Assessing an automated tool to quantify variation in movement and location: a case study of American Sign Language and Ghanaian Sign Language

Signs in sign languages have been mainly analyzed as composed of three formational elements: hand configuration, location, and move- ment. Researchers compare and contrast lexical differences and simi- larities among different signs and languages based on these formal elements. Such measurement requires extensive manual annotation of each feature based on a predefined process and can be time con- suming because it is based on abstract representations that usually do not take into account the individual traits of different signers. This study showcases a newly developed tool named DistSign, used here to measure and visualize variation based on the wrist trajectory in the lexica of two sign languages, namely American Sign Language (ASL) and Ghanaian Sign Language (GSL), which are assumed to be historically related (Edward 2014). The tool utilizes the pretrained pose estimation framework OpenPose to track the body joints of different signers. Subsequently, the Dynamic Time Warping (DTW) algorithm, which measures the similarity between two temporal sequences, is used to quantify variation in the paths of the dominant hand’s wrist across signs. This enables one to efficiently identify cognates across languages, as well as false cognates. The results show that the DistSign tool can recognize cognates with a 60 percent accuracy, using a semiautomated method that utilizes the Levenshtein distance metric as a baseline.Descriptive and Comparative Linguistic

Poly-chlorinated biphenyls (PCB) in European sea bass from different rearing systems

The chemical composition and the level of seven indicator congeners of PCB (BZ/IUPAC no. 28, 52, 101, 118, 138, 153, and 180) were determined in 133 specimens of farm-raised European sea bass (Dicentrarchus labrax). The fish were caught from different aquaculture rearing systems: extensive fish valley, semi-intensive ponds, sea-cages, and intensive concrete tanks. Fresh fillet chemical composition differed among the rearing systems (fat: 2.9, 7.5, 7.1, and 9.4%; P<0.001). Total concentrations of indicator congeners were below the EU limit (200ng/g fat) for meat, poultry and eggs, being the lowest in extensively-reared sea bass (75ng/g fat), intermediate in sea bass from semi-intensive ponds (119) and sea cages (116), and the highest in intensively-reared fish (133) (P<0.001). Similarly, PCB concentrations in fresh fillets were 2,438, 10,116, 8,491, and 12,952pg/g in the four systems (P<0.001). The congener 153 was the most represented in all rearing systems. TEQ concentrations for the dioxin-like congener no. 118 were 50 to 200 times lower than the maximum admitted value. Total concentration of indicator congeners of PCB was poorly correlated with fish slaughter weight (R2=0.17), while highly correlated with fat concentration of fish (R2=0.75)

A research and development investment strategy to achieve the Paris climate agreement

Climate stabilization requires the deployment of several low-carbon options, some of which are still not available at large scale or are too costly. Governments will have to make important decisions on how to incentivize Research and Development (R&D). Yet, current assessments of climate neutrality typically do not include research-driven innovation. Here, we link two integrated assessment models to study R&D investment pathways consistent with climate stabilization and suggest a consistent financing scheme. We focus on five low-carbon technologies and on energy efficiency measures. We find that timely R&D investment in these technologies lowers mitigation costs and induces positive employment effects. Achieving 2 °C (1.5 °C) requires a global 18% (64%) increase in cumulative low-carbon R&D investment relative to the reference scenario by mid-century. We show that carbon revenues are sufficient to both finance the additional R&D investment requirements and generate economic benefits by reducing distortionary taxation, such as payroll taxes, thus enhancing job creation

Sign and search: sign search functionality for sign language lexica

Sign language lexica are a useful resource for researchers and people learning sign languages. Current implementations allow a user to search a sign either by its gloss or by selecting its primary features such as handshape and location. This study focuses on exploring a reverse search functionality where a user can sign a query sign in front of a webcam and retrieve a set of matching signs. By extracting different body joints combinations (upper body, dominant hand's arm and wrist) using the pose estimation framework OpenPose, we compare four techniques (PCA, UMAP, DTW and Euclidean distance) as distance metrics between 20 query signs, each performed by eight participants on a 1200 sign lexicon. The results show that UMAP and DTW can predict a matching sign with an 80\% and 71\% accuracy respectively at the top-20 retrieved signs using the movement of the dominant hand arm. Using DTW and adding more sign instances from other participants in the lexicon, the accuracy can be raised to 90\% at the top-10 ranking. Our results suggest that our methodology can be used with no training in any sign language lexicon regardless of its size.Computer Systems, Imagery and Medi

