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Professional identity development in pre-service teachers: the impact of online informal mentoring
No full textThis case study aimed to examine how an online informal mentoring relationship among pre-service teachers and mentor teachers has functioned to support pre-service teachers’ professional identity development. The data were collected via video recordings that captured how 22 pre-service teachers and five mentor teachers worked in five groups to co-design lesson plans. Also, five mentor teachers and 11 pre-service teachers were interviewed. All data were analysed through MAXQDA (2020) software. The data analysis indicated that the online informal mentoring process has the potential to support pre-service teachers’ professional identity development. Furthermore, mentor teachers made use of several principles that have the potential to inform pre-service teachers’ professional identity development such as building and maintaining a strong relationship, offering support and encouragement, providing ongoing feedback, making time for reflective activities, creating a positive environment, enabling awareness, self-identifications, and future projections
A systematic review of socio-economic impact assessments of solar energy and photovoltaic (PV) technologies: network dynamics, societal problems and policy implications
No full textEnergy dissipation preserving physics informed neural network for Allen–Cahn equations
No full textThis paper investigates a numerical solution of Allen–Cahn equation with constant and degenerate mobility, with polynomial and logarithmic energy functionals, with deterministic and random initial functions, and with advective term in one, two, and three spatial dimensions, based on the physics-informed neural network (PINN). To improve the learning capacity of the PINN, we incorporate the energy dissipation property of the Allen–Cahn equation as a penalty term into the loss function of the network. To facilitate the learning process of random initials, we employ a continuous analogue of the initial random condition by utilizing the Fourier series expansion. Adaptive methods from traditional numerical analysis are also integrated to enhance the effectiveness of the proposed PINN. Numerical results indicate a consistent decrease in the discrete energy, while also revealing phenomena such as phase separation and metastability
Base-Mediated Synthesis of Imidazole-Fused 1,4-Benzoxazepines via 7-exo-dig Cyclizations: Propargyl Group Transformation.
Get PDFHerein, we describe the synthesis of a series of imidazole-fused 1,4-benzoxazepines using 7-exo-dig cyclizations. Two sets of substrates, one containing disubstituted alkyne functional groups and the other featuring terminal alkynes, were synthesized by using O-propargylation, Sonogashira cross-coupling, and condensation reactions between aldehydes and o-diaminobenzene. While the disubstituted substrates yielded exocyclic E/Z configured cyclization products smoothly, the reactions involving terminal alkynes resulted in the formation of isomeric products with altered skeletal structures, in addition to the expected 7-exo-dig cyclization products. Density functional theory (DFT) calculations were used to clarify the mechanisms underlying the formation of these products. It is suggested that these unexpected products are formed through a series of intermolecular O-to-N-propargyl transfer reactions, followed by 7-exo-dig cyclization, in accordance with Baldwin’s rules. Furthermore, this study extensively demonstrates the conversion of exocyclic products to endocyclic products through a base-mediated 1,3-H shift
Automated construction contract analysis for risk and responsibility assessment using natural language processing and machine learning
