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Found 6341 publications

Trademark protection for faces? A comprehensive analysis on the benefits and drawbacks of trademarks and the right to facial image

Barna Arnold Keserű

Publication Name: Journal of Intellectual Property Information Technology and E Commerce Law

Publication Date: 2024-06-01

Volume: 15

Issue: 1

Page Range: 88-99

Description:

The purpose of this paper is to present a comprehensive framework for the possibility of trademark protection for human faces. In the case law of the European Union Intellectual Property Office there are a few examples of trademarks, which consist of only photorealistic human faces. Private law protects the use of images; however, the trends of recent years demonstrate that trademarks could also have a role in such protection. The author aims to analyze the similarities and differences between trademark protection and personality rights in order to determine whether trademarks for faces are necessary or not. The over- arching analysis compares twelve aspects of the two ways in which the legal systems protect facial imagery, highlighting their various advantages and drawbacks. The comparison includes the following attributes: function of protection, scope of protection, territorial dimensions of protection, temporal dimensions of protection, conditions of protection, content of protection, limitations and exceptions, transferability of rights, enforcement of rights, requirement of use, termination of rights and costs.

Open Access: Yes

DOI: DOI not available

Weed Detection and Classification with Computer Vision Using a Limited Image Dataset

Gergely Teschner László Moldvai Péter Ákos Mesterházi A. Nyéki

Publication Name: Applied Sciences Switzerland

Publication Date: 2024-06-01

Volume: 14

Issue: 11

Page Range: Unknown

Description:

In agriculture, as precision farming increasingly employs robots to monitor crops, the use of weeding and harvesting robots is expanding the need for computer vision. Currently, most researchers and companies address these computer vision tasks with CNN-based deep learning. This technology requires large datasets of plant and weed images labeled by experts, as well as substantial computational resources. However, traditional feature-based approaches to computer vision can extract meaningful parameters and achieve comparably good classification results with only a tenth of the dataset size. This study presents these methods and seeks to determine the minimum number of training images required to achieve reliable classification. We tested the classification results with 5, 10, 20, 40, 80, and 160 images per weed type in a four-class classification system. We extracted shape features, distance transformation features, color histograms, and texture features. Each type of feature was tested individually and in various combinations to determine the best results. Using six types of classifiers, we achieved a 94.56% recall rate with 160 images per weed. Better results were obtained with more training images and a greater variety of features.

Open Access: Yes

DOI: 10.3390/app14114839

Numerical Study of the Ultimate Bearing Capacity of Two Adjacent Rough Strip Footings on Granular Soil: Effects of Rotational and Horizontal Constraints of Footings

Mojtaba Lezgy-Nazargah Majid Movahedi Rad Vahid Shafaie Mahdi Salari

Publication Name: Buildings

Publication Date: 2024-06-01

Volume: 14

Issue: 6

Page Range: Unknown

Description:

In this paper, the numerical study of the ultimate bearing capacity (UBC) of two closely spaced strip footings on granular soil is investigated using the finite element method (FEM) and upper bound limit analysis (UBLA). Although the UBC of two adjacent footings has previously been studied in other experimental and numerical research, in all the previously reported studies, the footings were not allowed to rotate and move horizontally freely. Due to the deformation of the soil medium, two closely spaced footings are subjected to horizontal movements and tilting, even under central vertical loads. When the two adjacent footings are not permitted to rotate and move in the horizontal directions, the unwanted bending moment and horizontal force act on the footings. Indeed, the UBC of two closely spaced rough footings is evaluated under incorrect constraints in earlier research. In the present research, the UBC of two adjacent rough footings is evaluated with and without these incorrect constraints. The key finding of this study is that constraining the horizontal and rotational movement of the foundation artificially increases the UBC, which does not reflect field conditions. When foundations are permitted to rotate and move horizontally, there is no increase in UBC; however, there is an increased risk of differential settlement and structural instability.

