Key Concepts of Systemological Approach to CPS Adaptive Information Security Monitoring

Modern cyber-physical systems (CPS) use digital control of physical processes. This allows attackers to conduct various cyberattacks on these systems. According to the current trends, an information security monitoring system (ISMS) becomes part of a security management system of CPS. It provides information to make a decision and generate a response. A large number of new methods are aimed at CPS security, including security assessment, intrusion detection, and ensuring sustainability. However, as a cyber-physical system operates over time, its structure and requirements may change. The datasets available for the protection object (CPS) and the security requirements have become dynamic. This dynamic effect causes asymmetry between the monitoring data collection and processing subsystem and the presented security tasks. The problem herein is the choice of the most appropriate set of methods in order to solve the security problems of a particular CPS configuration from a particular bank of the available methods. To solve this problem, the authors present a method for the management of an adaptive information security monitoring system. The method consists of solving a multicriteria discrete optimization problem under Pareto-optimality conditions when the available data, methods or external requirements change. The experimental study was performed on an example of smart home intrusion detection. In the study, the introduction of a constraint (a change in requirements) led to the revision of the monitoring scheme and a different recommendation of the monitoring method. As a result, the information security monitoring system gains the property of adaptability to changes in tasks and the available data. An important result from the study is the fact that the monitoring scheme obtained using the proposed management method has a proven optimality under the given conditions. Therefore, the asymmetry between the information security monitoring data collection and processing subsystem and the set of security requirements in cyber-physical systems can be overcome.

An Investigation of NEXRAD-Based Quantitative Precipitation Estimates in Alaska

Precipitation estimation by weather radars in Alaska is challenging. In this study, we investigate National Weather Service (NWS) precipitation products that are produced from the seven NEXRAD radar sites in Alaska. The NWS precipitation processing subsystem generates stages of data at each NEXRAD site which are then input to the weather forecast office to generate a regionwide precipitation product. Data from the NEXRAD sites and the operational rain gauges in the weather forecast region are used to produce this regionwide product that is then sent to the National Centers for Environmental Prediction (NCEP) to be included in the NCEP Stage IV distribution. The NCEP Stage IV product for Alaska has been available since 2017. We use the United States Climate Reference Network (USCRN) data from Alaska to compare to the NCEP Stage IV data. Given that the USCRN can be used in the production of the NCEP Stage IV data for Alaska, we also used the NEXRAD Digital Precipitation Array (DPA) that is generated at the site for comparison of the radar-only products. Comparing the NEXRAD-based data from Alaska to the USCRN gauge estimates using the USCRN site information on air temperature, we are able to condition the analysis based on the hourly or 6-hourly average air temperature. The estimates in the frozen phase of precipitation largely underestimate as compared to the gauge, and the correlation is low with larger errors as compared to other phases of precipitation. In the mixed phase the underestimation of precipitation improves, but the correlation is still low with relatively large errors as compared to the rain phases of precipitation. The difficulties in precipitation estimation in cold temperatures are well known and we show the evaluation for the NCEP Stage IV regional data for Alaska and the NEXRAD site specific Digital Precipitation Array (DPA) data. Results show the challenges of estimating mixed-phase and frozen precipitation. However, the DPA data shows somewhat better performance in the mixed precipitation phase, which suggests that the NWS Precipitation Processing Subsystem (PPS) is tuned to the climatology as it relates to precipitation in Alaska.

Advanced Technology Application on Monitoring and Forecasting Lobster Farming Environment in Phu Yen

Environmental monitoring is an urgent requirement in aquaculture. In this paper, the author presents solutions to apply advanced technologies in design and development in monitoring and forecasting lobster farming environment and practical implementation in Phu Yen. This is a complete IoT system including: (1) sensor/actuator module to collect data from the environment; (2) communication module connecting sensors, forming a flexible wireless network architecture, sending reliable data to the server/cloud, with long distance and low energy consumption; (3) data storage and processing subsystem using AI to provide real-time monitoring and forecasting of environmental trends, early warning of risks and epidemics; (4) application modules including web-app and mobile-app allow users to exploit services and interact with the system, manage and operate monitoring equipment.

Risk management in the healthcare safety management system

The paper discusses the main components of the modern system of risk management in medicine. Using the ISO 31000 standard of risk management and the ARIS integrated modeling environment, the authors have built a model of the risk management process in a medical organization, including the accounting subsystem, the risk analysis subsystem, and the risk processing subsystem. The concept of risk management proposed in the article is formulated on the basis of a system safety model, which assumes that adverse events related to the provision of medical care are based on systemic causes that under certain conditions turn into a hazard, and the latter is used to receive active threats and incidents. The risk management system is an executive block of the safety management system in a medical organization, which includes (in addition to risk management) an ideological block (a new safety culture) and an educational block (an organizational learning subsystem).

