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Physically occupy spaceWord LemmaPOS Tags: NN, NNSSecondary NodesPronounsObjectPOS Tags: PRP, Lemma: it, its, itselfPersonPOS Tags: PRP, PRP$, Lemma: I, you, myMasculine PersonPOS Tags: PRP, PRP$, Lemma: he, him, his, himselfFeminine PersonPOS Tags: PRP, PRP$, Lemma: she, her, herselfPeoplePOS Tags: PRP, PRP$, Lemma: we, they, them, ’em, themselvesDeterminersObjectPOS Tags: DT, Lemma: this, that, these, thoseProper NounsLocationPOS Tags: NNP, NNPS, NER Tag: LOCATIONPersonPOS Tags: NNP, NNPS, NER Tag: PERSONOrganizationPOS Tags: NNP, NNPS, NER Tag: ORGANIZATIONActions without SubjectsSubjectNATertiary NodesCreated during edge creation toaccount for missing nodesLocationPOS Tags: EXLocationPOS Tags: RP, Lemma = locationActionPrimary NodesEvents or activities connected with the entitiesWord LemmaPOS Tags: VB, VBD, VBG, VBN, VBP, VBZSecondary NodesAction nodes are NOT created for auxiliary verbsNot CreatedPOS Tags: VBTertiary NodesCreated during edge creation toaccount for missing nodesWord LemmaPOS Tags: VB, VBD, VBG, VBN, VBP, VBZ, TO, CCAttributesPrimary NodesProperties that further define the entities or actions.Word LemmaPOS Tags: JJ, JJR, JJS, RB, RBR, RBSTertiary NodesCreated during edge creation toaccount for missing nodesWord LemmaPOS Tags: IN (Prepositions)LemmaPOS Tags: CD, Word Lemma: “number” (Cardinals) Table 2. A summary of the edge creation protocols based on dependency relations. Table 2. A summary of the edge creation protocols based on dependency relations. Edge TypeDependencyDescriptionEdgeAgentA → nsubj → BNominal SubjectB → agent → AA → obl:agent → BOblique AgentsB → agent → AA → nsubj:xsubj → BSubjects of Embedded ActionsB → agent → AA → acl → BAdnominal ClauseB → agent → APatientA → obj → BDirect ObjectA → patient → BA → iobj → BIndirect ObjectB → patient

Introduction In the previous experiment, a pre-built DC motor speed control model was simulated and executed in real-time. In this experiment, one of the components, the switched mode converter will be explored in further detail. The next section deals with the theoretical background for this experiment followed by the simulation of a switched-mode DC converter. Finally, the simulation model is verified in real-time.Theoretical backgroundConsider half-bridge converter shown below: At no instant, can both switches be simultaneously ON, because this will lead to shoot-through because of directly shorting the DC bus. When switch S1 is ON, the output voltage Vo = Vdc. When switch S2 is ON, the output voltage Vo = 0. If S1 is switched ON for time Ton and S2 is switched ON for time Toff alternatively, then the average output voltage is given by Eqn. 1. In pulse width modulation, the total, Ton + Toff is held constant, called the switching period, Tprd. Inverse of this gives the switching frequency. As Ton is varied from 0 to Tprd, the output voltage varies between 0 and Vdc. The duty-cycle is the ratio of switching period during which, switch S1 must be held ON to generate the desired output voltage, as given in Eqn. 2.Vo = TonTon + Toff × Vdc = duty × Vdc(1)duty = VoVdc(2)The half-bridge converter allows only generation of a unipolar output voltage of variable magnitude. This limitation is overcome by using a full-bridge converter shown below: The output voltage is given in Eqn. 3 where Van and Vbn are the output voltage of each half-bridge with respect to the DC bus negative. The duty-cycle for each half-bridge is given in Eqns. 4 and 5.Vo = Van − Vbn(3)dutyA = 12 + Vo2×Vdc(4)dutyB = 12 − Vo2×Vdc(5) This configuration allows the output voltage to be varied between +Vdc and -Vdc. When Vo is positive: dutyA > 0.5 and dutyB , and when it is negative: dutyA and dutyB > 0.5. dutyA corresponds to the ratio of ON time to that of total switching time period, of switch S1. dutyB corresponds to the ratio of ON time to that of total switching time period, of switch S3. To generate the gate signal for switch S1 from dutyA, the duty-cycle is compared with a triangular carrier that varies from 0 to 1. The triangular carrier repeats every 1/fswitch, where fswitch is the desired switching frequency.Simulation of DC-DC switch-mode converterThe above operation is simulated in this section using Workbench. Open Workbench and create a new model file as follow: Click on to open the application. Pin () the Explorer dock on the right and the Toolbox dock on the left. Within the toolbar in the Explorer dock, click

Is defined typically by the actual token and lemma.Secondary nodes: These nodes are created by observing a combination of POS tags along with other factors such as the lemma or the named entity recognition tags. In these cases, the lemma of the created node is assigned a generic keyword.Tertiary nodes: These nodes are created when edges are created by reading the dependency relations. It may happen that an incoming dependency is coming from a word for which no primary or secondary node exists. Creation of Primary NodesFirstly, primary nodes are created by analyzing the parts-of-speech tags of the words. The properties for the nodes, i.e., the id, token, lemma, and parts-of-speech tags, are taken directly from the corresponding intermediate representation. The type of node created depends on the parts-of-speech tag of the word:Entity ← NN, NNS;Action ← VB, VBD, VBG, VBN, VBP, VBZ;Attribute ← JJ, JJR, JJS, RB, RBR, RBS. Creating Secondary NodesSome secondary nodes are also created with refined properties based on some additional conditions. These are listed below:Pronouns: Since pronouns are representative of nouns, they can be used to create different types of entities as mentioned below. The distinction in this case is made on the basis of the lemma of the word: it can be used to detect whether the entity is a person or an object. It can also detect the singular or plural nature of the entity. Additionally, it can also reflect the gender, which is added as an attribute node named “masculine” or “feminine”.

Types of parts-of-speech tags and the types of tertiary nodes are:Action nodes: VB, VBD, VBG, VBN, VBP, VBZ, TO, CC.Attribute nodes: IN (prepositions).CD (lemma = “number”).Entity nodes:EX, RP (lemma = “location”).A summary of the protocols for creating nodes is given in Table 1. 4.1.2. Creating EdgesFor edge extraction, various types of edges are added to the knowledge graph by categorizing several types of dependency tags. Agents Edges between subjects and actions are tagged as “agent”. This defines which entities are responsible for which actions. The agent relationship can be extracted from the dependencies as follows:Nominal subjects (“nsubj”): Nominal subjects primarily refer to the action causing proto-agents of a phrase. These dependencies can define which entities are responsible for which actions.Oblique agents (“obl:agent”): This type of relation highlights nominal subjects of passive verbs. The effect is similar to the “nsubj” node.Subjects of embedded actions (“nsubj:xsubj”): It is often seen that the scope of one verb is embedded and controlled by another verb. While the first verb exists as an open clausal complement (that is, without a direct subject), the controlling verb is associated with the subject. The “nsubj:xsubj” dependency connects those kinds of subjects with embedded actions.Adnominal clause (“acl”): This type of dependency connects verbs with nominals that modify the properties or state of the nominal. “acl” dependencies can thus be used to assign such actions to corresponding entities.Some examples are demonstrated in Figure 5 regarding these dependencies and how “agent” edges can be created from them. Patients Edges between actions