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In order to realize the quantitative management of higher education quality, an evaluation method of higher education quality management maturity based on OBE concept is proposed. Construct a phase space distribution structure model of higher education quality management maturity, establish a parameter set of higher education quality management maturity distribution index, adopt OBE concept to construct a fuzzy association rule distribution set, extract association regularity features, classify multi-dimensional attribute features, conduct data partition scheduling in the fuzzy clustering center according to the differences of statistical features, construct a feature decomposition model, and reorganize the ontology structure of higher education quality management maturity. The binary structure characteristics are reconstructed in the virtual database, and fuzzy clustering is carried out under the OBE concept according to the reconstruction results, so as to realize the optimal evaluation of the maturity of higher education quality management. The experimental simulation results show that this method has good feature clustering and high reliability in evaluating the maturity of higher education quality management.

The real-time monitoring and detection of the fruit carrying for monorail transporter in the mountain orchard are significant for the transporter scheduling and safety. In this paper, we present a fruit carrying monitoring system, including the pan-tilt camera platform, AI edge computing platform, improved detection algorithm and the web client. The system used a pan-tilt camera to capture images of the truck body of the monorail transporter, realizing monitoring of fruit carrying. Besides, we present an improved fruit carrying detection algorithm based on YOLOv5s, taking the “basket”, “orange” and “fullbasket” as the object. We introduced the improved attention mechanism E-CBAM (Efficient-Convolutional Block Attention Module) based on CBAM, into the C3 module in the neck network of YOLOv5s. Focal loss was introduced to improve the classification and confidence loss to improve detection accuracy; to deploy the model on the embedded platform better, we compressed the model through the EagleEye pruning algorithm to reduce the parameters and improve the detection speed. The experiment was performed on the custom fruit-carrying datasets, the mAP was 91.5%, which was 9.6%, 9.9% and 12.0% higher than that of Faster-RCNN, RetinaNet-Res50 and YOLOv3-tiny, respectively, and detection speed at Jetson Nano was 72ms/img. The monitoring system and detection algorithm proposed in the paper can provide technical support for the safe transportation of monorail transporter and scheduling transportation equipment more efficiently.

Falls can have a fatal effect on elderly, and fall-related injuries are increasing dramatically with age. Studies on risk of fall show that falls are often caused by changes in gait characteristics. Early detections by visiting clinic or hospital contribute to the prevention of falls. However, most of the elderly are not willing to visit clinics or hospitals for health screening. Thus, it will be useful if unobtrusive health screenings were to be brought to their home. Design guidelines for the home-based floor-mat include easy setup, simplicity, low cost, and less intervention of daily life are explained and highlighted. With the proposed daily monitoring system, the changes in gait characteristics, hardly distinguishable by the naked-eye, can be noticed. The reliability of the home-system was also verified with a comparison to Gaitrite. Finally, modeling experiments shows the effectiveness of the monitoring system. In conclusion, a home-based floor-mat system is able to provide daily non-intrusive monitoring.

The design of a handheld capnography device is in great demand because of its effective and practical uses in all cardiac arrest resuscitations, according to the recommendation of the American Heart Association. Herein, a handheld capnography device that can be used in clinical settings and the home environment is reported. The proposed device was developed by using an infrared CO₂ sensor, Arduino Mega2560, and a high-resolution display (2.8”). Furthermore, two rechargeable batteries (7.6V, 0.99A) and a secure digital card with a capacity of 16GB were incorporated to increase the portability and usability of the device. Algorithms were implemented to measure standard features, namely, inspired CO₂ (ICO₂), end-tidal CO₂ (EtCO₂), and respiratory rate (RR). The features of 15 healthy subjects were recorded by using the developed prototype and the standard capnography device (Capnostream^TM20 Model CS08798). Validation was performed with Bland–Altman plots. Findings revealed that mean differences $\pm$ standard deviations for the set limits of ICO₂, EtCO₂ and RR were 0.29 ± 1.30 millimeters of mercury (mmHg), 0.15 ± 1.77 mmHg and 0.40 ± 0.97 breaths per minute (bpm), respectively. Most of the differences among device measurements across all features fell within the 95% limits of agreement. Thus, the developed device may help manage respiratory distress conditions in and outside of a hospital setting.

Recently, the demand in tool support (performance analyzers, debuggers etc.) for efficient Java programming considerably increases. A universal, open interface between tools and a monitoring system, On-line Monitoring Interface Specification (OMIS), and the OMIS compliant monitoring system (OCM) enable to specify such a Java oriented monitoring infrastructure which allows for an extensible range of functionality intended for supporting various kinds of tools. The paper presents an approach to building a monitoring system which underlies this infrastructure, i.e. the issues of architecture, request processing, event handling, and processing RMI calls.

In order to improve the unsatisfied function of equipment attitude monitoring facilities, the equipment attitude monitoring system of the railway transportation based on WSN is designed. The framework of the software and the structure of the hardware had been studied and designed. The low pass filter has been applied to process the data of equipment’s attitude. The calculation algorithm of equipment attitude had been worked out and tested by using the models. Incidents caused by unexpected shift of equipment transported by train will be decreased, owing to this monitoring facilities.

The monitoring system conducts the remote sampling, data processing and mobile phone monitoring analysis on three important parameters of the water samples including the temperature, dissolved oxygen, and PH values. The STM32F103VET6 with ARM Core-M3 as the core processor is used for sampling and the collected data is sent to the remote server through ATK-SIM900A GPRS module with a 12-bit AD converter, the Android mobile phone users can download the data directly from the server. The system can realize the remote monitoring of field water quality through the Android mobile phone, providing a convenient real-time, continuous monitoring of water quality for the users.

Aiming at solar cells of the photovoltaic power station in decorate with remote, quantity, and easy to change and variety of features, this paper introduces a kind of wireless sensor network through real-time monitoring solar cell module, the design of the working state of the solar cells will be sent to the PC, make management through the PC interface can know exactly what the working state of every board, thus greatly simplify the maintenance of photovoltaic power station. First, through the source node acquisition solar cells of the voltage and current information, and the wireless network will carry information to base station node, the base station each node receiving the information source node and through the serial line transmitted PC. The whole monitoring system used the CC2430 as the main hardware platform and software of the ZigBee protocol stack. The experimental results show that the relative error voltage in 0.4 V within the current relative error in 0.04 A less than. The stability of the system is better, and satisfactory to solar cells monitoring stability requirement.

This paper introduces the monitoring of the gas oil lubrication system of aluminum foil mill based on WinCC and S7-300, mainly including the hardware composition, and the design of human machine interface of gas oil lubrication system. Since the running of this system, the loss has been reduced markedly. By the monitoring of human machine interface, the remote operating and real time monitoring may be realized better.

Sodium sulfur (NaS) battery energy storage system (BESS) was already widely used in the renewable energy and smart gird. Monitoring system as the control center of the whole system takes the responsibility for assurance system stable, secure, reliable and economic operation. This paper studied the requirements and problems to be solved of monitoring system for large-scale NaS BESS, then presents a modularized and distributed monitoring system architecture. The authors designed the architecture, communication protocol, software platform and function of the system. This work provides a reference for the large-scale NaS BESS designing and constructing.

In order to control in real-time ,closed-loop feedback the information, saving the money and labor,we distribute a platform of network data. It through the establishment of the platform in the oil drilling to achieve the easiest route of each device of the rig that conveying timely. The design proposed the platform to transfer networking data by PA which allows the rig control for optimal use. Against the idea,achieving first through on-site cabling and the establishment of data transmission module in the rig monitoring system. The results of standard field application show that the platform solve the problem of rig control.