Miracle-dz/UniFAR-FTUs huggingface dataset:
Reinforcement learning in a turn-based strategy game

Author: Hyrkäs Jarno Juha Tapio Title of the Publication: Reinforcement Learning in Turn-based Strategy Game Degree Title: Bachelor of Business Administration, Business Information Technology The goal of this Batchelor’s thesis was to study reinforcement learning in a turn based strategy game. The theoretical examination or the study includes chapters from explaining what is AI to in-depth analysis of Qlearning, which is the learning method used in the application. A general reinforcement learning template was made based on the theoretical examination. The code was done with C# Unity3D and the structure is explained in the application section. The code template was used to create AI for a based strategy game. The game is called King of Thule and the Bachelor’s thesis has a chapter which explains how the game is played. Another chapter explains what game states and actions were used for the game AI. The finished AI was trained by making AI agents play each other in a learning period. Data from the period was recorded and analysed. TABLE OF CONTENTS List of Symbols
High-resolution topographic imaging of the moving ocean surface

Imaging Doppler radar deployed in an interferometric mode can be used to map the time-varying surface displacement field. Applying techniques common in cross-track SAR interferometry, the authors have used a newly constructed focused phased-array radar to measure backscattered power, Doppler velocity, and surface displacement simultaneously from extended areas of the sea surface. "Direct" imaging of surface displacement via interferometry avoids the need for a surface wave model (linear or otherwise) to retrieve wave heights. They report results of held comparison between radar and wave-wire measurements of surface displacement performed from a small pier. Images of a 20 m/spl times/20 m area resolved to 0.5 m spatial resolution and 0.25 s time resolution were produced. Radar-derived height statistics are well correlated with those obtained by direct measurement. The technique can be extended to larger areas by increasing the height of the radar.
recognition and understanding

A continuous speech recognition and understanding system is presented that accepts queries about a restricted geographical domain, expressed in free but syntactically correct natural language, with a lexicon of the order of one thousand words. A lattice of word candidates hypothesized by the speaker dependent recognition level is the interface to an understanding module that performs the syntactic and semantic analysis. The recognition subsystem generates word hypotheses by exploiting Hidden Markov Models of sub-word units. Bottom-up constraints are also introduced to restrict the set of candidde words. The understanding module determines the most likely sequence of words and represents its meaning in a parse-tree suitable to access a data base. It makes use of a modified caseframe analysis driven by tlie word hypotheses likelihood scores. The results of a set of experiments performed on 150 sentences collected from one speaker are given.
Distributed dynamic channel resource allocation in wireless communication systems

We consider the problem of allocation of bits and power among N channels in a multi-user cellular system. We suppose that no users within the same cell interfere with each other, and that the N channels assigned to the users are randomized such that any given interferer is encountered in only one of the channels. We present distributed algorithms to allocate power and bits so as to maximize a cost function including as elements the bit rate already achieved and the likelihood of dropping calls already in progress. Procedures for rapidly estimating the likelihood of achieving target bit rates in the channel are also presented. <<ETX>>
Identification Of System Design Features That Affect Sickness In Virtual Environments

iii ACKNOWLEDGMENTS . vi TABLE OF CONTENTS. x LIST OF FIGURES . xiv LIST OF TABLES. xv LIST OF ACRONYMS . xviii CHAPTER ONE: INTRODUCTION. 1 Statement of the Problem. 2 CHAPTER TWO: LITERATURE REVIEW. 5 Applications of Virtual Environment Technology . 5 Effects of VE Exposure . 8 Significance of Side Effects from VE Exposure . 10 Classifications of Sickness from Exposure to Provocative Environments . 15 Motion Sickness Theories. 21 Sensory Conflict Theory . 22 Evolutionary Theory . 28 Postural Instability Theory. 31 Measurement of Sickness . 38 Objective Measures. 38 Subjective Measures . 44 Self-Report Measures of Motion Sickness . 45 Simulator Sickness Questionnaire . 50 Scoring Method. 52 Validity and Reliability. 53 Factors Influencing Sickness in Virtual Environments . 55 Individual Characteristics . 59 Age. 59
Methods and systems for graphical image authentication

A method and a system for authenticating a graphical image is provided to generate a password value which is not known to an invader by providing authentication using a dynamic graphical image arrangement. A method for authenticating a graphical image includes the steps of: generating at least one dynamic graphical arrangement of images having at least one image selected from graphic images of an authentication category and at least one image selected from graphic image of a non-authentication category, wherein the image has a corresponding access code; showing the dynamic graphic arrangement of the images to a user; receiving at least one user-typed access code corresponding to the image of the graphic images of the authentication category from the user; and comparing at least one user-typed access code with an authentication reference code to authenticate the user.
Virtual Grain: a Data Warehouse for Mesh Grid Representation of Cereal Grain Properties

