Search results for: skin or non-skin classification

Authors: Huang Hao, Li Weiwen

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Global biodiversity continues to decline as a result of global climate change and various human activities, such as habitat destruction, pollution, introduction of alien species and overfishing. Although there are connections between global marine organisms more or less, it is better to have clear geographical boundaries in order to facilitate the assessment and management of different biogeographical zones. And so area based management tools (ABMT) are considered as the most effective means for the conservation and sustainable use of marine biodiversity. On a large scale, the geographical gap (or barrier) is the main factor to influence the connectivity, diffusion, ecological and evolutionary process of marine organisms, which results in different distribution patterns. On a small scale, these factors include geographical location, geology, and geomorphology, water depth, current, temperature, salinity, etc. Therefore, the analysis on geographic and environmental factors is of great significance in the study of biodiversity characteristics. This paper summarizes the marine spatial classification and ABMTs used in coastal area, open oceans and deep sea. And analysis principles and methods of marine spatial classification based on biogeographic related factors, and take China Near Sea (CNS) area as case study, and select key biogeographic related factors, carry out marine spatial classification at biological region scale, ecological regionals scale and biogeographical scale. The research shows that CNS is divided into 5 biological regions by climate and geographical differences, the Yellow Sea, the Bohai Sea, the East China Sea, the Taiwan Straits, and the South China Sea. And the bioregions are then divided into 12 ecological regions according to the typical ecological and administrative factors, and finally the eco-regions are divided into 98 biogeographical units according to the benthic substrate types, depth, coastal types, water temperature, and salinity, given the integrity of biological and ecological process, the area of the biogeographical units is not less than 1,000 km². This research is of great use to the coastal management and biodiversity conservation for local and central government, and provide important scientific support for future spatial planning and management of coastal waters and sustainable use of marine biodiversity.

Keywords: spatial classification, marine biodiversity, bio-geographical, conservation

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Aliseydi Bozkurt, Ugur Yılmaz

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Objective: It was aimed to evaluate the current status of semen parameters in fertile males with one or more children and whose wife having a pregnancy for the last 1-12 months in Malatya region. Methods: Sperm samples were obtained from 131 voluntary fertile men. In each analysis, sperm volume (ml), number of sperm (sperm/ml), sperm motility and sperm viscosity were examined with Makler device. Classification was made according to World Health Organization (WHO) criteria. Results: Mean ejaculate volume ranged from 1.5 ml to 5.5 ml, sperm count ranged from 27 to 180 million/ml and motility ranged from 35 to 90%. Sperm motility was found to be on average; 69.9% in A, 7.6% in B, 8.7% in C, 13.3% in D category. Conclusion: The mean spermiogram values of fertile males in Malatya region were found to be similar to those in fertile males determined by the WHO. This study has a regional classification value in terms of spermiogram values.

Keywords: fertile men, infertility, spermiogram, sperm motility

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Authors: Caspar S. Carson, Gabriel W. Prather, Nicholas E. Wong, Jeffery R. Anton, William H. McCoy

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Cutibacterium acnes is a commensal bacterium found on human skin that has been linked to acne. C. acnes can also be an opportunistic pathogen when it infiltrates the body during surgery. This pathogen can cause dangerous infections of medical implants, such as shoulder replacements, leading to life-threatening blood infections. Compounding this issue, C. acnes resistance to many antibiotics has become an increasing problem worldwide, creating a need for special forms of treatment. C. acnes expresses the protein RoxP, and it requires this protein to colonize human skin. Though this protein is required for C. acnes skin colonization, its function is not yet understood. Inhibition of RoxP function might be an effective treatment for C. acnes infections. To develop such reagents, the McCoy Laboratory generated four unique anti-RoxP antibodies. Preliminary studies in the McCoy Lab have established that each antibody binds a distinct site on RoxP. To assess the potential of these antibodies as therapeutics, it is necessary to specifically characterize these antibody epitopes and evaluate them in assays that assess their ability to inhibit RoxP-dependent C. acnes growth. To provide material for these studies, an antibody expression construct, Fv-clasp(v2), was adapted to encode anti-RoxP antibody sequences. The author hypothesizes that this expression strategy can produce sufficient amounts of >95% pure antibody fragments for further characterization of these antibodies. Four anti-RoxP Fv-clasp(v2) expression constructs (pET vector-based) were transformed into E. coli BL21-Gold(DE3) cells and a small-scale expression and purification trial was performed for each construct to evaluate anti-RoxP Fv-clasp(v2) yield and purity. Successful expression and purification of these antibody constructs will allow for their use in structural studies, such as protein crystallography and cryogenic electron microscopy. Such studies would help to define the antibody binding sites on RoxP, which could then be leveraged in the development of certain methods to treat C. acnes infection through RoxP inhibition.

