Miracle-dz/UniFAR-FTUs huggingface dataset:
Comment: Can We Trust a Method Just Because We like its Predictions?

If the analysis and conclusions of Wainer, Njue, and Palmer (2000) are right, then we live in a special time: After 70 years in which men's and women's performances (both absolute and relative to one another) could be accurately extrapolated using straight lines, this method will stop working very soon. I happen to agree. But I wonder if there has ever been a time when people didn't feel that the runners and swimmers of their time were finally approaching the limits of human performance. Who knows, perhaps changes in training or diet, or in the rules regarding the usc of steroids and other drugs, will allow improvements to continue this way for several more decades. I doubt it, but history should make us cautious. An interesting feature of the analysis by Wainer et al. is that it attempts to predict differences between men's and women's speeds (in some future year in which records for both sexes have stabilized) without predicting the limiting speed for either sex. That's a very good thing, as it's clearly impossible to extract a reliable plateau speed hased on historical data, at least for running: Just take a look at Pig. 10! In fact, as can be seen in Fig. 10, and as noted by Whipp and Ward (1992), not only are running speeds (still) improving linearly for most running events,
Automatic link layer topology discovery of IP networks

Network topology information is useful for network administration and planning. Techniques for automatic generation of the network layer topology maps of IP networks have been proposed by Lin, Lai and Chen (see Proc. of IEEE ICC, 1998), by Mansfield, Ouchi, Jayanthi, Kimura, Ohta and Nemoto (see Proc. of IEEE INFOCOM, p.473-80, 1996) and by Schonwalder and Langendorfer (1993). The devices in a subnet can be found using a network layer topology discovery tool. However, the link layer topology of the subnet can not be obtained by a network layer topology discovery tool. An algorithm for automatic discovery of the link layer topology of an IP subnet is proposed in this paper. The algorithm uses the link layer topology configuration information obtained from various sources including the MIBs in routers, bridges, and switches, the Internet Control Message Protocol (ICMP), the Domain Name System (DNS), and etc. to produce the link layer topology map. The proposed link layer topology discovery algorithm has been implemented based on the Tcl/Tk and Scotty environment.
Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems (Signals and Communication Technology)

Space/Time Emerging Face Biometrics. - Pose and Illumination Invariant Face Recognition Using Video Sequences. - Recognizing Faces Across Age Progression. - Quality Assessment and Restoration of Face Images in Long Range/High Zoom Video. - Core Faces: A Shift-Invariant Principal Component Analysis (PCA) Correlation Filter Bank for Illumination-Tolerant Face Recognition. - Multi-Sensory Face Biometrics. - Towards Person Authentication by Fusing Visual and Thermal Face Biometrics. - Multispectral Face Recognition: Fusion of Visual Imagery with Physiological Information. - Feature Selection for Improved Face Recognition in Multisensor Images. - Multimodal Face Biometrics. - Multimodal Face and Speaker Identification for Mobile Devices. - Quo Vadis: 3D Face and Ear Recognition? - Human Recognition at a Distance in Video by Integrating Face Profile and Gait. - Generic Approaches to Multibiometric Systems. - Fusion Techniques in Multibiometric Systems. - Performance Prediction Methodology for Multibiometric Systems.
Mixture Model Clustering in the Analysis of Complex Diseases

The topic of this thesis is the analysis of complex diseases, and specifically the use of k-means and mixture modeling based clustering methods to do it. We concern ourselves mostly with the modeling of complex phenotypes of diseases: the symptoms and signs of diseases, and the other multiple cophenotypes that go with them. The two related questions we seek answers for are: 1) how can we use these clustering methods to summarize the complex, multivariate phenotype data, for example to be used as a simple phenotype in genetic analyses and 2) how can we use these clustering methods to find subgroups of sufferers of a particular disease, such that might share the same causal factors of the disease. Current methods for studies on medical genetics ideally call for a single or at most handful of univariate phenotypes to be compared to genetic markers. Multidimensional phenotypes cannot be handled by the standard methods, and treating each variable as independent and testing one hundred phenotypes with unclear true dependency structure against thousands of markers results into problems with both running times and multiple testing correction. In this work, clustering is utilized to summarize a multi-dimensional phenotype into something that can then be used in association studies of both genetic and other type of potential causes. I describe a clustering process and some clustering methods used in this
Lombardy EPA Obtorto Collo Data and Anti-pollution Policies Fallacies

