Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of comprehensible decision trees through evolution of training data

In machine learning, decision trees (DTs) are usually considered comprehensible because a reasoning process can be given for each conclusion. When the data set is large, however, the DTs obtained may become very large, and they are no longer comprehensible. To increase the comprehensibility of DTs, we have proposed several methods. For example, we have tried to evolve DTs using genetic programming (GP), with tree size as the secondary fitness measure; we have tried to initialize GP using results obtained by C4.5; and we have also tried to introduce the divide-and-conquer concept in GP, but all results obtained are still not good enough. Up to now we have tried to design good DTs from given fixed data. In this paper, we look at the problem from a different point of view. The basic idea is to evolve a small data set that can cover the domain knowledge as good as possible. From this data set, a small but good DT can be designed. The validity of the new algorithm is verified through several experiments.
Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis

Cognitive work analysis is gaining momentum as an approach for the analysis, design and evaluation of complex sociotechnical systems. This paper focuses on control task analysis (ConTA), the second phase of cognitive work analysis. The paper consolidates existing approaches to ConTA and extends the basic concepts, in particular, by asserting that activity in some work systems is better characterized by both work situations and work functions and by introducing a new formative representation for ConTA called the contextual activity template. In addition, the paper proposes a set of methodological guidelines for performing ConTA and presents a case study of a ConTA for a first-of-a-kind military system called Airborne Early Warning and Control. As well as illustrating the conceptual extensions and methodological guidelines for ConTA by example, this case study highlights some of the difficulties of conducting ConTA for first-of-a-kind, complex systems during the early stages of development.
Image Retrieval Based on Color and Texture

In this paper, a clustering algorithm based on mean shift is used to extract the dominant color in CIE L*a*b* color space. Earth Mover's Distance is used to calculate the color dissimilarity. In order to overcome disadvantages of color feature, a new method based on texture is proposed. The technique of relevance feedback is used to enhance the effectiveness. Finally, a prototype system is developed to compare the retrieval precision, the rank and the execution time by two experiments. The results show that the proposed approach is effective.
Global Least Squares Matching

Global Least Squares Matching (GLSM) is an advanced image matching technology that automates the image correlation process for applications such as very dense elevation data extraction, f e m e extraction, change detection, and automated mapping. GLSM was invented in 1976-77 by Dr. Urho Rauhala as an application of his efficient array algebra solution techniques to support stereo mensuration rates on the order of hundreds of posts per second on a general purpose 1 MIPS computer. This paper summarizes the GLSM technology and discusses some experimental results. All cases demonstrate GLSMs ability to produce dense image mensurations with very high reliability, accuracy and resolution. Other GLSM applications include Large Area Digital Image Maps, GIs database maintenance, automated planetary mapping, and vehicle navigation.
Sensitivity, residue and scent.: Concepts to inform interaction design for the support of information space navigation

Navigation through an information space that is often unknown, unstructured and extensive can be challenging, especially when the target is not fully formulated and exploration of the space is deemed to be beneficial. The design of an information space requires the provision of effective navigational cues to indicate to users what information the space contains and how to get to that information. We suggest, and demonstrate by means of examples that the concepts of sensitivity, residue and scent can inform the design of such navigational cues. In order to show the wide application of these concepts we identify their potential to facilitate navigation in three very different contexts. One is the traditional information space in which information is explicitly available to users. A second comprises information spaces in which sensitivity information can be computed, and is especially relevant to interactive design (e.g., engineering or financial) and decision-making. More speculatively, we suggest that the concepts of sensitivity, residue and scent may be of value in socially defined contexts in which navigational cues arise from the collective or individual behaviour of other users.
3-D Sensing With Polar Exponential Sensor Arrays

Computations for 3-D vision are greatly simplified by looking at the world through polar exponential sensor arrays. Rotation and zoom invariance, and wide field of view with reduced pixel count, are well known benefits of such arrays. More subtle, equally powerful properties applicable to the interpretation of 3-D images, are described in this paper. Computations involving scaling, such as perspective and optic flow, are reduced to additive operations by the implicit logarithmic transformation of image coordinates. Expressions for such computations are derived in this paper and applied to sensor design examples. Advantages of polar exponential arrays over x-y rasters for binocular vision are also discussed.
Bandwidth Guaranteed Multicast Scheduling for Buffered Crossbar

