Search results for: skin detection
4011 Detecting Venomous Files in IDS Using an Approach Based on Data Mining Algorithm
Authors: Sukhleen Kaur
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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper
Procedia PDF Downloads 4144010 Refined Edge Detection Network
Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni
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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone
Procedia PDF Downloads 1024009 Induction Machine Bearing Failure Detection Using Advanced Signal Processing Methods
Authors: Abdelghani Chahmi
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This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation
Procedia PDF Downloads 1394008 Efficacy of Ivermectin Agaist Sarcoptes Scabiei Var. Cameli in Libya
Authors: Ahmed Rashed
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Sarcoptic mange is generally recognized as one of the most serious diseases in camels in Libya. It is an extremely pruritic and contagious skin condition caused by Sarcoptes scabiei var cameli. Thirteen camels (camelis dromedaries), showing progressive infection with S.scabiei mites in skin scrapings, were chosen randomly from different affected herds at AL-Assa camel project. Ten camels were treated with ivermectin (22,23-dihydroavermectin B1, Ivomec, Merck) at a dose rate of 0.2 mg./kg.body weight. Scratching and rubbing had completely disappeared in the treated camels one week after the second injection. Two weeks after the second injection motile mites were found on only one camel, and three weeks after the second injection, no motile mites were detected. Motile mites were observed in the three untreated camels up to the end of the trial.Keywords: ivermecti, Sarcoptes scabiei, camels, scrapings
Procedia PDF Downloads 5084007 Burn/Traumatic Scar Maturation Using Autologous Fat Grafts + SVF
Authors: Ashok K. Gupta
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Over the past few decades, since the bio-engineering revolution, autologous cell therapy (ACT) has become a rapidly evolving field. Currently, this form of therapy has broad applications in modern medicine and plastic surgery, ranging from the treatment/improvement of wound healing to life-saving operations. A study was conducted on 50 patients having to disfigure, and deform post burn scars and was treated by injection of extracted, refined adipose tissue grafts with their unique stem cell properties. To compare the outcome, a control of 20 such patients was treated with conventional skin or soft-tissue flaps or skin grafting, and a control of 10 was treated with more advanced microsurgical techniques such as Pre-fabricated flaps/pre laminated flaps / free flaps. Assessment of fat volume and survival post- follow up period was done by radiological aid, using MRI and clinically (Survival of the autograft and objective parameters for scar elasticity were evaluated skin elasticity parameters 3 to 9 months postoperatively). Recently, an enzyme that is involved in collagen crosslinking in fibrotic tissue, lysyl hydroxylase (LH2), was identified. This enzyme is normally active in bone and cartilage but hardly in the skin. It has been found that this enzyme is highly expressed in scar tissue and subcutaneous fat; this is in contrast to the dermis, where the enzyme is hardly expressed. Adipose tissue-derived stem cell injections are an effective method in the treatment of various extensive post-burn scar deformities that makes it possible to re-create the lost sub-dermal tissue for improvement in the function of involved joint movements.Keywords: adipose tissue-derived stem cell injections, treatment of various extensive post-burn scar deformities, re-create the lost sub-dermal tissue, improvement in function of involved joint movements
Procedia PDF Downloads 674006 Applying Multiplicative Weight Update to Skin Cancer Classifiers
Authors: Animish Jain
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This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer
Procedia PDF Downloads 794005 Combined Treatment with Microneedling and Chemical Peels Improves Periorbital Wrinkles and Skin Laxity
Authors: G. Kontochristopoulos, T. Spiliopoulos, V. Markantoni, E. Platsidaki, A. Kouris, E. Balamoti, C. Bokotas, G. Haidemenos
