Search results for: skin or non-skin classification

Authors: Sunday Nathaniel Obasi, Chiamak Chinasa Obasi

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Soil characterization and classification provide the basic information necessary to create a functional evaluation and soil classification schemes. Fertility capability classification (FCC) on the other hand is a technical system that groups the soils according to kinds of problems they present for management of soil physical and chemical properties. This research was carried out in Ebonyi state, southeastern Nigeria, which is an agrarian state and a leading rice producing part of southeastern Nigeria. In order to maximize the soil and enhance the productivity of rice in Ebonyi soils, soil classification, and fertility classification information need to be supplied. The state was grouped into three locations according to their agricultural zones namely; Ebonyi north, Ebonyi central and Ebonyi south representing Abakaliki, Ikwo and Ivo locations respectively. Major rice growing areas of the soils were located and two profile pits were sunk in each of the studied zones from which soils were characterized, classified and fertility capability classification (FCC) developed. Soil classification was done using United State Department of Agriculture (USDA) Soil Taxonomy and correlated with World Reference Base for soil resources. Results obtained classified Abakaliki 1 and Abakaliki 2 as Typic Fluvaquents (Ochric Fluvisols). Ikwo 1 was classified as Vertic Eutrudepts (Eutric Vertisols) while Ikwo 2 was classified as Typic Eutrudepts (Eutric Cambisols). Ivo 1 and Ivo 2 were both classified as Aquic Eutrudepts (Gleyic Leptosols). Fertility capability classification (FCC) revealed that all studied soils had mostly loamy topsoils and subsoils except Ikwo 1 with clayey topsoil. Limitations encountered in the studied soils include; dryness (d), low ECEC (e), low nutrient capital reserve (k) and water logging/ anaerobic condition (gley). Thus, FCC classifications were Ldek for Abakaliki 1 and 2, Ckv for Ikwo 1, LCk for Ikwo 2 while Ivo 1 and 2 were Legk and Lgk respectively.

Keywords: soil classification, soil fertility, limitations, modifiers, Southeastern Nigeria

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Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

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The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: K. K. Balavenkatraman, B. Bertschi, K. Bigot, A. Grevot, A. Doelemeyer, S. D. Chibout, A. Wolf, F. Pognan, N. Manevski, O. Kretz, P. Swart, K. Litherland, J. Ashton-Chess, B. Ling, R. Wettstein, D. J. Schaefer

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Skin toxicity is poorly detected during preclinical studies, and drug-induced side effects in humans such as rashes, hyperplasia or more serious events like bullous pemphigus or toxic epidermal necrolysis represent an important hurdle for clinical development. In vitro keratinocyte-based epidermal skin models are suitable for the detection of chemical-induced irritancy, but do not recapitulate the biological complexity of full skin and fail to detect potential serious side-effects. Normal healthy skin explants may represent a valuable complementary tool, having the advantage of retaining the full skin architecture and the resident immune cell diversity. This study investigated several conditions for the maintenance of good morphological structure after several days of culture and the retention of phase II metabolism for 24 hours in skin explants in vitro. Human skin samples were collected with informed consent from patients undergoing plastic surgery and immediately transferred and processed in our laboratory by removing the underlying dermal fat. Punch biopsies of 4 mm diameter were cultured in an air-liquid interface using transwell filters. Different cultural conditions such as the effect of calcium, temperature and cultivation media were tested for a period of 14 days and explants were histologically examined after Hematoxylin and Eosin staining. Our results demonstrated that the use of Williams E Medium at 32°C maintained the physiological integrity of the skin for approximately one week. Upon prolonged incubation, the upper layers of the epidermis become thickened and some dead cells are present. Interestingly, these effects were prevented by addition of EGFR inhibitors such as Afatinib or Erlotinib. Phase II metabolism of the skin such as glucuronidation (4-methyl umbeliferone), sulfation (minoxidil), N-acetyltransferase (p-toluidene), catechol methylation (2,3-dehydroxy naphthalene), and glutathione conjugation (chlorodinitro benzene) were analyzed by using LCMS. Our results demonstrated that the human skin explants possess metabolic activity for a period of at least 24 hours for all the substrates tested. A time course for glucuronidation with 4-methyl umbeliferone was performed and a linear correlation was obtained over a period of 24 hours. Longer-term culture studies will indicate the possible evolution of such metabolic activities. In summary, these results demonstrate that human skin explants maintain a normal structure for several days in vitro and are metabolically active for at least the first 24 hours. Hence, with further characterisation, this model may be suitable for the study of drug-induced toxicity.