Keywords: structural biology, protein expression, infectious disease, antibody, therapeutics, E. coli

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).

Keywords: motion detection, motion tracking, trajectory analysis, video surveillance

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Authors: Carolina L. Cerdeira, Julia V. F. Cortes, Maria E. V. Amarante, Gersika B. Santos

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Skin cancer is the most common cancer in several parts of the world; in a tropical country like Brazil, the situation isn’t different. The Brazilian population is exposed to high levels of solar radiation, increasing the risk of developing cutaneous carcinoma. Aimed at encouraging prevention measures and the early diagnosis of these tumors, a study was carried out that analyzed data on cutaneous melanomas, basal cell, and epidermoid carcinomas, using as primary data source the medical records of 161 patients registered in one pathology service, which performs skin biopsies in a city of Minas Gerais, Brazil. All patients diagnosed with skin cancer at this service from January 2015 to December 2019 were included. The incidence of skin carcinoma cases was correlated with the identification of histological type, sex, age group, and topographic location. Correlation between variables was verified by Fisher's exact test at a nominal significance level of 5%, with statistical analysis performed by R® software. A significant association was observed between age group and type of cancer (p=0.0085); age group and sex (0.0298); and type of cancer and body region affected (p < 0.01). Those 161 cases analyzed comprised 93 basal cell carcinomas, 66 epidermoid carcinomas, and only two cutaneous melanomas. In the group aged 19 to 30 years, the epidermoid form was most prevalent; from 31 to 45 and from 46 to 59 years, the basal cell prevailed; in 60-year-olds or over, both types had higher frequencies. Associating age group and sex, in groups aged 18 to 30 and 46 to 59 years, women were most affected. In the 31-to 45-year-old group, men predominated. There was a gender balance in the age group 60-year-olds or over. As for topography, there was a high prevalence in the head and neck, followed by upper limbs. Relating histological type and topography, there was a prevalence of basal cell and epidermoid carcinomas in the head and neck. In the chest, the basal cell form was most prevalent; in upper limbs, the epidermoid form prevailed. Cutaneous melanoma affected only the chest and upper limbs. About 82% of patients 60-year-olds or over had head and neck cancer; from 46 to 59 and 60-year-olds or over, the head and neck region and upper limbs were predominantly affected; the distribution was balanced in the 31-to 45-year-old group. In conclusion, basal cell carcinoma was predominant, whereas cutaneous melanoma was the rarest among the types analyzed. Patients 60-year-olds or over were most affected, showing gender balance. In young adults, there was a prevalence of the epidermoid form; in middle-aged patients, basal cell carcinoma was predominant; in the elderly, both forms presented with higher frequencies. There was a higher incidence of head and neck cancers, followed by malignancies affecting the upper limbs. The epidermoid type manifested significantly in the upper limbs. Body regions such as the thorax and lower limbs were less affected, which is justified by the lower exposure of these areas to incident solar radiation.

Keywords: basal cell carcinoma, cutaneous melanoma, skin cancer, squamous cell carcinoma, topographic location

