Policy Coherence and Coordination for Trade Facilitation: Integrated Border Management, Single-Windows and other Options for Developing Countries

There is now increasing recognition of the critical importance of trade facilitation to further international commerce, accelerate growth, and enhance welfare if not alleviate poverty among trading nations. But there is also increasing appreciation that it is not just attention to the barriers and bottlenecks behind-the-border that are involved in trade facilitation (TF), it also calls for coherence between policies and regulations at the border and inside the border. The unavoidable participation of many government agencies and private stakeholders in border transactions calls for coordination among them towards a harmonized approach to trade facilitation. This paper discusses the need and relevance of policy coherence and coordination to facilitate trade and to what extent some trade facilitation measures (concepts) such as integrated border management and single-windows may be applicable in developing countries to improve both policy coherence and coordination.Trade Faclitation, Border trade, Policy coherence, Economic Integration

Towards Additional Policies to Improve the Environmental Performance of Buildings

This report supports EU policymaking on sustainable consumption and production (SCP) in the area of buildings, which were indentified as being particularly relevant for environmental improvements. While the objective of SCP policies is to address all the different types of environmental impacts in a balanced way, previous research by the JRC-IPTS (IMPRO-Buildings study) has shown that the energy consumption during the use phase of the buildings is by far the most important factor to take into account for the life cycle environmental impacts of buildings. Moreover, residential buildings are responsible for 27 % of final energy demand in the EU. The report reviews the barriers towards energy efficiency and the measures to overcome. It then compiles an overview over existing and planned EU policy instruments dealing with the environmental and energy performance of buildings, building elements and equipment. Finally, barriers, available measures and policy instruments are assessed against each other to find out what more could be done and to assess if there are additional policies to the existing ones that could lead to further improvements.JRC.J.2-Competitiveness and Sustainabilit

Meta-learning for dynamic tuning of active learning on stream classification

Supervised data stream learning depends on the incoming sample's true label to update a classifier's model. In real life, obtaining the ground truth for each instance is a challenging process; it is highly costly and time consuming. Active Learning has already bridged this gap by finding a reduced set of instances to support the creation of a reliable stream classifier. However, identifying a reduced number of informative instances to support a suitable classifier update and drift adaptation is very tricky. To better adapt to concept drifts using a reduced number of samples, we propose an online tuning of the Uncertainty Sampling threshold using a meta-learning approach. Our approach exploits statistical meta-features from adaptive windows to meta-recommend a suitable threshold to address the trade-off between the number of labelling queries and high accuracy. Experiments exposed that the proposed approach provides the best trade-off between accuracy and query reduction by dynamic tuning the uncertainty threshold using lightweight meta-features

Experimental Demonstration of Quantum Fully Homomorphic Encryption with Application in a Two-Party Secure Protocol

A fully homomorphic encryption system hides data from unauthorized parties, while still allowing them to perform computations on the encrypted data. Aside from the straightforward benefit of allowing users to delegate computations to a more powerful server without revealing their inputs, a fully homomorphic cryptosystem can be used as a building block in the construction of a number of cryptographic functionalities. Designing such a scheme remained an open problem until 2009, decades after the idea was first conceived, and the past few years have seen the generalization of this functionality to the world of quantum machines. Quantum schemes prior to the one implemented here were able to replicate some features in particular use-cases often associated with homomorphic encryption but lacked other crucial properties, for example, relying on continual interaction to perform a computation or leaking information about the encrypted data. We present the first experimental realisation of a quantum fully homomorphic encryption scheme. We further present a toy two-party secure computation task enabled by our scheme. Finally, as part of our implementation, we also demonstrate a post-selective two-qubit linear optical controlled-phase gate with a much higher post-selection success probability (1/2) when compared to alternate implementations, e.g. with post-selective controlled-$Z$ or controlled-$X$ gates (1/9).Comment: 11 pages, 16 figures, 2 table

Expanding the UK Secure by Design proposal for a usable consumer-focused IoT security label