ARPA Lombardia EPA maintains pollution monitoring stations since 1999. Measured data is “somewhat” available through ARPA’s website. “Somewhat” because a CAPTCHA protected download request form must be filled up for every combination of (station, pollutant, timeframe < 1 yr). I.e., citizens wanting the whole dataset should complete thousands requests by hand. In 2003 Lombardia government decided to ban classes of vehicles due to a supposed air pollution increase. The author searched for data to counteract that decision - air pollution is in fact almost constantly decreasing since the seventies - found about ARPA’s overcomplicated download procedure and downloaded some of the data, just the amount needed to argument against the ban. He also decided to set up an automated system to overcome that difficulty for future purposes. The system is working since 2005. The whole set of collected data has been published (i.e., “freed”) on the author’s website, thus implementing the title’s obtorto collo (from latin, it means “reluctantly”, “unwillingly”) data from ARPA.
Video shot classification with concept detection

It is a challenging work to classify video shots into a predefined genre set according to their semantic contents, which is helpful to video indexing, summarization and retrieval. This research proposes a novel shot classification algorithm with concept detection for news video programs. Six semantic shot types are studied and categorized: Anchorperson, Monologue, Reporter, Commercial, Still image and Miscellaneous, in which anchorperson shots are detected by clustering methods, reporter and monologue shots are distinguished by Conditional Random Fields (CRFs), and the last three categories are picked out by rule-based methods. Multimodality features are employed, such as visual, audio, face, temporal and contextual features. The experimental results show its effectiveness and achieve a high average accuracy of 96.5%.
Domain-Partitioned Parallel Sort-Merge Join

This thesis studies the utility of parallelizing sort-merge join in a shared-memory processing environment. The investigated algorithm partitions the work of the sort-merge equi-join by dividing the domain of the join attribute into a set of non-overlapping ranges. Two distinct ways of sorting the relations in parallel for the sort-merge join are investigated: one, based on a concurrent heap used for replacement selection, and a second, using in-memory sorting. The investigation includes both theoretical analysis and implementation results, with direct comparability to previous work on parallel hash-and nested loops joins. Both processor-and I/O-bound environments are considered. It is concluded that parallel sort-merge join is inferior to hash-based join algorithms unless the joining relations are already sorted. Parallel run forming in a shared-memory environment, and the parallel sorting of arrays with large elements are also discussed. ii Acknowledgements Thanks are in order to the taxpayers of Canada, who funded the author during his studies through the Natural Sciences and Engineering Research Council. Credit is also due Prof. P.-A. Larson, for suggesting the topic of parallelizing the sort-merge join algorithm, as well as the notion of joining attribute value ranges. Prof. Larson also arranged access to the Sequent multiprocessor at the University of Waterloo that was used for the experiments conducted for this thesis. on the tiller of this project, and for showing no fear when facing early drafts of this thesis. The author is indebted to Drs. Larson and Sevcik for much advice and patience in the course of the project. Finally, the author wishes to thank Prof. T. Abdelrahman, for generously agreeing to be the second reader of this thesis.
Decision Tree Algorithm Improved with a Time-weighted Entropy

— This paper proposes a method to construct a decision tree with a time-weighted entropy that is improved from ID3 algorithm. Decision tree is a typical method in learning tendencies of given data. We define a time-weighted entropy that can apply to data usefully which changes with time like user’s preference. A user’s preference may change with time, thus we need to look at recent profile more than old one in order to discover the user’s recent preference. The time-weighted entropy gives weight on each data according to its recentness. We replace the standard entropy in ID3 algorithm with the time-weighted entropy and also adopt it into two pruning methods for coping with over-fitting. The one is pre-pruning, which stops a node from being expanded if its entropy is smaller than a threshold, and the other is the post-pruning named EBP(Error-Based Pruning). We analyze the tendencies of users with the improved ID3 algorithm. The improved ID3 shows more favorable results than the existing method, because it considers the time when data is generated. The pro-posed algorithms that use the time-weighted entropy generates a decision tree which is much simpler and more effective than the existing decision tree generation and pruning algorithms.
Model‐based event‐triggered predictive control for networked systems with communication delays compensation

This paper addresses the model‐based event‐triggered predictive control problem for networked control systems (NCSs). Firstly, we propose a discrete event‐triggered transmission scheme on the sensor node by introducing a quadratic event‐triggering function. Then, on the basis of the aforementioned scheme, a novel class of model‐based event‐triggered predictive control algorithms on the controller node is designed for compensating for the communication delays actively and achieving the desired control performance while using less network resources. Two cases, that is, the value of the communication delay of the first event‐triggered state is less or bigger than the sampling period, are considered separately for certain NCSs, regardless of the communication delays of the subsequent event‐triggered states. The codesign problems of the controller and event‐triggering parameter for the two cases are discussed by using the linear matrix inequality approach and the (switching) Lyapunov functional method. Furthermore, we extended our results to the NCSs with systems uncertainties. Finally, a practical ball and beam system is studied numerically to demonstrate the compensation effect for the communication delays with the proposed novel model‐based event‐triggered predictive control scheme. Copyright © 2014 John Wiley & Sons, Ltd.
Cross platform classification of microarrays by rank comparison