The "Virtual Grain" project has a double objective: the first one is to gather in a data warehouse heterogeneous information concerning the properties of cereal grains (morphology, biochemistry, etc.) and the conditions in which these data were obtained; the second one is to use this data warehouse in order to obtain a cartography of grain properties that consists in a three-dimension mesh grid, and to identify potential relationships between these various properties.
Chain Identity Attestation (CIA) Method for preventing node cloning attack in Wireless Sensor Network

This paper presents a new technique in preventing node cloning attack. The significant contribution of this method or technique is in preventing node impersonation attack in Wireless Sensor Network (WSN). The new method named as Chain Identity Attestation Method (CIA) was developed on the basis of Diffie-Hellman hard problem algorithm. The exclusivity of CIA method is in the generation of node identity. In this method, the node identity is in each session. In other words, node identity is no longer fixed to a certain value. Perfect forward secrecy attack model is used to prove the security of this CIA method.
Implementation of Processing Element for Modular Multiplier Using Static CMOS and Multiplexer Logic Circuit at 65nm

- Many public key cryptographic algorithms require modular multiplication of very large operands as their core arithmetic operation. In this paper fast processing and low power consuming processing element of modular multiplier hardware is proposed. Proposed processing element is implemented of 4 bit in 65nm technology using static CMOS and multiplexer logic. The processing element designed using static CMOS logic consumes 1.2246uw power and multiplexer logic consumes 0.939uw with 1.2volt operating voltage and 1 fF capacitor. The number of transistor in static CMOS logic contains 58T and multiplexer logic contains is 42T. The multiplexer logic based processing element consumes 23% less power than the static CMOS.
An Efficient Calculation Algorithm in Continuous-Time Markov Analysis Using Large-Scale Numerical Calculation

We propose a new calculation algorithm in continuous-time Markov analysis on the precondition of using large-scale numerical calculation on a computer. Because it is more efficient than the ordinary calculation in absorbing Markov analysis in memory usage and computation time, it can be applied to Markov models with enormous numbers of states especially in the fields of reliability, dependability, and safety. Mathematics Subject Classification: 68M15, 60J27, 60J28
Music Style Analysis Using the Random Forest Algorithm

This paper aims to discuss a method for autonomously analyzing a musical style based on the random forest learning algorithm. This algorithm needs to be shown both positive and negative examples of the concept one is trying to teach it. The algorithm uses the Hidden Markov Model (HMM) of each positive and negative piece of music to learn to distinguish the desired musical style from melodies that don‘t belong to it. The HMM is acquired from the coefficients that are generated by the Wavelet Transform of each piece of music. The output of the random forest algorithm codifies the solution space describing the desired style in an abstract and compact manner. This information can later be used for recognizing and/or generating melodies that fit within the analyzed style, a capability that can be of much use in computational models of design and computational creativity.
Modeling Spelling Acquisition: The Effect of Orthographic Regularities on Silent-Letter Representations

ABSTRACT In this report, we propose a model of spelling acquisition inspired by statistical learning and a frame-like model of orthographic representations: the fuzzy representation model. To provide an initial test of the model’s predictions for inconsistent words, 107 French-speaking children in Grades 1 to 3 were asked to spell words ending with a silent letter. Half of the words ended with the frequent silent t and half with the less frequent silent d. As predicted, children accurately spelled more t- than d-words. Most errors were omissions and substitutions of the silent letter. Consistent with statistical learning, there was some evidence that children used the preceding orthographic context when making substitution errors. The proportion of omissions, however, was not consistent with the statistical properties of French. These findings are discussed in light of the fuzzy representation model, whereby inconsistencies in words are more likely to be underspecified, if represented at all.
Review of Measures of Computing Page Importance in Web Crawling

Web crawling has a great literature of extensive research and optimization of various aspects of a crawler, but still there are different areas to explore to satisfy every user's need. Researches in the past emphasized on the relevancy and robustness of search results. In order to have in-depth knowledge of web crawling, various crawling strategies and algorithms along with their issues need to be studied. In this paper, the author has reviewed the different aspects of crawling millions of web pages on web. On the basis of this review, new strategies to improve the search results index of a search engine can be devised in future.
Scalable Teaching and Learning via Intelligent User Interfaces

