System Monitoring Tools Research Articles

A Kullback–Leibler divergence method for input–system–state identification

The capability of a novel Kullback–Leibler divergence method is examined herein within the Kalman filter framework to select the input–parameter–state estimation execution with the most plausible results. This identification suffers from the uncertainty related to obtaining different results from different initial parameter set guesses, and the examined approach uses the information gained from the data in going from the prior to the posterior distribution to address the issue. Firstly, the Kalman filter is performed for a number of different initial parameter sets providing the system input–parameter–state estimation. Secondly, the resulting posterior distributions are compared simultaneously to the initial prior distributions using the Kullback–Leibler divergence. Finally, the identification with the least Kullback–Leibler divergence is selected as the one with the most plausible results. Importantly, the method is shown to select the better performed identification in linear, nonlinear, and limited information applications, providing a powerful tool for system monitoring.

Strategies to Reduce the Rate of Plate Waste in Hospitalized Patients: A Scoping Review.

There is evidence that hospital waste is indisputably high, and various strategies have been used to reduce the hospital's rate of plate waste. This study aimed to map the currently implemented strategies in lowering the rate of plate waste in hospitals and categorize the different types of strategies used as interventions, as well as determine their impact based on specific parameters. The scoping review method included a search of three databases using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-SCR). The duplicate articles (n = 80) were removed. A total of 441 articles remained for the title and abstract screening. After 400 were excluded, 41 articles were reviewed for eligibility. Thirty-two full articles were eliminated due to a lack of focus on plate waste evaluation. Finally, nine accepted studies were grouped into five categories: menu modification, room service implementation, menu presentation, meal-serving system, and dietary monitoring tool. In conclusion, results showed that the majority of the studies implemented either of the five strategies to reduce plate waste; however, the cook-freeze system and staff training for both kitchen and ward staff were not yet part of any intervention strategy. The potential of this method should be explored in future interventions.

A Powerful Tool for Power System Monitoring: Distributed Dynamic State Estimation Based on a Full-View Synchronized Measurement System

Modern power systems are witnessing a rapid transition with the increasing penetration of intermittent nonsynchronous renewable generation and distributed energy resources. According to the National Energy Administration, China’s installed wind and solar energy capacity accounted for 26.7% of the country’s total power generation capacity at the end of 2021. In terms of electricity generation, wind and solar energy accounted for 11.8% percent of the total electricity use that year. In the renewable energy development plan in the 14th Five-Year Plan (2021–2025), China aims for renewables to meet 33% of national power consumption and for nonhydro renewables to satisfy 18%. This transition poses challenges for system operators to grasp the actual status of power systems accurately and comprehensively.

A PMU-Based Data-Driven Approach for Enhancing Situational Awareness in Building A Resilient Power Systems

A data-driven approach for improving wide-area situational awareness (SA) in modern power systems for building a more resilient grid is proposed in this article. SA is of paramount importance when it comes to accurate sensing of events for better visualization of the power system dynamics. Various events uniquely excite particular states of the power systems resulting in a maximum change in the entropy for certain power system components. A new conceptual framework utilizing structure preserving energy function (SPEF) for identifying the specific component of the energy function and correlating it with the appropriate event has been suggested. Cubature Kalman filter-unknown input based dynamic state estimation technique has been employed for the extraction of states and unknown inputs from the phasor measurement unit (PMU) measurements for the derivation of the SPEF-based event indicators. In order to demonstrate the efficacy of the proposed technique, it has been validated on the IEEE 39-bus system and also on actual PMU data obtained from the Indian power grid. The results indicate the suggested technique to be accurate and robust to noise and thus can be a promising tool for real-time power system monitoring.

PERBANDINGAN NILAI ISPU HARIAN DI 5 TITIK PEMANTAUAN UDARA DKI JAKARTA PADA SAAT LOCKDOWN MARET 2020

One of the air quality conditions in the Special Capital City Region (DKI) Jakarta is the transportation sector. The air quality index is dominated by moderate conditions, even at dangerous levels. The COVID-19 pandemic caused the DKI Jakarta Provincial Government to lock down in March 2020. Research in several countries has shown that air quality has improved because people's mobility has been stopped. This study aims to determine the effect of the lockdown imposed in DKI Jakarta on its air quality and see a comparison at each point. The method used is descriptive method. The data analyzed in this study were collected from 5 points of the Air Quality Monitoring System (AQMS) monitoring tool. Based on the research, it was concluded that the lockdown imposed in DKI Jakarta only affected the location of point 1 at the Hotel Indonesia (HI) roundabout. The Air Pollution Status Index (ISPU) is dominated by good air quality conditions. Other areas such as West Jakarta, East Jakarta, North Jakarta and South Jakarta, the lockdown imposed in March 2020 did not have any effect on increasing the ISPU value. In 2021 the air quality condition in DKI Jakarta is worse than in previous years at all monitoring points since the activities have returned to normal and traffic jams frequently occur. Keywords: Air Quality Index, DKI Jakarta, Lockdown, Transportation.

