Issue Of Recognition Research Articles

National and foreign experience in determining the legal status of guardianship bodies

In the scientific article, the author conducted a scientific study of the peculiarities of the legal status of guardianship and guardianship bodies in Ukraine and other countries. On the basis of the conducted research, the author came to the conclusion that guardianship and guardianship bodies are distinguished by various authorities - local bodies of state executive power and local self-government bodies, separate departments of these bodies, services for children, which function under local state administrations and local councils, and as well as advisory and advisory support bodies. At the same time, the scientific literature notes the inexpediency of such a wide list of guardianship and guardianship bodies and the need to empower these bodies only with services for children. In the family law doctrine, there is no unanimity regarding the definition of the powers of the guardianship and guardianship authorities, which relate to the protection of the rights and legitimate interests of the child; they are contained in special legislation, which, however, does not fully correspond to each other and provides for the presence of a number of bodies that do not actually function or carry out activities formally, without having the appropriate competence (commissions for the protection of children's rights, departments of local state administrations), or at the same time function two bodies that are subordinate to each other (local state administrations and services for children). In the family law doctrine, there is no certainty in the issue of recognition of guardianship bodies and care by subjects of family relations; some scientists attribute them to the subjects of administrative-procedural relations or to the participants of legal relations of a complex nature, which are partly family, while others distinguish them as subjects of family relations. Analogues of guardianship and guardianship bodies in the states of the European Union and candidate states for EU membership are various types of bodies, including quasi-judicial ones, which perform both the functions of appointing, approving or dismissing a guardian, as well as supervising the observance of the rights of the child by its guardian (in France these functions are divided between the "family council” and the "guardianship judge”). Also, these bodies make decisions in family disputes regarding determining a child's surname, establishing his origin, his upbringing and maintenance.

Enhancing Fruit Fly Detection in Complex Backgrounds Using Transformer Architecture with Step Attention Mechanism

This study introduces a novel high-accuracy fruit fly detection model based on the Transformer structure, specifically aimed at addressing the unique challenges in fruit fly detection such as identification of small targets and accurate localization against complex backgrounds. By integrating a step attention mechanism and a cross-loss function, this model significantly enhances the recognition and localization of fruit flies within complex backgrounds, particularly improving the model’s effectiveness in handling small-sized targets and its adaptability under varying environmental conditions. Experimental results demonstrate that the model achieves a precision of 0.96, a recall rate of 0.95, an accuracy of 0.95, and an F1-score of 0.95 on the fruit fly detection task, significantly outperforming leading object detection models such as YOLOv8 and DETR. Specifically, this research delves into and optimizes for challenges faced in fruit fly detection, such as recognition issues under significant light variation, small target size, and complex backgrounds. Through ablation experiments comparing different data augmentation techniques and model configurations, the critical contributions of the step attention mechanism and cross-loss function to enhancing model performance under these complex conditions are further validated. These achievements not only highlight the innovativeness and effectiveness of the proposed method, but also provide robust technical support for solving practical fruit fly detection problems in real-world applications, paving new paths for future research in object detection technology.

Accurate detection and intelligent classification of solar cells defects based on photoluminescence images: A novel study on the optimized YOLOv5 model

In the production process of solar cells, inevitable faults such as cracks, dirt, dark spots, and scratches may occur, which could potentially impact the lifespan and power generation efficiency of solar cells. Addressing this issue, this paper combines neural networks with photoluminescence detection technology and proposes a novel neural network model for the classification and grading of defects in solar cells. Firstly, the YOLOv5 model is optimized and adjusted for algorithm and network structure. The optimization process is divided into three parts: global optimization of the network structure, optimization of the neck network structure, and optimization of the head structure, each addressing specific issues in recognition, detection, and classification. The impact of the optimized network model on recognition and detection speed is analyzed, and solutions are proposed to address any observed effects. Additionally, an iterative update of neural network hyperparameter combinations is performed for solar cell defect identification. Finally, using the ultimately optimized model structure in conjunction with the optimal hyperparameter combination, comparative experiments are conducted on neural networks for different target identification using the photoluminescence characteristics dataset of solar cells. The recognition improvement of the optimized model and its differences from other models are analyzed.

