontologies.
A Pilot Study of EMG Pattern Based Classification of Arm Functional Movements

Most previous studies of electromyography (EMG) pattern recognition with both able-bodied subjects and amputees for control of multifunctional prostheses had verified high performance in identifying different movements. While these movements mostly refer to single joint, it remains unclear whether the functional tasks involved in arm and hand could be discriminated by using EMG pattern based methods. In this pilot study, we investigated the performance of EMG pattern recognition in classifying eight functional movements plus a “no movement” task. Four kinds of EMG feature sets, time-domain (TD) features, auto-regression (AR) model features, combination of TD and AR features, and wavelet packet coefficients, were used to represent the EMG patterns, respectively. Using a linear discriminant analysis classifier, the TD features outperformed other three feature sets. The average classification accuracy of the TD features across four able-bodied subjects was greater than 94%. And the feasibility of EMG channels reduction was estimated with straightforward exhaustive search algorithm in terms of classification accuracy. The average classification accuracy of all 8-channel EMG combinations could achieve above 90%. This result was encouraging and suggested that it is feasible to use EMG pattern recognition for the classification of functional movements.
Hierarchical OBB-sphere tree for large-scale range data management

Recent research has shown that range data acquired from consumer imaging devices are successfully used to build accurate 3D geometric models of surrounding environments very quickly. However, as the volume of modeling space grows, its processing time inevitably becomes huge when a simple linear data structure is used to handle a large range data set. The main difficulty is that pairwise scan matching among all pairs of input data requires quadratic computational complexity. The OBB-sphere tree presented in this paper accelerates the process by intelligently choosing a subset of related pair candidates. The proposed data structure is an enhanced sphere tree in which every leaf node contains a set of 3D points computed from a depth image and bounded by one sphere and one tighter-fitting shape, which is the oriented bounding box (OBB). This approach exploits the simplicity of spheres in hierarchical tree construction and the intersection test which is performed to reject objects that are far apart. The compactness of OBBs is used to refine the results of the intersection test. The number of possible pairs was reduced by more than half in some test datasets in the experiment.
Video stabilization based on the detection and alpha-trimmed means smoothing filtering of undesirable motion

This paper presents video stabilization based on detection and adaptive alpha-trimmed means smoothing filtering of undesirable motion. The proposed algorithm consists of two stages: the detection of undesirable motion and smoothing filtering of detected undesired motion. To incorporate desired properties into the motion smoothing process, the local maximum and the local minimum are defined in a set composed of the parameters of accumulative global motion. Using the local information, the constraints on detecting undesirable motions are defined. Based on these constraints, the alpha parameter of the alpha-trimmed means filter is adjusted, so that the degree of motion smoothing in the reconstructed video sequence is controlled. The experimental results demonstrated the capability of the proposed algorithm.
Positive solutions for nonlinear singular boundary value problems on the half line

We discuss the existence of positive solutions for singular secondorder boundary value problems x �� = µf(t,x,x � ), ax(0) − bx � (0) = k ≥ 0, x � (∞) = 0, where f may be singular at x = 0 and x � = 0 and can change sign. Via fixed point theory, we establish the existence of positive solutions under some conditions on f. Our results deal with the situation where the solutions approach the singularities of the equation.
A Reflexive and Interactive Approach on novice-Based Data Collection to Investigate Information Infrastructure (II)

From the practice lens the use of artefacts is subject to implicit logic, tacit know-how, and embodied practical sense and is constantly negotiated in the context of performance and within a constellation of practices. We argue that this theoretical approach provides useful assumptions to study Information Infrastructure (II) beyond the conventional understanding of II as “tubes and wires”. Bringing practices into perspective we aim at better understanding the unexpected outcome of II development projects in healthcare. Methodically, this research requires a strategy to trap the opacity of practice. Being an expert transcends technical rationality and is built up from practice which tends to be tacit. Infrastructure is embedded into opaque work practices and transparent to use. Taking this methodical problem into account we suggest studying practices by novice practitioners as they are not yet “practice blind”. By diary writing they contribute to data collection. This idea allows analysing practices ‘from inside’, however puts the researcher in a novel position and bears methodical challenges. By suggesting a reflexive and interactive methodological approach we aim at contributing to practice-based research methods. In this paper we discuss our approach and results based on a first run with pharmacists in practical training.
Integration of geometric and dynamic features for facial expression recognition in color image sequences

