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NFT price and sales characteristics prediction by transfer learning of visual attributes
No full textNon-fungible tokens (NFTs) are unique digital assets whose possession is defined over a blockchain. NFTs can represent multiple distinct objects such as art, images, videos, etc. There was a recent surge of interest in trading them which makes them another type of alternative investment. The inherent volatility of NFT prices, attributed to factors such as over-speculation, liquidity constraints, rarity, and market volatility, presents challenges for accurate price predictions. For such analysis and forecasting, machine learning methods offer a robust solution framework. Here, we focus on three related prediction problems over NFTs: Predicting NFTs sale price, inferring whether a given NFT will participate in a secondary sale, and predicting NFT's sale price change over time. We analyze and learn the visual characteristics of NFTs by deep pre-trained models and combine such visual knowledge with additional important non-visual attributes such as the sale history, seller's and buyer's centralities in the trading network, and collection's resale probability. We categorize input NFTs into six categories based on their characteristics. Across detailed experiments, we found visual attributes obtained from deep pre-trained models to increase the prediction performance in all cases, and EfficientNet seems to perform the best. In general, CNN and XGBoost consistently outperformed the rest of them across all categories. We also publish our novel NFT dataset with temporal price knowledge, which is the first dataset to have NFT prices over time rather than at a single time point.Publisher versio
Priority-based dynamic multi-uav positioning for multi-target search and connectivity
No full textIn case of large-scale disasters such as earthquakes, where urban and public infrastructure might be destroyed, multiple unmanned aerial vehicle (UAV) or multi-drone systems can be very beneficial to rescue teams, by enabling them to carry out multiple tasks simultaneously, such as detecting, monitoring, and connecting multiple targets simultaneously. In this work, we propose an event-driven algorithm that integrates a novel connectivity-based prioritization of targets into dynamic positioning and path planning for multi-UAV systems in search and rescue (SAR) missions. Two distinct groups of UAVs are deployed. While search UAVs sense the area of interest as fast as possible, relay UAVs provide connectivity to search UAVs as well as targets depending on their priority level. Our results show that network formation and target connectivity can be improved up to 60% compared to a benchmark path planner that does not consider connectivity priorities.TÜBİTA
Performance characterization of rotary wing UAV-mounted fso links in the presence of pointing errors
No full textNon-terrestrial networks (NTNs) involve the use of unmanned aerial vehicles (UAVs), high-altitude platform stations (HAPSs), and low-earth orbit satellites (LEOs) and have emerged as a powerful tool to enable global connectivity. With their flexible deployment, rotary-wing UAVs are particularly useful to deliver versatile airborne wireless access and backhaul in areas where there is limited terrestrial infrastructure. In this paper, we consider a scenario where free space optical (FSO) terminals are mounted on rotary wing UAV to provide high capacity wireless backhaul for ground base stations. Due to the narrow divergence angle of laser tranmsitters, FSO systems are prone to pointing errors. In our study, we classify and analyze two primary sources of pointing errors in rotary-wing UAV-based links: horizontal movement and rotational stability. The former stems from the semi-fixed hovering nature of UAVs, introducing uncertainties in horizontal displacement that influence the positioning of the received beam along the x and y directions. Additionally, rotational stability issues in rotary-wing UAVs, including rolling, yawing, and pitching, lead to shifts in the center of the received beam. We classify these pointing errors as altitude-dependent and altitude-independent and analyze their distinct impacts on the bit error rate (BER) of UAV-based FSO links. Our findings contribute to a better understanding of pointing errors in UAV-based FSO communication, paving the way for enhanced airborne connectivity solutions.TÜBİTA
Towards a new rural and urban intersection, “R-Urban”: the Beykoz district case in Istanbul
No full textPurpose: Urbanization is among current global challenges along with climate change, population growth and depletion of natural resources. Rural areas have been transformed due to urbanization pressures, which leads to a change in the relationship between rural and urban spaces, blurring the boundaries between rural and urban areas. Due to the lack of a clear distinction, a new form of rural–urban relationship has emerged. The convergence and even disappearance of borders has paved the way for a rural–urban dichotomy and re-questioning the relationship between cities and nature. In the case of Istanbul, this transformation, especially since 1980, has been reshaping rural–urban relations. Thus, the present article aimed to rethink this new pattern described as “R-Urban”, a hybrid intersection as a field of experience. Design/methodology/approach: R-Urban creates an ambiguous and dynamic hybrid space where urban and rural operate within flexible and layered spatial boundaries. In the article, initially, a conceptual framework is presented based on the analysis of existing conceptual framework of rural–urban relationships, with transactional and dialectical perspectives. Secondly, fieldwork was investigated with representational tools such as mapping, photography and collages to determine the current status based on quantitative and qualitative data. Then, the rural–urban situation of Istanbul was conceptualized, with a focus on Beykoz neighborhood, a peripheral