Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-temporal pattern detection using dynamic Bayesian networks

This paper describes an intelligent decision aid, the TBM Reasoner, that helps military analysts rapidly identify time-critical targets (TCTs) involving theater ballistic missiles from sensor data. Our approach starts for the realization that existing sensors lack either the coverage or the resolution to reliably identify TCTs. Wide area sensors enable simultaneous tracking of all vehicles in a large area, but provide insufficient information to identify vehicle type. In contrast, current-generation high-resolution sensors can reliably identify vehicle type but are unable to search a large area fast enough to identify TCTs. To resolve this dilemma, we bring to bear additional knowledge regarding TCT behavior and capabilities. This knowledge is modeled using dynamic bayesian networks (DBNs). Our approach integrates established technology for multi-hypothesis tracking from data fusion with recently developed algorithms for efficient approximate inference in DBNs. The resulting "smart filter" can be employed to rapidly identify high-probability candidate targets in large volumes of sensor data. The approach described here can be easily generalized to a much wider range of problems of spatio-temporal pattern recognition under uncertainty.
Spaceborne Radar Remote Sensing: Applications and Techniques

The operation and applications of spaceborne radars for terrestrial and planetary remote sensing are described in an introduction for advanced students and practicing scientists. Chapters are devoted to imaging radars, wave-surface interactions and geoscientific applications, real- and synthetic-aperture radars, end-to-end system design, SAR data processing, altimeters, and scatterometers. Extensive diagrams, drawings, graphs, photographs, and sample radar images are provided.
An OWL-based WordNet lexical ontology

This paper discribes a data representation for WordNet 2.1 based on Web Ontology Language (OWL). The main components of WordNet database are transformed as classes in OWL, and the relations between synsets or lexcial words are transformed as OWL properties. Our conversion is based on the data file of WordNet instead of the Prolog database. This work can be used to enrich the work in progress of standard conversion of WordNet to the RDF/OWL representation at W3C.
Large scale semantic matching: agrovoc vs CABI

Achieving semantic interoperability is a difficult problem with a lot of challenges yet to address. Some of them include matching large-scale data sets, tackling the problem of missing background knowledge, evaluating large scale results, tuning the matching process and doing all of the above in a realistic setting with resource and time constraints. In this paper we report the results of a large-scale matching experiment performed on domain-specific resources: two agricultural thesauri. We share the experience concerning the above mentioned aspects of semantic matching, discuss the results, draw conclusions and outline perspective directions of future work.
A cell selection algorithm for area minimization

This paper presents a cell selection algorithm that minimizes the area of the cell-based design, while satisfying the given delay constraint. The proposed algorithm visits the given circuit in the forward direction and calculates the lower bound on the delay and area. Then, it visits the circuit in the reverse direction, and binds the logic gates with library cells using the Branch-and-Bound formulations of the lower bound. Experimental results show that the proposed algorithm minimizes the area of test circuits by 27.33% on the average.
Computer vision camera with embedded FPGA processing

Traditional computer vision is based on a camera-computer system in which the image understanding algorithms are embedded in the computer. To circumvent the computational load of vision algorithms, low-level processing and imaging hardware can be integrated in a single compact module where a dedicated architecture is implemented. This paper presents a Computer Vision Camera based on an open architecture implemented in an FPGA. The system is targeted to real-time computer vision tasks where low level processing and feature extraction tasks can be implemented in the FPGA device. The camera integrates a CMOS image sensor, an FPGA device, two memory banks, and an embedded PC for communication and control tasks. The FPGA device is a medium size one equivalent to 25,000 logic gates. The device is connected to two high speed memory banks, an IS interface, and an imager interface. The camera can be accessed for architecture programming, data transfer, and control through an Ethernet link from a remote computer. A hardware architecture can be defined in a Hardware Description Language (like VHDL), simulated and synthesized into digital structures that can be programmed into the FPGA and tested on the camera. The architecture of a classical multi-scale edge detection algorithm based on a Laplacian of Gaussian convolution has been developed to show the capabilities of the system.
Substrate network modeling for CMOS RF circuit simulation

The effect of the substrate network models for use in small-signal CMOS RF circuit simulation is examined in conjunction with the BSIM3 MOSFET model. Detailed comparisons of the small-signal Y and S parameters have been done with both two-dimensional device simulations and measurement data. These comparisons have been made for different bias conditions and channel lengths. It is shown that a simple, one resistance, substrate network model is accurate for small-signal analyses up to a frequency of 10 GHz in a 0.5 /spl mu/m CMOS process.
Adaptive processing to correct for organ motion artifacts in X-ray CT medical imaging systems

