Implementation Of Countermeasures Research Articles

Implementation of Road Safety Countermeasures in Four Cities to Reduce the Harmful Effects of Alcohol: A Progress Report

Implementation of Road Safety Countermeasures in Four Cities to Reduce the Harmful Effects of Alcohol: A Progress Report

Secure UAV-Aided Mobile Edge Computing for IoT: A Review

As the Internet of Things (IoT) ecosystem evolves, innovative applications with stringent demands with respect to latency will emerge. To handle computation-intensive tasks in a timely manner, data offloading to Mobile Edge Computing (MEC) servers has been suggested. On the other hand, prospective IoT networks are expected to include Unmanned Aerial Vehicles (UAVs) to enhance coverage and connectivity, while retaining reliable communication links with ground nodes in urban, suburban, and rural terrain. Nevertheless, the evolution of UAV-aided MEC-enabled IoT presupposes the mitigation of security threats through the implementation of efficient and robust countermeasures. As UAVs inherently have certain limitations in terms of energy, computational, and memory resources, designing lightweight security solutions is required. This paper provides an overview of the UAV-aided MEC-enabled IoT and a detailed presentation of use cases and application scenarios, where security is of utmost importance. Subsequently, up-to-date research works on security solutions for the UAV-aided MEC-enabled IoT are comprehensively presented. To this end, the adoption of information-theoretic techniques that ensure adequate Physical-Layer Security (PLS) is discussed along with sophisticated security approaches based on emerging technologies, such as Blockchain and Machine Learning (ML). In addition, research studies on software- and hardware-based methods for the identification and authentication of network nodes are presented. Finally, this paper provides future perspectives in this research domain, stimulating further work.

Determinants of Implementation of Countermeasures to Climate Change Risk

Determinants of Implementation of Countermeasures to Climate Change Risk

Points of Consideration on Climate Adaptation of Solar Power Plants in Thailand: How Climate Change Affects Site Selection, Construction and Operation

Solar energy is planned to undergo large-scale deployment along with Thailand’s transformation to a carbon neutral society in 2050. In the course of energy transformation planning, the issue of energy infrastructure adaptation to climate change has often been left out. This study aims to identify climate-related risks and countermeasures taken in solar power plants in Thailand using thematic analysis with self-administered observations and structured interviews in order to propose points of consideration during long-term energy planning to ensure climate adaptation capacity. The analysis pointed out that floods and storms were perceived as major climate events affecting solar power plants in Thailand, followed by lightning and fires. Several countermeasures were taken, including hard countermeasures that require extensive investment. Following policy recommendations were derived from the climate-proofing investment scenario study. Policy support in terms of enabling regulations or financial incentives is needed for implementation of climate-proofing countermeasures. Public and private sectors need to secure sufficient budget for fast recovery after severe climate incidents. Measures must be taken to facilitate selection of climate-resilient sites by improving conditions of power purchase agreement or assisting winning bidders in enhancing climate adaptability of their sites. These issues should be considered during Thailand’s long-term energy planning.

Development of exact and heuristic optimization methods for safety improvement projects at level crossings under conflicting objectives

A significant number of accidents occur each year at level crossings globally. Substantial efforts are being made by different railway authorities and other stakeholders to prevent accidents by installing various countermeasures at level crossings (e.g., mountable curbs, two-quad gates, four-quad gates). However, due to budgetary constraints, it is not possible to deploy countermeasures at all level crossings. Besides, countermeasures have certain effectiveness factors and the associated installation cost. Usually, the cost of the countermeasure increases with its effectiveness. Therefore, it is essential to select the most effective countermeasures at the riskiest level crossings. The implementation of countermeasures at level crossings may lead to certain negative externalities as well. In particular, the deployment of countermeasures can result in a decreased traffic flow, causing traffic delays and adversely affecting the continuity of freight and passenger train movements. This study proposes a multi-objective mathematical model for resource allocation among level crossings, which aims not only to minimize the total hazard severity due to potential accidents but the associated traffic delays as well. Exact and heuristic solution approaches are designed to solve the developed multi-objective model. A set of computational experiments are conducted for the level crossings located in the State of Florida (United States). The results demonstrate superiority of the exact optimization method, as it obtained optimal Pareto Fronts within acceptable computational time. Moreover, a number of sensitivity analyses are conducted to showcase certain managerial insights that would be of interest to railway authorities and other stakeholders involved in level crossing safety improvements.

