Miracle-dz/UniFAR-FTUs huggingface dataset:
Traffic parameter extraction using video-based vehicle tracking

We propose a vehicle tracking algorithm that takes a new occlusion reasoning approach. We consider two different types of occlusions: explicit occlusion and implicit occlusion. We also propose a traffic flow extraction method with the velocity and trajectory of the moving vehicles. The proposed vehicle tracking system is composed of three parts: vehicle segmentation, vehicle tracking, and traffic parameter extraction. The vehicle segmentation part separates moving vehicles from their background. We employ the adaptive background approach, which does not update the background of moving objects. We also design a 2D token-based algorithm for vehicle tracking using Kalman filtering that has a modest amount of computational complexity. The traffic parameter extraction part estimates the traffic parameters, such as the vehicle count and the average speed. It also extracts the traffic flows. Finally, we have evaluated the proposed algorithm with some MPEG-7 test sequences.
BIT: BYTECODE INSTRUMENTING TOOL

BIT: Bytecode Instrumenting Tool Thesis directed by Associate Professor Benjamin Zorn BIT (Bytecode Instrumenting Tool) is a set of interfaces that allows one to build customized tools to instrument Java Virtual Machine (JVM) bytecodes. To better understand program behavior, researchers and software developers have built numerous tools that carry out program analysis. Understanding the dynamic behavior of a program is important in improving program performance, in identifying critical parts of a program, and in measuring the effectiveness of different algorithms. The JVM is an abstract machine specification designed to support the Java programming language, which has become very popular during the last few years. Although there are tools that analyze and modify executables on a variety of operating systems and machine architectures, there currently is no framework for carrying out the same task for bytecodes, which are the binaries that the JVM interprets. In this thesis, we describe BIT, which allows researchers and software developers to instrument bytecodes to understand their dynamic behavior. To design and implement BIT, we investigated and studied different approaches for instrumenting executables as well as the inner workings of the JVM and the class files that contain bytecodes. We implemented BIT using the Java programming language, and it can be used on any platform that has an implementation of the JVM. BIT allows the user to insert calls to analysis methods anywhere in the bytecode, so that information can be extracted from the user program iv while it is being executed. This information, in turn, could be used in performance measurement and optimization. BIT is the first framework that allows researchers and software developers to create customized tools to analyze JVM bytecodes. A number of different tools ranging from dynamic instruction counters to path profilers could be built using BIT. In this thesis, we describe several customized applications that use BIT and also report on BIT's performance. We found that for a smaller program, the overhead for the execution speed and size were between 15% to 37%, while for a larger program, the overhead for the execution speed was about two times the original execution time. v ACKNOWLEDGEMENTS First, I would like to thank everyone who helped me with his or her suggestions and support during my master's study at the University of Colorado at Boulder. I would like to especially thank my thesis advisor, Benjamin Zorn, whose valuable insights, helpful suggestions, and patience were …
FAS A flexible Antagonistic spring element for a high performance over actuated hand

In robotic hands design tendon driven systems have been considered for years. The main advantage is a small end effector inertia e.g. a light, small hand with high dynamics due to remote actuators. To protect the actuators from impact in unknown environments a compliant mechanism can be used. It absorbs energy during an impact or saves energy to enhance the joint dynamics. In this paper an antagonistic tendon mechanism is presented. It fits 38 times in the DLR Hand Arm System forearm and enables is adapted to the different finger joints and different tendon lengths. A magnetic sensor was developed for the force measurement of the tendons. Finally, the calibration and the robustness are demonstrated through a set of experiments.
On the relevance of the 3D retinal vascular network from OCT data

Summary Abnormal patterns of the retinal vascular system have been associated with several heart and cerebral diseases. However, these correlations were obtained using 2D imaging of the eye fundus, disregarding information on the third component (depth) of the vascular system. In this paper, we show that the depth component is relevant and should not be disregarded in this analysis. In this way, the relevance of analysis of the retinal vascular network as a biometrical marker for the general health status of an individual can be increased.
Control and optimization methods in communication network problems

The authors focus on two areas of communication network design in which methods of control and optimization theory have proven useful. These are the area of multiple access communication (for networks with shared links such as radio networks and local area networks) and the area of network routing (for networks with point-to-point interconnections). They review a few selected problems in each area to show the role of the control concepts involved and then proceed to identify other areas of communication network design in which the same control theoretic and optimization methodology may be applicable and useful. They attempt to bring to the attention of the control systems community the numerous instances of problems arising in the pure communication network design process that can benefit from the attention and the capabilities of this community. >
Electrochemical Formation of Methoxy- and Cyano(phenylazo)alkanes from Aldehyde and Ketone Phenylhydrazones

