Miracle-dz/UniFAR-FTUs huggingface dataset:
Virtual Worlds as Fuzzy Cognitive Maps

Fuzzy cognitive maps (FCM) can structure virtual worlds that change with time. An FCM links causal events, actors, values, goals, and trends in a fuzzy feedback dynamical system. An FCM lists the fuzzy rules or causal flow paths that relate events. It can guide actors in a virtual world as the actors move through a web of cause and effect and react to events and to other actors. Experts draw FCM causal pictures of the virtual world. They do not write down differential equations to change the virtual world. Complex FCMs can give virtual worlds with new or chaotic equilibrium behavior. Simple FCMs give virtual worlds with periodic behavior. They map input states to limit-cycle equilibria. An FCM limit cycle repeats a sequence of events or a chain of actions and responses. Limit cycles can control the steady-state rhythms and patterns in a virtual world. In nested FCMs each causal concept can control its own FCM or fuzzy function approximator. This gives levels of fuzzy systems that can choose goals and causal webs as well as move objects and guide actors in the webs. FCM matrices sum to give a combined FCM virtual world for any number of knowledge sources. Adaptive FCMs change their fuzzy causal web as causal patterns change and as actors act and experts state their causal knowledge. Neural learning laws change the causal rules and the limit cycles. Actors learn new patterns and reinforce old ones. In complex FCMs the user can choose the dynamical structure of the virtual world from a spectrum that ranges from mildly to wildly nonlinear. We use a simple but adaptive FCM to model an undersea virtual world of dolphins, fish, and sharks.
Tabular Reinforcement Learning Aided by Generalisation Methods

Reinforcement learning is a machine learning paradigm that deals with optimisation and learns by interacting with its environment. Tabular reinforcement learning methods are popular because of their relative simplicity combined with good guarantees of finding an optimal solution. The downside is that they suffer from an exponentially growing exploration space, which will obstruct the learning of large tasks. Function approximation is the most commonly used alternative to deal with this problem. It involves interpolating of states that have never been encountered before by learning the values of generalising features. This generalising property is helpful in targeting larger problems and allows for faster learning. Unfortunately, it can be difficult to specify proper features that are required to learn a solution, and convergence cannot always be guaranteed. Generalisation at an even higher level is called transfer learning, where priorly acquired knowledge from one or more tasks is reused to aid the learning process of the next task. This thesis proposes a framework that combines tabular reinforcement learning methods with both of these generalising concepts to achieve a convergent learning process with good generalisation properties. To test the viability of the proposed method, it is used to solve discrete path planning problems. Results of these tests show that simultaneous learning with the help of function approximation in a parallel learning process can be leveraged to achieve a significant reduction in steps in both the first and consecutive tasks.
Natural Hand Interaction for Augmented Reality

Despite the increasing prevalence of Augmented Reality (AR) interfaces, there is still a lack of interaction techniques that allow full utilization of the medium. Natural hand interaction has the potential to offer these affordances however, as of yet, has not been well explored. The aim of this thesis is to improve the understanding of natural hand interaction and ultimately create a novel natural hand interaction technique that enhances user experience when interacting with AR. To better understand natural hand interaction, two prototype AR systems featuring environmental awareness and physical simulation were developed, one featuring interaction on a tabletop, and the other in a mobile tablet setting. Observations and feedback from public demonstrations of the systems were collected, and it was found that users felt that interacting physically using their hands and other tangible objects was natural and intuitive. Following this, a guessability study was conducted to elicit hand gestures for AR and obtain qualitative feedback from users in a video-see through head mounted display (HMD). From the results, a user-defined gesture set was created to guide the design of natural hand interaction for AR. Utilizing this deeper understanding and set of design guidelines, a gesture interface was developed that enabled hand tracking and gesture recognition based on depth sensing input. An AR framework that supports natural interaction as the primary input, called G-SIAR, was created, and a novel direct manipulation natural hand interaction technique, Grasp-Shell (GShell), was developed. This interaction technique was validated by comparing it to a traditional indirect manipulation gesture and speech interaction technique, Gesture-Speech (G-Speech), in a usability study. From the study, we gained insights into the strengths and weaknesses of each interaction technique. We found impacts on performance, usability, and user preference when comparing G-Shell’s direct interaction, where the user physically manipulates the object they are interacting with, and G-Speech’s indirect interaction, where the user interacts with the object remotely using gestures and speech commands, depending on the task. We concluded that these interaction techniques were complementing each other and should be offered together. The primary contributions of this thesis include a literature review of AR and its interaction techniques, the implementation of two AR systems and findings from the public demonstrations, findings from a guessability study on hand gestures for AR, the design and development of gesture interface and multimodal AR framework, and the design and evaluation of two natural interaction techniques, G-Shell and G-Speech. This research offers knowledge gained into natural hand interaction for AR and forms a new layer of foundation for research into interaction techniques in AR. Deputy Vice-Chancellor’s Office Postgraduate Office
Methods for Validating The use of virtual simulation generated from a computer game for environment and behaviour research