This work proposes a new approach for facial expression recognition in color image sequences, based on integrated evaluation of geometric and dynamic features. For this purpose a series of methods is introduced that on the one hand achieve high recognition rates for expressive facial behavior and on the other hand address a couple of common problems in this area of research. In particular we apply physiologically motivated image regions for the detection of dynamic features by using an optical flow method. In this way dynamic features capture the variations caused by facial expression changes. Opposed, geometric features do not contain temporal information but describe spatial feature parameters. These correspond to 3-D based Euclidean distances and angles. Particularly, the hypothesis of this work is that through integrated evaluation of geometric and dynamic features, improved recognition rates can be achieved. Based on comprehensive experimental investigations we show the advantage of the suggested approach.
Quantification Issues in Bolus-Tracking Perfusion MRI

Bolus-tracking perfusion MRI is based on the monitoring of the first passage of a bolus of contrast agent through the brain tissue and a brain-feeding artery. The contrast agent is injected rapidly in the antecubital vein in the patients arm by means of an MR-compatible power injector. This bolus of contrast agent is pushed in the direction of the heart by means of a saline flush. Continuous dynamic scanning with a typical temporal resolution of approximately 1-2 second is used to monitor the passage of the contrast agent through the brain tissue and a brain-feeding artery. The change in MR signal is hereafter converted into the concentration of contrast agent based on the physical properties of the contrast agent. The time evolution of the concentration of contrast agent in the brain-feeding artery is called the arterial input function. Deconvolving the passage through the brain tissue with the arterial input function, results in the tissue response function. Based on the theory of tracer kinetics, perfusion parameters are calculated from this tissue response function. To achieve quantitative measures of perfusion, all these different aspects should be considered.
Reconstructing a 3 D Model from Range Images Using Radial Flow

The reconstruction of a 3D model from range images can be conveniently split into two stages. The rst stage consists basically in the extraction of geometrical information, e.g. the depth and the orientation of image points, and the second stage concentrates on the transformation of these data to a 3D model. In this paper we focus on the second stage. Our approach is based on a deformable model, which ooers more exibility to mold a 3D model according to several geometrical constraints. Moreover, instead of looking for a global functional that carries out the deformation, we opted for establishing discrete local correspondences between 3D surface point data extracted from images and 3D model points.
Sensor Fusion for Intuitive Robot Programming

Fusion of information from multiple sensors can greatly enhance the performance of human-machine interaction, especially in the intuitive robot programming. The methods aim to allow rapid teaching of robotic tasks in a safe and efficient manner. The techniques can reduce the setup time of a robotic system. This is crucial for SMEs (Small and Medium Enterprise) where the products in the manufacturing area are in small lot size but with high batch mix. The objective of this research is to fuse the information from a range sensor and a camera. An unique method using the surface constraint has been adopted for the calibration of the sensor fusion system. By taking the surface normal of a calibration board as the common feature, the transformation between the two coordinate systems can be formulated. The end result is a fused scene with both range and texture (color in this case) information. The range information will be used for the path generation for robotic tasks. On the other hand, the images captured by the camera together with the graphical user interface provide an user friendly interface platform for the user. As the two images have been fused, the operator can program a path for a robot to execute by 'point-and-click' on the user interface screen. Experimental results have shown that the new method of robot programming, with sensor fusion information, has improved the robotic teaching process by at least 90% as compared to the manual programming method using teaching pendant.
Diffusion Scheme for Noise Reduction Using Cellular Automata

Cellular automata is a methodology that uses a discrete space to represents the state of each element of a domain, and this states can be changed according to a transition rule. In this work we use cellular automata to represent a digital image and to develop new diffusion scheme in a way to reduce the noise of the image. Then, the processed image will be converted in a binary one to perform segmentation. The main contribution is the fact that the proposed diffusion method works well in images with high noise intensity and the computational cost is small. We apply the methodology for medical images segmentations.
Design, Implementation, and Analysis of a Multimedia Indexing and Delivery Server

