Miracle-dz/UniFAR-FTUs huggingface dataset:
College Student Preferences for Trendy versus Classic Typefaces

The user-generated content trend extends beyond the blogosphere and into the arenas of visual c0l11111unication-particularly that of typography. Researchers have little knowledge about the ilnplicatiol1s of this typography booln, although young people today have been exposed to the user-generated trend for well over a decade. This study discerns groups of college students based on their opinions about both trendy user-generated typefaces and classic typefaces in college textbooks. Q rnethodology is used to collect and analyze data about typeface preference. This 111ethodo! ogy is especially suited to preIinl;naly research lIsed to obtain a deeper understanding abollt under-explored concepts like aesthetic typographic preference. The researcher identified four distinct groups of college students based lIpon individual subjective preferencesfor classic or trendy t;ypefaces.
Mastering Perl for Bioinformatics

Historically, programming hasn't been considered a critical skill for biologists. But now, with access to vast amounts of biological data contained in public databases, programming skills are increasingly in strong demand in biology research and development. Perl, with its highly developed capacities in string handling, text processing, networking, and rapid prototyping, has emerged as the programming language of choice for biological data analysis. Mastering Perl for Bioinformatics covers the core Perl language and many of its module extensions, presenting them in the context of biological data and problems of pressing interest to the biological community. This book, along with Beginning Perl for Bioinformatics, forms a basic course in Perl programming. This second volume finishes the basic Perl tutorial material (references, complex data structures, object-oriented programming, use of modules--all presented in a biological context) and presents some advanced topics of considerable interest in bioinformatics. The range of topics covered in Mastering Perl for Bioinformatics prepares the reader for enduring and emerging developments in critical areas of bioinformatics programming such as: Gene findingString alignmentMethods of data storage and retrieval (SML and databases)Modeling of networks (graphs and Petri nets)Graphics (Tk)ParallelizationInterfacing with other programming languagesStatistics (PDL)Protein structure determinationBiological models of computation (DNA Computers) Biologists and computer scientists who have conquered the basics of Perl and are ready to move even further in their mastery of this versatile language will appreciate the author's well-balanced approach to applying Perl's analytical abilities to the field of bioinformatics. Full of practical examples and real-world biological problem solving, this book is a must for any reader wanting to move beyond beginner level Perl in bioinformatics.
The hidden cost of low bandwidth communication

Every year manufacturers of massively parallel computers release new machines with ever more impressive benchmark performance. Unfortunately, these machines are not widely used in practice. To date, they have been used eeciently mostly to solve problems whose communication structure is well understood. Furthermore, the software for solving these problems has been highly engineered, and both data and machine speciic. Progress has been made recently on solving more irregular problems and machine-independent programming languages such as HPF have made software more portable, but the machines remain diicult to program. Our position is that much of this diiculty stems from a lack of appreciation of the impact of low performance interconnect on software development. To understand why the cost of low performance interconnect is underestimated, it helps to look at the standards by which parallel computers have been measured until now. Five years ago, a typical measure of the power of a massively parallel computer was the peak rate at which it could perform oating-point operations, i.e., how many gigaaops ((oating point operations per second) it could perform. Manufacturers produced machines that achieved very high oating point performance, but this measure was found to be nonpredictive because the machines could rarely achieve it. More recently, the performance of these machines has been judged against a set of standard benchmarks, which include the LINPACK and NAS 1] benchmarks. As shown in Figure 1, these benchmarks, especially the NAS, have exposed a large diierence between peak and achievable performance. One of the conclusions that can be drawn from these benchmarks is that machines with high communication bandwidth perform well across the board, whereas peak oating-point performance is relevant only on embarrassingly parallel problems. The benchmarks, however, still do not reveal the full cost of inadequate comunications bandwidth. Absent from the performance statistics is the cost of software development. In particular the statistics fail to capture 1. the time to write the code, 2. the time to write the compiler that translates the code, 3. the time to port the code to diierent distributions of data, and 4. the time to port to diierent machines. These hidden costs can be substantial. First, although the NAS benchmarks are relatively simple , manufacturers of parallel machines typically spend multiple man years of software development in order to draw high performance from their machines. Second, the time reported for the development of code for speciic benchmarks is often …
On learning how to learn learning strategies