Open Access: Yes

DOI: 10.3390/buildings14061653

Analyzing Barriers to Internet of Things (IoT) Adoption in Humanitarian Logistics: An ISM–DEMATEL Approach

Imen Zrelli Abderahman Rejeb Karim Rejeb

Publication Name: Logistics

Publication Date: 2024-06-01

Volume: 8

Issue: 2

Page Range: Unknown

Description:

Background: Effective humanitarian logistics (HL) is essential in disaster response. The “Internet of Things” (IoT) holds potential to enhance the efficiency and efficacy of HL, yet adoption is slowed by numerous barriers. Methods: This study employs interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) to explore and classify barriers to IoT integration in HL. Results: A total of 12 barriers were identified, classified, and ranked according to their driving power and dependence. Key barriers include lack of standardization, organizational resistance, data quality issues, and legal challenges. Conclusions: Overcoming these barriers could significantly improve relief operations, reduce errors, and enhance decision-making processes in HL. This investigation is the first of its kind into IoT barriers in HL, laying the groundwork for further research and providing valuable insights for HL managers.

Open Access: Yes

DOI: 10.3390/logistics8020038

Improving Autonomous Vehicle Perception through Evaluating LiDAR Capabilities and Handheld Retroreflectivity Assessments

Csaba Koren Ziyad N. Aldoski

Publication Name: Sensors

Publication Date: 2024-06-01

Volume: 24

Issue: 11

Page Range: Unknown

Description:

Road safety is a serious concern worldwide, and traffic signs play a critical role in confirming road safety, particularly in the context of AVs. Therefore, there is a need for ongoing advancements in traffic sign evaluation methodologies. This paper comprehensively analyzes the relationship between traffic sign retroreflectivity and LiDAR intensity to enhance visibility and communication on road networks. Using Python 3.10 programming and statistical techniques, we thoroughly analyzed handheld retroreflectivity coefficients alongside LiDAR intensity data from two LiDAR configurations: 2LRLiDAR and 1CLiDAR systems. The study focused specifically on RA1 and RA2 traffic sign classes, exploring correlations between retroreflectivity and intensity and identifying factors that may impact their performance. Our findings reveal variations in retroreflectivity compliance rates among different sign categories and color compositions, emphasizing the necessity for targeted interventions in sign design and production processes. Additionally, we observed distinct patterns in LiDAR intensity distributions, indicating the potential of LiDAR technology for assessing sign visibility. However, the limited correlations between retroreflectivity and LiDAR intensity underscore the need for further investigation and standardization efforts. This study provides valuable insights into optimizing traffic sign effectiveness, ultimately contributing to improved road safety conditions.

Open Access: Yes

DOI: 10.3390/s24113304

Mapping the scholarly landscape of TikTok (Douyin): A bibliometric exploration of research topics and trends

Horst Treiblmaier Andrea Appolloni Mohammad Iranmanesh Abderahman Rejeb Karim Rejeb

Publication Name: Digital Business

Publication Date: 2024-06-01

Volume: 4

Issue: 1

Page Range: Unknown

Description:

The TikTok platform has become widely popular among younger generations and has influenced various industries and aspects of life. This systematic literature review, using bibliometric methods, aims to examine the evolution of TikTok research from its initial development to its current status. A total of 402 journal articles from 2019 to 2022 were systematically selected from the Web of Science Core Collection. Descriptive statistical analysis identified the most contributing academic institutions, nations, journals, scholars, and influential studies. Using CiteSpace, three visualization types were implemented: cluster views, timezone views, and timeline views. The study results indicate that several TikTok research clusters exist, which summarize important topics such as the platform's overall impact on society, politics, culture, as well as human-centric issues such as social attachment, functional tics, and their implications for public health. According to the co-word analysis, TikTok research revolves around body consciousness, social behavior, consumer behavior, and news media. The comprehensive mapping of TikTok research provides valuable insights into the current state of knowledge and identifies numerous relevant technical and social areas for future investigation. As the first bibliometric review of TikTok research, this study offers an important foundation for future scholarly inquiry in various areas.

