Safety Guarantees Research Articles

Research on the evaluation of the operating effectiveness of the safety double prevention mechanism of coal mine enterprises based on matter-element extension

Safety production is a crucial guarantee for the country's economic development, and the safety double prevention mechanism is an effective way to realize safety production. In order to improve the operating effectiveness of coal mine enterprises' safety double prevention mechanism, this paper preliminarily constructs the evaluation indicator system for the operating effectiveness of the safety double prevention mechanism of coal mine enterprises based on the accident cases and literature analysis. The questionnaire was designed according to the index system, and the reliability and validity of the recovered data were analyzed. Based on the results of the analysis, the index system for evaluating the operating effectiveness of the safety double prevention mechanism of coal mine enterprises is established. This system comprises five first-level and 30 second‐level indicators for risk hierarchical control, hidden danger investigation and treatment, inspection review and update, employee safety management, and safety guarantee management. Subsequently, this paper utilized the AHP-EWM to empower the evaluation indicators and then constructed the matter-element extension model to evaluate the operating effectiveness of coal mine enterprises' safety double prevention mechanism. Finally, the Y coal mine enterprise is an example of empirical analysis. The results show that the operating effectiveness of the Y coal mine enterprise's safety double prevention mechanism has generally reached a good level. However, some evaluation indicators still have a low evaluation level, which is consistent with the actual situation of the Y coal mine enterprises. Evaluation results verify that this paper's evaluation indicators and model have strong applicability and scientificity.

Ultrasonic vibration cutting of advanced aerospace materials: a critical review of in-service functional performance

PurposeUnconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.Design/methodology/approachThe surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.FindingsTo address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.Originality/valueThis study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

Floating Schools: an Overview of Education in Bangladesh

highlighting education in Bangladesh is currently attracting world attention because there is a unique phenomenon that occurs due to the process of learning activities on boats in Bangladesh. Teaching and learning activities on a boat are not done because we want to exist and deliberately steal the world's attention because conditions must force these activities to occur. Bangladesh is a country that is prone to flooding problems which can paralyze life activities including educational activities. Problems arise from many parties who question the safety of teachers and students there because learning activities are not carried out in patented buildings. Then many parties also want to know the obstacles that arise from learning activities held on boats. The aim of this research is to determine safety efforts and also the obstacles faced during the learning process. This research uses mixed research methods, namely field research and literature study. The sources for this research are the manager of learning activities on the boat, 5 teachers and 10 students from 3 schools and also several relevant previous articles which were used as reference sources. The results of this research show that there is a guarantee of safety from the management, including starting from boat design , time management, provision for teachers to master the terrain and equipping the boat with sophisticated equipment. The challenges faced include aspects of funding, climate change, limited reach, teacher training and technological infrastructure.

Research on elastic governance strategy of urban public safety based on entropy weighted discrete clustering method

<p>Currently, there are problems in the governance of urban public safety, such as a single entity, outdated governance concepts, and immature governance technologies. This article combines big data analysis technology and utilizes intelligent emergency mechanisms to conduct in-depth research on governance strategies to enhance the resilience of urban public safety to disasters. This article first integrates big data analysis technologies, such as the Internet of Things and cloud computing, into UPS (urban public safety) and then builds a UPS system based on this. Combining the entropy-weighted dispersion clustering method, evaluate the values of urban public safety indicators. In order to verify the effectiveness of the intelligent emergency mechanism based on big data analysis, this article conducted experimental analysis on it. Under the intelligent emergency mechanism algorithm, the average seismic compliance rate of buildings in various cities has reached 88.57%. The conclusion indicates that an intelligent emergency mechanism based on big data analysis can enhance the adaptability of urban public safety governance strategies, improve the seismic and fire warning monitoring capabilities of urban buildings, reduce the occurrence of traffic accidents, and provide more guarantees for urban fire safety.</p>

Gaussian Process-Based Model Predictive Control for Autonomous Underwater Vehicles

Traditional MPC algorithms, assuming constant values, suffer from performance degradation caused by model mismatch. This paper addresses the enhancement of predictability in Autonomous Underwater Vehicles (AUVs) under uncertain disturbances and unknown system dynamics through the design of Model Predictive Controllers (MPCs). We propose a hybrid model that integrates a first-principles nominal model with a learning-based model utilizing Gaussian Processes (GPs). The algorithm addresses the problem of model mismatch in AUV motion control by constructing a precise GP model, which captures the dynamic characteristics of the process through the collection and learning of deviations between the reference model and the controlled system. Additionally, the GP model transforms stochastic constraints into deterministic convex constraints, enhancing safety guarantees in complex and challenging environments. The effectiveness of the proposed algorithm is demonstrated through two simulation examples.

