Mobile phones and radios: effects on transactions costs and market participation for households in Northern Ghana

The literature on agricultural markets suggests that transactions costs are the main obstacles preventing households from participating in agricultural markets. We examine the impact of the recent massive penetration of information communication technologies (ICTs), particularly mobile phones and radios, in developing countries to investigate the role of information in economic transactions and participation in food crop markets. To fully capture market participation behaviours, the current theoretical framework on market participation and transactions costs is extended to include those households that sell and buy in the same time period. We correct for endogeneity and selectivity throughout our models. We used a novel dataset of 393 households in northern Ghana with detailed information on market transactions and ICTs usage. Results show that receiving market information via mobile phones has a positive and significant impact on market participation, with a greater impact for households with a surplus of food crops. We find that radios have a larger impact on the quantity traded. This may reflect the nature of mobile phones in reducing searching costs, whereas radios provide an updated and regular flow of information which affects the pattern of crops consumed and sold. We also emphasise that the most significant factor is how ICTs are used, rather than their ownership.

Variability and trends in England and Wales precipitation

The England and Wales precipitation (EWP) dataset is a homogeneous time series of daily accumulations from 1931 to 2014, composed from rain gauge observations spanning the region. The daily regional-average precipitation statistics are shown to be well described by a Weibull distribution, which is used to define extremes in terms of percentiles. Computed trends in annual and seasonal precipitation are sensitive to the period chosen, due to large variability on interannual and decadal timescales. Atmospheric circulation patterns associated with seasonal precipitation variability are identified. These patterns project onto known leading modes of variability, all of which involve displacements of the jet stream and storm-track over the eastern Atlantic. The intensity of daily precipitation for each calendar season is investigated by partitioning all observations into eight intensity categories contributing equally to the total precipitation in the dataset. Contrary to previous results based on shorter periods, no significant trends of the most intense categories are found between 1931 and 2014. The regional-average precipitation is found to share statistical properties common to the majority of individual stations across England and Wales used in previous studies. Statistics of the EWP data are examined for multi-day accumulations up to 10 days, which are more relevant for river flooding. Four recent years (2000, 2007, 2008 and 2012) have a greater number of extreme events in the 3-and 5-day accumulations than any previous year in the record. It is the duration of precipitation events in these years that is remarkable, rather than the magnitude of the daily accumulations.

Productivity and the international firm: dissecting heterogeneity

Higher productivity of multinational firms and exporters has been widely documented in the literature, but the sources of this heterogeneity are still a black box. Using an original dataset on Italian firms, we show that higher total factor productivity of international firms can be to some extent explained by higher R&D intensity and managerial capabilities. However, our results suggest that heterogeneity is more in the slope than in the constant of the production function. In particular, allowing international firms to have different return to labour and capital inputs, we are able to account for their entire productivity premium. This has implications for both labour and capital market reforms.

Representing the Arctic in global surface temperature time series of recent climate change

The Arctic is an important region in the study of climate change, but monitoring surface temperatures in this region is challenging, particularly in areas covered by sea ice. Here in situ, satellite and reanalysis data were utilised to investigate whether global warming over recent decades could be better estimated by changing the way the Arctic is treated in calculating global mean temperature. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques. Kriging techniques provided the smallest errors in anomaly estimates. Similar accuracies were found for anomalies estimated from in situ meteorological station SAT records using a kriging technique. Whether additional data sources, which are not currently utilised in temperature anomaly datasets, would improve estimates of Arctic surface air temperature anomalies was investigated within the reanalysis testbed and using in situ data. For the reanalysis study, the additional input anomalies were reanalysis data sampled at certain supplementary data source locations over Arctic land and sea ice areas. For the in situ data study, the additional input anomalies over sea ice were surface temperature anomalies derived from the Advanced Very High Resolution Radiometer satellite instruments. The use of additional data sources, particularly those located in the Arctic Ocean over sea ice or on islands in sparsely observed regions, can lead to substantial improvements in the accuracy of estimated anomalies. Decreases in Root Mean Square Error can be up to 0.2K for Arctic-average anomalies and more than 1K for spatially resolved anomalies. Further improvements in accuracy may be accomplished through the use of other data sources.

