Scenario 1. PTC exploits the Programme Intellectual Property on a For-Profit Basis alone (or in collaboration with a Distributor or marketing/sales agent under which PTC retains overall control of worldwide commercialization).
Scenario 1. In the event that the Net Settlement Fund exceeds the total of the Amounts Allegedly Withheld for all Claimants submitting Valid Claims, Claimants submitting Valid Claims will be paid their Amount Allegedly Withheld, regardless of the Payment Group (defined below) to which they are assigned. Any remaining amount left in the Net Settlement Fund will be paid to the Cy Pres Recipients identified in § 1.11.
Scenario 1. If Seller breaches a CHP PPA with the Buyer, and Xxxxx has another PPA with Seller, then cross default could be triggered; provided that another PPA means a PPA between the specific Seller, as signatory and as referenced in Section 4.2.8.4.2, and the specific IOU Buyer, as signatory to such PPA. Another PPA is a contract between the Buyer and Seller for electric power, and not a contract for other goods or services.
Scenario 1 incident report from a Railway Operator. There aren’t many public incidents in this sector, but in May of 2018, the Danish state rail operator was hit by a DDoS cyberattack, causing a breakdown which prevented train passengers across the country from buying tickets on that day. This scenario represents information sharing of a cyber-security incident in the network of a RST, the steps and procedures to inform the community without compromising the reputation of the victim nor the operator, supporting CSIRT operations and threat intelligence.
Scenario 1. Smart City AI-aided emergency monitoring system Municipal operation centres play an important role in the response to emergencies and natural disasters through communication and coordination (Kula & Guler, 2016). City management centres support a variety of functions, for example: monitoring of vehicles and public transportation, control of traffic flow and adjustment of traffic lights to avoid traffic jams, monitoring and tracking of accidents in real time, enabling correct resource allocation to address a situation, collecting data on environmental conditions, allowing the measurement of air pollution, water levels and seismic activity, as well as aspects such as public participation and accountability through the monitoring of employees (Xxxxxxx, 2014a). Their operations are based on real-time analysis, which are, however, mainly manipulated by isolated systems and controlled by a single agency (Xxxxxxx, 2014b).
Scenario 1. Robot proactively reaching a group (of about 3 persons) First full scenario is shown in Figure 7. • Start condition: robot in interacting mode (perhaps showing a message on the screen). • End condition: the robot starts an interaction with the group (other ending conditions could be request from the terminal to go to a specific place or problems to the robot). State descriptions: • Detect Groups: The robot is detecting groups of person, looking for people interested in interacting. • Approach: The robot approaches the selected group. • Enter the group: If the group shows signs of being interested in the interaction the robot completes its approach- ing phase, getting at an interaction distance. • Interact:
Scenario 1 a) the Employer makes a lump sum payment to Delfluent (the "Lump Sum Payment 1") in an amount which enables Delfluent to repay the Senior Debt Outstanding in full;
Scenario 1 a) the Employer makes a lump sum payment to Delfluent (the "Lump Sum Payment 1+") in an amount of Euro 18 (eighteen) million;
Scenario 1. 60% GLF (long term) This water balance will be based on a 60% GLF. All input information is as per document [122] The Consultant shall take into consideration the decommissioning and phasing out of ash dam 1, 2 and 3 in the water balance.
Scenario 1. Demonstrator #4 The assessment of the operational scenario outlined by the Demonstrator #4 is quite straightforward: looking at the standard scenarios defined by ENAC (see section 3.4.2.3), the foreseen operations fits almost perfectly with S04 and S05 (depending on the mass of the RPAS). Being at the moment not yet defined the RPAS model to be used in demonstrator #4, this section will illustrate technical prescriptions and operational limitations for the two mass categories: less or equal to 4 kg and up to 25 kg. Standard Scenario S04: RPAS with a MTOM below or equal to 4 kg, without an inoffensive nature (art. 12), operated in extra-urban areas and over construction sites or linear infrastructures, e.g. highways, power lines, railways, gas pipelines Technical prescriptions: RPAS on-board lights: front-right green light, front-left red light, rear white light (in the case of night VLOS) Operational limitations Flight conditions: VLOS Maximum Altitude: 150 m in daylight VLOS / 50m in night VLOS Maximum distance from the pilot: 500 m from the pilot in daylight VLOS / 100m in night VLOS Maximum speed: 5 m/s Maximum wind speed: 5 m/s Minimum buffer size: 30 m (from other buildings/infrastructures) Minimum buffer size when “geofencing6” function available: 15 m Minimum buffer size for tethered operations: 5 m Conditions Operations should be conducted: In accordance with the operations manual defined by the operator and the flight manual provided by the manufacturer By a pilot with adequate qualification In accordance with the flight rules and access to the airspace The operator is responsible to check whether flight limitations are in place in the area of the operations. Standard Scenario S05: RPAS with a MTOM in between 4 and 25 kg, without an inoffensive nature (art. 12), operated in extra-urban areas and over construction sites or linear infrastructures, e.g. highways, power lines, railways, gas pipelines Technical prescriptions RPAS on-board lights: front-right green light, front-left red light, rear white light (in the case of night VLOS) Independent flight termination system, other than the command and control system Command and control system with geofencing and data link recovery functionalities
