243 research outputs found
Determination of necessary basis for positioning of drainage structures in forest roads (sample of belgrad forest)
Orman yollarında kullanılan drenaj yapıları ve koruyucu yapılar çeşitli tiplerdedir. Bunlar; kenar
hendekleri, büz, menfez, köprü, kasis ve duvarlardır. Tüm bu drenaj tesisleri ve duvarların ana görevi orman
yolunu dış etkenlere karşı korumaktır. Bu drenaj yapıları sayesinde yolun kullanım ömrü uzamaktadır. Drenaj
yapılarının planlanması ve yapımı çok önemlidir. Planlama ve yapım çalışmalarında yapılan hatalar drenaj
yapılarının ömrünü kısaltmaktadır. Bu çalışmada örnek bir orman yolu üzerinde yapılan drenaj yapılarının
planlama ve yapım çalışmaları incelenmiştir. Sonuç olarak, bazı drenaj yapılarının konumlarının ve yapımının
hatalı olduğu belirlenmiş ve hatalar ortaya konmuştur.The drainage structures and protective structures in used forest roads are various types. These are
dip drains, pipes, culverts, bridges, water-bars and walls. The main task of all drainage structures and walls is
protecting against external aggressors to the forest roads. The useful life of forest road due to drainage
structures is prolonged. The planning and constructions operations of drainage structures are very important.
The occurring errors by planning and constructions operations are shortened the life of drainage structures. In
this study, the planning and constructions operations of building drainage structures on a sample forest road
were investigated. In the results, locations and constructions of some drainage structures have been
determined to be incorrect and errors have revealed
Content-Based Medical Image Retrieval with Opponent Class Adaptive Margin Loss
Broadspread use of medical imaging devices with digital storage has paved the
way for curation of substantial data repositories. Fast access to image samples
with similar appearance to suspected cases can help establish a consulting
system for healthcare professionals, and improve diagnostic procedures while
minimizing processing delays. However, manual querying of large data
repositories is labor intensive. Content-based image retrieval (CBIR) offers an
automated solution based on dense embedding vectors that represent image
features to allow quantitative similarity assessments. Triplet learning has
emerged as a powerful approach to recover embeddings in CBIR, albeit
traditional loss functions ignore the dynamic relationship between opponent
image classes. Here, we introduce a triplet-learning method for automated
querying of medical image repositories based on a novel Opponent Class Adaptive
Margin (OCAM) loss. OCAM uses a variable margin value that is updated
continually during the course of training to maintain optimally discriminative
representations. CBIR performance of OCAM is compared against state-of-the-art
loss functions for representational learning on three public databases
(gastrointestinal disease, skin lesion, lung disease). Comprehensive
experiments in each application domain demonstrate the superior performance of
OCAM against baselines.Comment: 10 pages, 6 figure
Productivity of hauling by tajfun MOZ 500 GR cable yarder in Turkey
The extraction of timber is very important despite the process is difficult, expensive, time consuming, and has concerns with work safety. The extraction operations are used human, animal, and machine power. The purpose of this study is to investigate the productivity of the Tajfun MOZ 500 GR cable yarder during the extraction of timber from spruce stands in northeast Turkey. The research results imply that some working characteristics of the MOZ 500 GR cable yarder such as load volume, yarding distance, speed of the carriage, and time consumption per phase have an important impact on the productivity of the cable yarder. The results indicated that the productivity of MOZ 500 GR cable yarder was 8.39 m(3)/h for an average yarding distance of 90 m. Besides, the daily productivity of cable yarders was found at 67.12 m(3). The cable yarders seem ideal for use in the steep terrain. The use of cable yarders in wood production works is more ideal than other production techniques (human, animal, and tractor) in terms of productivity, speed, and work safety
HydraViT: Adaptive Multi-Branch Transformer for Multi-Label Disease Classification from Chest X-ray Images
Chest X-ray is an essential diagnostic tool in the identification of chest
diseases given its high sensitivity to pathological abnormalities in the lungs.