Symptom networks analysis among people with Meniere’s disease: Application for nursing care

ObjectivesThis study aimed to explore and visualize the relationships among multiple symptoms in patients with Meniere’s disease (MD) and aid clinical nurses in the design of accurate, individualized interventions. MethodsThis study included 790 patients with MD at the Eye and ENT Hospital of Fudan University from October 2014 to December 2021. A self-designed symptom checklist was used to assess 15 MD-related symptoms and construct contemporaneous networks with all 15 symptoms in R software. Qgraph package and Fruchterman-Reingold layout were used for network visualization. Bootstrapping methods were performed to assess network accuracy and stability, and three centrality indices were adopted to describe relationships among symptoms. ResultsSymptom networks showed good accuracy and stability. “Anxiety and nervousness”(98.2%), “aural fullness”(84.4%) and “tinnitus”(82.7%) were the common symptom in MD patients, while “tinnitus”, “aural fullness” and “decline in word recognition”, were more serious. MD patients with longer disease duration had higher prevalence and severity for all symptoms (P < 0.05). Symptom networks showed good accuracy and stability. “Decline in word recognition,” “fatigue,” and “anxiety and nervousness” were at the center of the symptom networks, which had the largest strength values and closeness. “Decline in word recognition,” “headache,” and “spatial discrimination and poor orientation” were the symptoms with the highest betweenness with the strongest bridging effect. The ≥1-year disease group exhibited higher centralities for “drop attack” and “anxiety and nervousness,” and a lower centrality for “headache” compared with the <1-year disease group. ConclusionsThe symptom networks of MD patients with varying disease durations were revealed. Clinicians and nurses must provide precision interventions tailored to modifying symptom severity and centrality. Nursing interventions should focus on word recognition issues and associated discomfort in MD patients with multiple symptoms.

Legal union of a same-sex couple in the Slovak Republic and the scope of recognition of such unions validly established abroad

The paper focuses on the issue of legal regulation of unions of same-sex couples under the conditions of the Slovak legal order. The author notes that within the Slovak Republic there is no equivalent of the institution of marriage for cohabiting persons of the same sex. It is further specified on the issues of recognition of marriages of same-sex couples, respectively registered partnerships established abroad. The aim of the contribution is to summarize and stimulate a wider discussion on the issues addressed and to point out the fact that human rights must be guaranteed in a state of law, while their guarantee can be interpreted as a security granted to all and the rejection of discrimination. The lack of legal recognition for same-sex unions not only presents social challenges but also practical hindrances in daily affairs such as healthcare, taxation, and social security benefits, which can often be predicated on marital status. It is crucial to consider the implications of such legal gaps on the well-being of individuals who are part of same-sex couples, as well as their children. The evolving social fabric and changing attitudes towards same-sex relationships necessitate a reassessment of existing legal frameworks to ensure inclusivity and equality under the law. The continued efforts and discussions within the Slovak Republic highlight a growing awareness and potential for legislative change that aligns with the European consensus on human rights. Moreover, the exploration of legal avenues for recognition of same-sex unions must consider the dynamic nature of family structures in the contemporary context, where diversity in family units is becoming increasingly normative.

MRSLN: A Multimodal Residual Speaker-LSTM Network to alleviate the over-smoothing issue for Emotion Recognition in Conversation

Multimodal Emotion Recognition in Conversation (ERC) plays a significant role in the field of human–computer intelligent interaction since it enables computers to perceive and infer the emotions expressed by the individuals, thereby intelligently responding to them. Most of current ERC methods pay more attention to modeling the complex interaction between different modalities. However, the features extracted by their unimodal networks are over-smoothed and may contain insufficient intra-speaker contextual information, which results in suboptimal results. In this paper, we focus on the unimodal learning and propose a simple late fusion framework named Multimodal Residual Speaker-LSTM Network (MRSLN), which uses speaker information to directly model inter-speaker and intra-speaker dependency, rather than fuse it into the learned features. MRSLN uses the speaker-LSTM consisting of the inter-speaker LSTM, intra-speaker LSTM, and the residual network between the input and output of the inter-speaker LSTM. Our proposed method can alleviate the issue of over-smoothing in deep Long Short Term Memory (LSTM) network and also incorporate additional intra-speaker contextual information. Extensive experiments conducted on IEMOCAP and MELD datasets demonstrate that MRSLN effectively captures inter-speaker and intra-speaker information and outperforms currently complex state-of-the-art (SOTA) models in efficiency and classification performance.

