5916 research outputs found
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At the unsettling limits of collaborative life writing: A memoir of an ethnography-memoir
No full textThis chapter uses a memoir to examine the limits of anthropological collaboration. I draw on 12 years of friendship and fieldwork that culminated in my writing an ethnographic life story of a German-Turkish return migrant (Leyla) and publishing it together with Leyla’s own original memoir. In recent years, anthropologists have rightly celebrated collaboration as the latest incarnation of engaged, public or activist anthropology. Yet, while reflecting on my collaborative project with Leyla and moving forward with further ones, I have found that collaboration is limited in ways that have not yet been fully explored. Researchers have tended to focus on barriers to collaboration stemming from unequal power dynamics, appropriation of an other’s story and the revealing of ethnographic secrets. In this chapter, I argue that important challenges for collaboration lie with the ethics of reciprocity in the ethnographic encounter and specifically with issues of authority, readership and publication goals; the limited training of anthropologists to engage in co-authorship; and the highly fraught nature of friendship itself under the pressures of late capitalism and professional academic anthropology
Conclusion
No full textThe findings of this in-depth case study provide insights for generalisations about how strategic temporality may operate in other refugee-hosting countries as well as specific findings about state responses to mass migration situations. Some key findings can be summarised as including a (1) complicated and fragmented legal system, (2) multiplicity of actors, (3) re-nationalisation and restrictiveness, (4) increased complexity and uncertainty in all layers of rules and practices, (5) consistent liminality experienced by refugees. These characteristics are observable in concrete policy practices in diverse sub-policy fields involving remote border controls, blocking reception, downgrading protection and slowing integration. As we showed, the concept of strategic temporality, along with its related components of liminality, uncertainty and complexity, is helpful for understanding state responses across time and sub-policy fields
Performance of the local reconstruction algorithms for the CMS hadron calorimeter with Run 2 data
No full textA description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015-2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared.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 n. 30820817; the Being Municipal Science& Technology Commission, No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy - EXC 2121 "Quantum Universe" - 390833306, and under project number 400140256 - GRK2497; the Hungarian Academy of Sciences, the New National Excellence Program - UNKP, the NKFIH research grants K 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; the National Research Foundation of Korea (NRF/MSIT) grant No. 2020R1C1C1005916 (Korea); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; 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 MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation, grant B05F650021 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.).Publisher versio
Generalization to unseen viewpoint images of objects via alleviated pose attentive capsule agreement
No full textDespite their achievements in object recognition, Convolutional Neural Networks (CNNs) particularly fail to generalize to unseen viewpoints of a learned object even with substantial samples. On the other hand, recently emerged capsule networks outperform CNNs in novel viewpoint generalization tasks even with significantly fewer parameters. Capsule networks group the neuron activations for representing higher level attributes and their interactions for achieving equivariance to visual transformations. However, capsule networks have a high computational cost for learning the interactions of capsules in consecutive layers via the, so called, routing algorithm. To address these issues, we propose a novel routing algorithm, Alleviated Pose Attentive Capsule Agreement (ALPACA) which is tailored for capsules that contain pose, feature and existence probability information together to enhance novel viewpoint generalization of capsules on 2D images. For this purpose, we have