Nowadays liquid crystal display (LCD) is an integral part of humans’ everyday life. High demand for new and innovative LCD products force LCD industry to develop and implement new types of LCDs. Bistable smectic-A (SmA) LCD is one of the most promising devices for smart glass applications due to long-term bistability, low haze at clear state, low transmittance at scatter state and low power consumption. The study describes the most relevant conclusions obtained from frequency response testing and electric current measurements of bistable SmA LCD samples. Bistable LCDs have two states: opaque (light scattering state) and focal conic (transparent state). Switching between clear and scatter states and vice versa is a frequency dependant process. The conducted research on bistable SmA LC frequency response provides important knowledge about operation principles of the smart glass devices.

Bistable smectic-A (SmA) liquid crystal display (LCD) is one of the most promising devices for smart glass applications due to long-term bistability, low haze at clear state, low transmittance at scatter state and low power consumption. The need of a good simulation model for an LCD becomes apparent during the design of driving system. Liquid crystal (LC) capacitance is critical in the simulation of LCD pixels and is voltage dependent due to the crystal characteristics. Bistable smectic-A LC capacitance model is introduced in the paper. The study describes the most relevant conclusions obtained from the measurements of electric properties of bistable SmA LCD samples and electric equivalent circuit characterization.

Promocijas darba mērķis ir noskaidrot, vai Smectic-A šķidrais kristāls var būt nākamās paaudzes produkts, kas spētu uzlabot cilvēku ikdienu. Šī šķidrā kristāla optiskās īpašības, salīdzinot ar tirgū pieejamajiem produktiem, ir krietni labākas, t. i., gaismas caurlaidība vienā stāvoklī ir > 85 %, otrā < 2 %. Tas paver iespējas produktu izmantot dažādiem nolūkiem, piemēram, viedajiem logiem, lai izkliedētu gaismu saulainā dienā vai sniegtu privātuma sajūta atklātā ofisa telpā. Veikta padziļināta Smectic-A šķidrā kristāla iepriekšējo pētījumu, iegūto eksperimentālo datu un mēģinājumu izstrādāt funkcionālus produktus analīze. Iegūtā informācija detalizēti aprakstīta, izceļot galvenās neatrisinātās problēmas un piedāvājot to risinājumus. Lai saprastu Smectic-A šķidrā kristāla potenciālu viedo logu tehnoloģijā, veikta esošo produktu analīze, sniegts kopsavilkums par aktīvajiem viedajiem logiem un to savstarpējais salīdzinājums. Eksperimentāli izpētīta Smectic-A šķidrā kristāla gaism...

The Thesis focuses on Smectic-A (SmA) liquid crystals' (LCs) functional behaviour in order to understand if this will be the next generation product that could improve the daily life of the society. The optical properties of this liquid crystal are by far the best compared to the products available in the market, i.e., the light transmittance in transparent state is >85 % and in scatter state <2 %. Enabling the LC to be used for a variety of purposes, such as smart windows to scatter light on a sunny day or provide a sense of privacy in an open type office space. An in-depth literature review discusses the existing studies, obtained experimental data and attempts to develop functional products. The main unresolved problems are highlighted, described in detail and solutions are offered. In order to understand the potential of SmA LC in the smart glass/window technology, analysis of existing products was performed, a summary of an active smart glass/windows provided, and a c...

Taking into account that each new day an amount of daily processed data grows exponentially, it is obvious that knowledge society needs flexible, effective and high performing tools to retrieve, learn and apply necessary information. Learning management systems become more and more intelligent and adaptive. Learning analytics instruments give course developers a possibility to assess and analyze learners’ activities and behavior patterns within e-learning environment, allowing to propose them personalized self-paced learning path and types of learning objects. This paper discusses challenges in development of adaptive learning management system and outlines its prospective models and properties.  

