Miracle-dz/UniFAR-FTUs huggingface dataset:
Winner-take-all networks

Although winner-take-all (WTA) networks have wide applications in neural networks, they face several difficulties, such as committing premature decisions and scaling poorly with input size. In particular, they do not work properly in an asynchronous environment. In this thesis, an alternative to the classic WTA structure and its update method is proposed: the relaxed alternate update WTA (RA-WTA) network and a general mechanism that implements the RA-WTA network in random-update environments. Compared to WTA's synchronous activation method, the RA-WTA networks update the activation of their units in a relaxed alternate order. Using a two-stage update function, the RA-WTA networks are easier to scale, able to detect conflicts in inputs, and more adaptive to varying input size and number of competing agents. Moreover, such an update function enables the network to work properly with a relaxed alternate update. This scheme is extended to WTA networks with a distributed representation, and then adapted to random-update environments using a distributed hand-shaking (DHS) update method. The DHS update method effectively transforms a random-update WTA network to an RA-WTA network without loss of functionality. In addition, the DHS update method has fault-tolerant capability. The method is implemented in a distributed connectionist production system. Experimental results are also provided and compared against theoretical analyses of the RA-WTA network and the update scheme.
Semantic Processing of Morphologically Complex Words: Experimental Studies in Visual Word Recognition

This thesis examines the semantic processing of morphologically complex words during visual word recognition. In a series of three experiments this thesis addresses (i) the role semantic transparency during compound word reading, (ii) the nature of the conceptual structure of compound words and its effect on visual word recognition, and (iii) the time-course of semantic access during the visual comprehension of derived words. Chapter 2 documents evidence that the outcome of the compound semantic transparency effect is dependent upon the amount of language experience of the reader. We report that high compound transparency inhibits less experienced readers during naturalistic reading, yet facilitates processing among relatively more experienced readers. This study is the first to demonstrate that semantic processing of compound words is driven by individual reading skill. The study reported in Chapter 3 tests the hypothesis that the conceptual representation of a compound is based on a relational structure linking the compound’s constituents. Across two lexical decision datasets, Chapter 3 reports that greater entropy (i.e., increased competition) among a set of conceptual relations associated with a compound gives rise to longer lexical decision latencies. This finding indicates that the same compound word form is associated with many potential relational meanings, and that these meanings compete for selection during visual word recognition. Chapter 4 concerns the time-course of lexical-semantic access during derived word recognition. Existing accounts of derived word recognition widely disagree about whether access to conceptual information is granted prior to morphological decomposition. We report evidence which shows that the semantics of derived words and their stems are accessed in concert with morphological sources of information. These results challenge theoretical accounts that advocate strictly serial access to (morpho-orthographic then morpho-semantic) lexical cues. Overall, the empirical evidence presented in this thesis suggests that morphological processing involves rapid and concurrent access to many sources of conceptual information. These findings align with a view of complex word processing in which the cognitive system utilizes as many cues as possible in order to maximize the opportunity of obtaining the meaning of the word.
Stylistic Patterns in Language Teaching Research Articles: A Multidimensional Analysis.

This paper presents the results of a multidimensional analysis to investigate stylistic patterns and their communicative functions in language teaching research articles. The findings were that language teaching research articles contained six stylistic patterns and communicative functions. Pattern I consisted of seven salient positive features (i.e. Present Perfect Aspects, Split Auxiliaries, Type Token Ratio, Possibility Modals, Total Adverbs, Infinitives, and That Relative Clauses on Subject Position) which cooccurred to perform a ‘Persuasion Focused’ function. Pattern II consisted of eight salient positive features (i.e. Predicative Adjectives, Be as Main Verbs, Analytic Negations, Downtoners, Emphatics, Demonstrative Pronouns, Predictive Modals, and Adverbs) which co-occurred to perform an ‘Evaluative Stance Focused’ function. Pattern III consisted of seven salient positive features (i.e. Suasive Verbs, The Pronoun It, That Verb Complements, Private Verbs, Wh Relative Clauses on Subject Positions, That Deletion, and Adverbial Subordinators) which occurred to perform a ‘Claim Focused’ function. Pattern IV consisted of five salient positive features (i.e. Present Tense, Conjuncts, 170 | PASAA Vol. 52 July December 2016 That Verb Complements, Attributive Adjectives, and Phrasal Coordinations) and three negative features (i.e. Past Participial WHIZ Deletion Relatives, Past Tense, and Agentless Passives) which co-occurred to perform ‘Established Knowledge versus Past Action Focused’ functions. Pattern V consisted of six salient positive features (i.e. First Person Pronouns, Public Verbs, Third Person Pronouns, Causative Adverbial Subordinators, and That Deletion) which co-occurred to perform a ‘Ownership Focused’ function. Pattern VI consisted of five salient positive features (i.e. Gerunds, Present Participial WHIZ Deletion Relatives, Average Word Length, Present Participial Clauses, and Demonstrative Adjectives) which co-occurred to perform a ‘Modified Information Focused’ function. The implication for instruction and future research has been presented in the Discussion.
MACHINE LEARNING APPROACHES FOR DEALING WITH LIMITED BILINGUAL TRAINING DATA IN STATISTICAL MACHINE TRANSLATION