X-ray CT scanners provide images of transverse cross sections of the human body from a large number of projections. During the data acquisition process, which usually takes about one second, motion such as respiration, cardiac motion and patient restlessness produce artifacts that appear as blurring in the reconstructed images and may lead to inaccurate diagnosis. This paper proposes a motion correction method that makes no assumptions about the properties of the motion. The approach uses a spatial overlap correlator (SOC) scheme to track organ motion in computed tomography (CT) imaging systems. An adaptive interference cancellation (AIC) algorithm is then used to correct for organ-motion artifacts. Synthetic data tests demonstrate the validity of this approach.
A New Multilevel Active Power Filter Using Switches Meticulously Controlled

Shunt active power filter based on multilevel inverter is used to compensate the power factor and to delete the harmonics. This one permits to reduce the inverse voltages applied to the filter switches and their switching frequencies. Nevertheless, the high number of used switches requires a complicated controller and increases the switching losses; where the necessity of finding another resolution system. In this work a new topology of multilevel inverter is proposed as a shunt active power filter using two IGBT transistors in series of opposite sense meticulously controlled by a parallel control algorithm, with the concept of reduced number of six switches which are able to create five levels of the output voltage. This system substute the classical system of eight switches. The harmonic currents identification is carried out using the instantaneous active and reactive power method. The simulation is performed using Matlab/Simulink. The obtained results show that the filtering performances are well enhanced.
Decision making in choosing information systems

Purpose – The purpose of this paper is to propose a framework to support decision-makers in selecting information systems (ISs) and knowledge management systems (KMSs), by taking into consideration factors and perspectives which influence the choice. Design/methodology/approach – The framework has been built on a hierarchical structure, where selection criteria and sub-criteria are defined and compared, and where alternatives are established and evaluated according to the software market trends. The application of the framework to an empirical study in two leading organizations in Jordan is provided as a validation of the proposed framework. Findings – The paper presents and applies a methodological framework, based on the analytic hierarchy process approach, to support decision-makers in the choice and in the implementation of an IS. Research limitations/implications – Future research could address the implementation of the framework within a selected industry. Successively, the framework could be utiliz.
Efficient block implementation of the LMS-based DFE

An efficient block adaptive implementation of the widely used decision feedback equalizer is developed. Both the feedforward and the feedback filters of the equalizer are updated once every K sample time intervals, with K being the block length. However this block adaptation is done in such a way that the resulting filters, as well as the decisions, are identical to those computed by the conventional sample by sample LMS based DFE (LMS-DFE). That is, the new block adaptive algorithm is mathematically equivalent to the LMS-DFE algorithm (and hence it features identical performance). At the same time the proposed algorithm offers substantial computational savings as compared to the sample by sample LMS-DFE. Thus the new block DFE turns out to be particularly suitable for applications in which long equalizers are required.
Proceedings of the 8th ACM European Conference on Computer Systems

It is our great pleasure to present the proceedings of the 8th ACM European Conference on Computer Systems. Ever since the first EuroSys conference in 2006, EuroSys has gained and maintained a reputation as one of the premier systems conferences in the world. This year is no exception. The program is thought-provoking, high quality, and very broad---with topics ranging from kernels to clouds; from storage to security; and from mobile devices to multicore servers. In addition, the program includes 5 colocated workshops, posters, and demos.
Tutorials on Google Analytics: How to Craft a Web Analytics Report for a Library Web Site

Libraries, along with other information service institutions, have entered a digital era in which resources are presented electronically through various digital platforms. The library Web site functions as the main source of information to patrons as well as a community outreach tool. Many library services now either succeed or fail based on how well users interact with the institution's Web site. In order to evaluate the effectiveness of library services, it thus becomes important for libraries to measure the performance of library Web sites. Web analytics is the ideal tool to answer questions regarding the evaluation of Web site performance. However, Web analytics can be hard to understand for those who do not have the time to familiarize themselves with all the terms and data. Writing a thorough Web analytics report can help make Web analytics easier to digest for administrators or Web site stakeholders. This tutorial provides step-by-step instructions on how to craft a Web analytics report. It provides suggestions on visualizing statistics, interpreting data, and customizing the report based on a real experience. The tutorial is facilitated with customized figures, charts, and tables from a real Web analytics report on the Texas Tech University Libraries Web site and concludes with recommendations on presenting the report to the administration and stakeholders.
Comparison Of Apriori And Fp-Growth Algorithms On Determination Of Association Rules In Authorized Automobile Service Centres