The purpose of this study is to between the learners' emotional characteristics and styles in touch screen environments. We propose a method to identify the variety of learners' boredom in the learning process utilising handwriting data. The novelty of the method is to avoid explicit polling of learners how do they feel. We use the recurring acquiring of personal handwriting data utilising the computational power of both a mobile device and cloud-based resources. Also, we use machine learning-based sentiment detection in the research. We smoothly inject periodic handwriting tests convolving them with learning objects to study the correlation between learners' emotions dynamic, they demonstrate, and the ability to focus and think critically. With the help of machine-learning methods and new communication protocols, we can step up the student-centric mobile-based education process by taking advantage of the latest achievements in a big data analysis and cloud computing. Also, we clarify the conceptual model for the testbed used in the experiment. The findings may likely impact the future personalized e-learning systems.

The quality of youth education, in general, is worsening (Coppola and O’Higgins, 2015). Some of the reasons for such a statement are (i) the current changes of educational systems in general, (ii) eventually unreasonable switching between ephemeral learning trends and tools. Despite the use of learning management systems, learners or educators, face today a real and increasing difficulty in finding optimal communication for the learning coalition between the students and the teachers. In this research, students’ activity in two popular learning management systems (LMS): MOODLE and Open edX are analyzed. We examine both platforms by measuring and comparing the students’ activity from the learning-time aspect. The novel – CAST algorithm is proposed to reduce the overestimated learners’ activity measuring errors, caused by unterminated WEB sessions. We conclude that Open edX engage students more, therefore, educational institutions should move forward to modern eLearning platforms.

Complex mathematical approaches exist in biological, social, and educational sciences, creating models to understand and explain cognition processes in human brain. Yet, the logged raw data is just an initial learners' behavior footprint in Virtual Learning Environments. Exploratory Data analysis would help to deepen the understanding of cognition processes in students' brain. The challenge is: the evaluation of usability of e-learning courses before the large-scale implementation. With this aim, we combine knowledge elements explored from logged learners behavior data and cognitive theories to formulate a computer model for Virtual Student's evolution. We assume that some of the brains energetic expenses in learning and memorization are due to energy-extraction skills from cognitive abilities, knowledge, information, etc. We also assume that the Virtual Student model can perform energy flow modeling by extracting energy from the environmental learning objects and losing the power in a tedious learning process. The research shows that on a Virtual Student's cognitive energy flow model based approach can potentially improve the model compliance with real student's behavior model and can be applied to predictive analytics classification problems in both inexpensive small and large-scale applications.

Abstrakt Previous experience shows that renovation of ventilation system is not a typical component of renovation of multi-apartment buildings (MABs) in Latvia. As a consequence, rooms are not ventilated enough and indoor air quality (IAQ) is reduced. This, in turn, ...

The aim of the study is to create the complete landscape model for learner behavior and knowledge acquisition data, and mapping the real learner performance data on it. This paper reports on a TELECI approach for learner knowledge acquisition data visualization. We present the new metrics for determination the relevance of the e-course content and delivery approach to learners. This approach is based on the assumption that knowledge acquisition of real e-content can be quantified by superposition of the impact of learning “perfect” content, “too easy” content, and “too complicated” content. The user learning performance data are generated in the TELECI e-learning environment with additional short, easy-to-use multiple-choice questions before and after each content subunit. This approach was well accepted by learners. The learner knowledge acquisition data are visualized on knowledge acquisition surface. This surface is calculated from the set of artificial data. The experimental dat...

In this paper, we introduce the Hybrid AI-Fuzzy Intelligent Control (HAFiC) system prototype. The proposed model is the add-on to online learning-tutoring environments to proactively detect learners’ emotional states by measuring performance gaining or degradation in a game-like form. We introduce a system model and experimental results implementing recently proposed Simple Algorithm for Boredom Identification (SABI) (Zagorskis et al.,2019) along with the Fuzzy Intelligent control approach to evaluate whether proposed indirect data acquisition method allows retrieving performance data variability in correspondence to real user emotional states. In the proposed system, the AI part cares about Image Processing and Text Recognition gathered from mobile-handwriting devices. In contrast, Fuzzy Expert System part organises users’ performance data utilisation and decision making based on adaptive fuzzy inference approach. First experiment results

We consider the problem of resource allocation in a substrate network and suggest a simulation scheme for dynamically adaptive bandwidth allocation protocols using CPN (Coloured Petri Nets) Tools. The proposed simulation scheme based on network virtualization according to DaVinci principles allows us to describe how a single physical network can support multiple traffic classes with different performance objectives by means of multiple virtual networks constructed by subdividing each physical link into multiple virtual links.