Several aldehyde and ketone phenylhydrazones were electrooxidized in MeOH. Electrooxidation in the presence of KI or tetraethylammonium p-toluenesulfonate as the supporting electrolyte afforded the corresponding methoxy(phenylazo)alkanes. whereas electrooxidation in the presence of KI, NaCN, and HOAc afforded the cyano(phenylazo)alkanes.
Distributed detection with multiple sensors I. Advanced topics

Following the foundational work that established basic ideas for optimum distributed defection schemes using multiple sensors (as reviewed in Part I of this two-part review), further work on distributed detection has developed many useful and interesting extensions of the basic concepts. These more recent developments parallel those that arose from the early work on centralized, classical signal detection, resulting in new ideas of asymptotically optimum nonparametric, robust, and sequential centralized detection. Recent developments on these topics in the setting of distributed signal detection are reviewed in the present paper. Results in these directions are important in practice because they allow cases of modeling uncertainty to be addressed, and they provide more efficient detection schemes by optimizing more general performance criteria.
Identification of nonlinear dynamic systems with recurrent neural networks and Kalman filter methods

Identification of nonlinear dynamic systems has been the topic of many research projects in recent years. At this moment no uniform method to solve this problem exists. In this paper a new approach of identifying nonlinear dynamic systems is presented. It is based on the use of a General Regression Neural Network (GRNN), the parameters of which are trained by the Extended Kalman Filter Method. This strategy can be used in systems, in which not all states are accessible, and was analysed for the nonlinear behaviour of the roll-bite in rolling mills.
A hybrid computer as a training simulator

This paper gives a general review of the various computational techniques employing conventional analogue, precision analogue and digital methods, and indicates the approach to the ideal hybrid techniques. It illustrates the present and future trends in training simulators, involving the use of precision analogue computers, fully integrated with digital control logic and high-speed arithmetic to form a true hybrid simulator.
On the Necessity of Including Joint Passive Dynamics in the Impedance Control of Robotic Legs

Bioinspired quadruped robots are among the best robot designs for field missions over the complex terrain encountered in extraterrestrial landscapes and disaster scenarios caused by natural and human-made catastrophes, such as those caused by nuclear power plant accidents and radiological emergencies. For such applications, the performance characteristics of the robots should include high mobility, adaptability to the terrain, the ability to handle a large payload and good endurance. Nature can provide inspiration for quadruped designs that are well suited for traversing complex terrain. Horse legs are an example of a structure that has evolved to exhibit good performance characteristics. In this paper, a leg design exhibiting the key features of horse legs is briefly described. This leg is an underactuated mechanism because it has two actively driven degrees of freedom (DOFs) and one passively driven DOF. In this work, two control laws intended to be use in the stan ce phase are described: a control law that considers passive mechanism dynamics and a second law that neglects these dynamics. The performance of the two control laws is experimentally evaluated and compared. The results indicate that the first control law better achieves the control goal; however, the use of the second is not completely unjustified.
11.3.3 Enabling Measurement‐Driven System Development by Analyzing Testing Strategy Tradeoffs

Measurement‐driven system development focuses on using quantitative data to evaluate capabilities, benefits, progress, and tradeoffs as well as identify improvement opportunities. This paper describes a controlled study that addresses software testing effectiveness and focuses on the combination of individual testing techniques into team‐based testing strategies. This analysis is intended to enable measurement‐driven process improvement by characterizing how testing effectiveness relates to several factors, including testing strategy, software type, and developer expertise. In this study, a representative group of software development professionals applied common testing techniques to different types of software. This study compares the six possible team combinations of three testing techniques: (1) code reading by stepwise abstraction, (2) functional testing using equivalence partitioning and boundary value analysis, and (3) structural testing using 100% statement coverage criteria. Thirty‐two professional developers applied the techniques to three unit‐sized programs in a fractional factorial experimental design.
AI Can Rival Control Theory for Goal Achievement in a Challenging Dynamical System

Nonlinear dynamical systems are notoriously difficult to control. The Acrobot is an under‐actuated double pendulum in a gravitational field. Under most driving schemes the Acrobot exhibits chaotic behavior. But with careful applications of energy it is possible to gradually pump the system so as to swing it over its supporting joint. This swing‐up task is of current interest to control theory researchers.
Electronic Mail as a Forum for Argumentative Interaction in Higher Education Studies

