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Item Restricted Quantum simulator and education tool(Nazarbayev University School of Science and Technology, 2017-04) Mami, DarkhanQuantum computing takes significant place among the spheres of modern information technology. Quantum computation is usually expressed by the quantum circuit with its sequences of quantum gates. One of the practical applications of quantum computation is to use it in a web-based tool for variety of purposes. Thereby, this project aimed to create an educational simulator for studying quantum circuits with different gates, functions, and transformation rules. The tool would help students to learn the principles of quantum circuit in their courses during undergraduate study. The application was created on the Python based Django framework with the help of Python library packages especially Quantum Toolbox in Python (QuTiP) package. Major steps of simulator implementation included the creation of functions able to build a quantum circuit, to add and remove of quantum gates, apply transformation rules. The challenge appeared around the frontend functions, particularly with the Drag and Drop feature. The result of entire work on this project ended up in a web-based simulator applicable for educational purposes, which allows investigation of quantum circuit work, and quantum gates influence on the quantum circuit unitary matrixItem Restricted Environment Estimation Based on Inter-object Relations(Nazarbayev University School of Science and Technology, 2017-04) Ismagambetov, AssetHere we presented the model for environment estimation based on the interobject relations. The uniqueness of this model is that it relies on the results of image segmentation and predicts environment based on the object properties and their relationships. The model provides context by describing the environment where particular objects’ setup can occur. Many other works reported usefulness of contextual information for image processing problems. In particular, [16] had proven that contextual information can improve the accuracy of the verification process up to 16%. As part of the feature work we plan to assess the improvement that our model brings to the overall image segmentation process as part of the Algorithm selection platform.Item Restricted Semantic segmentation by ways of interactive post-processing with active contours model(Nazarbayev University School of Science and Technology, 2017-04) Kubigenov, DarkhanActive contour has been proven to be effective at solving semantic segmentation of images. However, the use cases of such approaches were mostly on trivial problems with narrow utility. For instance, it was used for detecting tumors from MRI scans and finding oil spills from aerial photographs. This thesis considers ways of making active contour work for any kinds of images. Active contour is applied at post-processing step on results from other algorithms.Item Restricted Using Action Dependent Heuristic Dynamic Programming and Genetic Algorithms in the Energy Resource Scheduling Problem(Nazarbayev University School of Science and Technology, 2017-05) Sterling, GulnazEnergy management in smart buildings and homes has become an important issue. Proper energy management is judged upon the amount of consumed electrical energy as well as the total electricity cost. In this master thesis, two optimization algorithms, namely Action Dependent Heuristic Dynamic Programming (ADHDP) and Genetic Algorithms (GA) are used for the energy resource scheduling problem. The main objective of the renewable energy resource scheduling problem is to decrease the electricity cost over a fixed time period while meeting demand. In this work, ADHDP and GA were trained and evaluated on different simulation scenarios with various amounts of available renewable energy. It was demonstrated by computer simulations that both ADHDP and GA are effective in cost minimization compared to the baseline method. A correlation between optimization improvement and available renewable energy was also confirmed by computer simulation in all scenarios.Item Restricted A Distributed Software Architecture for Performing Text Analysis on Web content(Nazarbayev University School of Science and Technology, 2017-05) Aldabergenov, AibekWith the high availability of data on the World Wide Web, researchers are actively using Web content for performing various text analysis operations. The large amount of data introduces challenges in data acquisition, storage and processing for researchers who want to use data from different sources on the Internet. In an environment where several people might want to share their data and code, the problem is further complicated by researchers' use of different software applications for performing data collection, storage and analysis tasks. The goal of this thesis is to study the components that make up different parts of web mining systems, and present a scalable software architecture for large-scale Web content analytics tasks performed in a multi-user setting. Additionally, an implementation of the proposed software architecture using modern open source software frameworks and tools is presented in this work.Item Restricted Automated Theorem Proving in a Chat Environment(Nazarbayev University School of Science and Technology, 2018) Zhumagambetov, Rustam; Sterling, MarkWe present a chat bot interface for the Coq proof assistant system. The bot provides a new modality of interaction with Coq that functions across multiple devices and platforms. Our system is particularly suitable for mobile platforms, Android and iOS. The basic architecture of the bot software is reviewed as are the outcomes of several rounds of beta-testing. Potential