Heart and Temperature Monitoring Design and Testing Over the Internet

Design and testing of a heart rate monitoring system and human body temperature using an Arduino-based internet network, which aims to monitor heart conditions and body temperature on the internet network. This monitoring system tool is designed using Arduino with two measurement parameters, namely a heart rate sensor and a human body temperature sensor with the results displayed on the LCD, internet web, and android application. The research method used is to measure heart rate (BPM) and human body temperature compared with standard equipment in hospitals, by taking measurements of five patients with five measurements each. This study also aims to make it easier for medics to monitor patient conditions remotely. Based on measurement data for five patients who have been measured using a design tool, the relative error value for heart rate is less than 3% and body temperature with a correction factor of 1% and percentage below 2%. This value indicates that the designed tool functions quite well

A Novel Event Detection and Classification Scheme Using Wide-Area Frequency Measurements

Automated event detection and classification are vital to power system monitoring. This article proposes a novel event detection and classification scheme based on wide area frequency measurement system (WAFMS). Raw frequency measurements obtained from WAFMS are used as the only input to the event detection and classification algorithm (EDCA). Wavelet-based signal pre-processing is used to denoise the data. Afterward, the rate of change of frequency (ROCOF) is estimated from the frequency measurements using the Kalman filter (KF). In the same step, phase angle difference (PAD) across different stations is estimated using WAFMS. Thus, the overall algorithm uses three features such as frequency, ROCOF, and PAD to detect and classify events in the power system. In the first step, an event is detected based on standard deviation (SD) of estimated ROCOF and PAD. In the second step, four types of events are classified using wide area frequency measurements. The suggested algorithms have been validated with real WAFMS data from the Indian Power System, recent 9th August 2019 U.K. blackout data collected from the U.K. power system, and 20th July 2017 oscillation event data obtained from ISO New England (ISO-NE) power system. As a promising tool for power system monitoring, the suggested scheme requires less input measurement for decision making and is having a low computational complexity, which is suitable for practical application.

GIS database of groundwater flow characteristics in carbonate aquifers: Tracer test inventory from Slovenian karst

Karst aquifers that supply manifold ecosystem services, such as freshwater resources, and possess unique underground biodiversity are characterized by peculiar flow processes and are thus particularly susceptible to destruction. Their efficient protection is based on artificial tracing results that are usually scattered among different sources. In the case of Slovenia, the results of 231 available tracer tests, performed between 1905 and 2019, have been assembled, arranged and georeferenced. The inventory of the geospatial database, which is unique on a global scale, contains 36 different pieces of data for each tracing that have been compiled using geographic information system tools. In this study, the basic concepts, the step-by-step workflow and a detailed mapping procedure have been presented. The thorough collection of available data that is freely accessible online includes data on the date, location and details of implementation of the tracer test and on the identified groundwater flow characteristics. Also available are the sources of the published or unpublished reports from which the data were taken. The database includes a comment on the tracer test implementation or results. The inventory is very useful in the process of the integrated management of karst water sources, and especially as an early-warning and monitoring system tool in cases where there is an imminent danger of pollution, which requires a fast and accurate response. The database production is transferable to other karst-rich countries.

Comparing the Use of Echocardiography and Non-Invasive Cardiac System in Measuring the Cardiac Index to Predict Acute Kidney Failure in Patients with Heart Failure

