Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery

We consider the use of transfer learning, via the use of deep Convolutional Neural Networks (CNN) for the image classification problem posed within the context of X-ray baggage security screening. The use of a deep multi-layer CNN approach, traditionally requires large amounts of training data, in order to facilitate construction of a complex complete end-to-end feature extraction, representation and classification process. Within the context of X-ray security screening, limited availability of training for particular items of interest can thus pose a problem. To overcome this issue, we employ a transfer learning paradigm such that a pre-trained CNN, primarily trained for generalized image classification tasks where sufficient training data exists, can be specifically optimized as a later secondary process that targets specific this application domain. For the classical handgun detection problem we achieve 98.92% detection accuracy outperforming prior work in the field and furthermore extend our evaluation to a multiple object classification task within this context

On using Feature Descriptors as Visual Words for Object Detection within X-ray Baggage Security Screening

Here we explore the use of various feature point descriptors as visual word variants within a Bag-of-Visual-Words (BoVW) representation scheme for image classification based threat detection within baggage security X-ray imagery. Using a classical BoVW model with a range of feature point detectors and descriptors, supported by both Support Vector Machine (SVM) and Random Forest classification, we illustrate the current performance capability of approaches following this image classification paradigm over a large X-ray baggage imagery data set. An optimal statistical accuracy of 0.94 (true positive: 83%; false positive: 3.3%) is achieved using a FAST-SURF feature detector and descriptor combination for a firearms detection task. Our results indicate comparative levels of performance for BoVW based approaches for this task over extensive variations in feature detector, feature descriptor, vocabulary size and final classification approach. We further demonstrate a by-product of such approaches in using feature point density as a simple measure of image complexity available as an integral part of the overall classification pipeline. The performance achieved characterises the potential for BoVW based approaches for threat object detection within the future automation of X-ray security screening against other contemporary approaches in the field

Not by transmission alone: the role of invention in cultural evolution

Innovation—the combination of invention and social learning—can empower species to invade new niches via cultural adaptation. Social learning has typically been regarded as the fundamental driver for the emergence of traditions and thus culture. Consequently, invention has been relatively understudied outside the human lineage—despite being the source of new traditions. This neglect leaves basic questions unanswered: what factors promote the creation of new ideas and practices? What affects their spread or loss? We critically review the existing literature, focusing on four levels of investigation: traits (what sorts of behaviours are easiest to invent?), individuals (what factors make some individuals more likely to be inventors?), ecological contexts (what aspects of the environment make invention or transmission more likely?), and populations (what features of relationships and societies promote the rise and spread of new inventions?). We aim to inspire new research by highlighting theoretical and empirical gaps in the study of innovation, focusing primarily on inventions in non-humans. Understanding the role of invention and innovation in the history of life requires a well-developed theoretical framework (which embraces cognitive processes) and a taxonomically broad, cross-species dataset that explicitly investigates inventions and their transmission. We outline such an agenda here. This article is part of the theme issue ‘Foundations of cultural evolution’

Area Invariance of Apparent Horizons under Arbitrary Boosts

It is a well known analytic result in general relativity that the 2-dimensional area of the apparent horizon of a black hole remains invariant regardless of the motion of the observer, and in fact is independent of the $t=constant$ slice, which can be quite arbitrary in general relativity. Nonetheless the explicit computation of horizon area is often substantially more difficult in some frames (complicated by the coordinate form of the metric), than in other frames. Here we give an explicit demonstration for very restricted metric forms of (Schwarzschild and Kerr) vacuum black holes. In the Kerr-Schild coordinate expression for these spacetimes they have an explicit Lorentz-invariant form. We consider {\it boosted} versions with the black hole moving through the coordinate system. Since these are stationary black hole spacetimes, the apparent horizons are two dimensional cross sections of their event horizons, so we compute the areas of apparent horizons in the boosted space with (boosted) $t = constant$, and obtain the same result as in the unboosted case. Note that while the invariance of area is generic, we deal only with black holes in the Kerr-Schild form, and consider only one particularly simple change of slicing which amounts to a boost. Even with these restrictions we find that the results illuminate the physics of the horizon as a null surface and provide a useful pedagogical tool. As far as we can determine, this is the first explicit calculation of this type demonstrating the area invariance of horizons. Further, these calculations are directly relevant to transformations that arise in computational representation of moving black holes. We present an application of this result to initial data for boosted black holes.Comment: 19 pages, 3 figures. Added a new section and 2 plots along with a coautho

Design and testing of disconnection actuators for enhancing safety and preventing failure escalation

The growing demand for reliability has led to an increased interest in developing effective disconnection systems for enhancing the safety of and preventing failure escalation in engineering systems. Considering this prospect, the design optimization of two disconnection actuators composed of a coaxial magnetic coupling linked to an electromagnetic device is presented and discussed. The disconnection actuator delivers a contactless torque transmission through the coaxial magnetic coupling, whereas the torque transfer is interrupted by the electromagnetic device in case a failure is detected via a dedicated algorithm. The performed design procedure relies on 2D finite element analysis, and trade-off studies are carried out to achieve an optimized geometry of an electromagnetic device. Finally, two disconnection actuators, for high-speed and high-torque applications, are prototyped and tested, with the aim of evaluating their disconnection capability. For both disconnection actuators, the developed force and voltage–current characteristics are measured along with the disconnection time

