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715 results on '"Jennings, N."'

1. Multi-Issue Negotiation with Deadlines

Author

Fatima, S. S., Jennings, N. R., and Wooldridge, M. J.

Subjects
Computer Science - Multiagent Systems, Computer Science - Artificial Intelligence
Abstract

This paper studies bilateral multi-issue negotiation between self-interested autonomous agents. Now, there are a number of different procedures that can be used for this process; the three main ones being the package deal procedure in which all the issues are bundled and discussed together, the simultaneous procedure in which the issues are discussed simultaneously but independently of each other, and the sequential procedure in which the issues are discussed one after another. Since each of them yields a different outcome, a key problem is to decide which one to use in which circumstances. Specifically, we consider this question for a model in which the agents have time constraints (in the form of both deadlines and discount factors) and information uncertainty (in that the agents do not know the opponents utility function). For this model, we consider issues that are both independent and those that are interdependent and determine equilibria for each case for each procedure. In so doing, we show that the package deal is in fact the optimal procedure for each party. We then go on to show that, although the package deal may be computationally more complex than the other two procedures, it generates Pareto optimal outcomes (unlike the other two), it has similar earliest and latest possible times of agreement to the simultaneous procedure (which is better than the sequential procedure), and that it (like the other two procedures) generates a unique outcome only under certain conditions (which we define).

Published
2011
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2. Cooperative Information Sharing to Improve Distributed Learning in Multi-Agent Systems

Author

Dutta, P. S., Jennings, N. R., and Moreau, L.

Subjects
Computer Science - Multiagent Systems
Abstract

Effective coordination of agents actions in partially-observable domains is a major challenge of multi-agent systems research. To address this, many researchers have developed techniques that allow the agents to make decisions based on estimates of the states and actions of other agents that are typically learnt using some form of machine learning algorithm. Nevertheless, many of these approaches fail to provide an actual means by which the necessary information is made available so that the estimates can be learnt. To this end, we argue that cooperative communication of state information between agents is one such mechanism. However, in a dynamically changing environment, the accuracy and timeliness of this communicated information determine the fidelity of the learned estimates and the usefulness of the actions taken based on these. Given this, we propose a novel information-sharing protocol, post-task-completion sharing, for the distribution of state information. We then show, through a formal analysis, the improvement in the quality of estimates produced using our strategy over the widely used protocol of sharing information between nearest neighbours. Moreover, communication heuristics designed around our information-sharing principle are subjected to empirical evaluation along with other benchmark strategies (including Littmans Q-routing and Stones TPOT-RL) in a simulated call-routing application. These studies, conducted across a range of environmental settings, show that, compared to the different benchmarks used, our strategy generates an improvement of up to 60% in the call connection rate; of more than 1000% in the ability to connect long-distance calls; and incurs as low as 0.25 of the message overhead.

Published
2011
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5. TranAD

Author

Tuli, S, Casale, G, and Jennings, N

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, 0806 Information Systems, General Engineering, 0807 Library and Information Studies, 0802 Computation Theory and Mathematics, Machine Learning (cs.LG)
Abstract

Efficient anomaly detection and diagnosis in multivariate time-series data is of great importance for modern industrial applications. However, building a system that is able to quickly and accurately pinpoint anomalous observations is a challenging problem. This is due to the lack of anomaly labels, high data volatility and the demands of ultra-low inference times in modern applications. Despite the recent developments of deep learning approaches for anomaly detection, only a few of them can address all of these challenges. In this paper, we propose TranAD, a deep transformer network based anomaly detection and diagnosis model which uses attention-based sequence encoders to swiftly perform inference with the knowledge of the broader temporal trends in the data. TranAD uses focus score-based self-conditioning to enable robust multi-modal feature extraction and adversarial training to gain stability. Additionally, model-agnostic meta learning (MAML) allows us to train the model using limited data. Extensive empirical studies on six publicly available datasets demonstrate that TranAD can outperform state-of-the-art baseline methods in detection and diagnosis performance with data and time-efficient training. Specifically, TranAD increases F1 scores by up to 17%, reducing training times by up to 99% compared to the baselines., Comment: Accepted in VLDB 2022

Published
2022
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6. Grantham Institute Outlook 2022-2023

Author

Halkyard, S, Levey, S, Amer, H, Bushby, L, Evanson, D, Fredenburgh, J, Gilbert, A, Jennings, N, Houston, A, Johns, S, Kincaid, C, Kuchapski, N, Petersen, K, Wilson, J, and Wynton, L

Subjects
climate change, training, sustainability, environment, innovation
Abstract

The Grantham Institute Outlook magazine provides an overview of the climate and environmental research underway at Imperial College London, encompassing both recent achievements and future plans.

Published
2023
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7. Decarbonisation of buildings: Insights from across Europe

Author

Baker, W, Acha, S, Jennings, N, Markides, C, and Shah, N

Subjects
climate change, decarbonisation, buildings, environment
Abstract

This report considers four key challenges facing the UK in reducing carbon emissions from its building stock, and shares insights from across Europe that have the potential to help the UK to decarbonise and increase the energy efficiency of its buildings.

