5916 research outputs found
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Externalising externalisation and bad governance of migration in the EU: Turkey learning from Europe
No full textWhile the European Union (EU) might not do likewise, Fortress Europe is definitely enlarging. Reports (see, for example, Akkerman 2018) underline the momentous growth in Europe's border externalisation policies using various new instruments such as the EU Emergency Trust Fund for Africa (EUTF), the Migration Partnership Framework, and the Refugee Facility for Turkey, where the EU and individual member states are offering millions of euros for different projects to prevent migration of people (including those who are in need of international protection) to Europe. There is an increasing body of literature on the EU's externalisation policies in relation to Turkey, focusing on the effects of the March 2016 Turkey-EU statement, resulting FRIT, etc. Here, Turkey will be positioned from a different perspective. While serving as a platform for such projects, Turkey is also a firm apprentice of its own externalisation. Thus, this paper will concentrate on Turkey's efforts to externalise, its learning process from Europe, and will argue that externalisation is an example of the promotion of bad governance by the EU at the expense of democratic values
Modulating retroreflector based free space optical link for UAV-to-ground communications
No full textWeight reduction and low power consumption are key requirements in the next generation of unmanned aerial vehicle (UAV) networks. Employing modulating retro-reflector (MRR)-based free space optical (FSO) technology is an innovative technique for UAV-to-ground communication in order to reduce the payload weight and power consumption of UAVs which leads to increased maneuverability and flight time of UAV. In this paper, we consider an MRR-based FSO system for UAV-to-ground communication. We will show that the performance of the considered system is very sensitive to tracking errors. Therefore, to assess the benefits of MRR-based UAV deployment for FSO communications, the MRR-based UAV FSO channel is characterized by taking into account tracking system errors along with UAV's orientation fluctuations, link length, UAV's height, optical beam divergence angle, effective area of MRR, atmospheric turbulence and optical channel loss in the double-pass channels. To enable effective performance analysis, tractable and closed-form expressions are derived for probability density function of end-to-end signal to noise ratio, outage probability and bit error rate of the considered system under both weak-to-moderate and moderate-to-strong atmospheric turbulence conditions. The accuracy of the analytical expressions is verified by extensive simulations. Analytical results are then used to study the relationship between the optimal system design and tracking system errors
Energy aware trajectory optimization of solar powered AUVs for optical underwater sensor networks
No full textVisible light communication (VLC) provides an alternative underwater wireless connectivity solution with its low latency and high data rates albeit at relatively shorter distances in the order of tens of meters. In the context of underwater sensor networks (USNs), VLC is particularly suitable to establish connectivity between 'data mule' autonomous underwater vehicles (AUVs) and sensor nodes since communications is enabled only when the sensor node and mule AUV are in close proximity. In this paper, we consider a USN scenario where a solar-powered AUV gathers data from the sensor nodes using VLC signaling. We formulate a three-dimensional trajectory optimization for solar-powered AUVs with the goal of maximizing the harvested energy under constraints imposed by the data transmission. The optimization constraints include the minimum required data transfer rate, therefore a corresponding transmission distance, between the sensors and the AUV. We formulate the problem as a bilevel optimization problem. The lower-level objective function is in the form of traveling salesman problem which determines the optimum sequence order of the sensor nodes to be visited while the upper-level objective function is the optimization of the trajectory between each pair of adjacent nodes for the given order of node visits. Our numerical results demonstrate that the proposed trajectory significantly prolongs the mission time and autonomous operation of the AUV without the need to return to home base. Furthermore, since the proposed trajectory optimization is reactive to ocean currents, it brings reductions in the energy consumption of the AUVs
Measurement based non-line-of-sight vehicular visible light communication channel characterization
No full textVehicular visible light communication (V-VLC) aims to provide secure complementary vehicle-to-everything-communications (V2X) to increase road safety and traffic efficiency. V-VLC provides directional transmissions, mainly enabling line-of-sight (LoS) communications. However, reflections due to nearby objects enable non-line-of-sight (NLoS) transmissions, extending the usage scenarios beyond LoS. In this paper, we propose wide-band measurement based NLoS channel characterization, and evaluate the performance of direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) V-VLC scheme for NLoS channel. We propose a distance based NLoS V-VLC channel path loss model considering reflection surface characteristics and NLoS V-VLC channel impulse response (CIR) incorporating the temporal broadening effect due to vehicle reflections through weighted double gamma function. The proposed path loss model yields higher accuracy up to 14 dB when compared to single order reflection model whereas CIR model estimates the full width at half maximum up to 2 ns accuracy. We further demonstrate that the target bit-error-rate of can be achieved up to 7.86 m, 9.79 m, and 17.62 m distances for black, orange and white vehicle reflection induced measured NLoS V-VLC channels for DCO-OFDM transmissions
High-level features for resource economy and fast learning in skill transfer
