Level Risk Assessment Research Articles

Evaluation of Enterprise Financial Risk Level under Digital Transformation with Artificial Neural Network

With the continuous development of the national economy, enterprises have gradually entered the digital age from the industrial age, and digital transformation has become a must for enterprise survival. Digital transformation empowers the high-quality development of enterprises and puts forward higher requirements for financial risk management. The problem of enterprise financial risk is one that every business must deal with at some point during its operations. The digital age has ushered in a new era for enterprise financial risk management. Digital transformation is also a weather vane, which is beneficial to comprehensively avoid financial risks, do a good job in system defense and multiparty coordination, and can quickly and accurately manage corporate finances and solve risks in a timely manner. Starting from the background of digital transformation, this article clarifies the significance of preventing corporate financial risks in the new era. Combining it with artificial neural networks, this work proposes an intelligent method for assessing the financial risk level of enterprises in this context. This work proposes an EFRL-ResNet neural network, which is improved on the basis of ResNet. At the same time, the depth-wise separable convolution (DSConv) structure in Mobile-Net is combined with the ResNet network to build a lightweight deep neural network. Through the case of enterprise financial risk, it is verified that the method can reduce the training time of the model without losing the accuracy of grade evaluation. At the same time, this paper improves the loss function in the network model for the problem of an unbalanced number of data samples in the financial risk level assessment model.

Work Accident Analysis Using Hirarc Method (Hazard Identification, Risk Assessment And Risk Control) In Maintenance Division CV. Prosperous Utama Dira

Human resources are an important asset in a company and need to be developed. Human resource development is related to the performance generated in achieving the company's targets. The sustainability of human resource performance cannot be separated from work accidents. Many factors often cause work accidents such as: human error, electric shock, etc. This study aims to identify potential hazards, calculate risk level values, analyze the results of risk assessment calculations, and propose controls and solutions to reduce potential hazards and work accidents. The research was conducted in the maintenance division of CV. Dira Utama Sejahtera. It’s a manufacturing company engaged in the field of line pipe. The research was conducted using the Hazard Identification, Risk Assessment, and Risk Control (HIRARC) method. The results showed that there were 9 potential hazards, namely collision on the feet or head, electric shock, falling from the pipeline, pinched between pipelines, chemical explosion, hands hit by hot pipes, splashed by material, hands hit by drill bits, and slipped until the leg is sprained. The results of the risk level assessment that 11,1% fall into the category of low risk and extreme, 33,3% moderate risk, and 44,4% high risk. For risk control, it is proposed by elimination, administrative control, engineering control, and the use of Personal Protective Equipment (PPE).

Flood Hazard and Risk Mapping by Applying an Explainable Machine Learning Framework Using Satellite Imagery and GIS Data

Flooding is one of the most destructive natural phenomena that happen worldwide, leading to the damage of property and infrastructure or even the loss of lives. The escalation in the intensity and number of flooding events as a result of the combination of climate change and anthropogenic factors motivates the need to adopt real-time solutions for mapping flood hazards and risks. In this study, a methodological framework is proposed that enables the assessment of flood hazard and risk levels of severity dynamically by fusing optical remote sensing (Sentinel-1) and GIS-based data from the region of the Trieste, Monfalcone and Muggia Municipalities. Explainable machine learning techniques were utilised, aiming to interpret the results for the assessment of flood hazard. The flood inventory was randomly divided into 70%, used for training, and 30%, employed for testing. Various combinations of the models were evaluated for the assessment of flood hazard. The results revealed that the Random Forest model achieved the highest F1-score (approx. 0.99), among others utilised for generating flood hazard maps. Furthermore, the estimation of the flood risk was achieved by a combination of a rule-based approach to estimate the exposure and vulnerability with the dynamic assessment of flood hazard.