Safe-by-construction autonomous vehicle overtaking using control barrier functions and model predictive control

Ensuring safety for vehicle overtaking systems is one of the most fundamental and challenging tasks in autonomous driving. This task is particularly intricate when the vehicle must not only overtake its front vehicle safely but also consider the presence of potential opposing vehicles in the opposite lane that it will temporarily occupy. In order to tackle the overtaking task in such challenging scenarios, we introduce a novel integrated framework tailored for vehicle overtaking manoeuvres. Our approach integrates the theories of varying-level control barrier functions (CBF) and time-optimal model predictive control (MPC). The main feature of our proposed overtaking strategy is that it is safe-by-construction, which enables rigorous mathematical proof and validation of the safety guarantees. We show that the proposed framework is applicable when the opposing vehicle is either fully autonomous or driven by human drivers. To demonstrate our framework, we perform a set of simulations for overtaking scenarios under different settings. The simulation results show the superiority of our framework in the sense that it ensures collision-free and achieves better safety performance compared with the standard MPC-based approach without safety guarantees.

Evaluation of the photoprotective and antioxidant potential of an avobenzone derivative.

Solar radiation can cause damage to the skin, and the use of sunscreens is one of the main protective measures. However, photounstable ultraviolet (UV) filters can generate photoproducts and reactive oxygen species (ROS). Adding antioxidants, such as resveratrol, to enhance the action of UV filters in sunscreens is an interesting strategy for reducing the damage caused by UV radiation exposure. However, new compounds must have their stability, safety and efficacy guaranteed. Avobenzone, a commonly used UV filter, stands out as a promising candidate for structural modification to enhance its stability. Its molecular hybridization with other UV filters and antioxidants can lead to safer and more effective compounds. In this study, the photoprotective and antioxidant potential of a derivative of avobenzone, hybridized with resveratrol's molecule, was evaluated using in vitro models of cells in monolayer and reconstructed human skin (RHS). Phototoxic potential was assessed using fibroblasts, while the antioxidant activity was measured using the DCFH2-DA probe in HaCaT keratinocytes and in-house RHS. The derivative exhibited UV absorption and demonstrated photostability. It did not exhibit any phototoxic nor photoreactivity potential. Additionally, it was able to photo stabilize a combination of photounstable UV filters, avobenzone and octyl methoxycinnamate, and to reduce their phototoxic potential. In terms of antioxidant activity, the derivative successfully protected against UVA-induced ROS production in the HaCaT keratinocytes model, showing statistical equivalence to the antioxidant control, quercetin (10μg/mL). Furthermore, experiments conducted in the RHS model demonstrated a significant reduction of 30.7% in ROS generation compared to the irradiated control. This study demonstrated that structural modifications of avobenzone can lead to the development of a broad spectrum (absorbing UVB and UVA II radiation, as well as a portion of the UVA I radiation), non-phototoxic, non-photoreactive and photostable derivative for sunscreen and anti-aging formulations. This derivative enhances protection against oxidative stress induced by UV radiation and improves the effectiveness of sun protection. In addition to the monolayer model, the use of a standardized in-house RHS model was highly relevant for evaluating the effects of UV radiation and skin aging. This model closely mimics human physiological conditions and enables the testing of new compounds and the investigation of protective mechanisms against skin damage.

AI monitoring and warning system for low visibility of freeways using variable weight combination model

AbstractIn intelligent vehicles, road environment perception technology is a key component of autonomous driving assistance systems. This component is the foundation for vehicle decision‐making and control, and is a guarantee of safety during the driving of the vehicle. The existing environment perception technology mainly targets well‐lit environments and requires visible light imaging equipment. Therefore, in low visibility environments, this technology cannot make good judgments about the external environment. Many existing perception systems mainly rely on sensors. Under low visibility conditions, these sensors weaken their effectiveness due to signal transmission, reflection, or absorption, resulting in incomplete or distorted data collection. Reduced visibility often affects the sensing range of various sensors, hindering the system's ability to detect and recognize distant objects, thereby limiting the necessary advance warning and response time for safe navigation. In response to this issue, this study proposed a combined method of infrared imaging and polarized imaging to collect feature data on road conditions in low visibility environments. Then, the obtained images were denoised and enhanced. The processed images were input into the system for recognition, and the images were analyzed and recognized using a low visibility road situation semantic segmentation algorithm based on deep learning. The research outcomes denoted that the pixel accuracy, average pixel accuracy, and average intersection ratio of the variable weight combination model in polarized degree images were 91.2%, 89.1%, and 71.6%, respectively. Those in infrared images were 83.6%, 90.6%, and 62.1%, respectively. The various indicators of the variable weight combination model were higher than those of the U‐shaped neural network model, indicating its performance is relatively excellent. The research results indicated that infrared imaging helps to acquire information at night or in low light conditions, while polarized imaging can provide better adaptation to cluttered light and reflections, enabling the system to provide more robust environmental sensing in complex weather conditions. It fills a critical gap in perception for autonomous driving systems in adverse weather conditions.