This paper introduces the "incremental self-improvement paradigm". Unlike previous methods, incremental self-improvement encourages a reinforcement learning system to improve the way it learns, and to improve the way it improves the way it learns . , without significant theoretical limitations the system is able to "shift its inductive bias" in a universal way. Its major features are: (1} There is no explicit difference between "learning", "meta-learning", and other kinds of information processing. Using a Turing machine equivalent programming language, the system itself occasionally executes self-delimiting, initially highly random "self-modification programs" which modify the context-dependent probabilities of future action sequences (including future self-modification programs}. (2} The system keeps only those probability modifications computed by "useful" selfmodification programs: those which bring about more payoff (reward, reinforcement} per time than all previous self-modification programs. (3) The computation of payoff per time takes into account all the computation time required for learning the entire system life is considered: boundaries between learning trials are ignored (if there are any). A particular implementation based on the novel paradigm is presented. It is designed to exploit what conventional digital machines are good at: fast storage addressing, arithmetic operations etc. Experiments illustrate the system's mode of
Realization and high level specification of facial expressions for embodied agents

In this thesis we describe work done related to realization and high level specification of facial expressions for embodied agents. Realization is done by implementation of MPEG-4 Facial Animation. High level specification of facial expressions is done by creating FACS (Facial Action Coding Standard) configurations or by choosing points on a circular emotion space. For realization of facial expressions, an editor has been developed which can be used to set face dependent parameters like feature point location and other variables that control the way a face is deformed. Evaluation of our implementation of MPEG-4 Facial Animation is done by comparing it to several other virtual faces that have implemented it. This shows that our implementation is performing better than any of the faces it was compared to. We visually show that expressions created using the FACS high level specification method are corresponding to real life imagery very well
ADAPTING KERNEL-BASED METHODS TO SEMI-SUPERVISED LEARNING: FROM MULTI-CLASS SVM TO SPECTRAL ANALYSIS

This prospectus proposes a preliminary research topic about fusing the kernel-based SVM method and the similarity-based spectral clustering into a semi-supervised learning algorithm under the scope of learning from both labeled and unlabeled data. For the past nine months before the prospectus comes out, much effort has been put to extend the bloomed SVM to more practicable multi-class learning situations and to introduce the blooming spectral method to some semi-supervised learning scenarios, which, as a subordinate contributor, leads to two conference papers, one accepted, the other recently submitted. Furthermore, encouraged by some emerging progress in the field of semi-supervised learning from other pioneer researchers, my ongoing research is expected to be at a high feasibility rate, either in theory or practice. Hereafter, further study will be conducted to make the algorithm theoretically complete and practically realistic. Also, to validate the algorithm, besides testing on some standard datasets available in the machine learning community, comprehensive experimental results will be conducted to the task of text categorization. ABSTRACT ii 1 INTRODUCTION 1 1.
Réel, contexte, et cognition. Contribution à une histoire de la linguistique cognitive

Cet article interroge, dans une perspective historique et epistemologique, la maniere dont la linguistique cognitive du demi-siecle passe a pris en compte (ou non) le contexte dans les operations mentales de reception/ interpretation et de production langagiere auxquelles elle s’est, des son fondement, attachee. L’axe de reflexion est l’opposition internalisme vs externalisme et la question posee est celle de la prise en compte du poids et de l’existence de ce qui releve, dans la cognition linguistique, de la realite (materielle et culturelle). Sont abordes le traitement du contexte dans les linguistiques cognitives depuis Chomsky et celui du mind-body problem dans les courants heterodoxes de la cognition situee a partir des annees 1990. Des propositions sont faites pour une meilleure integration des environnements de la production verbale aux analyses linguistiques dans une perspective cognitive.
EtherLeak: Ethernet frame padding information leakage

Multiple platform Ethernet Network Interface Card (NIC) device drivers incorrectly handle frame padding, allowing an attacker to view slices of previously transmitted packets or portions of kernel memory. This vulnerability is the result of incorrect implementations of RFC requirements and poor programming practices, the combination of which results in several variations of this information leakage vulnerability. This bug is explored in its various manifestations through code examples and packet captures. Solutions to this flaw are provided.
Blending Theoretical and Practical Experiences for a Multimedia Development Graduate Course

The Center of Instructional Technology and Multimedia at the Universiti Sains Malaysia (Science University of Malaysia) has for the past three years conducted a Multimedia Development course for the Masters of Education program. This paper will present experiences and opinions from both the instructor’s and students’ of the course. The course objective is to provide both theoretical and practical experiences in Multimedia Courseware development to be used in the classroom or training facilities. Students are required to submit a four-research article revie w as well as produce two-multimedia courseware as their practical component for the course. They are also required to undertake a final examination. From the evaluation and assessment of the course the students are very positive in the experiences that the y have undergone and their major complaint is a lack of time to complete the practical component of the course. The instructor utilized PowerPoint and Microsoft Publisher as the introductory software for Multimedia and Web Page development.
Att hålla högpresterande värphöns friska i 100 veckor