Statistical Machine Translation (SMT) models learn how to translate by examining a bilingual parallel corpus containing sentences aligned with their human-produced translations. However, high quality translation output is dependent on the availability of massive amounts of parallel text in the source and target languages. There are a large number of languages that are considered low-density, either because the population speaking the language is not very large, or even if millions of people speak the language, insufficient online resources are available in that language. This thesis covers machine learning approaches for dealing with such situations in statistical machine translation where the amount of available bilingual data is limited. The problem of learning from insufficient labeled training data has been dealt with in machine learning community under two general frameworks: (i) Semi-supervised Learning, and (ii) Active Learning. The complex nature of machine translation task poses severe challenges to most of the algorithms developed in machine learning community for these two learning scenarios. In this thesis, I develop semi-supervised learning as well as active learning algorithms to deal with the shortage of bilingual training data for Statistical Machine Translation task, specific to cases where there is shortage of bilingual training data. This dissertation provides two approaches, unified in what is called the bootstrapping framework, to this problem. I assume that we are given access to a monolingual corpus containing large number of sentences in the source language, in addition to a small or moderate sized bilingual corpus. The idea is to take advantage of this readily available monolingual data in building a better SMT model in an iterative manner: By selecting an important subset of these monolingual sentences, preparing their translations, and using them together with the original sentence pairs to re-train the SMT model. When preparing the translation of the selected sentences, if we use a human annotator, then the framework fits into the
Adaptive Block Diagonalization and User Scheduling With Out of Cluster Interference

Interference in a cellular network is one of the main impairments that needs to be overcome. Coordination among the Base Stations may enable the use of the interference to improve the transmission rate at the cost of increased computational complexity and more stringent backhaul and feedback requirements. Practical problems of global coordination can be reduced through clustering which, in turn, will introduce Out of Cluster Interference (OCI). OCI can seriously hamper the advantages brought by precoding techniques like Block Diagonalization (BD). In this work we propose a mixed transmission strategy using BD and Single User transmission that is able to overcome the problems introduced by the OCI, in combination with a low complexity scheduling algorithm that enables an increased transmission rate in a multiuser scenario.
Making the MOST of It

Jeff Carlson was in our town last winter for a speaking engagement. He's one of our best golf course superintendents, a pioneer and leader in developing an organic approach to course management. I've heard him speak a number of times and even stopped at his course on Martha's Vineyard during a genealogy trip on the island. He's an interesting guy to listen to. I chatted with him for a while and he told me he appreciated this column as a viewpoint from an older superintendent. I was flattered! At 64,1 am both older and retired, and these two experiences have provided rich subject material for me to muse and write about. And it seems an inevitable result to be tempted to share a couple of lessons learned along the way. The first, most obvious and most important advice I would offer after a year and a half is to make the most of your time. It applies throughout life but is especially true for retirement years. One reason that quickly comes to the forefront for me is health. A few months after I retired on Dec. 31, 2008 ,1 suffered a detached retina. A surgeon reattached it, but I now live with diminished eyesight. That is compounded by the need for cataract surgery in the near future. Any decrease in eyesight is scary. Pat Jones wrote about tinnitus in the April issue; I have the same affliction. Many golf course superintendents have skin cancer; count me among them. High blood pressure? I am taking meds for that as well. I still consider myself as "healthy" but I know as you age you are more and more vulnerable to health problems. I guess you sort of wear out. That realization led me to a simple arithmetic calculation. If I live to 84, then I have 20 years left and that translates to only 7,300 days. Making it to the ripe old age of 90 gives me about 9,500. As fast as time flies, there isn't much time to complete your bucket list, make a contribution for the greater good and repay the debt you owe to your profession. It is always useful to look around and see people who are making the most out of their retirement years. For example, take Dr. Jim Beard. He and his wife, Harriett, remain a productive team, on our behalf, studying and researching and writing and preserving our heritage. Closer to home I watch emeritus professor Wayne Kussow, still cheerfully contributing to the science important to all of us. tune that we have been good savers, a lesson well learned from our Depression-era parents. We owned our current home early, own our vehicles, have zero debt and never carried any credit card debt. If we couldn't pay for something, we did without until we could. It is safe advice to say that saving money is a big key to a secure retirement. While it makes sense to have some investment in the stock market, the recent past notwithstanding, mostly it has been a big fairy tale over the last decade. If you invested $100 a decade ago in the stock market, today you would have $100. You could have put it under your mattress
IPv6 Host Address Usage Survey