The limitations in complexities and extensibilities of current scheduling policies based on combined input and cross-point queuing switch (CICQ) are first analyzed. To overcome the deficiencies in supporting fair and QOS scheduling, we propose a fair and simple high-performance multicast scheduling algorithm for Combined Input Crosspoint Queued Switches, which is called multicast Fair Service and Group Smoothed Round Robin (mFGSR). The complexity of the algorithm is only O(1). mFGSR groups and schedules flows according to the weight of flows, thus it has good fairness and can adapt to the need of real-time performance. Theorotical analysis and simulation results show that mFGSR exhibits good delay, throughput and anti-burst performance.
Critical literacy, self-protection and delinquency: the challenges of participatory media for youths at-risk

While pedagogy is predominantly viewed from the perspective of classroom instruction, educators worldwide invariably play a critical pastoral role of shaping the personal development of their students and nurturing in them life skills. With the avid use of participatory media by young people in peer interaction, educators need to be aware of the attendant risks and opportunities so that they may offer counsel and render appropriate advice. To this end, through interviews with 36 Singaporean male juvenile delinquents and youths-at-risk, this study explores how these youths utilise participatory media in their peer interaction. The findings indicate that for this vulnerable youth population, participatory media such as social networking sites can become a platform through which they are unwittingly drawn into criminal behaviour and post-rehabilitation, participatory media may offer an insidious route to recidivism. Participatory media complicates peer interaction by presenting risk factors such as network transparency, negative peer modelling, network seepage and network persistence, all of which have implications for these youths sliding further into delinquency and criminal activity. This article concludes with recommendations on the strategies which youths-at-risk can employ to avoid the risks of participatory media.
Improving Software Quality through Program Analysis

In this paper, we present the Program Analysis Framework (PAF) to analyze the software architecture and software modularity of large software packages using techniques in Aspect Mining. The basic idea about PAF is to record the call relationships information among the important elements firstly and then use the different analysis algorithms to find the crosscutting concerns which could destroy the modularity of the software from this recording information. We evaluate our framework through analyzing DATE, the ALICE Data-Acquisition (DAQ) software which handles the data flow from the detector electronics to the permanent storage archiving. The analysis results prove the effectiveness and efficiency of our framework. PAF has pinpointed a number of possible optimizations which could be applied and help maximizing the software quality. PAF could also be used for the analysis of other projects written in C language.
PC based number plate recognition system

A PC based number plate recognition system is presented. Digital gray-level images of cars are thresholded using the Niblack algorithm, which was found to outperform all binarization techniques previously used in similar systems. A simple yet highly effective rule-based algorithm detects the position and size of number plates. Characters are segmented from the thresholded plate using blob-colouring, and passed as 15/spl times/15 pixel bitmaps to a neural network based optical character recognition (OCR) system. A novel dimension reduction technique reduces the neural network inputs from 225 to 50 features. Six small networks in parallel are used, each recognising six characters. The system can recognize single and double line plates under varying lighting conditions and slight rotation. Successful recognition of complete registration plates is about 86.1%.
Textural classification of high resolution digital satellite imagery

This paper presents investigations with digital spectral and textural classification of urban environment using SPOT XS imagery and grey level co-occurrence matrix (GLCM) approach. The results indicate that a combination of texture and spectral features significantly improves the classification accuracy compared to a classification with pure spectral features only. This improvement is about 9% for an addition of one texture feature.
Mobile node extension employing buffering function to improve handoff performance

In the near future, a mobility management protocol (MMP) that provides network layer mobility over all access technologies will be required. Mobile IPv6 (MIP) and Hierarchical Mobile IPv6 (HMIP) are candidates for MMP; however the communication quality level of these candidates is severely degraded during handoff. As a result, over the past several years, many advanced MMPs have been proposed to improve handoff performance. Most of these require some modifications to the access routers (ARs) and some specifications on the access technologies though it will be difficult to manage all ARs and their wireless links in the future mobile Internet. Therefore, as another way to improve the handoff performance of MIP and HMIP, we propose a mobile node (MN) extension employing a buffering function. Computer simulation results show that the proposed MN improves handoff performance over UDP and TCP communications.
Decision theoretic framework for NLOS identification

This paper presents the problem of identifying whether a received signal at a base station is due to a line-of-sight (LOS) transmission or not (NLOS). This is a first step towards estimating the mobile station's location. We formulate the NLOS identification problem as a binary hypothesis test where the range measurements are modeled as being corrupted by additive noise, with different probability distributions depending on the hypothesis. We solve the binary hypothesis test under several assumptions, proposing appropriate decision criteria.
On Paradigms and Methods: What Do You Do When the Ones You Know Don't Do What You Want Them To? issues in the Analysis of Data in the Form of Videotapes