This article reports a study in which thirty-one undergraduate students practiced academic argumentation by electronic mail (e-mail). In the two “tutorled” e-mail study groups the discussion topics were selected by the tutor, while in the two self-directed “student-led” groups selection was by the students. The quantity and quality of student-student interaction, and the factors associated with this were investigated. The results indicated that 42 percent of the students' messages (n = 441) were interactive in nature, indicating at least one reference to fellow students' messages. When difficult contents were addressed, interaction in the tutor-led groups was more common than in the student-led groups. The student-student interaction was mainly non-argumentative: 62 percent of the students' references (n = 259) expressed something other than the taking a position, 24 percent agreement, 10 percent grounded disagreement, and 4 percent non-grounded disagreement. The students in the student-led groups grounded their disagreement more often, while the students in the tutor-led groups more often expressed agreement. The study supports the superiority of the student-led mode of e-mail studying over the tutor-led mode when promoting argumentative dialogue.
On-line system for automated auditory evoked response threshold determination

An online computer system has been developed to determine auditory-evoked-response thresholds for objective hearing testing of otherwise untestable patients. The system uses click-evoked auditory brainstem responses. Online threshold determination is accomplished by two modules: a response recognition unit which determines if a response is present and a threshold tracking unit which utilizes a modified PEST (parameter estimation by sequential testing) algorithm to determine the click intensity testing level. Thresholds obtained manually and automatically are compared in 161 tests from 62 ears. Results indicate that automatically obtained thresholds show a strong agreement with those obtained visually as determined by a panel of experts. <<ETX>>
What is interface pressure?

The term interface pressure (IP) is used widely in the area of wheelchair seating to describe the physical interaction between the buttocks and the seat surface. Methods of quantifying IP exist even though a formal, research-based definition does not exist. Using a previously proposed definition of IP, issues surrounding the definition are examined relative to research studies to show weaknesses in the definition. Additional concerns relative to current methods of quantifying IF, such as creep and hysteresis, are evaluated. Two alternative methods of considering the seating interface are presented. One involves standardization of IP measurement via an index whereas the other discards IP in favor of quantifying tissue deformation. It is concluded that a new method of considering the seating interface is required which allows for comparison between measurements and individuals.
Automatic satellite image registration based on intensity matching

In this paper, a new algorithm for satellite image registration was developed. The main characteristic of the algorithm is to align two images automatically, without requiring either control points or sensor parameters. Thanks to incorporation of a robust estimation mechanism and statistical optimisation technique into a multi-model and multi-resolution framework for intensity matching, the algorithm is able to work with images with large variation in orientation, scaling, illumination and translation. The effectiveness of the algorithm has been verified by an intensive experiment on a great number of real images.
Progress towards speech models that model speech

This paper presents a personal view of recent advances in automatic speech recognition. The analysis is concerned with progress in speech pattern modelling, rather than recogniser performance. Despite the limitations of current approaches, it is argued that extension and development of these techniques provides a viable way forward. It is further suggested that the significance of a number of recent developments, such as sub-band speech recognition and segment modelling, is primarily in their potential for overcoming fundamental limitations of current HMM-based approaches, and not in the short-term improvement in recognition accuracy which has been achieved.
A Data Mining Approach for Spatial Modeling in Small Area Load Forecast

In a competitive power market, locations of future load growth have to be described with sufficient geographic precision to permit valid marketing strategy and siting of future T&D equipment. Small area load forecast, which provides information of future electric demand that includes spatial and temporal characteristics, is useful for T&D and market planning. Domain experts for spatial load forecast require long-term practicing and are difficult to find. In order to capture the meaningful associations between spatial data and the load changes, and to provide a useful tool for spatial load forecast, a data mining technique based on a knowledge discovery in database (KDD) procedure is proposed to determine automatically the preferential "scores" of land use changes. The proposed spatial modeling approach is an exploratory data analysis, trying to discover useful pattems in spatial data that are not obvious to the data user and are useful in the spatial load forecast.
Emotion Fusion Recognition for Intelligent Surveillance with PSO-CSVM

The next generation of intelligent surveillance system should be able to recognize human’s spontaneous emotion state automatically. Compared to speaker recognition, sensor signals analyzing, fingerprint or iris recognition, etc, facial expression and body gesture processing are two mainly non-intrusive vision modalities, which provides potential action information for video surveillance. In our work, we care one kind of facial expression, i.e. anxiety and gesture motion only. Firstly facial expression and body gesture feature are extracted. Particle Swarm Optimization algorithm is used to select feature subset and parameters optimization. The selected features are trained or tested for cascaded Support Vector Machine to obtain a high-accuracy classifier.
Adaptive classification of textured images using moments and autoregressive models