Get PDFConstruction contracts contain critical risk-related information that requires in-depth examination, yet tight schedules for bidding limit the possibility of comprehensive review of extensive documents manually. This research aims to develop models for automating the review of construction contracts to extract information on risk and responsibility that will provide inputs for risk management plans. Models were trained on 2268 sentences from International Federation of Consulting Engineers templates and tested on an actual construction project contract containing 1217 sentences. A taxonomy classified sentences into Heading, Definition, Obligation, Risk, and Right categories with related parties of Contractor, Employer, and Shared. Twelve models employing diverse Natural Language Processing vectorization techniques and Machine Learning algorithms were implemented and benchmarked based on accuracy and F1 score. Binary classification of sentence types and an ensemble method integrating top models were further applied to improve performance. The best model achieved 89 % accuracy for sentence types and 83 % for related parties, demonstrating the capabilities of automated contract review for identification of risk and responsibilities. Adopting the proposed approach can significantly expedite contract reviews to support risk management activities, bid preparation processes and prevent disputes caused by overlooking risks and responsibilities
Effect of morphology on the optical limiting of BiVO4 films
No full textPrecise control over the morphology and crystal structure of semiconductor-based optical materials is essential for optimizing their nonlinear optical properties. Morphological factors significantly affect the material's interaction with light, influencing nonlinear absorption, harmonic generation, and optical confinement. In this study, the nonlinear optical (NLO) properties and optical limiting (OL) performance of bismuth vanadate (BiVO4) films depending on precursor solution pH condition, powder morphology and weight percentage of the BiVO4 powders in PMMA (10–30 wt.%) were investigated. The BiVO4 powders were synthesized via the hydrothermal method and the effect of precursor solution pH (pH of 1, 7.5 and 12) was investigated on the size and morphology of the BiVO4 powders. BiVO4 films were prepared using the spin coating method utilizing the BiVO4 powders and PMMA. The bandgap values of films were found to change from 3.39 to 3.56 eV depending on the BiVO4 growth solution pH. The nonlinear absorption coefficients (βeff), saturation intensity thresholds (ISAT) and optical limiting (OL) threshold were obtained using the open aperture (OA) Z-scan experiment. It has been observed that the nonlinear absorption and optical limitation performance of the BiVO4 films can be altered by changing the powder morphology and BiVO4 weight concentration. BiVO4 thin films fabricated using a precursor solution pH 12 and weight concentration of 30 wt.% showed the best performance among all fabricated films with the highest nonlinear absorption coefficient (βeff), saturation density threshold (ISAT) and lowest OL threshold value
Yinelemeli Eğitilen Nesne Algılayıcılar İle Hayvan Kolonilerinin Minimal Denetimli Takibi
No full textAnimal colonies exhibit highly intricate behaviours, many of which remain poorly understood or unexplored. Effectively monitoring these behaviours requires long-term tracking of a substantial proportion of the group members in their natural environments or an experimental setup. Recent advances in computer vision indicate that neural networks can reliably detect individuals within an animal colony, even in challenging environmental conditions. However, training a neural network with an error rate acceptable for scientific purposes generally requires a large amount of human-labeled training data. In this thesis, we propose an individual animal tracking framework without requiring any explicit human annotations by modifying one of the oldest semi-supervised learning methods called self-training with significant upgrades. Replacing the initial human-annotated dataset required for self-training with the unreliable object locations proposed by the Segment Anything Model (SAM), we iteratively train accurate object detectors. To demonstrate the effectiveness of our method, we conduct some comparative experiments containing our honeybee colony data and a few publicly available animal colony location datasets. The experimental results show that the object detectors trained with the proposed method can achieve scientifically satisfactory detection results without labelling any bounding boxes.Hayvan kolonileri, birçoğu yeterince anlaşılmamış veya keşfedilmemiş olan son derece karmaşık davranışlar sergiler. Bu davranışların etkili bir şekilde belirlenmesi, grup üyelerinin önemli bir kısmının doğal ortamlarında veya deneysel düzeneklerde uzun süreli takip edilmesini gerektirir. Bilgisayarla görü alanındaki son gelişmeler, derin sinir ağlarının zorlu