Health risk assessment of the population of the Republic of Buryatia associated with increased nitrate and nitrite intake

AIM: To conduct a hygienic assessment of the health risk levels associated with drinking water with high nitrate and nitrite contents in the rural territories of the Republic of Buryatia.
 MATERIAL AND METHODS: The content of nitrates and nitrites in drinking water in comparison with the maximum permissible concentrations (MPC) was assessed in the period of 20102019. With the use of the risk assessment methodology, non-carcinogenic risk (HQ) for adult and child populations of priority territories is calculated.
 RESULTS: In the territory of the Republic of Buryatia, two priority territories were identified according to the largest content of nitrates in the drinking water of a centralized cold water supply system: Mukhorshibirsky and Tarbagatai districts. The maximum nitrate concentrations reached 4.52 and 4.11 MPC, respectively, which are 1.71 and 1.45 times higher than in the previous five-year period, respectively. A similar situation was observed in the non-centralized water supply system in these areas, with 4.98 MPC in the Mukhorshibirsky district (1.88 times higher) and 3.41 MPC in Tarbagatai (2.53 times higher).
 CONCLUSIONS: The unacceptable level of non-carcinogenic risk due to nitrate contamination of drinking water at the level of the average centile trend (Me) is established for the adult and child population provided with centralized water supply in the Tarbagatai region. The HQ exceeds the acceptable level for children consuming decentralized drinking water in the Mukhorshibirsky district. The risk levels for children and adults due to oral intake of nitrites with drinking water of centralized and non-centralized water supply were not dangerous (HQ 1).

Оценка рисков в риск-ориентированных проверках подразделениями внутреннего аудита

The article combines the principles of risk management with the objectives of internal audit, defines and clarifies the concepts of risk management. Undoubtedly, external audit has a great influence on the formation of internal audit. This influence has both positive qualities, such as the use of the experience of highly qualified specialists from external audit, and a negative impact, due to the fact that external audit is primarily aimed at the confirmation of the financial statements of an organization, but in general does not consider business processes implemented in organizations, their effectiveness and adequacy to achieve organizations’ objectives, risks inherent in business processes. The article identifies the most important reason preventing the implementation of risk management principles in the Russian internal audit practice. The correlation of risk elements, which are sufficient for risk identification and risk level assessment within internal audit using a risk-oriented approach, has been disclosed. Based on the analysis of the essence of each risk element (risk source, event, consequence), their isolated role in assessing the likelihood of risk realization and the significance of the consequences, determining the necessity of risk management measures, has been determined. Using practical experience, the authors propose an algorithm of risk level assessment carried out within internal audit implementation. Possible qualitative and quantitative characteristics of determination of risk probability and materiality are considered. As part of the determination of the average likelihood of negative consequences’ occurrence, specific criteria of event likelihood assessment based on the history of similar events’ occurrence and the forecast assessment of likelihood of similar events’ occurrence are identified. Examples of determining the likelihood for each event within a group of events and the likelihood of occurrence of consequences in several groups of events are presented. Criteria for assessing the likelihood of risk realization are determined by establishing the set of events, whose simultaneous occurrence realizes the risk. Examples of financial and non-financial consequences and criteria for their assessment are given. In order to determine the elements of risk during internal audits, the essence of analytical procedures performed with the use of deductive and inductive methods is disclosed. At present, large Russian companies are taking certain steps to implement the principles of Industry 4.0 in their business processes. This trend has not passed unnoticed for internal audit; for example, principles of continuous audit and automated analysis of databases are being implemented. However, the implementation often ignores the main condition that this article discusses; without it implementation attempts will only lead to an irrational use of organizational resources. Contribution of the authors: the authors contributed equally to this article. The authors declare no conflicts of interests.

Risk based assessment of corroded oil drilling rig pipe integrity and remaining life

Risk based assessment of structural integrity of corroded oil drilling pipe is presented and applied on prototype (welded pressure vessel made of pipe) with artificial defects, which was previously investigated under service (10 MPa) and testing (22 MPa) pressure. The new concept based on application of structural integrity estimation to assess risk level according to probability and consequence of failure was used. Probability of failure is taken as the ratio of the service point, estimated by using the basic linear elastic fracture mechanics concept, and point on limit line in the Failure Analysis Diagramme (FAD). Taking into account measure of probability and consequence, the risk matrix is made for the round defect in a new pipe, 1.75 mm (depth) x 26 mm (length), service and testing pressure. Results are also compared with the previous ones for defects 3.5 × 28 mm and 5.25 × 30 mm. These results are useful for managers to make decision about further use of damaged pipes, based on data provided by engineers. The procedure for risk assessment of structural integrity is a general one, applicable to any component with known geometry, including crack, material properties and loading data, as well as to the structural life assessment.

