Kaunas University of Applied Engineering Sciences

Gypsum building materials are widely used in the construction sector and their use is growing steadily. At the end of the life cycle of a building, these gypsum materials become demolition waste. Thus, the increased consumption of gypsum building materials leads to an increased amount of demolition waste. The recycling of such demolition waste is becoming more and more relevant and important, as the recycling of gypsum waste would save natural raw materials and reduce waste. The main objective of this study was to investigate the effect of waste cellulose fibers on the physical and mechanical properties of gypsum samples. First of all, gypsum waste board was shredded and the cellulose separated from the gypsum. The gypsum particles were then ground in a ball mill to a fine powder. Calcination was carried out at 160 °C for 1,50 hours of 1 kg of gypsum. Citric acid was used as a set retarder and the amount was 0,05 wt. % by weight of the gypsum powder. The amount of waste cellulose fibers was 1, 3, 5 and 10 wt. % and as reference sample used gypsum sample without cellulose. The density, flexural and compressive strength were determined for all the samples. The microstructure was assessed by optical microscopy and the acoustic insulation properties were determined. The results showed that it is possible to obtain 5,75 MPa of compressive strength and 1,2 MPa of flexural strength by including 3 and 5 wt. % of waste cellulose fibers. The results of the sound insulation performance of gypsum composites with different amounts of waste cellulose fibers show that the highest levels of sound insulation were achieved when the composite contained 3 % and 5 % by weight of waste cellulose fibers. The findings of the study indicate that the utilization of recycled gypsum can yield environmental benefits when compared with the use of natural gypsum.

Addressing climate change necessitates coordinated efforts across multiple sectors, with agriculture representing a significant source of greenhouse gas (GHG) emissions. This requires sophisticated mitigation strategies at the farm level. Digital decision support tools (DSTs) tailored for this purpose play a crucial role in accelerating farm-level decarbonization. Ensuring the reliability and accuracy of these DSTs mandates thorough model robustness validation. This study validates a farm-level GHG accounting and decarbonization DST using Sobol and Morris global sensitivity analyses to evaluate output robustness and to identify key input parameters critical for reliable mitigation planning. Both sensitivity analysis methods provide a comprehensive assessment of the tool’s robustness and highlight parameters most influencing farm-level GHG emission outcomes. Results show consistent outcomes across sensitivity approaches, reinforcing confidence in the tool’s application for emission reduction planning. The sensitivity analysis results indicate that the tool delivers reliable outcomes across various sensitivity analysis methods, thereby enhancing confidence in its suitability for decarbonization planning. Furthermore, the findings of this study provide a methodological foundation for future advancements and expanded use within the agriculture sector. This supports the DST’s effectiveness in prioritizing mitigation strategies and planning emission reduction pathways at the farm scale, while providing a transparent template to guide future tool improvements and broader agricultural applications.

The global deployment of over seven billion IoT measuring devices in critical fields like healthcare and industrial safety systems exposes a pressing vulnerability to cyber-attacks, where compromised data integrity can lead to severe financial or life-threatening incidents. Calibration is the fundamental process ensuring measurement uniformity, yet the immense scale of the IoT makes traditional laboratory calibration physically impossible. Consequently, the calibration process must migrate on-site, relying on remote communication with calibration standards—a paradigm known as Calibration as a Service (CaaS). This digital shift, however, introduces significant cybersecurity risks into the very foundation of measurement trust. This paper addresses this critical challenge by presenting a comprehensive Standard Operating Procedure (SOP) for Secure IoT Measuring System Calibration. The proposed framework establishes the necessary protocols to protect the calibration process within a CaaS infrastructure. We further emphasize that the development and deployment of such secure IoT systems necessitate dedicated collaboration between IT security specialists and domain experts, ensuring that device integrity is prioritized from inception to safeguard end-users in an increasingly connected and vulnerable digital ecosystem.

ABSTRACT Accurate extraction of individual urban objects from aerial LiDAR point clouds presents a complex challenge due to the heterogeneity of object types, occlusions, and overlapping geometries. This research paper introduces a hybrid framework that combines deep learning and geometric algorithms for the detection and classification of both structured and unstructured urban objects within LiDAR point clouds, supported by auxiliary RGB and satellite data. The methodology incorporates a multistage pipeline: initial point cloud classification using neural architectures such as RandLANet and PointPillars, followed by semantic segmentation using YOLOv7, YOLOv11, and SegFormer, and refined object extraction using rule-based and geometric filtering (e.g. DBSCAN, RANSAC). A data set of over 3.1 billion classified points, derived from Estonian LiDAR and OSM data, was prepared and augmented to address the detection of small and overlapping objects. Experimental results demonstrate high accuracy for structured classes (e.g. buildings: 88.3%) and effective segmentation of unstructured objects (e.g. trees: 85.0%). Cascaded networks achieved up to 72.6% classification accuracy depending on neighbourhood size. The 9-channel data fusion (RGB + LiDAR features) significantly improved segmentation performance. Comparative evaluation shows that combining model specialization with rule-based metaclass grouping improves object detection granularity and classification consistency, providing a scalable approach to fine-grained object recognition in smart city and geospatial analysis applications.