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Authors: Chih-Yang Liao

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Baseball is usually played outdoors in the warmest months of the year. Therefore, baseball players are susceptible to the influence of the hot environment. It has been shown that hitting performance is increased in games played in warm weather, compared to in cold weather, in Major League Baseball. Intermittent cooling during sporting events can prevent the risk of hyperthermia and increase endurance performance. However, the effects of cooling during baseball games played in a hot environment are unclear. This study adopted a cross-over design. Ten Division I collegiate male baseball players in Taiwan volunteered to participate in this study. Each player played two simulated baseball games, with one day in between. Five of the players received intermittent cooling during the first simulated game, while the other five players received intermittent cooling during the second simulated game. The participants were covered in neck and forehand regions for 6 min with towels that were soaked in icy salt water 3 to 4 times during the games. The participants received the cooling treatment in the dugout when they were not on the field for defense or hitting. During the 2 simulated games, the temperature was 31.1-34.1°C and humidity was 58.2-61.8%, with no difference between the two games. Ratings of perceived exertion, thermal sensation, tympanic and forehead skin temperature immediately after each defensive half-inning and after cooling treatments were recorded. Ratings of perceived exertion were measured using the Borg 10-point scale. The thermal sensation was measured with a 6-point scale. The tympanic and skin temperature was measured with infrared thermometers. The data were analyzed with a two-way analysis of variance with repeated measurement. The results showed that intermitted cooling significantly reduced ratings of perceived exertion and thermal sensation. Forehead skin temperature was also significantly decreased after cooling treatments. However, the tympanic temperature was not significantly different between the two trials. In conclusion, intermittent cooling in the neck and forehead regions was effective in alleviating the perceived exertion and heat sensation. However, this cooling intervention did not affect the core temperature. Whether intermittent cooling has any impact on hitting or pitching performance in baseball players warrants further investigation.

Keywords: baseball, cooling, ratings of perceived exertion, thermal sensation

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Authors: Zhongjie Yu, Hancheng Yu

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In this paper, we propose an effective method to detect concentric circles with imperfect edges. First, the gradient of edge pixel is coded and a 2-D lookup table is built to speed up normal generation. Then we take an accumulator to estimate the rough center and collect plausible edges of concentric circles through gradient and distance. Later, we take the contour-based method, which takes the contour and edge intersection, to pre-classify the edges. Finally, we use the extended RANSAC method to find all the candidate circles. The center of concentric circles is determined by the two circles with the highest concentricity. Experimental results demonstrate that the proposed method has both good performance and accuracy for the detection of concentric circles.

Keywords: concentric circle detection, gradient, contour, edge pre-classification, RANSAC

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Authors: İsmail Kavdır, M. Burak Büyükcan, Ferhat Kurtulmuş

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Table olive is a valuable product especially in Mediterranean countries. It is usually consumed after some fermentation process. Defects happened naturally or as a result of an impact while olives are still fresh may become more distinct after processing period. Defected olives are not desired both in table olive and olive oil industries as it will affect the final product quality and reduce market prices considerably. Therefore it is critical to sort table olives before processing or even after processing according to their quality and surface defects. However, doing manual sorting has many drawbacks such as high expenses, subjectivity, tediousness and inconsistency. Quality criterions for green olives were accepted as color and free of mechanical defects, wrinkling, surface blemishes and rotting. In this study, it was aimed to classify fresh table olives using different classifiers and NIR spectroscopy readings and also to compare the classifiers. For this purpose, green (Ayvalik variety) olives were classified based on their surface feature properties such as defect-free, with bruised defect and with fly defect using FT-NIR spectroscopy and classification algorithms such as artificial neural networks, ident and cluster. Bruker multi-purpose analyzer (MPA) FT-NIR spectrometer (Bruker Optik, GmbH, Ettlingen Germany) was used for spectral measurements. The spectrometer was equipped with InGaAs detectors (TE-InGaAs internal for reflectance and RT-InGaAs external for transmittance) and a 20-watt high intensity tungsten–halogen NIR light source. Reflectance measurements were performed with a fiber optic probe (type IN 261) which covered the wavelengths between 780–2500 nm, while transmittance measurements were performed between 800 and 1725 nm. Thirty-two scans were acquired for each reflectance spectrum in about 15.32 s while 128 scans were obtained for transmittance in about 62 s. Resolution was 8 cm⁻¹ for both spectral measurement modes. Instrument control was done using OPUS software (Bruker Optik, GmbH, Ettlingen Germany). Classification applications were performed using three classifiers; Backpropagation Neural Networks, ident and cluster classification algorithms. For these classification applications, Neural Network tool box in Matlab, ident and cluster modules in OPUS software were used. Classifications were performed considering different scenarios; two quality conditions at once (good vs bruised, good vs fly defect) and three quality conditions at once (good, bruised and fly defect). Two spectrometer readings were used in classification applications; reflectance and transmittance. Classification results obtained using artificial neural networks algorithm in discriminating good olives from bruised olives, from olives with fly defect and from the olive group including both bruised and fly defected olives with success rates respectively changing between 97 and 99%, 61 and 94% and between 58.67 and 92%. On the other hand, classification results obtained for discriminating good olives from bruised ones and also for discriminating good olives from fly defected olives using the ident method ranged between 75-97.5% and 32.5-57.5%, respectfully; results obtained for the same classification applications using the cluster method ranged between 52.5-97.5% and between 22.5-57.5%.