However, image-driven diagnosis is still challenging due to heterogeneity in
size and location of pathology, as well as visual similarities and
co-occurrence of separate pathology. Since disease-related regions often occupy
a relatively small portion of diagnostic images, classification models based on
traditional convolutional neural networks (CNNs) are adversely affected given
their locality bias. While CNNs were previously augmented with attention maps
or spatial masks to guide focus on potentially critical regions, learning
localization guidance under heterogeneity in the spatial distribution of
pathology is challenging. To improve multi-label classification performance,
here we propose a novel method, HydraViT, that synergistically combines a
transformer backbone with a multi-branch output module with learned weighting.
The transformer backbone enhances sensitivity to long-range context in X-ray
images, while using the self-attention mechanism to adaptively focus on
task-critical regions. The multi-branch output module dedicates an independent
branch to each disease label to attain robust learning across separate disease
classes, along with an aggregated branch across labels to maintain sensitivity
to co-occurrence relationships among pathology. Experiments demonstrate that,
on average, HydraViT outperforms competing attention-guided methods by 1.2%,
region-guided methods by 1.4%, and semantic-guided methods by 1.0% in
multi-label classification performance
The use of portable winch for forest harvesting operations in Pinus pinaster plantation areas
Ülke nüfusunun artışına paralel olarak odun üretim miktarlarında da son yıllarda önemli artışlar
görülmektedir. Odun üretim miktarlarında ortaya çıkan bu artış üretim çalışmalarında da yeniliklere
gitmeyi zorunlu kılmaktadır. Özellikle odun üretim çalışmalarında taşınabilir ve düşük maliyetli yeni
teknolojilerin ve makinelerin kullanımı önemli bir hal almıştır. Bu makineler arasında el vinçleri son
yıllarda ülkemizde ve dünya ormancılık çalışmalarında da kullanılmaya başlanmıştır. Bu vinçler
kurulumu ve sökülmesi yanında kullanım açısından da çok kullanışlı makinelerdir. Bu çalışmada,
İstanbul Orman Bölge Müdürlüğü’ne bağlı Sarıyer Orman İşletme Şefliği sınırları içerisinde yer alan
Sahilçamı plantasyon sahalarında el vincinin kullanımı incelenmiştir. Çalışmalar sonucunda el vincinin
ortalama 50 metrelik sürütme mesafesinde saatlik verimi 1.10 m3/sa ve günlük verimi 8.80 m3/gün
olarak bulunmuştur. El vincinin saatlik yakıt tüketimi ise 1.4 lt/sa olarak belirlenmiştir.In parallel with the increase in the population in Turkey, there has been a significant increase in the
amount of wood production in recent years. This increase, which occurs in the amount of wood
production, makes it imperative to innovate in production of forest products. Especially in wood
production, the use of portable and low-cost new technologies and machines has become important.