The prevalence of heart failure is 1-2% of the adult population in developing countries. Decreased kidney function in these patients is influenced by several factors including low Cardiac Output (CO) (Liu, 2008). Cardiac Index (CI) is an important parameter for assessing patients with heart failure since a decrease in CI in heart failure patients indicates the inadequacy of tissue perfusion, including the kidney, which triggers Acute Kidney Injury (AKI). Thus, it is necessary to study hemodynamic surveillance in patients with heart failure both by using echocardiography which is routinely carried out in the Emergency Room (IGD) of the Saiful Anwar Public Hospital (RSSA) as well as a Non-invasive Cardiac System (NiCAS) monitoring tool to predict AKI in patients with heart failure. Methods: Analytical observations were done in 39 patients with heart failure in the Emergency Room of RSSA to determine the suitability of NiCAS and echocardiography in measuring CI to predict acute kidney failure in these patients. Results: The suitability of CI measurements on NiCAS and echocardiography was obtained in 23 samples (59%) (p = 0.175). Creatinine suitability and Echocardiography CI R² were 0.0068. Creatinine suitability and NiCAS CI were tested at 12 th hour, since the patient was hospitalized, under linearity conditions resulting in R 2 of 0.0024 and R 2 0.0287. Conclusion: Measurement of NiCAS matches measurement with echocardiography in measuring Cardiac Index. However, neither NiCAS nor Echocardiography does not a match in predicting acute kidney failure in patients with acute heart failure. Keywords: NiCAS, echocardiography, heart failure, kidney failure, Cardiac Output (CO), Cardiac Index (CI) DOI : 10.7176/JHMN/66-01 Publication date :September 30 th 2019

Assessment for Monitoring of Education Systems: The U.S. Example

Standardized tests are regularly used as education system monitoring tools to compare the average performance of students living in different states or belonging to different subgroups (e.g., defined by race/ethnicity, sex, or parental income) and to track their progress over time. This article describes some uses and design features of tests in system monitoring contexts. We provide the example of the National Assessment of Educational Progress (NAEP), the only large-scale system monitoring test in the United States. The availability of NAEP data, in turn, has facilitated the construction of the Stanford Education Data Archive (SEDA), a publicly available database that can be used to describe patterns of achievement for nearly all school districts in the United States. Here, we discuss progress in and challenges to the use of standardized tests as system monitoring tools.

CubeSats Enable High Spatiotemporal Retrievals of Crop-Water Use for Precision Agriculture

Remote sensing based estimation of evapotranspiration (ET) provides a direct accounting of the crop water use. However, the use of satellite data has generally required that a compromise between spatial and temporal resolution is made, i.e., one could obtain low spatial resolution data regularly, or high spatial resolution occasionally. As a consequence, this spatiotemporal trade-off has tended to limit the impact of remote sensing for precision agricultural applications. With the recent emergence of constellations of small CubeSat-based satellite systems, these constraints are rapidly being removed, such that daily 3 m resolution optical data are now a reality for earth observation. Such advances provide an opportunity to develop new earth system monitoring and assessment tools. In this manuscript we evaluate the capacity of CubeSats to advance the estimation of ET via application of the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) retrieval model. To take advantage of the high-spatiotemporal resolution afforded by these systems, we have integrated a CubeSat derived leaf area index as a forcing variable into PT-JPL, as well as modified key biophysical model parameters. We evaluate model performance over an irrigated farmland in Saudi Arabia using observations from an eddy covariance tower. Crop water use retrievals were also compared against measured irrigation from an in-line flow meter installed within a center-pivot system. To leverage the high spatial resolution of the CubeSat imagery, PT-JPL retrievals were integrated over the source area of the eddy covariance footprint, to allow an equivalent intercomparison. Apart from offering new precision agricultural insights into farm operations and management, the 3 m resolution ET retrievals were shown to explain 86% of the observed variability and provide a relative RMSE of 32.9% for irrigated maize, comparable to previously reported satellite-based retrievals. An observed underestimation was diagnosed as a possible misrepresentation of the local surface moisture status, highlighting the challenge of high-resolution modeling applications for precision agriculture and informing future research directions.

Optimization Based Evaluation of Grating Interferometric Phase Stepping Series and Analysis of Mechanical Setup Instabilities

The diffraction contrast modalities accessible by X-ray grating interferometers are not imaged directly but have to be inferred from sine-like signal variations occurring in a series of images acquired at varying relative positions of the interferometer’s gratings. The absolute spatial translations involved in the acquisition of these phase stepping series usually lie in the range of only a few hundred nanometers, wherefore positioning errors as small as 10 nm will already translate into signal uncertainties of 1–10% in the final images if not accounted for. Classically, the relative grating positions in the phase stepping series are considered input parameters to the analysis and are, for the Fast Fourier Transform that is typically employed, required to be equidistantly distributed over multiples of the gratings’ period. In the following, a fast converging optimization scheme is presented simultaneously determining the phase stepping curves’ parameters as well as the actually performed motions of the stepped grating, including also erroneous rotational motions which are commonly neglected. While the correction of solely the translational errors along the stepping direction is found to be sufficient with regard to the reduction of image artifacts, the possibility to also detect minute rotations about all axes proves to be a valuable tool for system calibration and monitoring. The simplicity of the provided algorithm, in particular when only considering translational errors, makes it well suitable as a standard evaluation procedure also for large image series.