Published
2022

10. Trading Strategies for Markets: A Design Framework and Its Application

Author

Vytelingum, P., Dash, R. K., He, M., Sykulski, A., Jennings, N. R., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Dough, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, La Poutré, Han, editor, Sadeh, Norman M., editor, and Janson, Sverker, editor

Published
2006
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11. Learning Environmental Parameters for the Design of Optimal English Auctions with Discrete Bid Levels

Author

Rogers, A., David, E., Schiff, J., Kraus, S., Jennings, N. R., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Dough, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, La Poutré, Han, editor, Sadeh, Norman M., editor, and Janson, Sverker, editor

Published
2006
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14. Grantham Institute Outlook 2021-2022

Author

Levey, S, Gilbert, A, Amer, H, Wynton, L, Jennings, N, and Petersen, K

Subjects
climate change, environment
Abstract

The Grantham Institute's annual Outlook magazine provides an overview of the climate and environmental research and activities underway at Imperial College London, encompassing both recent achievements and future plans.

Published
2022

17. Co-ordination in multi-agent systems

Author

Nwana, H. S., Lee, L., Jennings, N. R., Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Goos, G., editor, Hartmanis, J., editor, van Leeuwen, J., editor, Nwana, Hyacinth S., editor, and Azarmi, Nader, editor

Published
1997
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18. Research Directions for Service-Oriented Multiagent Systems

Author

Huhns, N., Singh, M., Burstein, M., Decker, K., Durfee, E., Finin, T., Gasser, L., Goradia, H., Jennings, N., Lakkaraju, K., Nakashima, Hideyuki, Parunak, V., Rosenschein, J., Ruvinsky, A., Sukthankar, G., Swarup, S., Sycara, K., Tambe, M., Wagner, T., Zavala, L., Huhns, N., Singh, M., Burstein, M., Decker, K., Durfee, E., Finin, T., Gasser, L., Goradia, H., Jennings, N., Lakkaraju, K., Nakashima, Hideyuki, Parunak, V., Rosenschein, J., Ruvinsky, A., Sukthankar, G., Swarup, S., Sycara, K., Tambe, M., Wagner, T., and Zavala, L.

