A comparison of processing techniques for producing prototype injection moulding inserts.

This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

Over provisioning-centric QoS-routing mechanism for the communication paradigm of future internet 4WARD proposal

The FP7 4WARD clean-slate Project envisions overcoming the limitations of current Internet by redefining it to efficiently support complex value-added sessions and services, such as location-based, health-care, critical-mission, and geo processing. The list of networking innovations from 4WARD’s Future Internet (FI) proposal includes a new connectivity paradigm called Generic Path (GP), a common representation for all communications. From the networking point of view, a GP is mapped to a communication path for data propagation. For that, GP architecture relies on routing mechanism for selecting best communication paths. In order to assure reliable communications, the routing mechanism must efficiently provision QoS-aware multi-party capable paths, with robustness functions, while keeping network performance. Therefore, this paper proposes the QoS-Routing and Resource Control (QoS-RRC) mechanism to deal with the hereinabove requirements by means of an over provisioning-centric (bandwidth and paths) approach. QoS-RRC achieves scalability by avoiding per-flow operations (e.g., signaling, state storage, etc.). Initial QoS-RRC performance evaluation was carried out in Network Simulator v.2 (NS-2), enabling drastic reduction of overall signaling exchanges compared to per-flow solutions

Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks

This paper investigates the use of deep reinforcement learning (DRL) in a MAC protocol for heterogeneous wireless networking referred to as Deep-reinforcement Learning Multiple Access (DLMA). The thrust of this work is partially inspired by the vision of DARPA SC2, a 3-year competition whereby competitors are to come up with a clean-slate design that "best share spectrum with any network(s), in any environment, without prior knowledge, leveraging on machine-learning technique". Specifically, this paper considers the problem of sharing time slots among a multiple of time-slotted networks that adopt different MAC protocols. One of the MAC protocols is DLMA. The other two are TDMA and ALOHA. The nodes operating DLMA do not know that the other two MAC protocols are TDMA and ALOHA. Yet, by a series of observations of the environment, its own actions, and the resulting rewards, a DLMA node can learn an optimal MAC strategy to coexist harmoniously with the TDMA and ALOHA nodes according to a specified objective (e.g., the objective could be the sum throughput of all networks, or a general alpha-fairness objective)