Comprehensive Supervision Research Articles

Depth Matters: Spatial Proximity-based Gaze Cone Generation for Gaze Following in Wild

Gaze following aims to predict where a person is looking in a scene. Existing methods tend to prioritize traditional 2D RGB visual cues or require burdensome prior knowledge and extra expensive datasets annotated in 3D coordinate systems to train specialized modules to enhance scene modeling. In this work, we introduce a novel framework deployed on a simple ResNet backbone, which exclusively uses image and depth maps to mimic human visual preferences and realize 3D-like depth perception. We first leverage depth maps to formulate spatial-based proximity information regarding the objects with the target person. This process sharpens the focus of the gaze cone on the specific region of interest pertaining to the target while diminishing the impact of surrounding distractions. To capture the diverse dependence of scene context on the saliency gaze cone, we then introduce a learnable grid-level regularized attention that anticipates coarse-grained regions of interest, thereby refining the mapping of the saliency feature to pixel-level heatmaps. This allows our model to better account for individual differences when predicting others’ gaze locations. Finally, we employ the KL-divergence loss to super the grid-level regularized attention, which combines the gaze direction, heatmap regression, and in/out classification losses, providing comprehensive supervision for model optimization. Experimental results on two publicly available datasets demonstrate the comparable performance of our model with less help of modal information. Quantitative visualization results further validate the interpretability of our method. The source code will be available at https://github.com/VUT-HFUT/DepthMatters .

Analysis of Securities Offering Regulations on Securities Crowdfunding Services Maslahah Approach

The acceleration of the Digital Era began with the spread of the COVID-19 virus, which caused the national economy to grow 2.5% in 2020, or down 5% from 2019. The lockdown policy was a factor in the slow turnaround of the economy. Another impact is digitalization in all aspects, including the financing sector and the formation of rules to regulate financing. Financial technology is an instrument that is experiencing accelerated growth because it is based on the internet of things (IOT). With the birth of the concept of crowdfunding securities, which has become an alternative funding source for business actors such as MSMEs, Initially, MSME funding activities in the crowdfunding cycle were limited to equity based on POJK 37 of 2018, then the regulation developed into POJK 57 of 2020 and became POJK 16 of 2021. These regulatory changes changed the funding mechanism, which was initially equity-based and then developed to be based on sukuk and debt securities. These regulatory changes became the focus of research after examining the impact of these regulations on the funding of MSMEs and legal business entities in Indonesia. Mas}lah}ah theory became the knife in analyzing these regulations using normative legal research methodology as the research method and descriptive analysis as the analytical method. The use of this theory is based on the impact of existing regulatory developments, which have reached funding worth $1 trillion and contain 481 business units, with funding sources coming from 160,368 investors. This funding achievement is a challenge to carry out comprehensive supervision regarding the distribution and use of capital by service-provider companies and the Financial Services Authority by paying attention to the principles of GCG, CSR, and open disclosure to guarantee and protect the rights of parties participating in related funding.

Training of New Professional Farmers in Rural Revitalization: A Reexamination based on Supply and Demand

The rural revitalization strategy is a crucial initiative aimed at promoting the modernization of rural areas, with the cultivation of new professional farmers emerging as a key component in its implementation. This paper conducts an in-depth analysis of the training of new professional farmers from the perspectives of both supply and demand. Addressing issues related to cultivation policies, key players, and training content during the cultivation process, the paper proposes a series of strategies in areas such as top-level design, classification management, cultivation models, content innovation, and supervision mechanisms. In terms of top-level design, the paper emphasizes the importance of defining strategic goals and pathways for cultivation to ensure alignment with the rural revitalization strategy. The strategy combining classification management with precision cultivation aims to implement differentiated training plans that better cater to the specific needs of different regions and rural areas. Reforms in cultivation models and content are advocated to align with the trends in modern agricultural development. Additionally, the establishment of a comprehensive supervision mechanism is recommended to ensure the fairness and transparency of cultivation efforts.

