16168 research outputs found
Sort by
2,1,3-benzotiadiazolo pagrindo savitvarkius monosluoksnius formuojančių junginių sintezė ir tyrimas /
No full textEmotion recognition with a randomized CNN-multihead-attention hybrid model optimized by evolutionary intelligence algorithm /
No full textEmotion recognition systems are vital for various applications, yet existing models often face limitations in computational efficiency and accuracy, especially when handling complex emotional expressions in sequential data. To address these challenges, we propose an innovative emotion recognition framework that integrates a Randomised Convolutional Neural Network (RCNN) with a Multi-Head Attention model, further optimized by the Football Team Training Algorithm (FTTA) metaheuristic to enhance network parameters effectively. The RCNN, characterized by fixed random weights in its convolutional layers, efficiently extracts features from facial landmarks, enabling robust and diverse feature extraction while reducing computational load. This structure is complemented by a multi-head attention mechanism that processes temporal dynamics in emotion data, with both components optimized through FTTA to balance exploration and exploitation. Our hybrid model undergoes rigorous testing on a widely recognized emotion recognition dataset, outperforming conventional fully trainable models and alternative architectures. The results indicate a substantial improvement in classification accuracy, with an overall accuracy of 99%, and a significant reduction in computational demands, achieving a 65% faster training time on average compared to state-of-the-art models. These enhancements confirm the model's efficiency and robustness across various emotional classifications. The synergy between the RCNN's fixed-weight feature extraction and FTTA's optimization capabilities demonstrates a powerful solution for emotion recognition systems. The combination of accuracy and efficiency renders our model suitable for real-world applications, particularly in fields like healthcare and mental health monitoring, where real-time emotion detection can have significant impacts
Green semiconductors: synthesis and analysis of indium sulfide thin films /
No full textThin films are essential in advancing modern technologies due to their wide range of applications in electronics, optoelectronics, and energy systems. Chemical synthesis methods—such as chemical bath deposition (CBD) and solvothermal processes—offer environmentally friendly, low-cost, and scalable alternatives to physical deposition techniques, aligning with current efforts toward greener materials processing [1][2]. Indium sulfide is a non-toxic, cadmium-free semiconductor with a suitable band gap (~2.0–2.3 eV) and high optical absorption, making it an environmentally responsible choice for replacing more hazardous compounds like CdS [3]. Its properties make it highly suitable for use in sustainable photovoltaic and photocatalytic systems [4]. The ecological and functional advantages of In₂S₃ have stimulated growing interest in its application as a buffer layer in thin-film solar cells, as well as in photodetectors and gas sensors [5][6]. The material’s performance is closely tied to the quality and morphology of the thin films, which can be fine-tuned through chemical synthesis routes [7]. In this work we have synthesized thin indium sulfide films by chemical bath deposition method. Structural and morphological analyses, including X-ray diffraction (XRD) and scanning electron microscopy (SEM), confirmed the successful formation of crystalline In₂S₃ thin films. This study demonstrates an environmentally friendly and cost-effective method for producing indium sulfide thin films. The results support the advancement of environmentally friendly materials for future optoelectronic and energy applications, providing a sustainable alternative to more harmful and resource-demanding materials
Biological heavy metal filter utilizing the protozoan tetrahymena thermophila bioaccumulation properties /
No full textDissolved heavy metals in wastewater represent a persistent threat to both environmental and public health due to their chronic toxicity [1]. Conventional treatment approaches—such as chemical precipitation and membrane ultrafiltration—are often energy-intensive and may not be sustainable at lower contaminant concentrations [2]. Alternatively, biological processes offer an environmentally friendly solution by exploiting the innate abilities to sequester heavy metals via mechanisms including bioprecipitation, biosorption, and bioaccumulation [3]. [...]
An efficiency study of foamed polyisocyanurate (PIR) materials as building insulators /
No full textoai:ktu.edu:elaba:229677003Polymeric foams are one of the most efficient thermal insulation materials because of the extra low thermal conductivity blowing agent gases trapped inside of the closed porous structures. Thermal conductivity is one of the most exclusive properties of foamed polyisocyanurate (PIR) materials. The blowing agent gases are selected based upon their characteristics of low thermal conductivity and slow diffusion rates through the foam polymers. The atmospheric gases have a greater thermal conductivity and are typically much smaller molecules with much faster diffusion rates through the foam. PIR gains much of its thermal resistance value from the blowing agents, often a pentane gas mixture, which is trapped in the foam cells. Pentane isomers are commonly used in Europe in manufacturing rigid insulating polyurethane foams. Since the thermal conductivities of the pentanes (between 0.010 and 0.014 W/(m⋅K)) fall significantly below that of air, polyurethane insulation panels may achieve thermal conductivity as low as 0.024 W/(m⋅K). This paper analyses results of the thermal conductivity study and measurements according to two different parameters: the initial value of thermal conductivity and the rate of aging, i.e., the rate of increase in thermal conductivity over time. The initial thermal conductivity value is influenced by the thermal conductivity of the gas inside the cell and the average diameter of the cell
The influence of user-generated content on the selection of travel destinations.
