Knowledge Modeling of power grid regulation based on reasoning map

To contribute to the intelligence and knowledge of power grid regulation and control operations, this paper presents a method of power grid regulation knowledge modeling based on ELG (Event Logic Graph), which includes an event word extraction based on a predicate-argument model, an event chain extraction and fusion based on event similarity theory, an event generalization based on a soft-pattern algorithm, and an event relationship recognition based on rule pattern matching method and joint constraints. Finally, this paper uses events as nodes and event relationships as directed edges to construct an affair graph stipulated by the power grid regulation and control regulations. The ELG is also called the new generation knowledge graph. But the knowledge graph can only describe the existence of entities and the upper and lower associations between entities. ELG can explain the inheritance, causality between entities and the logic of affair evolution, and the probability of transition between legacy and causality. Therefore, knowledge modeling based on ELG has intelligent advantages. Also, compared with ontology-based knowledge modeling methods, the method proposed in this paper can realize the dynamic representation of control operation knowledge, can express the logic of behavior and logic of operation, and also has higher retrieval accuracy.

Slovenian Territorial Defense in the Ten-Day War

In 1991, the process of disintegration of the Socialist Federal Republic of Yugoslavia began. The former Socialist Republics of Croatia and Slovenia were the first to announce their secession from the Federation in the last days of June. To restore the constitutional order, units of the Armed Forces of the SFR of Yugoslavia were sent to Slovenia, which faced the armed resistance of the Slovenian Territorial Defense (TO RS or TOS). In the Ten-Day War, the Federal troops, despite their numerical and technical advantage, suffered a defeat in the confrontation with the TOS subunits. Decisive for the success of Slovenian actions turned out to be the right choice of method of operation, knowledge of the combat environment, as well as high morale and support provided by the civilian population. The example of the Ten-Day War, an analysis of its course, shows that with the appropriate use of the TOS forces, they can conduct an effective fight against operational troops and be a fully-fledged component of the Armed Forces.

IoT Based Smart Parking Monitoring Using Labview and Node MCU

This paper is regarding planning a PC-based observance parking system supported IoT that may be applied at the park-like at the searching advanced and offices. This paper focuses on the event of front panel victimization National Instrument's LABVIEW package and Node MCU, Personal Computer (PC), and NODE MCU. The traditional parking lot system doesn't have a board and it cannot show the vacancy of automobile parking space. The user must gamble to hunt any vacancy and need to watch for the opposite automobile to exit from the automobile parking space. Up to the traditional parking system, it'll create the automobile parking space become well organized and user friendly. This paper can produce an automobile detection system by developing a PC-based front panel of parking lot operation knowledge. The system can convert the output from the sensing element to the programmable language to the computer-based mostly board. The board aims to indicate the standing and automobile parking space vacancy. The NODE MCU is employed to supply interfacing between hardware and package. By victimization Lab, VIEW, and Node MCU, the simulation of the physical system will be developed to watch the quantities to be measured and the standing of the instrumentation within the plant from remote purposes while not accessing the inaccessible areas of the plant. Through the traditional parking system victimization Lab VIEW and Node MCU, the front panel is with success developed and explained by planning a physical model of automobile parking space with automobile detector operation. These PC-based observance systems will be applied in varied industrial applications like building security systems and mill automation.

The prevalence and types of coronary artery abnormalities in pediatric patients with Tetralogy of Fallot

Objectives: Tetralogy of fallot (TOF) is one of the most common diseases among cyanotic congenital heart diseases which is associated with 2-23% of coronary artery abnormalities. Pre-operation knowledge the anatomy of coronary arteries in patients with TOF eliminates damage to them during surgery and prevents post-operative complications such as myocardial ischemia and heart failure.Materials and methods:This retrospective study was done on all patients with TOF who were referred for diagnostic catheterization and angiography before total surgical correction from 2006-2016. All patients entered the study and all angiographic views including extreme caudal, LAO cranial , and selective coronary artery angiography were evaluated and reviewed accurately.Results: 332 cases of patients with TOF including from one month to 36 years old were reviewed. The prevalence of coronary artery abnormalities among them was 11.4% (38 from 322 individual). 9.1% and 15.3% of males and females had abnormal coronary anomalies but it was not significant statically (p-value: 0.064). In 13 of 38 patients with coronary anomalies , coronary arteries crossed right ventricular out flow tract (RVOT)(3.4%). The most common coronary abnormality was origin of the both main coronary arteries from left sinus of Valsalva.Conclusion:Compared with other populations, the abnormal arteries among the patients with TOF in our study is significant (11.4%) and accurate assessment of their courses is necessary before surgery. Single origin of coronary arteries from the left side was the most common finding in our study too.

