An intelligent support system for local control center using meta-inference and reconstruction of knowledge-base

An integrated fuzzy expert system is presented to diagnose various faults that may occur in a regional transmission network and substations. Fuzzy reasoning method is applied, and it is discussed in detail. Discrimination of false operations or nonoperations of protective devices as well as the fault identification scheme are also analyzed, together with the fuzzy inference process. The proposed system is designed to improve efficiency, generality, and reliability of the solution. The system will replace a fault diagnosis system that had been tested as a part of an intelligent support system on a local control center in Korea.

The user interface to achieve IEC 61400-25 communication for virtual wind power plant is developed. The information from wind power plant is obtained by MMS service. And also, the data communication between the local control center and the remote control center is achieved by web service. MMS service is implemented with the aid of MMS Ease-lite and visual c++. MMS server detects and saves the information of the wind generator such as element type, the temperature, the speed and the voltage needed for the virtual system. MMS client can receive the information for control and monitoring through MMS service. And MMS client can be a web service server when the remote control center asks to send the data. The proposed user interface enables to access the data related with the wind power plant through the Ethernet at anyplace.

Ventricular assist device (VAD) implantation for patients with advanced heart failure as an alternative therapy to heart transplantation has increased patients' survival and quality of life thanks to improvements in the pump's geometry, local and supervisory control systems. Suppose the supervisory control system for these devices is considered an open system, in that case, an approach considers integrating various agents that interact collaboratively to determine the behavior. In addition to the physical device and its local control system, there is the patient and the medical team assisting this patient. In this way, a VAD can be considered a cyber-physical device, in which characteristics such as intelligence, connectivity, and reactivity can be observed. Based on this paradigm, there was a possibility of improvement from the interaction and collaboration between cyber-physical VADs capable of communicating with a supervisory control system. While the local control system is responsible for the device's drive functions, the supervisory system is responsible for managing several local control systems of each VAD. The connectivity between the devices is a fundamental characteristic for the proposal of intelligent VADs, which can offer the multidisciplinary medical team tools to monitor the patient's condition and decision support algorithms that make up the supervisory system. This new context causes an evolution from cyber-physical VADs to an architecture based on Reference Architecture Model for Industry 4.0 (RAMI 4.0) to allow the reconfiguration of VADs in a new paradigm based on Health 4.0.

In order to monitor bred fish in an offshore aquaculture cage farm and the aquatic environment surrounding the farm daily, a centralized remote monitoring system was developed. The system is composed of a group of Remote Detecting Nodes (RDNs) and a Local Monitor and Control Center (LMCC). RDNs based on the techniques of circular multi-beam detection and multi-path signal process were placed in the center of the cages to scan the inner space and measure the aquatic environment. LMCC based on LabVIEW was situated in the office to manage all the RNDs remotely and show fish activities and the state of net clothes. The communication between LMCC and RDNs used GPRS wireless data transmission technology. The system prototype was tested in the field of offshore aquaculture cage farm in Quanzhou, China. Results show that the system is reasonable design, simple operation, easy placement, and robust under different environmental conditions. It can monitor the aquatic environment and fish activities remotely and real-timely, provide users with a variety of culture information such as fish amount, fish growth conditions and culture safety in the offshore fish cage, and give an alarm in time when net clothing damage or fish escape.

This paper describes basic principles and purpose for applying wide area protection schemes, also known as remedial action schemes (RAS) or system protection schemes (SPS). In the areas of power system automation and substation automation, there are two different trends: centralization and decentralization. More and more dynamic functions are moving from local and regional control centers towards central or national control centers. At the same time we also observe more "intelligence" and "decision-power" moving closer towards the actual power system substations. Greater functional integration is being enclosed in substation hardware. This raises discussions concerning reliability (security and dependability). The main targets for this paper are to: (1) sort out the terminology used in this area; (2) describe different application areas and related requirements; (3) illustrate different design principles - "top-down", "bottom-up", hierarchy, flat, etc., for different applications; (4) identify similarities and differences between classic equipment protection and system protection -concerning philosophy as well as concerning product and system design; and (5) show the value of wide area protection; (6) illustrate the great breakthrough for wide area protection, since the introduction of synchronized phasor measurements, based on PMUs (phasor measurement units).

This paper describes an advanced restoration support system for regional load dispatching and local supervisory control centers. A model-based diagnostic task shell is applied to diagnose network faults, and an inference algorithm not dependent on a specific power system has been developed exclusively for restoration plan determination. With this system, adjustments for network fault diagnosis, necessitated by power system facility expansion or alteration, can be made simply by adding or changing models. Restoration knowledge can be partially revised in the case of restoration policy change. Connected on-line to an operator training simulator, this system's restoration support performance has been verified through daily restoration training. In this process, several problems of the system were detected and corrected. Consequently, it has become possible for the system to support restoration almost as well as a trainee, thereby confirming that connecting this system to an operator training simulator is an effective method for both verifying and improving restoration support system performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper describes an advanced restoration support system for regional load dispatching and local supervisory control centers. A model-based diagnostic task shell is applied to diagnose network faults, and an inference algorithm not dependent on a specific power system has been developed exclusively for restoration plan determination. With this system, adjustments for network fault diagnosis, necessitated by power system facility expansion or alteration, can be made simply by adding or changing models. Restoration knowledge can be partially revised in case of restoration policy change. Connected on-line to an operator training simulator, this system's restoration support performance has been verified through daily restoration training. In this process, several problems of the system were detected and corrected. Consequently, it has become possible for the system to support restoration almost as well as a trainee, thereby confirming that connecting this system to an operator training simulator is an effective method for both verifying and improving restoration support system performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Energy efficient clustering algorithm for maximizing lifetime of wireless sensor networks