implications of the system are discussed, such as the possibility of a seamless collaborative proof environment.Item Open Access QUANTUM EVOLUTIONARY ALGORITHM FOR QUANTUM CIRCUIT SYNTHESIS(School of Sciences and Technology, 2018-06) Krylov, GeorgiyQuantum computing area has a lot research attention due to opportunities that possessing such device could provide. For example, quantum computers could deliver new insights to previously unsolvable problems. The reason for that is higher parallel capabilities of such devices. In addition, since quantum computers are naturally reversible, no heat dissipation occurs during computation [21]. This property could serve as a viable solution to the problem that computer chip production industry faces. Moreover, since the chip manufacturing industry reaches nanometer scale of size of elements, the effects that could cause unexpected information behavior in classical paradigm are part of the technology of quantum devices [31, 14]. Considering possible benefits that could be achieved by quantum computing devices, the new areas of Quantum Information Theory, Quantum Cryptography, Quantum Algorithms and Logic Design and many others emerged at the end of the twentieth century [31]. These areas are concentrating their efforts on solving problems of designing communication protocols, ensuring the security of the new systems, constructing appropriate algorithms. Computers that could be advancing in finding solutions in problems listed above require quantum circuits that have optimal structure and could implement error correction. This is the main motivation for this thesis work to explore the problem of circuit design. The approach that we investigate is circuit construction by the means of Quantum Evolutionary Algorithms. We propose a version of an algorithm that accounts with specificity and constraints of quantum paradigm. We use its Graphic Processing Unit (GPU) accelerated classical implementation to evaluate the behavior and performance of the proposed algorithm. Later we discuss additional complexity introduced by accounting with these constraints. We support our ideas with results of synthesis of small circuits and compare the performance with classical genetic algorithm on similar task.Item Open Access BEHAVIOUR AND REASONING DESCRIPTION LANGUAGE (BRDL)(Software Engineering and Formal Methods, 2020) Cerone, AntonioIn this paper we present a basic language for describing human behaviour and reasoning and present the cognitive architecture underlying the semantics of the language. The language is illustrated through a number of examples showing its ability to model human reasoning, problem solving, deliberate behaviour and automatic behaviour. We expect that the simple notation and its intuitive semantics may address the needs of practitioners from non matematical backgrounds, in particular psychologists, linguists and other social scientists. The language usage is twofold, aiming at the formal modelling and analysis of interactive systems and the comparison and validation of alternative models of memory and cognition.Item Open Access SUBJECT-INDEPENDENT BRAIN–COMPUTER INTERFACES BASED ON DEEP CONVOLUTIONAL NEURAL NETWORKS(IEEE Transactions on Neural Networks and Learning Systems, 2020-10) Kwon, O-Yeon; Lee, Min-Ho; Guan, Cuntai; Lee, Seong-WhanFor a brain-computer interface (BCI) system, a calibration procedure is required for each individual user before he/she can use the BCI. This procedure requires approximately 20-30 min to collect enough data to build a reliable decoder. It is, therefore, an interesting topic to build a calibration-free, or subject-independent, BCI. In this article, we construct a large motor imagery (MI)-based electroencephalography (EEG) database and propose a subject-independent framework based on deep convolutional neural networks (CNNs). The database is composed of 54 subjects performing the left- and right-hand MI on two different days, resulting in 21 600 trials for the MI task. In our framework, we formulated the discriminative feature representation as a combination of the spectral-spatial input embedding the diversity of the EEG signals, as well as a feature representation learned from the CNN through a fusion technique that integrates a variety of discriminative brain signal patterns. To generate spectral-spatial inputs, we first consider the discriminative frequency bands in an information-theoretic observation model that measures the power of the features in two classes. From discriminative frequency bands, spectral-spatial inputs that include the unique characteristics of brain signal patterns are generated and then transformed into a covariance matrix as the input to the CNN. In the process of feature representations, spectral-spatial inputs are individually trained through the CNN and then combined by a concatenation fusion technique. In this article, we demonstrate that the classification accuracy of our subject-independent (or calibration-free) model outperforms that of subject-dependent models using various methods [common spatial pattern (CSP), common spatiospectral pattern (CSSP), filter bank CSP (FBCSP), and Bayesian spatio-spectral filter optimization (BSSFO)].Item Open Access A FORMAL MODEL FOR EMULATING THE GENERATION OF HUMAN KNOWLEDGE IN SEMANTIC MEMORY(From Data to Models and Back, 2021-03) Cerone, Antonio; Pluck, GrahamThe transfer of information processed by human beings from their short-term memory (STM) to their semantic memory creates two kinds of knowledge: a semantic network of associations and a structured set of rules to govern human deliberate behaviour under explicit attention. This paper focuses on the memory processes that create the first of these two kinds of knowledge. Human