Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Template Based Face and Iris Detection on Rotated Faces

Real-time iris and face detection on video sequences is important in applications such as study of the eye function, drowsiness detection, man-machine interfaces, face recognition security and multimedia retrieval. In this work, we present a real-time template based method for iris detection in faces with wide coronal (− 40°, + 40°) and transversal (− 45°, + 45°) axis rotations. This method is based on anthropometric templates that were constructed off-line for face coronal and transversal rotation, using face features such as elliptical shape, location of the eyebrows, nose and lips. A line integral is computed using these templates over the fine directional image to find the actual face location, face size and rotation angle. This information provides a region to search for the eyes and the iris boundary is detected. Results computed on five video sequences including coronal and transversal rotations with over 1,700 frames show correct face detection rate of 98.5% and iris detection rate of 94.4%. The method was compared with a “weighting mask method” on two video sequences showing an improved performance. The method was also compared for eye detection to a method using combined binary edge and intensity information in two subsets of the AR face database (63 and 564 images). Different disparity errors were considered and for the smallest error, a 100% correct detection was reached in the AR-63 subset and 99.8% was obtained in the AR-564 subset.
Why we should use function points [software metrics]

Function point analysis helps developers and users quantify the size and complexity of software application functions in a way that is useful to software users. Are function points a perfect metric? No. Are they a useful metric? In the author's experience, yes. Function points are technologically independent, consistent, repeatable, and help normalize data, enable comparisons, and set project scope and client expectations. The author addresses these issues from the perspective of a practitioner who uses the International Function Point Users Group's Counting Practices Manual, Release 4.0 rules for counting function points. Of course, other function point standards exist, including Mark II and Albrecht's original rules.
Maths concepts in teaching: Procedural and conceptual knowledge

In teaching a general course on mathematics for prospective teachers, I have found the theoretical distinction between conceptual knowledge and procedural knowledge (Hiebert & Lefevre, 1986) a useful focus for teaching practice. The constructs provide a scaffold for the learning of mathematics by the students and for thinking about the teaching of mathematics in the school environment. These theoretical insights uncover in part the processes for acquiring knowledge and provide a tool for addressing problematic areas of learning.
A pseudologarithmic rectifier using unbalanced bias MFMOS differential pairs

A pseudologarithmic rectifier using multi-input floating-gate MOS (MFMOS) transistors is presented in this paper. The rectifiers consist of unbalanced bias matched MFMOS transistor differential pairs. The transfer characteristics of each subrectifier are determined by an appropriate choice of transistor aspect ratio and capacitive input coupling ratio such that in the summation of the output currents from each rectifier stage, the overall transfer characteristics closely approximates that of a true logarithmic behavior. It is operable at low supply voltage (/spl plusmn/0.9 V) and has low temperature dependence. Measured dynamic range of 27 dB and 16.5 dB, with a corresponding logarithmic error of /spl plusmn/0.7 dB and /spl plusmn/0.35 dB, has been obtained for three-stage and two-stage pseudologarithmic rectifiers, respectively, at room temperature. The measured logarithmic error for the three-stage pseudologarithmic rectifier at 125/spl deg/C is /spl plusmn/1.05 dB which is an increase of /spl plusmn/0.35 dB over a 100/spl deg/C range.
Accelerated failure time models with covariates subject to measurement error

It has been well known that ignoring measurement error may result in substantially biased estimates in many contexts including linear and nonlinear regressions. For survival data with measurement error in covariates there has been extensive discussion in the literature with the focus being on the Cox proportional hazards models. However, the impact of measurement error on accelerated failure time (AFT) models has received little attention, though AFT models are very useful in survival data analysis. In this paper, we discuss AFT models with error‐prone covariates and study the bias induced by the naive approach of ignoring measurement error in covariates. To adjust for such a bias, we describe a simulation and extrapolation method. This method is appealing because it is simple to implement and it does not require modelling the true but error‐prone covariate process that is often not observable. Asymptotic normality for the resulting estimators is established. Simulation studies are carried out to evaluate the performance of the proposed method as well as the impact of ignoring measurement error in covariates. The proposed method is applied to analyse a data set arising from the Busselton Health study (Australian J. Public Health 1994; 18:129–135). Copyright © 2007 John Wiley & Sons, Ltd.
A facility for near end crosstalk measurements on ISDN subscriber loops

