Remote Extraction of Latent Fingerprints (RELF)

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordLatent fingerprints are the kind left on objects after direct contact with a person’s finger, often unwittingly at crime scenes. Most current techniques for extracting these types of fingerprint are invasive and involve contaminating the fingerprint with chemicals which often renders the fingerprint unusable for further forensic testing. We propose a novel and robust method for extracting latent fingerprints from surfaces without the addition of contaminants or chemicals to the evidence. We show our technique works on notoriously difficult to image surfaces, using off-the-shelf cameras and statistical analysis. In particular, we extract images of latent fingerprints from surfaces which are transparent, curved and specular such as glass lightbulbs and jars, which are challenging due to the curvature of the surface. Our method produces results comparable to more invasive methods and leaves the fingerprint sample unaffected for further forensic analysis. Our technique uses machine learning to identify partial fingerprints between successive images and mosaics them

A Comprehensive Summary of the Shrimp Fishery of the Gulf of Mexico United States: A Regional Management Plan

https://aquila.usm.edu/gcrl_publications/1011/thumbnail.jp

Inexact Bayesian point pattern matching for linear transformations

PublishedArticleWe introduce a novel Bayesian inexact point pattern matching model that assumes that a linear transformation relates the two sets of points. The matching problem is inexact due to the lack of one-to-one correspondence between the point sets and the presence of noise. The algorithm is itself inexact; we use variational Bayesian approximation to estimate the posterior distributions in the face of a problematic evidence term. The method turns out to be similar in structure to the iterative closest point algorithm.This work was supported by the University of Exeter’s Bridging the Gaps initiative, which was funded by EPSRC award EP/I001433/1 and the collaboration was formed through the Exeter Imaging Network

Fotodegradasi Zat Warna Metanil Yellow Menggunakan Fotokatalis TiO2-Karbon Aktif

Telah dilakukan penelitian untuk mempelajari pengaruh penambahan karbon aktif (KA) pada fotokatalis TiO2 serta aktivitas fotokatalitiknya dalam proses fotodegradasi zat warna metanil yellow. Penelitian diawali dengan pembuatan KA dari tempurung kelapa, kemudian dilakukan modifikasi fotokatalis TiO2–KA. Eksperiman fotodegradasi metanil yellow oleh fotokatalis TiO2–KA dilakukan dengan perbandingan berat TiO2:KA sebesar 9,9:0,1 dan 9,5:0,5 dan konsentrasi metanil yellow 2–50 ppm, serta variasi waktu penyinaran sinar UV selama 1, 2, 3, 4, 5, 19 dan 20 jam. Hasil penelitian menunjukkan bahwa persentase proses fotodegradasi tertinggi diperoleh pada perbandingan berat TiO2:KA (9,9:0,1) dan aktivitas fotodegradasi semakin meningkat seiring dengan bertambahnya waktu penyinaran.A research had been conducted to study the effect of the addition of activated carbon (AC) on TiO2 photocatalyst and its photocatalytic activity in photodegradation process of metanil yellow dye. The research was performed through the preparation of activated carbon from coconut shell and modification of photocatalyst TiO2–AC. Experiment of metanil yellow photodegradation by photocatalyst TiO2–AC was performed at the weight ratio of TiO2:AC of 9,9:0,1 and 9,5:0,5 with the concentrations of metanil yellow of 2–50 ppm, and time variations of UV rays irradiation of 1, 2, 3, 4, 5, 19 and 20 hours. The results showed that the highest percentage of photodegradation process obtained at the weight ratio of TiO2:AC of 9,9:0,1 and the photodegradation activity was increased along with increasing irradiation tim

On Random Sampling and Fourier Transform Estimation in Sea Waves Prediction

Improving the safety of a wide range of launch and recovery operations is of great international maritime interest. Deterministic sea wave prediction (DSWP) is a relatively new branch of science that can offer such opportunities by predicting the actual shape of the sea surface and its evolution for short time in the future. Fourier transform technique is the main building block in DSWP, which requires measurements of the sea surface. Nonetheless, uniformly sampled measurements of the sea surface cannot be practically achieved for various reasons. Conventional X-band radars are the most realistic candidate to provide a low-cost convenient source of two-dimensional wave profile information for DSWP purposes. Ship movement and mechanically rotating scanning antennas are among sources of irregularity in sea surface sampling. This in turn introduces errors when traditional Fourier transform based wave prediction methods are used. In this paper we show that by modelling the radar sampling instants as random variables and using the estimator of Tarczynski and Allay to process the samples, a reliable solution for DSWP can be constituted

