Iskanje po katalogu digitalne knjižnice

Opis: Crop inspection plays a significant role in modern agricultural practices as it enables farmers to evaluate the condition of their fields and make informed decisions regarding crop management. However, existing methods of crop inspection are often labor-intensive, leading to slow and costly processes. Therefore, there is a pressing need for more efficient and cost-effective approaches to crop inspection to improve agricultural productivity, sustainability, and to deal with labor shortage. In this study, we present Rockerbot, a novel agricultural robot designed as a compact rover capable of navigating and surveying maize fields in their early growth stages. This technology is essential for timely landscape adjustments to ensure optimal crop production. The document offers a comprehensive review of the decisions made during the hardware and software development stages. The hardware section is centered around design choices influenced by the rover’s kinematics, while the software section outlines the tasks that Rockerbot can perform using mobile perception, such as mapping, sensing, and detection.
Ključne besede: agricultural robotics, smart agriculture, autonomous navigation, watering, mapping
Objavljeno v DKUM: 23.04.2025; Ogledov: 0; Prenosov: 0
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Opis: Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time. Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. Feature extraction was performed using Tsfresh and ROCKET, which allowed us to capture the patterns in the motor current data corresponding to the geometric features of the machined parts. Our predictive models were trained and validated on a dataset that included motor current readings and corresponding geometric measurements of a mounting rail later used in an engine block. The results showed that the proposed approach enabled the prediction of three geometric features of the mounting rail with an accuracy (MAPE) below 0.61% during the learning phase and 0.64% during the testing phase. These results suggest that our method could reduce the need for post-machining inspections and measurements, thereby reducing production time and costs while maintaining required quality standards
Ključne besede: smart production machines, data-driven manufacturing, machine learning algorithms, CNC controller data, geometrical accuracy
Objavljeno v DKUM: 10.03.2025; Ogledov: 0; Prenosov: 6
Celotno besedilo (4,44 MB)
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Opis: Step by step, new digital technologies are capturing different spheres of our life. The opportunities of their application are almost infinite, and potential is very promising. But digital innovations as a trend represent a challenge for every modern state. Especially for member-countries of the BRICS union who seek to become the world's leading countries. For this reason, the most important task for the members of BRICS is to create adequate "smart" regulation, which offers alternative ways of regulatory impact on transforming business relations. Using the regulatory sandbox as an experimental legal regime is one of the ways to test the creation, production, and realization of digital innovation. Having been first applied in 2016 in the United Kingdom, nowadays this model is successfully implemented in such countries as Singapore, Australia, and the United Arab Emirates. Member-countries of BRICS are only beginning to adopt this unorthodox tool; in most of its countries the legal framework is ongoing now. The aim of this research is to analyze current legislation and legal framework on the regulatory sandboxes in BRICS countries, define features of national models, difficulties and further prospects of its usage. This research is based on the comparative and formal juridical analysis of legislation, draft laws, and research papers dedicated to regulatory sandboxes in BRICS. The authors identify different barriers and risks of using regulatory sandboxes for the digital innovations successfully and offer some ways to overcome these challenges, including the formulation of guidelines for operating regulatory sandboxes based on a balance of public and private interests. The authors conclude that it is necessary to update legislation on the regulatory sandboxes for reaching positive effect from the digital transformation and make several suggestions for optimization its provisions. The results achieved in research paper can be used both in the lawmaking process as well as the foundation for further scientific researches.
Ključne besede: regulatory sandboxes, experimental legal regime, smart regulation, digital economy, innovations
Objavljeno v DKUM: 23.01.2025; Ogledov: 0; Prenosov: 8
Celotno besedilo (1,01 MB)
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Opis: This dissertation introduces a novel off-chain channel model aimed at enhancing existing solutions to address scalability challenges in blockchain technology. It begins with an overview of the problem statement, research objectives, methodology, and potential limitations before establishing a thesis and hypotheses. A comprehensive theoretical background on blockchain technology, scalability solutions, and the off-chain channel approach ensures a common understanding of the topic. To provide a thorough overview of existing off-chain channel solutions and identify and categorize their limitations, we conducted a systematic literature review, identifying 65 relevant studies. Through detailed analysis, six categories of solutions and six implemented off-chain channel solutions were identified. Five primary categories of limitations were also identified: routing, flexibility, privacy, network properties, and online assumptions, some with sub-limitations. To address these limitations, a new off-chain channel model, named ”Off-chain Channel as a Service,” is proposed, featuring four core design decisions: eliminating the need for an off-chain channel network, assuming blockchain properties by design, introducing a trustworthy service, and enabling flexibility by design. Validation and evaluation of the proposed model employ case-study and experiment research methods to confirm compliance with off-chain channel principles, validate it against identified limitations of existing solutions, analyze its impact on blockchain scalability, and assess its applicability across blockchain platforms. For this purpose, two off-chain payment channel prototype solutions have been implemented, each using a different underlying blockchain platform, namely Ethereum and Solana. Moreover, the proposed model’s security evaluation using risk-analysis methodology is also provided. Qualitative and quantitative analysis demonstrates that the proposed off-chain channel model adheres to off-chain channel principles, improves most identified limitations of existing solutions, positively impacts blockchain scalability, and can be applied to different blockchain platforms supported by smart contracts.
Ključne besede: blockchain, distributed ledger technology, smart contracts, scalability, off-chain channel, payment channel
Objavljeno v DKUM: 01.10.2024; Ogledov: 0; Prenosov: 55
Celotno besedilo (3,87 MB)

Opis: Vision picking empowers users with access to real-time digital order information, while freeing them from handheld radio frequency devices. The smart glasses, as an example of vision picking enabler, provide visual and voice cues to guide order pickers. The glasses mostly also have installed navigation features that can sense the order picker's position in the warehouse. This paper explores picking errors in vision systems with literature review and experimental work in laboratory environment. The results show the effectiveness of applying vision picking systems for the purposes of active error prevention, when they are compared to established methods, such as paper-picking and using cart mounted displays. A serious competitor to vision picking systems are pick-to-light systems. The strong advantage of vision picking system is that most of the errors are detected early in the process and not at the customer's site. The cost of fixing the error is thus minimal. Most errors consequently directly influence order picker's productivity in negative sense. Nonetheless, the distinctive feature of the system is extremely efficient error detection.
Ključne besede: order picking, storage operations, warehousing, smart glasses, error prevention, inventory management, intralogistics
Objavljeno v DKUM: 22.08.2024; Ogledov: 83; Prenosov: 4
Celotno besedilo (672,66 KB)
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