No full textThis master's thesis analyzes the impact of user-generated content (user-generated content) on travel destination choice. User-generated content, including social media posts, blogs, reviews, photos, videos, and other digital formats, has become a significant source of information for travelers in recent years, influencing their decision-making and destination selection. Such content is often considered more reliable than traditional advertising, as it is created by real users sharing their personal experiences and insights. The aim of this thesis is to theoretically and empirically substantiate the impact of user-generated content on travel destination choice. Additionally, the research aims to assess which types of user-generated content (e.g., photos, videos, reviews, social media posts) have the greatest impact on consumer choices. The research part of this thesis is based on empirical data collected from a group of respondents whose travel choices are influenced by user-generated content. The study employed quantitative methods, including surveys and data analysis, to evaluate the key aspects of user-generated content that influence consumer behavior. The results indicate that user-generated content has a significant impact on the formation of destination image, attractiveness of travel locations, and the final choice of travelers. The main findings of the thesis demonstrate that user-generated content strengthens the emotional connection of potential tourists with a travel destination, increases their confidence in the chosen destination, and reduces information uncertainty. Furthermore, user-generated content provides authentic information, often perceived as more trustworthy than traditional marketing communication. It also encourages social engagement among users and increases their willingness to participate in travel-related communities. In summary, this thesis contributes to the understanding of how user-generated content shapes travel choices and offers practical recommendations for tourism marketing professionals on effectively leveraging user-generated content to promote travel. Additionally, the study highlights the importance of user-generated content in shaping destination image and emphasizes the need to integrate this content into modern tourism marketing strategies
The impact of stereotypical and non-stereotypical anthropomorphism of chatbots on users' responses in emotionally charged situations.
No full textNowadays, organizations are widely using anthropomorphized chatbots, which imitate human behavior, emotions, or feelings (Costa & Ribas, 2019). The anthropomorphism of chatbots is increasingly becoming a subject of scientific research, but there is a noticeable lack of research analyzing the impact of stereotypes on user responses and research of this interaction in emotionally charged situations. Users tend to attribute more community-reflecting qualities to chatbots with feminine appearance, such as warmth (Borau et al., 2021), empathy, and friendliness (Stroessner et al., 2019), and perceive them as more humanlike (Borau et al., 2021) and soothing users' negative emotions (Liang et al., 2023). However, users tend to trust male chatbots more and share information with them more freely (Behrens et al. 2018; and Law et al. 2020). In this paper, Fiske’s (1999) stereotype content model is used as a theoretical basis to analyze users’ responses to stereotypical anthropomorphism in chatbots. The model identifies two main dimensions: warmth and competence, which can be used to classify people’s stereotypical beliefs about other individuals and user responses (Halkias and Diamantopoulos, 2020; Bastiansen et al., 2022). The aim of this study is to empirically test the hypothesized relationships between the effects of stereotypical and non-stereotypical anthropomorphism in chatbots on users’ responses in emotionally stressful situations. The study revealed that stereotypical anthropomorphism does not have a greater positive impact on user responses, expressed in trust, perceived helpfulness of chatbots, and intentions to use the chatbot in the future. According to the findings of this study, interactions with stereotypically anthropomorphized chatbots (female exhibiting warmth and male exhibiting competence) did not lead to higher perceived self-congruence between user’s and chatbot’s personalities compared to interactions with non-stereotypically anthropomorphized chatbots. Study also revealed that the perceived self-congruence between user’s and chatbot’s personalities has a positive impact on user responses, expressed in trust, perceived helpfulness of chatbots, and intentions to use chatbot in the future. In addition, it was found that competence traits in the verbal expression of the anthropomorphized chatbot are more positively associated with trust than warmth traits, and there is a more positive relationship between the competence, used in the verbal expression of the chatbot and the intention to use chatbots in the future, than between warmth in the verbal expression and the aforementioned response element of the chatbots. Also, based on the obtained results, warmth traits in the verbal expression of the anthropomorphized chatbot did not have a more positive association with the perceived helpfulness of the chatbot than competence traits
Interpretation of galvanic series when teaching metal corrosion /
No full textThe article discusses the knowledge of students in metal corrosion. Usually, resistance of metals against corrosion is determined by the values of the standard electromotive force (EMF) of the metals determined versus the standard hydrogen electrode (SHE). However, the standard conditions differ from the real-world conditions under which metal corrosion occurs, so the standard EMF cannot be accepted as an absolute indication of metal's resistance to corrosion. This difference is due to many environmental factors (e.g., temperature, pH, pressure, concentrations of hydrogen and oxygen in the environment etc.); thus, the value of metal potential is affected. Therefore, the authors have suggested using stationary (corrosion) potentials of metals and galvanic series instead of the standard EMF in the education process. In the article, the authors present a comparison of metal activity series based on standard EMF and galvanic series. The advantage of the galvanic series offered to students studying corrosion is illustrated by the problematic tasks for light metals (Ti, Mg, and Al) and corrosion galvanic cells. Based on the presented values of the metal potentials in the galvanic series, students were able to correctly choose the type of metal coating, they can calculate the EMF values of the corrosion process more accurate and verify them experimentally during the laboratory session