No person whom has any knowledge of security in the Internet of Things (IoT) would claim the current landscape is desirable, as exceedingly poor security of devices is routinely exhibited in an ecosystem experiencing exponential growth of devices. If these devices follow past trends in Cyber Security, it is not unreasonable to assume that without intervention another decade of exponentially growing costs attributed to Cyber Crime may lay ahead. After the failure of the voluntary approach to IoT Security, works are now being taken to legislate a minimum security standard.Building from existing proposals, this paper outlines real improvements that could be made to current ongoing works, with the intention of providing incentive for manufacturers to improve device security in the IoT sector and reduce the timeline for routine deployment of secured devices.Incorporating strategies developed in other industries, as well as security requirements from across international borders, a point-of-sale user focused label is proposed, which can be easily interpreted by non-technical users. Intending to provoke curiosity and fully reassure the end-user, a two-layer system is chosen which allows the conveyance of more detailed information than could fit on a physical label

Using Web Audio To Deliver Interactive Speech Tools In The Browser

In 2014, the number of web pages delivered to tablets and smartphones overtook the number delivered to laptop and desktop computers, with a majority of users saying they prefer these new portable platforms over conventional computers for many tasks. This shift in device use provides both opportunities and challenges for providers of speech analysis tools, phonetic demonstrations and language teaching aids. It is an opportunity because web standards mean we can make our applications available to a wide audience through a single consistent programming architecture rather than writing for one particular computing platform. It is a challenge because tablets and smartphones are less powerful, require different programming skills and have different limitations in terms of user interface. In this article, I will show how interactive applications in Phonetics and Speech Science can be written to run in web browsers on any computing platform. These are native web applications, written in HTML, CSS and JavaScript that can capture, replay, display, process, and analyze audio using the Web Audio API without needing any plugins. I will describe - and give the URLs of - some demonstration applications. I will discuss some future opportunities in the area of collaborative research and some remaining challenges that arise from incompatibilities across browsers. My audience is teachers and students with intermediate web programming skills wanting to build custom speech displays, perform custom speech analysis or run speech audio experiments over the web

Static malware detection using recurrent neural networks

Neustále rostoucí počty útoků škodlivých programů na naši IT infrastrukturu si žádají nové a lepší metody ochrany. V této bakalářské práci se věnujeme využití rekurentních neuronových sítí pro rychlou a přesnou detekci malwaru. Pro reprezentaci podezřelých programů jsme využili pouze data extrahovaná ze souborů v PE formátu. Tato data jsme dále použili pro trénink různých druhů rekurentních neuronových sítí. V práci představujeme speciální architekturu neuronové sítě, kombinující husté a LSTM vrstvy, ke klasifikaci PE souborů. Pracovali jsme s naším vlastním datasetem obsahující 30154 souborů stažených z dostupných zdrojů. S tímto datasetem, který je rovnoměrně rozdělen mezi čisté a škodlivé soubory, jsme dosáhli přesnosti 98,41 % s pouze 0,5 % legitimních programů mylně klasifikovaných jako malware. K těmto výsledkům nám stačilo pouhých 250 iterací přes treninkový soubor vzorků k naučení naší sítě. Výsledky dokazují, že algoritmy strojového učení, hlavně LSTM sítě, mohou být využity jako rychlý a spolehlivý nástroj pro detekci škodlivých souborů.An ever-growing number of malicious attacks on our IT infrastructure calls for new and better methods of protection. In this thesis, we focus on the use of recurrent neural networks as an agile and accurate way of detecting malware. We only used features extracted from files in the PE file format to represent the suspicious programs which we used to train various types of recurrent neural networks. In this work, we present unique neural network architecture combining dense and stacked LSTM layers to classify PE files. We worked with our dataset of 30,154 files collected from available resources with which we achieved an accuracy of 98.41%, while only 0.5% of benign samples were misclassified as malware on our balanced dataset. All this was accomplished with only 250 epochs of training. These results prove that machine-learning algorithms, especially LSTM networks, can be used as a quick and reliable tool for malware detection