Cinema-going at the Southampton Odeon: Exhibition Data and Popular Taste

Cinemagoing data from the 1970s. A case study of the data from the Southampton Odeon

Establishing a population-based patient-reported outcomes study (PROMs) using national cancer registries across two jurisdictions: The Prostate Cancer Treatment, your experience (PiCTure) study

Objective: To establish an international patient-reported outcomes (PROMs) study among prostate cancer survivors, up to 18 years postdiagnosis, in two countries with different healthcare systems and ethical frameworks. Design: A cross-sectional, postal survey of prostate cancer survivors sampled and recruited via two population-based cancer registries. Healthcare professionals (HCPs) evaluated patients for eligibility to participate. Questionnaires contained validated instruments to assess health-related quality of life and psychological well-being, including QLQ-C30, QLQPR-25, EQ-5D-5L, 21-question Depression, Anxiety and Stress Scale (DASS-21) and the Decisional Regret Scale. Setting: Republic of Ireland (RoI) and Northern Ireland (NI). Primary outcome measures: Registration completeness, predictors of eligibility and response, data missingness, unweighted and weighted PROMs. Results: Prostate cancer registration was 80% (95% CI 75% to 84%) and 91% (95% CI 89% to 93%) complete 2 years postdiagnosis in NI and RoI, respectively. Of 12 322 survivors sampled from registries, 53% (n=6559) were classified as eligible following HCP screening. In the multivariate analysis, significant predictors of eligibility were: being ≤59 years of age at diagnosis (p<0.001), short-term survivor (<5 years postdiagnosis; p<0.001) and from RoI (p<0.001). 3348 completed the questionnaire, yielding a 54% adjusted response rate. 13% of men or their families called the study freephone with queries for assistance with questionnaire completion or to talk about their experience. Significant predictors of response in multivariate analysis were: being ≤59 years at diagnosis (p<0.001) and from RoI (p=0.016). Mean number of missing questions in validated instruments ranged from 0.12 (SD 0.71; EQ-5D-5L) to 3.72 (SD 6.30; QLQ-PR25). Weighted and unweighted mean EQ-5D-5L, QLQ-C30 and QLQ-PR25 scores were similar, as were the weighted and unweighted prevalences of depression, anxiety and distress. Conclusions: It was feasible to perform PROMs studies across jurisdictions, using cancer registries as sampling frames; we amassed one of the largest, international, population-based data set of prostate cancer survivors. We highlight improvements which could inform future PROMs studies, including utilising general practitioners to assess eligibility and providing a freephone service.

Next generation Bridge weigh-in-motion using fibre optic sensors

There have been over 3000 bridge weigh-in-motion (B-WIM) installations in 25 countries worldwide, this has led vast improvements in post processing of B-WIM systems since its introduction in the 1970’s. Existing systems are based on electrical resistance strain gauges which can be prohibitive in achieving data for long term monitoring of rural bridges due to power consumption. This paper introduces a new low-power B-WIM system using fibre optic sensors (FOS). The system consisted of a series of FOS which were attached to the soffit of an existing integral bridge with a single span of 19m. The site selection criteria and full installation process has been detailed in the paper. A method of calibration was adopted using live traffic at the bridge site and based on this calibration the accuracy of the system was determined. New methods of axle detection for B-WIM were investigated and verified in the field.

Spatio-Temporal Rich Model For Motion Vector Steganalysis

We propose a spatio-temporal rich model of motion vector planes as a part of a full steganalytic system against motion vector based steganography. Superior detection accuracy of the rich model over the previous methods has been lately demonstrated for digital images in both spatial and DCT domain. It has not been heretofore used for detection of motion vector steganography. We also introduced a transformation so as to extend the feature set with temporal residuals. We carried out the tests along with most recent motion vector steganalysis and steganography methods. Test results show that the proposed model delivers an outstanding performance compared to the previous methods.

Recent developments in bridge weigh-in-motion (B-WIM).