Fractional-order system identification for health monitoring

Fractional-order differential equations can describe the dynamics of robot formations and other high-order systems. These equations are useful models for such systems because of the flexibility afforded by including noninteger derivatives. A system’s fractional order may change in response to mechanical or operational damage, but the possibility of an order change is not typically considered in structural health monitoring or other system monitoring tools. Typically, the order is assumed to be an integer from the physics of the system, while behaviors are captured by parameters within the chosen model. In contrast, this work presents a procedure to identify the fractional order of a system’s dynamics across a variety of parameter changes; the inclusion of fractional orders allows order itself to measure dynamical shifts. This work presents the identification procedure, its mathematical foundations, and results from example systems representing two mobile robot formations. The fractional order changes in a manner consistent with the physical changes modeled by damage, suggesting that this procedure is widely applicable in health monitoring.

Cyber-Physical Production Testbed: Literature Review and Concept Development

Many researchers use virtual and simulation-based testbed technology for research in production and maintenance optimization. Although, the virtual environment produces good results, it cannot imitate the unexpected changes that occur in actual production. There are very few physical testbeds emulating actual production environment. The aim of this paper is to present a concept of a cyber-physical production testbed based on review of Cyber-Physical Systems (CPS) testbeds in research. The testbed consists of a semi-automatic production line equipped with system monitoring tools, data analysis capabilities and commercial software. This testbed will be used for demonstration of data acquisition for production and maintenance prioritization. Additionally, the testbed will be used for research in IoT platforms for production optimization.

Using a standard approach to the design of next generation e-Supply Chain Digital Forensic Readiness systems

The internet has had a major impact on how information is shared within supply chains, and in commerce in general. This has resulted in the establishment of information systems such as e-supply chains (eSCs) amongst others which integrate the internet and other information and communications technology (ICT) with traditional business processes for the swift transmission of information between trading partners. Many organisations have reaped the benefits that come from adopting the eSC model, but have also faced the challenges with which it comes. One such major challenge is information security. With the current state of cybercrime, system developers are challenged with the task of developing cutting edge digital forensic readiness (DFR) systems that can keep up with current technological advancements, such as (eSCs). Hence, the problem addressed in this paper is the lack of a well-formulated DFR approach that can assist system developers in the development of e-supply chain digital forensic readiness systems. The main objective of such a system being that it must be able to provide law enforcement/digital forensic investigators (DFI) with forensically sound and readily available potential digital evidence that can expedite and support digital forensics incident response processes. This approach, if implemented can also prepare trading partners for security incidents that might take place, if not prevent them from occurring. Therefore, the work presented in this paper is aimed at providing a procedural approach that is based on digital forensics principles. This paper discusses the limitations of current system monitoring tools in relation to the kind of specialised DFR systems that are needed in the eSC environment and proposes an eSC-DFR process model and architectural design model that can lead to the development of next-generation eSC DFR systems. It is the view of the authors that the conclusions drawn from this paper can spearhead the development of cutting-edge next-generation digital forensic readiness systems, and bring attention to some of the shortcomings of current system monitoring tools.

System dynamics and product quality during fluidized bed agglomeration of phytochemical compositions

Pressure fluctuation signals linked to growth kinetics and fluiddynamic data were used to characterize system dynamics during fluidized bed encapsulation/agglomeration of phytochemical compositions using microcrystalline cellulose of two different sizes as seed particles. Two distinct operating modes were investigated: intermittent (interrupting the atomization of the feed composition for a specific period of time in order to reduce the system humidity) and continuous (without interruption the atomization of the feed). The increase in the agglomeration percentage to a certain value during the processes caused an increase in the standard deviation of the amplitude of the pressure fluctuation signals while the system remained stable, indicative of slight changes on solids circulation patterns. However, the standard deviation of the amplitude of the pressure fluctuation signals tended to decrease when agglomeration percentage reached a value able to affect significantly the system stability, in which agglomerates growth tended to cause the system collapse. This behavior was most evident for small size seed particles and continuous operating mode. The changes in the standard deviation of the amplitude of pressure fluctuation signals show strong evidence that this method would be able to detect alterations in system dynamics and can be a useful tool for process control and system monitoring.