It is tempting to assume that for IPv6, with its 64-bit Interface IDs (IIDs), some existing address scanning attacks have become infeasible. RFC 5157 suggests how Interface IDs could be allocated so as to minimize a site's vulnerability to address scans, essentially by using IIDs consisting of a pseudorandom sequence of 1s and 0s. In this paper, we investigate how network administrators are actually allocating their Interface IDs. We have developed and carried out a survey of various IPv6 addresses from 50 countries. We find that few network administrators are using RFC 5157's allocation methods; instead we find that most network administrators are using one of five simple allocation schemes which tend to leave zero bits in large sections of their Interface IDs. We observe that such schemes can leave networks vulnerable to address scanning.
Metrics in Distributed Product Development

— Nowadays the products are increasingly developed globally in collaboration between subcontractors, third party suppliers and in-house developers. However, management of a distributed product development project is proven to be more challenging and complicated than traditional one-site development. From the viewpoint of project management, the measurements and metrics are important activities for successful product development. This paper is focused on describing a set of metrics that is successfully used in industrial practice in distributed product development. Based on the experiences, the reasoning for selecting these metrics was similar: they are easy to capture and can be quickly calculated and analysed on a regular interval. One of the most important reasons for choosing these metrics was that they were aimed especially to provide early warning signals, i.e., means to proactively react to potential issues in the project. This is especially important in distributed projects, where specific means to track project status are needed.
Understanding preferences and similarities from user-authored text: applications to search and recommendations

OF THE DISSERTATION Understanding Preferences and Similarities from User-Authored Text: Applications to Search and Recommendations by Gayatree Ganu Dissertation Director: Amelie Marian Users rely increasingly on online reviews, forums and blogs to exchange information, practical tips, and stories. Such social interaction has become central to their daily decision-making processes. However, user-authored content is in a free-text format, usually with very scant structured metadata information. Users often face the daunting task of reading a large quantity of text to discover potentially useful information. This thesis addresses the need to automatically leverage information from user-authored text to improve search and to provide personalized recommendations matching user preferences. We first focus on developing accurate text-based recommendations. We the rich information present in user reviews by identifying the review parts pertaining to different product features and the sentiment expressed towards each feature. We derive text-based ratings which serve as alternate indicators of user assessment of the product. We then cluster similar users based on the topics and sentiments in their reviews. Our results show that using text yields better user preference predictions than those from the coarse star ratings. We also make fine-grained predictions of user sentiments towards the individual product features. In the interactive and social forum sites users frequently make connections with other users, enabling them to find the right person to answer their questions. A challenge then, is to score and rank the short snippets of forum posts while taking into account these personal connections.
Implementation of a full frequency-dependent transmission line model within the framework of the (OVNI) real-time power system simulator

This thesis presents the methodology to implement a full frequency-dependent transmission line model in UBC's OVNI (Object Virtual Network Integrator) real-time power system simulator. OVNI utilizes an object-oriented approach to represent and implement its element models. Object-oriented programming permits a flexible, reliable, and expandable solution to the simulation program. In particular, OVNI represents each element model as a class inheriting common characteristics and properties from a parent class of basic elements. Each element object interacts with the network solver, the core, only by exchanging such parameters as external node voltages, external node names, the equivalent conductance matrix and the equivalent history source vector through some well-defined member functions. Model developers only needs to correctly and efficiently implement these member functions to successfully incorporate the model with the core. This clean-cut abstraction between element models and the core provides model developers with complete freedom and independence while designing, implementing, and upgrading models of different electric properties and complexities. The transmission line model implemented in this thesis is a phase-domain full frequency-dependent model (zLine). This model was developed in Ph.D projects by Castellanos [15] and Yu [16]. The model is suitable for time-domain EMTP (Electromagnetic Transient Program) simulations within OVNFs real-time framework. Z-line is accurate, efficient, numerically stable and strongly suited for multi-circuit asymmetrical line configurations. The model divides the line length into a number of small segments and separates the wave propagating in each segment into a constant idealline section and a frequency-dependent loss section. A numerically stable curve fitting routine was modified to synthesize elements of the loss matrix so that the equivalent time-domain model for the loss section can be formulated with an integration rule.
ACSI - Artifact-Centric Service Interoperation

