Automatic Warning Research Articles

MO357: Nephrology Consultation to Improve Acute Kidney Injury Outcome on General Wards

Abstract BACKGROUND AND AIMS Acute kidney injury (AKI) affects up to one in five hospitalized patients and is independently associated with high morbidity and mortality. Additionally, patients have an increased risk for developing chronic kidney disease (CKD) after AKI. The combined impact of short- and long-term consequences and the high incidence of AKI results in a significant financial burden. Adequate intervention and follow-up might reduce the clinical impact of AKI, however the evidence for this remains inconclusive. The aim of this prospective cohort study was to evaluate whether nephrology consultation had an impact on patient follow-up and clinical outcome after AKI. METHOD All patients, admitted to VU medical centre in Amsterdam between October 2018 and April 2019, were screened for AKI by an automatic warning system integrated into the hospital's electronic patient record. This warning system sent a signal if serum creatinine would rise >27 µmol/L in 48 h or increased by a factor of at least 1.5 within 7 days (KDIGO criteria for AKI). The nephrology or internal medicine resident would then assess eligibility. Exclusion criteria were: a rise in serum creatinine that did not represent an actual AKI, admittance to the intensive care unit at the time of the signal, admission for kidney transplantation and patients that died before consultation was possible. After identification, nephrology consultation was provided. For the least severe AKI cases (KDIGO stage 1), this was done by telephone after review of the patient record, and for severe AKI cases (KDIGO stage 2 and 3) by full clinical review. Patients were grouped according to adherence (consult or no consult) to this protocol. Adequate follow-up was defined as a specific post-AKI referral to a nephrologist or general practitioner after hospital discharge. Recovery of serum creatinine and 6-month mortality were used as primary measures of clinical outcome. RESULTS A total of 371 cases of possible AKI were identified by the warning system. Of those case, 218 cases were eligible for inclusion. In 160 cases, nephrology consultation was performed (consult group). In 58 cases, there was no consult (no-consult group). The average age was 67.4 years. The consult and no-consult groups were similar at baseline (mean age, male/female, incidence of hypertension and diabetes), besides a higher incidence of CKD in the consult group (79% versus 64%; P = 0.034). The consult group had a significantly larger percentage of severe AKI cases (stage 2 or 3 in 29.4% of cases versus 12.1%; P = 0.021). Treatment was initiated in 93.1% of consult cases and in 70.6% of no-consult cases (P < 0.001) and there was a more profound decrease in the serum creatinine level from peak till 6 months (–33.7% versus –19.4%; P = 0.033)). All-cause mortality (34.1% versus 27.6%; P = 0.510), post-AKI follow-up (83% versus 73.2%; P = 0.116) and median serum creatinine value at six months (119 µmol/L versus 100 µmol/L; P = 0.334) did not differ between the consult and no-consult group. A 6-month serum creatinine was only available for 50% of cases in both groups. CONCLUSION When compared with cases of generally less severe AKI in which nephrology consultation was not performed, cases with nephrology consultation were associated with higher rates of treatment of AKI, faster recovery of kidney function and similar mortality. The data are in line with earlier non-randomized research which concluded that nephrology consultation can be linked to improved outcome in AKI. Before any definitive conclusions can be drawn, these associations should be found replicable in a randomized multi-centre setting and cost-effectiveness and feasibility should be analysed.

Weather Radar in Complex Orography

Applications of weather radar data to complex orography are manifold, as are the problems. The difficulties start with the choice of suitable locations for the radar sites and their construction, which often involves long transport routes and harsh weather conditions. The next challenge is the 24/7 operation and maintenance of the remote, unmanned mountain stations, with high demands on the availability and stability of the hardware. The data processing and product generation also require solutions that have been specifically designed and optimised in a mountainous region. The reflection and shielding of the beam by the mountains, in particular, pose great challenges. This review article discusses the main problems and sources of error and presents solutions for the application of weather radar technology in complex orography. The review is focused on operational radars and practical applications, such as nowcasting and the automatic warning of thunderstorms, heavy rainfall, hail, flash floods and debris flows. The presented material is based, to a great extent, on experience collected by the authors in the Swiss Alps. The results show that, in spite of the major difficulties that emerge in mountainous regions, weather radar data have an important value for many practical quantitative applications.