Bricks vs clicks: entrepreneurial online banking behaviour and relationship banking

Purpose – Little research has been conducted on the effects of information technology on financing entrepreneurial businesses or small and medium sized enterprises (SMEs). The purpose of this paper is to examine the impacts of entrepreneurial online banking and relationship banking on the severity of financial problems perceived by entrepreneurs and their interactive effect. It also investigates how characteristics of individual businesses and entrepreneurial demographics influence SMEs’ financial situation. Design/methodology/approach – An ordered logistic model is used on a UK dataset to empirically test the hypotheses derived in this paper. The empirical evidence is drawn from the 2004 UK survey of SME finances, which contains a sample of 2,500 firms. Findings – This paper finds that both entrepreneurial online banking behaviour and relationship banking alleviates the severity of financial problems perceived by entrepreneurs. The relationship affect is less evident for entrepreneurs who most frequently use an online approach to communicate with their banks than for those using traditional methods. Business and entrepreneur characteristics also have a strong impact on the severity of the financial problems suffered by SMEs. Originality/value – This paper provides evidence supporting the favourable impacts of the application of information technology on entrepreneurial finance from the perspective of entrepreneur/business. It also identifies a substitute relationship between entrepreneurial online banking behaviour and relationship banking, a relationship which contradicts existing evidence.

The determinants of online loan applications from small businesses

Purpose – The purpose of this paper is to examine both the characteristics of the business customers and the types of venture which make use of online loan applications. Despite the growth in the use of technology in banking and the advent of online banking, little research has been conducted on the factors underlying online loan application behaviour amongst business banking customers. Design/methodology/approach – A multivariate analysis is conducted on a USA dataset to empirically test the hypotheses derived in this paper. The empirical evidence is drawn from the US Survey of Small Business Finances, which contains 3,561 sample ventures, representing 5.3 million small businesses in the USA. Findings – The paper finds that online loan behaviour is largely determined by the characteristics of the entrepreneur, rather than that of the venture. It is also found that factors that trust, evident in the length of the relationship between the applicants and their primary lender, is important. Moderating these effects is further evidence that suggests the number of lenders and distance between lenders and applicants has a marked effect on online loan behaviour. Originality/value – This paper identifies the factors determining small business online loan application behaviour. This is important because the nature of online loan behaviour is changing the existing relationships between banks and customers. Whilst online loan applications afford banks the opportunity to substantially reduce costs, the danger is that long term relationships with customers are harder to cement.

Glastonbury Abbey: archaeological investigations 1904-79

This volume reports on the results of the Glastonbury Abbey Archaeological Archive Project, a collaboration between the University of Reading and the Trustees of Glastonbury Abbey, funded principally by the Arts and Humanities Research Council. The project has reassessed and reinterpreted all known archaeological records from the 1908–79 excavations and made the complete dataset available to the public through a digital archive hosted by the Archaeology Data Service (http://dx.doi.org/10.5284/1022585). The scope of the project has included the full analysis of the archaeological collections of Glastonbury Abbey by thirty-one leading specialists, including chemical and compositional analysis of glass and metal and petrological analysis of pottery and tile, and a comprehensive geophysical survey conducted by GSB Prospection Ltd. For the first time, it has been possible to achieve a framework of independent dating based on reassessment of the finds and radiocarbon dating of surviving organic material from the 1950s excavations. The principal aim of the Glastonbury Abbey Archaeological Project was to set aside previous assumptions based on the historical and legendary traditions and to provide a rigorous reassessment of the archive of antiquarian excavations. This research has revealed that some of the best known archaeological ‘facts’ about Glastonbury are themselves myths perpetuated by the abbey’s excavators.

PETS 2015: datasets and challenge

This paper presents the two datasets (ARENA and P5) and the challenge that form a part of the PETS 2015 workshop. The datasets consist of scenarios recorded by us- ing multiple visual and thermal sensors. The scenarios in ARENA dataset involve different staged activities around a parked vehicle in a parking lot in UK and those in P5 dataset involve different staged activities around the perimeter of a nuclear power plant in Sweden. The scenarios of each dataset are grouped into ‘Normal’, ‘Warning’ and ‘Alarm’ categories. The Challenge specifically includes tasks that account for different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘atomic’ event detection) and High-Level Video Analysis (‘complex’ event detection). The evaluation methodology used for the Challenge includes well-established measures.

Vehicle subtype, make and model classification from side profile video

This paper addresses the challenging domain of vehicle classification from pole-mounted roadway cameras, specifically from side-profile views. A new public vehicle dataset is made available consisting of over 10000 side profile images (86 make/model and 9 sub-type classes). 5 state-of-the-art classifiers are applied to the dataset, with the best achieving high classification rates of 98.7% for sub-type and 99.7- 99.9% for make and model recognition, confirming the assertion made that single vehicle side profile images can be used for robust classification.

Big social data and political sentiment: the tweet stream during the UK General Election 2015 campaign

The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.