Keywords: human skin explant, phase II metabolism, epidermal growth factor receptor, toxicity

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: classification, data mining, decision tree, scholarship

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Authors: Akhtar Naveed, Kanwal Shahla, Khan HMS, Rasool Fatima, Ijaz Shakeel

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The focus of the study was to design, develop and characterize in vivo, a stable Emulgel formulation containing Anacardium occidentale L.(cashew extract) as an active ingredient. The formulation was prepared and kept at 8ºC, 25 ºC, 40ºC and 40ºC±RH for a period of 28 days. During this time period, stability, pH values, conductivity, organoleptic features (color, liquefaction, phase separation) were conducted at the intervals of day 1st, 2nd, 3rd , 7th, 14th and 28th days. In In vivo studies, the test formulation (5% Anacardium occidentale L, extract) and a base formulation (without cashew extract) were prepared and both were applied on cheek areas of healthy human female volunteers, after the skin sensitivity test of each volunteer, for a study period of 8 weeks after getting consent from them. Various parameters of skin like Melanin level, Erythema level, and skin elasticity were measured at regular time intervals. Results of the study were analyzed by statistical techniques i.e. Two Way ANOVA and paired sample t-test. The result showed significant results as the p ≤ 0.05. Findings of paired sample t-test explained that test formulation have profound effects on skin parameters when compared with control formulation.

Keywords: Anacardium occientale L., anti-oxidant, cashew nut, emulgel

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words (BOVW), classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar (PolSAR)

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

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Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

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Authors: Aya Al Masri, Stefaan Carpentier, Fabrice Leroy, Thibault Julien, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: During an 'Interventional Radiology (IR)' procedure, the patient's skin-dose may become very high for a burn, necrosis and ulceration to appear. In order to prevent these deterministic effects, an accurate calculation of the patient skin-dose mapping is essential. For most machines, the 'Dose Area Product (DAP)' and fluoroscopy time are the only information available for the operator. These two parameters are a very poor indicator of the peak skin dose. We developed a mathematical model that reconstructs the magnitude (delivered dose), shape, and localization of each irradiation field on the patient skin. In case of critical dose exceeding, the system generates warning alerts. We present the results of its comparison with clinical studies. Materials and methods: Two series of comparison of the skin-dose mapping of our mathematical model with clinical studies were performed: 1. At a first time, clinical tests were performed on patient phantoms. Gafchromic films were placed on the table of the IR machine under of PMMA plates (thickness = 20 cm) that simulate the patient. After irradiation, the film darkening is proportional to the radiation dose received by the patient's back and reflects the shape of the X-ray field. After film scanning and analysis, the exact dose value can be obtained at each point of the mapping. Four experimentation were performed, constituting a total of 34 acquisition incidences including all possible exposure configurations. 2. At a second time, clinical trials were launched on real patients during real 'Chronic Total Occlusion (CTO)' procedures for a total of 80 cases. Gafchromic films were placed at the back of patients. We performed comparisons on the dose values, as well as the distribution, and the shape of irradiation fields between the skin dose mapping of our mathematical model and Gafchromic films. Results: The comparison between the dose values shows a difference less than 15%. Moreover, our model shows a very good geometric accuracy: all fields have the same shape, size and location (uncertainty < 5%). Conclusion: This study shows that our model is a reliable tool to warn physicians when a high radiation dose is reached. Thus, deterministic effects can be avoided.

Keywords: clinical experimentation, interventional radiology, mathematical model, patient's skin-dose mapping.