This article examines a range of issues related to the development of nonstandard methods for the analysis of videotapes of problem-solving sessions. It proposes some rather stringent standards for novel methods, standards concerned with issues of validity, reliability, and the communication of methods and data. The discussion is illustrated by the detailed examination of two case studies that employ two different grain sizes of analysis—the first macroscopic, the second microscopic. In the light of those case studies, theoretical issues regarding the relationships among theory-based, method-based, and problem-based approaches to programmatic research in the learning sciences are considered.
The Dynamic Model Embed in Augmented Graph Cuts for Robust Hand Tracking and Segmentation in Videos

Segmenting human hand is important in computer vision applications, for example, sign language interpretation, human computer interaction, and gesture recognition. However, some serious bottlenecks still exist in hand localization systems such as fast hand motion capture, hand over face, and hand occlusions on which we focus in this paper. We present a novel method for hand tracking and segmentation based on augmented graph cuts and dynamic model. First, an effective dynamic model for state estimation is generated, which correctly predicts the location of hands probably having fast motion or shape deformations. Second, new energy terms are brought into the energy function to develop augmented graph cuts based on some cues, namely, spatial information, hand motion, and chamfer distance. The proposed method successfully achieves hand segmentation even though the hand passes over other skin-colored objects. Some challenging videos are provided in the case of hand over face, hand occlusions, dynamic background, and fast motion. Experimental results demonstrate that the proposed method is much more accurate than other graph cuts-based methods for hand tracking and segmentation.
Video-Based Language Learning Environment Using an Online Video-Editing System

Unlike most videoconferencing systems, the new videoconferencing system we have developed allows sessions between a native English teacher and a non-native second language learner to be recorded and edited for later reuse for educational instruction purposes as a teaching aid thus enhancing explanations and comments about pronunciation and intonation. To develop easy-to-use tools for adding such enhancements, a new paradigm called video correction is proposed implementing as a video correction system so that the learner can understand the teacher's comments as if they were corrections on paper. The prototype system, called Viclle (Vi deo-based C ommunication L anguage L earning System),support both a teacher (a native English speaker) and a learner (non-native speaker) with video correction and communication. A new XML schema, called VCML (V ideo-based C orrection M arkup L anguage), is exploited to represent pedagogical correction essentially in a compact text format so that both teacher and learner can communicate through e-mail without sending video files back and forth. In addition, VCML relates the teacher's corrections to the video with links, and it includes the learner's feedback. Therefore, the teacher and the learner can communicate with each other by using the VCML document only.
Attitude and altitude control using discontinuous gaits for walking machines

Principles of legged locomotion have been established in the previous years. At present, many mathematical problems have been studied and solved; but in the implementation of this knowledge, new real problems have appeared. Flexion on links and joints and terrain compression introduce some undesirable characteristics in the system. These phenomena are not easy to model; therefore, sensors should be used. This paper deals with the implementation of attitude/altitude control on a walker. The main scope is to perform control using non-sophisticated sensors such as contact sensors, inclinometers, and joint position sensor. This paper describes the algorithms and the experimental results obtained working on a four legged walking machine. <<ETX>>
Comment: Graphical Models, Causality and Intervention

I am grateful for the opportunity to respond to these two excellent papers. Although graphical models are intuitively compelling for conceptualizing statistical associations, the scientific community generally views such models with hesitancy and suspicion. The two papers before us demonstrate the use of graphs specifically, directed acyclic graphs (DAGs) -as a mathematical tool of great versatility and thus promise to make graphical languages more common in statistical analysis. In fact, I find my own views in such close agreement with those of the authors that any attempt on my part to comment directly on their work would amount to sheer repetition. Instead, as the editor suggested, I would like to provide a personal perspective on current and future developments in the areas of graphical and causal modeling. A complementary account of the evolution of belief networks is given in Pearl (1993a). I will focus on the connection between graphical models and the notion of causality in statistical analysis. This connection has been treated very cautiously in the papers before us. In Lauritzen and Spiegelhalter (1988), the graphs were called "causal networks," for which the authors were criticized; they have agreed to refrain from using the word "causal. " In the current paper, Spiegelhalter et al. deemphasize the causal interpretation of the arcs in favor of the "irrelevance" interpretation. I think this retreat is regrettable for two reasons: first, causal associations are the primary source of judgments about irrelevance, and, second, rejecting the causal interpretation of arcs prevents us from using graphical models for making legitimate predictions about the effect of actions. Such predictions are indispensable in applications such as treatment management and policy analysis. I would like to supplement the discussion with an ac'count of how causal models and graphical models are related. It is generally accepted that, because they provide information about the dynamics of the system under study, causal models, regardless of how they are discovered or tested, are more useful than associational models. In other words, whereas the joint distribution
Learning Designs