Real-Time Implementation of Optimal Energy Management in Hybrid Electric Vehicles: Globally Optimal Control of Acceleration Events

Widely published research shows that significant fuel economy improvements through optimal control of a vehicle powertrain are possible if the future vehicle velocity is known and real-time optimization calculations can be performed. In this research, however, we seek to advance the field of optimal powertrain control by limiting future vehicle operation knowledge and using no real-time optimization calculations. We have realized optimal control of acceleration events (AEs) in real-time by studying optimal control trends across 384 real world drive cycles and deriving an optimal control strategy for specific acceleration event categories using dynamic programming (DP). This optimal control strategy is then applied to all other acceleration events in its category, as well as separate standard and custom drive cycles using a look-up table. Fuel economy improvements of 2% average for acceleration events and 3.9% for an independent drive cycle were observed when compared to our rigorously validated 2010 Toyota Prius model. Our conclusion is that optimal control can be implemented in real-time using standard vehicle controllers assuming extremely limited information about future vehicle operation is known such as an approximate starting and ending velocity for an acceleration event.

Spoken dialogue BIM systems – an application of big data in construction

Purpose With the rapid development in the internet technologies, the applications of big data in construction have seen considerable attention. Currently, there are many input/output modes of capturing construction knowledge related to all construction stages. On the other hand, building information modelling (BIM) systems have been developed to help in storing various structured data of buildings. However, these systems cannot fully capture the knowledge and unstructured data used in the operation of building systems in a usable format that uses the intelligent capabilities of BIM systems. Therefore, this research aims to adopt the concept of big data and develop a spoken dialogue BIM system to capture buildings operation knowledge, particularly for building maintenance and refurbishment. Design/methodology/approach The proposed system integrates cloud-based spoken dialogue system and case-based reasoning BIM system. Findings The system acts as an interactive expert agent that seeks answers from the user for questions specific to building maintenance problems and helps searching for solutions from previously stored knowledge cases. The practices of monitoring and maintaining buildings performance can be more efficient by the retrieval of relevant solutions from the captured knowledge to new problems when maintaining buildings components. The developed system enables easier capture and search for solutions to new problems with a more comprehensive retrieval of information. Originality/value Capturing multi-modes data into BIM systems using the cloud-based spoken dialogue systems will help construction teams use the high volume of data generated over building lifecycle and search for the most suitable solutions for maintenance problems. This new area of research also contributes to the current BIM systems by advancing their capabilities to instantly capture and retrieve knowledge of operations instead of only information.

A synthesis of research needs for improving the understanding of atmospheric mercury cycling

This synthesis identifies future research needs in atmospheric mercury science, based on a series of review papers, as well as recent developments in field data collection, modeling analysis, and emission assessments of speciated atmospheric mercury. Research activities are proposed that focus on areas that we consider important. These include refinement of mercury emission estimations, quantification of dry deposition and air–surface exchange, improvement of the treatment of chemical mechanisms in chemical transport models, increase in the accuracy of oxidized mercury measurements, better interpretation of atmospheric mercury chemistry data, and harmonization of network operation. Knowledge gained in these research areas will significantly improve our understanding of atmospheric cycling from local to global scales.

A synthesis of research needs for improving the understanding of atmospheric mercury cycling

This synthesis identifies future research needs in atmospheric mercury science, based on a series of review papers, as well as recent developments in field data collection, modeling analysis, and emission assessments of speciated atmospheric mercury. Research activities are proposed that focus on areas that we consider important. These include refinement of mercury emission estimations, quantification of dry deposition and air-surface exchange, improvement of the treatment of chemical mechanisms in chemical transport models, increase in the accuracy of oxidized mercury measurements, better interpretation of atmospheric mercury chemistry data, and harmonization of network operation. Knowledge gained in these research areas will significantly improve our understanding of atmospheric cycling from local to global scales.

The Performance Mining Method

Software Performance is a critical aspect for all software products. In terms of Software Operation Knowledge, it concerns knowledge about the software product's performance when it is used by the end-users. In this paper the authors suggest data mining techniques that can be used to analyze software operation data in order to extract knowledge about the performance of a software product when it operates in the field. Focusing on Software-as-a-Service applications, the authors present the Performance Mining Method to guide the process of performance monitoring (in terms of device demands and responsiveness) and analysis (finding the causes of the identified performance anomalies). The method has been evaluated through a prototype which was implemented for an online financial management application in the Netherlands.