Ammar Huneiti

Semantic data model for product support systems

Organisations need a structured approach for managing the design of their electronic product support systems (PSSs) since, although technology can assist users with faster information retrieval, if the information is incorrect, the technology could actually increase the error rate. We present an approach for the semantic design and analysis of PSSs as part of a systematic methodology for the development of optimal PSSs. A semantic data model for PSSs is proposed based on an information usage analysis. This analysis aims at abstracting the intended purpose for the product information, the supported user tasks, and the functional characteristics of the product information elements. These abstract views are combined together into an activity-based semantic network and set of rules and constraints, which are then mapped into a database schema. This mapping creates a knowledge base that preserves the data semantics, which can then be used by authors in order to implement the PSS. A Web-based technical manual, which is a special type of PSS, is used in order to demonstrate the applicability of the proposed semantic data model.

Product Lifecycle Management for Performance Support

This paper shows how product lifecycle information can be utilized to assist people engaged in product lifecycle tasks, in particular those concerned with product support. A progression of product data management methods based on knowledge engineering techniques is presented to allow the creation and delivery of effective, personalized performance support information. The product data management methods discussed include semantic hypermedia authoring, automated construction of product documentation, automated diagnostic module construction, and adaptive product support generation. These methods are utilized to improve the performance of product lifecycle actors, while reducing the time, knowledge, and input required from them, through increased task support and automation.

Mesenchymal stem cells and conditioned media in the treatment of multiple sclerosis patients: Clinical, ophthalmological and radiological assessments of safety and efficacy

This open‐label prospective phase I/IIa clinical study used autologous bone marrow‐derived mesenchymal stromal cells (BM‐MSCs) followed by mesenchymal stromal cells conditioned media (MSC‐CM) for the first time to treat multiple sclerosis (MS) patients. The primary goal was to assess the safety and feasibility and the secondary was efficacy. The correlation between the MSC‐CM content and treatment outcome was investigated.

Semantic Modeling of Product Manuals

Compared to other product lifecycle phases, the development of product documentation and technical manuals in particular, is an area currently undersupported by tools. This is in contrast with the benefits associated with the production of high quality product documentation, and the effort involved to produce it. This paper addresses this problem by proposing three complementary semantic-based methods for modeling product manuals. The first approach is based on using semantically linked information objects. The second approach focuses on abstracting the intended purpose, user tasks and the functional characteristics of the product data elements. The third approach uses ontologies to capture the semantic complexity of the product support domain.

A New Parallel Matrix Multiplication Algorithm on Tree-Hypercube Network using Iman1 Supercomputer

The tree-hypercube (TH) interconnection network is relatively a new interconnection network, which is constructed from tree and hypercube topologies. TH is developed to support parallel algorithms for solving computation and communication intensive problems. In this paper, we propose a new parallel multiplication algorithm on TH network to present broadcast communication operation for TH using store-and-forward technique, namely, one-to-all broadcast operation which allows a message to be transmitted through the shortest path from the source node to all other nodes. The proposed algorithm is implemented and evaluated in terms of running time, efficiency and speedup with different data size using IMAN1. The experimental results show that the runtime, efficiency and the speedup of the proposed algorithm decrease as a number of processors increases for all cases of matrices size of 1000?1000, 2000?2000, and 4000?4000.