Published
2022

20. Cost‐effectiveness of emergency versus delayed laparoscopic cholecystectomy for acute gallbladder pathology

Author

Sutton, A. J., Vohra, R. S., Hollyman, M., Marriott, P. J., Buja, A., Alderson, D., Pasquali, S., Griffiths, E. A., Vohra, R. S., Spreadborough, P., Hollyman, M., Marriott, P. J., Kirkham, A., Pasquali, S., Alderson, D., Griffiths, E. A., Fenwick, S., Elmasry, M., Nunes, Q. M., Kennedy, D., Khan, R. B., Khan, M. A. S., Magee, C. J., Jones, S. M., Mason, D., Parappally, C. P., Mathur, P., Saunders, M., Jamel, S., Ul Haque, S., Zafar, S., Shiwani, M. H., Samuel, N., Dar, F., Jackson, A., Lovett, B., Dindyal, S., Winter, H., Fletcher, T., Rahman, S., Wheatley, K., Nieto, T., Ayaani, S., Youssef, H., Nijjar, R. S., Watkin, H., Naumann, D., Emesih, S., Sarmah, P. B., Lee, K., Joji, N., Heath, J., Teasdale, R. L., Weerasinghe, C., Needham, P. J., Welbourn, H., Forster, L., Finch, D., Blazeby, J. M., Robb, W., McNair, A. G. K., Hrycaiczuk, A., Charalabopoulos, A., Kadirkamanathan, S., Tang, C.‐B., Jayanthi, N. V. G., Noor, N., Dobbins, B., Cockbain, A. J., Nilsen‐Nunn, A., de Siqueira, J., Pellen, M., Cowley, J. B., Ho, W.‐M., Miu, V., White, T. J., Hodgkins, K. A., Kinghorn, A., Tutton, M. G., Al‐Abed, Y. A., Menzies, D., Ahmad, A., Reed, J., Khan, S., Monk, D., Vitone, L. J., Murtaza, G., Joel, A., Brennan, S., Shier, D., Zhang, C., Yoganathan, T., Robinson, S. J., McCallum, I. J. D., Jones, M. J., Elsayed, M., Tuck, E., Wayman, J., Carney, K., Aroori, S., Hosie, K. B., Kimble, A., Bunting, D.M., Fawole, A. S., Basheer, M., Dave, R. V., Sarveswaran, J., Jones, E., Kendal, C., Tilston, M. P., Gough, M., Wallace, T., Singh, S., Downing, J., Mockford, K. A., Issa, E., Shah, N., Chauhan, N., Wilson, T. R., Forouzanfar, A., Wild, J. R. L., Nofal, E., Bunnell, C., Madbak, K., Rao, S. T. V., Devoto, L., Siddiqi, N., Khawaja, Z., Hewes, J. C., Gould, L., Chambers, A., Rodriguez, D. U., Sen, G., Robinson, S., Carney, K., Bartlett, F., Rae, D. M., Stevenson, T. E. J., Sarvananthan, K., Dwerryhouse, S. J., Higgs, S. M., Old, O. J., Hardy, T. J., Shah, R., Hornby, S. T., Keogh, K., Frank, L., Al‐Akash, M., Upchurch, E. A., Frame, R. J., Hughes, M., Jelley, C., Weaver, S., Roy, S., Sillo, T. O., Galanopoulos, G., Cuming, T., Cunha, P., Tayeh, S., Kaptanis, S., Heshaishi, M., Eisawi, A., Abayomi, M., Ngu, W. S., Fleming, K., Bajwa, D. S., Chitre, V., Aryal, K., Ferris, P., Silva, M., Lammy, S., Mohamed, S., Khawaja, A., Hussain, A., Ghazanfar, M. A., Bellini, M. I., Ebdewi, H., Elshaer, M., Gravante, G., Drake, B., Ogedegbe, A., Mukherjee, D., Arhi, C., Iqbal, L. G. N., Watson, N. F., Aggarwal, S. K., Orchard, P., Villatoro, E., Willson, P. D., Mok, J., Woodman, T., Deguara, J., Garcea, G., Babu, B. I., Dennison, A. R., Malde, D., Lloyd, D., Satheesan, S., Al‐Taan, O., Boddy, A., Slavin, J. P., Jones, R. P., Ballance, L., Gerakopoulos, S., Jambulingam, P., Mansour, S., Sakai, N., Acharya, V., Sadat, M. M., Karim, L., Larkin, D., Amin, K., Khan, A., Law, J., Jamdar, S., Smith, S. R., Sampat, K., Oʼshea, K. M., Manu, M., Asprou, F. M., Malik, N. S., Chang, J., Johnstone, M., Lewis, M., Roberts, G. P., Karavadra, B., Photi, E., Hewes, J., Gould, L., Chambers, A., Rodriguez, D., OʼReilly, D. A., Rate, A. J., Sekhar, H., Henderson, L. T., Starmer, B. Z., Coe, P. O., Tolofari, S., Barrie, J., Bashir, G., Sloane, J., Madanipour, S., Halkias, C., Trevatt, A. E. J., Borowski, D. W., Hornsby, J., Courtney, M. J., Virupaksha, S., Seymour, K., Robinson, S., Hawkins, H., Bawa, S., Gallagher, P. V., Reid, A., Wood, P., Finch, J. G., Parmar, J., Stirland, E., Gardner‐Thorpe, J., Al‐Muhktar, A., Peterson, M., Majeed, A., Bajwa, F. M., Martin, J., Choy, A., Tsang, A., Pore, N., Andrew, D. R., Al‐Khyatt, W., Taylor, C., Bhandari, S., Chambers, A., Subramanium, D., Toh, S. K. C., Carter, N. C., Tate, S., Pearce, B., Wainwright, D., Mercer, S. J., Knight, B., Vijay, V., Alagaratnam, S., Sinha, S., Khan, S., El‐Hasani, S. S., Hussain, A. A., Bhattacharya, V., Kansal, N., Fasih, T., Jackson, C., Siddiqui, M. N., Chishti, I. A., Fordham, I. J., Siddiqui, Z., Bausbacher, H., Geogloma, I., Gurung, K., Tsavellas, G., Basynat, P., Shrestha, A. K., Basu, S., Mohan, A. C., Harilingam, M., Rabie, M., Akhtar, M., Kumar, P., Jafferbhoy, S. F., Hussain, N., Raza, S., Haque, M., Alam, I., Aseem, R., Patel, S., Asad, M., Booth, M. I., Ball, W. R., Wood, C. P. J., Pinho‐Gomes, A. C., Kausar, A., Obeidallah, M. R., Varghase, J., Lodhia, J., Bradley, D., Rengifo, C., Lindsay, D., Gopalswamy, S., Finlay, I., Wardle, S., Bullen, N., Iftikhar, S. Y., Awan, A., Ahmed, J., Leeder, P., Fusai, G., Bond‐Smith, G., Psica, A., Puri, Y., Hou, D., Noble, F., Szentpali, K., Broadhurst, J., Date, R., Hossack, M. R., Goh, Y. L., Turner, P., Shetty, V., Riera, M., Macano, C. A.W., Sukha, A., Preston, S. R., Hoban, J. R., Puntis, D. J., Williams, S. V., Krysztopik, R., Kynaston, J., Batt, J., Doe, M., Goscimski, A., Jones, G. H., Smith, S. R., Hall, C., Carty, N., Ahmed, J., Panteleimonitis, S., Gunasekera, R. T., Sheel, A. R. G., Lennon, H., Hindley, C., Reddy, M., Kenny, R., Elkheir, N., McGlone, E. R., Rajaganeshan, R., Hancorn, K., Hargreaves, A., Prasad, R., Longbotham, D. A., Vijayanand, D., Wijetunga, I., Ziprin, P., Nicolay, C. R., Yeldham, G., Read, E., Gossage, J. A., Rolph, R. C., Ebied, H., Phull, M., Khan, M. A., Popplewell, M., Kyriakidis, D., Hussain, A., Henley, N., Packer, J. R., Derbyshire, L., Porter, J., Appleton, S., Farouk, M., Basra, M., Jennings, N. A., Ali, S., Kanakala, V., Ali, H., Lane, R., Dickson‐Lowe, R., Zarsadias, P., Mirza, D., Puig, S., Al Amari, K., Vijayan, D., Sutcliffe, R., Marudanayagam, R., Hamady, Z., Prasad, A. R., Patel, A., Durkin, D., Kaur, P., Bowen, L., Byrne, J. P., Pearson, K. L., Delisle, T. G., Davies, J., Tomlinson, M. A., Johnpulle, M. A., Slawinski, C., Macdonald, A., Nicholson, J., Newton, K., Mbuvi, J., Farooq, A., Mothe, B. S., Zafrani, Z., Brett, D., Francombe, J., Spreadborough, P., Barnes, J., Cheung, M., Al‐Bahrani, A. Z., Preziosi, G., Urbonas, T., Alberts, J., Mallik, M., Patel, K., Segaran, A., Doulias, T., Sufi, P. A., Yao, C., Pollock, S., Manzelli, A., Wajed, S., Kourkulos, M., Pezzuto, R., Wadley, M., Hamilton, E., Jaunoo, S., Padwick, R., Sayegh, M., Newton, R. C., Hebbar, M., Farag, S. F., Spearman, J., Hamdan, M. F., DʼCosta, C., Blane, C., Giles, M., Peter, M. B., Hirst, N. A., Hossain, T., Pannu, A., El‐Dhuwaib, Y., Morrison, T. E. M., Taylor, G. W., Thompson, R. L. E., McCune, K., Loughlin, P., Lawther, R., Byrnes, C. K., Simpson, D. J., Mawhinney, A., Warren, C., McKay, D., McIlmunn, C., Martin, S., MacArtney, M., Diamond, T., Davey, P., Jones, C., Clements, J.M., Digney, R., Chan, W. M., McCain, S., Gull, S., Janeczko, A., Dorrian, E., Harris, A., Dawson, S., Johnston, D., McAree, B., Ghareeb, E., Thomas, G., Connelly, M., McKenzie, S., Cieplucha, K., Spence, G., Campbell, W., Hooks, G., Bradley, N., Hill, A. D. K., Cassidy, J. T., Boland, M., Burke, P., Nally, D. M., Hill, A. D. K., Khogali, E., Shabo, W., Iskandar, E., McEntee, G. P., OʼNeill, M. A., Peirce, C., Lyons, E. M., OʼSullivan, A. W., Thakkar, R., Carroll, P., Ivanovski, I., Balfe, P., Lee, M., Winter, D. C., Kelly, M. E., Hoti, E., Maguire, D., Karunakaran, P., Geoghegan, J. G., McDermott, F., Martin, S. T., Cross, K. S., Cooke, F., Zeeshan, S., Murphy, J. O., Mealy, K., Mohan, H. M., Nedujchelyn, Y., Ullah, M. F., Ahmed, I., Giovinazzo, F., Milburn, J., Prince, S., Brooke, E., Buchan, J., Khalil, A. M., Vaughan, E. M., Ramage, M. I., Aldridge, R. C., Gibson, S., Nicholson, G. A., Vass, D. G., Grant, A. J., Holroyd, D. J., Jones, M. A., Sutton, C. M. L. R., OʼDwyer, P., Nilsson, F., Weber, B., Williamson, T. K., Lalla, K., Bryant, A., Carter, C. R., Forrest, C. R., Hunter, D. I., Nassar, A. H., Orizu, M. N., Knight, K., Qandeel, H., Suttie, S., Belding, R., McClarey, A., Boyd, A. T., Guthrie, G. J. K., Lim, P. J., Luhmann, A., Watson, A. J. M., Richards, C. H., Nicol, L., Madurska, M., Harrison, E., Boyce, K. M., Roebuck, A., Ferguson, G., Pati, P., Wilson, M. S. J., Dalgaty, F., Fothergill, L., Driscoll, P. J., Mozolowski, K. L., Banwell, V., Bennett, S. P., Rogers, P. N., Skelly, B. L., Rutherford, C. L., Mirza, A. K., Lazim, T., Lim, H. C. C., Duke, D., Ahmed, T., Beasley, W. D., Wilkinson, M. D., Maharaj, G., Malcolm, C., Brown, T. H., Shingler, G. M., Mowbray, N., Radwan, R., Morcous, P., Wood, S., Kadhim, A., Stewart, D. J., Baker, A. L., Tanner, N., Shenoy, H., Hafiz, S., De Marchi, J. A., Singh‐Ranger, D., Hisham, E., Ainley, P., OʼNeill, S., Terrace, J., Napetti, S., Hopwood, B., Rhys, T., Downing, J., Kanavati, O., Coats, M., Aleksandrov, D., Kallaway, C., Yahya, S., Weber, B., Templeton, A., Trotter, M., Lo, C., Dhillon, A., Heywood, N., Aawsaj, Y., Hamdan, A., Reece‐Bolton, O., McGuigan, A., Shahin, Y., Ali, A., Luther, A., Nicholson, J. A., Rajendran, I., Boal, M., and Ritchie, J.

