In the era of Industry 4.0, service robot path planning has emerged as a pivotal element in the optimization of logistic tasks within manufacturing, warehousing and service applications. In this context, the adoption of advanced path planning algorithms, such as the Grey Wolf Optimizer (GWO) swarm algorithm, play a key role in enabling these robots to navigate through complex environments with precision and agility. Harnessing the power of bio-inspired algorithms, our framework establishes a methodical and effective approach to the intricate task of service robot path planning.

Denial of Service (DoS) attacks, particularly the distributed variant known as DDoS, are easily initiated but pose significant challenge in terms of mitigation, especially in the case of DDoS. These attacks involve the use of a vast number of packets, often generated by specialized programs and scripts, crafted for specific attack types like SYN flood, ICMP Smurf, and similar. Malicious DoS packets share similar attributes, such as packet length, interval time, destination port, TCP flags, and the number of connections to the same host or service. To rapidly identify anomalous packets amidst legitimate traffic, we propose a system that incorporates the Newcombe-Benford power law and Kolmogorov-Smirnov test. This approach enables the detection of matching first occurrences of leading digits, such as packet size indicating the use of automated scripts for malicious purposes, and the count of connections to the same host or service.

Power system stability plays a significant role in the overall power system analysis. With the high penetration level of distributed generation (DG), especially large-scale wind farms, this problem needs to be addressed. This study investigates the system stability in case of a wind park (WP) integration using doubly fed induction generators (DFIGs) to transmission grid, while focusing on WP fault ride-through ability. The system was modelled for time-domain simulations. The results indicate that WP parallel operation with the high voltage network is possible if specific conditions are met, with fault clearance time being crucial. This is shown through scenarios, in which each of the overhead lines (OHL) was disconnected due to three-phase short circuit symmetrical fault, and the network parameters were observed for each case. The predefined control and protection configurations in the DFIG-based wind farm model simplify the analysis. The introduction of a battery energy storage system (BESS) with P and Q control strategies, improves WP stability during faults. Professional software tools, PSSE, and EMTP-RV, were employed for the analysis. The study showed that simulated WP and BESS connected to a real network, paired with appropriate fault clearance time and protection settings, can operate effectively while maintaining overall system stability. This research is significant for power system planning, especially with the growing integration of large-scale wind generation.

With the development of new technologies, next-generation mobile networks have brought new services with strict performance and security requirements. One promising solution that can ensure the highest possible level of security is quantum key distribution (QKD). This technology provides information-theoretical security using the principles of quantum physics. This paper presents an extended analysis of one implementation of the QKD key delivery protocol defined in the ETSI GS QKD 014 standard, considering a multi-user environment. We propose an empirically derived model of key delivery latency in such an environment based on regression analysis of experimental results. Using the proposed model, we estimate the limitations of the implemented solution in terms of maximum number of simultaneous users connected to one key management server, considering several applications in 5G/6G networks.

Professional football players often need legal help in managing disputes with football clubs. The Professional Football Players Syndicate of Bosnia and Herzegovina is an organization founded with this purpose. Due to an increasing need for legal help and a large number of cases, their legal associates need systematic management of data. This work presents the first information system entirely intended for the usage by sports law professionals. It contains a desktop application where legal disputes are shown in the form of an organized dispute table. Real-time information about football players is acquired by using the TransferMarkt web API. The system was successfully used for two years, resulting in 103 documented cases involving 87 players and 31 clubs. As a result, 69.90% of disputes were archived and 43.69% of disputes resulted in agreements, indicating that the productivity of legal associates and the mediator role of the Syndicate were improved.

Procedural modeling is used to generate virtual content in organized layouts of exterior and interior elements. There is a large number of existing layout generation methods, and newer approaches propose the generation of multiple layout types within the same generation session. This introduces additional constraints when manually created layout elements need to be combined with the automatically generated content. Existing approaches are either designed to work with existing elements for a single layout type, or require a high amount of manual work for adding existing elements within multiple layouts. This paper presents a method that enables the application of existing subdivision methods on multiple layout types by inserting existing content into the generation result. This method can generate test cases by creating variations of partially generated layouts for procedural modeling methods that can work with existing content.

Clustering users on social media based on text involves grouping individuals with similar text patterns, language usage, or content interests. This text-based clustering provides insights into user preferences, enables personalized content recommendations, and facilitates understanding of social networking trends and user engagement. However, traditional text clustering methods rely heavily on language-specific features. This limits their applicability in multilingual media environments where linguistic diversity prevails. In this paper, the problem of clustering users on social networks, specifically focusing on text-based clustering independent of the language in which the text is written, is addressed. A practical methodology is presented, outlining an iterative procedure for clustering based solely on language-independent features such as emojis, hashtags, URLs, text length, and punctuation count. The effectiveness of the language-independent clustering approach is compared with the usual text based clustering approach. Comparison of these results shows that for the used dataset, the proposed clustering method using language independent features gives higher quality results than text clustering.

In research aimed at determining the level of interest of high school students in enrolling in colleges, predictive analysis models and comparisons are rarely applied during the classification and processing of various data. All of this leads to significant fluctuations in college admissions, where certain schools are unable to admit a large number of students who show interest in a specific field. On the other hand, high school students lose interest in certain schools, leading to the discontinuation of specific directions essential for today's job market needs. Institutions largely fail to conduct a comparison and linkage of teaching and non-teaching activities when analyzing the talents and interests of high school students from different fields. The goal of this paper is to use programming language classifiers to predict student enrollments in colleges based on the results students demonstrate during regular attendance in high schools through participation in innovation fairs.