ABSTRACT An adaptive approach to the classification of textured images is presented, based onthe extraction of appropriate features from images. Autoregressive linear prediction mod-els, as well as moments of images, are features which are examined and compared in thepaper. Classification is achieved in an adaptive way, using an artificial feedforward neuralnetwork, which is trained by examples, using an efficient variant of the backpropagation learning algorithm. It is also shown that an adaptive least squares estimation algorithm can be appropriately interweaved with the network, resulting in an on-line adaptive clas- sification scheme. Simulation results are given, which illustrate the performance of the presented method. 1. INTRODUCTION Segmentation and classification of textured images has received considerable attention in many applications, such as cartography, military surveillance and recognition, land classification and medical imaging . Extraction of characteristic features is generallyrequired before the classification task, in order to reduce the dimension of the problem
Linear Regression Method for Review Aspect Rating Prediction

Online reviews as a new textual domain offer a unique proposition for sentiment analysis. The reviewers usually give a whole rating score to the product. The potential customers tend to make decision according to the reviews. Previous works mainly focus on the summarization of the rating and sentiment of reviews. However, they ignore an important question. The whole rating can be regarded as linear regression of different aspect ratings. High aspect rating and low aspect rating compensate each other. Therefore, previous works are coarse-grained analysis. This paper first proposed a weak supervised learning method to extract implicit aspect with aspect seeds. It then formulates the aspect rating problem as a linear regression model. Finally a gradient descent method is proposed to handle the problem. Different datasets are collected. Experimental result in the datasets demonstrates the advantage of the proposed model.
Utilizing WebQuests for Information Literacy Instruction in Distance Education

ABSTRACT The increasing use of problem-based learning in higher education affords librarians new avenues for promoting the development of information literacy skills among students. Information literacy instruction supports problem-based learning activities by providing students with skills to locate relevant resources for developing solutions to these exercises. The author created three WebQuests (together with tutorials) aimed at promoting faculty-librarian partnerships to deliver information literacy instruction through a problem-based learning approach in the context of course work in a distance learning environment. These problem-based learning WebQuests can be adapted to various disciplines as well as to traditional learning environments. Lastly, these WebQuests promote the development of information literacy skills in students as well as increase their exposure to problem-based learning. doi:10.1300/J106v14n03_03
ARC and gLite interoperability in ATLAS sites

In the Worldwide Large Hadron Collider Computing Grid several sites deploy both gLite and ARC middlewares. In this manner they are simultaneously providing resources to more than one federation of sites. In this article the interoperability between the two middleware flavors at sites that provide distributed resources to the ATLAS experiment is described. Some motivations for dual deployments, the coexistence of a gLite computing element and an ARC front-end on the same local resource management system, consistent monitoring, accounting and ticket handling are discussed.
A fast and high-sensitive dual-wavelength diffuse optical tomography system using digital lock-in photon-counting technique

We presented a novel dual-wavelength diffuse optical imaging system which can perform 2-D or 3-D imaging fast and high-sensitively for monitoring the dynamic change of optical parameters. A newly proposed lock-in photon-counting detection method was adopted for week optical signal collection, which brought in excellent property as well as simplified geometry. Fundamental principles of the lock-in photon-counting detection were elaborately demonstrated, and the feasibility was strictly verified by the linearity experiment. Systemic performance of the prototype set up was experimentally accessed, including stray light rejection and inherent interference. Results showed that the system possessed superior anti-interference capability (under 0.58% in darkroom) compared with traditional photon-counting detection, and the crosstalk between two wavelengths was lower than 2.28%. For comprehensive assessment, 2-D phantom experiments towards relatively large dimension model (diameter of 4cm) were conducted. Different absorption targets were imaged to investigate detection sensitivity. Reconstruction image under all conditions was exciting, with a desirable SNR. Study on image quality v.s. integration time put forward a new method for accessing higher SNR with the sacrifice of measuring speed. In summary, the newly developed system showed great potential in promoting detection sensitivity as well as measuring speed. This will make substantial progress in dynamically tracking the blood concentration distribution in many clinical areas, such as small animal disease modeling, human brain activity research and thick tissues (for example, breast) diagnosis.