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Value creation in an algorithmic world: Towards an ethics of dynamic pricing
Full text linkChoice of pricing strategy plays a central role in value creation and the effective functioning of markets. Shifts in technology and the growing availability of data are facilitating ever more innovative forms of pricing strategy. Within the emerging literature on pricing ethics, there is a gap in our understanding of the specific challenges of algorithmically generated dynamic pricing. Increasing pricing automation shifts the managerial focus from the selection of prices to the choice of algorithms. This paper expands the literature on pricing ethics by conceptualizing the ethical challenges raised by the contemporary use of dynamic pricing. We propose a governance model for algorithmically generated dynamic pricing, taking into account the role of the customer as a stakeholder in value generation
Enhancing CZTSSe solar cells through electric field induced ion migration
No full textSolar cells made from Cu 2 ZnSn(S,Se) 4 (CZTS)-derived materials have been widely studied for their favourable material properties utilized in photovoltaic energy conversion. Drawbacks of the materials are associated with low open circuit voltage (V oc) resulting from non-radiative recombination at grain boundaries and interfaces. Considerable work has focused on the incorporation of sodium (Na), which is found to passivate trap states and reduce electronic losses. Here we present evidence that Na + as well as several ionic species (Se 2À and Zn 2+), do not remain stationary after device fabrication, but in fact migrate under electrical biasing. Furthermore, this ionic migration can be manipulated at room temperature by exposing the device to an external electric forming field. We outline a novel procedure that can effectively control and adjust ionic movement and associated local distribution in fully fabricated devices. Our results show that this simple treatment leads to favourable improved device performance and provides insight into light-induced reduction in performance which may be partially reversible
SAKE*: A Symmetric Authenticated Key Exchange Protocol with Perfect Forward Secrecy for Industrial Internet of Things
No full textSecurity in Industrial Internet of Things (IIoT) is of vital importance as there are some cases where IIoT devices collect sensory information for crucial social production and life. Thus, designing secure and efficient communication channels is always a research hotspot. However, end devices have limitations in memory, computation, and power-supplying capacities. Moreover, perfect forward secrecy (PFS), which means that long-term key exposure cannot disclose previous session keys, is a critical security property for authentication and key exchange (AKE). In this paper, we propose an AKE protocol named SAKE* for the IIoT environment, where PFS is provided by two types of keys (i.e., a master key and an evolution key). In addition, the SAKE* protocol merely uses concatenation, XOR, and hash function operations to achieve lightweight authentication, key exchange, and message integrity. We also compare the SAKE* protocol with seven recent and IoT-related authentication protocols in terms of security properties and performance. Comparison results indicate that the SAKE* protocol consumes the least computation resource and third least communication cost among eight AKE protocols while equipping with twelve security properties
Tourism memory, mood repair and behavioral intention
No full textRecall of tourism experiences evokes pleasant affect tied to the trip, which leads to mood and behavioral intentions. Based on experimental design with two studies, this research investigates the mood-repairing role of tourism memory, memory characteristics, and affective and behavioral consequences of tourism memory. Study 1 confirmed that both positive and negative mood groups recall positive tourism memories, and the effect of mood repair motivation on tourism memory valence is moderated by mood state. Study 2 identified tourism memory characteristics and the effect of tourism memory valence on mood and behavioral intentions. Findings contribute to the literature on relationships between tourism memories, mood and behavioral intentions, and inform tourism organizations on how to use tourism memories for experience management. </p
Spaceborne SAR and AIS Data Fusion for Dense Shipping Environments
Full text linkA wide range of research activities exploit spaceborne Synthetic Aperture Radar (SAR) and Automatic Identification System (AIS) for applications that contribute to maritime safety, security and sustainability. An important requirement of SAR and AIS data fusion is accurate data association (or correlation), which is the process of linking SAR ship detections and AIS observations considered to be of a common origin. The data association is particularly challenging in dense shipping environments, where ships detected in SAR imagery can be wrongly associated with AIS observations. This often results in an erroneous and/or inaccurate maritime picture which disrupts surveillance operations and negatively affects research activities that use AIS as a source of ground truth. Therefore, a classification-aided data association technique is proposed which uses a transfer learning method to classify ship types in SAR imagery. Specifically, a ship classification model is first trained on AIS data and then transferred to make predictions on SAR ship detections. These predictions are subsequently used in the data association which uses a rank-ordered assignment technique to provide a robust match between the data.A series of Monte Carlo tests are performed to evaluate the performance and robustness of the classification-aided data association technique. Subsequently, two case studies of dense shipping environments in the UK are used to validate a multisensor fusion framework based on the types of SAR product used for maritime surveillance: wide-area and large-scale data association in the English Channel and focused data association in the Solent. Results show a high level of correspondence between the data that is robust to dense shipping or high traffic areas, and the confidence in the data association is improved when using class (i.e. ship type) information. Additionally, the effectiveness of co-located SAR and AIS datasets collected from the UK’s first spaceborne radar mission, NovaSAR-1, is evaluated. Finally, future research directions involving the fusion of SAR and AIS data are discussed
Police perceptions of problem-oriented policing and evidence-based policing: evidence from England and Wales
Full text linkThe history of policing is littered with reform programmes, which aim to improve effectiveness, efficiency and legitimacy. Problem-oriented policing (POP) and evidence-based policing (EBP) are two popular and enduring reform efforts, both of which have generated significant researcher and practitioner attention. There are important similarities between POP and EBP: both approaches provide a framework intended to improve the outcomes of policing. There are also key differences, however, in terms of their main objectives, standards of evidence and units of analysis. Despite both approaches being widely advocated and implemented, presently little is known about police practitioner understanding of the relationship between POP and EBP, both in principle and in practice. To address this gap, this paper draws on survey (n = 4,141) and interview (n = 86) data collected from 19 police forces in England and Wales in 2019 to explore police practitioners’ views on the relationship between POP and EBP, and the extent to which these two approaches inform contemporary police practices. Our findings indicate that respondents generally viewed the two approaches as complementary and important frameworks for orienting police work. However, respondents also drew attention to how the two approaches are not always connected organisationally nor in the minds of police personnel. In addition, challenges were identified in the application of both approaches in practice. Our results suggest that more needs to be done to maximise the potential of POP and EBP, both separately and synergistically. The article concludes by suggesting some ways in which this might be achieved