Multi-vehicle interaction safety of connected automated vehicles in merging area: A real-time risk assessment approach

The risky lane-changing manoeuvre of vehicles often occurs at expressway entrances, which would result in a high crash risk in the freeway system and significantly impact its safety. The highly anticipated environment of connected and autonomous vehicles (CAVs) is expected to reduce the associated crash risk of lane changing by offering various types of driving support, which utilise surrounding traffic information. The modelling crash risk under the environment of CAV driving during mandatory lane changing in merging areas faces new challenges due to the novelty of CAVs and subsequent shortage of data. To explore such risk situation of multi-vehicle interaction at expressway entrances, this study proposed a supervised learning algorithm and a Bayesian hierarchical model to assess risk levels and predict the probability of risk occurrence at different risk levels of interactive vehicles in real time of mandatory driving behaviour during the merging process. The learning algorithm, based on XGBoost, was exploited to classify risk levels. The Bayesian hierarchical model was used to analyse the probability of real-time risk comprising vehicle physical state layer, multi-vehicle interaction layer and risk probability layer. The probabilistic model parameters were calibrated using Markov Chain Monte Carlo (MCMC) Gibbs sampling method. The K-fold cross validation method was used to validate the proposed model of risk level. The probabilistic model validity was tested through posterior prediction of P-value. The quantitative risk estimation of CAVs through a few merging cases was conducted. Results show that the identification accuracy of slight, low, moderate and high risk is 94.24%, 85.82%, 84.16% and 79.69%, respectively. The P-value of Durbin–Watson’s posterior, normal hypothesis, test distribution symmetry and kurtosis are all close to 0.5. Therefore, the method of real-time risk assessment is convergent and has good fitting. This research can promote cautious driving behaviours and provide reference for driver’s decision making in the long term under the environment of CAVs.

A cyber‐attack detection method for load control system based on cyber and physical layer crosscheck mechanism

Cyber-attack has become one of the main threats to the safe operation of the load control system in the distribution network. Currently, a large number of methods are developed to detect cyber-attacks. However, most of these methods make decisions based on information from a single cyber layer or physical layer. If the decision is wrong, there is no way to verify it. Therefore, if the separate decisions can be made in the cyber layer and physical layer at the same time, and a final judgment is received throughout the two decisions, then the accuracy and credibility of cyber-attack detection can be improved. First, the particle swarm optimization-based backpropagation neural network is adopted to detect attacks in the cyber layer, at the same time, the criteria importance though intercrieria correlation-based grey relational analysis is adopted for the assessment of node risk level in the physical layer. Then, based on the incidence matrix model between the cyber layer and the physical layer, a crosscheck mechanism is proposed to detect the cyber-attack through the verification of the two decisions. Finally, taking the IEEE 33-node system as an example, the validity of the proposed method to detect the denial of service attack is verified.

Analisis Risiko Teknologi Informasi Menggunakan Metode FMEA dan SAW dengan COBIT 5

The use of Information Technology (IT) in a university raises various problems, one of which is the understanding of risks its use. Universitas Quality Medan was identified as having no IT risk documents. This study aims to analyze and rank risks provide recommendations for improvements. Risk assessment is carried out on 9 business processes use COBIT 5 framework in domains APO12 and EDM03, the risk level assessment uses FMEA, for rank and recommendations using SAW. The current risk management process is still level 1 with the APO12 capability value of 1.36 and to be conditions at level 2 a capability value of 2.32 a gap of 0.96. EDM03 current condition is at level 1 a capability value of 1.19, while the expected condition at level 2 a capability value of 2.11 a gap value of 0.91. The results of the identification of risk levels in the APO12 have 3 risk level processes on a scale of 6, 1 process a scale of 7, and 2 processes a scale of 8. For EDM03, have 2 risk level processes a scale of 9 and 1 process level of risk on a scale 8. Priority of risks and recommendations for APO12 is subdomains APO12.06 (Respond to Risk) the most priority to improve management process, and for EDM03 subdomains is the priority for improvement in EDM03.03 (Monitor Risk Management)

A risk-level assessment system based on the STRIDE/DREAD model for digital data marketplaces

Security is a top concern in digital infrastructure and there is a basic need to assess the level of security ensured for any given application. To accommodate this requirement, we propose a new risk assessment system. Our system identifies threats of an application workflow, computes the severity weights with the modified Microsoft STRIDE/DREAD model and estimates the final risk exposure after applying security countermeasures in the available digital infrastructures. This allows potential customers to rank these infrastructures in terms of security for their own specific use cases. We additionally present a method to validate the stability and resolution of our ranking system with respect to subjective choices of the DREAD model threat rating parameters. Our results show that our system is stable against unavoidable subjective choices of the DREAD model parameters for a specific use case, with a rank correlation higher than 0.93 and normalised mean square error lower than 0.05.