Implementation of Organized Cyber Crime Countermeasures Against National Investment

Internet abuse is also evidenced by the frequent discovery of crimes through the internet network. Internet abuse is also evidenced by the frequent discovery of crimes through the internet network. The implementation of online transactions there are also those who use social media, but many parties who abuse social media transactions as well as fraud crimes. Misuse of crimes against matters related to data and systems on computers should get special attention because it is related to confidentiality. The implementation of organized cyber crime countermeasures against national investments can be in the form of improvement of legal tools, education and training of traditional human resources, researchers' abilities, evidence tools and inadequate computer tools. To overcome the obstacles identified in cybercrime investigations, legal instruments, researcher training, appropriate facilities can be built, enhance an international investigation and participation effort, and make efforts to get out of cybercrime. The legal system in Indonesia does not separately manage computer crime through the internet world. Obstacles found in cybercrime investigations include related to legal issues. Keywords: Implementation, Cyber Crime, Countermeasures. DOI: 10.7176/JLPG/115-06 Publication date: November 30 th 2021

Spatiotemporal distribution of COVID-19 during the first 7\xa0months of the epidemic in Vietnam

BackgroundUnderstanding the spatiotemporal distribution of emerging infectious diseases is crucial for implementation of control measures. In the first 7 months from the occurrence of COVID-19 pandemic, Vietnam has documented comparatively few cases of COVID-19. Understanding the spatiotemporal distribution of these cases may contribute to development of global countermeasures.MethodsWe assessed the spatiotemporal distribution of COVID-19 from 23 January to 31 July 2020 in Vietnam. Data were collected from reports of the World Health Organization, the Vietnam Ministry of Health, and related websites. Temporal distribution was assessed via the transmission classification (local or quarantined cases). Geographical distribution was assessed via the number of cases in each province along with their timelines. The most likely disease clusters with elevated incidence were assessed via calculation of the relative risk (RR).ResultsAmong 544 observed cases of COVID-19, the median age was 35 years, 54.8% were men, and 50.9% were diagnosed during quarantine. During the observation period, there were four phases: Phase 1, COVID-19 cases occurred sporadically in January and February 2020; Phase 2, an epidemic wave occurred from the 1st week of March to the middle of April (Wave 1); Phase 3, only quarantining cases were involved; and Phase 4, a second epidemic wave began on July 25th, 2020 (Wave 2). A spatial cluster in Phase 1 was detected in Vinh Phuc Province (RR, 38.052). In Phase 2, primary spatial clusters were identified in the areas of Hanoi and Ha Nam Province (RR, 6.357). In Phase 4, a spatial cluster was detected in Da Nang, a popular coastal tourist destination (RR, 70.401).ConclusionsSpatial disease clustering of COVID-19 in Vietnam was associated with large cities, tourist destinations, people’s mobility, and the occurrence of nosocomial infections. Past experiences with outbreaks of emerging infectious diseases led to quick implementation of governmental countermeasures against COVID-19 and a general acceptance of these measures by the population. The behaviors of the population and the government, as well as the country’s age distribution, may have contributed to the low incidence and small number of severe COVID-19 cases.