Method of forest fire automatic early warning and alarm system design

Forest is a huge green wealth bestowed by nature to mankind, but forest fire will cause great harm. Automatic forest fire early warning and alarm system can warn the high fire risk areas in the forest, or find and alarm the forest fire as early as possible, which is of great significance to reduce the loss of forest fire. This paper introduces a construction method of forest fire automatic early warning and alarm system, which provides knowledge and experience accumulation for the subsequent research and development of related systems.

Research on the Early Warning System of Cold Chain Cargo Based on OCR Technology

This paper designs a set of semi-automatic intelligent cold chain cargo proximity warning system with wireless data transmission, lightweight Optical Character Recognition identification algorithm framework and electronic label automatic warning as the core technology for cold chain dairy Fast Moving Consumer Goods contractors. In terms of hardware, Pulse Frequency Modulation modulation and demodulation are used as the main technology to realize wireless transmission and reception of equipment, and digital electronic tags are added to warn the same batch of upcoming goods. In terms of software, based on Chinese-ocr algorithm, image preprocessing and recognition methods are studied, and an early warning system is designed. So as to realize semi-automatic early warning of cold chain logistics goods.

Automatic Warning System for Weather Station Power Supply

Weather observation is one of the important factors in agriculture. Data from weather observations can be used for various things, including to predict future risks due to these weather conditions. An Automatic Weather Station (AWS) is needed to read weather conditions continuously. Some of the devices that will be built for the AWS system are data communication, sensors, and power supply. AWS is usually installed in certain areas where there is no power source. Hence, it takes a power supply system that can stand alone and has a security system that can monitor the components connected to the system in real-time.
 This research successfully designed a power supply system for a weather station that is equipped with current and voltage measurement features for its load as well as a warning system feature in case of interference on GSM SIM900-based Weather Station. Based on the results of the study the system using solar cell modules has an efficiency of 14,1% and is supported with the help of batteries that can be recharged through solar energy. Using the INA219 sensor to measure the voltage and load current connected to devices that have an error percentage value of less than 1%, the data is then uploaded to Thingspeak. Testing of warning systems at the Weather Station is conducted using Magnetic reed sensors capable of detecting changes when the separation distance between the sensor and other magnets is more than 3cm.

Safety Management System Prototype/Framework of Deep Foundation Pit Based on BIM and IoT

With the huge demand for building underground spaces, deep foundation pits are becoming more and more common in underground construction. Due to the serious effects associated with accidents that occur in deep foundation pits, it is very important for underground construction safety management to be proactive, targeted, and effective. This research develops a conceptual framework adopting BIM and IoT to aid the identification and evaluation of hazards in deep foundation pit construction sites using an automated early warning system. Based on the accident analysis, the system framework of Safety Management System of Deep Foundation Pits (SMSoDFP) is proposed; it includes a function requirement, system modules, and information needs. Further, the implementation principles are studied; they cover hazardous areas, namely, visualization, personnel position monitoring, structural deformation monitoring, and automatic warning. Finally, a case study is used to demonstrate the effectiveness and feasibility of the system proposed. This research provides suggestions for on-site management and information integration of deep foundation pits, with a view to improving the safety management efficiency of construction sites and reducing accidents.