In recent years, with the progress of society and the development of the economy, the number of cars in China has been increasing. In wireless communication networks, the choice of wireless nodes has a greater impact on the improvement of system performance (such as channel capacity, coverage area, etc.). The intelligent vehicle target detection system can perceive and recognize the surrounding objects such as pedestrians and vehicles through sensors, which is the basis for realizing the unmanned driving of intelligent vehicles. In a wireless environment where multiple wireless nodes coexist, current research focuses on how long it takes to re-plan the selection of wireless nodes (for mobile environments) and how to allocate and manage wireless nodes, such as where under the conditions of wireless, who will wireless with whom, and in what way (such as auto focus, digital fusion, or other) wireless, etc.; the dedicated centralized controller (such as the base station of the infrastructure-based wireless access network) determines the wireless partner (i.e., centralized type selection), or the wireless node decides by itself (i.e., distributed selection); select the appropriate number of wireless nodes to take into account the system performance gain and implementation complexity. The popularity of automobiles has brought great convenience to people's lives, but it has also brought greater traffic pressure. At present, the amount of domestic automobile traffic has increased exponentially, and urban traffic congestion has become more serious, and even caused serious traffic accidents, directly affecting people's quality of life. The emergence of intelligent transportation systems has effectively alleviated road traffic pressure and reduced the incidence of traffic accidents. As an important part of the intelligent transportation system, the research of intelligent vehicles has received extensive attention. Intelligent vehicles use a variety of sensors installed on the body to sense the environment, and realize intelligent driving functions such as lane line detection, obstacle detection, dynamic cruise control, and unmanned driving, which is conducive to reducing the incidence of traffic accidents and improving the safety of vehicle driving. At present, in the research of target recognition and tracking of intelligent vehicles, the traditional target detection method is mainly based on artificial feature extraction, which is difficult to describe more complex or higher-order image features, and the tracking effect is not good, which limits the target detection. An intelligent vehicle is an intelligent system with functions such as environment perception, planning decision-making, and operation control, and is an important part of the intelligent transportation system. Identify the effect. In response to these problems, we present a study of the target recognition and tracking of intelligent vehicles based on grid map and lidar sensor technology. To verify the proposed method in the actual scene, we identify and track the vehicle ahead on the road through a car equipped with a lidar sensor. The meaning of target detection: target detection, also called target extraction, is an image segmentation based on target geometric and statistical features. The results show that the proposed research method can accurately identify the vehicle in front and detect the moving targets such as pedestrians. The tracking trajectory is also consistent with the expected route. The results show that the laser radar-based vehicle target recognition and tracking in this study is effective. In the 10 frames of images, the average time taken for the recognition of one frame of image is 9.8 ms, while the traditional method is 12.9 ms. Technology can improve reliable road information for intelligent vehicle driving and improve the transportation efficiency and safety performance of intelligent vehicles. There are two main target detection methods for lidar: detection methods based on feature extraction and detection methods based on grid maps.

Diagnostics and real-time forecasting of the technical condition of aircraft electrical equipment plays a crucial role in the process of operation. In order to diagnose and predict the technical condition, it is reasonable to apply digital twin technology. The functioning of various components of aviation electrical equipment is determined by physical and chemical processes occurring in these objects. To model and analyze the dynamics of such processes, the authors have developed a method of mathematical prototyping of energy processes – a unified approach to building correct (not contradicting physical laws) models of processes of various nature. The equations derived by the method of mathematical prototyping make models with inputs containing measurable characteristics, and outputs containing controlled characteristics of the object. Such models are the mathematical basis of digital twins of aviation electrical equipment. Building of the mentioned mathematical models demands big computational expenses; hence there is a necessity of development of the programtechnological platform of digital twins, providing construction and storage of digital twins of aviation electrical equipment. The construction of digital twins is performed on the ground and the use of already constructed digital twins is performed on board the aircraft. The development of the concept of such a digital twin platform is the focus of this paper.

The infrastructure for smart grid is classified into three categories: infrastructure for electric power generation, delivery, and consumption, infrastructure for information measurement, surveillance, and management, and infrastructure for information communication. In this paper, we derive the total amount of traffic in the network, average end-to-end communication delay, and availability when using IP and CCN (Content-Centric Networking) as the communication infrastructure for a smart grid, respectively. Through several numerical examples, we clarify under what conditions either IP or CCN is suitable for the communication infrastructure of a smart grid. We found that, in terms of the total amount of traffic and the average end-to-end communication delay, CCN is effective compared with IP except when cache hit rates in RGCC (Remote Grid Control Center) and LGCC (Local Grid Control Center) are very low. We also found that, in terms of availability, the performance advantage of CCN over IP is marginal.

