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Copyright of Science: Future of Lithuania / Mokslas: Lietuvos Ateitis is the property of Vilnius Gediminas Technical University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Traditional product modeling methods mainly aim at physical products. However, with cloud manufacturing, the efficient management and utilization of big data under the support of cloud service platform are a challenge, and establishing a reasonable data model is the core of product life cycle data management for generalized products. Aiming at big data management of generalized product modules, the definition, description, and classification of general modules are given in this paper firstly. Then, modular master structure data models are built, including the composition of the generalized modular master structure, property description of generalized part variables, connection objects among the generalized parts, etc. Thirdly, modular instance structure data models of the generalized product are established, the formation process of the instance structure model is analyzed, and the structure mapping views in different phases of the product life cycle are also presented. Finally, based on the secondary development of a product life cycle management (PLM) system, the generalized product data models and the modular structure models of the transformer are carried out. The traditional integrated product models are enriched and improved so the demand of modular data management of generalized products is satisfied under the environment of cloud manufacturing. [ABSTRACT FROM AUTHOR]

Telecommunication services are traditionally described from the terminal viewpoint, including the user interaction with the service, as well as the specific terminal characteristics to the network that it is meant for. Also traditionally the instance of the telecommunication service was a call and a connection as a one-to-one couple. Nowadays networks with powerful multimedia/multiconnection/multiparty capabilities require that a telecommunication service should not be described any more as a conglomerate, but by its main service elements, which in turn are supported by other service elements, so that a service may be built up by building blocks in a levelled model. The criteria to be considered to find these elements are the user viewpoint, the information coding (or terminal) viewpoint and the network access viewpoint. This leads to the telecommunication service, party, party edge, user service module and abstract service module as pure user-dependent service elements, the service module for the terminal aspect, and the access connection element for transfer of the information over the network. All these basic service elements are ordered in a levelled structure called a multilevel framework. Each level or co-level represents a service element type which may be instanciated as a service object, and which is described statically by a table of attributes. Attributes for each level are listed and clarified. An example describing a well-known service is given to illustrate the use of the framework. The views expressed in this document have been developed by the RACE 2044 MAGIC. * The concepts presented are related to Release 2 and 3 for BISDN as defined in ITU-T. [ABSTRACT FROM AUTHOR]

Drone delivery has a great potential to change the traditional parcel delivery service in consideration of cost reduction, resource conservation, and environmental protection. This paper introduces a novel drone fleet deployment and planning problem with uncertain delivery demand, where the delivery routes are fixed and couriers work in collaboration with drones to deliver surplus parcels with a relatively higher labor cost. The problem involves the following two-stage decision process: (i) The first stage determines the drone fleet deployment (i.e., the numbers and types of drones) and the drone delivery service module (i.e., the time segment between two consecutive departures) on a tactical level, and (ii) the second stage decides the numbers of parcels delivered by drones and couriers on an operational level. The purpose is to minimize the total cost, including (i) drone deployment and operating cost and (ii) expected labor cost. For the problem, a two-stage stochastic programming formulation is proposed. A classic sample average approximation method is first applied. To achieve computational efficiency, a hybrid genetic algorithm is further developed. The computational results show the efficiency of the proposed approaches. [ABSTRACT FROM AUTHOR]