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Authors: Venkata Buddharaju, Irene Mccarron, Hazel Alba

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Introduction: Male external catheters (MECs) are commonly used to collect and drain urine. MECs are increasingly used in acute care, long-term acute care hospitals, and nursing facilities, and in other patients as an alternative to invasive urinary catheters to reduce catheter-associated urinary tract infections (CAUTI).MECs are also used to avoid the need for incontinence pads and diapers. Most of the Male External Catheters are held in place by skin adhesive, with the exception of a few, which uses a foam strap clamp around the penile shaft. The adhesive condom catheters typically stay for 24 hours or less. It is also a common practice that extra skin adhesive tape is wrapped around the condom catheter for additional security of the device. The fixed nature of the adhesive will not allow the normal skin expansion of penile size over time. The adhesive can cause skin irritation, redness, erosion, and skin damage. Acanthus condom catheter (ACC) is a patented, specially designed, stretchable silicone catheter without adhesive, adapts to the size and contour of the penis. It is held in place with a single elastic strap that wraps around the lower back and tied to the opposite catheter ring holescriss cross. It can be reused for up to 5 days on the same patient after daily cleaning and washingpotentially reducing cost. Methods: The study was conducted from September 17th to October 8th, 2020. The nursing staff was educated and trained on how to use and reuse the catheter. After identifying five (5) appropriate patients, the catheter was placed and maintained by nursing staff. The data on the ease of use, leak, and skin damage were collected and reported by nurses to the nursing education department of the hospital for analysis. Setting: RML Chicago, long-term acute care hospital, an affiliate of Loyola University Medical Center, Chicago, IL USA. Results: The data showed that the catheter was easy to apply, remove, wash and reuse, without skin problems or urine infections. One patient had used for 16 days after wash, reuse, and replacement without any urine leak or skin issues. A minimal leak was observed on two patients. Conclusion: Acanthus condom catheter was easy to use, functioned well with minimal or no leak during use and reuse. The skin was intact in all patients studied. There were no urinary tract infections in any of the studied patients.

Keywords: CAUTI, male external catheter, reusable, skin adhesive

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Authors: Najoua El Hajjaji El Idrissi, Necip Gokhan Kasapoglu

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Polarimetric Synthetic Aperture Radar-based imaging is a powerful technique used for earth observation and classification of surfaces. Forest evolution has been one of the vital areas of attention for the remote sensing experts. The information about forest areas can be achieved by remote sensing, whether by using active radars or optical instruments. However, due to several weather constraints, such as cloud cover, limited information can be recovered using optical data and for that reason, Polarimetric Synthetic Aperture Radar (PolSAR) is used as a powerful tool for forestry inventory. In this [14paper, we applied support vector machine (SVM) and Mahalanobis distance to the fully polarimetric AIRSAR P, L, C-bands data from the Nezer forest areas, the classification is based in the separation of different tree ages. The classification results were evaluated and the results show that the SVM performs better than the Mahalanobis distance and SVM achieves approximately 75% accuracy. This result proves that SVM classification can be used as a useful method to evaluate fully polarimetric SAR data with sufficient value of accuracy.

Keywords: classification, synthetic aperture radar, SAR polarimetry, support vector machine, mahalanobis distance

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Authors: Savita Dixit

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Rutin is the bioactive flavonoid isolated from the straw part of Triticum aestivum and possess various pharmacological applications. The aim of this study is to evaluate the chemopreventive potential of rutin in an experimental skin carcinogenesis mice model system. Skin tumor was induced by topical application of 7, 12-dimethyl benz(a) anthracene (DMBA) and promoted by croton oil in Swiss albino mice. To assess the chemopreventive potential of rutin, it was orally administered at a concentration of (200 mg/kg and 400 mg/kg body weight) continued three times weekly for 16th weeks. The development of skin carcinogenesis was assessed by histopathological analysis. Reductions in tumor size and cumulative number of papillomas were seen due to rutin treatment. Average latent period was significantly increased as compared to carcinogen-treated control. Rutin produced a significant decrease in the activity of serum enzyme serum glutamate oxalate transaminase (SGOT), serum glutamate pyruvate transaminase (SGPT), alkaline phosphatase (ALP) and bilirubin when compared with the control. They significantly increased the levels of enzyme involved in oxidative stress glutathione (GSH), superoxide dismutase (SOD) and catalase. The elevated level of lipid peroxidase in the control group was significantly inhibited by rutin administration. The results of the present study suggest the chemopreventive effect of rutin in DMBA and croton oil-induced skin carcinogenesis in swiss albino mice and one of the probable reasons would be its antioxidant potential.