The increasing demand for higher education and the educational budget cuts lead to large class sizes. Learning at scale is also the norm in Massive Open Online Courses (MOOCs). While it seems cost-effective, the massive scale of class challenges the adoption of proven pedagogical approaches and practices that work well in small classes, especially those that emphasize interactivity, active learning, and personalized learning. As a result, the standard teaching approach in today’s large classes is still lectured-based and teacher-centric, with limited active learning activities, and with relatively low teaching and learning effectiveness. This dissertation explores the usage of Intelligent User Interfaces (IUIs) to facilitate the efficient and effective adoption of the tried-and-true pedagogies at scale. The first system is MindMiner, an instructor-side data exploration and visualization system for peer review understanding. MindMiner helps instructors externalize and quantify their subjective domain knowledge, interactively make sense of student peer review data, and improve data exploration efficiency via distance metric learning. MindMiner also helps instructors generate customized feedback to students at scale. We then present BayesHeart, a probabilistic approach for implicit heart rate monitoring on smartphones. When integrated with MOOC mobile clients, BayesHeart can capture learners’ heart rates implicitly when they watch videos. Such information is the foundation of learner attention/affect modeling, which enables a ‘sensorless’ and scalable feedback channel from students to instructors. We then present CourseMIRROR, an intelligent mobile system integrated with Natural Language Processing (NLP) techniques that enables scalable reflection prompts in large classrooms. CourseMIRROR 1) automatically reminds and collects students’ in-situ written reflections after each lecture; 2) continuously monitors the quality of a student’s reflection at composition time and generates helpful feedback to scaffold reflection writing; 3) summarizes the reflections and presents the most significant ones to both instructors and students. Last, we present ToneWars, an educational game connecting Chinese as a Second Language (CSL) learners with native speakers via collaborative mobile gameplay. We present a scalable approach to enable authentic competition and skill comparison with native speakers by modeling their interaction patterns and language skills asynchronously. We also prove the effectiveness of such modeling in a longitudinal study.
SEIMCHA: a new semantic image CAPTCHA using geometric transformations

As protection of web applications are getting more and more important every day, CAPTCHAs are facing booming attention both by users and designers. Nowadays, it is well accepted that using visual concepts enhance security and usability of CAPTCHAs. There exist few major different ideas for designing image CAPTCHAs. Some methods apply a set of modifications such as rotations to the original image saved in the data base, to make the CAPTCHA more secure. In this paper, two different approaches for designing image based CAPTCHAs are introduced. The first one _which is called Tagging image CAPTCHA _is based on pre-tagged images, using geometric transformations to increase security, and the second approach tries to enhance the first one by eliminating the use of tags and relying on semantic visual concepts. In fact, recognition of up- right orientation is used as a visual cue. The usability of the proposed approaches is verified using human subjects. An estimation of security is also obtained by different kinds of attacks. Further studies are done on the proposed transformations and also on the properness of each original image for each approach. Results suggest a practical Semantic Image CAPTCHA which is usable and secure compared to its peers.
Measuring the Effects of Moods and Heart Rate Variability when Playing Video Games

In this study, we recruited 20 college students who are video games enthusiasts and assigned them to two groups, namely, video game playing (as a testing group), and bookreading (as a control group). We use profile of mood state (POMS) scale and electrocardiography (ECG) patch physiological signal device as tools to measure moods and heart rate variability (HRV) before and after the experiment, and we assessed the effects of playing video games on physical and mental health. We expect that the low frequency (LF) and high frequency (HF) powers for HRV in testing group to be significantly higher than the value in the control one after the experiment and to have 30 minutes duration in the following sleep stage. We show that playing video games may excite the sympathetic and parasympathetic systems during and after playing. This will disturb sleep and increase the risk of chronic diseases. Based on these findings, we recommend avoiding playing video games for extended periods of time. Keywords—video game; mood; heart rate variability (HRV); sympathetic; parasympathetic.
Multi-Biometric Person Authentication System Using Speech, Signature And Handwriting Features

-------------------------------------------------------------ABSTRACT-------------------------------------------------------Biometric Technologies are automated methods for verifying or recognizing the identity of a living person based on physiological or behavioral characteristics. Multimodal Biometric Systems are those which utilize more than one physiological or behavioral characteristic for enrollment, verification or identification. Speaker Recognition is the task of recognizing the speakers using their speech signal. Mel Frequency Cepstral Coefficients (MFCCs) of speaker is determined by extracting and analyzing speaker – specific features from the speech signal. Signature Recognition is the task of recognizing signatories by using their signatures. Features like Horizontal Projection Profile (HPP), Vertical Projection Profile (VPP) and Discrete Cosine Transform (DCT) are determined. Handwriting biometric feature can also be used for person authentication, since handwriting has been trained during initial days of learning of language; it is possible to find more regular and reliable results using this feature. In this project, we develop a Multimodal Biometric System using speech, signature and handwriting features, with the objective of improving performance and robustness. For identification and verification, we use MATLAB 7.14 to determine MFCC, HPP, VPP, DCT coefficients. KeywordsBiometrics; Speaker recognition; Signature recognition; Handwriting recognition; Multimodal system. --------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 06 June 2014 Date of Publication: 20 June 2014 ---------------------------------------------------------------------------------------------------------------------------------------
Intelligence and Security Databases (ISD) vs. ’Hard Core’ Sciences Databases (HCSD): Challenges and Opportunities