A facility for making near-end crosstalk measurements on multipair cable is described. This facility yields pair-to-pair frequency- and time-domain responses, useful for characterizing crosstalk in digital loop transmission. Through measurements with multiple synchronous ISDN (integrated services digital network) loop transmitters, it also allows measurement and characterization of cyclostationary crosstalk variation. Preliminary results clearly show this cyclostationary characteristic. <<ETX>>
The role of TQM and KM in Supply Chain Learning: a conceptual model

Supply Chain Management (SCM) competitiveness is achieved based on process efficiency. To improve efficiency, we depend greatly on knowledge acquisition and utilisation in the area of Knowledge Management (KM). KM is particularly relevant to every stage in SCM in order to make accurate and timely decisions that are critical to the firms' effectiveness and efficiency in SCM. At the same time, the Total Quality Management (TQM) concept proposes a system to improve the efficiency and productivity. This study makes a significant contribution by developing a proposed model as a methodological example which can be useful for tracking the degree of KM and TQM effects on SCL in both the service and the manufacturing industry.
Symbolic behavioral model generation of nonlinear analog circuits

A new method for symbolic behavioral model generation of nonlinear analog circuits is presented. Equation-based simplification techniques for symbolic analysis of nonlinear circuits are proposed. They comprise global and local simplification operations which are performed on the system of nonlinear circuit equations. This system is derived from a transistor level netlist. Behavioral models are generated for DC-transfer and multiple AC operating conditions using an efficient error estimation algorithm. They include symbolic physical circuit parameters and allow deeper insight into nonlinear circuit behavior. Some examples are given to show the feasibility of this approach.
Researches on scheme of pairwise key establishment for distributed sensor networks

Security schemes of pairwise key establishment, which enable sensors to communicate with each other securely, play a fundamental role in research on security issue in wireless sensor networks. A new kind of cluster deployed sensor networks distribution model is presented, and based on which, an innovative Hierarchical Hypercube model - H(k,u,m,v,n) and the mapping relationship between cluster deployed sensor networks and the H(k,u,m,v,n) are proposed. By utilizing nice properties of H(k,u,m,v,n) model, a new general framework for pairwise key predistribution and a new pairwise key establishment algorithm are designed, which combines the idea of KDC(Key Distribution Center) and polynomial pool schemes. Furthermore, the working performance of the newly proposed pairwise key establishment algorithm is seriously inspected. Theoretic analysis and experimental figures show that the new algorithm has better performance and provides higher possibilities for sensor to establish pairwise key, compared with previous related works.
Making News Today: a tool for adoption of ethics principles using technology‐supported television journalism

There are movements internationally towards curricula that incorporate values and citizenship education. In Australia, this movement has been illustrated with the adoption of a national curriculum in values education. This has arisen from the perceived need for citizens to hold values around the rights and responsibilities of functioning within a democracy. The Making News Today programme has been designed to develop a range of literacies enabling learners, for example, to read the media beyond the interests of the elite. The programme incorporates a journalistic process for television news production for middle school students using laptop and handheld video technologies, with embedded ethics and values education. The article reports on an analysis of the implementation of this programme with middle school students in Australia with reference to student adoption of ethical stances in the journalistic process and the implications for the use of this project in developing ethics, values and citizenship as part of the curriculum process.
Effect of the buffer layer on the microwaves properties in the coplanar waveguide for LiNbO/sub 3/ optical modulators with superconducting electrodes

The effects of a buffer layer on the modulation bandwidth of LiNbO/sub 3/ optical modulators with superconducting and normal-conducting electrodes have been deduced by using the transverse resonance method (TRM). The analysis is based on the integral equations and the equivalent network representation of each structure. A high Tc superconducting material Yba/sub 2/Cu/sub 3/O/sub 7-8/ (YBCO) has been used for the super-conducting electrode case. The microwave effective index (N/sub m/) as a function of the thickness and dielectric constant of the buffer layer has been computed. Also the bandwidth-length product (/spl Delta/f.L) as a function of the thickness and dielectric constant of the buffer layer has been computed. A comparison with published results is also included to check the accuracy of TRM technique's results.
Why do users intend to continue using the digital library? An integrated perspective

Purpose – The purpose of this paper is to propose a hybrid model based on expectation-confirmation model (ECM), technology acceptance model (TAM), and updated DeLone and McLean information system (IS) success model to examine whether quality factors as the antecedents to user beliefs affected users’ continuance intention of the digital library. Design/methodology/approach – Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed in the campus library, and 525 (87.5 percent) usable questionnaires were analyzed using structural equation modeling (SEM) in this study. Findings – Findings show that the proposed research model integrating ECM, TAM, and updated DeLone and McLean IS success model has good explanatory power for quality antecedents of users’ continuance intention of the digital library. Information relevance, system accessibility, and technical support play key roles in explaining users’ continuance int.
An Examination of How a Teacher's Use of Digital Tools Empowers and Constrains Language Arts Instruction