While text indexing on the Web and corporate intranets has received considerable attention, indexing of multimedia documents in the same environments is still in its nascent stages. We have developed a system that allows us to index and serve multimedia documents over the Internet. The system has been in continuous operation since March 1998 within the company and has been tested extensively under heavy load conditions. In this paper we describe the design and implementation of the system and we present a user-model study indicating the usage patterns that we encountered during the system deployment. The main part of the paper presents the results of a detailed study that sheds light into the performance characteristics of the system components, identifies bottlenecks, and provides information to systems designers interested in delivering systems with good performance for this important class of applications. We find that the limiting factor for the three major subcomponents that comprise the indexing service is the memory system performance, while the component responsible for delivering the video/audio bits to the users is only limited by the bandwidth of our Internet connection. Surprisingly, I/O is not a bottleneck on our system despite the large amount of disk space consumed by the multimedia data. c Compaq Computer Corporation, 1999 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of the Cambridge Research Laboratory of Compaq Computer Corporation in Cambridge, Massachusetts; an acknowledgment of the authors and individual contributors to the work; and all applicable portions of the copyright notice. Copying, reproducing, or republishing for any other purpose shall require a license with payment of fee to the Cambridge Research Laboratory. All rights reserved. CRL Technical reports are available on the CRL’s web page at http://www.crl. research.digital. com. Compaq Computer Corporation Cambridge Research Laboratory One Kendall Square, Building 700 Cambridge, Massachusetts 02139 USA
DiG: Data-centers in the Grid

We are witnessing a considerable amount of research work related to data center and cloud infrastructures but evaluations are often limited to small-scale scenarios as very few researchers have access to a real infrastructure to confront their ideas to reality. In this demo we will reveal our experiment automation tool, DiG (Data centers in the Grid), which explicitly allocates physical resources in grids to emulate data center and cloud networks. DiG allows one to utilize grid infrastructures to evaluate research ideas pertaining to data centers and cloud environments at massive scale and with real traffic workload. We have automated the procedure of building target network topologies while respecting available physical resources in the grid against the demand of links and hosts in the experiment. We will present a showcase where DiG automatically builds a large data center topology composed of hundreds of servers executing various Hadoop intensive workloads.
Coordinated motion of a new staircase climbing wheelchair with increased passenger comfort

This paper describes the mechanical devices, the movements and the trajectory generation of a novel wheelchair prototype capable of climbing staircases. The key feature of the mechanical design is the use of two decoupled mechanisms for each axle, one used to negotiate steps, and the other to position the axle with respect to the chair to accommodate the overall slope. This decoupling makes many different climbing strategies possible, the overall mechanism becoming extraordinarily versatile from a control point of view. A control system is necessary to synchronize the movements of all the actuators of the wheelchair so that its centre of mass can follow arbitrary spatial trajectories. Different trajectories have been designed in order to keep the seat as erect as possible to guarantee passenger comfort. Experimental results with the real prototype are reported which show the efficiency of our mechanism, the accuracy of the developed kinematic models for control, and the comparison of comfort for two different spatial trajectories
Research of cues selection in pedestrian detector based on adaboost

Which cues to be used in describing pedestrian are the key to detect pedestrian with Adaboost algorithm. In this paper we presented 4 triangle cues and 16 complex cues by researching on pedestrianpsilas figures and proposed the way to calculate these cuespsila sum. To evaluate this calculating method, we proved the relation of iterative times with error and time spending. Compared with rectangle and asymmetry cues, triangle and complex cues are better in describing local characteristics of peoplepsilas appearance and designing pedestrian detector. The experiment indicated that triangle and complex cues can be used in constructing robust classifier to detect pedestrian.
Line-based 3D Reconstruction of Wiry Objects

Man-made environments contain many weakly textured surfaces which are typically poorly modeled in sparse point reconstructions. Most notable, wiry structures such as fences, scaffolds, or power pylons are not contained at all. This paper presents a novel approach for generating line-based 3D models from image sequences. Initially, camera positions are obtained using conventional Structurefrom-Motion techniques. In order to avoid explicit matching of 2D line segments in the various views we exploit the epipolar constraints and generate a series of 3D line hypotheses, which are then verified and clustered to obtain the final result. We show that this approach can be used to densify various sparse occupied point clouds of urban scenes in order to obtain a meaningful model of the underlying structure.