Mining the microarray data accumulated in the public data repositories can save experimental cost and time and provide valuable biomedical information. Big data analysis pooling multiple data sets increases statistical power, improves the reliability of the results, and reduces the speciﬁc bias of the individual study. However, integrating several data sets from diﬀerent studies is needed to deal with many problems. In this study, I limited the focus to the cross platform classiﬁcation that the platform of a testing sample is diﬀerent from the platform of a training set, and suggested a simple classiﬁcation method based on rank. This method is compared with the diagonal linear discriminant analysis, k nearest neighbor method and support vector machine using the cross platform real example data sets of two cancers.
A corpus driven study of the potential for vocabulary learning through watching movies

In this corpus driven study, the scripts of 143 movies consisting of 1,267,236 running words were analyzed using the RANGE program (Heatley et al. 2002) to determine the number of encounters with low frequency words. Low frequency words were operationalized as items from Nation’s (2004) 4th to 14th 1,000-word BNC lists. The results showed that in a single movie, few words were encountered 10 or more times indicating that only a small number of words may be learned through watching one movie. However, as the number of movies analyzed increased, the number of words encountered 10 or more times increased. Twenty-three percent of the word families from Nation’s (2004) 4th 1,000-word list were encountered 10 or more times in a set of 70 movies. This indicates that if learners watch movies regularly over a long period of time, there is the potential for significant incidental learning to occur
Software Usability Testing: Do User Self-Consciousness and the Laboratory Environment Make any Difference?

The purpose of the study was to evaluate the effect of laboratory environment, user self-consciousness, and user experience on the user's subjective evaluation of software usability. The study employed a 2 × 2 × 2 factorial between-subjects design with 2 levels of Laboratory Environment (Cameras and Mirror vs. No Cameras and Mirrors), 2 levels of User Self-Consciousness (Low vs. High), and 2 levels of User Experience (Novice, Experienced). The users were asked to learn, then use, and finally subjectively evaluate a restricted subset of common word processing features over three hours of participation. Day 1 was a training day and Day 2 was a test day. Results indicated that high self-conscious and novice users make more word processing errors. However, they were no more likely to make those errors in the presence of cameras and a mirror. More importantly, the evidence for any effect of the independent variables on subjective evaluation was sparse–limited to the interaction of self-consciousness and laboratory environment on just three of twelve factors. Moreover, the pattern of these interactions indicated that self-consciousness and the laboratory environment did not influence subjective evaluation in any predictable manner. Despite some methodological shortcomings, the conclusion was drawn that these variables do not have a major impact on subjective evaluation of software usability.
Introduction to linear optimization

p. 27, l. −11, replace “Schwartz” by “Schwarz” p. 69, l. −13: “ai∗x = bi” should be “ai∗x = bi∗” p. 126, l. 16, replace “inequality constraints” by “linear inequality constraints” p. 153, l. −8, replace aix 6= bi by aix 6= bi p. 163, Example 4.9, first line: replace “from” with “form” p. 165, l. 11, replace p′Ax ≥ 0 by p′Ax ≥ 0 p. 175, l. 1, replace “To this see” by “To see this” p. 203, l. 12: replace x ≥ 0 by x ≥ 0, xn+1 ≥ 0 p. 216, l. −6: replace “≤ c}” by “≤ c′}” p. 216, l. −3: replace c′ by (c1)′ p. 216, l. −2: replace c′ by (c2)′ p. 216, l. −1: right-hand side should be λ(c1)′ + (1− λ)(c2)′ p. 220, l. −12: replace “added to the pivot row” by “added to the zeroth row”
Open badges for education: what are the implications at the intersection of open systems and badging?

Badges have garnered great interest among scholars of digital media and learning. In addition, widespread initiatives such as Mozilla’s Open Badge Framework expand the potential of badging into the realm of open education. In this paper, we explicate the concept of open badges. We highlight some of the ways that researchers have examined badges as part of educational practice and also highlight the different definitions of open-ness that are employed in popular and scholarly thought. By considering badges from three different perspectives (motivation, pedagogy, and credential) and the concept of openness from three different perspectives (production, access and appropriation) we develop a framework to consider the tensions where these competing conceptions meet. This explication illuminates how the ideas of open and badges intersect, and clarifies situations where these concepts come into direct conflict or mutually enhance each other. Our analysis pinpoints and elucidates particular areas where research is needed to better understand the complex phenomenon of open badges, and also offers design considerations for developers, educators, and organizations that are actively involved in open badges. Keywords: open education; gamification; learning; credentials; badges; education reform (Published: 8 August 2014) Citation : Research in Learning Technology 2014, 22 : 23563 - http://dx.doi. org/10.3402/rlt.v22. 23563
Proportional reasoning as a threshold to numeracy at university: a framework for analysis