This paper shows that computer game technology can generate virtual environments for use as research settings in environment and behaviour research. It illustrates the development of a simulation of a retail shop generated by the game engine Counter-Strike. In addition, this paper suggests methods to interface with this virtual shop. Lastly, it proposes methods to assess the validity of the simulation of this virtual shop.
A study of user acceptance of destination management systems in Taiwan tourism with the modified technology acceptance model

In the tourism sector, the Internet is a medium of growing importance. Over the years, people's strategies and choices to utilize tourism information have shifted dramatically due to the increased accessibility provided by the Internet. Today, most of the daily operations of travel enterprises involve the use of the Internet to connect to distributed resources, personnel and travelers globally. The accurate and specific travel-related information provided via the Internet can reach the target audience with the accuracy of more personalized information sources. According to Buhalis and Law (2008), multimedia on the Internet is becoming one of the key areas of development that influences tourism. Even though there are many tourism information searches on the Internet involving geospatial information through WebGIS, few researchers have discussed tourists' behavioral patterns with destination management systems (DMSs) media. The purpose of this study was to test the modified Technology Acceptance Model (TAM), to apply it to a broad sample of Taiwan tourists and to examine the factors affecting consumers' intentions to use and adopt destination management systems (DMSs) in Taiwan. By integrating new constructs into the technology acceptance model (TAM), this study aims to discuss the hypotheses and to demonstrate the effect of a modified TAM on the intention of DMSs. A questionnaire survey was conducted to explore the correlations between the variables. The empirical results overall support a modified TAM in explaining consumers' behavioral intentions to use/adopt DMSs. Implications of this study are important for both researchers and practitioners.
Evaluating a City Exploration Dialogue System with Integrated Question-Answering and Pedestrian Navigation

We present a city navigation and tourist information mobile dialogue app with integrated question-answering (QA) and geographic information system (GIS) modules that helps pedestrian users to navigate in and learn about urban environments. In contrast to existing mobile apps which treat these problems independently, our Android app addresses the problem of navigation and touristic questionanswering in an integrated fashion using a shared dialogue context. We evaluated our system in comparison with Samsung S-Voice (which interfaces to Google navigation and Google search) with 17 users and found that users judged our system to be significantly more interesting to interact with and learn from. They also rated our system above Google search (with the Samsung S-Voice interface) for tourist information tasks.
Non-continuous Syntactic N-grams

—In this paper, we present the concept of non-continuous syntactic n-grams. In our previous works we introduced the general concept of syntactic n-grams, i.e., n-grams that are constructed by following paths in syntactic trees. Their great advantage is that they allow introducing of the merely linguistic (syntactic) information into machine learning methods. Certain disadvantage is that previous parsing is required. We also proved that their application in the authorship attribution task gives better results than using traditional n-grams. Still, in those works we considered only continuous syntactic n-grams, i.e., the paths in syntactic trees are not allowed to have bifurcations. In this paper, we propose to remove this limitation, so we consider all sub-trees of length n of a syntactic tree as non-continuous syntactic n-grams. Note that continuous syntactic n-grams are the particular case of non-continuous syntactic n-grams. Further research should show which n-grams are more useful and in which NLP tasks. We also propose a formal manner of writing down (representing) non-continuous syntactic n-grams using parenthesis and commas, for example, " a b [c [d, e], f] ". In this paper, we also present examples of construction of non-continuous syntactic n-grams on the basis of the syntactic tree of the FreeLing and the Stanford parser. Grigori Sidorov
The Statistical Classification of Breast Cancer Data

In this article, we study the statistical classification of breast cancer of two well-known large breast cancer databases. We use various classification rules, such as linear, quadratic, logistic, k nearest neighbor (k-NN), and k rank nearest neighbor (k-RNN) rules and compare the performances. We also conduct feature analysis for both data sets using logistic regression model.
Meta-Analysis: The End of the Beginning, or the Beginning of the End?