Keywords: artificial neural networks, statistical classifiers, NIR spectroscopy, reflectance, transmittance

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Authors: Emily Moore, Dora Amos, Tracy Ellimah, Natasha Parrott

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Postoperative haematoma is a well-recognised complication of thyroid surgery with an incidence of 1-5%. Haematoma formation causes progressive airway obstruction, necessitating emergency bedside haematoma evacuation in up to ¼ of patients. ENT UK, BAETS and DAS have developed consensus guidelines to improve perioperative care, recommending that all healthcare staff interacting with patients undergoing thyroid surgery should be trained in managing post-thyroidectomy haematoma. The aim was to assess the effectiveness of a hybrid simulation model in improving clinician’s confidence in dealing with this surgical emergency. A hybrid simulation was designed, consisting of a standardised patient wearing a part-task trainer to mimic a post-thyroidectomy haematoma in a real patient. The part-task trainer was an adapted C-spine collar with layers of silicone representing the skin and strap muscles and thickened jelly representing the haematoma. Both the skin and strap muscle layers had to be opened in order to evacuate the haematoma. Boxes have been implemented into the appropriate post operative areas (recovery and surgical wards), which contain a printed algorithm designed to assist in remembering a sequence of steps for haematoma evacuation using the ‘SCOOP’ method (skin exposure, cut sutures, open skin, open muscles, pack wound) along with all the necessary equipment to open the front of the neck. Small-group teaching sessions were delivered by ENT and anaesthetic trainees to members of the multidisciplinary team normally involved in perioperative patient care, which included ENT surgeons, anaesthetists, recovery nurses, HCAs and ODPs. The DESATS acronym of signs and symptoms to recognise (difficulty swallowing, EWS score, swelling, anxiety, tachycardia, stridor) was highlighted. Then participants took part in the hybrid simulation in order to practice this ‘SCOOP’ method of haematoma evacuation. Participants were surveyed using a Likert scale to assess their level of confidence pre- and post teaching session. 30 clinicians took part. Confidence (agreed/strongly agreed) in recognition of post thyroidectomy haematoma improved from 58.6% to 96.5%. Confidence in management improved from 27.5% to 89.7%. All participants successfully decompressed the haematoma. All participants agreed/strongly agreed, that the sessions were useful for their learning. Multidisciplinary team simulation teaching is effective at significantly improving confidence in both the recognition and management of postoperative haematoma. Hybrid simulation sessions are useful and should be incorporated into training for clinicians.

Keywords: thyroid surgery, haematoma, teaching, hybrid simulation

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Maria E. V. Amarante, Carolina L. Cerdeira, Julia V. Cortes, Fiorita G. L. Mundim

