Iterative methodology on locating a cement plant

In this study, a cement plant location was determined by considering essential parameters such as the locations of resources and their importance in the manufacturing process. A crucial mathematical problem, named Weber problem, reinforced the decision of the method of allocating the factory. Additionally, not only the limitations of the cement production but also the importance weights of goods used in the manufacturing were taken into account in the iterative methodology in order to answer the engineering question via the mathematical problem. As a result, by optimizing the case through the iterations introduced in the paper, the location of the cement plant was set. Hence several losses such as extra travel distances and time wasting in transportation were minimized.No sponso

Comparison of thermal performances of plywood shear walls produced with different thermal insulation materials

Shear walls are one of the envelopes of light-frame wooden buildings where thermal insulation is most required. The thermal performance of shear walls can vary according to the type, properties and thickness of the wood and insulation materials used in their production. In this study, it was aimed to compare the thermal performances of plywood shear walls produced with different thermal insulation materials. For this aim, the archetype walls with properties similar to commonly used plywood shear walls were designed and produced for each thermal insulation material type and wood specie. The shear wall groups were formed by using Scots pine (Pinus sylvestris), black pine (Pinus nigra) and spruce (Picea orientalis) as wood species and cellulose, flax, felt, XPS, EPS, sheep’s, rock and glass wool as thermal insulation materials. Thermal conductivity of the shear wall groups was determined according to the ASTM C518-04 standard. Thermal resistance and other thermal performance parameters were calculated using the thermal conductivity values. As a result of the study, rock wool was the best thermal insulation material among the Scots pine shear wall groups while glass wool was the best thermal insulation material among the black pine and spruce shear wall groups. The shear walls produced with EPS foam boards indicated the worst thermal performance among all group

Ultrafine conducting fibers: metallization of poly(acrylonitrile-co-glycidyl methacrylate) nanofibers

Electrospun poly(glycidylmethacrylate) (PGMA) and poly(acrylonitrile-co-glycidyl methacrylate) (P(AN-GMA)) nanofibers were coated with monodisperse silver nanoparticles by using an electroless plating technique at ambient conditions. Oxirane groups on the surface of nanofibers were replaced with reducing agent, hydrazine. Surface modified nanofibers were allowed to react with ammonia solution of AgNO3. A redox reaction takes place and metallic silver nucleate on fibers surface. Parameters affecting the particle size were determined

Explainable Transformer Prototypes for Medical Diagnoses

Deployments of artificial intelligence in medical diagnostics mandate not just accuracy and efficacy but also trust, emphasizing the need for explainability in machine decisions. The recent trend in automated medical image diagnostics leans towards the deployment of Transformer-based architectures, credited to their impressive capabilities. Since the self-attention feature of transformers contributes towards identifying crucial regions during the classification process, they enhance the trustability of the methods. However, the complex intricacies of these attention mechanisms may fall short of effectively pinpointing the regions of interest directly influencing AI decisions. Our research endeavors to innovate a unique attention block that underscores the correlation between 'regions' rather than 'pixels'. To address this challenge, we introduce an innovative system grounded in prototype learning, featuring an advanced self-attention mechanism that goes beyond conventional ad-hoc visual explanation techniques by offering comprehensible visual insights. A combined quantitative and qualitative methodological approach was used to demonstrate the effectiveness of the proposed method on the large-scale NIH chest X-ray dataset. Experimental results showed that our proposed method offers a promising direction for explainability, which can lead to the development of more trustable systems, which can facilitate easier and rapid adoption of such technology into routine clinics. The code is available at www.github.com/NUBagcilab/r2r_proto