created a Novel ViewPoint Dataset (NVPD) a viewpoint-controlled texture-free dataset that has 8 different setups where training and test samples are formed by different viewpoints. In addition to NVPD, we have conducted experiments on iLab2M dataset where the dataset is split in terms of the object instances. Experimental results show that ALPACA outperforms its capsule network counterparts and state-of-the-art CNNs on iLab2M and NVPD datasets. Moreover, ALPACA is 10 times faster when compared to routing-based capsule networks. It also outperforms attention-based routing algorithms of the domain while keeping the inference and training times comparable. Lastly, our code, the NVPD dataset, test setups, and implemented models are freely available at https://github.com/Boazrciasn/ALPACA
Need for low latency: Media over QUIC
No full textThis paper overviews developing a low-latency solution for media ingest and distribution, the work undertaken by the IETF's new Media over QUIC (moq) working group. It summarizes the motivation, goals, current work and potential improvements
Banka örneğinde konut kredilerinde erken ödeme modellemesi
No full textHome loans are one of the longest-term products in the Banking sector and are exposed to multiple macroeconomic cycles throughout their maturity. Each home loan contract includes the right of the loan to pay at any time during the term of the loan which causes the risk of changes in the contractual cash flows of the Banks. When the literature for the Turkish market is analyzed, studies are done on calculating home loan option prices and most of the calculations are based on classical option techniques. In previous studies, market spot interest rate and house price levels are used as variables. Aside from other studies in the literature, this thesis is based on prepayment probability of the home loans. Borrower-specific, loan-specific and macro economic specific factors are chosen as the variables affecting prepayment probability. To analyze the cyclical effects, the study is carried out in one of the top 10 banks with asset sizes by selecting a 12-year data observation interval between 01.01.2010 and 31.12.2021. The study aims to model customer prepayment behavior by estimating a logistic regression using 694.778 fixed-rate home loans and 247.572 prepayment events. The data set has about 30 million observations where each home loan has monthly observations until each home loan is closed. The logistic regression model can accurately predict the prepayment behavior of contracts with an Area-under-the-Curve (AUC) statistic of 0.921 and Gini coefficient of 0.843. In studies investigating home loans out of Turkey, interest rate, borrower income, loan to value ratio, borrower age, loan age and region are the variables that affect prepayment in the loan portfolios. This thesis shows that the most effective variables in the prepayment behaviors are the interest rate level changes, reference market interest rates, current risk of home loan and customer total debt which affect home loans payment schedule. Interestingly, original and current Loan to Value ratio, loan maturity, loan age, customer age, customer education status and customer income have limited impact on the prepayments as indicated by the model. The most plausible for this observation is the fact that people in Turkey buy their houses for residential purposes, not for trade and do not sell their houses in a short time unless it is compulsory can be interpreted.Konut kredileri, Bankacılık sektörünün en uzun vadeli ürünlerinden biridir ve vadeleri boyunca birden fazla makroekonomik döngüye maruz kalmaktadır. Her konut kredisi sözleşmesi, kredinin vadesi boyunca herhangi bir zamanda ödeme hakkını içerir ve bu da Bankaların sözleşmeye bağlı nakit akışlarında değişiklik riskine neden olur. Türkiye piyasası ile ilgili literatür çalışmaları incelendiğinde konut kredisi opsiyon fiyatlarının hesaplanmasına yönelik çalışmalar yapılmaktadır ve hesaplamaların çoğu klasik opsiyon tekniklerine dayanmaktadır. Önceki çalışmalarda değişken olarak piyasa spot faiz oranı ve konut fiyat seviyeleri kullanılmıştır. Literatürdeki diğer çalışmaların yanı sıra bu tez, konut kredilerinin erken ödeme olasılığının hesaplanmasına dayanmaktadır. Erken ödeme olasılığını etkileyen değişkenler olarak borçluya özel, krediye özel ve makro ekonomik faktörler kredi düzeyinde seçilmiştir. Döngüsel etkilerin analiz edilebilmesi