Accident susceptibility index for a passenger ship-a framework and case study

The continuous monitoring and assessment of operational vulnerability and accident susceptibility of passenger ships is crucial from the perspective of ship and passenger safety. Despite the existing solutions for vulnerability monitoring, stemming mainly from watertight door operations, a comprehensive framework for accident susceptibility assessment and monitoring is missing in the literature.Therefore, this paper offers a straightforward approach, utilizing heuristics rooted in the solid foundations of the first principles related to human performance. The proposed approach allows the evaluation of accident susceptibility of a ship in operation involved in open-sea and coastal navigation. The framework presented is based on observable and relevant factors, known to affect the navigator's performance, and as a consequence accident probability. The layout of the framework as well as the parameters of the developed model are based on literature survey in maritime and aviation domains, knowledge elicited from maritime experts and extensive simulations with the use of an in-house developed ship-ship encounter simulator. Subsequently, the model is applied to selected case studies, involving two distinctive ship types, namely a large cruise ship and a RoPax vessel.The results obtained for the case study presented in this paper reveal that most of their time the analyzed ships operate with negligible accident susceptibility (87%), while 1% of the cases are labelled as very high accident susceptibility. The remaining share of 12% is distributed among low, moderate and high values of accident susceptibility. The results are in line with earlier studies conducted in the same area but adopting different methods.The proposed solution can be applied as an onboard decision support tool, evaluating the operational accident susceptibility and vulnerability, thus increasing the crew's situational awareness. Additionally, it can be applied to historical data, allowing ship navigational safety diagnosis and implementation of appropriate countermeasures.

Lessons learned from the 2011 Great East Japan Earthquake: A case study of tsunami risk assessment in a Japanese chemical corporation

AbstractNatural hazard triggering technological disasters (Natech) pose a major risk to chemical industries. Natural disasters, such as earthquakes, floods, and tsunamis, may cause massive fires, explosions, and toxic chemical release into the environment. Thus, Natech risks have recently attracted considerable research attention. Although Natech‐related case studies are seldom reported in the literature, the results obtained thereof facilitate concrete risk assessments and countermeasure implementation against natural hazards. This article presents a case study on tsunami risk assessment performed by Asahi Kasei Corporation, Japan, based on four steps: (1) review of Natech events caused by the 2011 Great East Japan Earthquake, (2) hazard identification at the plant, (3) risk assessment considering human casualties, equipment loss, environment, and business continuity, and (4) evaluation and implementation of appropriate countermeasures. The risks posed by tsunamis were identified and analyzed. The inundation heights of Level‐1 and Level‐2 tsunamis were estimated to be 1 and 10 m, respectively. A tsunami evacuation tower and tidal wall were built as appropriate countermeasures to prevent or mitigate fatalities, loss of containment, and business interruption. The results obtained in this study facilitate adequate preparedness of chemical plants against future tsunami occurrences.

Determinants of Preventive Behaviors for COVID-19 in Japan.

As of June 2021, there have been more than 13,000 deaths in Japan due to the COVID-19 pandemic. Data from the Ministry of Health, Labor, and Welfare show that the mortality rate of COVID-19 greatly varies by age. In this study, using data from a questionnaire survey, an investigation was carried out to find differences in anxiety and risk perception, attitudes toward risk, and the frequency of implementation of countermeasures to infection among age groups that are prone to a greater risk of mortality, as well as the main factors that determine the frequency of implementation. Older people, who form a high-risk group, have a stronger tendency for anxiety and cautious attitudes toward COVID-19, and they more frequently implement preventive behaviors. The results of multiple regression analysis showed that the frequency of implementation of behaviors is determined not only by anxiety, cautious attitude, risk of aggravation to oneself, and perceived effectiveness of behaviors but also by regret, altruism, and conformity. In addition, almost no age-based gap was found between the determinants, suggesting that the motivation to take infection preventive behaviors is the same regardless of age.

Image Processing for the Prevention of Infectious Diseases: Determination of Mask Wearing, Measurement of Hand Washing Time, and Disinfection Support System.

The new coronavirus infection (COVID-19) has spread to numerous countries around the world since several cases of the disease were first reported in late December 2019 in China. Currently, the WHO strongly recommends infection prevention measures such as wearing masks, hand washing, and frequent disinfection of high-touch surfaces, but there were many arguments against infection prevention policy in March 2020. For example, the WHO did not recommend the use of masks for the healthy general public. In Japan, wearing a mask was required before the habit of wearing a mask was established, which gave additional works of checking whether customer was wearing a mask to the employees. To reduce the workloads of employee and ensure mask-wearing, we started providing the mask-wearing system free of charge on March 5, 2020. We also developed hand washing time estimation and disinfection support system. It is useful to accumulate data on the status of implementation of countermeasures by our application, which leads to gain useful knowledge regarding countermeasures against COVID-19 as well as other infectious diseases. In this paper, we describe the development and introduction impacts of these systems in a pandemic emergencies. In addition, because of the security and privacy issues in running these image analysis applications, we discuss the delivery methods suitable for each service.

Establishment of epidemic early warning index system and optimization of infectious disease model: Analysis on monitoring data of public health emergencies

The ability to mitigate the damages caused by emergencies is an important symbol of the modernization of an emergency capability. When responding to emergencies, government agencies and decision makers need more information sources to estimate the possible evolution of the disaster in a more efficient manner. In this paper, an optimization model for predicting the dynamic evolution of COVID-19 is presented by combining the propagation algorithm of system dynamics with the warning indicators. By adding new parameters and taking the country as the research object, the epidemic situation in countries such as China, Japan, Korea, the United States and the United Kingdom was simulated and predicted, the impact of prevention and control measures such as effective contact coefficient on the epidemic situation was analyzed, and the effective contact coefficient of the country was analyzed. The paper strives to provide early warning of emergencies scientifically and effectively through the combination of these two technologies, and put forward feasible references for the implementation of various countermeasures. Judging from the conclusion, this study reaffirmed the importance of responding quickly to public health emergencies and formulating prevention and control policies to reduce population exposure and prevent the spread of the pandemic.

Automotive Ground Vehicles' Resilience to HEMP Attack: An Emergency Management Mitigation Plan

United States exposure to attack from a nuclear weapon of mass destruction (WMD) optimized to generate a high‐altitude electromagnetic pulse (HEMP) is a concern in national security forums. Such an attack could lead to widespread damage to the electrical components of many critical infrastructures. The purpose of this study was to develop a framework to better understand the hazard risks from a HEMP attack on non‐military (non‐MIL), “electronics‐heavy” automotive ground vehicles that could inform an effective emergency management response and recovery plan. A hybrid emergency management and engineering hazards risk analysis utilizing a Failure Modes and Effects Analysis (FMEA) format helped visualize the critical vehicle electronics subsystems and components, and their respective potential failure modes. A design of experiments test plan was developed to quantify the risks, and to develop a pathway to validate cost‐effective mitigation countermeasures based on present‐day best practices for HEMP hardening. The proposed emergency management plan emphasized strategic implementation of HEMP mitigation countermeasures to support continuity in emergency services and delivery of community lifelines to the public. The results of this study will serve as a foundation for future HEMP projects with automotive ground vehicles that will support the FEMA National Preparedness Goal, Presidential Executive Order 13865, and the recent FY2020 National Defense Authorization Act (NDAA) legislation. The methodologies can also apply to other critical infrastructure segments.

Current status of the environmental monitoring database on the accident at Fukushima Daiichi Nuclear Power Plant

An enormous amount of environmental monitoring data has been acquired by various organisations for the evaluation and implementation of countermeasures to mitigate the effects of the accident at the Fukushima Daiichi Nuclear Power Plant. However, it is difficult to collate, compare, and analyse this data because it was published in different formats at different sites according to the respective objectives of the publishing organisations. Moreover, these organisations have been accumulating data in large volumes for over nine years after the accident. We established procedures to collect this data, convert them into a unified format, classify them according to categories, and make the data accessible on a web-based database system. The database contains environmental monitoring data on air dose rates, ground deposition densities, and concentrations in various environmental samples such as soil, water, and food. This data is being provided not only in numerical format for quantitative analysis but also as distribution maps and time-series graphs for visual understanding. The database system enabled us to spatially and temporally compare large volumes of monitoring data. By using the database functions, characteristics of some representative data in the database was clarified.