Published
2017
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24. Net-zero solutions and research priorities in the 2020s

Author

Ainalis, D, Bardhan, R, Bell, K, Cebon, D, Czerniak, M, Doyne Farmer, J, Fitzgerland, S, Galkowski, K, Grimshaw, S, Harper, G, Hunt, H, Jennings, N, Keshav, S, Mackie, E, Maroto-Valer, M, Michalopoulou, E, Reay, D, Seddon, N, Smith, SM, Smith, T, Simpson, K, Stranks, SD, Tennyson, EM, Uekert, T, Vera-Morales, M, and Woodcock, J

Abstract

Key messages • Technological, societal and nature-based solutions should work together to enable systemic change towards a regenerative society, and to deliver net-zero greenhouse gas (GHG) emissions. • Prioritise research into efficient, low-carbon and carbon-negative solutions for sectors that are difficult to decarbonise; i.e. energy storage, road transport, shipping, aviation and grid infrastructure. • Each solution should be assessed with respect to GHG emissions reductions, energy efficiency and societal implications to provide a basis for developing long-term policies, maximising positive impact of investment and research effort, and guiding industry investors in safe and responsible planning.

Published
2021

25. Predicting the difficult laparoscopic cholecystectomy: development and validation of a pre-operative risk score using an objective operative difficulty grading system