COSST: Multi-Organ Segmentation With Partially Labeled Datasets Using Comprehensive Supervisions and Self-Training.

Deep learning models have demonstrated remarkable success in multi-organ segmentation but typically require large-scale datasets with all organs of interest annotated. However, medical image datasets are often low in sample size and only partially labeled, i.e., only a subset of organs are annotated. Therefore, it is crucial to investigate how to learn a unified model on the available partially labeled datasets to leverage their synergistic potential. In this paper, we systematically investigate the partial-label segmentation problem with theoretical and empirical analyses on the prior techniques. We revisit the problem from a perspective of partial label supervision signals and identify two signals derived from ground truth and one from pseudo labels. We propose a novel two-stage framework termed COSST, which effectively and efficiently integrates comprehensive supervision signals with self-training. Concretely, we first train an initial unified model using two ground truth-based signals and then iteratively incorporate the pseudo label signal to the initial model using self-training. To mitigate performance degradation caused by unreliable pseudo labels, we assess the reliability of pseudo labels via outlier detection in latent space and exclude the most unreliable pseudo labels from each self-training iteration. Extensive experiments are conducted on one public and three private partial-label segmentation tasks over 12 CT datasets. Experimental results show that our proposed COSST achieves significant improvement over the baseline method, i.e., individual networks trained on each partially labeled dataset. Compared to the state-of-the-art partial-label segmentation methods, COSST demonstrates consistent superior performance on various segmentation tasks and with different training data sizes.

Study on the technical management practice of rock burst prevention and control - Case study of Yankuang Energy Group Company Limited

To ensure the on-site implementation of regulations and technical measures for rock burst prevention and control, taking Yankuang Energy Group Company Limited. as an example, an on-site technical management system for preventing and controlling rock burst in coal mines is established. This on-site technical management system is based on the principles of “zero rock burst accident”, “graded management and control”, “general manager and chief engineer responsibility”, and “scientific, systematic, streamlined, and efficient management”. This system includes a technical management system and an on-site management mode, among which the former includes an organizational system, an institutional system, a technical data management system, and a comprehensive supervision and management system. Each system is interrelated, mutually promoting and supporting the other system. The on-site management mode includes five aspects and six links. These “five aspects” refer to the standardization of safe production, normalization of on-site operations, processization of system operation, quantification of antirisk ability, and demonstration of mine management. The “six links” on-site management mode includes the management system, source risk management and control, dynamic risk analysis, monitoring and control, on-site implementation and management, and emergency management. The construction of an on-site technical management system for rock burst prevention and control can ensure the timely detection and rectification of problems, remove management loopholes, and prevent the occurrence of rock burst disasters.

Players' strategy selection in co-governance and supervision of internet platforms' monopolistic behaviors: A study on new media participation.

Incidents of monopolies among Internet platforms have seriously endangered the development of the market economy, public interest, and social fairness, making it a highly discussed topic of broad public concern. Preventing such incidents requires not only a comprehensive supervision system by governments, but also contributions from other relevant parties. The new media environment has provided a new platform to support such joint supervision from multiple parties. As such, this study constructed an evolutionary game model involving the government, Internet platforms, new media, and the public to explore the stable equilibrium point of players' strategy selections. The stability of the strategy combinations was tested using Lyapunov's first stability method, and MATLAB 2021b was used to conduct simulation analysis of the impact of each decision variable on players' strategy selection. The results showed that (1) new media participation in co-governance and public complaints/reports facilitated government supervision; (2) government's application of co-governance and supervision and public complaints/reports promotes compliance by Internet platforms; (3) new media plays a supplementary role when government supervision is lacking; the greater the impact of new media, the greater its supervisory effect on Internet platforms; and (4) effective reduction of costs stimulates the enthusiasm of the government and new media, and increases the success of the anti-monopoly co-governance and supervision system. Measures and suggestions to improve supervision of monopolistic behaviors among Internet platforms are proposed.