The Common Core State Standards produce a need to understand how digital tools can support literacy instruction. The purpose of this case study was to explore how a language arts teacher's integration of computers and iPads empowered and constrained her and the resulting classroom instruction. Constraining factors included (a) inadequate technological knowledge, (b) expectations of students’ comfort with technology, (c) inappropriate expectations for assignments, and (d) limited conceptions of the purposes of technology. Subthemes related to enhancement included: enhancement of classroom environment, simplicity and sophistication equal innovation and empowerment, combining tools, and digital tools support multimodal communication.
Temporal Reasoning for Events in a Knowledge-Based Network

Case Studies Severe weather reporting service Provides timely, accurate reports on severe weather Uses the temporal operators, spatial ontology Automatic log-level refining Changes logging level based on event patterns Easily performed using AFTER operator CEP Overview Filter a continuous event stream Find composite events Correlate atomic or composite events into patterns Active databases or middleware systems
How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: sensitivity to calibration methods

Different techniques for obtaining probabilistic quantitative precipitation forecasts (PQPFs) over South America are tested during the 2002–2003 warm season. They have been applied to a regional ensemble system which uses the breeding technique to generate initial and boundary conditions perturbations. This comparison involves seven algorithms and also includes experiments to select an adequate size for the training period. Results show that the sensitivity to different calibration strategies is small with the exception of the rank histogram algorithm. The inclusion of the ensemble spread or the use of different ensemble members for the computation of probabilities shows almost no improvement with respect to probabilistic forecasts computed using the ensemble mean. This is basically due to the strong relationship between precipitation error and its amount. Copyright © 2011 Royal Meteorological Society
Technology Integration: Best Practices–Where Do Teachers Stand? 5(11)

As technology becomes more available in k-12 classrooms and teachers apply it their teaching, it is important to consider how we are going to evaluate the technology integration efforts of teachers. This article summarizes the stages of technology integration, and then goes on to present examples of best technology integration practices. Finally, it offers questions to consider when assessing teachers and their uses of technology. The idea of "technology integration" has evolved during the last several decades from teaching programming, to utilizing drill and practice, to implementing integrated learning systems, to addressing computer literacy skills, to participating in web-based communities. A more current view of technology integration involves the practice of using technology in ways that are both curriculum-based and future-oriented. According to Ertmer (1999), teachers should focus on meeting content objectives within the "three Cs": communication, collaboration, and creative problem-solving. It also requires that attention be given to preparing students for the future: theirs, not ours. The challenge for today’s educators is not programming the computer or learning cumbersome DOS commands. It lies in using computers and other technologies in ways to promote meaningful learning for students. The purpose of this paper is to describe teachers’ transformation process into technology integrators, to explore best practices in teaching with technology, and to suggest how administrators might consider evaluating teachers’ integration efforts. Now that computer technology is more prevalent in classrooms, it is becoming less a decision of whether or not to adopt, and more of a dilemma of how to implement it effectively into instruction.
Interacting multiple model tracking with target amplitude feature

A recursive tracking algorithm is presented which uses the strength of target returns to improve track formation performance and track maintenance through target maneuvers in a cluttered environment. This technique combines the interacting multiple model (IMM) approach with a generalized probabilistic data association (PDA), which uses the measured return amplitude in conjunction with probabilistic models for the target and clutter returns. Key tracking decisions can be made automatically by assessing the probabilities of target models to provide rapid and accurate decisions for both true track acceptance and false track dismissal in track formation. It also provides the ability to accurately continue tracking through coordinated turn target maneuvers. >
Software protection mechanisms for dependable systems

We expect that in future commodity hardware will be used in safety critical applications. But the used commodity microprocessors will become less reliable because of decreasing feature size and reduced power supply. Thus software-implemented approaches to deal with unreliable hardware will be required. As one basic step to software- implemented hardware-fault tolerance (SIHFT) we aim at providing failure virtualization by turning arbitrary value failures caused by erroneous execution into crash failures which are easier to handle. Existing SIHFT approaches either are not broadly applicable or lack the ability to reliably deal with permanent hardware faults. In contrast, Forin [7] introduced the Vital Coded Microprocessor which reliably detects transient and permanent hardware errors but is not applicable to arbitrary programs and requires special hardware. We discuss different approaches to generalize Forin's approach and make it applicable to modern infrastructures.
Q(λ)-learning fuzzy logic controller for differential games