Keywords: chemoprevention, papilloma, rutin, skin carcinogenesis

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Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Renata Karina Reis, Soraia Assad Nasbine Rabeh, Mayra Gonçalves Menegueti, Ana Cristina de Oliveira e Silva, Sheila Araújo Teles

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Context and significance: Nursing team professionals faced challenges in combating the COVID-19 pandemic around the world. They were subjected to exhausting workloads and prolonged use of Personal Protective Equipment. Using N95 masks for long periods of time can cause skin changes. In this context, health professionals who worked on the front lines of fighting the pandemic were more exposed to possible physical and psychological changes. Objective: The aim of the study was to analyze the factors associated with skin lesions resulting from the use of N95 masks among nursing team professionals. Method: The study was carried out in all regions of Brazil from October to December 2020, with professionals from the nursing team who worked in health care during the COVID-19 pandemic. Participants were recruited via social media, and information was collected electronically and stored on the Survey Monkey platform. Descriptive statistics were used to characterize the sample, association tests (Chi-square), with a statistical significance level of p < 0.05. Factors associated with skin lesions resulting from the use of an N95 mask were determined by Binary Logistic Regression, with a significance level of 5% (α = 0.05). Results: 8,405 nursing professionals participated in the study, 5,492 nurses (65.3%), 2,747 nursing technicians (32.7%), and 7,084 females (84.3%). Female nursing team professionals were 1.4 times more likely to develop skin lesions due to the use of N95 masks when compared to males (OR 1.4 [CI95% 1.22 – 1.59] p < 0.001). The following protective factors were identified: nursing technician (ORA 0.608 [CI95% 0.43 – 0.86] p = 0.005) and not having provided assistance in field hospitals for COVID-19 (0.73 [CI95% 0.65-0.81] p<0.000). Conclusion: It was concluded that female nursing team professionals were more likely to have skin changes related to the use of N95 masks. The need for intervention studies is emphasized in order to explore measures to prevent these types of injuries. Descritores: Nursing professionals; COVID-19; SARS-CoV-2; Brazil.

Keywords: nursing professionals, COVID-19, SARS-CoV-2, Brazil

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Authors: Stefaan Carpentier, Aya Al Masri, Fabrice Leroy, Thibault Julien, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: During an 'Interventional Radiology (IR)' procedure, the patient's skin-dose may become very high for a burn, necrosis, and ulceration to appear. In order to prevent these deterministic effects, a prediction of the peak skin-dose for the patient is important in order to improve the post-operative care to be given to the patient. The objective of this study is to estimate, before the intervention, the patient dose for ‘Chronic Total Occlusion (CTO)’ procedures by selecting relevant clinical indicators. Materials and methods: 103 procedures were performed in the ‘Interventional Cardiology (IC)’ department using a Siemens Artis Zee image intensifier that provides the Air Kerma of each IC exam. Peak Skin Dose (PSD) was measured for each procedure using radiochromic films. Patient parameters such as sex, age, weight, and height were recorded. The complexity index J-CTO score, specific to each intervention, was determined by the cardiologist. A correlation method applied to these indicators allowed to specify their influence on the dose. A predictive model of the dose was created using multiple linear regressions. Results: Out of 103 patients involved in the study, 5 were excluded for clinical reasons and 2 for placement of radiochromic films outside the exposure field. 96 2D-dose maps were finally used. The influencing factors having the highest correlation with the PSD are the patient's diameter and the J-CTO score. The predictive model is based on these parameters. The comparison between estimated and measured skin doses shows an average difference of 0.85 ± 0.55 Gy for doses of less than 6 Gy. The mean difference between air-Kerma and PSD is 1.66 Gy ± 1.16 Gy. Conclusion: Using our developed method, a first estimate of the dose to the skin of the patient is available before the start of the procedure, which helps the cardiologist in carrying out its intervention. This estimation is more accurate than that provided by the Air-Kerma.