Pengaruh Brand Awereness, Brand Trust dan Promosi Terhadap Keputusan Pembelian Regulator Gas

The use of the Kopana Top Gas Brand Gas Regulator makes cooking easier for consumers, alleviating concerns about safety. This, in turn, reduces the risk of unexpected accidents such as fires resulting from gas leaks or gas cylinders losing gas due to loose regulator installation. Not all products offer a safety guarantee, leaving consumers unaware of potentially significant risks. This lack of awareness can make it challenging for consumers to distinguish between products that provide genuine benefits and those that may be less reliable. Therefore, the aim of this research is to examine the impact of the Brand Awareness variable, Brand Trust, and promotional activities on the purchasing decisions regarding the Kopana Top Gas Brand Gas Regulator. The study employed a questionnaire distribution method with 60 respondents selected randomly from a population of 150 potential respondents. Data analysis was conducted using the SPSS version 26 program, involving three testing stages: instrument validation, classical assumption testing, and hypothesis testing. The findings indicate that the variables brand awareness, brand trust, and promotion collectively influence the purchasing decision of the kopana top gas brand gas regulator. specifically, brand trust emerges as the most influential factor in shaping purchasing decisions.

PENGARUH KESELAMATAN DAN KESEHATAN KERJA (K3) LINGKUNGAN KERJA DAN MOTIVASI TERHADAP KINERJA KARYAWAN PT. SAWIT KALTIM LESTARI SABINTULUNG MUARA KAMAN

The achievement of improving an employee's performance can be seen from each completion of work carried out. If an employee is able to complete all assigned tasks well, accompanied by a good attitude, such as a good level of absenteeism, then the employee is considered to have maximum performance. In the last three years, PT. Sawit Kaltim Lestari declined but production realization remained almost perfect. There are many factors that can influence employee performance, especially for employees who work in the production department. One of them is the guarantee of Occupational Safety and Health (K3) levels provided by the company to employees, a supportive work environment, and employee motivation. The aim of this research is to determine the influence of Occupational Safety and Health (K3), Work Environment and Motivation. The sample in this study was 66 respondents. The data was then analyzed using the multiple regression method. The results of the research show that Occupational Health and Safety (K) has a partial positive and significant effect, the work environment has a partial positive and significant effect, motivation has a partial positive and significant effect, and Occupational Health and Safety, Work Environment, and Motivation have a positive and significant effect simultaneously on the performance of PT. Sawit Kaltim Lestari.

Reinforcement learning for distributed transient frequency control with stability and safety guarantees

This paper proposes a reinforcement learning-based approach for optimal transient frequency control in power systems with stability and safety guarantees. Building on Lyapunov stability theory and safety-critical control, we derive sufficient conditions on the distributed controller design that ensure the stability and transient frequency safety of the closed-loop system. Our idea of distributed dynamic budget assignment makes these conditions less conservative than those in recent literature, so that they can impose less stringent restrictions on the search space of control policies. We construct neural network controllers that parameterize such control policies and use reinforcement learning to train an optimal one. Simulations on the IEEE 39-bus network illustrate the guaranteed stability and safety properties of the controller along with its significantly improved optimality.

Adversarial Robustness of Neural Networks From the Perspective of Lipschitz Calculus: A Survey

We survey the adversarial robustness of neural networks from the perspective of Lipschitz calculus in a unifying fashion by expressing models, attacks and safety guarantees, that is, a notion of measurable trustworthiness, in a mathematical language. After an intuitive motivation, we discuss algorithms to estimate a network’s Lipschitz constant, Lipschitz regularisation techniques, robustness guarantees, and the connection between a model’s Lipschitz constant and its generalisation capabilities. Afterwards, we present a new vantage point regarding minimal Lipschitz extensions, corroborate its value empirically and discuss possible research directions. Finally, we add a toolbox containing mathematical prerequisites for navigating the field (Appendix).

Stability analysis of pumped storage hydropower plant in abandoned open-pit mine affected by dynamic surface subsidence of combined mining.

