Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation and Robustness of Hopfield Networks with Spiking Neurons

Computational models of neural activity and neural networks have been an active area of research as long as there have been computers, and have led several important discoveries in the eld of machine learning. One kind of articial network proposed by John J. Hopeld in 1982 has been among the more successful ones, and is still in active use today. It has been suggested that in addition to its merits in machine learning, it could also serve as a foundation of the explanation of human ability of recollection and association. However, Hopeld's original design used a very simplied model of neurons. By using so called integrate-and-remodels, higher realism can be achieved.This report begins with a discussion of mechanistic and quantitative description of neurons, in particular the induction of action potentials, and furthermore why an integrate-and-re model is a reasonable choice for a model of intermediate complexity. By explicitly describing individual spikes, a fundamental but often neglected characteristic of communication between neurons is captured. Integrate-and-re models are included in the Neural Simulation Tool (NEST), and in this report such a neural model is applied to Hopeld networks. Both spike-rate coding and temporal coding are studied, as well as a simple model of synaptic Spike-Timing DependentPlasticity (STDP) for online learning. The networks' robustness is evaluated with respect to changes in (a) global scaling of the synaptic weights, (b) delays in the synaptic connections, (c) level of noise and (d) strength of input stimuli. They are found to be somewhat sensitive, with (a) giving the most denite results, suggesting that the used description of Hopfield networks might not be an immediately plausible biological model. In particular, networks using temporal coding are found to be especially difficult to calibrate. This could reveal a potential weakness in relatively recent and apparently successful models.
Displaying readable object-space text in a head tracked, stereoscopic virtual environment

Object space text, although desirable for its correct occlusion behavior, often appears blurry or “shimmery” due to rapidly alternating text thickness when used with head tracked binocular stereo viewing. Text thickness tends to vary because it depends on scan conversion, which in turn depends on the user’s location in a head tracked environment, and the user almost never stays perfectly still. This paper describes a simple method of eliminating such blurriness for object space text that need not have a fixed location in the virtual environment, such as menu system and annotation text. Our approach positions text relative to the user’s view frustums (one frustum per eye), adjusting the 3D position of each piece of text as the user moves, so that the text occupies a constant place in each of the view frustums and projects to the same pixels regardless of the user’s location.
An Algorithmic Approach to Optimizing Network Resources for Public Safety LTE Networks

This report examines the problem of how to allocate limited network resources in a public safety LTE network for the purpose of disseminating video streams to end users. We develop a mathematical model of the network environment, including the definition of a new metric called usefulness. We then apply known optimization techniques and algorithms to our model and analyze the results. We incorporate the concept of local control for public safety practitioners into our model through the use of a priority function and simulate its performance.
Proceedings of the Third ACM SIGPLAN Workshop on Continuations (CW'01)

Local CPS conversion is a compiler transformation for impro ving the code generated for nested loops by a direct-style com piler. The transformation consists of a combination of CPS convers ion and light-weight closure conversion, which allows the comp iler to merge the environments of nested recursive functions. This merging, in turn, allows the backend to use a single machine-leve l procedure to implement the nested loops. Preliminary experiment s with the Moby compiler show the potential for significant reducti ons in loop overhead as a result of Local CPS conversion.
Sex determination of ancient human remains

6 LIST OF TABLES 7 LIST OF FIGURES 9 CHAPTER 1 10 INTRODUCTION 10 Research Aim 12 Problems 12 Thesis Organisation 12 CHAPTER 2 14 METHODOLOGY 14 Morphological Assessment 14 Population Variability 15 Reference Collections 17 Observer Error.18 Preservation and Recovery . 18 Statistical Analysis of Ancient Remains.20 CHAPTER 3 25 REVIEW OF STUDIES INVOLVING DETERMINATION OF SEX.25 Cranium 25 Pelvis. 35 Post–cranial.45 CHAPTER 4. 74 RESEARCH MATERIAL 74 Historical Setting.74 Equipment.77 Skeletal Material.77 CHAPTER 5.85 RESULTS AND DISCUSSION.85 Analysis of pelvis.85
A matrix-geometric solution for the multiserver nonpreemptive priority queueing model with mixed priorities