Analisis tingkat risiko ergonomi pada pekerja Welding (Pengelasan) dengan Metode Rapid Entire Body Assessment (REBA)

Introduction: Diseases caused by work become a common health problem and can affect almost all people in the world. As you can see, one of the hazards in the field is ergonomics. The danger from bad posture at work is the cause of the position of the body parts moving uncomfortably which can cause various problems at work, both health problems and work accident problems. Therefore, so that a job does not pose a dangerous risk, it is necessary to have an assessment of ergonomic risk. Researchers aim to analyze the level of ergonomic risk to Welding workers with the Rapid Entire Body Assessment (REBA) Method in the Workshop area of PT. Cemindo Gemilang Bayah Banten in 2020.
 Methods: This research uses mix methods, which is a research step by combining two forms of research approaches, namely qualitative and quantitative. The subjects in this study were the main informants and key informants totaling 4 people. The main informants in this study were 3 welding workers. The key informant is 1 person, namely HSE.
 Results: The results of the risk level assessment using the REBA method for welding workers are obtained from the scoring of group A with a value of 8 and the results of scoring for group B with a value of 4, then the total results of C to the scoring of groups A and B have a value of 10.
 Discussion: Based on the Action Level Score, REBA score 10 shows a high level of risk. 3 people out of 4 workers are known to be at high risk of pain so further review and implementation of changes / immediate action are required.

Indeks dan Tingkat Risiko Bahaya Longsor pada Ruas Jalan Nasional di Kabupaten Kerinci dan Kota Sungai Penuh, Provinsi Jambi

The Regency of Kerinci and The City of Sungai Penuh are areas that prone to landslides. In 2021 and 2021, were 13 landslides on national road sections in both, which disrupted access to both areas. This study aims to calculate the index and determine the risk level of landslides on roads and bridges on national roads in both regions. Assessment methods and variables are taken based on the Guidelines for the Implementation of Risk Analysis for Natural Disasters Affecting Roads and Bridges. The index and risk level assessment are carried out by analyzing the risk factors for landslides, namely: hazard, exposure, vulnerability, external context, and capacity. The mapping of landslide risk based on Geographic Information Systems is based on scoring and weighting in all parameters, as well as overlays among all the constituent parameters. Based on the results of the study on ten national roads (with a total road length of 82.50 km) in the study area into two classes, namely: (a) low class (= 8.72%) on 7 roads located within the city, and (b) medium class (= 91.28%) on three roads connecting the cities.

Leveraging Artificial Intelligence (AI) Capabilities for COVID-19 Containment.

The Coronavirus disease (COVID-19) is an infectious disease caused by the newly discovered Severe Acute Respiratory Syndrome Coronavirus two (SARS-CoV-2). Most of the people do not have the acquired immunity to fight this virus. There is no specific treatment or medicine to cure the disease. The effects of this disease appear to vary from individual to individual, right from mild cough, fever to respiratory disease. It also leads to mortality in many people. As the virus has a very rapid transmission rate, the entire world is in distress. The control and prevention of this disease has evolved as an urgent and critical issue to be addressed through technological solutions. The Healthcare industry therefore needs support from the domain of artificial intelligence (AI). AI has the inherent capability of imitating the human brain and assisting in decision-making support by automatically learning from input data. It can process huge amounts of data quickly without getting tiresome and making errors. AI technologies and tools significantly relieve the burden of healthcare professionals. In this paper, we review the critical role of AI in responding to different research challenges around the COVID-19 crisis. A sample implementation of a powerful probabilistic machine learning (ML) algorithm for assessment of risk levels of individuals is incorporated in this paper. Other pertinent application areas such as surveillance of people and hotspots, mortality prediction, diagnosis, prognostic assistance, drug repurposing and discovery of protein structure, and vaccine are presented. The paper also describes various challenges that are associated with the implementation of AI-based tools and solutions for practical use.