çevre koşullarında bile bir hayvan kolonisindeki bireyleri güvenilir bir şekilde tespit edebileceğini göstermektedir. Bununla birlikte, bilimsel amaçlar için kabul edilebilir bir hata oranına sahip bir sinir ağının eğitilmesi genellikle büyük miktarda insan etiketli eğitim verisi gerektirir. Bu tezde, kendi kendine eğitim olarak adlandırılan en eski yarı denetimli öğrenme yöntemlerinden birini Her Şeyi Bölütle (SAM) isimli yeni bir model ile destekleyerek herhangi bir işaretli veriye ihtiyaç duymayan bir hayvan takibi sistemi öneriyoruz. Kendi kendine öğrenme için ihtiyaç duyulan ilk veri setini SAM tarafından önerilen konumlar ile değiştirerek yüksek doğruluklu obje tespit eden modelleri yinelemeli olarak eğitiyoruz. Yöntemimizin etkinliğini göstermek için, bal arısı kolonisi verilerimizi ve halka açık birkaç hayvan kolonisi tespiti veri kümesini içeren bazı karşılaştırmalı deneyler gerçekleştiriyoruz. Deneysel sonuçlar, önerilen yöntemle elde edilen nesne dedektörlerinin, herhangi bir veri işaretlemeden bilimsel olarak tatmin edici sonuçlara ulaşabileceğini gösteriyor.M.S. - Master of Scienc
Zonguldak endüstriyel limanının miras alanı olarak öneminin değerlendirilmesi
No full textThe shift in technology after the industrial revolution brought forth industrial cities that thrived on industrial production. Industrial ports emerged during the mid to late 19th century in port cities to match the speed of industrial production through industrialized facilities and transportation. The industrial port-cities developed rapidly and became forefront cities in their countries through rapid economic growth followed by socio-cultural growth.
A second shift in technology happened with the invention of containerization during the late 20th century. Ports that could not adapt to containerization became redundant and were relocated to outer peripheries of their cities or downstream. These ports were then adapted into their cities as heritage places through waterfront regeneration and adaptive re-use projects. However, this caused the value of an active industrial port as a heritage place that supports its city as a backbone to be excluded from the perspective of decision makers. This thesis aims to emphasize the importance of active industrial ports for decision makers and the local community as heritage places, that they are still valuable when in active use. This study tries to establish a comprehensive understanding of industrial ports, their developments, transformation processes and value as heritage places.
The Industrial Port of Zonguldak is chosen as a case study for this thesis. The transformation processes, historical timeline, local dynamics, context and current situation of the port is covered in depth to convey its significance not just to decision makers but for all which are concerned with the conservation of cultural heritage. The significance of the Industrial Port of Zonguldak was assessed to prevent further loss of its values, provide a base for future conservation efforts regarding it, and to ensure its continuation as an active industrial port that is a living heritage place.Endüstri devrimi ile beraber ortaya çıkan teknolojideki değişim endüstriyel üretim üzerinden hızla gelişen endüstriyel şehirleri meydana getirdi. On dokuzuncu yüzyılın ikinci yarısında, endüstrileşmeden kaynaklı doğan üretim hızını karşılamak üzere, endüstriyel nakliye sistemleri ve tesisleri ile liman kentlerinde endüstriyel limanlar ortaya çıktı. Endüstriyel liman kentleri, hızla kalkınan ekonomileri ve gelişen sosyoekonomik süreçleri ile ülkelerinde önemli konumlara geldiler.
On dokuzuncu yüzyılın sonlarında, konteyner taşımacılığı ile beraber ikinci bir teknolojik değişim meydana geldi. Bu değişime uyum sağlayamayan özgün limanlar kent merkezlerinde işlevsiz kaldı ve liman faaliyetleri şehirlerin dış periferlerine taşındı. Zamanla özgün limanlar, yeniden işlevlendirme ve kıyı yenileme projeleri ile kültürel miras alanları olarak şehirlerine kazandırıldılar. Ancak bu durum aktif endüstriyel limanların miras alanları olarak öneminin göz ardı edilmesine sebep oldu. Endüstriyel limanların devamlılığı ve değerlerinin korunmasını sağlamak için ana karar mercilerinin ve halkın bu limanların miras alanı olarak değerlerini anlaması zorunludur. Bu çalışma endüstriyel limanlar, gelişimleri, dönüşüm süreçleri ve miras alanı olarak değerleri üzerine bütüncül bir anlayış sağlamaya çalışmaktadır.