Author

Nassar, A. H. M., Hodson, J., H. J., Ng, Vohra, R. S., Katbeh, T., Zino, S., Griffiths, E. A., Kirkham, A. J., Pasquali, S., Marriott, P., Johnstone, M., Spreadborough, P., Alderson, D., Fenwick, S., Elmasry, M., Nunes, Q. M., Kennedy, D., Khan, R. B., Khan, M. A. S., Magee, C. J., Jones, S. M., Mason, D., Parappally, C. P., Mathur, P., Saunders, M., Jamel, S., Haque, S. U., Zafar, S., Shiwani, M. H., Samuel, N., Dar, F., Jackson, A., Lovett, B., Dindyal, S., Winter, H., Fletcher, T., Rahman, S., Wheatley, K., Nieto, T., Ayaani, S., Youssef, H., Nijjar, R. S., Watkin, H., Naumann, D., Emesih, S., Sarmah, P. B., Lee, K., Joji, N., Lambert, J., Heath, J., Teasdale, R. L., Weerasinghe, C., Needham, P. J., Welbourn, H., Forster, L., Finch, D., Blazeby, J. M., Robb, W., Mcnair, A. G. K., Hrycaiczuk, A., Charalabopoulos, A., Kadirkamanathan, S., Tang, C. -B., Jayanthi, N. V. G., Noor, N., Dobbins, B., Cockbain, A. J., Nilsen-Nunn, A., de Siqueira, J., Pellen, M., Cowley, J. B., W. -M., Ho, Miu, V., White, T. J., Hodgkins, K. A., Kinghorn, A., Tutton, M. G., Al-Abed, Y. A., Menzies, D., Ahmad, A., Reed, J., Khan, S., Monk, D., Vitone, L. J., Murtaza, G., Joel, A., Brennan, S., Shier, D., Zhang, C., Yoganathan, T., Robinson, S. J., Mccallum, I. J. D., Jones, M. J., Elsayed, M., Tuck, L., Wayman, J., Carney, K., Aroori, S., Hosie, K. B., Kimble, A., Bunting, D. M., Fawole, A. S., Basheer, M., Dave, R. V., Sarveswaran, J., Jones, E., Kendal, C., Tilston, M. P., Gough, M., Wallace, T., Singh, S., Mockford, J. D. K. A., Issa, E., Shah, N., Chauhan, N., Wilson, T. R., Forouzanfar, A., Wild, J. R. L., Nofal, E., Bunnell, C., Madbak, K., Rao, S. T. V., Devoto, L., Siddiqi, N., Khawaja, Z., Hewes, J. C., Gould, L., Chambers, A., Rodriguez, D. U., Sen, G., Robinson, S., Bartlett, F., Rae, D. M., Stevenson, T. E. J., Sarvananthan, K., Dwerryhouse, S. J., Higgs, S. M., Old, O. J., Hardy, T. J., Shah, R., Hornby, S. T., Keogh, K., Frank, L., Al-Akash, M., Upchurch, E. A., Frame, R. J., Hughes, M., Jelley, C., Weaver, S., Roy, S., Sillo, T. O., Galanopoulos, G., Cuming, T., Cunha, P., Tayeh, S., Kaptanis, S., Heshaishi, M., Eisawi, A., Abayomi, M., Ngu, W. S., Fleming, K., Bajwa, D. S., Chitre, V., Aryal, K., Ferris, P., Silva, M., Lammy, S., Mohamed, S., Khawaja, A., Hussain, A., Ghazanfar, M. A., Bellini, M. I., Ebdewi, H., Elshaer, M., Gravante, G., Drake, B., Ogedegbe, A., Mukherjee, D., Arhi, C., Giwa, L., Iqbal, N., Watson, N. F., Aggarwal, S. K., Orchard, P., Villatoro, E., Willson, P. D., Mok, K. W. J., Woodman, T., Deguara, J., Garcea, G., Babu, B. I., Dennison, A. R., Malde, D., Lloyd, D., Satheesan, S., Al-Taan, O., Boddy, A., Slavin, J. P., Jones, R. P., Ballance, L., Gerakopoulos, S., Jambulingam, P., Mansour, S., Sakai, N., Acharya, V., Sadat, M. M., Karim, L., Larkin, D., Amin, K., Khan, A., Law, J., Jamdar, S., Smith, S. R., Sampat, K., O'Shea, K. M., Manu, M., Asprou, F. M., Malik, N. S., Chang, J., Lewis, M., Roberts, G. P., Karavadra, B., Photi, E., Hewes, J., Rodriguez, D., O'Reilly, D. A., Rate, A. J., Sekhar, H., Henderson, L. T., Starmer, B. Z., Coe, P. O., Tolofari, S., Barrie, J., Bashir, G., Sloane, J., Madanipour, S., Halkias, C., Trevatt, A. E. J., Borowski, D. W., Hornsby, J., Courtney, M. J., Virupaksha, S., Seymour, K., Hawkins, H., Bawa, S., Gallagher, P. V., Reid, A., Wood, P., Finch, J. G., Guy Finch, J., Parmar, J., Stirland, E., Gardner-Thorpe, J., Al-Muhktar, A., Peterson, M., Majeed, A., Bajwa, F. M., Martin, J., Choy, A., Tsang, A., Pore, N., Andrew, D. R., Al-Khyatt, W., Taylor, C., Bhandari, S., Subramanium, D., Toh, S. K. C., Carter, N. C., Tate, S., Pearce, B., Wainwright, D., Mercer, S. J., Knight, B., Vijay, V., Alagaratnam, S., Sinha, S., El-Hasani, S. S., Hussain, A. A., Bhattacharya, V., Kansal, N., Fasih, T., Jackson, C., Siddiqui, M. N., Chishti, I. A., Fordham, I. J., Siddiqui, Z., Bausbacher, H., Geogloma, I., Gurung, K., Tsavellas, G., Basynat, P., Shrestha, A. K., Basu, S., Chhabra, A., Harilingam, M., Rabie, M., Akhtar, M., Kumar, P., Jafferbhoy, S. F., Hussain, N., Raza, S., Haque, M., Alam, I., Aseem, R., Patel, S., Asad, M., Booth, M. I., Ball, W. R., Wood, C. P. J., Pinho-Gomes, A. C., Kausar, A., Obeidallah, M. R., Varghase, J., Lodhia, J., Bradley, D., Rengifo, C., Lindsay, D., Gopalswamy, S., Finlay, I., Wardle, S., Bullen, N., Iftikhar, S. Y., Awan, A., Ahmed, J., Leeder, P., Fusai, G., Bond-Smith, G., Psica, A., Puri, Y., Hou, D., Noble, F., Szentpali, K., Broadhurst, J., Date, R., Hossack, M. R., Goh, Y. L., Turner, P., Shetty, V., Riera, M., Macano, C. A. W., Sukha, A., Preston, S. R., Hoban, J. R., Puntis, D. J., Williams, S. V., Krysztopik, R., Kynaston, J., Batt, J., Doe, M., Goscimski, A., Jones, G. H., Hall, C., Carty, N., Panteleimonitis, S., Gunasekera, R. T., Sheel, A. R. G., Lennon, H., Hindley, C., Reddy, M., Kenny, R., Elkheir, N., Mcglone, E. R., Rajaganeshan, R., Hancorn, K., Hargreaves, A., Prasad, R., Longbotham, D. A., Vijayanand, D., Wijetunga, I., Ziprin, P., Nicolay, C. R., Yeldham, G., Read, E., Gossage, J. A., Rolph, R. C., Ebied, H., Phull, M., Khan, M. A., Popplewell, M., Kyriakidis, D., Henley, N., Packer, J. R., Derbyshire, L., Porter, J., Appleton, S., Farouk, M., Basra, M., Jennings, N. A., Ali, S., Kanakala, V., Ali, H., Lane, R., Dickson-Lowe, R., Zarsadias, P., Mirza, D., Puig, S., Al Amari, K., Vijayan, D., Sutcliffe, R., Marudanayagam, R., Hamady, Z., Prasad, A. R., Patel, A., Durkin, D., Kaur, P., Bowen, L., Byrne, J. P., Pearson, K. L., Delisle, T. G., Davies, J., Tomlinson, M. A., Johnpulle, M. A., Slawinski, C., Macdonald, A., Nicholson, J., Newton, K., Mbuvi, J., Farooq, A., Mothe, B. S., Zafrani, Z., Brett, D., Francombe, J., Barnes, J., Cheung, M., Al-Bahrani, A. Z., Preziosi, G., Urbonas, T., Alberts, J., Mallik, M., Patel, K., Segaran, A., Doulias, T., Sufi, P. A., Yao, C., Pollock, S., Manzelli, A., Wajed, S., Kourkulos, M., Pezzuto, R., Wadley, M., Hamilton, E., Jaunoo, S., Padwick, R., Sayegh, M., Newton, R. C., Hebbar, M., Farag, S. F., Spearman, J., Hamdan, M. F., D'Costa, C., Blane, C., Giles, M., Peter, M. B., Hirst, N. A., Hossain, T., Pannu, A., El-Dhuwaib, Y., Morrison, T. E. M., Taylor, G. W., Thompson, R. L. E., Mccune, K., Loughlin, P., Lawther, R., Byrnes, C. K., Simpson, D. J., Mawhinney, A., Warren, C., Mckay, D., Mcilmunn, C., Martin, S., Macartney, M., Diamond, T., Davey, P., Jones, C., Clements, J. M., Digney, R., Chan, W. M., Mccain, S., Gull, S., Janeczko, A., Dorrian, E., Harris, A., Dawson, S., Johnston, D., Mcaree, B., Ghareeb, E., Thomas, G., Connelly, M., Mckenzie, S., Cieplucha, K., Spence, G., Campbell, W., Hooks, G., Bradley, N., Hill, A. D. K., Cassidy, J. T., Boland, M., Burke, P., Nally, D. M., Khogali, E., Shabo, W., Iskandar, E., Mcentee, G. P., O'Neill, M. A., Peirce, C., Lyons, E. M., O'Sullivan, A. W., Thakkar, R., Carroll, P., Ivanovski, I., Balfe, P., Lee, M., Winter, D. C., Kelly, M. E., Hoti, E., Maguire, D., Karunakaran, P., Geoghegan, J. G., Mcdermott, F., Martin, S. T., Cross, K. S., Cooke, F., Zeeshan, S., Murphy, J. O., Mealy, K., Mohan, H. M., Nedujchelyn, Y., Ullah, M. F., Ahmed, I., Giovinazzo, F., Milburn, J., Prince, S., Brooke, E., Buchan, J., Khalil, A. M., Vaughan, E. M., Ramage, M. I., Aldridge, R. C., Gibson, S., Nicholson, G. A., Vass, D. G., Grant, A. J., Holroyd, D. J., Jones, M. A., Sutton, C. M. L. R., O'Dwyer, P., Nilsson, F., Weber, B., Williamson, T. K., Lalla, K., Bryant, A., Carter, C. R., Forrest, C. R., Hunter, D. I., Nassar, A. H., Orizu, M. N., Knight, K., Qandeel, H., Suttie, S., Belding, R., Mcclarey, A., Boyd, A. T., Guthrie, G. J. K., Lim, P. J., Luhmann, A., Watson, A. J. M., Richards, C. H., Nicol, L., Madurska, M., Harrison, E., Boyce, K. M., Roebuck, A., Ferguson, G., Pati, P., Wilson, M. S. J., Dalgaty, F., Fothergill, L., Driscoll, P. J., Mozolowski, K. L., Banwell, V., Bennett, S. P., Rogers, P. N., Skelly, B. L., Rutherford, C. L., Mirza, A. K., Lazim, T., Lim, H. C. C., Duke, D., Ahmed, T., Beasley, W. D., Wilkinson, M. D., Maharaj, G., Malcolm, C., Brown, T. H., Al-Sarireh, B., Shingler, G. M., Mowbray, N., Radwan, R., Morcous, P., Wood, S., Kadhim, A., Stewart, D. J., Baker, A. L., Tanner, N., Shenoy, H., Hafiz, S., De Marchi, J. A., Singh-Ranger, D., Hisham, E., Ainley, P., O'Neill, S., Terrace, J., Napetti, S., Hopwood, B., Rhys, T., Downing, J., Kanavati, O., Coats, M., Aleksandrov, D., Kallaway, C., Yahya, S., Templeton, A., Trotter, M., Lo, C., Dhillon, A., Heywood, N., Aawsaj, Y., Hamdan, A., Reece-Bolton, O., Mcguigan, A., Shahin, Y., Aymon, Luther, A. A., Nicholson, J. A., Rajendran, I., Boal, M., and Ritchie, J.