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Introduction: There is a high patient demand for periorbital rejuvenation since the facial area is often the first to show visible signs of aging. With advancing age, there are sometimes marked changes that occur in the skin, fat, muscle and bone of the periorbital region, resulting to wrinkles and skin laxity. These changes are among the easiest areas to correct using several minimally invasive techniques, which have become increasingly popular over the last decade. Lasers, radiofrequency, botulinum toxin, fat grafting and fillers are available treatments sometimes in combination to traditional blepharoplasty. This study attempts to show the benefits of a minimally invasive approach to periorbital wrinkles and skin laxity that combine microneedling and 10% trichloroacetic acid (TCA) peels. Method: Eleven female patients aged 34-72 enrolled in the study. They all gave informed consent after receiving detailed information regarding the treatment procedure. Exclusion criteria in the study were previous treatment for the same condition in the past six months, pregnancy, allergy or hypersensitivity to the components, infection, inflammation and photosensitivity on the affected region. All patients had diffuse periorbital wrinkles and mild to moderate upper or lower eyelid skin laxity. They were treated with Automatic Microneedle Therapy System-Handhold and topical application of 10% trichloroacetic acid solution to each periorbital area for five minutes. Needling at a 0,25 mm depth was performed in both latelar (x-y) directions. Subsequently, the peeling agent was applied to each periorbital area for five minutes. Patients were subjected to the above combination every two weeks for a series of four treatments. Subsequently they were followed up regularly every month for two months. The effect was photo-documented. A Physician's and a Patient's Global Assessment Scale was used to evaluate the efficacy of the treatment (0-25% indicated poor response, 25%-50% fair, 50%-75% good and 75%-100% excellent response). Safety was assessed by monitoring early and delayed adverse events. Results: At the end of the study, almost all patients demonstrated significant aesthetic improvement. Physicians assessed a fair and a good improvement in 9(81.8% of patients) and 2(18.1% of patients) participants respectively. Patients Global Assessment rated a fair and a good response in 6 (54.5%) and 5 (45.4%) participants respectively. The procedure was well tolerated and all patients were satisfied. Mild discomfort and transient erythema were quite common during or immediately after the procedure, however only temporary. During the monthly follow up, no complications or scars were observed. Conclusions: Microneedling is known as a simple, office–based collagen induction therapy. Low concentration TCA solution applied to the epidermis that has been more permeable by microneedling, can reach the dermis more effectively. In the present study, chemical peels with 10% TCA acted as an adjuvant to microneedling, as it causes controlled skin damage, promoting regeneration and rejuvenation of tissues. This combined therapy improved periorbital fine lines, wrinkles, and overall appearance of the skin. Thus it constitutes an alternative treatment of periorbital skin aging, with encouraging results and minor side-effects.Keywords: chemical peels, microneedling, periorbital wrinkles, skin laxity
Procedia PDF Downloads 3544004 Antibiogram and Molecular Characterization of Methicillin-Resistant Staphylococcus Pseudintermedius from Shelter Dogs with Skin Infections and Dog Owners in Abakaliki, Nigeria
Authors: Moses Ikechukwu Benjamin
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The continued increase in methicillin-resistant Staphylococcuspseudintermedius (MRSP) among dogs and the zoonotic transmission event of MRSP from dogs to humans threaten veterinary medicine and public health. The cardinal objective of this study was to determine the antibiogram and frequency of toxingenes in MRSP obtained from shelter dogs with skin infections and dog owners in Abakaliki, Eastern Nigeria. Skinswabs from 61 shelter dogs with skin infections and 33 nasal swabs from dog owners were processed and analyzed using standard microbiological techniques. Susceptibility to antibiotics was determined by Kirby Bauer disc diffusion technique. The screening for Seccanine, lukD, siet, and exitoxin genes was carried out by PCR. A total of 23 (37.7 %) and 1 (3 %) MRSP strains were obtained from shelter dogs and dog owners, respectively. Generally, isolates exhibited high resistance to amoxicillin-clavulanic acid, ceftazidime, and cefepime (100 % - 66.7 %) but were very susceptible (100 % - 70.7 %) to chloramphenicol and doripenem. The only isolate from dog owners harbouredseccanine, lukD, and siet toxin genes while solatesfrom shelter dogs harbouredseccanine16 (69.6 %), lukD 17 (73.9 %), siet 20 (87 %), and exi1 (4.4 %) toxin genes. Isolates were generally observed to be more resistant than other reports from the literature. Interesting, there was a similarity in the resistance antibiotypes and frequency of toxin genes harboured by MRSP isolates between shelter dogs with skin infections and their owner in a sampled household, thus suggesting a likely zoonotic transmission event. This report of the occurrence of MRSP and high frequency of toxin genes (Seccanine,lukD, and siet) in shelter dogs and dog owners represent a major challenge, especially in terms of antibiotic therapy, and is a serious concern for both animal and public health.Keywords: methicillin-resistant S. pseudintermedius, zoonotic transmission, antibiotic resistance, companion dogs, toxin genes