This report contains documentation for the Deliverable 2.2. 2: Model Checking Tool for Artifact Interoperations (MOCAI) of Work Package 2 after 24 months in the ACSI project. We present the requirements that serve as a guide for selecting the necessary features of the toolkit. We outline a methodology to model check declarative models of artifact-centric systems by translating GSM-based artifact-centric systems into a symbolic transition system used for symbolic model checking. A notable feature of our approach is that it is completely automatic. We implement the methodology in the GSMC model checker. The toolkit takes files directly from the web-based GSM engine Barcelona as input. We also provide preliminary results on the verification of artifact-centric systems using GSMC and demonstrate the applicability on an example from a real-world application. c © D2.2. 2 Model Checking Tool for Artifact Interoperations (MOCAI) – Iteration II Page 3 of 47
Spectrum Sensing Techniques For Cognitive Radio Applications

Cognitive Radio (CR) has received tremendous research attention over the past decade, both in the academia and industry, as it is envisioned as a promising solution to the problem of spectrum scarcity. A CR is a device that senses the spectrum for occupancy by licensed users (also called as primary users), and transmits its data only when the spectrum is sensed to be available. For the efficient utilization of the spectrum while also guaranteeing adequate protection to the licensed user from harmful interference, the CR should be able to sense the spectrum for primary occupancy quickly as well as accurately. This makes Spectrum Sensing (SS) one of the fundamental blocks in the operation of a CR. At its core, SS is a hypothesis testing problem, where the goal is to test whether the primary user is inactive (the null or noise-only hypothesis), or not (the alternate or signal-present hypothesis). Computational simplicity, robustness to uncertainties in the knowledge of various noise, signal, and fading parameters, and ability to handle interference or other source of non-Gaussian noise are some of the desirable features of a SS unit in a CR. In many practical applications, CR devices can exploit known structure in the primary signal. In the IEEE 802.22 CR standard, the primary signal is a wideband signal, but with a strong narrowband pilot component. In other applications, such as military communications, and bluetooth, the primary signal uses a Frequency Hopping (FH) transmission. These applications can significantly benefit from detection schemes that are tailored for detecting the corresponding primary signals. This thesis develops novel detection schemes and rigorous performance analysis of these primary signals in the presence of fading. For example, in the case of wideband primary signals with a strong narrowband pilot, this thesis answers the further question of whether to use the entire wideband for signal detection, or whether to filter out the pilot signal and
Online professional learning for rural teachers of mathematics and science

Professional learning is crucial for the ongoing development of teachers and the improvement of student outcomes. Professional learning in mathematics and science education has the potential to address concerns about shortages in these areas and their impact on economic growth. However, attendance at face-to-face professional learning is problematic for many teachers located in rural areas. This study explores the utilisation of online professional learning in mathematics and science education by teachers in rural areas, and canvasses teachers’ requirements for this form of professional learning. An activity system, using cultural-historical activity theory, is developed for online professional learning for teachers of mathematics and/or science. Qualitative interpretive analysis of transcripts of 14 semi-structured individual interviews with three different groups of people suggests that teachers of mathematics/science require professional learning programs which are not only flexibly delivered but also provide professional learning content that has high utility value. By better understanding how teachers respond to the notion and practice of online professional learning, informed decisions can be made about how best to support teachers and thus build capacity in schools for success in mathematics and science.
Face super-resolution based on online dictionary learning

Recent learning-based face super-resolution methods, such as Yang's Sparse Coding Super-Resolution (SCSR) are promising with sharp edges visually. But it also leads to obvious artifacts. In order to eliminate the artifacts, Online Dictionary Learning (ODL) algorithm is introduced in the dictionary learning phase to generate accurate overcomplete dictionary. On the other hand, the reconstruction regularization parameter is tuned independently to acquire the optimal sparse coefficient. With the solved dictionary and sparse coefficient, the recovered high-resolution image patches are predicted to reconstruct the target output image. In the experiments, the PSNRs and SSIMs of the proposed method are much higher than some state-of-the-art super-resolution methods. The PSNR is 0.85dB higher than SCSR in average, while the SSIM is 0.0133 higher. The artifacts and noise along the edges and corners are both eliminated effectively. More details of the faces are added to make the recovered high-resolution image clear. Additionally, the PSNRs decreases more smoothly while the noise level of the input lowre-solution image increases. It means that the proposed algorithm has promising performance in super-resolution reconstruction with good denoising effect.