Assessment of the Effectiveness of Thermographic and Computer Vision Techniques in Analyzing Thermal Phenomena during Drilling: Wood-Based Materials Perspective DOI
Patryk Król, Piotr Podziewski,

Dritan Ajdinaj

и другие.

Annals of WULS Forestry and Wood Technology, Год журнала: 2023, Номер 124, С. 36 - 44

Опубликована: Дек. 26, 2023

A new direction related to research in the wood industry may be thermal imaging together with computer vision techniques. In this work, an attempt was made use these record temperature phenomena during drilling woodbased materials, using MDF as example. For purpose, a CNC station created built-in high-resolution camera (260x200 px). Two drill bits were examined – sharp and dull. The temperatures generated by them compared. It shown that which can recorded process associated changes tool geometry, therefore used for heat drilling. presented results open many interesting directions wood-based materials technology.

Язык: Английский

Predicting compressive strength of grouted masonry using machine learning models with feature importance analysis DOI
Navaratnarajah Sathiparan

Materials Today Communications, Год журнала: 2024, Номер unknown, С. 110487 - 110487

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

6
Leveraging explainable machine learning for enhanced management of lake water quality DOI

Sajad Soleymani Hasani,

Mauricio E. Arias,

Hung Quang Nguyen

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 370, С. 122890 - 122890

Опубликована: Окт. 13, 2024

Язык: Английский

Процитировано

4
Current Trends in Monitoring and Analysis of Tool Wear and Delamination in Wood-Based Panels Drilling DOI Creative Commons
Tomasz Trzepieciński, Krzysztof Szwajka, Joanna Zielińska-Szwajka

и другие.

Machines, Год журнала: 2025, Номер 13(3), С. 249 - 249

Опубликована: Март 20, 2025

Wood-based panels (WBPs) have versatile structural applications and are a suitable alternative to plastic metallic materials. They appropriate strength parameters that provide the required stiffness for furniture products construction applications. WBPs usually processed by cutting, milling drilling. Especially in industry, accuracy of processing is crucial aesthetic reasons. Ensuring WBP surface’s high quality production cycle associated with selection tools adapted specificity material (properties wood, glue, type resin possible contamination). Therefore, expert assessment durability difficult. The interest automatic monitoring cutting sustainable production, according concept Industry 4.0, constantly growing. use flexible automation machining related provision state tool wear surface quality. Drilling most common process prepares assembly operations directly affects holes appearance products. This paper aimed synthesize research findings across Medium-Density Fiberboards (MDFs), particleboards oriented strand boards (OSBs), highlighting impact identifying areas future investigation. article presents trend adoption new general methodological assumptions allow one define both drill condition delamination drilling commonly used wood-based boards, i.e., particleboards, MDFs OSBs.

Язык: Английский

Процитировано

0
Enhancing multiclass COVID-19 prediction with ESN-MDFS: Extreme smart network using mean dropout feature selection technique DOI Creative Commons
Saghir Ahmed, Basit Raza, Lal Hussain

и другие.

PLoS ONE, Год журнала: 2024, Номер 19(11), С. e0310011 - e0310011

Опубликована: Ноя. 12, 2024

Deep learning and artificial intelligence offer promising tools for improving the accuracy efficiency of diagnosing various lung conditions using portable chest x-rays (CXRs). This study explores this potential by leveraging a large dataset containing over 6,000 CXR images from publicly available sources. These encompass COVID-19 cases, normal patients with viral or bacterial pneumonia. The research proposes novel approach called "Enhancing COVID Prediction ESN-MDFS" that utilizes combination an Extreme Smart Network (ESN) Mean Dropout Feature Selection Technique (MDFS). aimed to enhance multi-class condition detection in X-rays combining static texture features dynamic deep extracted pre-trained VGG-16 model. To optimize performance, preprocessing, data imbalance, hyperparameter tuning were meticulously addressed. proposed ESN-MDFS model achieved peak 96.18% AUC 1.00 six-fold cross-validation. Our findings demonstrate model's superior ability differentiate between COVID-19, pneumonia, conditions, significant advancements diagnostic efficiency.

Язык: Английский

Процитировано

0
Assessment of the Effectiveness of Thermographic and Computer Vision Techniques in Analyzing Thermal Phenomena during Drilling: Wood-Based Materials Perspective DOI
Patryk Król, Piotr Podziewski,

Dritan Ajdinaj

и другие.

Annals of WULS Forestry and Wood Technology, Год журнала: 2023, Номер 124, С. 36 - 44

Опубликована: Дек. 26, 2023

A new direction related to research in the wood industry may be thermal imaging together with computer vision techniques. In this work, an attempt was made use these record temperature phenomena during drilling woodbased materials, using MDF as example. For purpose, a CNC station created built-in high-resolution camera (260x200 px). Two drill bits were examined – sharp and dull. The temperatures generated by them compared. It shown that which can recorded process associated changes tool geometry, therefore used for heat drilling. presented results open many interesting directions wood-based materials technology.

Язык: Английский

Процитировано

0