Open Access: Yes

DOI: 10.1016/j.digbus.2024.100075

Effect of pH, Carbonate and Clay Content on Magnesium Measurement Methods on Hungarian Soils

Csaba Centeri Renato Kalocsai Márton Vona Zsolt Biró Viktoria Vona Tamás Szakál István Mihály Kulmány Sándor Zsebő Lajos Kubina Zsolt Giczi

Publication Name: Soil Systems

Publication Date: 2024-06-01

Volume: 8

Issue: 2

Page Range: Unknown

Description:

More exact information on soil nutrient management is crucial due to environmental protection, nature conservation, decreasing sources for mining, general precaution, etc. Soil magnesium (Mg) analytical methods of potassium chloride (KCl), Mehlich 3 (M3), water (WA) and cobalt hexamine (CoHex) extractions are compared with an elemental analysis and X-ray fluorescence (XRF) analysis. The ratio of the available to the total Mg content was calculated and compared on the whole dataset. The results showed that the linear regressions between all the pairs of Mg content measurement methods were significant. The linear relationship between the KCl and CoHex methods has the highest determination coefficient (R2 = 0.96), followed by WA–M3 (R2 = 0.68), M3–CoHex (R2 = 0.66) and M3–KCl (R2 = 0.60). The M3 solution demonstrated a greater capacity for extracting Mg from the soil. The second part is the analysis of the influence of CaCO3, pH, soil texture and clay content on the measurable magnesium content of soils. It was established that the extraction methods, the soil and the classification method of the soil properties affect the evaluation. These results may help through the nutrient replenishment and the melioration of soils. These results can help the examination of mineral nutrients, especially the Mg uptake.

Open Access: Yes

DOI: 10.3390/soilsystems8020049

Complex Building’s Decision Support Method Based on Fuzzy Signatures †

Adam Bukovics Ferenc Lilik László T. Kóczy

Publication Name: Buildings

Publication Date: 2024-06-01

Volume: 14

Issue: 6

Page Range: Unknown

Description:

In the inner areas of large cities, many residential buildings built at the turn of the 19th and 20th centuries remain standing. The maintenance and renovation of these buildings have emerged as critical priorities over recent decades. E.g., in Budapest during the socialist era, the majority of these buildings were not renovated, and maintenance was largely neglected. In the subsequent 10–15 years following the end of socialism, financial resources for renovations were scarce due to the extensive transfer of properties from state to private ownership. It is only in the last decade or so that renovations have begun to be systematically addressed. Consequently, a significant portion of the building stock is still pending renovation. Given the current economic conditions, sustainable maintenance and necessary conversion are of paramount importance. Unfortunately, few standardized condition assessment methods are implemented in industrial practice, and the literature on this topic is limited. To address these challenges, we have developed an algorithm and model for condition assessment and decision support, which we refer to as the Complex Building’s Decision Support System based on Fuzzy Signatures (CBDF system). Our model employs a fuzzy signature-based approach to account for uncertainties, errors, and potentially missing data that may arise during the assessment process. The primary aim of this model is to equip professionals involved in building condition assessment with a tool that enables them to make consistent and objective decisions while minimizing errors. This paper provides a brief overview of the CBDF system and presents test results from the assessment of a selected structural component of a building, demonstrating the system’s functionality.

Open Access: Yes

DOI: 10.3390/buildings14061630

Review of DC Motor Modeling and Linear Control: Theory with Laboratory Tests

Miklós Kuczmann

Publication Name: Electronics Switzerland

Publication Date: 2024-06-01

Volume: 13

Issue: 11

Page Range: Unknown

Description:

This review paper introduces the modeling, measurement, identification and control of direct current motors based on the state space modeling and the transfer function representation. These models are identified by real laboratory measurements, and the simulated results are compared with the measurements. Continuous-time and discrete-time PID (Proportional-Integral-Derivative) controllers, discrete-time state feedback and linear quadratic controllers are designed mathematically. The designed controllers are realized by the microcontroller Arduino UNO, and the behavior of the controllers is compared and analyzed. The noisy current signal has been measured by a discrete-time observer, steady-state Kalman filtering is also studied. The practical results of the implemented controllers support the theoretical results very well.

Open Access: Yes

DOI: 10.3390/electronics13112225