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Basal cell carcinoma (BCC) is the most prevalent type of skin cancer in humans. It arises from the basal cells of the epidermis and cutaneous appendages. The role of sunlight exposure as a risk factor for BCC is very well defined due to its power to influence genetic mutations, in addition to having a suppressor effect on the skin immune system. Despite showing low metastasis and mortality rates, the tumor is locally infiltrative, aggressive, and destructive. Considering the high prevalence rate of this carcinoma and the importance of early detection, a retrospective study was carried out in order to correlate the clinical data available on BBC, characterize it epidemiologically, and thus enable effective prevention measures for the population. Data on the period from January 2015 to December 2019 were collected from the medical records of patients registered at one pathology service located in the southeast region of Brazil, known as SVO, which delivers skin biopsy results. The study was aimed at correlating the variables, sex, age, and subtypes found. Data analysis was performed using the chi-square test at a nominal significance level of 5% in order to verify the independence between the variables of interest. Fisher's exact test was applied in cases where the absolute frequency in the cells of the contingency table was less than or equal to five. The statistical analysis was performed using the R® software. Ninety-three basal cell carcinoma were analyzed, and its frequency in the 31-to 45-year-old age group was 5.8 times higher in men than in women, whereas, from 46 to 59 years, the frequency was found 2.4 times higher in women than in men. Between the ages of 46 to 59 years, it should be noted that the sclerodermiform subtype appears more than the solid one, with a difference of 7.26 percentage points. Reversely, the solid form appears more frequently in individuals aged 60 years or more, with a difference of 8.57 percentage points. Among women, the frequency of the solid subtype was 9.93 percentage points higher than the sclerodermiform frequency. In males, the same percentage difference is observed, but sclerodermiform is the most prevalent subtype. It is concluded in this study that, in general, there is a predominance of basal cell carcinoma in females and in individuals aged 60 years and over, which demonstrates the tendency of this tumor. However, when rarely found in younger individuals, the male gender prevailed. The most prevalent subtype was the solid one. It is worth mentioning that the sclerodermiform subtype, which is more aggressive, was seen more frequently in males and in the 46-to 59-year-old range.

Keywords: basal cell carcinoma, epidemiology, sclerodermiform basal cell carcinoma, skin cancer, solar radiation, solid basal cell carcinoma

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: M. Safiqul Islam, Md Arafat Hossain Sarkar

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Brachytherapy is one of the most important cancer treatment management systems in radiotherapy department. Brachytherapy treatment is moved into High Dose Rate (HDR) after loader from Low Dose Rate (LDR) after loader due to radiation protection advantage. HDR Brachytherapy is a highly multipurpose system for enhancing cure and achieving palliation in many common cancers disease of developing countries. High-dose rate (HDR) Brachytherapy is a type of internal radiation therapy that delivers radiation from implants placed close to or inside, the tumor(s) in the body. This procedure is very effective at providing localized radiation to the tumor site while minimizing the patient’s whole body dose. Brachytherapy has proven to be a highly successful treatment for cancers of the prostate, cervix, endometrium, breast, skin, bronchus, esophagus, and head and neck, as well as soft tissue sarcomas and several other types of cancer. For the time being in our country we have 10 new HDR Remote after loading Brachytherapy. Right now 4 HDR Brachytherapy is already installed and running for patient’s treatment out of 10 HDR Brachytherapy. Ir-192 source is more comfortable than Co-60. In that case people or expert personnel prefer Ir-192 source for different kind of cancer patients. Ir-192 are economically, more flexible and familiar in our country.

Keywords: Ir-192, brachytherapy, cancer treatment, prostate, cervix, endometrium, breast, skin, bronchus, esophagus, soft tissue sarcomas

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Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

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Authors: Soheir Weheida, Amal E. Shehata, Samira E. Aboalizm

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The aim of this study was to examine the effect of surgical safety checklist on surgical team’s knowledge and performance in operating room. Subjects: A convenience sample 151 (48 head nurse, 45 nurse, 37 surgeon and 21 anesthesiologist) which available in operating room at two different hospitals was included in the study. Setting: The study was carried out at operating room in Menoufia University and Shebin Elkom Teaching Hospitals, Egypt. Tools: I: Surgical safety: Surgical team knowledge assessment structure interview schedule. II: WHO surgical safety observational Checklist. III: Post Surgery Culture Survey scale. Results: There was statistical significant improvement of knowledge mean score and performance about surgical safety especially in post and follow up than pre intervention, before patients entering the operating, before induction of anesthesia, skin incision and post skin closure and before patient leaves operating room, P values (P < 0.001). Improvement of communication post intervention than pre intervention between surgical team’s (4.74 ± 0.540). About two thirds (73.5 %) of studied sample strongly agreed on surgical safety in operating room. Conclusions: Implementation of surgical safety checklist has a positive effect on improving knowledge, performance and communication between surgical teams and these seems to have a positive effect on improve patient safety in the operating room.