Robust face recognition by an albedo based 3D morphable model

Large pose and illumination variations are very challenging for face recognition. The 3D Morphable Model (3DMM) approach is one of the effective methods for pose and illumination invariant face recognition. However, it is very difficult for the 3DMM to recover the illumination of the 2D input image because the ratio of the albedo and illumination contributions in a pixel intensity is ambiguous. Unlike the traditional idea of separating the albedo and illumination contributions using a 3DMM, we propose a novel Albedo Based 3D Morphable Model (AB3DMM), which removes the illumination component from the images using illumination normalisation in a preprocessing step. A comparative study of different illumination normalisation methods for this step is conducted on PIE and Multi-PIE databases. The results show that overall performance of our method outperforms state-of-the-art methods

A novel Markov logic rule induction strategy for characterizing sports video footage

The grounding of high-level semantic concepts is a key requirement of video annotation systems. Rule induction can thus constitute an invaluable intermediate step in characterizing protocol-governed domains, such as broadcast sports footage. We here set out a novel “clause grammar template” approach to the problem of rule-induction in video footage of court games that employs a second-order meta grammar for Markov Logic Network construction. The aim is to build an adaptive system for sports video annotation capable, in principle, both of learning ab initio and also adaptively transferring learning between distinct rule domains. The method is tested with respect to both a simulated game predicate generator and also real data derived from tennis footage via computer-vision based approaches including HOG3D based player-action classification, Hough-transform based court detection, and graph-theoretic ball-tracking. Experiments demonstrate that the method exhibits both error resilience and learning transfer in the court domain context. Moreover the clause template approach naturally generalizes to any suitably-constrained, protocol-governed video domain characterized by feature noise or detector error

Radiofrequency-assisted liver resection versus clamp-crush liver resection: protocol for an updated meta-analysis and systematic review

Background: Malignancy of the liver has historically meant a poor prognosis and remains the second most common cause of cancer-related deaths globally. Traditionally, hepatectomy has utilized the clamp-crush technique; however, this is associated with high incidence of postoperative complications. Many novel techniques have been developed—radiofrequency ablation and transarterial chemoembolization; however, these are not applicable to numerous cases. Clamp-crush liver resection (CCLR) remains the gold standard. Radiofrequency-assisted liver resection (RFLR) is a technique that aims to reduce mortality through bloodless liver resection. A systematic review was previously performed on RFLR but the results neither recommended nor refuted the use of RFLR owing to the lack of sufficient evidence from well-designed randomized controlled trials (RCTs) at the time. Objective: The aim of the study is the meta-analysis and systematic review of recent studies comparing RFLR against CCLR. Methods: Articles comparing RFLR and CCLR that were published from 2014 until 2019 will be reviewed and relevant data will be extracted and statistically analyzed through Review Manager 5 (by the Cochrane Collaboration) together with the results of the previous meta-analysis. Results: Data collection is currently underway, with papers being screened. We hope to publish the results by the end of 2019. Conclusions: Given the high mortality rates currently associated with liver resection, it is imperative that novel surgical techniques are undertaken and investigated so we can improve best practice guidance and outcomes. International Registered Report Identifier (IRRID): DERR1-10.2196/1343

Sea State Estimation from Uncalibrated, Monoscopic Video

This is the final version. Available on open access from Springer via the DOI in this recordVideo of the ocean surface is used as a means for estimating the sea state. Time series of pixel intensity values are given as input to a method that uses the Kalman filter and the least squares approximate solution for estimating the uncalibrated video amplitude spectrum. A method is proposed for scaling this spectrum to metres with the use of an empirical model of the ocean. The significant wave height is estimated from the calibrated video amplitude spectrum. The results are tested against two sets of video data, and buoy measurements in both cases are solely used for indicating the true state. For significant wave height values between 0.5 and 3.6 m, the maximum observed value of root mean square error is 0.37 m and of mean absolute percentage error 16%