Sign and search: sign search functionality for sign language lexica

Sign language lexica are a useful resource for researchers and people learning sign languages. Current implementations allow a user to search a sign either by its gloss or by selecting its primary features such as handshape and location. This study focuses on exploring a reverse search functionality where a user can sign a query sign in front of a webcam and retrieve a set of matching signs. By extracting different body joints combinations (upper body, dominant hand's arm and wrist) using the pose estimation framework OpenPose, we compare four techniques (PCA, UMAP, DTW and Euclidean distance) as distance metrics between 20 query signs, each performed by eight participants on a 1200 sign lexicon. The results show that UMAP and DTW can predict a matching sign with an 80\% and 71\% accuracy respectively at the top-20 retrieved signs using the movement of the dominant hand arm. Using DTW and adding more sign instances from other participants in the lexicon, the accuracy can be raised to 90\% at the top-10 ranking. Our results suggest that our methodology can be used with no training in any sign language lexicon regardless of its size.Computer Systems, Imagery and Medi

Design and performance evaluation of a lightweight wireless early warning intrusion detection prototype

The proliferation of wireless networks has been remarkable during the last decade. The license-free nature of the ISM band along with the rapid proliferation of the Wi-Fi-enabled devices, especially the smart phones, has substantially increased the demand for broadband wireless access. However, due to their open nature, wireless networks are susceptible to a number of attacks. In this work, we present anomaly-based intrusion detection algorithms for the detection of three types of attacks: (i) attacks performed on the same channel legitimate clients use for communication, (ii) attacks on neighbouring channels, and (iii) severe attacks that completely block network's operation. Our detection algorithms are based on the cumulative sum change-point technique and they execute on a real lightweight prototype based on a limited resource mini-ITX node. The performance evaluation shows that even with limited hardware resources, the prototype can detect attacks with high detection rates and a few false alarms. © 2012 Fragkiadakis et al

Limited emission reductions from fuel subsidy removal except in energy exporting regions

Hopes are high that removing fossil fuel subsidies could help to mitigate climate change by discouraging inefficient energy consumption and levelling the playing field for renewables1–3. In September 2016, the G20 countries re-affirmed their 2009 commitment (at the G20 Leaders’ Summit) to phase out fossil fuel subsidies4,5 and many national governments are using today’s low oil prices as an opportunity to do so6–9. In practical terms, this means abandoning policies that decrease the price of fossil fuels and electricity generated from fossil fuels to below normal market prices10,11. However, whether the removal of subsidies, even if implemented worldwide, would have a large impact on climate change mitigation has not been systematically explored. Here we show that fossil fuel subsidy removal would have a small impact on global energy demand and carbon dioxide emissions and would not increase renewable energy use by 2030. Subsidy removal would reduce the carbon price necessary to stabilize greenhouse gas concentration at 550 parts per million by only 2–12 per cent under low oil prices. Removing subsidies in most regions would deliver smaller emission reductions than the Paris Agreement (2015) climate pledges and in some regions global subsidy removal may actually lead to an increase in emissions, owing to either coal replacing subsidized oil and natural gas or natural-gas use shifting from subsidizing, energy-exporting regions to non-subsidizing, importing regions. Our results show that subsidy removal would result in the largest CO2 emission reductions in oil- and gas-exporting regions, where reductions would exceed their climate pledges and where subsidy removal would also affect fewer people below the poverty line than in lower-income regions

Ubiquitous robust communications for emergency response using multi-operator heterogeneous networks

A number of disasters in various places of the planet have caused an extensive loss of lives, severe damages to properties and the environment, as well as a tremendous shock to the survivors. For relief and mitigation operations, emergency responders are immediately dispatched to the disaster areas. Ubiquitous and robust communications during the emergency response operations are of paramount importance. Nevertheless, various reports have highlighted that after many devastating events, the current technologies used, failed to support the mission critical communications, resulting in further loss of lives. Inefficiencies of the current communications used for emergency response include lack of technology inter-operability between different jurisdictions, and high vulnerability due to their centralized infrastructure. In this article, we propose a flexible network architecture that provides a common networking platform for heterogeneous multi-operator networks, for interoperation in case of emergencies. A wireless mesh network is the main part of the proposed architecture and this provides a back-up network in case of emergencies. We first describe the shortcomings and limitations of the current technologies, and then we address issues related to the applications and functionalities a future emergency response network should support. Furthermore, we describe the necessary requirements for a flexible, secure, robust, and QoS-aware emergency response multi-operator architecture, and then we suggest several schemes that can be adopted by our proposed architecture to meet those requirements. In addition, we suggest several methods for the re-tasking of communication means owned by independent individuals to provide support during emergencies. In order to investigate the feasibility of multimedia transmission over a wireless mesh network, we measured the performance of a video streaming application in a real wireless metropolitan multi-radio mesh network, showing that the mesh network can meet the requirements for high quality video transmissions