Spatial information extraction of fishing grounds for light purse seine vessels in the Northwest Pacific Ocean based on AIS data

Ecological fishery management requires high-precision fishery information to support resource management and marine spatial planning. In this paper, the Automatic Identification System (AIS) was adopted to extract the spatial information on the fishing grounds of light purse seine vessels in the Northwest Pacific Ocean. The spatial distributions of fishing grounds mapped by the data mining, kernel density analysis and hotspot analysis methods were compared. The spatial similarity index was applied to determine the spatial consistency between the computed spatial information and fisheries resource information. Finally, the spatial information derived by the best method was used to investigate the characteristics of fishing activity. The results showed that: the speed of light purse seine vessels related to operations was lower than 1.6 knots. The spatial information extracted by the three methods was consistent with the catch data distribution, and the spatial similarity between the fishing effort and catch data was the highest. The spatial variation in fishing activity was similar to that in the chub mackerel migration route. AIS data could be used to provide high-resolution fishery information. Light purse seine fishing vessels typically operate and travel along the exclusive economic zone boundary, and increased attention must be given to fishing vessel operation supervision. A comprehensive supervision system can be employed to monitor the operations of fishing vessels more effectively. The results of this study can provide technical support for the management of fishing activities and conservation of marine resources in this region using AIS data.

中国托育服务发展的政策支持与完善路径研究

The childcare service in our country has just started and is faced with many problems and challenges. At present, there are some urgent problems to be solved in the development of childcare services in China, such as the contradiction between supply and demand of childcare services, regional differences in the implementation of childcare service policies, insufficient national and local financial investment and subsidies, unclear responsibilities of management departments, and uneven quality of childcare services. In order to address the negative impact of market-oriented childcare services, the government has included childcare services in the strategic planning of establishing a sound social welfare system. In the path of the development of childcare services, the policy intention of promoting the development of childcare services can be promoted by advocating new and changing childcare institutions, breaking the traditional dual type system of childcare services, implementing price control of childcare services and improving the comprehensive supervision system of childcare services, so as to promote the healthy and rapid development of childcare services in China and meet the needs of society and families.

Phenomenology of Clinical Supervision: Examining Pre-observation to Post observation in Teacher Development

This phenomenological study explored teachers’ lived experiences during clinical supervision from pre-observation to post-observation stages in Agusan del Sur, Philippines. Using purposive sampling, 40 teachers with 1-3 years of service from four high schools participated in semi-structured interviews and reflective journaling. Thematic analysis revealed three key themes: (1) Impact of prior experiences, relational factors, and reflective practices on teacher readiness for supervision; (2) Real-time adaptation, reflective practice, and growth opportunities during classroom observations; and (3) Self-assessment, feedback integration, and collaborative professional growth following supervision sessions. Findings align with Bandura’s social cognitive theory and Acheson and Gall’s three-phase model of clinical supervision, emphasizing the importance of positive prior experiences, strong teacher-supervisor relationships, and reflective practices in enhancing supervision effectiveness. The study highlights the critical role of the post-observation phase in facilitating deep reflection, active feedback implementation, and collaborative learning. Recommendations include developing comprehensive supervision programs, fostering supportive organizational cultures, and implementing structured post-observation protocols. This research contributes to the understanding of clinical supervision in education and offers a framework for improving supervisory practices and teacher professional development.

Tinjauan Yuridis atas Peredaran Produk Obat Pelangsing Ilegal Melalui Perdagangan Online yang Beresiko terhadap Kesehatan