Integrated Fruit Ripeness Assessment System Based on an Artificial Olfactory Sensor and Deep Learning.

Artificial scent screening systems, inspired by the mammalian olfactory system, hold promise for fruit ripeness detection, but their commercialization is limited by low sensitivity or pattern recognition inaccuracy. This study presents a portable fruit ripeness prediction system based on colorimetric sensing combinatorics and deep convolutional neural networks (DCNN) to accurately identify fruit ripeness. Using the gas chromatography-mass spectrometry (GC-MS) method, the study discerned the distinctive gases emitted by mango, peach, and banana across various ripening stages. The colorimetric sensing combinatorics utilized 25 dyes sensitive to fruit volatile gases, generating a distinct scent fingerprint through cross-reactivity to diverse concentrations and varieties of gases. The unique scent fingerprints can be identified using DCNN. After capturing colorimetric sensor image data, the densely connected convolutional network (DenseNet) was employed, achieving an impressive accuracy rate of 97.39% on the validation set and 82.20% on the test set in assessing fruit ripeness. This fruit ripeness prediction system, coupled with a DCNN, successfully addresses the issues of complex pattern recognition and low identification accuracy. Overall, this innovative tool exhibits high accuracy, non-destructiveness, practical applicability, convenience, and low cost, making it worth considering and developing for fruit ripeness detection.

External defect detection technology and application status of transmission and transformation equipment based on video images

Power transmission and distribution equipment plays a critical role in supplying electricity to consumers. However, these assets are susceptible to external defects, such as corrosion, mechanical damage, and wear, which can lead to failures and disruptions in the electrical grid. Traditional inspection methods for detecting these defects often rely on manual inspections, which are time-consuming, costly, and subjective. To overcome these limitations, this paper explores the current state of video image-based external defect detection techniques for power transmission and distribution equipment. This makes up for the deficiencies of conventional approaches to inspecting and maintaining power transmission and transformation equipment by decreasing the waste of human resources and increasing the frequency and efficiency of intelligent operation and maintenance of power systems. This work investigates a completely convolutional block detection-based defect identification method to address the issue of defect recognition. The fully convolutional neural network is enhanced with the concept of block detection thanks to this approach. The local discrimination mechanism may be realized, and the drawbacks of the conventional block detection receptive field are avoided in the process. This approach offers improved generalization and fault identification over the original ResNet image classification system.

Understanding the dilemma of explainable artificial intelligence: a proposal for a ritual dialog framework

This paper addresses how people understand Explainable Artificial Intelligence (XAI) in three ways: contrastive, functional, and transparent. We discuss the unique aspects and challenges of each and emphasize improving current XAI understanding frameworks. The Ritual Dialog Framework (RDF) is introduced as a solution for better dialog between AI creators and users, blending anthropological insights with current acceptance challenges. RDF focuses on building trust and a user-centered approach in XAI. By undertaking such an initiative, we aim to foster a thorough Understanding of XAI, capable of resolving the current issues of acceptance and recognition.

Multikulturalisme dan Kebijakan Publik: Rekognisi dan Perlindungan Hak Asasi Masyarakat Adat di Indonesia dalam Perspektif Universalisme Interaktif Seyla Benhabib

This article discusses the issue of recognition and protection of community rights in Indonesia in the light of Seyla Benhabib's interactive universalism. The research aims to analyse the challenges and opportunities in pursuing recognition and protection of indigenous peoples within the framework of interactive universalism, by emphasising cultural diversity and the importance of the local context. Interactive universalism concerns about the importance of dialogue, public participation, and the adaptation of democratic principles in preserving indigenous peoples' rights. Here interactive universalism is used to review the state of indigenous peoples' rights in Indonesia. Various public policies have caused conflicts, ranging from land take over to human rights violation, that are detrimental to the existence of indigenous peoples. Public policy as a representation of the state should protect their rights. In this article public policies are reviewed from the perspective of interactive universalism. The review process will consider cultural diversity in order to prevent future problems and to recommend adequate and assured protection of the rights of indigenous peoples. This research is a qualitative research using a philosophical approach and literature review to analyse actual problems.