This issue of KT Update (V2 N5) presents another in a series of brief articles by Dr. Marcel Dijkers. This article discusses the history, present, and possible future of meta-analysis. Meta-analysis is defined in the Medical Subject Headings (MeSH) as “A quantitative method of combining the results of independent studies (usually drawn from the published literature) and synthesizing summaries and conclusions which may be used to evaluate therapeutic effectiveness, plan new studies, etc., with application chiefly in the areas of research and medicine” (http://www.ncbi.nlm.nih.gov/mesh/? term=meta+analysis). The SEDL-published manual for Assessing the Quality and Applicability of Systematic Reviews (AQASR) gives this description: “A (statistical) procedure that combines quantitatively the results of several studies that address the same question. This is typically done by identification of a common measure of effect size and other parameters that are more precise and less likely to be in error (due to sampling) than the individual studies being reviewed” (Task Force on Systematic Review and Guidelines, 2013).
Volume haptization

The authors describe haptic representation of volume data. Volume visualization is a powerful tool in the field of scientific visualization. However, visual representation of full three-dimensional volume is hard to comprehend because of occlusion. Higher-dimensional and multi-parameter data sets are also difficult to present by visual image. The authors propose methods for presentation of volume data by force sensation. A six degree-of-freedom force reflective master manipulator is used for haptization. The manipulator is combined to real-time visual image of volume data. Methods of haptic representation of scalar, vector, and tensor data are discussed. Recognition performance tests of scalar and multiparameter volume data are examined. <<ETX>>
Learning of Generic Vision Features Using Deep CNN

Eminence of learning algorithm applied for computer vision tasks depends on the features engineered from image. It's premise that different representations can interweave and ensnare most of the elucidative genes that are responsible for variations in images, be it rigid, affine or projective. Hence researches give at most attention in hand-engineering features that capture these variations. But problem is, we need subtle domain knowledge to do that. Thereby making researchers elude epitome of representations. Hence learning algorithms never reach their full potential. In recent times there has been a shift from hand-crafting features to representation learning. The resulting features are not only optimal but also generic as in they can be used as off the shelf features for visual recognition tasks. In this paper we design and experiment with a basic deep convolution neural nets for learning generic vision features with an variant of convolving kernels. They operate by giving importance to individual uncorrelated color channels in a color model by convolving each channel with channel specific kernels. We were able to achieve considerable improvement in performance even when using smaller dataset.
On-demand QoS routing in multihop mobile networks

The emergence of nomadic applications have generated a lot of interest in next generation wireless network infrastructures which provide differentiated service classes. So it is important to study how the quality of service (QoS) should be guaranteed. To accomplish this, we develop an admission control scheme which can guarantee bandwidth for real-time applications in multihop mobile networks. In our scheme, a host need not discover and maintain any information of the network resources status on the routes to another host until a connection request is generated for the communication between the two hosts, unless the former host is offering its services as an intermediate forwarding station to maintain connectivity between two other hosts. This bandwidth guarantee feature is important for a mobile network to interconnect wired networks with QoS support. Our connection admission control scheme can also work in a standalone mobile ad hoc network for real-time applications. This control scheme contains end-to-end bandwidth calculation and bandwidth allocation. Under such a scheme, the source is informed of the bandwidth and QoS available to any destination in the mobile network. This knowledge enables the establishment of QoS connections within the mobile network and the efficient support of real time applications. In the case of an ATM interconnection, the bandwidth information can be used to carry out intelligent handoff between ATM gateways and/or to extend the ATM virtual circuit service to the mobile network with possible renegotiation of QoS parameters at the gateway. We examine via simulation the system performance in various QoS traffic flows and mobility environments. The "on-demand" feature enhances the performance in the mobile environment because the source can keep more connectivity with enough bandwidth to a receiver in the path-finding duration.
Wavelet Features and Gaussian Process Classifiers for Face Recognition

Recently, Gaussian Process has been extended to classification problem and some Gaussian Process classifiers had been proposed. Engaging the Gaussian Process classifiers, in this paper, we propose a new face recognition algorithm based on wavelet face features and binary Gaussian Process classifiers. This method employs a binary tree method to extend the ability of binary Gaussian Process classifiers for dealing with multi-class problem. In the experiments, we compare our face recognition algorithm with other traditional techniques including PCA and Associative memory Model on ORL and MIT-CBCL face database. The experimental results show that our face recognition algorithm is effective and competitive.
Parameterized extensible effects and session types (extended abstract)

Parameterized monad goes beyond monads in letting us represent type-state. An effect executed by a computation may change the set of effects it may be allowed to do afterwards. We describe how to easily `add' and `subtract' such type-state effects. Parameterized monad is often used to implement session types. We point out that extensible type-state effects are themselves a form of session types.
Functional interactions in basal ganglia studied by multiple single unit recordings sorted by an unsupervised template matching algorithm