This paper describes the analysis of multiserver queues with nonpreemptive mixed priorities. Such priority structures occur, for example, in initiator settings within the mainframe operating system MVS: job classes have to be assigned to initiators and their priorities may differ amongst the initiators. Results of the analysis provide insight in how average queue lengths in this priority system behave under different class loads. Bounds have to be defined in order to obtain a matrix-geometric solution and it is shown how this affects the average queue lengths. The results should eventually allow to derive guidelines with respect to initiator definitions.
Plagiarism as a Violation of Scientific and Academic Integrity

Plagiarism is unauthorized appropriation of other people’s ideas, processes or text without giving correct credit and with intention to present it as own property. Appropriation of own published ideas or text and passing it as original is denominated self-plagiarism and considered as bad as plagiarism. The frequency of plagiarism is increasing and development of information and communication technologies facilitates it, but simultaneously, thanks to the same technology, plagiarism detection software is developing. There are diff erent software solutions for checking plagiarism. Most of them are based on concordance, i.e., comparison of text where program tools isolate and mark correspondent parts of the text and calculate its rate regarding the whole text. Several programs, besides comparing the texts, also search the Internet aiming for text with corresponding content. All programs can compare text written in the same language but translingual comparison with plagiarism detection software is not yet possible. The software is available through computer programs (WCopyfi nd) or Web Services (eTBlast, CrossCheck). Their advantage is in the possibility of fi nding the original source paper. eTBlast is the free of charge web based service for searching corresponding and highly similar scientific paper abstracts (it searches also Medline database), which served as the ground for constructing Deja vu database. Web based service CrossCheck is accessible only for members (academic institutions and journals) and by using computer similarity algorithm iThen cate of company iParadigms (Oakland, CA, USA), it checks accordance of the given text with the complete texts in the CrossCheck database. It is organized by collaboration of journal editorial boards and publishers who pass the published papers to the base and enable searching of content usually protected by subscription. The importance of recognizing and teaching plagiarism in the academic community at all levels of education is enormous. Scientific journal editors and scientists should fight together against unethical researches which are opposite to the scientific idea and harmful for scientific community and society, critically read and examine scientific publications, report plagiarism and other suspicious research misconduct to journal editorial boards and institutional authorities.
Virtual Reality on Mobile Devices: Investigating Factors Affecting the Shoebox VR Experience in Motion-based Games

Mobile 3D applications, especially games, are gaining popularity and due to the constant increase in graphics capabilities of mobile devices, the creation of more elaborate virtual worlds becomes possible. However, compared to traditional gaming platforms, mobile devices have a small form factor, which imposes new challenges on game designers, but also opens new opportunities. Shoebox VR offers a novel way of visualizing virtual environments and has already been applied in games. Whereas current games mainly use still scenes, we investigated the use of Shoebox VR in motion-based games. Our previous study demonstrated that Shoebox VR improved subjective user experience, in terms of subjective sense of depth perception, entertainment value and immersion. To further explore how user experience and gameplay are affected by Shoebox VR, this study investigated whether these variables are affected by factors like screen size and user interaction. By developing games, we were able to show that although screen size did not affect subjective experience, gameplay performance increased with a smartphone-sized device at low speeds using Shoebox VR. In addition, we demonstrated that touch screen interaction affects games using Shoebox VR, as gameplay performance was higher for Shoebox VR compared to standard visualization methods. In contrast, tilting interaction did not appear to affect Shoebox VR, indicating that the tilting controls can be used in combination with Shoebox VR without decreasing user experience or gameplay performance. Finally, our results suggested that Shoebox VR is especially functional and well-used when it is implemented as an essential part of the gameplay. Our study provided more insight in the usability of Shoebox VR in motion-based games, which contributes to the improvement of visualization methods of 3D environments on mobile devices.
Gradients from GOCE reveal gravity changes before Pisagua Mw 1⁄4 8 . 2 and Iquique Mw 1⁄4 7 . 7 large megathrust earthquakes

