Research Contributions Sample Clauses

Research Contributions. Without limiting the foregoing, the Parties agree to commit the resources set forth in this Section 2.2 to perform their obligations under the Research Plan: (a) Axys will initially provide Cytovia with approximately [ * ] each of approximately four hundred thousand (400,000) compounds (each, an "Axys Compound") in a [ * ] format to be delivered to Cytovia in approximately equal installments over the first [ * ] of the Research Term, or as soon as reasonably practicable thereafter. After Cytovia completes its screening of such compounds, or within thirty (30) days after [ * ], whichever is earlier, the Parties will determine in good faith whether screening of additional compounds is appropriate. If such additional screening is agreed to, Axys will provide Cytovia with an additional quantity of compounds as determined by the JRC, not to exceed an additional three hundred thousand (300,000) compounds in total, as soon as reasonably practicable following such determination. Upon completion of all screening hereunder Cytovia will, at Axys' election, return or destroy remaining compound inventories provided by Axys to Cytovia. (b) Cytovia will initially contribute to the Research, from its libraries of compounds, [ * ] compounds (each, a "Cytovia Compound"), identified by the Parties and set forth on the attached Schedule 2.2(b), which will be the subject of initial research related activities as provided in the Research Plan. If and at such time as a Cytovia Compound fails either the second or third of the Lead Compound tests set forth on Schedule 1.27, Cytovia will contribute an additional Cytovia Compound mutually identified and agreed to by the Parties from Cytovia's libraries of compounds which compound will become the subject of research activities under the Research Plan. Notwithstanding anything to the contrary herein, unless otherwise agreed by the Parties, Cytovia will only be required to contribute a maximum of [ * ] such replacement Cytovia Compounds (for a maximum total of [ * ] Cytovia Compounds contributed altogether). Cytovia will provide Axys with the synthetic route for the Cytovia Compounds and such quantities of such Cytovia Compounds as Axys reasonably requests for [ * ] = CERTAIN CONFIDENTIAL INFORMATION CONTAINED IN THIS DOCUMENT, MARKED BY BRACKETS, HAS BEEN OMITTED AND FILED SEPARATELY WITH THE SECURITIES AND EXCHANGE COMMISSION PURSUANT TO RULE 24b-2 OF THE SECURITIES EXCHANGE ACT OF 1934, AS AMENDED.

Research Contributions. The contributions and novelties of this dissertation have been drawn from and are disseminated through the following technical papers: [C1] X. Xxxxxxxxx, X. X. Xxxxxxx, and X.X.X Xxxx, ”Problem formulation for joint cooperative downlink scheduling and power allocation for joint pro- cessing coordinated multipoint,” in International Conference on Consumer Electronics, IEEE, April 2014, pp. 1-3, [C2] X. Xxxxxxxxx, X. Xxxxxxxxxxx, and X. X. Xxxxxxx, ”Joint inter-cell inter- xxxxxxx coordination and forced cooperative scheduling for the downlink of LTE systems,” in Wireless Communications and Networking Conference, WCNC, IEEE, November 2014, pp. 1880-1884, [J1] X. Xxxxxxxxx, X. Xxxx, and A. Xxxxx Xxxxxxx, ”Joint Adaptive Power Allocation and Resource Management for the Downlink of a Load-Balanced Multi-Carrier LTE HetNet,” submitted to IEEE Transactions on Wireless Communications, August, 2015. [J2] X. Xxxxxxxxx, M. A. Xxxx, X. Xxxxxx, and A. Xxxxx Xxxxxxx, ”Fronthaul- Aware UL-DL Decoupling (FA-DUDe) for CoMP-enabled Heterogeneous Systems,” submitted to Elsevier, International Journal of Computer and Telecommunications Networking, September, 2015.

Research Contributions. ‌ In this dissertation, we address the following research problems: • How to sample high-dimensional and large data from original data while guaranteeing high utility under differential privacy? • How to release series of dynamic datasets in real time under differential privacy? • How to handle personalized differential privacy when record owners have different privacy preferences?

Research Contributions. The article makes the following major contributions: The proposed protocol offers a mechanism for secure mutual authentication utilizing multi-factors, such as a user’s password, real-identity, personal biometrics and mobile de- vice as four factors, to establish the session keys among the communicating parties (here, drones and users). In the proposed scheme, a major advantage is that limited payload and processing power of the deployed drones do not affect the scalability of the proposed scheme irrespective of the number of deployed drones. At the same time, a drone establishes a session key with the ground station (GS) for secret sharing. Here, a user Ui can not only access the real time data from a deployed drone DRj securely, but the GS also aggregates the same data securely with a session key with each other for storing into a blockchain center. A detailed formal security verification using broadly- accepted Scyther automated software validation tool and the informal (non-mathematical) security analysis show the pro- posed scheme’s robustness against various potential attacks needed for air-smart vehicular networks. A real-time testbed experiment for various cryptographic primitives as well as for the proposed authentication protocol is used to show the feasibility, the testbed uses Raspberry Pi 4 (model B) devices with cryptographic standard library (cryptography 37.0.2). Moreover, a blockchain simulation on the real data (image type) is also presented for this protocol which identifies the uniqueness of the scheme. In this article, our primary focus is to tackle the security concerns surrounding the communication channels between drones and users.

Research Contributions. In this dissertation, we propose a novel framework for location-aware task manage- ment to handle uncertainty and ensure privacy in MCS applications while achieving desired task coverage with minimal cost. In Chapter 3 and Chapter 4, we present two spatial task assignment and selection methods to address the location privacy concerns of the participants in our framework. Chapter 5 and 6 extend the task management framework using an adaptive data-driven solution which deals with the continuous change and the uncertainty of dynamic environments in MCS. The rest of this section highlights the details of our contributions.

Research Contributions