I bl.a. svensk aggproduktion finns en onskan om att halla varphonsen under en betydligt langre period an vad som gors idag. Om aggproducenter vill behalla varphons langre i produktion bor sarskilt produktionsuthallighet av agg, skalkvalitet och fjaderplockning tas i beaktning samt benhalsa for att fa en ekonomisk och hallbar produktion. Normalt halls en svensk varphona i produktion i 60 veckor innan hon slaktas. Den storsta anledningen till varfor dessa varphons slaktas ut ar en kombination av att de producerar skorare och tunnare aggskal och att de far en samre aggproduktion. Det finns manga utmaningar om varphonan skall vara frisk och valmaende samtidigt som den skall producera manga hallbara agg under en sadan langre period. Ett hallfast och starkt aggskal ar en grundforutsattning for att agget skall hallas helt anda fram till konsumenten, vilket forsamras med honans stigande alder. Om skalet inte halls intakt innebar det aven en risk for konsumenten att ata agget eftersom ett skadat aggskal forlorar sitt naturliga skydd mot omvarlden och kan darmed exponeras for mikroorganismer. Varphons producerar manga agg under sin korta livstid, vilket kraver en stor kalciumreserv for tillverkning av aggskalet. Denna reserv aterfinns i varphonans ben och vingar, vilket gor att om denna reserv inte fylls pa kommer benet bli skorare och oka risken for osteoporos eller benskorhet. Varphons i den senare delen av produktionen drabbas oftare av frakturer, jamfort med i borjan av produktionen i framforallt vingar och ben, vilket kan innebara att honsen far svarare och ta sig till foder och vatten. Eftersom varphons upplever smarta om det uppkomit en fraktur pa ben eller vingar, innebar det att det inte enbart ar nodvandigt av hansyn till ekonomin i denna viktiga fraga utan aven for djurvalfarden.
Stronger authentication in e-commerce: how to protect even naïve user against phishing, pharming, and MITM attacks

Phishing, pharming and MITM attacks, i.e. the theft of user credentials, are a major threat to e-commerce applications. As soon as the attacker manages to talk a user into revealing his/her credentials needed to access an e-commerce application (e.g. user name, password, transaction number (TAN) in case of e-banking applications), the user's account is open to any kind of (financial) transaction by the attacker. In this paper, we propose using the trusted platform module (TPM) --- a piece of hardware which will be built into all computers shipped in the near future --- for ensuring both an e-commerce application's integrity and binding user authentication to user credentials and the usage of specific hardware during the authentication process. By doing so, strong authentication is achieved (something one knows is combined with something one possesses physically), which renders phishing attacks unsuccessful as the phisher will not be in possession of the required hardware and therefore getting user credentials will not open the e-commerce account for exploitation.
Connectionist Learning of Natural Language Lexical Phonotactics

AbstractConnectionist learning of natural language words and their phoneticregularities is presented. The Neural Network (NN) model we employ in thisproblem is the Simple Recurrent Network, trained with the BackpropagationThrough Time (BPTT) learning algorithm. During the training, it was assignedthe task of predicting the next phoneme given one phoneme at each momentand keeping information of the past phonemes from a given word in a fewcontext neurons. The phonotactics of the Dutch language was studied amongothers. The shortcomings of some similar previous implementations areexplained and successfully overcome. Among the techniques we employed toachieve the much-improved error rate of 1.1% with monosyllabic words and3.5% with multisyllabic ones are new methods for network responseinterpretation, an evolutionary approach in training a set of networks, and theexploitation of the word frequencies in training. Finally, an analysis of thephonotactics rules extracted by a trained network is presented.Keywords: connectionism, neural networks, SRN, machine learning, linguistics, phonotactics,
Classification management and use in a networked environment: the case of the Universal Decimal Classification

In the Internet information space, advanced information retrieval (IR) methods and automatic text processing are used in conjunction with traditional knowledge organization systems (KOS). New information technology provides a platform for better KOS publishing, exploitation and sharing both for human and machine use. Networked KOS services are now being planned and developed as powerful tools for resource discovery. They will enable automatic contextualisation, interpretation and query matching to different indexing languages. The Semantic Web promises to be an environment in which the quality of semantic relationships in bibliographic classification systems can be fully exploited. Their use in the networked environment is, however, limited by the fact that they are not prepared or made available for advanced machine processing. The UDC was chosen for this research because of its widespread use and its long-term presence in online information retrieval systems. It was also the first system to be used for the automatic classification of Internet resources, and the first to be made available as a classification tool on the Web. The objective of this research is to establish the advantages of using UDC for information retrieval in a networked environment, to highlight the problems of automation and classification exchange, and to offer possible solutions. The first research question was is there enough evidence of the use of classification on the Internet to justify further development with this particular environment in mind? The second question is what are the automation requirements for the full exploitation of UDC and its exchange? The third question is which areas are in need of improvement and what specific recommendations can be made for implementing the UDC in a networked environment? A summary of changes required in the management and development of the UDC to facilitate its full adaptation for future use is drawn from this analysis.
In air acoustic vector sensors for capturing and processing of speech signals