Data Mining is used to describe the totality of techniques which aim to find the unexplored patterns in a set of data. The purpose of data mining is to create models of decision-making devoted to estimations of future behavior based on analysis of past activities. In this study the shopping data of the customers of an authorized service, operating in the automative sector in Turkey, were analyzed using Apriori and FP-Growth Algorithms. This way, it is observed which products were purchased together by customers and in line with this observation, campaigns and promotions were given a direction to increase the profit.
Collecting and archiving tweets: a DataPool case study

Information presented to a user via Twitter is variously called a ‘stream’, that is, a constant flow of data passing the viewer or reader. Where the totality of information passing through Twitter at any moment is considered, the flow is often referred to as a ‘firehose’, in other words, a gushing torrent of information. Blink and you’ve missed it. But does this information have only momentary value or relevance? Is there additional value in collecting, storing and preserving these data? This short report describes a small case study in archiving collected tweets by, and about, a research data project, DataPool at the University of Southampton. It explains the constraints imposed by Twitter on the use of such collections, describes how a service for collections evolved within these constraints, and illustrates the practical issues and choices that resulted in an archived collection. The second version of the report adds a short postscript on rights, ethics and privacy of archiving Twitter data, prompted by a Twitter dialogue on this report. Two additional references of related work at Southampton are provided towards the end of sections 1 and 2.
Dynamic slicing in higher-order programming languages

Dynamic slicing is a technique for isolating segments of a program that (potentially) contribute to the value computed at a point of interest. Dynamic slicing for restricted first-order imperative languages has been extensively studied in literature. In contrast, little research has been done with regard to the slicing of higher-order programs. Most first-order imperative programming languages are statement-based while most higher-order programming languages are expression-based. Unlike first-order programs, higher-order programs have no simple concept of static control flow: control flow depends on the binding of formal parameters to actuals. Because of these differences, formalising a definition of slicing for higher-order programs involves some novel concepts. The aim of the work, presented here, is to extract 'executable' slices of higher-order programs solely from the execution trace. In the absence of assignments, i.e. in purely functional programs, dynamic slices satisfying very strong criteria can be extracted. This is because purely functional languages have a demand-driven evaluation strategy. A realistic higher-order programming language, like Standard ML (SML), uses imperative features like assignments and exceptions. We provide algorithms to compute dynamic slices of programs containing such features. It is shown that, just like first-order programs, higher-order programs can be instrumented to collect data, regarding its dynamic slice, during execution. We have implemented a tool which performs such instrumentation on core SML programs. Experiments conducted, with the tool, throw light on the utility and limitations of dynamic slicing as technique for analysing higher-order programs.
Achieving Synergies through generic skills: A strength of online communities

Educators are often torn between impositions of the institution in which they work and the imperatives of their individual courses or units and the impact this tension might have on student satisfaction with the learning experience. It is common to hear that students must graduate with multiple generic attributes or skills, yet these skills may not be within the gamut normally required in a specific undergraduate unit. This paper reports on an attempt to integrate both University sanctioned or top down generic skills and an instructor's organic or bottom up desirable skills in a multimedia unit at an Australian university, and the impact this has on student satisfaction. Specifically both asynchronous and synchronous tools were used to facilitate online community characteristics, in turn usable to foster the generic skills of collaboration, communication and problem solving. Results reveal synergies between the possibly divergent and potentially opposed goals of the university and the classroom. This paper demonstrates the ways that the conscious promotion of an online community to simultaneously assist achieving both the unit learning outcomes and prescribed generic skills, caused no evident conflict for student participants.
High school teachers' use of graphing calculators when teaching linear and quadratic functions: Professed beliefs and observed practice

This study was designed to explore secondary mathematics teachers’ beliefs about graphing calculators, their practices with the graphing calculators when teaching linear and quadratic functions, and the relationship between the teachers’ beliefs and their practices. The study was conducted in two phases. In the first phase, 81 teachers responded to a questionnaire about their beliefs regarding the use of graphing calculators in the teaching and learning of linear and quadratic functions. Six of these teachers then participated in the second phase involving task-based interviews and classroom observations. A major finding from the survey was a possible link between teachers’ frequency of calculator use and their views regarding sequencing of function representations. I found that low frequency users held the view that algebraic symbols should always precede tables while high frequency users did not hold a similar view. Teachers in this study were also split on which type of tasks students should be allowed to use graphing calculators. Some teachers stated that they would encourage their students to use the graphing calculator when the students felt it was appropriate regardless of the task while others stated that they would always want their students to learn to solve each type of problem with paper and pencil before they could use a calculator. Findings from the interviews and classroom observations highlighted some differences among the moderate and high frequency users in terms of how they guide their classes – teacher direction and student exploration – and the level of direction they provide to their students when working with graphing calculators. In terms of classroom dynamics, I found that classes taught by high frequency users seemed to involve more student exploration than those taught by moderate frequency users. I also found that when lessons were characterized by teacher direction, the graphing calculator was used as a computational tool and when lessons were characterized by student exploration, the graphing calculator was used as a visualizing tool and checking tool. HIGH SCHOOL TEACHERS’ USE OF GRAPHING CALCULATORS WHEN TEACHING LINEAR AND QUADRATIC FUNCTIONS: PROFESSED BELIEFS AND OBSERVED PRACTICE
A wide-range and fixed latency of one clock cycle delay-locked loop