Abstract Researchers espouse that youth are learning differently than any other generation. Many researchers believe that because youth are leading the way with technology, their technology practices impact the way that they connect with the world around them. As a result, educators examine how to successfully engage youth in learning by understanding how to tap their technology practices. This study utilizes a sociotechnical framework to bring to light emergent structures of participation during student-teacher instant messaging interactions to support learning. Analysis illuminates three emergent and fluid participation structures. These structures reflect both pedagogical models and the most current literature on how people learn.
Do choropleth maps linked with parallel coordinates facilitate an understanding of multivariate spatial characteristics?

Our study has three objectives. We want to investigate (1) whether choropleth maps linked with parallel coordinates help people understand the locations of vulnerable places and the factors making these places vulnerable, (2) whether sparklines that imitate the polylines from a parallel coordinate plot support the understanding of the information provided in that plot, and (3) whether a multiple-view geovisualization approach might be intuitive and useful also for nonexperts. Although we base our work on the functionalities available in the tool called ‘ViewExposed,’ we intend to outline more general conclusions on whether multiple linked views facilitate the understanding of multivariate spatial characteristics. An empirical study with 53 individuals was conducted to obtain insights on these objectives. Our task-based assessment considered the ways in which participants understood the dynamic linking capabilities. Some of the key findings are as follows: (1) even nonexpert users are able to use parallel coordinates linked with choropleth maps; however, only those with extensive inference-making abilities will do so efficiently; (2) parallel coordinates sparklines work as an independent component facilitating the understanding of multivariate data; and (3) the intuitive nature of a multiple-view geovisualization tool is not enough to encourage people to use it.
Searching data streams for variable length anomalies

Anomaly detection in data streams is the problem of extracting subsequences, which do not match an expected behavior. Its importance originates from its applicability in many fields such as system health monitoring, event detection in sensor networks, and detecting eco-system disturbances, etc. In detecting anomalous subsequences from data streams, the main challenge for the existing techniques is to determine the lengths of the normal and anomalous subsequences and thus creating a robust model for detecting the anomalous subsequences. In this paper, we propose an incremental algorithm based on the dynamic time warping technique to detect anomalous subsequences in data streams. The proposed algorithm works with relaxed constrains regarding the lengths of normal and/or the anomalous subsequences. That is the proposed algorithm is able to detect variable length anomalous subsequences from among variable length normal sequences. The proposed algorithm can extract variable length anomalies with linear cost of time and memory.
The Changing Information Systems (IS) Curriculum: A Survey of Undergraduate Programs in the United States

The core curriculum of information systems (IS) is vital to the IS field. It serves as a base of knowledge that all IS graduates should possess. Within academic and practitioners' communities, there have been constant discussions about the content of the IS core curriculum. In this article, the authors used a direct survey strategy to examine all undergraduate IS programs offered by business schools in the United States. The survey presents the core curricula of undergraduate IS programs based on accreditation criteria and the most recent IS curriculum model, IS 2002. The authors also compared the current results with those obtained 10 years ago in a separate study (J. L. Maier & S. Gambill, 1996). The research established the current baseline of undergraduate IS curricula and showed how the curricula have changed in the past decade. Information provided in this article should be valuable to IS educators and curriculum designers, as well as IS practitioners, to better understand the foundational knowledge.
Modelling of bibliometric approaches and importance of output verification in research performance assessment

This paper presents a model describing the various possibilities in the application of bibliometric techniques in evaluation processes. The model distinguishes between the goals and functions of a bibliometric analysis, and clearly indicates the limits of the various bibliometric approaches. In the so-called top-down or bottom-up approaches, the importance of verification of publication material is indicated. Another important feature of the paper is the description of the problem of the interpretation of the relationship between on the one hand organizational structures, and on the other hand fields of science, in the light of the two main approaches in bibliometric studies. Finally the paper contains a number of case-study examples of the model described. Copyright , Beech Tree Publishing.