No full textAbstraction is an important aspect of intelligence which enables agents to construct robust representations for effective and efficient decision making. Although, deep neural networks are proven to be effective learning systems due to their ability to form increasingly complex abstractions at successive layers these abstractions are mostly distributed over many neurons, making the re-use of a learned skill costly and blind to the insights that can be obtained on the emergent representations. For avoiding designer bias and unsparing resource use, we propose to exploit neural response dynamics to form compact representations to use in skill transfer. For this, we consider two competing methods based on (1) maximum information compression principle and (2) the notion that abstract events tend to generate slowly changing signals, and apply them to the neural signals generated during task execution. To be concrete, in our simulation experiments, we either apply principal component analysis (PCA) or slow feature analysis (SFA) on the signals collected from the last hidden layer of a deep neural network while it performs a source task, and use these features for skill transfer in a new, target, task. We then compare the generalization and learning performance of these alternatives with the baselines of skill transfer with full layer output and no-transfer settings. Our experimental results on a simulated tabletop robot arm navigation task show that units that are created with SFA are the most successful for skill transfer. SFA as well as PCA, incur less resources compared to usual skill transfer where full layer outputs are used in the new task learning, whereby many units formed show a localized response reflecting end-effector-obstacle-goal relations. Finally, SFA units with the lowest eigenvalues resemble symbolic representations that highly correlate with high-level features such as joint angles and end-effector position which might be thought of as precursors for fully symbolic systems.TÜBİTA
A cost-benefit analysis of sensor quality and spatial density for rapid regional post-event seismic damage assessment: Application to Istanbul
No full textA quantitative evaluation of the influence of sensor quality and spatial density on the results of rapid regional seismic damage evaluations of buildings can provide an important reference for the deployment of a strong-motion network. However, the influence of sensor quality and spatial density on seismic damage assessment is still unclear. Therefore, a cost-benefit analysis framework of sensor quality and spatial density for rapid regional post-event seismic damage assessment is proposed. In this framework, a simulation method for sensor-recorded ground motions and an interpolation-based ground motion field refinement method are used to consider the influence of the quality and density of the sensor network. The accuracies of seismic damage assessments with different sensor layout schemes were compared using the time-history analysis-based regional seismic damage assessment method, through which the influence of sensor quality and spatial density on the seismic damage assessment can be quantitatively evaluated. Finally, the Zeytinburnu district of Istanbul was selected as an example for illustrating the proposed framework. The main conclusions are as follows: (1) the spatial density of the sensors used is more significant for improving the accuracy of a seismic damage assessment than the quality of the sensors used; (2) the influence of population density can be considered using the proposed framework; and (3) the proposed framework can quantitatively consider the influence of sensor quality and spatial density on the rapid regional seismic damage assessment of buildings, which provides an important reference for the deployment of a strong-motion network for a given budget.National Key R D Program ; Beijing Natural Science Foundation ; Tencent Foundation ; Shuimu Tsinghua Scholar Program ; TÜBİTA
Measurement of the Higgs boson width and evidence of its off-shell contributions to ZZ production
No full textSince the discovery of the Higgs boson in 2012, detailed studies of its properties have been ongoing. Besides its mass, its width—related to its lifetime—is an important parameter. One way to determine this quantity is to measure its off-shell production, where the Higgs boson mass is far away from its nominal value, and relating it to its on-shell production, where the mass is close to the nominal value. Here we report evidence for such off-shell contributions to the production cross-section of two Z bosons with data from the CMS experiment at the CERN Large Hadron Collider. We constrain the total rate of the off-shell Higgs boson contribution beyond the Z boson pair production threshold, relative to its standard model expectation, to the interval [0.0061, 2.0] at the 95% confidence level. The scenario with no off-shell contribution is excluded at a p-value of 0.0003 (3.6 standard deviations). We measure the width of the Higgs boson as ΓH=3.2−1.7+2.4MeV, in agreement with the standard model expectation of 4.1 MeV. In addition, we set constraints on anomalous Higgs boson couplings to W and Z boson pairs.BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); MoER, ERC PUT and ERDF (Estonia); Academy of Finland, MEC and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG and HGF (Germany); GSRI (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and NRC KI (Russia); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (United States). Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant under contracts nos. 675440, 724704, 752730, 758316, 765710, 824093, 884104 and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the `Excellence of Science-EOS' -be.h project no. 30820817; the Beijing Municipal Science & Technology Commission, no. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy-EXC 2121 `Quantum Universe'-390833306, and under project no. 400140256-GRK2497; the Lendulet (`Momentum') Program and the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program UNKP, NKFIA research grants 123842, 123959, 124845, 124850, 125105, 128713, 128786 and 129058 (Hungary); the Council of Science and Industrial Research (India); the Latvian Council of Science; the Ministry of Science and Higher Education and the National Science Center, contracts Opus 2014/15/B/ST2/03998 and 2015/19/B/ST2/02861 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant no. CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; the Ministry of Science and Higher Education (projects nos. 0723-2020-0041 and FSWW-20200008) (Russia); MCIN/AEI/10.13039/501100011033, ERDF `a way of making Europe', and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant no.
MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Stavros Niarchos Foundation (Greece); the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract no. C-1845; and the Weston Havens Foundation (United States).Publisher versio
A teaching methodology on the combination of architectural tradition and parametric design: A case study with birdhouses
No full textBirdhouses were produced in Anatolia from the thirteenth century to the nineteenth century, each with period-specific features. The Industrial Revolution’s call for efficiency however, mandated that birdhouses were no longer manufactured. In this study, parametric design, which is based on an algorithmic design, is used to re-implement the lost practice of birdhouse construction. In the defined methodology, deployed in an undergraduate architectural course, this study considers all stages, from the design process through to the digital fabrication process, that occurs during the birdhouse design process based on metaball geometry created in visual programming language. I will present the problems encountered by the students and the solutions to these problems. In addition, I will evaluate the students’ attitude and response toward the teaching methodology statistically with SPSS Statistics (Statistical Product and Service Solutions).Publisher versio
Early teacher–child relationships promote self-regulation development in prekindergarten
No full textChildren’s experiences during the prekindergarten period are critical for shaping their emerging self-regulation skills. The purpose of this study was to examine the contribution of teacher–child relationship quality to children’s performance on a self-regulation task at the end of prekindergarten. Teachers rated the conflict, closeness, and dependency in their relationships with 104 children in the fall of prekindergarten, and children’s self-regulation was independently measured with a visual attention task in the spring of prekindergarten. In addition, teachers and parents rated children’s temperamental self-regulation (i.e., effortful control). Results indicate that greater teacher–child dependency predicted children’s longer time on the visual attention task, and greater teacher–child closeness predicted children’s lower accuracy on the visual attention task. In addition, children who were rated as more self-regulated by parents were more accurate on the visual attention task. The implications of the results are discussed.Research Council of the University of Nebraska-LincolnPublisher versio
Multimodal reinforcement learning for partner specific adaptation in robot-multi-robot interaction
No full textSuccessful and efficient teamwork requires knowledge of the individual team members' expertise. Such knowledge is typically acquired in social interaction and forms the basis for socially intelligent, partner-Adapted behavior. This study aims to implement this ability in teams of multiple humanoid robots. To this end, a humanoid robot, Nao, interacted with three Pepper robots to perform a sequential audio-visual pattern recall task that required integrating multimodal information. Nao outsourced its decisions (i.e., action selections) to its robot partners to perform the task efficiently in terms of neural computational cost by applying reinforcement learning. During the interaction, Nao learned its partners' specific expertise, which allowed Nao to turn for guidance to the partner who has the expertise corresponding to the current task state. The cognitive processing of Nao included a multimodal auto-Associative memory that allowed the determination of the cost of perceptual processing (i.e., cognitive load) when processing audio-visual stimuli. In turn, the processing cost is converted into a reward signal by an internal reward generation module. In this setting, the learner robot Nao aims to minimize cognitive load by turning to the partner whose expertise corresponds to a given task state. Overall, the results indicate that the learner robot discovers the expertise of partners and exploits this information to execute its task with low neural computational cost or cognitive load.Deutsche Forschungsgemeinschaft ; Japan Society for the Promotion of Science ; Osaka Universit