Subjects
Adult, Male, operative difficulty, medicine.medical_specialty, medicine.medical_treatment, Difficulty grading, difficult cholecystectomy, predictive score, surgery, laparoscopic, cholecystectomy, Surgical planning, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Preoperative Care, Humans, Medicine, Laparoscopic cholecystectomy, Framingham Risk Score, business.industry, General surgery, Reproducibility of Results, Middle Aged, medicine.disease, Pre operative, Single surgeon, Cholecystectomy, Laparoscopic, ROC Curve, 030220 oncology & carcinogenesis, Multivariate Analysis, Cholecystitis, Female, 030211 gastroenterology & hepatology, Surgery, Cholecystectomy, business, Abdominal surgery
Abstract

The prediction of a difficult cholecystectomy has traditionally been based on certain pre-operative clinical and imaging factors. Most of the previous literature reported small patient cohorts and have not used an objective measure of operative difficulty. The aim of this study was to develop a pre-operative score to predict difficult cholecystectomy, as defined by a validated intra-operative difficulty grading scale. Two cohorts from prospectively maintained databases of patients who underwent laparoscopic cholecystectomy were analysed: the CholeS Study (8755 patients) and a single surgeon series (4089 patients). Factors potentially predictive of difficulty were correlated to the Nassar intra-operative difficulty scale. A multivariable binary logistic regression analysis was then used to identify factors that were independently associated with difficult laparoscopic cholecystectomy, defined as operative difficulty grades 3 to 5. The resulting model was then converted to a risk score, and validated on both internal and external datasets. Increasing age and ASA classification, male gender, diagnosis of CBD stone or cholecystitis, thick-walled gallbladders, CBD dilation, use of pre-operative ERCP and non-elective operations were found to be significant independent predictors of difficult cases. A risk score based on these factors returned an area under the ROC curve of 0.789 (95% CI 0.773–0.806, p

Published
2019
Full Text
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28. BETH dataset: real cybersecurity data for anomaly detection research

Author

Highnam, K, Arulkumaran, K, Hanif, Z, and Jennings, N

Abstract

We present the BETH cybersecurity dataset for anomaly detection and out-of-distribution analysis. With real “anomalies” collected using a novel tracking system, our dataset contains over eight million data points tracking 23 hosts. Each host has captured benign activity and, at most, a single attack, enabling cleaner behavioural analysis. In addition to being one of the most modern and extensive cybersecurity datasets available, BETH enables the development of anomaly detection algorithms on heterogeneously-structured real-world data, with clear downstream applications. We give details on the data collection, suggestions on pre-processing, and analysis with initial anomaly detection benchmarks on a subset of the data.

Published
2021

33. How can carbon offsetting help UK further and higher education institutions achieve net zero emissions?

Author

Mitchell-Larson, E, Green, T, Lewis-Brown, E, Jennings, N, Joly, C, Goodwin, F, Reay, D, Rothman, R, Scott, C, Allen, M, and Forster, P

Abstract

There are a range of views on the use of carbon offsetting among academics, higher and further education professional staff, corporates and offsetting providers. When and where offsets should be used or not used, and what types of offsets to use, are to some extent value-laden choices. These choices are being actively debated at the international and community level. This briefing note provides guidance to support the development of further and higher education offsetting policies and to challenge institutions, including our own. It specifically discusses the use of offsetting in the context of net zero strategies. We are also using the briefing to consult our institutions on the approaches they are taking. We hope it prompts discussion and collective action towards making net zero a reality.

