SURVIVABILITY OF SHIPS AT SEA: A PROPOSED MODEL TO ACCOUNT FOR HUMAN FACTORS IN A SAFETY-CRITICAL SYSTEM

Most serious accidents at sea are caused by minor incidents that escalated into an uncontrolled situation. This study is aiming to develop a model to investigate the likelihood of fatal accidents, given that a critical incident has already occurred. The focus of the study is on human behaviour, adopting a hardware reliability perspective. The vessel is considered as a safety-critical system to be protected by several barriers. The crew role is modelled as active barriers and distinguishing between different functions: perception, decision and action. A Markov approach is proposed to model different situations on the vessel. A mathematical model to estimate the probability of failure in an emergency situation is formulated. A new parameter is defined for the survivability of a vessel, given that a critical incident has taken place. The methods were applied to examine ship-platform collisions cases and the results show strong benefits for diagnosing and evaluating accidents from a human factors perspective as well as for training purposes.

Hardware Reliability Analysis of a Coal Mine Gas Monitoring System Based on Fuzzy-FTA

The hardware reliability of a gas monitoring system was investigated using the fuzzy fault tree analysis method. A fault tree was developed considering the hardware failure of the gas monitoring system as a top event. Two minimum path sets were achieved through qualitative analysis using the ascending method. The concept of fuzzy number of the fuzzy set theory was applied to describe the probability of basic event occurrence in the fault tree, and the fuzzy failure probabilities of the middle and top events were calculated using fuzzy AND and OR operators. The results show that the proposed fuzzy fault tree is an effective method of reliability analysis for gas monitoring systems. Results of calculations using this method are more reasonable than those obtained with the conventional fault tree method.

A Comprehensive Risk Assessment Framework for Synchrophasor Communication Networks in a Smart Grid Cyber Physical System with a Case Study

The smart grid (SG), which has revolutionized the power grid, is being further improved by using the burgeoning cyber physical system (CPS) technology. The conceptualization of SG using CPS, which is referred to as the smart grid cyber physical system (SGCPS), has gained a momentum with the synchrophasor measurements. The edifice of the synchrophasor system is its communication network referred to as a synchrophasor communication network (SCN), which is used to communicate the synchrophasor data from the sensors known as phasor measurement units (PMUs) to the control center known as the phasor data concentrator (PDC). However, the SCN is vulnerable to hardware and software failures that introduce risk. Thus, an appropriate risk assessment framework for the SCN is needed to alleviate the risk in the protection and control of the SGCPS. In this direction, a comprehensive risk assessment framework has been proposed in this article for three types of SCNs, namely: dedicated SCN, shared SCN and hybrid SCN in an SGCPS. The proposed framework uses hardware reliability as well as data reliability to evaluate the associated risk. A simplified hardware reliability model has been proposed for each of these networks, based on failure probability to assess risk associated with hardware failures. Furthermore, the packet delivery ratio (PDR) metric is considered for measuring risk associated with data reliability. To mimic practical shared and hybrid SCNs, the risk associated with data reliability is evaluated for different background traffics of 70%, 80% and 95% using 64 Kbps and 300 Kbps PMU data rates. The analytical results are meticulously validated by considering a case study of West Bengal’s (a state in India) power grid. With respect to the case study, different SCNs are designed and simulated using the QualNet network simulator. The simulations are performed for dedicated SCN, shared SCN and hybrid SCN with 64 Kbps and 300 Kbps PMU data rates. The simulation results are comprehensively analyzed for risk hedging of the proposed SCNs with data reliability and hardware reliability. To summarize, the mean risk with data reliability (RwDR) as compared to the mean risk with hardware reliability (RwHR) increases in shared SCN and hybrid SCN by a factor of 17.108 and 23.278, respectively. However, minimum RwDR increases in shared and hybrid SCN by a factor of 16.005 and 17.717, respectively, as compared to the corresponding minimum RwHR. The overall analysis reveals that the RwDR is minimum for dedicated SCN, moderate for shared SCN, and highest for hybrid SCN.