A wide-range delay-locked loop (DLL) with a fixed latency of one clock cycle is proposed. The phase selection circuit and the start-controlled circuit are used for this DLL to enlarge the operating frequency range and eliminate the harmonic locking problems. The operating frequency range of the DLL can be from 1/T/sub Dmin/ to 1/(N/spl times/T/sub Dmax/), where T/sub Dmin/ and T/sub Dmax/ are the minimum and maximum delay of a delay cell, respectively, and N is the number of delay cells used in the delay line theoretically. The prototype chip is fabricated in a 0.35-um 1P3M CMOS process. The measurement results exhibit the proposed DLL can operate from 6 MHz to 130 MHz and the latency of this DLL is just one clock cycle. From the entire operating frequency range, the maximum rms jitter doesn't exceed 25 ps. The DLL occupies an active area of 880-um/spl times/515-um and consumes a maximum power of 132 mW at 130 MHz.
in the Map,

In this paper we prove the existence of a chaotic saddle for a piecewise linear map of the plane, referred to as the Lozi map. We study the Lozi map in its orientation and area preserving version. First, we consider the autonomous version of the Lozi map to which we apply the Conley-Moser conditions to obtain the proof of a chaotic saddle. Then we generalize the Lozi map on a nonautonomous version and we prove that the ﬁrst and the third Conley-Moser conditions are satisﬁed, which imply the existence of a chaotic saddle. Finally, we numerically demonstrate how the structure of this nonautonomous chaotic saddle varies as parameters are varied.
Comparison of Energy Efficient Clustering Protocols for Heterogeneous Wireless Sensor Networks

Wireless sensor networks are on the rise in realtime deployment and also a major field to work on for the research and development teams. These networks consist of a number of sensor nodes that sense various parameters such as temperature, pressure, etc from an environment they are deployed in, perform data aggregation and send the data to the user application that makes use of it to detect the conditions in that environment. However there is one factor that decides the use of WSN: the energy. Since each sensor node needs to perform actions of collecting, aggregating and transferring of data they need some source of energy to drive the network. Currently they derive their energy from the batteries which can provide limited amount of energy. Hence various energy efficient routing protocols have been proposed which help in minimum energy consumption ensuring longer stability period which in turn increases the lifetime of the network. In this paper, we compute the average energy of a WSN after every logical round of operation for our protocol HEEPSCC and compare it with two well known heterogeneous protocols namelySEP and EECS. A heterogeneous WSN is one where every node has different amount of energy associated with it before being deployed in a network. Simulations using MATLAB prove that HEEPSCC protocol causes less energy consumption among the three at the end of the considered number of logical operations.
Neural networks for control and system identification

A review is presented of the field of neuroengineering as a whole, highlighting the importance of neurocontrol and neuroidentification. Then a description is given of the five major architectures in use today in neurocontrol (in robotics, in particular) and a few areas for future research. The author concludes with comments on neuroidentification. <<ETX>>
Hand Tracking and its Pattern Recognition in a Network of Calibrated Cameras

This thesis presents a vision-based approach for hand gesture recognition which combines both trajectory and hand posture recognition. The hand area is segmented by fixedrange CbCr from cluttered and moving backgrounds, and tracked by Kalman Filter. With the tracking results from two calibrated cameras, the 3D hand motion trajectory can be reconstructed. It is then modeled by dynamic movement primitives (DMP) and a support vector machine (SVM) is trained for trajectory recognition. Scale-invariant feature transform (SIFT) is employed to extract features on segmented hand postures, and a novel strategy for hand posture recognition is proposed. A gesture vector is introduced to recognize hand gesture as a whole which combines the recognition results of motion trajectory and hand postures, where an SVM is trained for gesture recognition based on gesture vectors.