Keywords: chronic total occlusion procedures, clinical experimentation, interventional radiology, patient's peak skin dose

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Pennisi Stefania, Giuffrida Graziella, Coppa Federica, Iannello Giulia, Cartelli Simone, Lo Faro Riccardo, Ferruggia Greta, Brundo Maria Violetta

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Tissue engineering aims to develop advanced medical devices to restore normal functions of damaged tissue. These devices, even more effective than conventional methods, are called skin substitutes and are configured as drugs to be applied to the damaged area, to heal extensive and deep wounds which could otherwise lead to chronic wounds lasting over time. Among the variety of commercially available skin substitutes, those that have proven to be most effective are those consisting of a bilayer scaffold. The aim of our research was to design a skin substitute which can promote cell proliferation, cell migration and angiogenesis, and which can guarantee timely closure of the wound with satisfactory aesthetic results, in order to avoid the patient excessive pain, risk of contracting infections and long-term hospitalization. The product was tested in vitro using the Scratch Assay. The assay was carried out both on the matrix modified with hyaluronic acid and on the matrix based only on collagen. In both cases, after 48 hours of exposure the wound scratch was almost completely closed in treated cells compared to untreated control.

Keywords: collagen, hyaluronic acid, scratch- wound-healing assay, tissue regeneration

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Authors: Michelle Sánchez de León Brajkovich, Nuria Martí Audi

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The envelope is one of the most important elements when one analyzes the operation of the building in terms of sustainability. Taking this into consideration, this research focuses on setting a classification system of the envelopes opaque systems, crossing the knowledge and parameters of construction systems with requirements in terms of sustainability that they may have, to have a better understanding of how these systems work with respect to their sustainable contribution to the building. Therefore, this paper evaluates the importance of the envelope design on the building sustainability. It analyses the parameters that make the construction systems behave differently in terms of sustainability. At the same time it explains the classification process generated from this analysis that results in a classification where all opaque vertical envelope construction systems enter.

Keywords: sustainable, exterior walls, envelope, facades, construction systems, energy efficiency

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Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

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Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

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Authors: Mohammad F. Bostanudin, Tan S. Fei, Azwan M. Lazim

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Toward the development of colloidal systems that are able to enhance permeation across the skin, a material combining the non-toxic and non-immunogenic of dextran with alkylglycerols permeation enhancing property has been designed. To this purpose, a range of butylglyceryl dextrans (DEX-OX4) were synthesized via functionalization with n-butylglycidyl ether and the successful functionalization was confirmed by NMR and FT-IR spectroscopies, along with GPC with a degree of modification in the range 6.3–35.7 %. A reduced viscosity and an increased molecular weight of DEX-OX4 were also recorded when compared to that of the native dextran. DEX-OX4 was further formulated into nanocarriers and loaded with α-arbutin prior to be investigated for their particle size, morphology, stability, loading ability, and release profiles. The resulting nanoparticles were found to be close-to-spherical and relatively stable at pH 5 and 7, with size 180–220 nm (ζ-potential -22 to -25 mV), and a loading degree of 11.7 %. Lack of toxicity at application-relevant concentrations and increased permeation across skin biological membrane model were demonstrated by nanoparticles in-vitro results against immortalized skin human keratinocytes cells (HaCaT).

Keywords: butylglycerols, dextran, nanoparticles, transdermal

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Authors: Hyo-Su Lim, Ye-Eun Song, Eun-Bi Lee, Sang-Yoon Lee, Young-Il Seo, Jin-Pyo Kim, Nam-Kyu Park

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If we analogize any physical external force given to victims in many crimes including violence, it would be possible not only to presume mutual action between victims and suspects, but to make a deduction of more various facts in cases. Therefore, the aim of this study is to identify criminal tools through secretion on clothes by using amino acid reagents such as Ninhydrin, DFO(1,8-dizafluoren-9-one), 1,2 – IND (1,2-indanedione) which are reacting to skin secretion. For more effective collecting condition, porcine skin which is physiologically similar to human was used. Although there were little differences of shape identification according to sensitivity, amino acid reagents were able to identify the fist, foot, and baseball bat. Furthermore, we conducted the experiments for developmental variations through change over time setting up 5-weeks period including first damage as variation factor, and developing materials in each action through certain reagents. Specimen level of development depending on change over time was identified. As a result, each of initial level of development was seen no changes.