On fusion for multispectral iris recognition

Multispectral iris recognition uses information from multiple bands of the electromagnetic spectrum to better represent certain physiological characteristics of the iris texture and enhance obtained recognition accuracy. This paper addresses the questions of single versus cross spectral performance and compares score-level fusion accuracy for different feature types, combining different wavelengths to overcome limitations in less constrained recording environments. Further it is investigated whether Doddington's “goats” (users who are particularly difficult to recognize) in one spectrum also extend to other spectra. Focusing on the question of feature stability at different wavelengths, this work uses manual ground truth segmentation, avoiding bias by segmentation impact. Experiments on the public UTIRIS multispectral iris dataset using 4 feature extraction techniques reveal a significant enhancement when combining NIR + Red for 2-channel and NIR + Red + Blue for 3-channel fusion, across different feature types. Selective feature-level fusion is investigated and shown to improve overall and especially cross-spectral performance without increasing the overall length of the iris code.

Towards anomaly detection for increased security in multibiometric systems: spoofing-resistant 1-median fusion eliminating outliers

Multibiometrics aims at improving biometric security in presence of spoofing attempts, but exposes a larger availability of points of attack. Standard fusion rules have been shown to be highly sensitive to spoofing attempts – even in case of a single fake instance only. This paper presents a novel spoofing-resistant fusion scheme proposing the detection and elimination of anomalous fusion input in an ensemble of evidence with liveness information. This approach aims at making multibiometric systems more resistant to presentation attacks by modeling the typical behaviour of human surveillance operators detecting anomalies as employed in many decision support systems. It is shown to improve security, while retaining the high accuracy level of standard fusion approaches on the latest Fingerprint Liveness Detection Competition (LivDet) 2013 dataset.

On fusion for robust motion segmentation

While a multitude of motion segmentation algorithms have been presented in the literature, there has not been an objective assessment of different approaches to fusing their outputs. This paper investigates the application of 4 different fusion schemes to the outputs of 3 probabilistic pixel-level segmentation algorithms. We performed an extensive experimentation using 6 challenge categories from the changedetection.net dataset demonstrating that in general simple majority vote proves to be more effective than more complex fusion schemes.

On the importance of Vaisala RS92 radiosonde humidity corrections for a better agreement between measured and modeled satellite radiances

A study has been carried out to assess the importance of radiosonde corrections in improving the agreement between satellite and radiosonde measurements of upper-tropospheric humidity. Infrared [High Resolution Infrared Radiation Sounder (HIRS)-12] and microwave [Advanced Microwave Sounding Unit (AMSU)-18] measurements from the NOAA-17 satellite were used for this purpose. The agreement was assessed by comparing the satellite measurements against simulated measurements using collocated radiosonde profiles of the Atmospheric Radiation Measurement (ARM) Program undertaken at tropical and midlatitude sites. The Atmospheric Radiative Transfer Simulator (ARTS) was used to simulate the satellite radiances. The comparisons have been done under clear-sky conditions, separately for daytime and nighttime soundings. Only Vaisala RS92 radiosonde sensors were used and an empirical correction (EC) was applied to the radiosonde measurements. The EC includes correction for mean calibration bias and for solar radiation error, and it removes radiosonde bias relative to three instruments of known accuracy. For the nighttime dataset, the EC significantly reduces the bias from 0.63 to 20.10 K in AMSU-18 and from 1.26 to 0.35 K in HIRS-12. The EC has an even greater impact on the daytime dataset with a bias reduction from 2.38 to 0.28 K in AMSU-18 and from 2.51 to 0.59 K in HIRS-12. The present study promises a more accurate approach in future radiosonde-based studies in the upper troposphere.

Collocating satellite-based radar and radiometer measurements — methodology and usage examples

Collocations between two satellite sensors are occasions where both sensors observe the same place at roughly the same time. We study collocations between the Microwave Humidity Sounder (MHS) on-board NOAA-18 and the Cloud Profiling Radar (CPR) on-board CloudSat. First, a simple method is presented to obtain those collocations and this method is compared with a more complicated approach found in literature. We present the statistical properties of the collocations, with particular attention to the effects of the differences in footprint size. For 2007, we find approximately two and a half million MHS measurements with CPR pixels close to their centrepoints. Most of those collocations contain at least ten CloudSat pixels and image relatively homogeneous scenes. In the second part, we present three possible applications for the collocations. Firstly, we use the collocations to validate an operational Ice Water Path (IWP) product from MHS measurements, produced by the National Environment Satellite, Data and Information System (NESDIS) in the Microwave Surface and Precipitation Products System (MSPPS). IWP values from the CloudSat CPR are found to be significantly larger than those from the MSPPS. Secondly, we compare the relation between IWP and MHS channel 5 (190.311 GHz) brightness temperature for two datasets: the collocated dataset, and an artificial dataset. We find a larger variability in the collocated dataset. Finally, we use the collocations to train an Artificial Neural Network and describe how we can use it to develop a new MHS-based IWP product. We also study the effect of adding measurements from the High Resolution Infrared Radiation Sounder (HIRS), channels 8 (11.11 μm) and 11 (8.33 μm). This shows a small improvement in the retrieval quality. The collocations described in the article are available for public use.