Serious drug abuse and addiction related to dextromethorphan-containing cough preparations has been a problem in the United States since the 1950s, but few physicians are aware of it. Physicians must be alert to the type of substances and quantities used and misused by patients in obtaining a thorough routine history of over-the-counter medication use. We describe the case of a 66-year-old clerical worker who ingested 4 to 16 oz of dextromethorphan on a regular basis over an 8-year period. We consulted with our local Poison Control Center and undertook a literature search to research previous reports of similar cases to identify the features that would aid physicians in recognition and management of this problem. Despite the availability of a substantial number of case reports in specialty journals, there are almost no reports in the primary care literature of chronic dextromethorphan addiction. Our case highlights the difficulties in making an appropriate diagnosis and in obtaining effective help for the patient.

Effects of patient load and travel distance on HIV transmission in a cohort of serodiscordant couples in rural China: a longitudinal analysis

[Author Affiliation]Jennifer Walton. 1 Department of Pediatrics, Nationwide Children's Hospital, Columbus, Ohio.Michelle Byrum. 2 Department of Clinical Services and Care Coordination, Nationwide Children's Hospital, Columbus, Ohio.Amanda Shumaker. 2 Department of Clinical Services and Care Coordination, Nationwide Children's Hospital, Columbus, Ohio.Daniel L. Coury. 1 Department of Pediatrics, Nationwide Children's Hospital, Columbus, Ohio.Address correspondence to: Jennifer Walton, MD, MPH, Department of Pediatrics, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH 43205, E-mail: Jennifer.Walton@nationwidechildrens.orgTo The Editor:Attention deficit hyperactivity disorder (ADHD) is one of the most commonly diagnosed disorders of childhood. Currently, ADHD affects ∼4-9% of the youth population (National Institutes of Health 2000).There are many types of treatments for ADHD, which vary from behavioral therapy to medication. The most commonly prescribed medications for the treatment of ADHD are psychostimulants, derived from either amphetamine or methylphenidate (Wilens and Spencer 2000). However, other treatments include nonstimulant medications such as atomoxetine, clonidine (immediate and extended release), and guanfacine (immediate and extended release).Guanfacine extended release is an α-agonist that is approved to treat ADHD in children and adolescents. Before receiving approval from the United States Food and Drug Administration (FDA) for use in ADHD, guanfacine was approved for use as an antihypertensive medication. In a placebo-controlled trial, guanfacine extended release was shown to be effective at reducing ADHD symptoms, while having mild to moderate adverse effects (somnolence, fatigue, and sedation) that generally subsided after the first 2 weeks of treatment (Sallee et al. 2009). Compared with guanfacine immediate release, guanfacine extended release has a longer duration of action and fewer fluctuations in concentration. As the use of guanfacine extended release in the treatment of ADHD is relatively new, there is not much information regarding intentional or accidental overdose. We present a case report of an accidental overdose of guanfacine extended release in a boy, which resulted in prolonged hypotension, bradycardia, and admission to the intensive care unit.Case ReportThe patient was an 8 years and 11 months old male with ADHD and a history of auditory hallucinations. His home medications include long-acting dexmethylphenidate 20 mg in the morning, short-acting dexmethylphenidate 5 mg at noon, guanfacine extended release 3 mg in the morning, and risperidone 0.25 mg in the evening. He and his parents reported good benefit from this pharmacological regimen.The outpatient clinic staff were notified at 1:26 p.m. by the patient's school that he was accidentally given guanfacine extended release twice, once in the morning (as prescribed) and again at noon. The school stated that at the time of the second administration of guanfacine, the patient did not have any adverse reactions. However, the clinic staff asked the school personnel to contact the local poison control center, monitor the patient's hydration, and monitor for increased fatigue and lowering of blood pressure. School personnel were also advised that if the patient's symptoms worsened, they were to take him to the nearest emergency department (ED). The patient's mother was also notified and made aware of this situation.The patient came home from school at ∼4:30 p.m. and was noted to have significant fatigue; he fell asleep easily but was difficult to arouse. The patient also seemed cold and had been perspiring since he came home. His mother took him to an urgent care center, where his pulse was recorded to be 56 beats per minute and his blood pressure was recorded to be 97/43 mm Hg. …

Power systems are presently remotely operated and controlled from control centers that receive online information about the power system state. Control center operators have very high-demanding tasks that makes their training a key issue for the performance of the whole power system. Simulators are usually used by electrical utilities for this purpose, but they are very expensive applications as they have to model the control center as well as the power system. On the other hand, their use requires the preparation of the training sessions by a qualified training staff, which is a very time consuming task. Intelligent tutoring systems (ITS) provide some new possibilities for training control center operators without much assistance of the teaching staff. Also, the expert system used in the control center can easily be adapted to an ITS. This paper presents the training module of SPARSE, the expert system for fault analysis and power restoration assistance in the Portuguese transmission network. >