Considerable improvements in the measurement of the Earth gravity field from GOCE satellite mission have provided global gravity field models with homogeneous coverage, high precision and good spatial resolution. In particular, the vertical gravity gradient (Tzz), in comparison to the classic Bouguer anomaly, defines more accurately superficial mass heterogeneities. Moreover, the correction of these satellitederived data from the effect of Earth topographic masses by means of new techniques taking into account the Earth curvature, improves results in regional analyses. In a recent work we found a correlation between Tzz and slip distribution for the 2010 Maule Mw 1⁄4 8.8 earthquake. In the present work, we derive the vertical gravity gradient from the last GOCE only model, corrected by the topographic effect and also by the sediments on depocenters of the offshore region at the PerueChile margin, in order to study a spatial relationship between different lobes of the gravity derived signal and the seismic sources of large megathrust earthquakes. In particular, we analyze this relation for the slip models of the 1996 Mw 1⁄4 7.7 Nazca, 2001 Mw 1⁄4 8.4 Arequipa, 2007 Mw 1⁄4 8.0 Pisco events and for the slip models of the 2014 Mw 1⁄4 8.2 Pisagua and Mw 1⁄4 7.7 Iquique earthquakes from Schurr et al. (2014), including the previously analyzed 2010 Mw 1⁄4 8.8 Maule event. Then we find a good correlation between vertical gravity gradients and main rupture zones, correlation that becomes even stronger as the event magnitude increases. Besides this, a gravity fall in the gravity gradient was noticed over the area of the main slip patches at least for the two years before 2014 Mw 1⁄4 8.2 Pisagua and Mw 1⁄4 7.7 Iquique earthquakes. Additionally, we found temporal variations of the gravity field after 2010 Mw 1⁄4 8.8 Maule event, related to the main patches of the slip distribution, and coseismic deformation. Therefore, we analyzed vertical gravity gradient field variations as an indirect measure of the variable seismic coupling finding a potential relationship between Tzz and the seismic b-value. These relationships exemplify the strong potential of the satellite only derived models as a predictive tool to determine potential seismic energy released in a subduction segment, determining the potential size of a potential rupture zone, and in particular internal slip distribution that allows inferring coseismic displacement field at surface. © 2015 Published by Elsevier Ltd.
A novel method for EMG decomposition based on matched filters

Introduction Decomposition of electromyography (EMG) signals into the constituent motor unit action potentials (MUAPs) can allow for deeper insights into the underlying processes associated with the neuromuscular system. The vast majority of the methods for EMG decomposition found in the literature depend on complex algorithms and specific instrumentation. As an attempt to contribute to solving these issues, we propose a method based on a bank of matched filters for the decomposition of EMG signals. Methods Four main units comprise our method: a bank of matched filters, a peak detector, a motor unit classifier and an overlapping resolution module. The system’s performance was evaluated with simulated and real EMG data. Classification accuracy was measured by comparing the responses of the system with known data from the simulator and with the annotations of a human expert. Results The results show that decomposition of non-overlapping MUAPs can be achieved with up to 99% accuracy for signals with up to 10 active motor units and a signal-to-noise ratio (SNR) of 10 dB. For overlapping MUAPs with up to 10 motor units per signal and a SNR of 20 dB, the technique allows for correct classification of approximately 71% of the MUAPs. The method is capable of processing, decomposing and classifying a 50 ms window of data in less than 5 ms using a standard desktop computer. Conclusion This article contributes to the ongoing research on EMG decomposition by describing a novel technique capable of delivering high rates of success by means of a fast algorithm, suggesting its possible use in future real-time embedded applications, such as myoelectric prostheses control and biofeedback systems.
Data Modeling and Database Design

DATA MODELING AND DATABASE DESIGN presents a conceptually complete coverage of indispensable topics that each MIS student should learn if that student takes only one database course. Database design and data modeling encompass the minimal set of topics addressing the core competency of knowledge students should acquire in the database area. The text, rich examples, and figures work together to cover material with a depth and precision that is not available in more introductory database books.
A NEW DESIGN TOOL FOR TRAFFIC MANAGEMENT SCHEMES

Conventional traffic models can be used to predict how road-users will respond to traffic management measures, but they are not capable of making intelligent decisions about how the measures themselves should be configured. This paper describes a design tool currently being developed to improve traffic circulation so as to encourage a safer and more efficient pattern of movement. It is based on a heuristic algorithm that attempts to minimize the overall level of 'conflict' generated through the interaction between traffic streams on an urban network.
A learning framework for higher-order consistency models in multi-class pixel labeling problems