Subsidence monitoring system for offshore applications: technology scouting and feasibility studies

Abstract. Because of concern about possible impacts of hydrocarbon production activities on coastal-area environments and infrastructures, new hydrocarbon offshore development projects in Italy must submit a monitoring plan to Italian authorities to measure and analyse real-time subsidence evolution. The general geological context, where the main offshore Adriatic fields are located, is represented by young unconsolidated terrigenous sediments. In such geological environments, sea floor subsidence, caused by hydrocarbon extraction, is quite probable. Though many tools are available for subsidence monitoring onshore, few are available for offshore monitoring. To fill the gap ENI (Ente Nazionale Idrocarburi) started a research program, principally in collaboration with three companies, to generate a monitoring system tool to measure seafloor subsidence. The tool, according to ENI design technical-specification, would be a robust long pipeline or cable, with a variable or constant outside diameter (less than or equal to 100 mm) and interval spaced measuring points. The design specifications for the first prototype were: to detect 1 mm altitude variation, to work up to 100 m water depth and investigation length of 3 km. Advanced feasibility studies have been carried out with: Fugro Geoservices B.V. (Netherlands), D'Appolonia (Italy), Agisco (Italy). Five design (using three fundamental measurements concepts and five measurement tools) were explored: cable shape changes measured by cable strain using fiber optics (Fugro); cable inclination measured using tiltmeters (D'Appolonia) and measured using fiber optics (Fugro); and internal cable altitude-dependent pressure changes measured using fiber optics (Fugro) and measured using pressure transducers at discrete intervals along the hydraulic system (Agisco). Each design tool was analysed and a rank ordering of preferences was performed. The third method (measurement of pressure changes), with the solution proposed by Agisco, was deemed most feasible. Agisco is building the first prototype of the tool to be installed in an offshore field in the next few years. This paper describes design of instruments from the three companies to satisfy the design specification.

Analyzing data flows of WLCG jobs at batch job level

With the introduction of federated data access to the workflows of WLCG, it is becoming increasingly important for data centers to understand specific data flows regarding storage element accesses, firewall configurations, as well as the scheduling of batch jobs themselves. As existing batch system monitoring and related system monitoring tools do not support measurements at batch job level, a new tool has been developed and put into operation at the GridKa Tier 1 center for monitoring continuous data streams and characteristics of WLCG jobs and pilots. Long term measurements and data collection are in progress. These measurements already have been proven to be useful analyzing misbehaviors and various issues. Therefore we aim for an automated, realtime approach for anomaly detection. As a requirement, prototypes for standard workflows have to be examined. Based on measurements of several months, different features of HEP jobs are evaluated regarding their effectiveness for data mining approaches to identify these common workflows. The paper will introduce the actual measurement approach and statistics as well as the general concept and first results classifying different HEP job workflows derived from the measurements at GridKa.

A Grid Computing Based Power System Monitoring Tool Using Gridgain

With the advancement of civilization, Power Sector is undergoing drastic upheavals. With the ever increasing demand and dependence on electric power, protection of power system against failures remains a major challenge, particularly against cascading failures that lead to blackouts. There is a great demand for power systems protection that is scattered all around the globe. Effective monitoring of the power system parameters is a prerequisite in providing effective control and protection schemas. This paper advocates the use of grid computing in power system monitoring which discusses the suitability of grid computing to address the requirements of distinguished power system protection. Albeit, the Supervisory Control And Data Acquisition (SCADA) system is presently implied for monitoring power systems; yet it has its limitations. This paper proposes to use Grid Computing as an aid to the existing SCADA based power system monitoring & control framework and demonstrates is applicability by means of a grid based real-time power system monitoring system. The afore mentioned system has been deployed in desktop computers with GridGain 2.0 as middleware has been employed to set up the grid environment, all relevant details of the design framework has been shown.

Working with TCP\IP Based Network Monitoring System Using Linux

Nagios is a stable, scalable and extensible enterprise-class network and system monitoring tool which allows administrators to monitor network and host resources such as HTTP, SMTP, POP3, disk usage and processor load. Originally Nagios was designed to run under Linux, but it can also be used on several UNIX o132perating systems. This chapter covers the installation and parts of the configuration of Nagios. The purpose of this paper is not only to introduce to everyone the concept of distributed monitoring with Nagios but capturing the beauty of it to improve the security of computer networks. Firstly, an introduction to Nagios will be discussed to provide readers a brief overview of what Nagios is. Next, it will discuss how distributed network monitoring is an essential part to information security. It will then proceed to introducing the requirements needed to build a distributed Nagios network monitoring environment and demonstrate how Nagios can be configured to construct a distributed monitoring environment that helps improve the state of security of distributed networks. In essence, companies hould be aware of the need for hiring specialized security analysts to perform round-the-clock systems monitoring to secure their resources.