The construction of a pumped storage hydropower plant (PSHP) in an abandoned open-pit mine is a potential alternative to green mining and energy storage, which can increase the utilization rate of renewable energy and develop residual resources of abandoned mines. Dynamic surface subsidence affected by combined underground and open-pit mining (CUOPM) seriously affects the construction and operation of the PSHP and is one of the critical scientific issues that needs to be solved immediately. The stability of the PSHP was analyzed and treatment scheme of the goafs was proposed based on on-site measurement, theoretical analysis, and numerical simulation. First, the distribution of goafs in the Haizhou open-pit mining area was investigated and surface subsidence value was obtained using InSAR technology and ground monitoring. Secondly, the surface subsidence mechanism affected by CUOPM is analyzed and indicates the subsidence maximum values and scope of influence are greater than those of single underground mining. A dynamic surface subsidence prediction model for combined mining is established based on the Knothe time function model. Thirdly, based on the CVISC model, the numerical calculation models were established by using FLAC3D, and the characteristics and laws of surface subsidence in different periods of CUOPM were studied. The comparative analysis of the observation results shows that the proposed model and numerical simulation calculation method have excellent applicability and accuracy. Finally, a stability evaluation method of PSHP was established, and the results of the evaluation show that the affected areas are the semi-ground powerhouse (SGPH) and the west side of the lower reservoir. The method of grouting filling was used to treat the goafs, and the results showed that it effectively alleviates the dynamic surface subsidence affected by CUOPM, and provides a safety guarantee for PSHP.

Cerise: Program Verification on a Capability Machine in the Presence of Untrusted Code

A capability machine is a type of CPU allowing fine-grained privilege separation using capabilities , machine words that represent certain kinds of authority. We present a mathematical model and accompanying proof methods that can be used for formal verification of functional correctness of programs running on a capability machine, even when they invoke and are invoked by unknown (and possibly malicious) code. We use a program logic called Cerise for reasoning about known code, and an associated logical relation, for reasoning about unknown code. The logical relation formally captures the capability safety guarantees provided by the capability machine. The Cerise program logic, logical relation, and all the examples considered in the paper have been mechanized using the Iris program logic framework in the Coq proof assistant. The methodology we present underlies recent work of the authors on formal reasoning about capability machines [Georges et al. 2021 ; Skorstengaard et al. 2019a ; Van Strydonck et al. 2022 ], but was left somewhat implicit in those publications. In this paper we present a pedagogical introduction to the methodology, in a simpler setting (no exotic capabilities), and starting from minimal examples. We work our way up to new results about a heap-based calling convention and implementations of sophisticated object-capability patterns of the kind previously studied for high-level languages with object-capabilities, demonstrating that the methodology scales to such reasoning.

INTERNATIONAL LEGAL MECHANISM FOR ENSURING ENVIRONMENTAL SECURITY IN UKRAINE DURING THE CONDITIONS OF MARITAL STATE

The article highlights the results of the study of the problem of international legal guarantee of environmental safety in the conditions of the legal regime of martial law, which is extremely relevant for Ukraine. It is noted that the occurrence of threats and risks to human life and health, which often lead to a critical state of the environment, requires the search for optimal ways to eliminate their consequences in the event of environmental emergencies and their possible prevention. In this regard, a comprehensive state-legal mechanism, which provides for a number of measures and means aimed at supporting the provision of environmental safety, is of primary importance. It is primarily about the development and improvement of legislation in this field in the system of national security and defense, taking into account international experience. One of the most urgent issues regarding the negative impact is armed aggression, and there is precisely the impact on the environment during hostilities. Therefore, an integral direction of the adaptation of the legal system of Ukraine and the system of environmental protection supervision and control in the conditions of martial law is the improvement of the international legal mechanism for responding to environmental risks and threats, the possibility of their prevention through the involvement of international institutions in the ecological sphere of Ukraine.

Analysis of occupational health and safety management system internal audit implementation based on SMK3 PP No. 50, 2012 (Study at Pasuruan Concrete Industry, Indonesia)

