Coherent Diffraction Imaging of Single 95nm Nanowires

Photonic or electronic confinement effects in nanostructures become significant when one of their dimension is in the 5-300 nm range. Improving their development requires the ability to study their structure - shape, strain field, interdiffusion maps - using novel techniques. We have used coherent diffraction imaging to record the 3-dimensionnal scattered intensity of single silicon nanowires with a lateral size smaller than 100 nm. We show that this intensity can be used to recover the hexagonal shape of the nanowire with a 28nm resolution. The article also discusses limits of the method in terms of radiation damage.Comment: 5 pages, 5 figure

Cross-Layer Optimization of Fast Video Delivery in Cache-Enabled Relaying Networks

This paper investigates the cross-layer optimization of fast video delivery and caching for minimization of the overall video delivery time in a two-hop relaying network. The half-duplex relay nodes are equipped with both a cache and a buffer which facilitate joint scheduling of fetching and delivery to exploit the channel diversity for improving the overall delivery performance. The fast delivery control is formulated as a two-stage functional non-convex optimization problem. By exploiting the underlying convex and quasi-convex structures, the problem can be solved exactly and efficiently by the developed algorithm. Simulation results show that significant caching and buffering gains can be achieved with the proposed framework, which translates into a reduction of the overall video delivery time. Besides, a trade-off between caching and buffering gains is unveiled.Comment: 7 pages, 4 figures; accepted for presentation at IEEE Globecom, San Diego, CA, Dec. 201

Organizational Culture, Knowledge Structures, and Relational Messages in Organizational Negotiation: A Systems Approach

This study examines a recent bargaining process between the Faculty Association and Central Michigan University. Taking a systems approach, we began with the assumption that a healthy organizational culture produces negative feedback which can help keep participants at the bargaining table despite disagreement. However, if organizational members’ relationships are threatened, organizational culture unravels as destructive messages provide positive feedback to disrupt the system and make impasse more likely. To understand how an university’s culture is impacted during contract negotiations we examined messages published in a university student newspaper, transcripts from the local NPR station, CMU’s press releases, a Facebook page, and a fact-finding report on the university climate after contract negotiations had been concluded. We found that each side constructed their own identity and that of the other and attributed motives to each side’s bargaining tactics resulting in straining of the relationship between the bargaining parties and a breakdown of faculty-administrative trust throughout the University

Motivational Patterns Of Enrollees In University-Based Executive And Professional Education Courses

The purpose of this paper is to begin an exploration into high-skills lifelong learning in the field of business and management, referred to as executive and professional education (EPE).  Several additional undertakings were necessary, including: discovering methods of valuing knowledge to a region, state or country, and establishing why participants in EPE programs enroll in them. To support this inquiry two research questions were developed, as follows:  1. What are the components of relevant EPE? 2. What motivates participants to take part in EPE? An exploratory case study was written exploring the intricacies of developing a successful EPE department.  This exploratory case study served as a basis for developing a survey, administered to participants in EPE to determine reasons for their participation.  This final survey was conducted in the classroom. The researchers believe that the findings and conclusions will be of value to practitioners involved in EPE, as well as to academics studying this area of business education.  This research exercise has assisted the researchers in being more effective in managing and developing EPE within their own university.  As professions and skills are made obsolete in the knowledge economy the need for continued high level lifelong learning becomes increasing important to the sustainability and viability of local, regional, state and national economies

AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

Cache-Aided Non-Orthogonal Multiple Access

In this paper, we propose a novel joint caching and non-orthogonal multiple access (NOMA) scheme to facilitate advanced downlink transmission for next generation cellular networks. In addition to reaping the conventional advantages of caching and NOMA transmission, the proposed cache-aided NOMA scheme also exploits cached data for interference cancellation which is not possible with separate caching and NOMA transmission designs. Furthermore, as caching can help to reduce the residual interference power, several decoding orders are feasible at the receivers, and these decoding orders can be flexibly selected for performance optimization. We characterize the achievable rate region of cache-aided NOMA and investigate its benefits for minimizing the time required to complete video file delivery. Our simulation results reveal that, compared to several baseline schemes, the proposed cache-aided NOMA scheme significantly expands the achievable rate region for downlink transmission, which translates into substantially reduced file delivery times.Comment: Accepted for presentation at IEEE ICC 201

Rate-Splitting for Intelligent Reflecting Surface-Aided Multiuser VR Streaming

The growing demand for virtual reality (VR) applications requires wireless systems to provide a high transmission rate to support 360-degree video streaming to multiple users simultaneously. In this paper, we propose an intelligent reflecting surface (IRS)-aided rate-splitting (RS) VR streaming system. In the proposed system, RS facilitates the exploitation of the shared interests of the users in VR streaming, and IRS creates additional propagation channels to support the transmission of high-resolution 360-degree videos. IRS also enhances the capability to mitigate the performance bottleneck caused by the requirement that all RS users have to be able to decode the common message. We formulate an optimization problem for maximization of the achievable bitrate of the 360-degree video subject to the quality-of-service (QoS) constraints of the users. We propose a deep deterministic policy gradient with imitation learning (Deep-GRAIL) algorithm, in which we leverage deep reinforcement learning (DRL) and the hidden convexity of the formulated problem to optimize the IRS phase shifts, RS parameters, beamforming vectors, and bitrate selection of the 360-degree video tiles. We also propose RavNet, which is a deep neural network customized for the policy learning in our Deep-GRAIL algorithm. Performance evaluation based on a real-world VR streaming dataset shows that the proposed IRS-aided RS VR streaming system outperforms several baseline schemes in terms of system sum-rate, achievable bitrate of the 360-degree videos, and online execution runtime. Our results also reveal the respective performance gains obtained from RS and IRS for improving the QoS in multiuser VR streaming systems.Comment: 20 pages, 12 figures. This paper has been submitted to IEEE journal for possible publicatio

Sub-Poissonian statistics of Rydberg-interacting dark-state polaritons

Interfacing light and matter at the quantum level is at the heart of modern atomic and optical physics and enables new quantum technologies involving the manipulation of single photons and atoms. A prototypical atom-light interface is electromagnetically induced transparency, in which quantum interference gives rise to hybrid states of photons and atoms called dark-state polaritons. We have observed individual dark-state polaritons as they propagate through an ultracold atomic gas involving Rydberg states. Strong long-range interactions between Rydberg atoms give rise to an effective interaction blockade for dark-state polaritons, which results in large optical nonlinearities and modified polariton number statistics. The observed statistical fluctuations drop well below the quantum noise limit indicating that photon correlations modified by the strong interactions have a significant back-action on the Rydberg atom statistics.Comment: 7 pages, 4 figure