Domain-Specific Deep Learning Feature Extractor for Diabetic Foot Ulcer Detection

Diabetic Foot Ulcer (DFU) is a condition requiring constant monitoring and evaluations for treatment. DFU patient population is on the rise and will soon outpace the available health resources. Autonomous monitoring and evaluation of DFU wounds is a much-needed area in health care. In this paper, we evaluate and identify the most accurate feature extractor that is the core basis for developing a deep-learning wound detection network. For the evaluation, we used mAP and F1-score on the publicly available DFU2020 dataset. A combination of UNet and EfficientNetb3 feature extractor resulted in the best evaluation among the 14 networks compared. UNet and Efficientnetb3 can be used as the classifier in the development of a comprehensive DFU domain-specific autonomous wound detection pipeline.Comment: 5 pages, 2 figures, 3 tables, 2022 IEEE International Conference on Data Mining Workshop

A DNN-based image retrieval approach for detection of defective area in carbon fiber reinforced polymers through LDV data

Carbon fiber reinforced polymer (CFRP) materials, due to their specific strength and high consistency against erosion and corrosion, are widely used in industrial applications and high-tech engineering structures. However, there are also disadvantages: e.g. they are prone to different kinds of internal defects which could jeopardize the structural integrity of the CFRP material and therefore early detection of such defects can be an important task. Recently, local defect resonance (LDR), which is a subcategory of ultrasonic nondestructive testing, has been successfully used to solve this issue. However, the drawback of utilizing this technique is that the frequency at which the LDR occurs must be known. Further, the LDR-based technique has difficulty in assessing deep defects. In this paper, deep neural network (DNN) methodology is employed to remove this limitation and to acquire a better defect image retrieval process and also to achieve a model for the approximate depth estimation of such defects. In this regards, two types of defects called flat bottom holes (FBH) and barely visible impact damage (BVID) which are made in two CFRP coupons are used to evaluate the ability of the proposed method. Then, these two CFRPs are excited with a piezoelectric patch, and their corresponding laser Doppler vibrometry (LDV) response is collected through a scanning laser Doppler vibrometer (SLDV). Eventually, the superiority of our DNN-based approach is evaluated in comparison with other well-known classification methodologies

Optimization Model for Maintenance Planning of Loading Equipment in Open Pit Mines

Maintenance plays a significant role in operating costs in the mining industry. Improving this matter controls maintenance costs and enhances productivity and production effectively. Shovels are one of the most widely used loading machines in non-continuous activities. Thus, evaluating and optimizing their availability is one of the essential solutions to achieving high productivity and cost reduction. This paper presents a mathematical programming model to maximize availability and minimize the total expected costs. We programmed the proposed nonlinear planning model using the Symbiotic Organisms Search (SOS) meta-heuristic algorithm in Matlab software. It determines the optimal maintenance intervals for different parts of the shovel. The maintenance benefit analysis approach selects various maintenance activities in optimal maintenance intervals. The model is implemented in a practical case study, Chadormalu Iron Mine, to evaluate its performance. The failure distribution matches the Weibull distribution function. The computational results show the efficiency of the presented approach

PREGLED ODRŽIVOGA RAZVOJA I ODRŽIVOSTI OKOLIŠA U RUDARSKOJ DJELATNOSTI

A comprehensive systemic approach is needed to make effective decisions for global sustainability. The system’s points of view introduced sustainable development (S.D.) and sustainability in prior years. Sustainable development is expressed as a desire followed by humanity to live in a better condition considering all the limits that nature could have. Social, environmental, and economic responsibilities are the wide-ranging developmental characteristics that form sustainability. In this paper, with the help of search engines like Scopus and Web of Science, several documents related to environmental sustainability in the mining industry were studied. The principal investigated problems were tailings dam failure, forestland use in mining operations, social and environmental issues in crushed stone mining industries, landfill mining challenges, climatic problems, economic problems, and fatalities in artisanal and small-scale mines. Also, a table was designed to categorise these problems and determine the solution and primary goal. This study investigates the severity of mining operation conditions and environmental issues in this industry. The common environmental problems in the mining industry include soil degradation, deforestation, land subsidence, acid mine drainage, waste production, natural landscape destruction, coal production, carbon footprint, dust pollution, greenhouse gas emissions and climatic problems. To have a more sustainable mining industry, all the mining stages, from the exploration to the post-closure stages, must minimise resource and energy consumption and waste products.Za donošenje učinkovitih odluka u sklopu globalne održivosti potreban je sveobuhvatan sustavan pristup, što posebno dolazi do izražaja prethodnih godina. Održivi razvoj izražava se kao želja čovječanstva za životom u boljim uvjetima uzimajući u obzir moguća ograničenja prirode. Društvene, ekološke i ekonomske odgovornosti ubrajaju se među brojne karakteristike razvoja koje čine održivost. U ovome radu, uz pomoć tražilica poput Scopusa i Web of Science, proučavano je nekoliko dokumenata vezanih uz održivost okoliša u rudarskoj industriji. Glavni fokusi studija vezani su uz probleme kao što su klizanje jalovišta, korištenje šumskoga zemljišta u rudarskim radovima, socijalna i ekološka pitanja u eksploataciji i proizvodnji tehničko-građevnoga kamena, izazovi eksploatacije na odlagalištima, klimatski problemi, ekonomski problemi i smrtni slučajevi u privatnim i malim rudnicima. Također, osmišljena je tablica koja kategorizira te probleme i njihova rješenja te primarni cilj. Ova studija istražuje važnost radnih uvjeta u rudarstvu i probleme okoliša u rudarskoj industriji. Uobičajeni ekološki problemi u toj industriji uključuju degradaciju tla, krčenje šuma, slijeganje zemljišta, odvodnju kiselih otpadnih voda iz rudnika, proizvodnju otpada, degradaciju prirodnoga krajolika, proizvodnju ugljena, ugljični otisak, onečišćenje prašinom, emisije stakleničkih plinova i klimatske probleme. Kako bismo imali održiviju rudarsku industriju, sve faze rudarstva, od istraživanja do faza nakon zatvaranja, moraju minimizirati potrošnju resursa i energije te otpadne proizvode