development with blurred rural and urban borders. Findings: Beykoz, as an R-Urban space, has a significant potential regenerating the relations between nature, humans and space and production to practices to ensure ecological resilience. The article demonstrated that the coexistence of different lifestyles paved the way for cultural diversity and the development of social relations. This diversity allowed innovative and sustainable practices while increasing social cooperation and solidarity in the region. Practical implications: To improve urban resilience, especially in Istanbul against future poly-crises, effective use of resources, healthy social environment, production-consumption network and symbiotic rural-urban relationships could be developed. Social implications: Strengthening the socio-cultural, economic and ecological systems could lead to dynamic interactions that would reduce vulnerabilities in rural–urban intersections that would regenerate and renew the city and reconsider adaptation capabilities. Originality/value: The present article rethinks this new pattern described as “R-Urban”, a hybrid intersection as a field of experience, highlighting the potential of these rural–urban intersections for future urban resilience and adaptation capabilities
A guided-ensembling approach for cell counting in fluorescence microscopy images
No full textAlthough deep learning and computer vision based approaches have demonstrated success in the field of cell counting and detection in microscopic images, they continue to have certain limitations. More specifically, they experience an overall increase in false positives when dealing with cell populations that show high density and heterogeneity. Existing approaches require the reselection of parameters for each new dataset to improve the accuracy of cell counting. Therefore, it is necessary to revise the fundamental models for each new microscopic image. This study introduces a novel neural network-based method that eliminates the need for retraining by combining the pretrained Cellpose and Stardist models. The accuracy of our proposed approach was evaluated on a variety of microscopic images. Despite variations in cell densities, our proposed approach demonstrated a notably improved cell counting performance in comparison to solely utilizing the Cellpose and Stardist models.EMBO Installation for acquiring the Original Dataset (DORIG) for AnalysesPublisher versio
States of cultivation: Imperial transition and scientific agriculture in the eastern mediterranean
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Performance of CMS muon reconstruction from proton-proton to heavy ion collisions
No full textThe performance of muon tracking, identification, triggering, momentum resolution, and momentum scale has been studied with the CMS detector at the LHC using data collected at √s NN= 5.02 TeV in proton-proton (pp) and lead-lead (PbPb) collisions in 2017 and 2018, respectively, and at √s NN= 8.16 TeV in proton-lead (pPb) collisions in 2016. Muon efficiencies, momentum resolutions, and momentum scales are compared by focusing on how the muon reconstruction performance varies from relatively small occupancy pp collisions to the larger occupancies of pPb collisions and, finally, to the highest track multiplicity PbPb collisions. We find the efficiencies of muon tracking, identification, and triggering to be above 90% throughout most of the track multiplicity range. The momentum resolution and scale are unaffected by the detector occupancy. The excellent muon reconstruction of the CMS detector enables precision studies across all available collision systems.SC (Armenia), 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); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); 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); LMTLT (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 (U.S.A.).r 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, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); 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 Be.ing Municipal Science & Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy -EXC 2121 "Quantum Universe"-390833306, and under project number 400140256-GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program -UNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; ICSC National Research Center for High Performance Computing, Big Data and Quantum Computing and FAIR-Future Artificial Intelligence Research, funded by the EU NexGeneration program (Italy); 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 B37G660013 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA)
Visible light communication (VLC) basics
No full textVisible light communication (VLC) has emerged as a transformative technology that leverages light as a carrier for wireless data transmission. This chapter delves into the fundamentals of VLC, beginning with an insightful exploration of its background and subsequently addressing the advantages and challenges inherent in VLC systems. The discussion extends to diverse application areas where VLC proves to be a promising solution. Notably, the chapter highlights the motivation for integrating VLC into the 6G and beyond communication landscape. The heart of VLC lies in its principles, comprehensively outlined in the second section. Here, the basics of light propagation and the key components of VLC systems are explained, providing a solid foundation for understanding the intricacies of this communication paradigm. Channel modelling in VLC is explored in detail, with a special focus on indoor line-of-sight (LOS) VLC channel model. The fourth section discusses the diverse modulation techniques employed in VLC, ranging from pulse-based methods to optical orthogonal frequency division multiplexing (OFDM) and VLC-specific modulation techniques. This chapter encapsulates the essence of VLC, offering a comprehensive overview of its principles, channel modelling, and modulation techniques
Silikon tabanlı çığ fotodiyot ile tek foton algılama.
