961 research outputs found

    Discernment as Practical Wisdom: Toward a Disruptive Practical Theology of Ministry Leadership

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    Leadership is a slippery concept. Those committed to the work of ministry formation in particular, and practical theology in general, struggle with leadership education for at least three reasons. First, leadership is difficult to define. a second slippery feature of leadership: the kind of work leadership is has been overwhelmingly defined and theorized in disciplinary frames that are instrumental in nature—particularly in business, military, and political contexts. Thirdly, context matters

    Ministry Formation in the Places of Wisdom

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    Ministry formation in places of wisdom

    Mentoring for Ministry in Christian Tradition

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    Understanding the role of mentoring for ministry in the Christian tradition. &nbsp

    Performance Analysis of Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach

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    © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cell-free (CF) massive multiple-input-multiple-output (MIMO) has emerged as an alternative deployment for conventional cellular massive MIMO networks. As revealed by its name, this topology considers no cells, while a large number of multi-antenna access points (APs) serves simultaneously a smaller number of users over the same time/frequency resources through time-division duplex (TDD) operation. Prior works relied on the strong assumption (quite idealized) that the APs are uniformly distributed, and actually, this randomness was considered during the simulation and not in the analysis. However, in practice, ongoing and future networks become denser and increasingly irregular. Having this in mind, we consider that the AP locations are modeled by means of a Poisson point process (PPP) which is a more realistic model for the spatial randomness than a grid or uniform deployment. In particular, by virtue of stochastic geometry tools, we derive both the downlink coverage probability and achievable rate. Notably, this is the only work providing the coverage probability and shedding light on this aspect of CF massive MIMO systems. Focusing on the extraction of interesting insights, we consider small-cells (SCs) as a benchmark for comparison. Among the findings, CF massive MIMO systems achieve both higher coverage and rate with comparison to SCs due to the properties of favorable propagation, channel hardening, and interference suppression. Especially, we showed for both architectures that increasing the AP density results in a higher coverage which saturates after a certain value and increasing the number of users decreases the achievable rate but CF massive MIMO systems take advantage of the aforementioned properties, and thus, outperform SCs. In general, the performance gap between CF massive MIMO systems and SCs is enhanced by increasing the AP density. Another interesting observation concerns that a higher path-loss exponent decreases the rate while the users closer to the APs affect more the performance in terms of the rate.Peer reviewe

    Dynamic bandwidth allocation for OFDMA-PONs using Hidden Markov Model

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    Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Abstract: Accurate prediction of traffic conditions on OFDMA-PONs is important because of its vital role in network resource management and efficient bandwidth allocation. Given the dynamic and stochastic nature of network traffic, our proposed algorithm conducts a probabilistic approach by using the Hidden Markov Model (HMM). The HMM defines traffic states with two parameters: the mean and contrast of the bandwidth request observations. Simulation results demonstrate the performance comparison between with and without the prediction method in terms of throughput and end-to-end delay. As a result, the throughput improves 15% and the saturation offered load of the delay for the prediction and non-prediction is 0.8 and 0.7, respectively.Peer reviewedFinal Published versio

    Higher education for a sustainable world

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    Purpose: The paper aims to explore the nature and purpose of higher education (HE) in the twenty-first century, focussing on how it can help fashion a green knowledge-based economy by developing approaches to learning and teaching that are social, networked and ecologically sensitive. Design/methodology/approach: The paper presents a discursive analysis of the skills and knowledge requirements of an emerging green knowledge-based economy using a range of policy focussed and academic research literature. Findings: The business opportunities that are emerging as a more sustainable world is developed requires the knowledge and skills that can capture and move then forward but in a complex and uncertain worlds learning needs to non-linear, creative and emergent. Practical implications: Sustainable learning and the attributes graduates will need to exhibit are prefigured in the activities and learning characterising the work and play facilitated by new media technologies. Social implications: Greater emphasis is required in higher learning understood as the capability to learn, adapt and direct sustainable change requires interprofessional co-operation that must utlise the potential of new media technologies to enhance social learning and collective intelligence. Originality/value: The practical relationship between low-carbon economic development, social sustainability and HE learning is based on both normative criteria and actual and emerging projections in economic, technological and skills needs