memory storage and processing are modeled using the Real-time Maude rewrite language. Maude’s capability of specifying complex data structures as many sorted algebras and the time features of Real-Time Maude are exploited for (1) providing a means for formalising alternative memory models, (2) modelling in silico experiments to compare and validate such models. We aim at using our model for the comparison of alternative cognitive hypothesis and theories and the analysis of interactive systems.Item Open Access A FORMAL MODEL FOR THE SIMULATION AND ANALYSIS OF EARLY BIOFILM FORMATION(From Data to Models and Back, 2021-03-05) Cerone, Antonio; Marsili, EnricoBiofilms are structured communities of bacterial cells adherent to a surface. This bacterial state is called sessile. This paper focuses on the modelling of the transition between planktonic and sessile state using Real-time Maude as the modelling language. With more and more bacteria joining the sessile community, the likelihood of producing a biofilm increases. Once the percentage of bacterial cells that adheres to the surface reaches a threshold, which is specific for the considered bacterium species, a permanent biofilm is formed. An important challenge is to predict the time needed for the formation of a biofilm on a specific surface, in order to plan when the material infrastructure that comprises such a surface needs to be cleaned or replaced. We exploit the model-checking features of Real-time Maude to formally prove that a regular cleaning or replacement of the infrastructure prevents the biofilm formation.Item Embargo MULTIMODAL EMOTION RECOGNITION USING DEEP LEARNING AND FUSION TECHNIQUES(Nazarbayev University School of Engineering and Digital Sciences, 2024-04-20) Mukhametsharip, Zhanna; Khamitova, Ainur; Kabdrakhmetova, Zhazira; Nurmakhan, TemirlanEmotion recognition plays a crucial role in human-computer interaction, significantly influencing the advancement of virtual assistants, mental health diagnosis tools, and customer experience analysis systems. Our senior project aims to develop an advanced multimodal emotion recognition (MER) model using modern deep learning techniques and fusion methods. Most traditional emotion recognition models rely on a single modality for decision-making, such as facial expressions or text. However, this approach can be limited in capturing the complexity of human emotions. To overcome this limitation, we will integrate multiple input types to create a more comprehensive model, reducing misclassifications and improving overall system performance. Our system includes an emotion recognition model and a user interface for interaction. The web application will serve as the interface, allowing users to upload video materials of a specified duration. The application extracts audio, video, and text from the uploaded video and feeds them into different deep-learning models customized for each modality. The outputs, representing probabilities for various emotion classes (e.g., ”happy,” ”sad,” ”fearful,” ”surprised,” ”angry,” ”disgusted,” and ”neutral”), will be combined using fusion techniques for enhanced accuracy. The web app then presents visual representations of the emotions through graphs and descriptions for user interpretation.Item Open Access EMEN, AST-BASED PROGRAMMING LANGUAGE(Nazarbayev University School of Engineering and Digital Sciences, 2024-04-21) Tokan, Bexultan; Kabdrashev, Bekzat; Serikbayev, Marat; Surpkelov, NurlybekThe goal of our senior project, "Emen," is to overcome the traditional text-based programming languages' difficult learning curve and error-prone character, which deter many newcomers. Emen is a programming language that takes a new approach by using an Abstract Syntax Tree (AST) and combining a customized editor and compiler to reduce common syntactic and semantic problems. The constraints found in current programming environments and the advantages of visual languages like Scratch for education served as the inspiration for this project. By making programming more approachable and less daunting for novices while maintaining its power and flexibility for more experienced programmers, Emen seeks to transform the programming industry. Our team used the Agile process to create Emen, a functional programming language with a feature set, by utilizing development technologies including Git, Go, and Raylib. Type and variable declarations, function calls, support for logical and arithmetic operations, static arrays, and control structures like while loops and if-else statements are a few examples of these. By enabling direct interaction and editing in the user interface (UI) and providing a visual representation of the code in AST format, Emen's editor guarantees a syntax-error-free writing experience. Significant improvements were made in the spring after the programming language was successfully implemented with an operating editor and compiler by the end of the fall semester. A revamped user interface (UI) influenced by the color scheme of VS Code, a reorganized code base for easier navigation and maintenance, and the transition from an array to a linked-list structure for effective code node management were among the modifications. Notably, these updates improved the backend operations by fixing reference problems and drastically reducing time complexity. As it stands now, Emen set the stage for future advancements. Future work ideas include investigating automatic mistake correction, making sure the language is cross-platform compatible, and extending its capabilities to accommodate object-oriented programming concepts. Emen aims to become a standard instrument in programming education and a driving force behind innovation in software development methodologies.