No full textDue to significant advances in quantum technologies, the use of single photon detectors (SPDs) is becoming common in various fields. As a result of the excellent photodetection performance of SPDs, they are used in a wide range of fields, such as quantum cryptography, astronomy, spectroscopy, and medical applications. There is no doubt that improvements in the performance of SPDs will pave the way for new technologies based on quantum information. Over the years, several different types of SPDs have been developed, such as photomultiplier tubes based on vacuum tubes, avalanche photodiodes (APDs) based on semiconductors, or nanowires based on superconducting technology. Any of these technologies have been preferred by evaluating their advantages and disadvantages for the intended applications. At that point, SPDs based on semiconductor technology have many advantages, including low voltage operation, high reliability, simple electronic requirements, and high detection efficiency. In this work, the TO-8 SAP500 series Silicon APD provided by Laser Component was preferred, the driving circuit was designed for visible (VIS) range sensing applications, and all stages of work were explained in detail. This thesis consists of four sections: the general information on SPDs is covered in the first section, the general information on APDs is covered in the second section, the experimental part is covered in the third section, and the results are covered in the last section.Kuantum teknolojilerindeki önemli gelişmeler nedeniyle, tek foton dedektörlerinin (TFD'ler) kullanımı çeşitli alanlarda yaygınlaşmaktadır. TFD'ler, mükemmel ışık algılama performansları sonucunda; kuantum kriptografi, astronomi, spektroskopi ve tıbbi uygulamalar gibi çok çeşitli alanlarda kullanılmaktadırlar. TFD'lerin performansındaki gelişmelerin, kuantum bilgiye dayalı yeni teknolojilerin önünü açacağına hiç şüphe yoktur. Yıllar içinde, vakum tüplerine dayalı fotoçoğaltıcı tüpler, yarı iletkenlere dayalı çığ fotodiyotları (ÇFD) ve süper iletken teknolojisine dayalı nanoteller gibi birkaç farklı TFD türü geliştirilmiştir. Bu teknolojilerden herhangi biri amaçlanan uygulamalara yönelik avantaj ve dezavantajları değerlendirilerek tercih edilmektedir. Bu noktada, yarı iletken teknolojisine dayanan TFD'lerin düşük voltajda çalışma, yüksek güvenilirlik, basit elektronik gereksinimler ve yüksek algılama verimliliği gibi birçok avantajı vardır. Bu çalışmada Laser Component firmasının sağladığı TO-8 SAP500 serisi Silicon ÇFD tercih edilmiş olup, görünür bölge algılama uygulamaları için sürücü devresi tasarlanmış ve tüm aşamalar detaylı bir biçimde açıklanmıştır. Bu tez dört bölümden oluşmaktadır: birinci bölümde TFD'ler hakkında genel bilgiler, ikinci bölümde ÇFD'ler hakkında genel bilgiler, üçüncü bölümde deneysel kısım ve son bölümde ise sonuçlar yer almaktadır
Kentsel bina enerji modellemesi: zaman serisi analizi için dinamik ve veriye dayalı modellerin entegre edilmesi.
No full textThis study addresses a critical gap in Urban Building Energy Modeling (UBEM) by introducing an innovative hybrid approach that combines dynamic and statistical models. Previous hybrid studies faced challenges in result validation, model calibration, and delivering predictions at high temporal resolution. To fill this gap, the study presents an integrated UBEM for time-series analysis. The methodology involves creating a dynamic model for 13 buildings on a university campus, with key parameters calibrated using Bayesian Optimization. This calibration reduces the simulation's annual Mean Absolute Percentage Error (MAPE) from 21.56\% to 4.60\% and the monthly MAPE from 22.14\% to 9.90\%. The calibrated dynamic model's hourly energy consumption data is then incorporated into a statistical model, a Long Short-Term Memory (LSTM) network utilized in time-series regression. The statistical model predicts the hourly energy consumption with an average R-squared value of 0.915. The proposed hybrid model facilitates the creation of synthetic hourly energy consumption data for urban building stocks. In this sense, the energy use patterns derived from the hourly consumption can be combined with the building characteristics to identify parameters that shape the building energy demand. The hybrid model can also optimize the building energy efficiency design by exploring various configurations in the building envelope and operational schedules and minimizing the