In realizing a healthy state, medicine and food play a very important role. However, not all drugs and foods distributed online have a distribution permit and meet other requirements in accordance with laws and regulations so that they can threaten public health. The circulation of drug products online has the risk of circulating certain drugs that are often misused and illegal products that harm public health, one of which is illegal direct drug products such as Slim Strong, Slim Fast, Slimming Pro, etc.), containing BKO sibutramin which can cause side effects such as palpitations, shortness of breath, anxiety, and hallucinations. The method used in writing this article is a qualitative approach with a descriptive method of analysis. Data collection techniques are carried out by literature study. Data and information are collected from various related literature such as books, journals, related laws and regulations, government documents, news in mass media both print and electronic, and others. Data and information are combined and analyzed based on discussion groups. The last stage, the results of the analysis that has been made, conclusions are drawn as answers to research questions and also some suggestions or recommendations to relevant stakeholders. This study emphasizes that supervision carried out by the Food and Drug Administration on the circulation of illegal slimming drug products as a form of comprehensive supervision ranging from pre-market to post-market supervision. This supervision is strengthened by the existence of Presidential Instruction (Inpres) Number 3 of 2017 concerning Increasing the Effectiveness of Food and Drug Control. Then, law enforcement that can have a deterrent effect is to apply criminal sanctions, as stipulated in Article 197 Jo. Article 106 paragraph (1) of RI Law Number 36 of 2009 concerning Health as amended by Article 60 number 10 of RI Law Number 6 of 2023 concerning the Stipulation of Government Regulations in Lieu of RI Law on Job Creation and in RI Law Number 8 of 1999 concerning Consumer Protection.

THE ANALYSIS OF PERSONNEL SUPERVISION FUNCTIONS APRON MOVEMENT CONTROL (AMC) EFFORTS TO REDUCE THE RATE OF VIOLATION OF GROUND SUPPORT EQUIPMENT (GSE) VEHICLE SPEED LIMITS ON THE SERVICE ROAD AT SAM RATULANGI INTERNATIONAL AIRPORT, MANADO

This thesis examines performance issues concerning the supervision of AMC personnel on the Service Road of Sam Ratulangi International Airport Manado. The issue under discussion is the prevalence of Ground Support Equipment (GSE) exceeding the stipulated speed limits, which poses a potential hazard. Additionally, the service road at Sam Ratulangi International Airport Manado serves as a pathway for passengers embarking or disembarking from aircraft, making the situation more critical due to insufficient supervision by AMC personnel regarding orderliness on the apron. This research aims to optimize the performance of Apron Movement Control (AMC) unit personnel related to the supervision of Ground Support Equipment (GSE) order. The theoretical framework for this research is based on Manual Of Standard CASR – Part 139, Volume I, Chapter 9, Point 9.6.6, which covers The Duties of Apron Movement Control (AMC) Personnel, and SKEP 140/VI/1999, which outlines Requirements and Operational Procedures of Vehicles on Air Side, particularly Chapter IV addressing the Code of Conduct of Traffic On Air Side. This research uses a qualitative combination method and data collection techniques using observation, interviews, documentary studies, and questionnaires. The findings of this study highlight the importance of adhering to the AMC Standard Operating Procedure (SOP) in terms of comprehensive supervision. To address the identified issues, it is recommended to implement coaching sessions and conduct regular and scheduled Ramp Safety Campaigns."

Attention-based dual-color space fusion network for low-light image enhancement

The low visibility and dull colors associated with low-light images are not only difficult to satisfy the photographer, but also hinder further visual tasks. In this study, we propose an attention-based dual-color space fusion network to enhance low-light images. By introducing HSV color space, the network can solve the problems of dim color and insufficient contrast existing in previous RGB color space methods. In both color spaces, the network adopts a large number of attention mechanisms to highlight important features in real time. To better achieve feature fusion across color space, we design adaptive large-kernel attention (ALKA) and feature extraction module (FEM), respectively. The ALKA adaptively selects features for enriching the encoding input in the HSV color space during the RGB color space encoding process. The FEM assists the network in more comprehensive supervision of the enhancement process and generates the attention map to transmit the marking features in the previous color space. At the end of the network, we also design channel enhancement module (CEM) to protect the texture details lost during the scale change. We have conducted experiments on a variety of public datasets, and both subjective and objective comparisons have demonstrated the particularity and prominence of our method.