There is a generally acknowledged need for students to be quantitatively literate in an increasingly quantitative world. This includes the ability to reason critically about data in context. We have noted that students experience difficulty with the application of certain mathematical and statistical concepts, which in turn impedes progress in the development of students’ critical reasoning ability. One such concept, which has the characteristics of a threshold concept, is that of proportional reasoning. The main focus of this article is a description of the development of a framework using an adapted phenomenographic approach that can be used to describe students’ experiences in the acquisition of the concept of comparing quantities in relative terms. The framework has also helped to make explicit the elements that constitute a full understanding of the requirements for the proportional comparison of quantities. Preliminary results from using the framework to analyse students’ responses to assessment questions showed that many students were challenged by proportional reasoning. When considering the notion of the liminal space that is occupied en route to a full understanding of a threshold concept, about half of the students in the study were at the preliminal stage of understanding the concept and very few were at the threshold.
Profiling e-health projects in Africa: trends and funding patterns

There is a severe shortage of healthcare provision in Africa. e-Health, the use of Information and Communication Technologies (ICT) to support healthcare, may help to ease this problem. e-Health projects support a wide range of applications ranging from telemedicine to global research collaborations made possible via e-Infrastructures, worldwide systems of integrated advanced high performance networking and computing ICT. To try to understand the state of e-Health in Africa, this paper aims to create a picture and to present an analytical review of some of these initiatives in Africa. A review framework composed of multiple search methods is developed and applied to yield a broad coverage of e-Health projects over the African continent. Seven quantitative analyses on the projects are presented. Major observations include that there is a tendency for e-Health projects to grow in number in some African countries over time; that African countries with larger Gross National Incomes tend to attract more e-Health projects; that e-Health projects in Africa focus on telemedicine, health education and health-related research; that there is a wide range of funding bodies, some of which have a geographical focus, and that the number of m-Health projects has been rising sharply.
Improving the presentation of library data using FRBR and Linked data

When a library end-user searches the online catalogue for works by a particular author, he will typically get a long list that contains different translations and editions of all the books by that author, sorted by title or date of issue. As an attempt to make some order in this chaos, the Pode project has applied a method of automated FRBRizing based on the information contained in MARC records. The project has also experimented with RDF representation to demonstrate how an author’s complete production can be presented as a short and lucid list of unique works, which can easily be browsed by their different expressions and manifestations. Furthermore, by linking instances in the dataset to matching or corresponding instances in external sets, the presentation has been enriched with additional information about authors and works.
Network efficiency for wireless Internet access

It is foreseeable that more and more data traffic generated by interactive application will be carried by the current mobile cellular networks, which is currently dominated by circuit based voice calls. In this paper we propose to use network efficiency, which considers both revenue and network cost as criteria to dimension bandwidth between real-time service and best effort service. Optimized network efficiency reserves some bandwidth for best-effort services, while real-time traffic enjoys preemptive priority beyond the reserved bandwidth. The reservation for best-effort traffic has special significance for users accessing the Internet via a radio link.
Using a neural network to predict test case effectiveness

Test cases based on command language or program language descriptions have been generated automatically for at least two decades. More recently, domain based testing (DBT) was proposed as an alternative method. Automated test data generation decreases test generation time and cost, but we must evaluate its effectiveness. We report on an experiment with a neural network as a classifier to learn about the system under test and to predict the fault exposure capability of newly generated test cases. The network is trained on test case metric input data and fault severity level output parameters. Results show that a neural net can be an effective approach to test case effectiveness prediction. The neural net formalizes and objectively evaluates some of the testing folklore and rules-of-thumb that are system specific and often require many years of testing experience. <<ETX>>
DNA Chemical Reaction Network Design Synthesis and Compilation

The advantages of biomolecular computing include 1) the ability to interface with, monitor, and intelligently protect and maintain the functionality of living systems, 2) the ability to create computational devices with minimal energy needs and hazardous waste production during manufacture and lifecycle, 3) the ability to store large amounts of information for extremely long time periods, and 4) the ability to create computation analogous to human brain function. To realize these advantages over electronics, biomolecular computing is at a watershed moment in its evolution. Computing with entire molecules presents different challenges and requirements than computing just with electric charge. These challenges have led to ad-hoc design and programming methods with high development costs and limited device performance. At the present time, device building entails complete low-level detail immersion. We address these shortcomings by creation of a systems engineering process for building and programming DNA-based computing devices.