Судимость за преступление, совершенное с применением насилия, как квалифицирующий признак, предусмотренный ч. 2 ст. 116.1 Уголовного кодекса Российской Федерации

This article considers the problems of application of part 2 of article 116.1 of the Criminal Code of the Russian Federation, associated with the interpretation of the sign in the form of «... by a person who has a criminal record for a crime committed with the use of violence». The ambiguity of the legislative wording in this part determines the need to establish the type of violence, as well as crimes that can be recognized as committed with its use. As a result of the study recommendations have been formed to help resolve the issue of recognition or non-recognition of a crime committed with the use of violence for the purposes of part 2 of article 116.1 of the Criminal Code of the Russian Federation.

The Right of the Consumer to Protect Personal Data and its Implementation

Relevance. The article discusses ways to protect the personal data of the consumer as their subject. It is noted that the risk of violation of the rights of this category of citizens has increased significantly in the era of digitalization. Legislative novelties proposed by the scientific community concerning the recognition of personal data as a personal non-property good are analyzed. Based on the generalization of judicial practice, approaches to assessing the illegality of processing, distribution or use of other people's personal data in decisions on claims for recognition of such actions as violating the provisions of civil legislation are shown. The purpose of the study is to supplement scientific knowledge about ways to protect consumer personal data and improve the quality of law enforcement practice when considering claims in cases of this category. Objectives: to analyze the practice of the Constitutional, Supreme Courts of the Russian Federation, courts of general jurisdiction in cases of consumer personal data protection and to identify problems related to the implementation of this right.Methodology. When writing the work, methods of analysis and synthesis, system-analytical, documentary and formal legal methods were used. The results of the study are theoretical and applied in nature and are aimed at finding optimal solutions for the effective implementation of the consumer's right to personal data protection. The issue of legislative recognition of a person's personal data as a personal intangible good is raised in order to ensure proper restoration of violated rights.The conclusions made in the article, as well as the proposals made, are aimed at continuing scientific developments on the stated topic, are of a debatable nature and allow for a uniform way to resolve problems arising in the implementation of the consumer's right to personal data protection. Conclusion and proposals are aimed at continuing scientific developments on the stated topic, are of a debatable nature and allow solving problems arising in the implementation of the consumer's right to personal data protection in a uniform way.

Joint Obligations of Spouses When Courts Consider Cases on Bankruptcy of a Citizen

The article is devoted to the study of the issue of recognition of obligations as general in bankruptcy cases. The study analyzed the general provisions of the legislation on joint obligations of spouses in a bankruptcy case and examined individual problems that arise when courts consider creditors’ requests to recognize the debt as common. As a result of the study, the author concluded that at present the issue of recognizing obligations as general in bankruptcy cases is solely at the discretion of the judge and there are no clear criteria for considering the issue of recognizing a debt as general. Based on the results of the work, the authors developed his own approach to improving legislation, which is expressed in the need to amend the legislation on consumer lending.

Принципы общественной установленности школьного образования в России

The scale of the modern education system and the role of the educational paradigm in Russia's strategic plans are emphasized. The authors explains the social necessity of creating the necessary conditions and mechanisms that improve the organizational characteristics of education and ensure the effective solution of current and future tasks in the educational field. The principle of unity of educational space on the territory of the Russian Federation is analyzed. The main institutions that postulate the meanings of education and regulate the stability of the entire educational complex are highlighted. Attention is focused on the essential assessment of the institutions of upbringing, learning, pedagogical education, and pedagogical science. The issue of recognition of pedagogy and pedagogical education as a national heritage and heritage responsible for the reproduction of the collective worldview and social harmony of Russian society is discussed. Additional organizational and technological steps aimed at improving Russian education are proposed. The goals and objectives of the study are related to the need for systematic improvement of the country's educational complex.

A fault recognition method for transmission systems based on independent component analysis and convolutional neural networks

Accurate recognition of transmission line (TL) faults plays a vital role in protection systems, avoiding misoperations and false trips. Several studies in this area have revealed the limitations of existing algorithms, particularly when considering more complex electrical power systems (EPS), where some expected operations (capacitor and load switching, for example) can be misinterpreted as fault events. This work addresses the critical issue of fault recognition (FR) in TLs with a special focus on distinguishing faults from other types of disturbances. The primary objective of this study is to introduce an approach based on Convolutional Neural Networks (CNN) and Continuous Wavelet Transform (CWT) for FR in EPS. This method relies only on voltage signals acquired with a reasonable sampling frequency. The proposed method is enhanced with an Independent Component Analysis (ICA)-based preprocessing, making it robust and versatile in handling different types of disturbances, such as adjacent line faults, load switching and capacitor switching. The evaluation of the proposed method is done considering two different EPS, achieving an accuracy up to 99 %, showing the robustness of the method against different scenarios such as fault events and switching operations.