A BIM-Based Visual Warning Management System for Structural Health Monitoring Integrated with LSTM Network

Structural health monitoring is an important task in the construction and maintenance stage. Because sensors are widely distributed in large and complex building space, it is difficult to visualize and locate hazard sources. In this paper, a visual warning framework of structural health monitoring is proposed based on the building information modeling (BIM) platform. The monitoring data bound with the sensors is stored in the database, and the monitoring data is mined to obtain the warning information by the deep learning algorithm long short-term memory (LSTM); The BIM elements are associated with sensors to make the monitoring area correspond to the BIM model so that the sensor and monitoring area can be visible on the BIM platform. Through the development of an integrated plug-in, the user interface and the database are connected by back-end controls to realize the three-dimensional display of the monitoring space on the BIM platform, corresponding with the visualization of the monitoring data and the automatic warning based on LSTM. This study also integrates the Internet of things technology to automatically control the indicator lights based on real-time sensor data and prediction data. The system framework integrates the application of BIM, deep learning algorithm and Internet of things in structural health monitoring, it realizes the spatial visualization of monitoring area corresponding with monitoring data information, quickly locates and issues early warning of dangerous components. It provides a basis for remote structural health monitoring and safety management.

Temporary shutdowns of the high-head run-of-river HPP Fieschertal to prevent excessive turbine erosion during floods

Hydro-abrasive erosion on hydraulic turbines is economically and energetically important. To better understand the causes and consequences of turbine erosion and to further develop mitigation measures, the suspended sediment concentration (SSC) and size distribution of mineral particles in the turbine water of the 64 MW high-head run-of-river hydropower plant (HPP) Fieschertal, Switzerland, have been continuously measured since 2012. An innovative combination of measuring techniques is used: turbidimeters, single-frequency acoustics, densimetry, laser diffraction and gravimetric analysis of water samples. Automatic warnings have been defined in the HPP’s control system to allow for systematic HPP shutdowns when the SSC in the valve chamber exceeds the threshold value of 10 g/l for at least 15 minutes. During the flood of July 29 and 30, 2017 with an SSC peak of 110 g/l, the intake was closed and the HPP was shut down for half a day. This prevented about 8000 tons of fine sediment from entering the HPP, which corresponds to 9 % of the turbines’ annual suspended sediment load (SSL) in 2017, or 12 % of the SSL in an average year without a significant flood. If the intake had been closed one hour earlier, the SSL could have been further reduced by about 3000 tons. For an earlier closing of the intake in case of floods, the turbidimeter at the intake shall be complemented by an additional instrument capable of measuring also medium to high SSC. Apart from the described flood event, SSC peaks in the range of 5 to 20 g/l occurring typically in late summer were attributed to re-suspension events in the storage tunnel due to HPP operation.

Design and Implementation of the Weather Radar Mobile Monitoring System Based on WeChat Enterprise

In order to solve the problems of China’s new generation Doppler weather radar observation network, such as the lack of mobile monitoring platform, the untimely malfunction alarm and the slow interaction, a mobile operation monitoring system based on WeChat Enterprise has been designed, which is mainly composed of collection, processing, dispersal and feedback of radar’s operational status information, and interactive communication between different radar facilities and support personnel. This system can realize weather radar operating status monitoring based on cell phone, hierarchical automatic warning of operating status information, automatic video push of maintenance support activities and interactive feedback and exchange of information among maintenance support personnel, etc. Based on this system, the operational monitoring and technical support capabilities of China’s new generation Doppler weather radar are greatly improved, and it plays an important role in promoting the operational efficiency of the weather radar.

Research on dynamic data monitoring of marine bridge steel structure building information based on BIM model

According to the current situation of informatization in the field of marine engineering in China, this paper puts forward the idea of applying BIM technology (building information model) to implement BLM (building engineering life cycle management) system in the stage of design, construction, operation, and maintenance, so as to improve the core competitiveness of enterprises more quickly. BIM has powerful visualization and information integration ability, combines BIM with health monitoring, provides a good expression environment for monitoring information, and improves the interaction between monitoring information and BIM model. The experimental results show that the song fairy bridge detection in ocean engineering projects, the use of Revit structures, project structure, and the software sensor model, using visual warning based on BIM plug-in and data management platform, has realized the data view, view and data management, automatic warning, monitoring curve in this paper; the proposed method was verified and applied in practical engineering projects.