Precise variable spraying system based on improved genetic proportional-integral-derivative control algorithm

Currently, the most efficient method of resolving the pollution problem of weed management is by using variable spraying technology. In this study, an improved genetic proportional-integral-derivative control algorithm (IGA-PID) was developed for this technology. It used a trimmed mean operator to optimize the selection operator for an improved searching rate and accuracy. An adaptive crossover operator and mutation operator were constructed for a rapid convergence speed. The weed density detection was performed through an image acquisition and processing subsystem which was capable of determining the spraying quantity. The variable spraying control sub-system completed variable spraying operation. The performance of the system was evaluated by simulations and field tests, and compared with conventional methods. The simulation results indicated that the parameters of the overshoot (1.25%), steady-state error (1.21%) and the adjustment time (0.157s) of IGA-PID were the lowest when compared with the standard algorithms. Furthermore, the field validation results showed that the system with the proposed algorithm achieved the optimal performance with spraying quantity error being 2.59% and the respond time being 3.84s. Overall, the variable spraying system based on an IGA-PID meets the real-time and accuracy requirements for field applications which could be helpful for weed management in precise agriculture.

SISTEM INFORMASI PENGELOLAAN KEUANGAN DI KANTOR CAMAT KECAMATAN BABAT TOMAN

A financial information system is an information system designed to provide information about money options for users throughout the company. The financial information system is part of the MIS which is used to solve corporate financial problems. In general, the financial information system has an income system consisting of a data processing subsystem supported by an internal audit subsystem that provides internal data and information. For large companies it usually has staff internal auditors. Like other subsystems, this system is also equipped with the financial intelligence subsystem, which collects information from the environment.

Adaptation of cassava agribusiness systems during the Covid-19 pandemic (case in Pasar Pedati Village, Bengkulu Province)

The cassava agribusiness system involves farmers from upstream to downstream. This study aims to determine the effect of the covid-19 pandemic on the cassava agribusiness system and the adaptation of farmers. The research was conducted from March to April 2021 in Pasar Pedati Village, Pondok Kelapa Subdistrict, which is the center of cassava production in Bengkulu Tengah Regency. Data has collected the conditions of cassava agribusiness system and farmers’ adaptation in pandemic through in-depth interviews involved seven key informants, besides observation and secondary data collections. Data analyzed descriptively. The results showed that the pandemic does not affect the entire cassava agribusiness, disrupted only the marketing and processing subsystem, because: (1) cassava cultivation is a part-time business that low costs input; (2) farmers adjusting the production capacity of cassava chips by the demands of traders; (3) farmers still selling cassava harvests in fresh form even at low prices and making dried cassava (gaplek) to extend the shelf life of cassava. Farmers continued to cultivate cassava in the hope that the pandemic will end at any time in addition to anticipating the fulfilled of family food needs to replace rice as a staple food.

Development of neural network model for signs determination of atrial fibrillation for subsystem of cardiorhythmogram signals processing

Task of the analysis of a cardio rhythm in real time is detection of early arrhythmias for the purpose of their treatment and prevention of life-endangering arrhythmias. In order to solve the problem of classification of heart rhythm features based on cardiorhythmogram processing, an apparatus of artificial neural networks can be used. One of the most dangerous arrhythmias is atrial fibrillation. Therefore, the development of a neural network model for determining atrial fibrillation features, suitable for implementation on the programmable logic basis, for a subsystem for processing cardiorhythmogram signals is an urgent task. Purpose – development of a neural network model for determining atrial fibrillation features for a signal processing subsystem characterized by high reliability and the implementation possibility on the basis of programmable logic. A neural network model for features determining of atrial fibrillation has been developed, characterized by high reliability and insignificant hardware costs when implemented on field programmable gate arrays (FPGA). Program modeling of neural network model for signs determination of atrial fibrillation is performed. A neural network model for characteristics determining of atrial fibrillation on hardware description language VHDL for use in the signal processing subsystem of a cardiorhythmogram based on FPGA was implemented. The findings suggest that the proposed model can be used in the construction of real-time heart rhythm control systems both for monitoring already diagnosed cardiovascular diseases, especially in intensive care wards, and for the prevention and early diagnosis of arrhythmias in individuals at high myocardial risk.

APPROACHES TO METHOD OF BINARY CLASSIFICATION SELECTING FOR TEXT MESSAGES IN STREAMING DISTRIBUTED SYSTEMS OF INFORMATION PROCESSING

В статье представлен вариант решения задачи выбора метода двоичной (двухклассовой) классификации потока текстовых сообщений (на примере новостных источников - сервиса RSS), поступающих на вход распределенной системы обработки информации. Рассматриваются вопросы, как выбора рационального, с точки зрения потоковой обработки, метода двоичной классификации для подсистемы обработки текстовых сообщений на основе технологии машинного обучения, так и формирования обучающей и тестовой выборок массива текстовых сообщений, необходимых на этапе обучения двоичного классификатора. Представлены результаты экспериментальной проверки полученных значений указанных выборок применительно к рассмотренным методам двоичной классификации. Приводится подход к процессу обучения классификатора для подсистемы обработки текстовых сообщений в распределенной системе потоковой обработки информации. The article presents a variant of solving problem of a method for binary (two-class) classification choosing of a text messages stream (using the example of news sources - the RSS service) entering on input of a distributed information processing system. The issues of both the choice of a rational binary classification method for a text message, from the point of view of stream processing for subsystem based on machine learning technology, and the formation of training and test samples of an array of text messages required at the stage of training a binary classifier are considered. The results of experimental verification of the obtained values ??of these samples are presented in relation to the considered methods of binary classification. An approach to the process of classifier training for text message processing subsystem in a distributed system of streaming information processing is presented.