Synthesizing Diabetic Foot Ulcer Images with Diffusion Model

Diabetic Foot Ulcer (DFU) is a serious skin wound requiring specialized care. However, real DFU datasets are limited, hindering clinical training and research activities. In recent years, generative adversarial networks and diffusion models have emerged as powerful tools for generating synthetic images with remarkable realism and diversity in many applications. This paper explores the potential of diffusion models for synthesizing DFU images and evaluates their authenticity through expert clinician assessments. Additionally, evaluation metrics such as Frechet Inception Distance (FID) and Kernel Inception Distance (KID) are examined to assess the quality of the synthetic DFU images. A dataset of 2,000 DFU images is used for training the diffusion model, and the synthetic images are generated by applying diffusion processes. The results indicate that the diffusion model successfully synthesizes visually indistinguishable DFU images. 70% of the time, clinicians marked synthetic DFU images as real DFUs. However, clinicians demonstrate higher unanimous confidence in rating real images than synthetic ones. The study also reveals that FID and KID metrics do not significantly align with clinicians' assessments, suggesting alternative evaluation approaches are needed. The findings highlight the potential of diffusion models for generating synthetic DFU images and their impact on medical training programs and research in wound detection and classification.Comment: 8 pages, 3 figures, 6th Workshop on AI for Aging, Rehabilitation and Intelligent Assisted Living at European Conference on Machine Learning, Italy, 202

Phytoremediation of Contaminated Soils to Sludge of Oil Reservoirs using Prosopis juliflora (Sw.) DC.

Oil contaminated soil is a vital threat to the environment. The aim of the present research was to investigate the total petroleum hydrocarbon (TPH), and heavy metals of nickel and vanadium reduction using Prosopis juliflora, under different treatments of biochar and compost in pots. One-year-old P. juliflora seedlings were planted in pots containing oil sludge. The pots included 1 and 2% of compost and biochar. Furthermore, two control treatments including with and without P. juliflora were used for the study. This study was conducted in the complete randomized plot sampling with three replications. After six months, soil samples were taken from the pots and transferred to the laboratory. Then, the concentration of TPH, nickel, and vanadium was determined. The results indicated that the least TPH belonged to the compost 2% treatment (10.63 ppm), which was significantly different compared with other studied treatments. The highest value belonged to the control treatment without P. juliflora (22.57 ppm). The highest value of vanadium belonged to the control treatment (69.50 mg/kg). Compost 2% had the least values of vanadium (47.66 mg/kg). Comparison between treatments showed no significant differences among compost 1% (117.17 mg/kg), compost 2% (118.00 mg/kg), and biochar 2% (116.67 mg/kg). The highest reduction of nickel was observed within the mentioned treatments. Therefore, using biochar and compost can improve the phytoremediation capacity of P. juliflora

Interleukin-6 and airflow limitation in chemical warfare patients with chronic obstructive pulmonary disease

Objectives: Chronic obstructive pulmonary disease (COPD) is one of the main late complications of sulfur mustard poisoning. The aim of this study was to evaluate serum levels of interleukin (IL)-6 in war veterans with pulmonary complications of sulfur mustard poisoning and their correlation with severity of airways disease. Methods: Fifty consecutive patients with sulfur mustard poisoning and stable COPD, and of mean age 46.3 ± 9.18 years were enrolled in this study. Thirty healthy men were selected as controls and matched to cases by age and body mass index. Spirometry, arterial blood gas, six-minute walk test, BODE (body mass index, obstruction, dyspnea, and exercise capacity), and St George’s Respiratory Questionnaire about quality of life were evaluated. Serum IL-6 was measured in both patient and control groups. Results: Fifty-four percent of patients had moderate COPD. Mean serum IL-6 levels were 15.01 ± standard deviation (SD) 0.61 pg/dL and 4.59 ± 3.40 pg/dL in the case and control groups, respectively (P = 0.03). There was a significant correlation between IL-6 levels and Global Initiative for Chronic Obstructive Lung Disease stage (r = 0.25, P = 0.04) and between IL-6 and BODE index (r = 0.38, P = 0.01). There was also a significant negative correlation between serum IL-6 and forced expiratory volume in one second (FEV1, r = −0.36, P = 0.016). Conclusion: Our findings suggest that serum IL-6 is increased in patients with sulfur mustard poisoning and COPD, and may have a direct association with airflow limitation

Primary Adenocarcinoma of the Urethra: A Case Report and Review of the Literature

Abstract Primary adenocarcinoma of the urethra is rarely reported. We report a case of a 47-year-old male with symptoms of urinary obstruction started 2 years before diagnosis. Video-assisted urethrocystoscopy revealed a papillary mass almost obstructing the entire lumen with bleeding. Pathology report was consistent with primary adenocarcinoma of the urethra