Keywords: hit marks, amino acid reagents, porcine skin, criminal tool

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Authors: M. Zasada, A. Markiewicz, A. Erkiert-Polguj, E. Budzisz

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The epidermis is a keratinized stratified squamous epithelium covered by the hydro-lipid barrier. Therefore, active substances should be able to penetrate through this hydro-lipid coating. L-ascorbic acid is one of the vitamins which plays an important role in stimulation fibroblast to produce collagen type I and in hyperpigmentation lightening. Vitamin C is a water-soluble antioxidant, which protects skin from oxidation damage and rejuvenates photoaged skin. No-needle mesotherapy is a non-invasive rejuvenation technique depending on electric pulses, electroporation, and ultrasounds. These physicals factors result in deeper penetration of cosmetics. It is important to increase the penetration of L-ascorbic acid, thereby increasing the spectrum of its activity. The aim of the work was to assess the effectiveness of pure L-ascorbic acid activity in anti-aging therapy using a needle-free and micro-needling mesotherapy. The study was performed on a group of 35 healthy volunteers in accordance with the Declaration of Helsinki of 1964 and agreement of the Ethics Commissions no RNN/281/16/KE 2017. Women were randomized to mesotherapy or control group. Control group applied topically 2,5 ml serum containing 20% L-ascorbic acid with hydrate from strawberries, every 10 days for a period of 9 weeks. No-needle mesotherapy, on the left half of the face and micro-needling on the right with the same serum, was done in mesotherapy group. The pH of serum was 3.5-4, and the serum was prepared directly prior to the facial treatment. The skin parameters were measured at the beginning and before each treatment. The measurement of the forehead skin was done using Cutometer® (measurement of skin elasticity and firmness), Corneometer® (skin hydration measurement), Mexameter® (skin tone measurement). Also, the photographs were taken by Fotomedicus system. Additionally, the volunteers fulfilled the questionnaire. Serum was tested for microbiological purity and stability after the opening of the cosmetic. During the study, all of the volunteers were taken care of a dermatologist. The regular application of the serum has caused improvement of the skin parameters. Respectively, after 4 and 8 weeks improvement in hydration and elasticity has been seen (Corneometer®, Cutometer® results). Moreover, the number of hyper-pigmentated spots has decreased (Mexameter®). After 8 weeks the volunteers has claimed that the tested product has smoothing and moisturizing features. Subjective opinions indicted significant improvement of skin color and elasticity. The product containing the L-ascorbic acid used with intercellular penetration promoters demonstrates higher anti-aging efficiency than control. In vivo studies confirmed the effectiveness of serum and the impact of the active substance on skin firmness and elasticity, the degree of hydration and skin tone. Mesotherapy with pure L-ascorbic acid provides better diffusion of active substances through the skin.

Keywords: anti-aging, l-ascorbic acid, mesotherapy, promoters

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Authors: Bharatendra Rai

Abstract:

The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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Authors: Manisha, Manisha Mathur, Jay K. Desai, Shesh Asopa, Manisha Mehra

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The present study was carried out for the comprehensive analysis of lumpy skin disease (LSD) in cattle and to elucidate the histopathology of vital organs in natural outbreaks. Lumpy skin disease (LSD) is a viral infection that primarily affects cattle. It is caused by a Capri pox virus and is characterized by the formation of skin nodules or lesions. For this study, a postmortem of 20 cows who died of Lumpy skin disease in different regions of Rajasthan was conducted. This study aimed to examine a cow's external and internal organs to confirm if lumpy skin disease was the cause of death. Accurate diagnosis is essential for improving disease surveillance, understanding the disease's progression, and informing control measures. Pathological examinations reveal virus-induced changes across organs, while histopathological analyses provide crucial insights into the disease's pathogenesis, aiding in the development of advanced diagnostics and effective prevention strategies. Histopathological examination of nodular skin lesions revealed edema, hyperemia, acanthosis, severe hydropic degeneration/ballooning degeneration, and hyperkeratosis in the epidermis. In the lungs, congestion, oedema, emphysema, and atelectasis were observed grossly. Microscopically changes were suggestive of interstitial pneumonia, suppurative pneumonia, bronchopneumonia post pneumonic fibrosis, and stage of resolution. Grossely liver showed congestion and necrotic foci microscopically in most of the cases, and the liver showed acute viral hepatitis. Microscopically in kidneys, multifocal interstitial nephritis was observed. There was marked interstitial inflammation and zonal fibrosis with cystically dilated tubules and bowman's capsules. Microscopically, most of the heart tissue section showed normal histology with few sarcocysts in between cardiac muscles. In some cases, loss of cross striation, sarcoplasmic vacuolation, fregmentation, and disintegration of cardiac fibres were observed. The present study revealed the characteristic gross and histopathological changes in different organs in natural cases of lumpy skin disease. Further, the disease was confirmed based on the molecular diagnosis and transmission electron microscopy of capripox infection in the affected cattle in the study area.