Bridge Weigh in Motion (B-WIM) uses accurate sensing systems to transform an existing bridge into a mechanism to determine actual traffic loading. This information on traffic loading can enable efficient and economical management of transport networks and is becoming a valuable tool for bridge safety assessment. B-WIM can provide site specific traffic loading on deteriorating bridges, which can be used to determine if the reduced capacity is still sufficient to allow the structure to remain operational and minimise unnecessary replacement or rehabilitation costs and prevent disruption to traffic. There have been numerous reports on the accuracy classifications of existing B-WIM installations and some common issues have emerged. This paper details some of the recent developments in B-WIM which were aimed at overcoming these issues. A new system has been developed at Queens University Belfast using fibre optic sensors to provide accurate axle detection and improved accuracy overall. The results presented in this paper show that the fibre optic system provided much more accurate results than conventional WIM systems, as the FOS provide clearer signals at high scanning rates which require less filtering and less post processing. A major disadvantage of existing B-WIM systems is the inability to deal with more than one vehicle on the bridge at the same time; sensor strips have been proposed to overcome this issue. A bridge can be considered safe if the probability that load exceeds resistance is acceptably low, hence B-WIM information from advanced sensors can provide confidence in our ageing structures.

Assessment Of various sensors for structural health monitoring for bridge weigh-in-motion (B-WIM).

In recent years, Structural Health Monitoring (SHM) systems have been developed to monitor bridge deterioration, assess real load levels and hence extend bridge life and safety. A road bridge is only safe if the stresses caused by the passing vehicles are less than the capacity of the bridge to resist them. Conventional SHM systems can be used to improve knowledge of the bridges capacity to resist stresses but generally give no information on the causes of any increase in stresses (based on measuring strain). The concept of in Bridge Weigh-in-Motion (B-WIM) is to establish axle loads, without interruption to traffic flow, by using strain sensors at a bridge soffit and subsequently converting the data to real time axle loads or stresses. Recent studies have shown it would be most beneficial to develop a portable system which can be easily attached to existing and new bridge structures for a specified monitoring period. The sensors could then be left in place while the data acquisition can be moved for various other sites. Therefore it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, the adhesives layer and the strain sensor. This paper describes research investigating the suitably of using various sensors for the monitoring of concrete structures under dynamic vehicle load. Electrical resistance strain (ERS) gauges, vibrating wire (VW) gauges and fibre optic sensors (FOS) are commonly used for SHM. A comparative study will be carried out to select a suitable sensor for a bridge Weigh in Motion System. This study will look at fixing methods, durability, scanning rate and accuracy range. Finite element modeling is used to predict the strains which are then validated in laboratory trials.

A Novel Approach for Axle Detection in Bridge Weigh-In-Motion Systems

Bridge weigh-in-motion (B-WIM), a system that uses strain sensors to calculate the weights of trucks passing on bridges overhead, requires accurate axle location and speed information for effective performance. The success of a B-WIM system is dependent upon the accuracy of the axle detection method. It is widely recognised that any form of axle detector on the road surface is not ideal for B-WIM applications as it can cause disruption to the traffic (Ojio & Yamada 2002; Zhao et al. 2005; Chatterjee et al. 2006). Sensors under the bridge, that is Nothing-on-Road (NOR) B-WIM, can perform axle detection via data acquisition systems which can detect a peak in strain as the axle passes. The method is often successful, although not all bridges are suitable for NOR B-WIM due to limitations of the system. Significant research has been carried out to further develop the method and the NOR algorithms, but beam-and-slab bridges with deep beams still present a challenge. With these bridges, the slabs are used for axle detection, but peaks in the slab strains are sensitive to the transverse position of wheels on the beam. This next generation B-WIM research project extends the current B-WIM algorithm to the problem of axle detection and safety, thus overcoming the existing limitations in current state-of–the-art technology. Finite Element Analysis was used to determine the critical locations for axle detecting sensors and the findings were then tested in the field. In this paper, alternative strategies for axle detection were determined using Finite Element analysis and the findings were then tested in the field. The site selected for testing was in Loughbrickland, Northern Ireland, along the A1 corridor connecting the two cities of Belfast and Dublin. The structure is on a central route through the island of Ireland and has a high traffic volume which made it an optimum location for the study. Another huge benefit of the chosen location was its close proximity to a nearby self-operated weigh station. To determine the accuracy of the proposed B-WIM system and develop a knowledge base of the traffic load on the structure, a pavement WIM system was also installed on the northbound lane on the approach to the structure. The bridge structure selected for this B-WIM research comprised of 27 pre-cast prestressed concrete Y4-beams, and a cast in-situ concrete deck. The structure, a newly constructed integral bridge, spans 19 m and has an angle of skew of 22.7°.