5916 research outputs found
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ANAC 2017: Repeated multilateral negotiation league
No full textThe Automated Negotiating Agents Competition (ANAC) is annually organized competition to facilitate the research on automated negotiation. This paper presents the ANAC 2017 Repeated Multilateral Negotiation League. As human negotiators do, agents are supposed to learn from their previous negotiations and improve their negotiation skills over time. Especially, when they negotiate with the same opponent on the same domain, they can adopt their negotiation strategy according to their past experiences. They can adjust their acceptance threshold or bidding strategy accordingly. In ANAC 2017, participants aimed to develop such a negotiating agent. Accordingly, this paper describes the competition settings and results with a brief description of the winner negotiation strategies.Nederlandse Organisatie voor Wetenschappelijk Onderzoe
Aid allocation for camp-based and urban refugees with uncertain demand and replenishments
No full textThere are 26 million refugees worldwide seeking safety from persecution, violence, conflict, and human rights violations. Camp-based refugees are those that seek shelter in refugee camps, whereas urban refugees inhabit nearby, surrounding populations. The systems that supply aid to refugee camps may suffer from ineffective distribution due to challenges in administration, demand uncertainty and volatility in funding. Aid allocation should be carried out in a manner that properly balances the need of ensuring sufficient aid for camp-based refugees, with the ability to share excess inventory, when available, with urban refugees that at times seek nearby camp-based aid. We develop an inventory management policy to govern a camp's sharing of aid with urban refugee populations in the midst of uncertainties related to camp-based and urban demands, and replenishment cycles due to funding issues. We use the policy to construct costs associated with: (i) referring urban populations elsewhere, (ii) depriving camp-based refugee populations, and (iii) holding excess inventory in the refugee camp system. We then seek to allocate aid in a manner that minimizes the expected overall cost to the system. We propose two approaches to solve the resulting optimization problem, and conduct computational experiments on a real-world case study as well as on synthetic data. Our results are complemented by an extensive simulation study that reveals broad support for our optimal thresholds and allocations to generalize across varied key parameters and distributions. We conclude by presenting related discussions that reveal key managerial insights into humanitarian aid allocation under uncertainty
Campaign participation prediction with deep learning
No full textIncreasingly, on-demand nature of customer interactions put pressure on companies to build real-time campaign management systems. Instead of having managers to decide on the campaign rules, such as, when, how and whom to offer, creating intelligent campaign management systems that can automate such decisions is essential. In addition, regulations or company policies usually restrict the number of accesses to the customers. Efficient learning of customer behaviour through dynamic campaign participation observations becomes a crucial feature that may ultimately define customer satisfaction and retention. This paper builds on the recent successes of deep learning techniques and proposes a classification model to predict customer responses for campaigns. Classic deep neural networks are good at learning hidden relations within data (i.e., patterns) but with limited capability for memorization. One solution to increase memorization is to use manually craft features, as in Wide & Deep networks, which are originally proposed for Google Play App. recommendations. We advocate using decision trees as an easier way of mining high-level relationships for enhancing Wide & Deep networks. Such an approach has the added benefit of beating manually created rules, which, most of the time, use incomplete data and have biases. A set of comprehensive experiments on campaign participation data from a leading GSM provider shows that automatically crafted features make a significant increase in the accuracy and outperform Deep and Wide & Deep models with manually crafted features
A wideband smart EMF detector for mobile devices
No full textA wideband electromagnetic field (EMF) sensor system is introduced in this study. This small form factor, low-cost system is intended for use with smart mobile devices and can precisely measure the imminent field strength through the combination of a wideband omnidirectional receive antenna, RF, and audio mixing front-end as well as signal processing algorithm in the mobile unit. A detection dynamic range of 30 dB is shifted toward the high-field intensity regimes to enable its use as a hazardous EM field detector. The total diameter of the device was 13 cm with a cylindrical thickness of 1.6 mm (standard FR4), and it can interface with the audio port of any mobile device including cell-phones or tablets. Field strengths in the range of 5 V/m–50 V/m can be detected in approximately by 10 MHz–3 GHz RF transmission bands
UAV-assisted free space optical communication system with amplify-and-forward relaying