Egocentric Early Action Prediction via Multimodal Transformer-Based Dual Action Prediction

Egocentric early action prediction, which aims to recognize the on-going action in the video captured in the first-person view as early as possible before the action is fully executed, is a new yet challenging task due to the limited partial video input. Pioneer studies focused on solving this task with LSTMs as the backbone and simply compiling the observed video segment and unobserved video segment into a single vector, which hence suffer from two key limitations: lack the non-sequential relation modeling with the video snippet sequence and the correlation modeling between the observed and unobserved video segment. To address these two limitations, in this paper, we propose a novel multimodal TransfoRmer-based duAl aCtion prEdiction (mTRACE) model for the task of egocentric early action prediction, which consists of two key modules: the early (observed) segment action prediction module and the future (unobserved) segment action prediction module. Both modules take Transformer encoders as the backbone for encoding all the potential relations among the input video snippets, and involve several single-modal and multi-modal classifiers for comprehensive supervision. Different from previous work, each of the two modules outputs two multi-modal feature vectors: one for encoding the current input video segment, and the other one for predicting the missing video segment. For optimization, we design a two-stage training scheme, including the mutual enhancement stage and end-to-end aggregation stage. The former stage alternatively optimizes the two action prediction modules, where the correlation between the observed and unobserved video segment is modeled with a consistency regularizer, while the latter seamlessly aggregates the two modules to fully utilize the capacity of the two modules. Extensive experiments have demonstrated the superiority of our proposed model. We have released the codes and the corresponding parameters to benefit other researchers <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> .

Nadzor u oblasti digitalne imovine

The paper analyzes the regulation of supervision in the feld of digital assets, which is carried out by the National Bank of Serbia and the Securities Commission. Despite the aspiration towards comprehensive supervision, it seems that the legislator has chosen several legal solutions, which create unnecessary confusion, leave vagueness, and in some places excessively narrow the protection of the rights and legitimate interests of the subjects of supervision. Specifcally, it is a provision on the appropriate application of norms governing the jurisdiction of supervisory authorities in the event of the appearance of „mixed“ digital assets. Te legislator left a number of unanswered questions there – the posibility of appropriate application of jurisdictional norms, resolution of conficts and conjunction of jurisdictions, as well as the creation of opportunities for confict of laws. Also questionable is the provision that leaves it to the supervisory authority’s discretion to determine the measures and amount of fines imposed in the supervision procedure. This results in confusion regarding the conditions for the imposition of measures, on the one hand, and a significant narrowing of the possibilities for protecting the rights of the subjects of supervision, on the other hand.

ANALISA TERHADAP SISTEM PENGENDALIAN INTERNAL PENERIMAAN DAN PENGELUARAN KAS (Studi Pada Rumah Pemotongan Hewan Kota Malang)

Abstract: In conjunction with the increasing complexity of financial transactions in a company, the escalating business competition requires the management to have comprehensive supervision of the entire flow of the company's transactions. One of the financial instruments majorly influencing financial statements, cash has different characteristics from other assets: difficult ownership identification, transferable, small in size, and highly desirable. To avoid cash misappropriation, an accounting control system of cash receipts and disbursements is required in a precise and systematic manner. This study aims to determine how the company applies the accounting system of cash receipts and disbursements and whether the elements of internal control have been implemented in both systems. This study is analyzed descriptively utilizing a qualitative approach involving primary and secondary data collected from interviews, observations, and documentation in the Regional Slaughterhouse Company of Malang City. The results of this study revealed that the Regional Slaughterhouse Company of Malang City has relatively properly implemented an accounting system of cash receipts and disbursements despite some weaknesses such as double accounting recording tasks conducted by the treasurer, cash receipts (BKM) made by the cash receipts treasurer, the cash disbursements (BKK) made by the cash disbursement treasurer, and the absence of cash insurance on hand and cash in transit insurance.