Next-generation mobile networks, such as 5G/6G, have envisioned the possibility of direct communication between user devices, known as Device-to-Device (D2D) communication. Given that in D2D networks, traffic is transmitted ad-hoc from device to device, the range and quality of service are directly dependent on the number of nodes forming the D2D network. Therefore, we need to incentivize users to participate in the network operation through appropriate compensation for the provided resources and work done. A D2D network formed this way is inherently decentralized, making blockchain the primary choice as a technology. In this paper, we propose a new blockchain-based protocol for active tracing of IP traffic via in-band network telemetry. The experiment demonstrates that the proposed protocol can record all nodes participating in traffic forwarding in the D2D network through active traffic monitoring. Blockchain-based microtransactions can use participation records provided by our protocol to incentivize users to expand and strengthen the D2D network.

The applications presented in this conference paper focus on the development of a mobile and web application serving as a planner with a focus on tracking persons with Down syndrome. These innovative technological solutions contribute to the development of independence and functionality for persons with Down syndrome while emphasizing the importance of inclusivity in society. In addition to focusing on organizing activities, the mobile and web applications provide support and facilitate daily tasks. The web application allows parents/guardians/teachers to add new activities to the planner and track the progress of these activities. On the other hand, the mobile application enables persons with Down syndrome to record their activities within the application, considering their specific challenges, and customizing the user interface to their needs.

Software development is implemented in several key phases, one of which is software testing. Software testing consists of selecting techniques for the purpose of finding software defects and bugs in the process of writing code. There are several ways and approaches that lead us to that purpose, with the goal of selecting the most adequate method in terms of cost, complexity, and efficiency. In this paper, we will take a deeper dive into mutation testing techniques. Mutation testing techniques are fault-based and focus more on test structures than the input data, which is considered the testing start point. The basic concept of mutation testing consists of a few steps, which will be covered in this paper, and metrics that measure how effective the tests really are. With a few code examples, we will show why code coverage, which is mostly taken as a measure while testing, is sometimes not the most reliable source and does not give a full picture when talking about the quality of written tests.

Embedded real-time clock systems have a large number of applications in practice. The main issue is the accuracy of time they show, which is why performing time synchronization is very important for their usability and reliability. This paper proposes an embedded real-time analogue clock that uses an AdaFruit NeoPixel LED ring for visualizing current time. Three different colors are used for showing hour, minute and second values, whereas different levels of brightness are used for describing accurate values of time to the level of milliseconds. An Ethernet LAN module is used for performing time synchronization via a remote NTP server. Dynamic synchronization interval change is used for removing the effect of the microcontroller clock error on the accuracy of the shown time. After being put to use, the system was able to perform multiple functions successfully, including the conveying of information to the user when the clock is out of sync.

This research delves into the crucial role of solar energy, particularly photovoltaic (PV) conversion, in the global shift towards renewable sources. Focusing on the stochastic nature of PV power plants, the study emphasizes fault ride-through operations and their repercussions on electrical power systems. A detailed modeling approach is employed using Electromagnetic Transient Program (EMTP) software to simulate a large-scale PV power plant connected to a high-voltage transmission network. The analysis encompasses various fault scenarios, shedding light on the resilience of PV systems and their broader impacts during faults. This investigation enhances the understanding of PV dynamics in fault conditions, providing valuable insights for sustainable energy systems.

This article aims to show the potential contribution of high-yielding rice varieties to achieve sustainable intensification in paddy farming, by focusing on a developing country. A comparative life cycle assessment of traditional vs. high-yielding varieties is carried out by comparing the area-based and yield-based results. Primary data are collected through a farm survey (49 farms in the Mazandaran province, Iran; spring 2018). The results highlight that high-yielding varieties can reduce the yield-scaled impacts. However, area-scaled impacts are subject to increase for most impact categories. Statistically significant trade-offs involve global warming potential (+13% per ha and −28% per t in high-yielding varieties) and fossil resource depletion (+15% per ha and −26% per t in high-yielding varieties). Pesticide management is the most alarming practice. High-yielding varieties increase pesticide consumption and related toxicity impacts both per t and per ha. This study is a new contribution to the literature by improving and broadening the mainstream productivity perspective of current life cycle assessment research about crop varieties. The lessons learnt from this study suggest that the trade-offs between yield-scaled and area-scaled impacts should be carefully considered by decision-makers and policymakers, especially in developing countries that, like Iran, are affected by the overexploitation of natural resources. Targeted policy and the development of farmer education and advisory services are needed to create the enabling conditions for farm management changes, including conscious use of production inputs while avoiding heuristics.

This paper describes a new smartphone-based colorimetric method for the determination of N-acetyl-L-cysteine and glutathione using a reaction with the Cu(II)–neocuproine complex. The reaction resulted in the formation of a yellow Cu(I)–neocuproine complex. Reaction solutions, prepared according to the selected optimal conditions, are placed in front of a light blue background, and a smartphone camera is used for digital image acquisition. The intensity of the blue RGB canal was selected for analytical response and determined using the free Color Grab mobile app. Also, absorbance at a wavelength of 450 nm was measured for all reaction solutions using a UV–Vis spectrophotometer. The proposed procedures allow the determination of both thiols in the linear dynamic range from 3.0 × 10–6 to 2.0 × 10–4 mol L−1 for a spectrophotometer as a detector, or from 6.0 × 10–6 to 2.0 × 10–4 mol L−1 for a smartphone as a detector. The obtained results indicate that the proposed method is accurate, simple, cost-effective, and applicable to the determination of thiols in pharmaceuticals.