Using AI to Improve Corporate Governance

This paper mainly discusses the relationship between corporate governance and dynamic business performance in semiconductor industry. Although there have been many discussions on the relationship between corporate governance and corporate performance in the past, there is no consistent conclusion. We intend to analyze and compare the corporate governance variables group, the expression of long-term performance and the differences between upstream, midstream and downstream of semiconductor industry. In addition, because the existing problems of corporate governance can not be solved by the current rigid system, we attempt to cut in from the perspective of AI and propose the effect of automatic warning.

Online monitoring of the morphology of an industrial sugarcane biofuel yeast strain via in situ microscopy

In industrial yeast fermentation processes, single-cell yeast suspensions are usually preferable to cells in aggregates, as single cells exhibit a larger contact area with the nutrient medium, which in many cases helps optimize the process. In addition to affecting fermentation time and efficiency, cell aggregates (e.g., pseudohyphal yeast morphology) may also impair centrifugation systems, one of the most expensive and complex steps of the production process that involves the recovery of yeast cells for subsequent fermentation cycles. To date, no standard technique allows for a systematic diagnosis of yeast morphology in real time during sugarcane biofuel fermentation. Accordingly, we investigate an in situ microscope (ISM) for online monitoring of the density and morphology of an industrial Saccharomyces cerevisiae strain widely used in Brazilian distilleries (PE-2). During batch and repeated batch sugarcane molasses fermentation, the instrument revealed single cells, budding yeast cells, and pseudohyphae, all in a variety of sizes and shapes. The ISM image analysis indicated that the volume of single yeast cells increased by roughly 40% over the lag phase before budding and remained approximately constant thereafter. Pseudohyphae with three and more cells appeared mostly during the stationary phase. Cooling problems were simulated by raising the temperature from 33 to 45 °C. During this thermal stress, single cells as well as budding cells and pseudohyphae forming cells became smaller and exhibited intracellular inhomogeneities. From these results, we conclude that an ISM is a useful tool for monitoring yeast morphology during sugarcane fermentation. Atypical morphologies can be detected early and be used as an automatic warning system.

Control and Integration of Automatic Flood Warning and Alert System Using Internet of Things

The information capability of an impending flash flood or release of water from the dam which is available for the people near the catchment area of the river is deficient and unsystematic. Therefore in order to make it sufficient and systematic, information gathering the opening of dams, its capacity and its rapid increase in the level are monitored accurately. The data of the monsoonal shift and the climatic change are merged as the cloud data. The PA system along with the OPGW cables and the GSM based system which are used for making alert for the people in the catchment area gives direction over the elevated region for their safety which in turn saves the life of the people a lot.

Design and Development of Automatic Water Level and Quality Warning System of Latphrao Canal Community Bangkok, Thailand

The objectives of this research were to design and develop an automatic water level warning system for communities living along Khlong Lad Phrao (Lad Phrao Canal) in Bangkok. The development of the system was divided into the following four main parts: 1) a water level measurement system; 2) a precipitation measurement system; 3) a water quality testing system covering dissolved oxygen, pH, turbidity and electrical conductivity and 4) an internet alert system utilizing the LINE application and web-based application information display. The first three parts were to be solar-powered. The design and development effort showed that the system successfully measured water levels along with water quality with speed and precision. Moreover, the system was easy to measure results and was able to alert through the LINE application when water in Khlong Lad Phrao approached critical levels, thereby reducing damage from water levels. Precision testing of the developed water level and quality measurement systems found that precision was in the range of 99.74-99.77%.