Contribution of Earth observation data to support SDG indicators: An analytical framework and related case studies
Full text linkIn 2015, member countries of the United Nations adopted the 17 Sustainable Development Goals (SDGs) at the Sustainable Development Summit in New York. These global goals have 169 targets and 232 indicators that are based on the three pillars of sustainable development: economic, social, and environmental. Substantial challenges remain in obtaining data of the required quality to inform the indicators, especially in developing countries, given the often limited resources that are available. One promising and relatively innovative way of addressing this issue is to use Earth Observation (EO) satellite data. This research aimed to critically analyse the potential of EO approaches to data collection for populating SDG indicators, with the particular focus on those covering the social and economic dimensions of sustainable development, as these are relatively unexplored in the EO context. Additionally, this research aimed to explore the use of EO technologies linked to monitoring, reporting and verification within policy. Firstly, a novel analytical framework entitled Maturity Matrix Framework (MMF) was developed for assessing the potential of EO to populate all 232 SDG indicators. This framework was further consolidated by using a wide consultation with 38 experts in sustainability and EO, thus obtaining the advanced MMF 2.0 framework. Both frameworks have been applied to all SDG indicators and the results demonstrated that the potential of EO‐derived data do vary among the SDG indicators, but overall, EO can have a direct contribution to make towards populating environmental indicators and an indirect (proxy) measure or weakcontribution for socio-economic indicators. Therefore, the evaluation of the potential of EO satellite data against MMF 2.0 and the literature available shown that 19 indicators have weak support from EO, 67 partial support from EO, and 22 strong EO support. The results that emerged from both frameworks (MMF and MMF 2.0) led towards exploring a more conventional application of satellite data and its implications in the policy context but also towards, developing an EO approach that measures socio-economic indicators. Therefore, this research presents three case studies. The first case study shows how EO satellite data can be used for assessing the habitat of five key species in Surrey Hills. In the second case study available published literature was assessed to understand the potential of estimating SOC using EO technologies. This review was complemented by a series of semistructuredinterviews with specialists in the soil health and policy sector. Both case studies can help the current Environmental Land Management Scheme in the context of the monitoring, reporting and verification (MRV) process. In the third case study, 1900 rural primary schools across 19 Nigerian states were measured using satellite images and teaching area per pupil was calculated. The approach identified 81.4 % of the schools as being overcrowded
Flood characterization based on UAV mapping and forensic analysis of a structural failure
No full textMechanistic model based optimization of feeding practices in aquaculture
Full text linkFish feed accounts for more than 50% of total production cost in intensive aquaculture. Feeding fish with low-quality feed or adopting inappropriate feeding strategies causes not only food waste and consequent loss of income but also lead to water pollution. The aim of this study was to develop a mechanistic model based optimization method to determine aquaculture feeding programs. In particular, we integrate a fish weight prediction model and a requirement analysis model to establish an optimization method for designing balanced and sustainable feed formulations and effective feeding programs. The optimization strategy is necessary to maximise the fish weight at harvest, while constraints include specific feed requirements and fish growth characteristics. The optimization strategy is re-solved with new available fish weight measurement by using the error between measurement and model prediction to adjust the requirement analysis model and update feeding amount decision. The mechanistic models are parameterised using the existing nutritional data on gilthead seabream (Sparus aurata) to demonstrate the usefulness of proposed method. The simulation results show that the proposed approach can significantly improve aquaculture production. This particular simulation study reveals that when “Only prediction” method is considered as benchmark, the average improvement in fish weight of proposed method would be 13.25% when fish weight is measured once per four weeks (mimicking manual sampling practice), and 38.43% when daily measurement of fish weight is possible (e.g. through automatic image-based methods). Furthermore, if feed composition (460 g protein.kg feed−1; 18.9 MJ kg feed−1) is adjusted, the average improvement of proposed method could reach 46.85%. Compared with traditional feeding methods, the improvement of proposed method could reach 36.36% of the final fish weight at harvest. Further studies will consider improving the quality of feed plus executing more appropriate mathematical prediction models to optimize production performance
Design of Monopiles for Offshore and Nearshore Wind Turbines in Seismically Liquefiable Soils: Methodology and Validation
Full text linkAn increasing number of offshore wind farms are being constructed in seismic regions over liquefaction susceptible soils. This paper presents a methodology for the analysis and design of monopiles in seismically liquefiable soils by extending the established "10-step methodology" with an additional 7 steps. These additional steps include assimilation of seismic data, site response analysis, stability check of the structure (ULS check through the concept of load-utilization ratio), input motion selection, prediction of permanent tilt/rotation, and ground settlement post liquefaction. A flow chart, which shows the interdependence of the different disciplines, is presented and can be extended to routine design. This proposed method is validated using the observed performance of an offshore and nearshore turbine from the Kamisu wind farm during the 2011 Great East Japan earthquake. Predicted results based on the proposed methodology compare well with the field observation and demarcate the (i) good overall performance of the offshore turbines and (ii) limit state exceedance of the nearshore turbine. It is envisaged that the proposed method will be useful towards the design of monopiles-supported wind turbines in seismic areas
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