Keywords: knowledge, operating room, performance, surgical safety checklist

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Authors: Umran Erciyes, Filiz Okumus

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The purpose of this study was the determination of factors which impact the pregnancy, birth experience and the opinions regarding the delivery type of the puerperants, after vaginal birth. This descriptive study includes 349 patients who gave births with normal birth in one of the hospital in İstanbul in May- November 2014. After birth, we interview with these women face to face. The descriptive information form and Perception of Birth Scale were used as data collection tool. SPSS (Statistical Package for the Social Sciences) was used for statistical analysis. The average age of patients was 27.13, and the average score was 76.93±20.22. The patients are primary school graduate, and they do not have a job. They expressed an income outcome equality. More than half of women did not get educated before birth. Among educated patients, few women got educated overcoming the pain during labor process. As the time spent in the hospital for the birth increases, the birth perception of mothers is affected negatively. %86.8 of participants gave assisted delivery. Spontaneous vaginal birth has positive effects on birth perception. Establishing a vascular access, induction of labor performing enema, restriction of orally intake and movement, fundal pressure, episiotomy, nor to perform skin to skin contact with the baby after birth has adverse effects on the birth perceptions.

Keywords: antenatal care, birth experience, perception of birth, vaginal birth

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Authors: Naghmeh Moradpoor Sheykhkanloo

Abstract:

Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

Procedia PDF Downloads 468

Authors: Katsumi Hirata

Abstract:

Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: environmental sound, bispectrum, spectrogram, slice bispectrogram, convolutional neural network

Procedia PDF Downloads 124

Authors: Nandita Ghosh, Shinjini Mitra, Ena Ray Banerjee

Abstract:

Atopic dermatitis (AD) is a chronic disease of the skin, involving itchy, reddish, and scaly lesions. It mainly affects children and has a high prevalence in developing countries. The AD may occur due to environmental or genetic factors. There is no permanent cure for the AD. Currently, all therapeutic strategies involve methods to simply alleviate the symptoms, and include lotions and corticosteroids, which have adverse effects. Use of phytochemicals and natural products has not yet been exploited fully. The particle used in this study is derived from Cyamopsis tetragonoloba, an edible polysaccharide with a galactomannan component. The mannose component mainly increases its specificity towards cellular uptake by mannose receptors, highly expressed by the macrophage. The aim of this study was to determine the therapeutic effect of guar gum nanoparticles (GN) in vitro and in vivo in the AD. To assess the wound healing capacity of the guar gum nanoparticle (GN), we first treated adherent NIH3T3 cells, with a scratch injury, with GN. GN successfully healed the wound caused by the scratch. In the in vivo experiment, Balb/c mice ear were topically treated with oxazolone (oxa) to induce AD and then were topically treated with GN. The ear thickness was increased significantly till day 28 on the treatment of Oxa. The GN application showed a significant decrease in the thickness as assessed on day 28. The total cell count of skin cells showed fold increase when treated with oxa, was again decreased on topical application of GN on the affected skin. The eosinophil count, as assessed by Giemsa staining was also increased when treated with oxa, GN application led to a significant decrease. The IgE level was assessed in the serum samples which showed that GN helped in restoring the alleviated IgE level. The T helper cells and the macrophage population showed increased percentage when treated with oxa, the GN application. This was examined by flow cytometry. The H&E staining of the ear tissue showed epidermal thickness in the oxa treated mice, GN application showed reduced cellular filtration followed by epidermal thickness. Thus our assays showed that GN was successful in alleviating the disease caused by Oxa when administered topically.

Keywords: allergen, inflammation, nanodrug, wound

Procedia PDF Downloads 241

Authors: Ashish Jain, Satish Nayak

Abstract:

Transdermal iontophoretic drug delivery system is viable drug delivery platform technology and has a strong market worldwide. Transdermal drug delivery system is particularly desirable for therapeutic agents that need prolonged administration at controlled plasma level. This makes appropriateness to antihypertensive and anti-diabetic agents for their transdermal development. Controlled zero order absorption, easily termination of drug delivery and easy to administration also support for popularity of transdermal delivery. In this current research iontophoretic delivery of various anti diabetic agents like glipizide, glibenclamide and glimepiride were carried out. The experiments were carried out at different drug concentrations and different current densities using cathodal iontophoresis. Diffusion cell for iontophoretic permeation study was modified according to Glikfield Design. Pig skin was used for in vitro permeation study and for the in-vivo study New Zealand rabbits were used. At all concentration level iontophoresis showed enhanced permeation rate compared to passive controls. Iontophoretic transports of selected drugs were found to be increased with the current densities. Results showed that target permeation rate for selected drugs could be achieved with the aid of iontophoresis by increasing the area in an appreciable range.