için, çalışma 01.01.2010-31.12.2021 tarihleri arasında 12 yıllık veri gözlem aralığı seçilerek Türkiye'de aktif büyüklüğe sahip ilk 10 bankadan birinde gerçekleştirilmiştir. Çalışma, 694.778 sabit faizli konut kredisi ve 247.572 erken ödeme olayı kullanılarak lojistik regresyon tahmin ederek müşteri erken ödeme davranışını modellemeyi amaçlamaktadır. Veri seti, her bir konut kredisinin her biri kapatılana kadar aylık gözlemlere sahip olduğu yaklaşık 30 milyon gözleme sahiptir. Lojistik regresyon modeli, Eğri Altında Kalan Alan (AUC) istatistiği 0,921 ve Gini katsayısı 0,843 ile kredilerin erken ödeme davranışını doğru bir şekilde tahmin edebilir. Türkiye dışında konut kredilerini araştıran çalışmalarda, kredi portföylerinde faiz oranı, borçlunun geliri, kredi teminat oranı, borçlunun yaşı, kredinin yaşı ve coğrafi bölgesi gibi değişkenler erken ödemeyi etkilemektedir. Bu tez, erken ödeme davranışlarında en etkili değişkenlerin konut kredisi ödeme planını etkileyen faiz oranı değişimlerinin, referans piyasa kredi faiz oranlarının, ev kredisinin güncel riskinin ve müşteri toplam borcunun olduğunu göstermektedir. İlginç bir şekilde, orijinal ve güncel kredi teminat oranı, kredi vadesi, kredi yaşı, müşteri yaşı, müşteri eğitim durumu ve müşteri geliri, modelde belirtildiği gibi erken ödemeler üzerinde sınırlı etkiye sahiptir. Bu gözlem için en makul olanı, Türkiye'de insanların evlerini ticaret amaçlı değil, ikamet amaçlı aldıkları ve zorunlu olmadıkça kısa sürede satmadıkları şeklinde yorumlanabilir
Piecewise-tunneled captive processes and corridored random particle systems
No full textWe introduce a family of processes that generalises captive diffusions, whereby the stochastic evolution that remains within a pair of time-dependent boundaries can further be piecewise-tunneled internally. The tunneling effect on the dynamics can be random such that the process has non-zero probability to find itself within any possible tunnel at any given time. We study some properties of these processes and apply them in modelling corridored random particles that can be observed in fluid dynamics and channeled systems. We construct and simulate mean-reverting piecewise-tunneled captive models for demonstration. We also propose a doubly-stochastic system in which the tunnels themselves are generated randomly by another stochastic process that jumps at random times.Publisher versio
Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector
No full textA novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz-boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used in high energy physics analyses. It uses minimally processed detector data as input and directly outputs particle properties of interest. The new technique is demonstrated for the reconstruction of the invariant mass of particles decaying in the CMS detector. The decay of a hypothetical scalar particle Formula Presented into two photons, Formula Presented, is chosen as a benchmark decay. Lorentz boosts Formula Presented are considered, ranging from regimes where both photons are resolved to those where the photons are closely merged as one object. A training method using domain continuation is introduced, enabling the invariant mass reconstruction of unresolved photon pairs in a novel way. The new technique is validated using Formula Presented decays in LHC collision data.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); NKFIH (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);
MES and NSC (Poland); FCT (Portugal); MESTD
(Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri
Lanka); Swiss Funding Agencies (Switzerland); MST
(Taipei); MHESI and NSTDA (Thailand); TUBITAK
and TENMAK (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, Contracts No. 675440, No. 724704, No. 752730,
No. 758316, No. 765710, No. 824093, No. 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
Hellenic Foundation for Research and Innovation
(HFRI), Project No. 2288 (Greece); the Deutsche
Forschungsgemeinschaft (DFG), under Germany’s
Excellence Strategy—EXC 2121 “Quantum Universe”—
390833306, and under Project No. 400140256—
GRK2497; the Hungarian Academy of Sciences, the
New National Excellence Program—ÚNKP, the NKFIH
Research Grants No. K 124845, No. K 124850, No. K
128713, No. K 128786, No. K 129058, No. K 131991,
No. K 133046, No. K 138136, No. K 143460, No. K
143477, 2020-2.2.1-ED-2021-00181, and TKP2021-
NKTA-64 (Hungary); the Council of Science and