energy consumption and the resultant environmental impact. When adapted to the urban scale, this hybrid model can provide valuable insights for urban planners in identifying high-demand areas and implementing energy-efficient interventions based on high-resolution temporal energy consumption data. Instead of testing energy and cost-efficiency scenarios using dynamic simulations, the proposed hybrid model can effectively monitor and control the hourly building energy use over time-series analysis once calibrated. This study underscores the potential of hybrid modeling in UBEM despite facing challenges, like complexities in generating the validation data from a limited number of metered energy consumption and computational constraints. In summary, this research introduces a robust hybrid UBEM and draws a roadmap for future research to comprehend urban building energy demand accurately. Future research includes reliability improvements for the validation and input data, efficient and precise dynamic modeling approaches, and utilizing thermal interactions between buildings within the statistical model.Bu çalışma, dinamik ve istatistiksel modelleri birleştiren yenilikçi bir hibrit yaklaşım sunarak Kentsel Bina Enerji Modellemesindeki (UBEM) kritik bir boşluğu dikkat çekmektedir. Önceki hibrit çalışmalar, sonuçların doğrulanması, model kalibrasyonu ve tahminlerin yüksek zamansal çözünürlükte sunulması konularında zorluklarla karşılaşıyordu. Bahsi geçen sorunlara çözüm üretmek amacıyla bu çalışma, istatiksel ve dinamik modelleri bütünleştiren bir hibrit model sunmaktadır. Bu kapsamda ilk olarak 13 binalık bir üniversite kampüsünün dinamik modeli oluşturulmuş, daha sonra bu modelin temel parametreleri Bayes Optimizasyonu kullanılarak kalibre edilmiştir. Kalibrasyon sonucunda dinamik model simülasyonunun yıllık Ortalama Mutlak Yüzde Hatası (MAPE) \%21,56'dan \%4,60'a ve aylık \%22,14'ten \%9,90'a düşmüştür. Kalibre edilen dinamik model daha sonra saatlik enerji tüketim verileri yaratmada kullanılmıştır. Bu tüketim verileri, çalışmanın bir diğer kısmı olan istatiksel modelin doğrulama verilerini teşkil etmektedir. İstatiksel modelde her bir bina için bir tür Özyinelemeli Sinir Ağı (RNN) olan Uzun Kısa Süreli Bellek (LSTM) modeli oluşturulmuş, daha sonra bu modeller zaman serisi regresyon analiziyle binaların saatlik enerji tüketimlerini tahmin etmede kullanılmıştır. Regresyon sonuçlarına göre modellerin ortalama determinasyon katsayısı (R-sqaured) 0.915'tir. Önerilen hibrit model, kentsel bina stokları için sentetik saatlik enerji tüketimi verilerinin oluşturulmasını kolaylaştırmaktadır. Bu anlamda, saatlik tüketimlerden elde edilen enerji kullanım davranışları, binaların enerji talebini şekillendiren parametreleri belirlemek için binaların ayırt edici özellikleriyle birleştirilebilir (ör. yalıtım bilgileri) . Hibrit model aynı zamanda bina kabuğundaki ve operasyonel programlardaki çeşitli konfigürasyonları keşfederek enerji tüketimini ve bunun sonucunda ortaya çıkan çevresel etkiyi en aza indirebilir. Bu sayede önerilen hibrit model enerji verimli bina tasarımında değerlendirilebilir. Saatlik çözünürlükteki bina enerji tüketimi verilerini tahmin edebilen bu hibrit model, kentsel ölçeğe uyarlandığında kent planlayıcılarına yüksek enerji tüketen bölgelerin belirlenmesi ve bu bölgeler için gerekli önlemlerin alınması konusunda değerli bilgiler sağlayabilir. Önerilen hibrit model, dinamik simülasyonlar üzerinden enerji ve maliyet verimliliği senaryolarını test etmek yerine, istatiksel modelin sunduğu zaman serisi analizi yöntemiyle saatlik bina enerji kullanımını etkili bir biçimde tahmin edebilir ve kontrol edebilir. Bu çalışmada, doğrulama verileri oluşturulurken ölçülmüş tüketim verisine sahip ay sayısının az olması ve simülasyon ve tahminlerin yoğun hesaplama gücüne ve uzun bir zamana ihtiyaç duyması gibi sorunlarla karşılaşılmıştır. Fakat tüm zorluklara rağmen bu çalışma, UBEM alanındaki hibrit modellerin potansiyeline dikkat çekmiştir. Özetle, bu araştırma güçlü bir hibrit UBEM'i tanıtırken kentsel bina enerji talebini doğru şekilde anlamak için gelecekteki araştırmalara bir yol haritası çizmektedir. Gelecekteki yürütülmesi planlanan araştırmalar arasında doğrulama ve girdi verilerinin güvenilirliğinin iyileştirilmesi, verimli ve tutarlı dinamik modelleme yöntemlerinin geliştirilmesi ve binalar arasındaki termal etkileşimi göz önüne alan parametrelerin istatiksel modele tanıtılması yer almaktadır