Among these machines, portable winches have been used in forest operations in the world and in
Turkey as well in recent years. These winches are very useful machines in terms of installation and
uninstallation. In this study, the use of portable winch in the Sahilçamı plantation areas within the
boundaries of Sarıyer Forest Operation Directorate affiliated to the Istanbul Forest Regional
Directorate has been examined. As a result of the studies, the hourly yield of the portable winch at an
average skid distance of 50 meters was found as 1.110 m3/hr and the daily yield was found as 8.800
m3/day. Hourly fuel consumption of the hand winch was determined as 1.4 lt/h
Technical features and working principles of valmet 911 harvester
Tomruk üretimi hala pek çok önemli ormancılık aktivitelerinden biridir. Gelişmiş ülkelerde ormancılık
çalışmaları içerisinde yer alan orman ürünlerinin üretimi ve taşınmasında teknoloji en iyi şekilde
kullanılmaktadır. Orman makinelerinin verimliliği; arazi koşulları ve bitki özelliklerine göre farklı ekolojik
durumlara ve onların negatif - pozitif etkilerine bağlıdır. Orman ürünlerinin kalite ve kantite kaybı olmaksızın
bölmeden çıkarılması tehlikeli, güç ve masraflı bir süreci oluşturmaktadır. Günümüzde, gelişmiş ülkelerde
üretim alanında ağaçların kesilmesi, kabuklarının soyulması, tomruklanması, bölmeden çıkarılması, yüklenmesi,
taşınması, boşaltılması ve istiflenmesi çalışmalarının büyük bir bölümü makineler ile yapılmaktadır. Bu
çalışmada, Valmet 911 üretim aracının teknik özellikleri ve çalışma prensipleri incelenmiş ve ülkemizde bu
makinenin kullanılabilirliği tartışılmıştır.The production of timber is still one of the most important forestry practical. In developed countries,
the best way of advanced technologies is used to production and transport of forest products with in the
forest activities. The productivity of forest machines depends on various ecological factors as terrain
conditions and plant features and their positive and negative effects. The extraction and production process of
forest products without loss of quality and quantity is an important subject. A large part of processes as
cutting tree, barking, preparing of timber, hauling, loading, transporting, unloading and stacking are done
with machines. In this study, the technical features and working principles of Valmet 911 harvester are
investigated and the availability of these machines in Turkey is discussed
Investigation of forest road construction technique by bulldozer in Eskisehir region
Bu çalışmada, Eskişehir bölgesindeki ormanlarda orman yol yapım teknikleri, çevresel zararlar ve
dozerin yol yapımı sırasındaki verimliliği araştırılmıştır. Çalışmada, yol üzerinde enkesitler alınarak dozerin kazı
ve dolgu şevleri incelenmiştir. Yol yapımı esnasında maksimum dolgu şevi uzunluğu %70 eğimde 17 m olarak
bulunmuştur. Dozerin maliyeti 8.5 8.5 per meter and average productivity of
bulldozer was found 105.8 m3
/hr. The types of damages on trees are determined. These types are wounded,
bending and crushing. 40% of trees under road fill during road construction are occured for 36-70 % ground
slop
Simplified Indirect Bonding Technique for Lingual Retainer Fabrication
Aim:The aim of this study was to describe a simplified technique for fabricating an indirectly bonded lingual retainer using a light cure composite resin and clear tape.Subjects and Methods:Lingual retainers, made of dead soft wire, were bended to the lingual contour of the lower incisors on the stone models of patients and placed to the mouth. Fabricating lingual retainers with this method were used in 6 patients who were followed for 6 months.Results:During this period, failures occurred in 2 teeth. One failure was on a canine; the other one is on an incisor.Conclusion:Due to the isolation done with a clear tape in this method, there is no need for an extra procedure for the removal of the remnants of the separating medium from the resin surface. These extra procedures applied can cause the degradation of the resin surface which may lead to bonding failure
Adaptive Diffusion Priors for Accelerated MRI Reconstruction
Deep MRI reconstruction is commonly performed with conditional models that
de-alias undersampled acquisitions to recover images consistent with
fully-sampled data. Since conditional models are trained with knowledge of the
imaging operator, they can show poor generalization across variable operators.
Unconditional models instead learn generative image priors decoupled from the
imaging operator to improve reliability against domain shifts. Recent diffusion
models are particularly promising given their high sample fidelity.
Nevertheless, inference with a static image prior can perform suboptimally.
Here we propose the first adaptive diffusion prior for MRI reconstruction,
AdaDiff, to improve performance and reliability against domain shifts. AdaDiff
leverages an efficient diffusion prior trained via adversarial mapping over
large reverse diffusion steps. A two-phase reconstruction is executed following
training: a rapid-diffusion phase that produces an initial reconstruction with
the trained prior, and an adaptation phase that further refines the result by
updating the prior to minimize reconstruction loss on acquired data.
Demonstrations on multi-contrast brain MRI clearly indicate that AdaDiff
outperforms competing conditional and unconditional methods under domain
shifts, and achieves superior or on par within-domain performance
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