Industrial Research, India; the Latvian Council of
Science; the Ministry of Education and Science, Project
No. 2022/WK/14, and the National Science Center,
Contracts No. Opus 2021/41/B/ST2/01369 and
No. 2021/43/B/ST2/01552 (Poland); the Fundação para a
Ciência e a Tecnologia, Grant No. CEECIND/01334/2018
(Portugal); the National Priorities Research Program by
Qatar National Research Fund; MCIN/AEI/10.13039/
501100011033, ERDF “a way of making Europe,” and
the Programa Estatal de Fomento de la Investigación
Científica y T´ecnica de Excelencia María de Maeztu,
Grant No. MDM-2017-0765 and Programa Severo
Ochoa del Principado de Asturias (Spain); the
Chulalongkorn Academic into Its 2nd Century Project
Advancement Project, and the National Science,
Research and Innovation Fund via the Program
Management Unit for Human Resources & Institutional
Development, Research and Innovation, Grant
No. B05F650021 (Thailand); the Kavli Foundation;
the Nvidia Corporation; the SuperMicro Corporation; the
Welch Foundation, Contract No. C-1845; and the Weston
Havens Foundation (USA).Publisher versio
Land subsidence susceptibility mapping using interferometric synthetic aperture radar (InSAR) and machine learning models in a semiarid region of iran
No full textMost published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect the occurrence of LS. In this study, radar interferometric techniques and machine learning (ML) models were used for the prediction, susceptibility zoning, and prioritization of influential variables in the occurrence of LS in the Bakhtegan basin. The LS rate was characterized by applying an interferometric synthetic aperture radar (InSAR). The recursive feature elimination (RFE) method was used to detect and select the dominant combination of indicators to prepare an LS susceptibility map. Three ML models, including random forest (RF), k-nearest neighbors (KNN), and classification and regression trees (CART), were used to develop predictive models. All three models had acceptable performance. Among the ML models, the RF model performed the best (i.e., Nash–Sutcliffe efficiency, Kling–Gupta efficiency, correlation coefficient, and percent bias metrics of 0.76, 0.78, 0.88, and 0.70 for validating phase, respectively). The analysis conducted on all three ML model outputs showed that high and very high LS susceptibility classes were located on or near irrigated agricultural land. The results indicate that the leading cause of land LS in the study region is not due to groundwater withdrawals. Instead, the distance from dams and the proximity to anticlines, faults, and mines are the most important identifiers of LS susceptibility. Additionally, the highest probability of LS susceptibility was found at distances less than 18 km from synclines, 6 to 13 km from anticlines, 23 km from dams, and distances less than 20 to more than 144 km from mines. The validated methods presented in this study are reproducible, transferrable, and recommended for mapping LS susceptibility in semiarid and arid climate zones with similar environmental conditions.Publisher versio
Observation of same-sign WW production from double parton scattering in proton-proton collisions at √s=13 TeV
No full textThe first observation of the production of Formula Presented bosons from double parton scattering processes using same-sign electron-muon and dimuon events in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of Formula Presented recorded at a center-of-mass energy of 13 TeV using the CMS detector at the CERN LHC. Multivariate discriminants are used to distinguish the signal process from the main backgrounds. A binned maximum likelihood fit is performed to extract the signal cross section. The measured cross section for production of same-sign Formula Presented bosons decaying leptonically is Formula Presented, whereas the measured fiducial cross section is Formula Presented. The observed significance of the signal is 6.2 standard deviations above the background-only hypothesis.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) ; NKFIH (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) ; MES and NSC (Poland) ; FCT (Portugal) ; MESTD (Serbia) ; MCIN/AEI and PCTI (Spain) ; MOSTR (Sri Lanka) ; Swiss Funding Agencies (Switzerland) ; MST (Taipei) ; MHESI and NSTDA (Thailand) ; TUBITAK and TENMAK (Turkey) ; NASU (Ukraine) ; STFC (United Kingdom) ; and DOE and NSF (USA) .Publisher versio