FIVER – Robust Verification of Countermeasures against Fault Injections

Fault Injection Analysis is seen as a powerful attack against implementations of cryptographic algorithms. Over the last two decades, researchers proposed a plethora of countermeasures to secure such implementations. However, the design process and implementation are still error-prone, complex, and manual tasks which require long-standing experience in hardware design and physical security. Moreover, the validation of the claimed security is often only done by empirical testing in a very late stage of the design process. To prevent such empirical testing strategies, approaches based on formal verification are applied instead providing the designer early feedback.In this work, we present a fault verification framework to validate the security of countermeasures against fault-injection attacks designed for ICs. The verification framework works on netlist-level, parses the given digital circuit into a model based on Binary Decision Diagrams, and performs symbolic fault injections. This verification approach constitutes a novel strategy to evaluate protected hardware designs against fault injections offering new opportunities as performing full analyses under a given fault models.Eventually, we apply the proposed verification framework to real-world implementations of well-established countermeasures against fault-injection attacks. Here, we consider protected designs of the lightweight ciphers CRAFT and LED-64 as well as AES. Due to several optimization strategies, our tool is able to perform more than 90 million fault injections in a single-round CRAFT design and evaluate the security in under 50 min while the symbolic simulation approach considers all 2128 primary inputs.

Towards improving sustainability of rail transport by reducing traffic delays at level crossings: A case study for the State of Florida

Rail transport makes a significant contribution to the economy of many geographical locations around the globe. Along with numerous merits, rail transport has some demerits as well, such as traffic delays and safety issues at level crossings. Traffic delays at level crossings have various negative impacts, including economic losses, increasing number of violations because of delays, queue spillbacks at the adjacent intersections, and environmental impacts. This study reviews a number of level crossing delay estimation approaches found in the literature. Based on the state-of-the-art review and practical considerations, a new approach for estimation of the overall traffic delay per day at level crossings with the existing warning devices is proposed to improve the sustainability of rail transport. Moreover, in order to assist with the selection of countermeasures for level crossing upgrades, the proposed approach can be also used to estimate the overall traffic delay per day at level crossings after implementation of countermeasures. A case study is conducted for the public and private level crossings in the State of Florida, considering the countermeasures commonly used in the United States. It was revealed that traffic delays were higher at the public level crossings than at the private level crossings, both before and after implementation of the candidate countermeasures. The case study also indicated that low-cost countermeasures could be more advantageous in terms of safety effectiveness and traffic delays as compared to many high-cost conventional countermeasures. Furthermore, certain attributes of the level crossings in Florida with the highest traffic delays were investigated.

Policy and planning for large epidemics and pandemics - challenges and lessons learned from COVID-19.

Purpose of reviewThe COVID-19 pandemic is a global catastrophe that has led to untold suffering and death. Many previously identified policy challenges in planning for large epidemics and pandemics have been brought to the fore, and new ones have emerged. Here, we review key policy challenges and lessons learned from the COVID-19 pandemic in order to be better prepared for the future.Recent findingsThe most important challenges facing policymakers include financing outbreak preparedness and response in a complex political environment with limited resources, coordinating response efforts among a growing and diverse range of national and international actors, accurately assessing national outbreak preparedness, addressing the shortfall in the global health workforce, building surge capacity of both human and material resources, balancing investments in public health and curative services, building capacity for outbreak-related research and development, and reinforcing measures for infection prevention and control.SummaryIn recent years, numerous epidemics and pandemics have caused not only considerable loss of life, but billions of dollars of economic loss. The COVID-19 pandemic served as a wake-up call and led to the implementation of relevant policies and countermeasures. Nevertheless, many questions remain and much work to be done. Wise policies and approaches for outbreak control exist but will require the political will to implement them.

Evolution and Epidemic Spread of SARS-CoV-2 in Colombia: A Year into the Pandemic.