Technological updates impact the risk of new hazards that can cause accidents and occupational diseases. The risk of hazards in the workplace is controlled through control efforts and the commitment of industries and workers to implementing the Occupational Health and Safety Management System. Indonesian manufacturing industries in implementing Occupational Health and Safety Management System are guided by SMK3 PP No. 50, 2012. Internal audit includes the fourth principle of occupational health and safety management system, namely monitoring and evaluating Occupational Health and Safety (OHS) performance. This research is descriptive research that aims to describe and analyze the application of occupational health and safety management system based on SMK3 PP No. 50, 2012 at Pasuruan Concrete Industry, Indonesia. Information sources are obtained from in-depth interviews, filling out document study checklist sheets, and field observations. The method to obtain in-depth interview informants through purposive sampling, with research informants is the party who has the authority and knowledge regarding the implementation of Occupational Health and Safety Management System in the Pasuruan Concrete Industry, Indonesia. Of the total 166 elements required by SMK3 PP No. 50, 2012, the company managed to fulfill as many as 160 elements, or 96%, with the category 'Satisfactory'. Overall, the company implements occupational health and safety management system progressively and sustainably, as evidenced by the increase in achieving the conformity of occupational health and safety management system audit internal elements and the guarantee of worker safety and health starting from management support, OHS programs, and the availability of adequate facilities and infrastructure.

Analysis of the Performance of the Transportation Agency in the Framework of Optimising the Safety Guarantee of Public Transport Passengers in Medan City (Study on Trans Metro Deli Buses)

This study aims to determine how the Performance of the Medan City Transportation Agency in the Framework of Optimising the Safety Guarantee of Public Transport Passengers in Medan City (Study on Trans Metro Deli Bus) using descriptive research methods with a qualitative approach. Data collection is done by interview, observation, and documentation techniques. Data were obtained through primary and secondary data and analysed using data reduction, data presentation, and conclusion drawing. The results of this study indicate that the performance of the Medan City Transportation Agency in the context of Optimising the Safety Guarantee of Public Transport Passengers in Medan City has been running well but there is still a need for supervision and a high sense of responsibility for the implementation and running of the Trans Metro Deli Bus and to further improve socialisation and good communication with passengers in order to attract their interest to always use the Bus because it is guaranteed safety, security and comfort.

Control of Autonomous Aerial Vehicles to Transport a Medical Supplies

Public health surveillance must guarantee the safety of people by limiting human mobility, in cases of isolation, through product deliveries, making it necessary to use drones to guarantee safety because they play a crucial role in several sectors. The literature review highlights the benefits of automation in-home delivery using drones, focusing on time efficiency and competitiveness in various sectors, and provides crucial design parameters to ensure its implementation in urban areas using different control techniques. A contribution was proposed to a solution that aims to realize the honeycomb design, which drones create during flight, controlled by a flight and delivery algorithm in a simulation environment applying an iterative methodology and continuous transport tests. medical burden. The results indicate a qualitative advance in the successful creation of simulated terrain, although the lack of numerical data on takeoffs and landings suggests the need for additional quantitative measurements. The current results support the efficiency of drones in route planning, precise management of medical cargo, and reduction of delivery time is numerical evidence that reinforces the robustness of the solution. In conclusion, this study developed a functional prototype to control drones with a flight planning algorithm and a swarm formation system for the transport of medical supplies in urban environments, although the need for future research to implement artificial intelligence technologies is noted. that improve transportation efficiency.

Community Service to Tandes Village Residents in the Form of Making Logo and Packaging Designs for Fermented Glutinous Rice Products

Small Medium Emeetrise (MSME) is a productive businessowned by individuals or business entities that meets the criteria for being a micro enterprise. MSME, because it is still a microbusiness, has many obstacles to develop. During COVID-19pandemic, many MSMEs in Tandes Village were forced to closetheir business. The level of demand also decreased significantly and thus led them near to bankruptcy. Through this program, we, Ciputra University students, are trying to contribute tosolutions to problems in society. This program aims to helpTandes village Fermented Glutinous Rice Products to be moreattractive and viable in various ways, that supports culinary tourism in Tandes village including marketing, trust, health and safety guarantees, and various other small product details. A visit to Tandes Village to provide support to MSMEs wascarried out on December 13, 2023. We all went there to handover the logo and packaging design. We also help promote theirproducts through our social media. From the results of ourpromotion, more than 20 product sales have been successfullycarried out and purchased by our relatives and friends.

Stability and Safety Learning Methods for Legged Robots

Learning-based control systems have shown impressive empirical performance on challenging problems in all aspects of robot control and, in particular, in walking robots such as bipeds and quadrupeds. Unfortunately, these methods have a major critical drawback: a reduced lack of guarantees for safety and stability. In recent years, new techniques have emerged to obtain these guarantees thanks to data-driven methods that allow learning certificates together with control strategies. These techniques allow the user to verify the safety of a trained controller while providing supervision during training so that safety and stability requirements can directly influence the training process. This survey presents a comprehensive and up-to-date study of the evolving field of stability certification of neural controllers taking into account such certificates as Lyapunov functions and barrier functions. Although specific attention is paid to legged robots, several promising strategies for learning certificates, not yet applied to walking machines, are also reviewed.