Building a digital twin of the main automated systems of an industrial enterprise to determine the level of information security

The aim of the scientific work is to assess the level of information security of the automated enterprise systems using modelling based on the concept of digital twins of production. The article is devoted to solving the problem of constructing a model that is a digital twin of the enterprise automated systems. Within the framework of a systematic approach, solving this problem implies modelling environmental conditions, software and hardware reliability, as well as the human factor. The novelty of the work is the proposed creative concept of using the digital twin technology for a detailed assessment of the information security level of the automated systems. The study findings are the recommendations for assessing the level of information security using a digital twin.

SECOND BIRTH OF TROPOSPHERIC COMMUNICATION. PHASED ANTENNA ARRAY COGNITIVE RADIO STATIONS

Рассмотрены новые прорывные технические решения по тропосферной связи на основе когнитивных радиостанций с фазированной антенной решеткой (ФАР). Показана возможность повышения (в десятки раз)аппаратурной надежности за счет исключения из состава ТРС мощных передатчиков и применения вместо них маломощных антенных приемопередающих модулей (АППМ),синфазноработающих в составе ФАР. Представлены преимуществами ТРС: возможность длительной работа без технического обслуживания, снижение вдвое энергопотребления, а также глубокая унификация построения ТРС разного класса на основе унифицированных АППМ. New breakthrough technical solutions for tropospheric communication based on cognitive radio stations with a phased antenna array (PAA) are considered. These solutions provide the possibility of increasing the hardware reliability tenfold due to exclusion of powerful transmitters from tropospheric stations (TS) and using instead of them low-power antenna receive-transmitting modules (ARTM), operating in phase as part of the PAA. The advantages of such TSs are shown that enable long-term operation without maintenance, halving power consumption, as well as deep unification of the construction of TSs of different classes based on unified ARTMs.

Automated video monitoring of insect pollinators in the field

Ecosystems are at increasing risk from the global pollination crisis. Gaining better knowledge about pollinators and their interactions with plants is an urgent need. However, conventional methods of manually recording pollinator activity in the field can be time- and cost-consuming in terms of labour. Field-deployable video recording systems have become more common in ecological studies as they enable the capture of plant-insect interactions in fine detail. Standard video recording can be effective, although there are issues with hardware reliability under field-conditions (e.g. weatherproofing), and reviewing raw video manually is a time-consuming task. Automated video monitoring systems based on motion detection partly overcome these issues by only recording when activity occurs hence reducing the time needed to review footage during post-processing. Another advantage of these systems is that the hardware has relatively low power requirements. A few systems have been tested in the field which permit the collection of large datasets. Compared with other systems, automated monitoring allows vast increases in sampling at broad spatiotemporal scales. Some tools such as post-recording computer vision software and data-import scripts exist, further reducing users’ time spent processing and analysing the data. Integrated computer vision and automated species recognition using machine learning models have great potential to further the study of pollinators in the field. Together, it is predicted that future advances in technology-based field monitoring methods will contribute significantly to understanding the causes underpinning pollinator declines and, hence, developing effective solutions for dealing with this global challenge.

An Empirical Analysis of Software Reliability using Reliability Analysis Algorithm

Reliability is the fundamental aspect of a software system that cannot be ignored and hard to measure. Two major elements namely hardware and software need to be measured to evaluate the reliability of software system. The work that is already existing give focus on measuring the reliability of software alone. With little consideration in measuring the reliability of hardware. The present work focuses on computation of hardware reliability and software reliability together. The aim is to propose an algorithm to develop a model for estimation of reliability. The algorithm is named as reliability analysis algorithm. Using comparison criteria developed model is compared with other two traditional models. The result of this study shows that the developed model can be used to measure and predict the reliability with high degree of accuracy