Recognition Issues in Televised Representations of High-Level Women Athletes during World Championships and the Olympics: Deconstructing the “Male Gaze,” Focusing on Sport Performance and Considering Discrimination from an Intersectional Perspective

Recognition Issues in Televised Representations of High-Level Women Athletes during World Championships and the Olympics: Deconstructing the “Male Gaze,” Focusing on Sport Performance and Considering Discrimination from an Intersectional Perspective

Research on the Scientific Issues of Identity Recognition of Image Traces

Research on the Scientific Issues of Identity Recognition of Image Traces

사자(死者)의 점유(占有)’에 대한 새로운 접근법

This paper introduces the domestic discussion of “ownership” or “occupation” of Kant, which is considered to be a meaningful review in the field of criminal law, especially in relation to “occupation” of criminals in each theory of criminal law. I hope that this study will be a meaningful suggestion for reference in re-evaluating the issue of recognition of possession by the deceased or the criteria for judging the commencement of occupation by heirs, which the Supreme Court precedent is concerned about.&#x0D; I think it is also necessary for practical law that philosophy of law, judicial history, or comparative law perspectives continue to be presented in relation to important issues of law. The subject of deceased's possession covered in this paper was also logically unconvincing to say that his possession was terminated because the victim died when he committed murder to steal goods, and to solve this problem, the precedent devised the deceased's survival possession to fill the gap. However, even in this case, the attempt to introduce 'legal philosophy, judicial history, and comparative law' thinking beyond the legal logic level is the way to revive legal philosophy, judicial history, and comparative law.

Recognition and detection of unusual activities in ATM using dual-channel capsule generative adversarial network

Real-time detection of human activity has become essential for monitoring and security of public spaces such as bank ATMs and workplaces, due to daily rise in criminal activities. Currently, monocular CCTV cameras that only record RGB video are used for monitoring such restricted areas. In addition to RGB data, the RGB + D sensor also offers depth information about the scene. To overcome the issue of online recognition of anomalous activities in Bank ATMs, a supervised deep learning method utilizing Dual-Channel Capsule Generative Adversarial Network (DCCGAN) and RGB + D sensor is proposed. The input RGB + D Dataset is given to super pixel motion detection method to find the region of interest (ROI). Motion detection is a significant stage examination of wide scene for background subtraction and foreground detection. After arranging the motion detection, its region is positioned frame by frame. Then, the detected ROI is given to fast discrete curvelet transform with the wrapping (FDCT-WRP) method. FDCT-WRP feature extraction method. These extracting features are supplied to Deep Convolutional Spiking neural network (DCSNN), which realize the object. RGB and depth video segments are used to create motion templates from the RGB + D data online video stream. These templates are trained on DCCGANs to identify distrustful events in current activity and categorized as normal and abnormal. Additionally, a unique RGB + D dataset is employed because there was no existing dataset available for analyzing human activity in ATMs. The proposed DUA-DCCGAN-ATM approach is assessed on qualitative with quantitative statistical evaluation parameters and identify suspect occurrence with 0.932 precision and 98.2 % accuracy. The detailed statistical analysis exemplifies that the proposed technique can identify distrustful events in a real-time online manner prior completing the anomalous activity.

Wearing out the Watchdog: The Impact of SEC Case Backlog on the Formal Investigation Process

ABSTRACT We examine a comprehensive set of investigations by the SEC’s Division of Enforcement offices to provide evidence on the consequences of these office’s busyness on the formal investigation process. We find that higher office case backlog decreases the likelihood of an investigation into a restating firm. Our results show no evidence that higher backlogs affect the SEC’s ability to pursue cases involving revenue recognition issues and high insider trading, which is consistent with the agency’s stated priorities. But our findings indicate that busy SEC offices are less likely to pursue cases with the largest shareholder losses, which is inconsistent with SEC priorities. Backlog also impacts pursued investigations, leading to more prolonged investigations, a lower Accounting and Auditing Enforcement Releases likelihood, and smaller SEC penalties. Our evidence suggests that busyness undermines the SEC’s investigation process. JEL Classifications: G18; G38; K42; M41.