Intelligence and security databases (ISD) are facing the specific challenges and opportunities of information overload and the ultimate need for advanced intelligence analyses and investigations. We summarize analogies with hard core science databases (HCSD) challenges(the case of synoptic astronomy) and point out HCSD experiences which could be applied on problems facing ISD.
Four-dimensional representation and collision detection for moving objects

We consider the collision detection problem for general objects. A four-dimensional approach is proposed for this problem which detects exactly and in one-step when and where the earliest collision will occur between the objects. This is done by using four-dimensional sets to represent the objects in both space and time. The problem is then posed as a nonlinear programming problem. The algorithm can handle the case of a rigid body moving on a general path in /spl Rfr//sup 2/ or /spl Rfr//sup 3/ with simultaneous translation and rotation. Simulation results on some example problems are given, and show that the algorithm is superior to those available in the literature.
Transforming GRAI Models into UML Models, a First Step to Model Driven Interoperability

One of the main weaknesses of Enterprise Modelling is the difficulty to generate software from enterprise models. In this context, a model-driven approach can be useful to improve this poorness, transforming these models at different levels of abstraction down to achieving the code generation. The main advantage of this kind of approaches is to try to automate this transformation process as much as possible. However, interoperability problems arise in networked enterprises when they try to apply them, and the main difficulties to achieve the objective appear at conceptual level. In this paper, we present a general proposal, called Model Driven Interoperability (MDI), for transforming models at different levels of abstraction focused on interoperability issues. At conceptual level, it provides a method to transform GRAI Models into UML models, as a first step to achieve interoperability following a model driven approach. Moreover, we show a practical example of transforming a GRAI Extended Actigram into a UML Activity Diagram using a tool in order to show its feasibility.
Brain Tumor Segmentation using Multiobjective Fuzzy Clustering

The segmentation of magnetic resonance images plays a crucial role in medical image analysis because it extracts the required area from the image. Despite intensive research, it still remains a challenging problem and there is a need to develop an appropriate and efficient medical image segmentation method. In this paper, we propose a clustering approach for brain tumor segmentation to diagnose accurately the region of cancer. Applied to magnetic resonance image brain our method provides better identification of brain tumor.
Semi-automatic Linking of New Czech Synsets Using PrincetonWordNet

In this paper we discuss extending Czech WordNet with verb synsets coming from the Verbalex database of Czech valency frames. One of the main tasks involved is linking newly added verb synsets to their Czech hypernyms and their English counterparts in Princeton WordNet. To spare the human lexicographers from tedious work, and to make the task more efficient, we have developed WordNet Assistant, a software tool that helps locate the relevant synset(s) in the already existing structures. According to our experience so far, this tool is of great advantage when incorporating new synsets to Czech WordNet, and we regard it as a worthwhile facility when extending WordNets also for other languages.
Ecofriendly Antifouling Marine Coatings

Foul release coatings were first used on vessels in the early 1990s, but despite early excitement about the technology, they have had a prolonged modest market share due to high cost and poorer performance when compared to biocidal marine coatings. Recently, these coatings are experiencing a renaissance. Accelerated progress based on nanochemistry has enabled the synthesis of ecofriendly coatings with improved foul release performance, and also antifouling properties. This study aims to provide an holistic overview of the research achievements that are driving the emerging commercially available nonbiocidal technologies for both large and small vessels.
Prototyping and Evaluation of an Interactive DoorSign Aufbau und Evaluierung eines interaktiven Türschildes

Optimized usage of rooms at university becomes more and more important with a growing number of students. As a student today it is close to impossible to reserve a room for learning. Of course there are rooms known to be available at a certain time, but these can not be booked by students so there is the possibility that you and your learning group will compete with some noisy group of other students who occupied the room as well. To improve that situation the Interactive DoorSign, a prototype developed to manage rooms through an Android tablet attached next to them, was put into beta testing. There are existing projects on the topic which were reviewed in chapter 2. The improvements on the existing concept and development required to put the prototype into testing are described as well, especially the casing that was assembled using rapid prototyping technology is unusual. Details of the security implications, the possible attack vectors on the system and the concerns about the privacy of the users are discussed in chapter 3. The evaluation of the prototype can be found in chapter 4 and 6. The methodology of the evaluation is described. The results show that while the prototype implementation receives a low value on the System Usability Scale (SUS) every user was able to complete the given tasks and was able to learn the interaction with the system quickly.