INDEX AND RISK LEVEL OF LANDSLIDES ON ROAD AND BRIDGES LOCATED ON NATIONAL ROADS (CASE STUDY: KERINCI DISTRICT AND SUNGAI PENUH CITY, JAMBI PROVINCE)

The regency of Kerinci and The city of Sungai Penuh are among the areas prone to landslides, which can impact roads and bridges on national roads. This study aims to determine the index and risk level of landslides on roads and bridges located on national roads in both regions. The index and risk level assessment are carried out by analyzing disaster risk factors, namely: hazard, exposure, vulnerability, external context and capacity. Assessment methods and variables are taken based on the Guidelines for the Implementation of Risk Analysis for Natural Disasters Affecting Roads and Bridges. The mapping of landslide risk based on the Geographical Information System is compiled based on scoring and weighting all parameters, as well as an overlay among all constituent parameters. Based on the sampling results of ten samples of national road sections in the Kerinci Regency and Sungai Penuh City, the risk level of hazard, exposure, vulnerability, external context and road management capacity is divided into two classes, namely the Low class about 7.19 km (= 8.72 %) with seven short roads located within the city and the Medium class, which is 75.31 Km (= 91.28 %), with three roads connecting the cities.

Application of Collision Warning Algorithm Alarm in Fishing Vessel’s Waterway

The aim of this study is to apply a collision warning algorithm for a small fishing vessel in a fishing waterway to verify its alarm operation and to validate its feasibility. For this purpose, a scenario-based real ship test was conducted, and cases extracted from real sea data (Vpass data) were applied. Moreover, zones with frequent alarms and high-risk waters were compared. First, we installed millimeter-wave communication terminals in three small fishing vessels and applied our algorithm based on two scenarios. Furthermore, we applied the collision warning algorithm by extracting two cases encountered by multiple ships from the Vpass data. The results show that the algorithm triggered alarms continuously under risky situations. This study also compares waterway risk levels as assessed by maritime risk-assessment tools (potential assessment of risk model, environment stress model, and International Association of Marine Aids to Navigation and Lighthouse Authorities Waterway Risk Assessment Program MkII) and the locations having frequent alarms based on Vpass data collected for 7 days. Not only did the eastern sea of Yeongheung Island indicate that more alarms were triggered, but we found high-risk results from the risk-level assessment, indicating that the risky zones and the frequent alarm zones were identical. Additional research is necessary to develop an algorithm based on qualitative evaluation by actual ship operators. In addition, since fishing vessels navigate differently from general navigation methods during fishing, it is necessary to develop additional algorithms for this.

Image‐based road crack risk‐informed assessment using a convolutional neural network and an unmanned aerial vehicle

Rapid crack assessment is widely thought to be critical for monitoring and maintaining roads in appropriate conditions. In this paper, a novel crack-affected risk-informed assessment framework is proposed for the monitoring and maintenance of roads. The framework includes five steps: data collection, crack detection, crack location extraction, crack real-size calculation, and risk-level assessment. To support the framework, an unmanned aerial vehicle (UAV) is used to monitor roads and collect data. A state-of-the-art semantic segmentation network, DeepLabv3+, is also applied to detect cracks. Based on the height and pixel statistics of the detected crack, the real size of the crack can be calculated using the pixel-physical conversion coefficient equation. This is followed by a risk-informed assessment of the road identifying the location of the crack for maintenance priority determination. Data collection and experiments using a UAV were performed on a real road to verify the feasibility and effectiveness of the proposed method. It was found that the proposed method was not only able to determine the real size of the cracks from the collected images but also able to determine their risk levels. In summary, this method presents a convenient and reliable solution for risk-informed road crack assessment that can be employed in practical applications.