Current efforts to understand the epidemiology, transmission dynamics and emergence of novel SARS-CoV-2 variants worldwide has enabled the scientific community to generate critical information aimed at implementing disease surveillance and control measures, as well as to reduce the social, economic and health impact of the pandemic. Herein, we applied an epidemic model coupled with genomic analysis to assess the SARS-CoV-2 transmission dynamics in Colombia. This epidemic model allowed to identify the geographical distribution, Rt dynamics and predict the course of the pandemic considering current implementation of countermeasures. The analysis of the incidence rate per 100,000 inhabitants carried out across different regions of Colombia allowed visualizing the changes in the geographic distribution of cases. The cumulative incidence during the timeframe March 2020 to March 2021 revealed that Bogotá (8063.0), Quindío (5482.71), Amazonas (5055.68), Antioquia (4922.35) and Tolima (4724.41) were the departments with the highest incidence rate. The highest median Rt during the first period evaluated was 2.13 and 1.09 in the second period; with this model, we identified improving opportunities in health decision making related to controlling the pandemic, diagnostic testing capacity, case registration and reporting, among others. Genomic analysis revealed 52 circulating SARS-CoV-2 lineages in Colombia detected from 774 genomes sequenced throughout the first year of the pandemic. The genomes grouped into four main clusters and exhibited 19 polymorphisms. Our results provide essential information on the spread of the pandemic countrywide despite implementation of early containment measures. In addition, we aim to provide deeper phylogenetic insights to better understand the evolution of SARS-CoV-2 in light of the latent emergence of novel variants and how these may potentially influence transmissibility and infectivity.

A study of profit shifting using the Hines and Rice approach

Adopting and modifying the approach used by Hines and Rice (1994), we investigate the extent of crossborder profit shifting activities by foreign-owned Australian companies (FOACs) and evaluate the effectiveness of the measures implemented by the Australian government to combat base erosion and profit shifting (BEPS) by multinational enterprises (MNEs). Specifically, we measure the sensitivity of profit before tax reported in Australia by FOACs to the tax rate differentials between Australia and other countries where the related foreign-based MNE groups operate and examine whether such sensitivity decreases after the implementation of BEPS countermeasures. Overall, we find that profit shifting from Australia to low-tax countries took place throughout the 14-year study period, 2007 to 2020. The higher the Australian corporate tax rate relative to the tax rates of immediate parent entity, ultimate parent entity, and the higher the ranking of Australian tax rate relative to those of other countries where the foreign MNEs operate, the lower is the profit reported in Australia. In general, crossborder profit shifting from Australia to low-tax countries has not reduced in the post-BEPS period from 2013 to 2020 after the launch of the BEPS Project by the OECD and the implementation of BEPS countermeasures in Australia, although there is some evidence from breaking down the post-BEPS period by years which shows that profit shifting might have reduced in the year 2019. Such reduction, however, does not sustain in 2020.

A comprehensive analysis of factors that influence interstate highway crash severity in Alabama

This paper identifies factors that influence the severity of interstate crash outcomes and how they vary depending on the location and manner of collision. Four separate injury severity models were developed to explore the differences and similarities in crash factors between single-and multi-vehicle crashes that occurred in rural and urban areas of the state. Random parameters multinomial logit with heterogeneity in means and variances modeling approach was used to account for unobserved heterogeneity in the crash data. The model estimation results show that some driver behavioral factors such as speeding, aggressive driving, failure to use seatbelt, and driving without a valid license were found to significantly contribute to some form of injury outcome. The influence of roadway features such as type of opposing lane separation, collision type, temporal and lighting conditions on crash outcomes were also explored. Some differences and similarities in the associations between these factors and crash injury severity based on the manner and location of crash were unraveled. These findings are expected to guide the implementation of crash countermeasures on interstates. The findings of this study further support the evidence for the analysis of subsets of crash data to unravel underlying complex relationships within factors that influence crash injury severity.