This paper addresses the problem of tuning the input and the output parameters of a fuzzy logic controller. A novel technique that combines Q(λ)-learning with a fuzzy inference system as a function approximation is proposed. The system learns autonomously without supervision or a priori training data. The proposed technique is applied to two different differential games. The proposed technique is compared with the classical control strategy, Q(λ)-learning only, and the technique proposed in [1] in which a neural network is used as a function approximation for Q-learning. Computer simulations show the usefulness of the proposed technique.
Self-shaping dynamical systems and learning

We associate learning and adaptation in living systems with the shaping of the velocity vector field in the respective dynamical systems in response to external, generally random, stimuli. With this, a mathematical concept of self-shaping dynamical systems is proposed. Initially there is a zero vector field and an "empty" phase space with no attractors or other non-trivial objects. As the random stimulus begins, the vector field deforms and eventually becomes smooth and deterministic, despite the random nature of the applied force, while the phase space develops various geometrical objects. We consider gradient self-shaping systems, whose vector field is the gradient of some energy function, which under certain conditions develops into the multi-dimensional probability density distribution (PDD) of the input. Self-shaping systems are relevant to neural networks (NNs) of two types: Hopfield, and probabilistic. Firstly, we show that they can potentially perform pattern recognition tasks traditionally delegated to Hopfield NNs, but without supervision and on-line, and without developing spurious minima of the energy. Secondly, like probabilistic NNs, they can reconstruct the PDD of input signals, without the limitation that new training patterns have to enter as new hardware units. Thus, self-shaping systems can be regarded as a generalization of the NN concept, achieved by abandoning the "rigid units" - "flexible couplings" paradigm and making the vector field fully flexible and amenable to external force. The new concept presents an engineering challenge requiring new principles of hardware design. It might also become an alternative paradigm for modeling of living and learning systems.
Short-term stock price analysis based on order book information

Efficient market hypothesis is widely accepted in financial market studies and entails the unpredictability of future stock prices. In this study, we show that a simple analysis can classify short-term stock price changes with an 82.9% accuracy. Our analysis uses the order book information of high-frequency trading. The volume of highfrequency trading, which is responsible for short-term stock price changes, is increasing dramatically; therefore, our study suggests the importance of analyzing short-term market fluctuations, an aspect that is not well studied in conventional market theories. The experimental results also suggest the importance of the new data representation and analysis methods we propose, neither of which have been thoroughly investigated in conventional financial studies.
Tissue object patterns for segmentation in histopathological images

In the current practice of medicine, histopathological examination is the gold standard for routine clinical diagnosis and grading of cancer. However, as this examination involves the visual analysis of biopsies, it is subject to a considerable amount of observer variability. In order to decrease the variability, it has been proposed to develop systems that mathematically model the histopathological tissue images and automate the analysis. Segmentation constitutes the first step for most of these automated systems. Nevertheless, the segmentation in histopathological images remains a challenging task since these images typically show variances due to their complex nature and may include a large amount of noise and artifacts due to the tissue preparation procedures. In our research group, we recently developed different segmentation algorithms that rely on representing a tissue image with a set of tissue objects and using the structural pattern of these objects in segmentation. In this paper, we review these segmentation algorithms, discussing their clinical demonstrations on colon tissues.
Outage analysis for novel selection cooperation in multi-source cognitive networks

A novel selection cooperation scheme for cognitive nodes (Cog-Sel scheme) in multiple sources cooperative networks is presented and the outage probability is derived. In the proposed scheme, the source chooses a single optimal relay or transmits directly to the destination in terms of the SNR between the source-destination pair with some feedback. Each node can "smartly" utilize the idle frequency band to transmit signal using cognitive radio technology. Therefore, no extra channel resources are allocated for cooperation and the system encounters no bandwidth losses. The outage probability of the proposed scheme is analyzed and the result reveals that it outperforms the conventional relaying strategies such as simple selection and opportunistic relaying schemes. These benefits contribute to the efficient use of power and channel resources. Theoretic analysis and numerical simulation results are presented to verify our analysis.
Generalised nearest feature line for subspace learning

Nearest feature line (NFL) is a powerful tool in pattern recognition, which generalises the representational capacity of available prototypes by using linear interpolation and extrapolation between the feature points. NFL is generalised to subspace learning so that the obtained subspace has desirable discriminating ability. Experiments on face recognition demonstrate its effectiveness.