A multi‐year assessment of sub‐hourly gridded precipitation for Switzerland based on a blended radar—Rain‐gauge dataset

AbstractBlended high‐resolution sub‐hourly precipitation fields are increasingly needed for nowcasting and automatic warnings systems. Here we present a 7‐year (2012–2018) assessment of (5‐min) precipitation characteristics for the topographically complex region of Switzerland. We use CombiPrecip, a blended radar—rain‐gauge product that provides high resolution (1 km2) hourly precipitation fields. Five‐minute fields (CPCD), fine enough to disentangle even the shortest convective events from longer‐lasting precipitation, are obtained by temporally disaggregating these hourly fields. A rain‐gauge verification of the sub‐hourly precipitation fields shows that CPCD out‐performs the radar‐only estimates both in terms of quantitative error and in detecting wet/extreme periods, making CPCD sufficiently accurate to be used with confidence as input fields for hydrological modelling or for regional model validation. The quantitative error of CombiPrecip at the 60 (10)‐min time‐scale, as expressed by the scatter, is 40% (22%) lower than that of the radar‐only product. Radar‐gauge discrepancies are large and the quantitative error of CPCD increases by 30% when decreasing aggregation times from 60 to 10 min. Although summertime 5‐min precipitation extremes are strongest and more frequent on average south of the Alps, where they contribute to approximately 10% of the seasonal total precipitation, the most intense extremes are observed over the Jura Mountains in the afternoon and the highest wet 5‐min frequency in the Prealps around the same time. Intense precipitation is more evenly distributed throughout the day south of the Alps. Extreme intensity and frequency peaks 2 hr earlier in the Prealps, the Jura Mountains and the Alps (~1600 UTC) compared to the Swiss Plateau (~1800 UTC). Extremes are less intense and frequent at high elevations (>2,000 MASL) than over the Swiss Plateau (<800 MASL).

Development of Automatic Warning System for Water Salinity in Bangkachao, Thailand

Development of Automatic Warning System for Water Salinity in Bangkachao, Thailand

Assessment of a Smartphone-Based Camera System for Coastal Image Segmentation and Sargassum monitoring

Coastal video monitoring has proven to be a valuable ground-based technique to investigate ocean processes. Presently, there is a growing need for automatic, technically efficient, and inexpensive solutions for image processing. Moreover, beach and coastal water quality problems are becoming significant and need attention. This study employs a methodological approach to exploit low-cost smartphone-based images for coastal image classification. The objective of this paper is to present a methodology useful for supervised classification for image semantic segmentation and its application for the development of an automatic warning system for Sargassum algae detection and monitoring. A pixel-wise convolutional neural network (CNN) has demonstrated optimal performance in the classification of natural images by using abstracted deep features. Conventional CNNs demand a great deal of resources in terms of processing time and disk space. Therefore, CNN classification with superpixels has recently become a field of interest. In this work, a CNN-based deep learning framework is proposed that combines sticky-edge adhesive superpixels. The results indicate that a cheap camera-based video monitoring system is a suitable data source for coastal image classification, with optimal accuracy in the range between 75% and 96%. Furthermore, an application of the method for an ongoing case study related to Sargassum monitoring in the French Antilles proved to be very effective for developing a warning system, aiming at evaluating floating algae and algae that had washed ashore, supporting municipalities in beach management.