Tezin kapsamı ve amacını doğrultusunda Zonguldak Endüstriyel Limanı çalışılmıştır. Yalnızca limanın ana karar mercileri ve limandan etkilenen kişiler için değil, kültürel mirasın korunmasıyla ilgilenen tüm kesimler için limanın dönüşüm süreçleri, tarihsel çizelgesi, yerel dinamikleri, bağlamı ve günümüz durumu derinlemesine araştırılıp sunulmaya çalışılmıştır. Limanın mevcut değerlerinin kaybını önlemek, liman üzerine gelecekteki kültürel mirası koruma çalışmaları için zemin oluşturmak ve limanın yaşayan bir miras alanı olarak aktif kullanımına devam etmesini sağlamak için Zonguldak Endüstriyel Limanı’nın bir miras alanı olarak önemi değerlendirilmiştir.M.S. - Master of Scienc
A model for assessing the urban heat Island effect in urban regeneration areas: case of mamak and the north ankara
No full textUrban regeneration, which aims to provide increased sustainability in terms of higher quality urban environment and better urban livability, has been on the agenda in Türkiye. Ankara, the capital city, has long faced uncontrolled development of squatter areas due to rural-to-urban migration, resulting in critical structural problems, including low-quality constructions, poor infrastructure, and insufficient urban services. Urban regeneration has been presented as a solution to those problems. This study investigates whether urban regeneration provides environmental benefits in terms of mitigating urban heat islands (UHI). Two large-scale urban regeneration areas in Ankara, the New Mamak Urban Regeneration Project (NMURP) and the North Ankara Urban Regeneration Project (NAURP), are anaylzed, both of which have been undergoing transformation more than a decade. Landsat 5 and Landsat 8 satellite images were used to detect the land use-based changes in the surface UHI, based on UHIER index, between 2005 and 2022, CORINE datasets were utilized for land use classification in the study areas for comparison. The results show that UHI values decreased in entire project areas due to removal of squatter settlements and partial completion of the transformation. However, when the local variations are observed, it is concluded that UHI values increased in already transformed sites as a result of high built-up densities, where complex cultivation pattern is replaced by urban fabric in NMURP, agriculture and construction sites replaced by urban fabric, natural grasslands replaced by road network and urban fabric, and urban fabric is replaced by urban green areas and construction sites in NAURP
EnSCAN: ENsemble Scoring for prioritizing CAusative variaNts across multiplatform GWASs for late-onset alzheimer's disease.
Get PDFLate-onset Alzheimer’s disease (LOAD) is a progressive and complex neurodegenerative disorder of the aging population. LOAD is characterized by cognitive decline, such as deterioration of memory, loss of intellectual abilities, and other cognitive domains resulting from due to traumatic brain injuries. Alzheimer’s Disease (AD) presents a complex genetic etiology that is still unclear, which limits its early or differential diagnosis. The Genome-Wide Association Studies (GWAS) enable the exploration of individual variants' statistical interactions at candidate loci, but univariate analysis overlooks interactions between variants. Machine learning (ML) algorithms can capture hidden, novel, and significant patterns while considering nonlinear interactions between variants to understand the genetic predisposition for complex genetic disorders. When working on different platforms, majority voting cannot be applied because the attributes differ. Hence, a new post-ML ensemble approach was developed to select significant SNVs via multiple genotyping platforms. We proposed the EnSCAN framework using a new algorithm to ensemble selected variants even from different platforms to prioritize candidate causative loci, which consequently helps improve ML results by combining the prior information captured from each dataset. The proposed ensemble algorithm utilizes the chromosomal locations of SNVs by mapping to cytogenetic bands, along with the proximities between pairs and multimodel Random Forest (RF) validations to prioritize SNVs and candidate causative genes for LOAD. The scoring method is scalable and can be applied to any multiplatform genotyping study. We present how the proposed EnSCAN scoring algorithm prioritizes candidate causative variants related to LOAD among three GWAS datasets