Integrated Model for Soft Drink Industry Supply Chain Risk Assessment: Implications for Sustainability in Emerging Economies

Recently, the soft drink industry has been confronted with a rapidly changing business climate and increased competition, creating risks and uncertainties in its supply chain. Thus, immediate actions are required to handle these risks and uncertainties. The purpose of this paper is to identify and classify these risks in the soft drink supply chain and to develop a methodology comprising a fuzzy analytical hierarchy process (FAHP) and fuzzy comprehensive evaluation of these risks. FAHP was used to determine the weights of five major risk categories and 23 sub risks under these major categories. Afterward, a fuzzy comprehensive evaluation method (FCEM) was applied for the assessment of overall risk level, risk levels of the five major categories and relative risk levels of the 23 sub risks. This research has been conducted focusing on the soft drink industry of Bangladesh, a developing country with an emerging economy. In the existing literature, this work contributes by identifying and evaluating risks in the soft drink supply chain in the context of Bangladesh. The outcome of this study indicates that the overall risk level in the supply chain of the soft drink industry is between low and medium, and the risk level of the demand risks is the highest whereas the risk level of infrastructural risks is the lowest. It was also found that loss of reputation and brand image is the most significant sub risk, and natural disasters are the least significant sub risk.

Анализ управления профессиональными рисками на предприятиях при эксплуатации грузоподъемного оборудования

The model for assessing the levels of occupational risks was introduced and is used at the mechanical engineering enterprises during lifting equipment operation. The analysis of injuries carried out six months after the start of its use and familiarization of employees with the register and the level of hazards showed a decrease in risk levels in relation to previous periods. The results of the study of the procedure for managing occupational risks when working on three types of cranes are presented: electric bridge crane; gantry crane and single-girder electric supporting bridge crane. The first two listed cranes are installed at hazardous production facilities. After drawing up a plan for assessing occupational risks at the stage of risk identification, the method of questionnaires was used to collect information about production processes and determine the register of hazards. To analyze the work of the occupational health and safety management system, a multi-level control of the technological process and ensuring its safety was introduced. In practice, the relevance and availability of the Fine — Kinney method for assessing the levels of occupational risks was confirmed. When studying the significance of the impact of the procedures (elements) of the occupational health and safety management system on the probability of a hazard and, consequently, on the final level of occupational risk, the method of expert assessments was used. The methods for formalizing assessment results proposed and implemented in the organizations reflect all the stages of the process and provide answers at any stage of the study of the occupational risk levels. The measures developed based on the results of the assessment of occupational risk levels allow to maintain safe working conditions and prevent the occurrence of hazards that lead to injuries at work.

Assessment of Risk and Emergency Knowledge Level - Cardiovascular Emergencies in Rural Communities Sungai Nagara, Margasari Village, Tapin, South Kalimantan

Background Cardiovascular disease contributes to a massive mortality rate in the world and also in Indonesia. Assessment of the risk and level of knowledge of cardiac emergency symptoms needs to be carried out, especially in rural areas where access to cardiovascular treatment is far.Purposes This study aims to assess risk stratification and the level of knowledge. The method of measuring risk and level of knowledge was carried out on 100 Margasari Ilir respondent who were over 40 years old and carried out using the stratified random sampling method during September 2020—measuring risk using the instrument Framingham Risk Score and the level of knowledge using the ACS Response Index.Result The average age of respondents was 54.98 years, 30 men (30%) and 70 women (70%), 22 smokers (22%), seven diabetes mellitus (7%), 11 people ( 11%) had high cholesterol, 41 people (41%) had hypertension, and 33 people (33%) had low HDL levels. The number of people who have a high risk of emergency - cardiovascular emergency is seven people (7%), 24 people are at moderate risk (24%), and 69 people are at low risk (69%). The level of knowledge about cardiac emergencies is in the low category of 80 people (80%), 19 people (19%), and one high (1%).Conclusion It is necessary to increase public knowledge about cardiovascular emergencies.

Determining the Probability of Cyberattacks

Abstract The use of information is inextricably linked with its security. The presence of vulnerabilities enables a third party to breach the security of information. Threat modeling helps to identify those infrastructures, which would be most likely exposed to cyberattacks. In some cases, however, threat modeling can not be classified as sufficient method of protection. This paper entitled “Determining the probability of cyberattacks” presents an analysis of different techniques with an attempt to identify the most informative parameters and cyberattack prediction markers, which would lay the foundation for the development of cyberattack probability functions. Next, it would be relevant to design such cyberattack probability functions, which would be used upon the initial identification of a cyberattack. The findings of this research could be applied during the future assessment of risk levels of information systems to ensure more effective information security management.