The multilevel inverters (MLIs) are classified into three topologies such as Diode Clamped, Flying Capacitor and Cascade Multilevel Inverter (CMLI). CMLI topologies include two kind of structure that is named symmetri...
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Maintenance starts with reliable diagnostics. programming Logic Controllers (PLCs) are often equipped with a high degree of diagnostic procedures in order to ensure that the processing unit is functioning correctly. I...
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ISBN:
(纸本)9781629935881
Maintenance starts with reliable diagnostics. programming Logic Controllers (PLCs) are often equipped with a high degree of diagnostic procedures in order to ensure that the processing unit is functioning correctly. It is vital to verify that the system with its programme is still within a 'healthy' state, otherwise a safety function is called and the system is brought into a safe state, or if possible, defect and malfunctioning components are exchanged during operation and the process can continue without shutting down the system. However, when it comes to smaller devices such as intelligent sensors, embedded controller devices with the functionality of an e.g. PID (Proportional-Integral-Derivative), predictive controller, filter or analytical algorithm, which is embedded into a FPGA or micro-controller then diagnostics and verification methods are often not considered in the way they should be. For example, if an intelligent sensor system is not able to diagnose that the sensor-head is malfunctioning, but the sensor-head still provides some data, then the smart algorithm bases its calculation on wrong data, which can cause a dangerous situation. This paper investigates and shows recent results to combine diagnostic methods for small scale devices. Several safety-related structures are considered with a high degree of diagnostic coverage. The paper presents relevant procedures and structures to increase the reliability of small devices without utilising a full scale microcontroller system.
The goal of Partitioned Global Address Space (PGAS) languages is to improve programmer productivity in large scale parallel machines. However, PGAS programs may have many fine-grained shared accesses that lead to perf...
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The multilevel inverters (MLIs) are classified into three topologies such as Diode Clamped, Flying Capacitor and Cascade Multilevel Inverter (CMLI). CMLI topologies include two kind of structure that is named symmetri...
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ISBN:
(纸本)9781467363914
The multilevel inverters (MLIs) are classified into three topologies such as Diode Clamped, Flying Capacitor and Cascade Multilevel Inverter (CMLI). CMLI topologies include two kind of structure that is named symmetric and asymmetric topologies. Asymmetric Cascade MLI (ACMLI) topologies consist of unequal DC sources. Many modulation techniques have been used in ACMLI topology such as Multi-Carrier PWM (MC-PWM), Space Vector PWM and Selective Harmonic PWM. The MC-PWM technique is achieved by four different types. In this study, MC-PWM techniques which are named Phase Disposition PWM, Phase Opposition Disposition PWM, Alternate Phase Opposition Disposition PWM and Phase Shifted PWM have been compared. It is uncovered that Phase Opposition Disposition PWM technique is more convenient in terms of Total Harmonic Distortion of output voltage and current signals and in terms of the quality of power factor in ACMLI which is performed in this study.
Data mining has become an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering interesting and previously unknown knowledge from...
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An L(0,1)-labelling of a graph G is an assignment of nonnegative integers to the vertices of G such that the difference between the labels assigned to any two adjacent vertices is at least zero and the difference betw...
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An L(0,1)-labelling of a graph G is an assignment of nonnegative integers to the vertices of G such that the difference between the labels assigned to any two adjacent vertices is at least zero and the difference between the labels assigned to any two vertices which are at distance two is at least one. The span of an L(0,1)-labelling is the maximum label number assigned to any vertex of G. The L(0,1)-labelling number of a graph G, denoted by λ0.1(G) is the least integer k such that G has an L(0,1)-labelling of span k. This labelling has an application to a computer code assignment problem. The task is to assign integer control codes to a network of computer stations with distance restrictions. A cactus graph is a connected graph in which every block is either an edge or a cycle. In this paper, we label the vertices of a cactus graph by L(0,1)-labelling and have shown that, △-1≤λ0.1(G)≤△ for a cactus graph, where △ is the degree of the graph G.
An L(0,1)-labelling of a graph G is an assignment of nonnegative integers to the vertices of G such that the difference between the labels assigned to any two adjacent vertices is at least zero and the difference betw...
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An L(0,1)-labelling of a graph G is an assignment of nonnegative integers to the vertices of G such that the difference between the labels assigned to any two adjacent vertices is at least zero and the difference between the labels assigned to any two vertices which are at distance two is at least one. The span of an L(0,1)-labelling is the maximum label number assigned to any vertex of G. The L(0,1)-labelling number of a graph G, denoted by λ0.1(G) is the least integer k such that G has an L(0,1)-labelling of span k. This labelling has an application to a computer code assignment problem. The task is to assign integer control codes to a network of computer stations with distance restrictions. A cactus graph is a connected graph in which every block is either an edge or a cycle. In this paper, we label the vertices of a cactus graph by L(0,1)-labelling and have shown that, △-1≤λ0.1(G)≤△ for a cactus graph, where △ is the degree of the graph G.
Data mining has become an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering interesting and previously unknown knowledge from...
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Data mining has become an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering interesting and previously unknown knowledge from very large real world database. These databases contain potential gold mine of valuable information, but it is beyond human ability to analyze massive amount of data and elicit meaningful patterns by using conventional techniques. In this study, DNA sequence was analyzed to locate promoter which is a regulatory region of DNA located upstream of a gene, providing a control point for regulated gene transcription. In this study, some supervised learning algorithms such as artificial neural network (ANN), RULES-3 and newly developed keREM rule induction algorithm were used to analyse to DNA sequence. In the experiments different option of keREM, RULES-3 and ANN were used, and according to the empirical comparisons, the algorithms appeared to be comparable to well-known algorithms in terms of the accuracy of the extracted rule in classifying unseen data.
Accelerators such as graphics processing units (GPUs) provide an inexpensive way of improving the performance of cluster systems. In such an arrangement, the individual nodes of the cluster are directly connected to o...
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