Capturing speech signals for enhancement is an important stage in all modern communication systems. Traditionally, speech enhancement is performed on a single channel recording, but recently the advantages of multichannel speech processing have been indentified. The multichannel speech signals are captured using a microphone array, and by using the spatio-temporal information at the output of the microphone array the directional information of the source can be derived and spatial filtering of the captured signal can be performed, which show superior performance over single channel approaches. Generally, spatially distributed microphone arrays as used in speech signal processing, only capture the acoustic pressure. In this thesis, however, a co-located microphone array which captures both acoustic pressure and particle velocity, known as an Acoustic Vector Sensor (AVS), will be used for capturing speech signals for enhancement. The AVS used in this work consists of two pressure gradient sensors and an omni-directional microphone which enables the capturing of speech of signals in 2D. Compared with other microphone arrays, the size of the AVS array is small, occupying a volume of approximately 1cm 3 . The small size of the AVS array enables it be used in mobile electronic devices such as mobile phones and mobile personal computers which traditionally have a single microphone capsule. In this thesis, a design change for the AVS is presented, which, improves the accuracy of Direction of Arrival (DOA) estimates from the AVS. It is shown that by offsetting the directional sensors on the AVS array, a source direction can be identified with an accuracy of two degrees for a stationery speech source and five degrees for both moving and multiple speech sources. Here, DOA estimates are found using the MUltiple SIgnal Classification (MUSIC) Algorithm in the time domain and an intensity based algorithm in the frequency domain. For multiple sources, a new data clustering technique is introduced with the existing frequency domain intensity based algorithm. Speech enhancement methods, which take advantage of the directional characteristics of the AVS array are presented. It is shown that by taking advantage of the directional characteristics of the AVS to obtain noise estimates used in the Minimum Variance Distortionless Response (MVDR) beamformer, an improvement of
An examination of feedback request strategies when learning a multi-dimensional motor task under self-controlled and yoked conditions

Recent research investigating how learners benefit from having control over some aspect of their practice environment has led to numerous potential explanations for its beneficial effects (Janelle et al., 1997; Chiviacowsky & Wulf, 2002). These explanations, however, are vague and difficult to directly measure. Current research suggests that learners in a self-controlled setting prefer feedback after relatively good performances. More recently, Aiken and colleagues (2012) have provided evidence suggesting that when learners control their feedback schedule while learning a task with multiple dimensions of performance, they prefer and request feedback after both “good” and “poor trials” equally. The purpose of this study was to directly address how learners in self-controlled and yoked conditions learn a task with two conflicting elements of performance in a laboratory setting. Participants (n=22) learned a discrete aiming task for which they had to move from a starting zone around a barrier to a target with a handheld stylus in their non-dominant hand in 600 ms. Success was determined on two criteria: temporal and spatial accuracy. Participants completed motivation scales assessing intrinsic motivation, perceptions of choice and competence, and fulfillment of basic psychological needs. A post-training questionnaire was used to examine learner preferences for feedback. Results indicated the selfcontrol group outperformed the yoked group in spatial accuracy during transfer tests. Further, analysis of performance and questionnaire data revealed that the self-control group requested feedback equally on their best performance as on their worst performances. The findings of this study support the notion that learners request and benefit from feedback differently dependent on task complexity. Future research should consider using semi-structured interviews to better understand how learners use and develop strategies related to feedback requests.
Optimization of Fast MR Imaging Technologies using the Case-PDM to Quantitatively Assess Image Quality

6 Chapter 1: Introduction . 8 Chapter 2: Quantitative Image Quality Evaluation of MR Images using Perceptual Difference Models . 35 Chapter 3: Diagnostically Relevant Quantitative Image Quality Evaluation: A Preliminary Study . 77 Chapter 4: Diagnostically Relevant Image Quality Evaluation with Relative Disturbance of MR Image Artifacts to Radiologists . 105 Chapter 5: Optimization of Compressed Sensing MRI reconstruction using a Perceptual Difference Model . 128 Chapter 6: Future Works and Conclusions . 153 Appendix: Calculation of d’. 174 Appendix: CASE-PDM . 176
The Impact of Technology on Plagiarism Prevention and Detection

A multi-sided container, preferably formed of a unitary blank of paperboard, having two adjacent top closure flaps which are connected by a fold line and which have fold lines and frangible perforated lines therein to define three hingedly connected, superimposed triangular areas. Upon severance of these perforated lines, the three triangular areas are pulled away from the container to unfold them from their superimposed position, thereby forming the spout. A third top closure flap is also provided, which flap has a fourth triangular area that is superimposed on the top of the other three.