No full textIn this paper, the performance of an unmanned aerial vehicle (UAV)-based free-space optical relay system with amplify-and-forward relaying is analyzed. In particular, the statistical probability of end-to-end signal-to-noise ratio at the destination is obtained under a general condition that takes into account the effects of nonzero boresight pointing errors along with the effects of orientation and position fluctuations of the UAV relay, the UAV position with respect to the source and destination nodes, the optical beamwidth, turbulence strength of both source-to-relay and the relay-to-destination links. Subsequently, the closed-form expressions are derived for the bit-error rate and outage probability of the considered system. The accuracy of the analytical expressions is verified by performing extensive simulations. Analytical results are then utilized to study of the relationship between the optimal system parameters design and UAV's position in the sky. The results show that the optimal UAV's position that achieves a minimum outage probability highly depends on the optical beamwidth at the destination. Moreover, to achieve a minimum outage probability, the relay-to-destination link length must be shorter than source-to-destination (SR) link and by deceasing beamwidth at the destination, the optimal value for SR link length increases.TÜBİTA
Mechanical behavior of constrained groove pressed stainless steel and pure zinc
No full textConstrained groove pressing (CGP), a severe plastic deformation method, has been implemented on AISI 304 and commercially pure zinc samples in the present work. Four CGP passes were successfully applied to both materials providing a remarkable improvement in both strength and hardness values, despite reduced ductility. Average grain size values were diminished by around 45% for 304 stainless steel and 47% for commercially pure zinc. The highest levels of strengthening due to severe deformation were displayed after the initial passes for both materials. CGP was shown to be a viable method for strengthening based on deformation processing, whereby similar trends in microstructure and mechanical behavior were observed for both crystal structures
Parenting styles and Turkish children’s emotion regulation: The mediating role of parent-teacher relationships
No full textThe current study examined the contributions of parenting styles (inductive reasoning and punishment) and parent-teacher relationships to Turkish preschool children’s emotion regulation, with a specific focus on the mediating role of parent-teacher relationship between parenting styles and children’s emotion regulation. A total of 140 preschoolers (59 girls), their parents and teachers were recruited for the current study. Children’s age ranged from 39 to 77 months (M = 62.56, SD = 8.52). All teachers (n = 10) were female and working at a state-funded school. Mothers reported on their parenting styles and teachers reported on parent-teacher relationship and children’s emotion regulation. Results from regression analysis showed that parents’ inductive reasoning was positively associated with children’s emotion regulation and parent-teacher relationship. Higher parent-teacher relationship was positively associated with higher levels of children’s emotion regulation. In addition, parent-teacher relationship mediated the association between inductive parenting and emotion regulation of children. Limitations and future directions of the current study are discussed
Combined searches for the production of supersymmetric top quark partners in proton–proton collisions at √s = 13 TeV
No full textA combination of searches for top squark pair production using proton–proton collision data at a center-of-mass energy of 13Te at the CERN LHC, corresponding to an integrated luminosity of 137fb-1 collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on the model, the combined result excludes a top squark mass up to 1325Ge for a massless neutralino, and a neutralino mass up to 700Ge for a top squark mass of 1150Ge. Top squarks with masses from 145 to 295Ge, for neutralino masses from 0 to 100Ge, with a mass difference between the top squark and the neutralino in a window of 30Ge around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420Ge.BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (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); GSRT (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 UASLPFAI (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); SEIDI, CPAN, PCTI, and FEDER (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 (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 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 doorWetenschap en Technologie (IWTBelgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science -EOS" -be.h project n. 30820817; the Beijing Municipal Science& Technology Commission, No. Z191100007219010; theMin-istry of Education, Youth and Sports (MEYS) of the Czech Republic; theDeutsche Forschungsgemeinschaft (DFG), underGermany's Excellence Strategy -EXC 2121 "Quantum Universe" -390833306, and under project number 400140256 -GRK2497; the Lendulet ("Momentum") Program and the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program UNKP, the 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 National Priorities Research Program by Qatar National Research Fund; the Ministry of Science and Higher Education, project no.
0723-2020-0041 (Russia); the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; 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 C-1845; and the Weston Havens Foundation (USA).Publisher versio
Supplier selection and order allocation in the presence of suppliers with exact annual capacity
No full textIn this paper, we focus on the supplier selection and order quantity allocation for a single retailer. The retailer orders a product from multiple suppliers with capacities, adds value to the product and fulfils the demand while meeting the minimum quality level. There is a distinct difference between our work and the prior works in the literature in that we assume the (annual) capacities of the suppliers to be exact annual capacities, i.e., the total order amount in a given calendar/fiscal year from a supplier must be less than or equal to its capacity. First, we discuss the implications of this exact annual capacity assumption on the ordering policy of the retailer. Next, to determine an ordering policy, we propose a heuristic algorithm using a novel idea of iteratively updating the annual ordering cost estimates. We demonstrate the efficacy of the proposed algorithm on randomly generated instances