ПЕРСПЕКТИВНЫЕ СПОСОБЫ РАСХОЖДЕНИЯ СУДОВ И АНАЛИЗ ИХ ЭФФЕКТИВНОСТИ

The article is devoted to the analysis of the most perspective and effective locally-independent methods of divergence of vessels for forming of the system of the automatic warning of collisions, providing safety of perspective autonomous vessels. Development of method of estimation of efficiency of methods of divergence of vessels, which characterizes the degree of safety of completion of process of divergence of vessels, is offered, since the moment of discovery of situation of dangerous rapprochement. The stages of process of decision-making divergence of vessels of necessity are considered at their rapprochement and choice of strategy of divergence. It is shown that a decision-making process contains the following stages: control of environment, including relative position and parameters of relative motion, exposure of situation of rapprochement of vessels, estimation of degree of danger of rapprochement and choice of strategy of divergence. Analytical expressions for formalization of the offered stages of process of decision-making divergence of vessels of necessity are resulted. It is shown that depending on the degree of danger of situation of rapprochement, it is necessary to choose strategy of divergence, coming co-ordination of maneuvers of the drawn together vessels from, foreseen ColReg. Thus character of maneuver of divergence is also determined by the value of situation indignation. As a rule, application of standard maneuver of divergence is foreseen, and in the situation of excessive rapprochement of vessels, in order to avoid the collision it is necessary to use the maneuver of urgent divergence. As the index of efficiency of the analytical collision avoidance systems vessels probability of safe completion of process of divergence, which is work of probabilities of successful finish of stages of process of decision-making on the choice of strategy of divergence, is offered. For the system of the automatic warning of collisions the methods of divergence with one dangerous target are offered by the change of course or speed of ship and with two dangerous targets by the combined maneuver of the repeated change of course of ship. After the preliminary analysis the perspective most effective methods of the mentioned types of maneuvers of divergence were offered. For the operative choice of parameters of maneuver of divergence of ship with a target the regions of impermissible values of parameters of deviation and region of acceptability parameters of deviation and output are offered. For the case of choice of maneuver of divergence of ship by the decline of speed the active or passive braking offers the method of forming of region of impermissible speeds and calculation of its scopes. In the situation of dangerous rapprochement of ship with two targets for the operative choice of parameters of maneuver of divergence of ship in work it is suggested to form the region of acceptability successive courses of deviation.

The Plant Health Monitoring System of the EDEN ISS Space Greenhouse in Antarctica During the 2018 Experiment Phase.

The EDEN ISS project has the objective to test key technologies and processes for higher plant cultivation with a focus on their application to long duration spaceflight. A mobile plant production facility was designed and constructed by an international consortium and deployed to the German Antarctic Neumayer Station III. Future astronaut crews, even if well-trained and provided with detailed procedures, cannot be expected to have the competencies needed to deal with all situations that will arise during a mission. Future space crews, as they are today, will be supported by expert backrooms on the ground. For future space-based greenhouses, monitoring the crops and the plant growth system increases system reliability and decreases the crew time required to maintain them. The EDEN ISS greenhouse incorporates a Plant Health Monitoring System to provide remote support for plant status assessment and early detection of plant stress or disease. The EDEN ISS greenhouse has the capability to automatically capture and distribute images from its suite of 32 high-definition color cameras. Collected images are transferred over a satellite link to the EDEN ISS Mission Control Center in Bremen and to project participants worldwide. Upon reception, automatic processing software analyzes the images for anomalies, evaluates crop performance, and predicts the days remaining until harvest of each crop tray. If anomalies or sub-optimal performance is detected, the image analysis system generates automatic warnings to the agronomist team who then discuss, communicate, or implement countermeasure options. A select number of Dual Wavelength Spectral Imagers have also been integrated into the facility for plant health monitoring to detect potential plant stress before it can be seen on the images taken by the high-definition color cameras. These imagers and processing approaches are derived from traditional space-based imaging techniques but permit new discoveries to be made in a facility like the EDEN ISS greenhouse in which, essentially, every photon of input and output can be controlled and studied. This paper presents a description of the EDEN ISS Plant Health Monitoring System, basic image analyses, and a summary of the results from the initial year of Antarctic operations.

Real Time Pedestrian Detection and Tracking for Driver Assistance Systems

In Autonomous driving technology detecting pedestrians and vehicles should be fast and efficient in order to avoid accidents. Pedestrian detection and tracking is challenging for complex real world scenes. In proposed system Kalman filter has been used to detect and track the pedestrians. From three frames initially eigen object is computed in video sequences for detection of moving objects, then shape information is used to classify humans and other objects. Moreover with the help of continues multiple frames occlusion between objects get calculated. In the proposed system an application is developed which gives automatic warning in case of doubtful activities performed by pedestrian of zone monitoring which can be used in various domains like defence and traffic monitoring. Proposed algorithm gives accurate moving object detection and advanced sensors are used to detect human movements ahead and alert the driver by using buzzer, result does not affect by body pose of individual.