Use of biochemical and protein profiles of seminal plasma to prediction of semen quality and fertility in stallions

The identification of various substances in seminal plasma has opened the way to study their functionality. It was aimed to identify the electrophoretic protein profile (EPP) and biochemical parameters (BP) of seminal plasma (SP) as predictors of semen quality and fertility in stallion. Forty-six ejaculates from 7 fertile stallions, aged between 6-26 years, were collected from May to July and 117 mares were used to obtain fertility data. For each ejaculate, volume, sperm motility, concentration were determined and seminal plasma samples were collected to perform one-dimensional electrophoresis and biochemical profiling. Following the estrus detection, mares were inseminated with fresh sperm. Pregnancy rates and foal rates were recorded. The concentration of 15-18 kDa molecular weight (MW) proteins has shown a positive correlation with sperm concentration and foal rate. Besides, a strong positive correlation was found between sperm concentration and 23-28 kDa MW proteins (r=0.77). The volume of 19-22 kDa MW proteins was negatively correlated with pregnancy and foal rate. Similarly, the volume of high MW proteins (173-385 kDa) correlated negatively with sperm motility and foal rate. Apart from the protein profile, while Magnesium and Glucose levels were negatively correlated with sperm quality and foal rate, Cholesterol level was a positive indicator of the quality of semen as well as the foaling rate. Moreover, the total protein level was correlated negatively with the sperm concentration whereas triglyceride was correlated positively. In conclusion, EPP and BP of seminal plasma are valuable clinical tools as predictors of fertility and semen quality in the stallion.Fil: Stelletta, C.. Università di Padova; ItaliaFil: Alberti, S.. Università di Padova; ItaliaFil: Cil, B.. Ankara University; TurquíaFil: Tekin, K.. Ankara University; TurquíaFil: Tirpan, M. B.. Ankara University; TurquíaFil: Argañaraz, Martin Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Akcay, E.. Ankara University; TurquíaFil: Daskin, A.. Ankara University; Turquí

Concept and Demonstration of a Coaxial Magnetic Coupling with Electromagnetic Disconnection for Aircraft Permanent Magnet Generators

The application of more electrified systems in aircraft is required to achieve the target of a more sustainable aviation industry. This in turn relies on the development of new electro-mechanical devices to ensure reliability of critical aircraft functions during flight. The aim of this work is to develop and test a device capable of protecting permanent magnet generators from damage, thus enabling the practical use of such high power density generators in aircraft while eliminating their inherent vulnerability to sustained electrical faults. A novel electromechanical actuator concept for decoupling a permanent magnetic generator from an aircraft gas turbine engine is introduced and experimentally validated. The proposed concept combines a coaxial magnetic coupling with an electromagnetic actuator, allowing for rapid disconnection in case of electrical fault detection. The 2D finite element magnetic analysis methodology employed in the design of the magnetic coupling and electromagnetic actuator is validated with experiments that reveal the peak torque results of the magnetic coupling are accurate to within a 2.5% error and the actuator can produce the 450 N pull force required for disconnection. The device is capable of operating at a maximum speed of 12,000 RPM and transmitting a load of 32 Nm

Estimating the profitability of hydropower investments with a case study from Turkey

Energy demand has been increasing, but traditional sources of energy are depletable. New investments are needed in renewable energy production. Hydroelectric power plants are often considered a feasible renewable source of energy and are often organized as a public private partnerships (PPP). However, risk factors stemming from the macro environment as well as project conditions should be considered in performing feasibility studies. The objective of this study was to develop a method that can be used to predict the profitability of hydropower investments considering the relevant risk factors. To that end, a cash flow that represents the construction and operation period is set up, the risk fac­tors involved in such projects are identified, the impacts of these risk factors on the cash flow parameters are assessed, and Monte Carlo simulation is performed to estimate the net present value (NPV) of a hydropower investment. The proposed method was tested in a hydropower investment located in Turkey and generated credible results that could be of great benefit to potential investors operating in similar conditions. The primary contribution of this research is the creation of a method that allows investors to assess the profitability of a hydropower investment by using a stochastic approach

Negotiating the selling price of hydropower energy using multi-agent systems in BOT

During the feasibility study of BOT (Build-Operate-Transfer) hydropower investments, the selling price of energy is the most critical parameter that impacts the net present value (NPV) estimated by the investors. Investors usually consider the price of energy guaranteed by the government during their feasibility studies which is the worst case scenario. However, it is apparent that negotiations that take place between investor and broker determine the price of energy which is affected by various sources of uncertainty associated with the energy demand and country conditions. The objective of this study was to make a realistic estimate of the investor’s selling price by modeling the negotiation process between investor and broker using a multi-agent system (MAS). Thus, the factors affecting the negotiation process were identified, a negotiation protocol between the parties was set up, negotiation scenarios were determined, and modelled by using a MAS. The model was tested on a hydropower investment in Turkey and generated more realistic results compared to the current practice. Investors and brokers may benefit from this study because it considers the potential changes in the market as well as the negotiating postures of parties under different scenarios