Recently, higher-order Markov random field (MRF) models have been successfully applied to problems in computer vision, especially scene understanding problems. One successful higher-order MRF model for scene understanding is the consistency model [Kohli and Kumar, 2010; Kohli et al., 2009] and earlier work by Ladicky et al. [2009, 2013] which contain higher-order potentials composed of lower linear envelope functions. In semantic image segmentation problems, which seek to identify the pixels of images with pre-defined labels of objects and backgrounds, this model encourages consistent label assignments over segmented regions of images. However, solving this MRF problem exactly is generally NP-hard; instead, efficient approximate inference algorithms are used. Furthermore, the lower linear envelope functions involve a number of parameters to learn. But, the typical cross-validation used for pairwise MRF models is not a practical method for estimating such a large number of parameters. Nevertheless, few works have proposed efficient learning methods to deal with the large number of parameters in these consistency models. In this thesis, we propose a unified inference and learning framework for the consistency model. We investigate various issues and present solutions for inference and learning with this higher-order MRF model as follows. First, we derive two variants of the consistency model for multi-class pixel labeling tasks. Our model defines an energy function scoring any given label assignments over an image. In order to perform Maximum a posteriori (MAP) inference in this model, we minimize the energy function using move-making algorithms in which the higher-order problems are transformed into tractable pairwise problems. Then, we employ a max-margin framework for learning optimal parameters. This learning framework provides a generalized approach for searching the large parameter space. Second, we propose a novel use of the Gaussian mixture model (GMM) for encoding consistency constraints over a large set of pixels. Here, we use various oversegmentation methods to define coherent regions for the consistency potentials. In general, Mean shift (MS) produces locally coherent regions, and GMM provides globally coherent regions, which do not need to be contiguous. Our model exploits both local and global information together and improves the labeling accuracy on real
Collaboration between UK universities : a machine-learning based webometric analysis

I TABLE OF CONTENTS IV ACKNOWLEDGEMENTS IX PUBLICATIONS FROM THESIS X LIST OF FIGURES XII LIST OF TABLES XIV INTRODUCTION 1 AIM 4 Study One: Automatically classifying web pages and hyperlink targets 5 Study Two: Using machine learning to filter out irrelevant links for collaboration studies 7 Study Three: Investigating web mentions as a collaboration indicator 9 Study Four: Exploratory cluster analysis of computer science research groups. 11 THESIS OUTLINE 13 LITERATURE REVIEW 16 INTRODUCTION 17 WEB MINING 23 Web Content Mining 25 Web Structure Mining 25 Web Usage Mining 26
Implementation and Management of an Information Systems Practicum in a Graduate Computer Information Technology Curriculum

This paper reports on the implementation and management of an Information Systems Practicum used in a graduate Computer Information Technology program. The Information Systems Practicum provides a student with an 8 month learning experience that is academically rigorous, intellectually challenging, and which serves as a culminating experience to the student’s coursework. Specifically designed around an action research methodology, the Information Systems Practicum engages the student as a practitioner and provides real work opportunity congruent with the course of study. Implementation and management strategies, as well as the educational and philosophical foundations of the Practicum, are investigated along with providing conclusions about the program drawn over a 4 year period of time.
gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution

Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones’ relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system’s application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.
What Does Average Really Mean? Making Sense of Statistics.

has put many educational leaders in a position where they are expected to collect and use increasing amounts of data to inform their decision making. Yet, because many programs that prepare administrators, including school business officials, do not require a statistics course or a course that is more theoretical than practical, administrators tend to have only limited knowledge of how to analyze, interpret, and use their data. We’re here to help. This article provides a userfriendly primer on basic statistics and how you can use them to make sense of your data. Statistics can be broken into two broad categories: descriptive and inferential. Descriptive statistics are used to describe or summarize a collection of data. You almost certainly have experience with descriptive statistics, such as the mean that is often used for reporting attendance data and personnel salaries. Inferential statistics, in contrast, are most often used when you want to generalize beyond the data that you have. For example, your district has results from a curricular intervention that was piloted in two elementary schools and needs to determine whether to expand the intervention to the rest of its elementary classrooms. You would use inferential statistics in your decision-making process. What Does Average Really Mean? Making Sense of Statistics