Application of Unmanned Aerial Vehicle 3D Model to Comprehensive Supervision of Mining and Virtual Simulation Training and Teaching

Application of Unmanned Aerial Vehicle 3D Model to Comprehensive Supervision of Mining and Virtual Simulation Training and Teaching

Scene Recognition for Construction Projects Based on the Combination Detection of Detailed Ground Objects

The automatic identification of construction projects, which can be considered as complex scenes, is a technical challenge for the supervision of soil and water conservation in urban areas. Construction projects in high-resolution remote sensing images have no unified semantic definition, thereby exhibiting significant differences in image features. This paper proposes an identification method for construction projects based on the detection of detailed ground objects, which construction projects comprise, including movable slab houses, buildings under construction, dust screens, and bare soil (rock). To create the training data set, we select highly informative detailed ground objects from high-resolution remote sensing images. Then, the Faster RCNN (region-based convolutional neural network) algorithm is used to detect construction projects and the highly informative detailed ground objects separately. The merging of detection boxes and the correction of detailed ground object combinations are used to jointly improve the confidence of construction project detection results. The empirical experiments show that the accuracy evaluation indicators of this method on a data set of Wuhan construction projects outperform other comparative methods, and its AP value and F1 score reached 0.773 and 0.417, respectively. The proposed method can achieve satisfactory identification results for construction projects with complex scenes, and can be applied to the comprehensive supervision of soil and water conservation in construction projects.

A model for CBDC audits based on blockchain technology: Learning from the DCEP

The rapid rise of central bank digital currency (CBDC) has sparked a heated discussion on its security, supervision and audit. To this end, this study designs a CBDC system based on the prototype of digital currency electronic payment (DCEP) that can provide real-time transaction verification, with an emphasis on comprehensive supervision, privacy-preserving transactions, verifiable audits, and a constant amount of CBDC. Meanwhile, we use blockchain technology and Pederson Commitment to design architecture to prove the records' veracity and the auditing's accuracy. The results of numerical experiments show that under the proposed CBDC system, (1) the central bank can audit 50 commercial banks in roughly one second; (2) the true value of the total bonds is comparable to the amount calculated by the Pedersen Committee; (3) the operation performance of the system is superior. Therefore, the security, effectiveness and practicability of our proposed CBDC system are demonstrated.

A Novel RDA-Based Network to Conceal Image Data and Prevent Information Leakage

Image data play an important role in our daily lives, and scholars have recently leveraged deep learning to design steganography networks to conceal and protect image data. However, the complexity of computation and the running speed have been neglected in their model designs, and steganography security still has much room for improvement. For this purpose, this paper proposes an RDA-based network, which can achieve higher security with lower computation complexity and faster running speed. To improve the hidden image’s quality and ensure that the hidden image and cover image are as similar as possible, a residual dense attention (RDA) module was designed to extract significant information from the cover image, thus assisting in reconstructing the salient target of the hidden image. In addition, we propose an activation removal strategy (ARS) to avoid undermining the fidelity of low-level features and to preserve more of the raw information from the input cover image and the secret image, which significantly boosts the concealing and revealing performance. Furthermore, to enable comprehensive supervision for the concealing and revealing processes, a mixed loss function was designed, which effectively improved the hidden image’s visual quality and enhanced the imperceptibility of secret content. Extensive experiments were conducted to verify the effectiveness and superiority of the proposed approach.

Protection of Personal Information in the Era of Big Data

In recent years, cloud computing and big data technologies have been widely used in China in the fields of public security, medical and health care, intelligent transportation, telecommunications and education, etc. The quality of life of the people has been improved and the digital industry has gained tremendous development, but at the same time, a series of personal information infringement disputes have arisen and the protection of personal information has attracted much attention. At present, insufficient protection of personal information under public law, the shortcomings of traditional informed consent rules, imperfect regulatory mechanism for personal information, and weak awareness of personal information protection have become major obstacles to balance the protection and utilization of personal information. Accordingly, it is necessary to adhere to the personal information protection path that combines public law protection and private law protection, to apply informed consent in the handling of personal information, and to improve the comprehensive supervision mechanism that unifies administrative supervision, industry association supervision, corporate internal supervision, and public opinion supervision, and on this basis, to improve the personal information infringement remedy mechanism that combines judicial remedy and private remedy.