The emergence of new services requires a lot of effort, and most of all, creativity. The business longs for innovation in all fields, including the agricultural business. Moreover, the development of sustainable services in agriculture is even more important to enable a response to climate change, meet customers' demands for ecology, and comply with government regulations for sustainable farming. There is no specific model for organizing the idea generation process for modeling sustainable services, or the existing models do not fully satisfy the businesses looking for the idea generation guidelines in sustainable farming. Therefore, all these factors underscore the need for a specific model to develop sustainable services in agriculture. Based on research on designing sustainable services, the modelling process of idea generation, and the model of the idea generation process for designing sustainable services in the agricultural sector was developed and presented in this article. The article explains the process of creating a model in the field of sustainability and conducts research on its implementation involving companies operating in the sustainable agriculture sector. The steps of the model application are explained in detail. As the study shows, the model of the idea generation process can be widely used not only for modeling sustainable services in agriculture, but also in a broad spectrum of service design.

A study explores the mathematical knowledge embedded in the daily practices of the Kewrat community of Nepal. Employing an ethnography research design, with aims to identify the traditional counting, measurement, and geometrical concepts used by the Kewrat people and their potential pedagogical applications. The information from respondents selected with purpose sampling of 5 - elderly community members, 2 - native school teachers, 10 – students from Kewrat family and their parents with interview, observation and photographs, shows that that mathematical practices in the Kewrat culture is based on counting, measuring, arithmetic operations and geometrical principles. The study found that “ganda," "vira," "vanja," and "skori” are used in counting, fingers and hands are used for arithmetic operations, indigenous measurement tools are "dandi" for weight, “lota" and "kat-tha" for volume, and "bitta" and "haat" for measuring length and calculating area. Kewrat people also demonstrate a practical understanding of geometrical concepts, such as cones, cylinders, and prisms, applied in crafting tools for daily uses. These findings highlight the richness of cultural mathematics and its relevance to formal education. This study suggests incorporating these traditional practices into mathematics classrooms to enhance student engagement, promote hands-on learning, and connect cultural knowledge with academic concepts.

The structural, electronic and elastic properties of LiBeF3 under high pressure were investigated using the density functional theory. The optimized lattice constant and the bulk modulus of elasticity at 0 GPa were obtained as 3.500 Å and 104.79 GPa, respectively, which are in good agreement with the previously available results. To study the effect of pressure, variable-cell relaxation (vc-relax) calculations were performed at different pressures ranging from 0 to 50 GPa. The mechanical properties of LiBeF3 reveal that it is mechanically stable at the chosen pressures of 0, 10, 20, 30, 40 and 50 GPa. The Pugh’s ratio and Poisson’s ratio for LiBeF3 were consistent throughout the increase in pressure, suggesting the brittle nature and dominance of ionic bonding in LiBeF3. The electronic band gap of LiBeF3 at 0 GPa was found to be 7.46 eV with indirect nature. On further increasing the pressure, the band gap of the LiBeF3 crystal increased while maintaining its indirect nature. The Young’s modulus, shear modulus and anisotropy factor of LiBeF3 were also investigated and presented in this paper.

In this paper, a two-dimensional nonlinear elliptic equation with an integral boundary condition depending on two parameters is investigated. The problem is solved using the finite difference method. The error in the solution is evaluated based on the properties of M-matrices, and herewith the convergence of the difference scheme is proved. The majorant is constructed to estimate the error of the solution of the system of difference equations.

Abstract This article examines demographic shifts and changing housing needs in Latvia, with a focus on their implications for social housing policy. Latvia faces significant demographic challenges, including population decline, rapid ageing, and changing household structures. The study analyses historical trends in population, age structure, household composition, and migration patterns based on data from the Latvian Central Statistical Bureau and Eurostat. It also assesses the current housing landscape, including characteristics of housing stocks, homeownership rates, rental market dynamics, and social housing provision. The research reveals a growing mismatch between the existing housing stock and evolving needs, particularly for smaller, accessible units suitable for an ageing population. Based on these findings, the article proposes policy recommendations to address Latvia’s evolving housing needs. These include short-term adjustments to current policies, long-term strategic planning for housing development, and innovative financing mechanisms for social housing. The study also explores potential challenges in implementing these recommendations, such as funding restrictions and political acceptance. By aligning housing policy with demographic realities, Latvia can better meet the needs of its changing population and enhance the overall quality of life of its citizens. This research contributes to a better understanding of the adaptation of housing policy adaptation in the context of significant demographic change.