    Organised Crime: Combating an Elusive Transnational Threat

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    Since the end of the Cold War; wide spread political, economic, social and technological changes have enabled organised criminal groups to develop transnational activities. Encouraged by the United States, the world has conceived transnational organised crime as a 'new' and serious security threat. The international community has acknowledged the inherent incapability of national strategies, alone, to combat transnational organised crime. Therefore, concerted efforts have been taken to develop a global and uniformed response. Efforts to combat transnational organised crime have been underpinned by a perceived necessity to protect national borders. This reaction is based on traditional, inaccurate, conceptions of organised crime, which focuses on structured, ethnically defined 'outsider' groups as a serious threat to security and the very fabric of society. This concept of organised crime is overly simplistic and fails to grasp the complexity of modern organised crime and its interaction with legal and illegal markets. Organise crime is a multifaceted phenomenon, characterised by loose networks of criminals, who are primarily motivated by profit and operate based on particular 'opportunities'. Strategies to combat organised crime have been preoccupied with traditional, repressive, criminal justice measures; at the expense of developing a comprehensive understanding of the root problems that allow illicit markets and organised crime to flourish, in communities and society in general. It is essential that the international community, through the United Nations, realistically assess the effectiveness of its current approach, to aid the development of comprehensive strategies for the future. New Zealand has taken promising steps to combat transnational organised crime. Although in its infancy, NZ has developed a comprehensive strategy which not only utilises traditional criminal justice tools, but also seeks to engage with communities to develop effective prevention measures

    'Tales Of Nikolai Gogol' Orchestration

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    Orchestration of full score for Music Theatre work 'Tales Of Nikolai Gogol' for premier live performance at the Clarence Street Theatre, Hamilton, Sat Feb 20 2016. The original one act version (2012 - for rhythm section and strings) was expanded to two acts which comprised 41 separate scores. I collaborated with composer David Sidwell on appropriate instrumentation to score his piano and vocal scores and the final versions were orchestrated for Flute, Oboe, Clarinet, Trumpet, F Horn, Trombone, Piano and Keyboard 2, Guitar, Bass, Drums, soloists and and chorus. I proposed the adoption of 2 'alter-ego' voices for the tormented character of artist Piskarev: solo violin depicts his romantic vision of "She" while an angst-ridden heavily distorted guitar depicts his anguish. I was honoured to be asked to compose two pieces for the work: "Ti Sento Qui" for characters Princess Volkonskaya and Nikolai Gogol and "The Secret" sung by Pisarev's love interest "SHE". NB. As the mp3 files are computer generated from Finale music software files the simulated vocal lines do not contain lyrics

    Time-delay neural network for continuous emotional dimension prediction from facial expression sequences

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    "(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."Automatic continuous affective state prediction from naturalistic facial expression is a very challenging research topic but very important in human-computer interaction. One of the main challenges is modeling the dynamics that characterize naturalistic expressions. In this paper, a novel two-stage automatic system is proposed to continuously predict affective dimension values from facial expression videos. In the first stage, traditional regression methods are used to classify each individual video frame, while in the second stage, a Time-Delay Neural Network (TDNN) is proposed to model the temporal relationships between consecutive predictions. The two-stage approach separates the emotional state dynamics modeling from an individual emotional state prediction step based on input features. In doing so, the temporal information used by the TDNN is not biased by the high variability between features of consecutive frames and allows the network to more easily exploit the slow changing dynamics between emotional states. The system was fully tested and evaluated on three different facial expression video datasets. Our experimental results demonstrate that the use of a two-stage approach combined with the TDNN to take into account previously classified frames significantly improves the overall performance of continuous emotional state estimation in naturalistic facial expressions. The proposed approach has won the affect recognition sub-challenge of the third international Audio/Visual Emotion Recognition Challenge (AVEC2013)1

    Asynchronous Distributed Averaging on Communication Networks

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    Distributed algorithms for averaging have attracted interest in the control and sensing literature. However, previous works have not addressed some practical concerns that will arise in actual implementations on packet-switched communication networks such as the Internet. In this paper, we present several implementable algorithms that are robust to asynchronism and dynamic topology changes. The algorithms are completely distributed and do not require any global coordination. In addition, they can be proven to converge under very general asynchronous timing assumptions. Our results are verified by both simulation and experiments on Planetlab, a real-world TCP/IP network. We also present some extensions that are likely to be useful in applications
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