Published
2021

34. Human vs. machine: identification of bat species from their echolocation calls by humans and by artificial neural networks

Author

Jennings, N., Parsons, S., and Pocock, M.J.O.

Subjects
Animal navigation -- Research -- Usage -- Behavior, Bats -- Identification and classification -- Behavior -- Research -- Usage, Echolocation (Physiology) -- Evaluation -- Usage -- Research, Neural networks -- Usage -- Evaluation, Zoology and wildlife conservation, Neural network, Identification and classification, Evaluation, Usage, Research, Behavior
Abstract

Abstract: Automated remote ultrasound detectors allow large amounts of data on bat presence and activity to be collected. Processing of such data involves identifying bat species from their echolocation calls. [...]

Published
2008

35. Grantham Institute Outlook 2020-2021

Author

Levey, S, Gilbert, A, Amer, H, Petersen, K, Jennings, N, and Butler, C

Subjects
Climate change, Environment
Abstract

The Grantham Institute Outlook magazine provides an overview of the climate and environmental research underway at Imperial College London, encompassing both recent achievements and future plans.

Published
2020
Full Text
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46. Searches for Axion-Like Particles with X-ray astronomy

Author

Jennings, N and Conlon, J

Abstract

Axion-Like Particles (ALPs) are a very well-motivated class of Beyond the Standard Model particles. They can be implemented as a minimal extension of the Standard Model that could solve many mysteries (the Strong CP Problem, Dark Matter, origin of Inflation), and also commonly arise in String Theory compactifications. This motivates the commissioning of dedicated experiments looking for these particles, as well as the utilisation of telescope data to search for their astrophysical effects. Through their coupling to electromagnetism, they will interconvert with photons in the presence of a magnetic field. A promising environment to look for this effect is the intracluster medium of Galaxy Clusters, which can have weak but very extensive magnetic fields. At X-ray energies, the conversion probability of photons to ALPs is periodic in energy, imprinting a quasi-sinusoidal oscillation on the energy spectrum of an object shining through the cluster. This thesis describes an analysis of data taken by the Chandra and XMM-Newton satellites of point sources (such as active galactic nuclei) shining through galaxy clusters. The absences of modulations in the spectra of these objects lead to constraints on the ALP-photon coupling. With this analysis, a previously unexplored region of parameter space is ruled out. This thesis also details simulations that were performed of the capabilities of the Athena X-ray Observatory, due to launch in 2028, and predicts its ability to place further constraints on ALPs.

Published
2019

49. Bending the curve of terrestrial biodiversity needs an integrated strategy

Author

Leclère, D., Obersteiner, M., Barrett, M., Butchart, S.H.M., Chaudhary, A., De Palma, Adriana, DeClerck, F.A.J., Di Marco, M., Doelman, J.C., Dürauer, M., Freeman, R., Harfoot, M., Hasegawa, T., Hellweg, S., Hilbers, J.P., Hill, S.L.L., Humpenöder, F., Jennings, N., Krisztin, T., Mace, G.M., Ohashi, H., Popp, Alexander, Purvis, A., Schipper, A.M., Tabeau, A., Valin, H., Meijl, H. van, Zeist, W.J. van, Visconti, P., Alkemade, R., Almond, R., Bunting, G., Burgess, N.D., Cornell, S.E., Di Fulvio, F., Ferrier, S., Fritz, S., Fujimori, S., Grooten, M., Harwood, T., Havlík, P., Herrero, M., Hoskins, A.J., Jung, M., Kram, T., Lotze-Campen, H., Matsui, T., Meyer, C., Nel, D., Newbold, T., Schmidt-Traub, G., Stehfest, E., Strassburg, B.B.N., Vuuren, D.P. van, Ware, C., Watson, J.E.M., Wu, W., Young, L., Leclère, D., Obersteiner, M., Barrett, M., Butchart, S.H.M., Chaudhary, A., De Palma, Adriana, DeClerck, F.A.J., Di Marco, M., Doelman, J.C., Dürauer, M., Freeman, R., Harfoot, M., Hasegawa, T., Hellweg, S., Hilbers, J.P., Hill, S.L.L., Humpenöder, F., Jennings, N., Krisztin, T., Mace, G.M., Ohashi, H., Popp, Alexander, Purvis, A., Schipper, A.M., Tabeau, A., Valin, H., Meijl, H. van, Zeist, W.J. van, Visconti, P., Alkemade, R., Almond, R., Bunting, G., Burgess, N.D., Cornell, S.E., Di Fulvio, F., Ferrier, S., Fritz, S., Fujimori, S., Grooten, M., Harwood, T., Havlík, P., Herrero, M., Hoskins, A.J., Jung, M., Kram, T., Lotze-Campen, H., Matsui, T., Meyer, C., Nel, D., Newbold, T., Schmidt-Traub, G., Stehfest, E., Strassburg, B.B.N., Vuuren, D.P. van, Ware, C., Watson, J.E.M., Wu, W., and Young, L.

Abstract

Contains fulltext : 228862.pdf (Publisher’s version ) (Open Access)

Published
2020

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