The present thesis is devoted to the development of a new unsupervised spike sorting method and its application to the investigation of neuronal activity. The development of new approaches to spike sorting is crusial both for the intrasurgical electrophusiology and for the efficience of real time electrophysiological experiences. The method presented in the first part of this thesis is a novel approach to the problem which describes action potential by means of differential equations with perturbation characterizing the internal variation of their forms. The unsupervised spike sorting software implemented on the basis of the presented method comprises an automatic algorithm of estimation of class centers and their radiuses. The second part presents the application of the method to the investigation of neuronal activity in basal ganglia. The data for the analyses were acquired in the surgical room of the department of neurosurgery of the University Hospital, Grenoble, and represent the STN (950 recordings), the GPI (183) and the SNR (105) of 13 Parkinsonian patients and 2 dystonia patients. The analyses are aimed to define typical forms of action potential and to reveal a parallel between the nature of neural activity and the gravity of the Parkinsonian disease symptoms.
Poster: Physics-Based Attack Detection for an Insider Threat Model in a Cyber-Physical System

To ensure the proper functioning of critical systems, it is important to design secure Cyber Physical Systems (CPS). Since CPS are connected systems, most studies consider external adversaries as a threat model, which might not be able to cater for an insider threat with the physical access to the system. In this article, we proposed an attack detection mechanism for an insider who has physical access to a CPS. The proposed method exploits the dynamics of the system and detects an attack based on the laws of Physics. Based on the mass flow equations, we analyze the rate of change in the plant's process and create a feature vector based on the process dynamics. The model has been trained by passing rate of change in system's state as input to Support Vector Machine (SVM), to detect the abnormal behavior in the system. Based on the proposed framework, experiments are performed on a real water treatment testbed, to validate our model and to measure the efficiency of the plant in normal and under attack scenarios. The detection result shows that proposed scheme can detect attacks with accuracy as high as $96%$.
Ciphertext Integrity with Misuse and Leakage: Definition and Efficient Constructions with Symmetric Primitives

Leakage resilience (LR) and misuse resistance (MR) are two important properties for the deployment of authenticated encryption (AE) schemes. They aim at mitigating the impact of implementation flaws due to side-channel leakages and misused randomness. In this paper, we discuss the interactions and incompatibilities between these two properties. We start from the usual definition of MR for AE schemes from Rogaway and Shrimpton, and argue that it may be overly demanding in the presence of leakages. As a result, we turn back to the basic security requirements for AE: ciphertext integrity (INT-CTXT) and CPA security, and propose to focus on a new notion of CIML security, which is an extension of INT-CTXT in the presence of misuse and leakages. We discuss the extent to which CIML security is offered by previous proposals of MR AE schemes, conclude by the negative, and propose two new efficient CIML-secure AE schemes: the DTE scheme offers security in the standard model, while the DCE scheme offers security in the random oracle model, but comes with some efficiency benefits. On our way, we observe that these constructions are not trivial, and show for instance that the composition of a LR MAC and a LR encryption scheme, while providing a (traditional) MR AE scheme, can surprisingly lose the MR property in the presence of leakages and does not achieve CIML security. Eventually, we show the LR CPA security of DTE and DCE.
TABIQUE WALLS COMPOSITE EARTH BASED MATERIAL CHARACTERIZATION IN THE ALTO DOURO WINE REGION , PORTUGAL

The Alto Douro Wine Region, located in the northeast of Portugal, a UNESCO World Heritage Site, presents a relevant tabique building stock, a traditional vernacular building technology. A technology based on a timber framed structure filled with a composite earthbased material. Meanwhile, previous research works have revealed that, principally in rural areas, this Portuguese heritage is highly deteriorated and damaged because of the rareness of conservation and strengthening works, which is partly related to the non-engineered character of this technology and to the growing phenomenon of rural to urban migration. Those aspects associated with the lack of scientific studies related to this technology motivated the writing of this paper, whose main purpose is the physical and chemical characterization of the earth-based material applied in the tabique buildings of that region. Consequently, an experimental work was conducted and the results obtained allowed, among others, the proposal of a particle size distribution envelope in respect to this material. This information will provide the means to assess the suitability of a given earthbased material in regard to this technology. The knowledge from this study could be very useful for the development of future normative documents and as a reference for architects and engineers that work with earth to guide and regulate future conservation, rehabilitation or construction processes helping to preserve this fabulous legacy.