Data analysis in Virtual Learning Environment deepens the understanding of cognition processes in real student’s brain. The challenge is the evaluation of the quality of e-learning courses before the large-scale implementation. With this aim, we formulate the concept for a computer model for Virtual Student’s evolution. We combine knowledge elements explored from learners behavior data and cognitive theories. We assume that some of the brains energy flow expenses in learning and memorization are due to energy extraction for applying existing skills, analysis of accumulated knowledge, and adaptation of newly available information. We argue that the proposed Virtual Student model can perform cognitive energy flow modeling by extracting energy from the environmental learning objects and losing the power in a tedious learning process. The research shows that Cognitive Energy Flow model can be computerized to produce synthetic data to improve e-learning courses and predict real student’s...

We consider the problem of bandwidth allocation in a substrate network as an optimization problem for the aggregate utility of multiple applications with diverse requirements and describe a simulation scheme for dynamically adaptive bandwidth allocation protocols. The proposed simulation model based on Coloured Petri Nets (CPN) is realized using CPN Tools.

The user behavior data generated in the TELECI learning environment with additional short, easy-to-use multiple-choice questions before and after each content subunit are used for visualization and correlation analysis. Three user behavior data clusters were identified in data landscape. The student behavior change among the TELECI-clusters was used for TELECI learning support algorithm design. The student performance data before and after learning the econtent were used for knowledge acquisition model design. This model is based on the assumption that knowledge acquisition of real e-content can be quantified by superposition of the impact of learning "perfect" content, too easy content, and too complicated content. The learner knowledge acquisition surface is calculated on this assumption. The data of real course learner knowledge acquisition are located on this surface as "telecides". Telecides are the visualization of the appropriateness of an e-content unit for the needs of the specific learner or learners target group.1

This article examines our proposed innovative strategies to further improve e-learning and new eBig3 learning approaches using an e-Ecosystem that is based on a multi-screen concept to support e-learning. Here we present the data comparison of user behavior in well-known Moodle and EdX learning environments. We propose the New Media art code analysis as an experimental method for eContent evaluation, and present the design science research method as a tool for application of e-learning research results. This paper is a part of a cross-cutting research in the fields of digital / new media art and ICT product innovation. The research is aimed at finding a path to open up the cache of knowledge situated in the theory of modern art, and to incorporate the codes of modern art into the field of ICT. The goal of the research is to transfer knowledge of modern art into areas traditionally not related to contemporary art and its specific academic trends, as well as to encourage the intersection of these disciplines. Consequently, this research aims to create a new profile of products that would exemplify modern interdisciplinary and analytic thought.

For reduction of the impact of electromagnetic field on parameters of electronic equipment, shielding in many different shapes and qualities is used. The quality of the shielding is dependent on size, shape and amount of openings in the body of the shield. In electromagnetic immunity and emission tests it is very difficult to predict the shielding efficiency from theory of refraction, reflection and diffraction due to the very complicated shape and material mix in the design configuration of multilayer PCB, supports, covers and screens. For this reason in order to build up and make calculations of scattering matrix parameters as the estimation of the shielding efficiency in the given frequency range we propose to use the drawn 3D electromagnetic model.

The energy consumption and electrical characteristics of a novel direct current (DC) power supplied industrial robot prototype are compared and analyzed with a state of the art alternating current (AC) supplied industrial robot. An extensive set of experiments shows an important reduction of the total energy consumption for different electrical power profiles measured in various robot trajectories with specific working temperatures. The recuperated energy is also analyzed in the different scenarios. Experimental results show that a DC type robot can be up to 12.5% more energy-efficient than an equivalent AC type robot.