Keywords: transdermal, iontophoresis, pig skin, rabbits, glipizide, glibeclamide

Procedia PDF Downloads 381

Authors: Bencherif Kada

Abstract:

In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

Procedia PDF Downloads 119

Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

Abstract:

With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

Procedia PDF Downloads 542

Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

Abstract:

In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

Procedia PDF Downloads 62

Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

Abstract:

Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

Procedia PDF Downloads 531

Authors: Atitallah Sofien, Bouyahia Olfa, Krifi farah, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

Abstract:

Introduction: Subcutaneous fat necrosis of the newborn (SCFN) is a rare acute hypodermatitis characterized by skin lesions in the form of infiltrated, hard plaques and subcutaneous nodules, with a purplish-red color, occurring between the first and sixth week of life. SCFN is generally a benign condition that spontaneously regresses without sequelae, but it can be complicated by severe hypercalcemia. Methodology: This is a retrospective case report of neonatal subcutaneous fat necrosis complicated with severe hypercalcemia and nephrocalcinosis. Results: This is a case of a female newborn with a family history of a hypothyroid mother on Levothyrox, born to non-consanguineous parents and from a well-monitored pregnancy. The newborn was delivered by cesarean section at 39 weeks gestation due to severe preeclampsia. She was admitted to the Neonatal Intensive Care Unit at 1 hour of life for the management of grade 1 perinatal asphyxia and immediate neonatal respiratory distress related to transient respiratory distress. Hospitalization was complicated by a healthcare-associated infection, requiring intravenous antibiotics for ten days, with a good clinical and biological response. On the 20th day of life, she developed skin lesions in the form of indurated purplish-red nodules on the back and on both arms. A SCFN was suspected. A calcium level test was conducted, which returned a result of 3 mmol/L. The rest of the phosphocalcic assessment was normal, with early signs of nephrocalcinosis observed on renal ultrasound. The diagnosis of SCFN complicated by nephrocalcinosis associated with severe hypercalcemia was made, and the condition improved with intravenous hydration and corticosteroid therapy. Conclusion: SCFN is a rare and generally benign hypodermatitis in newborns with an etiology that is still poorly understood. Despite its benign nature, SCFN can be complicated by hypercalcemia, which can sometimes be life-threatening. Therefore, it is important to conduct a thorough skin examination of newborns, especially those with risk factors, to detect and correct any potential hypercalcemia.

Keywords: subcutaneous fat necrosis, newborn, hypercalcemia, nephrocalcinosis

Procedia PDF Downloads 56

Authors: Bencherif Kada

Abstract:

In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

Procedia PDF Downloads 30

Authors: Krishna Prasad Regmi, Jun-Bo Tu, Cheng-Qun Hou, Li-Feng Li

Abstract:

Maxillofacial trauma in a pediatric group of patients is particularly challenging, as these patients have significant differences from adults as far as the facial skeleton is concerned. Mandibular condylar fractures are common presentations to hospitals across the globe and remain the most important cause of temporomandibular joint (TMJ) ankylosis. The etiology and epidemiology of pediatric trauma involving the diacapitular condylar fractures (DFs) have been reported in a large series of patients. Nevertheless, little is known about treatment protocols for DFs in children. Accordingly, the treatment modalities for the management of pediatric fractures also differ. We suggest following the PDA and intracapsular ABC classification of condylar fracture to increase the overall postoperative satisfaction level that bypasses the change of subjective feelings of patients’ from preoperative to the postoperative condition. At the same time, use of 3-D technology and surgical navigation may also increase treatment accuracy.

Keywords: maxillofacial trauma, diacapitular fracture, condylar fracture, PDA classification

Procedia PDF Downloads 268