Keywords: Capripoxvirus, lumpy skin disease, polymerage chain reaction, transmission electron microscopy

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Authors: Gladys Abiemwense Ibhaze, Anthony Henry Ekeocha, Adebowale Noah Fajemisin, Tope Oke, Caroline Tosin Alade,

Abstract:

The study was conducted to evaluate the silage quality and acceptability of ensiled avocado pear skin (APS) with cassava peel (CSP) and brewers’ grain (BG) using eighteen (18) West African Dwarf goats with an average weight of 7.0±1.5 kg. The experimental diets; 1) 50% cassava peel+ 50% brewers’ grain, 2) 50% brewers’ grain+ 50% avocado pear skin, 3) 50% cassava peel +25% brewers’ grain+ 25% avocado pear skin were ensiled for 21 days. The experimental design was a completely randomized design (CRD). The chemical composition of the diets was investigated. The acceptability of the diets was evaluated for twelve (12) days. Results obtained showed that the crude protein content ranged from 12.18 – 12.47%, crude fiber (15.99-22.67%). Results obtained showed that diet 1 had the least pH value (4.0), followed by diet 3 (4.5) and diet 2 (5.2). All diets were firm in texture and maintained their initial color. The temperature ranged from 27-29 ⁰C with diet 2 having the highest temperature of 29 ⁰C. Acceptability of experimental diets varied (p < 0.05) significantly. Dry matter intake ranged from (426.22-686.73g/day) with animals on a diet one recording the highest dry matter intake. The coefficient of preference and percentage preference, also differed (p <0.05) significantly among the diets. Diet 1 had a coefficient of preference greater than unity. However, this was not significantly (p>0.05) different from diet two but differed from diet 3. Conclusively, APS could be included in goats’ diets in the absence of CSP during feed scarcity provided a rich source of protein is available.

Keywords: avocado pear skin, Brewers' grain, Cassava peel, preference

Procedia PDF Downloads 203

Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

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Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

Procedia PDF Downloads 520

Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

Procedia PDF Downloads 313

Authors: Ghazanfari Masoumeh, Hajimohammadi Bahador, Eskandari Soheyl, Karimian Khosroshahi Nader

Abstract:

Consumption of ready to cook meat products such as hamburgers, sausages and etc is being increased in the worldwide specially in the big cities , so safety and quality required for food products is very important and vital for consumers with consideration of meat price and increasing demands for meat products, possibility of substitution of cheep and unauthorized textures such as undesirable enclosures animals (massacre, lung tissue, breast of spleen, the organs abdominal cavity, gizzard chicken, skin, etc. ) have increased in the recent years, in this study 30 industrial and 30 handmade hamburgers in fast food restaurants detected out of Iranian national standard for hamburger No. 2304 in using the unauthorized textures. The purpose of this study was to determine using of chicken skin in produced hamburgers from chicken meat in Tehran base on histology methods. The rates of skin used were, 2 % in industrial and 9 % in handmade formula samples. Statistically using the unauthorized textures had significant higher rate in handmade (P < 0.05) in compare with the industrial samples. The results showed the handmade hamburgers with higher adulteration rate and non-compliance with the hamburger national standard could be a potentially health hazard.

Keywords: histology, adulteration, unauthorized textures, undesirable enclosures animals

Procedia PDF Downloads 455

Authors: Boukari Nassim

Abstract:

This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

Procedia PDF Downloads 345