Procedia PDF Downloads 1624003 The Results of the Study of Clinical Forms of Actinic Keratosis in Uzbekistan
Authors: Ayubova Nargiza Mirzabixulaevna, Kiryakov Dmitriy Andreyevich
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Relevance: According to experts from the World Health Organization, in 80% of cases, the causes of skin cancer are external factors: polluted air, radioactive substances, solar flares, and free radicals. In dermatology, one of the most common related to obligate diseases is actinic keratosis. Actinic keratosis (AC) is an area of abnormal proliferation and differentiation of keratinocytes, which carry the risk of progression into invasive squamous cell carcinoma of the skin. The purpose of the study is to study the prevalence of various forms of actinic keratosis among the population of Uzbekistan. Materials and methods of research: The study is based on the observation and clinical laboratory examination of 96 patients who were divided by gender and age. Women made up 45% and men made up 55%. The youngest patient was 43 years old, and the oldest was 92 years old. The control group consisted of 40 patients. The following clinical signs were evaluated: peeling, hyperkeratosis, erythema, pigmentation, atrophy. Results: Studies have shown that of all forms of actinic keratosis, erythematous (36%), hyperkeratotic (27%), pigmented (12%), cutaneous horn (7.0%), atrophic (7.0%), Actinic cheilitis (6%), lichenoid (5%) are common. Conclusion: Thus, the data we have obtained indicate that the main and pronounced clinical sign in the erythematous form is erythema and the hyperkeratic form is often found. With cutaneous horn, there is a sharp hyperkeratosis of the epidermis.Keywords: actinic keratosis, patient, skin cancer, obligate diseases
Procedia PDF Downloads 274002 Fused Structure and Texture (FST) Features for Improved Pedestrian Detection
Authors: Hussin K. Ragb, Vijayan K. Asari
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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor
Procedia PDF Downloads 4884001 Efficacy Testing of a Product in Reducing Facial Hyperpigmentation and Photoaging after a 12-Week Use
Authors: Nalini Kaul, Barrie Drewitt, Elsie Kohoot
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Hyperpigmentation is the third most common pigmentary disorder where dermatologic treatment is sought. It affects all ages resulting in skin darkening because of melanin accumulation. An uneven skin tone because of either exposure to the sun (solar lentigos/age spots/sun spots or skin disruption following acne, or rashes (post-inflammatory hyperpigmentation -PIH) or hormonal changes (melasma) can lead to significant psychosocial impairment. Dyschromia is a result of various alterations in biochemical processes regulating melanogenesis. Treatments include the daily use of sunscreen with lightening, brightening, and exfoliating products. Depigmentation is achieved by various depigmenting agents: common examples are hydroquinone, arbutin, azelaic acid, aloesin, mulberry, licorice extracts, kojic acid, niacinamide, ellagic acid, arbutin, green tea, turmeric, soy, ascorbic acid, and tranexamic acid. These agents affect pigmentation by interfering with mechanisms before, during, and after melanin synthesis. While immediate correction is much sought after, patience and diligence are key. Our objective was to assess the effects of a facial product with pigmentation treatment and UV protection in 35 healthy F (35-65y), meeting the study criteria. Subjects with mild to moderate hyperpigmentation and fine lines with no use of skin-lightening products in the last six months or any dermatological procedures in the last twelve months before the study started were included. Efficacy parameters included expert clinical grading for hyperpigmentation, radiance, skin tone & smoothness, fine lines, and wrinkles bioinstrumentation (Corneometer®, Colorimeter®), digital photography and imaging (Visia-CR®), and self-assessment questionnaires. Safety included grading for erythema, edema, dryness & peeling and self-assessments for itching, stinging, tingling, and burning. Our results showed statistically significant improvement in clinical grading scores, bioinstrumentation, and digital photos for hyperpigmentation-brown spots, fine lines/wrinkles, skin tone, radiance, pores, skin smoothness, and overall appearance compared to baseline. The product was also well-tolerated and liked by subjects. Conclusion: Facial hyperpigmentation is of great concern, and treatment strategies are increasingly sought. Clinical trials with both subjective and objective assessments, imaging analyses, and self-perception are essential to distinguish evidence-based products. The multifunctional cosmetic product tested in this clinical study showed efficacy, tolerability, and subject satisfaction in reducing hyperpigmentation and global photoaging.Keywords: hyperpigmentation; photoaging, clinical testing, expert visual evaluations, bio-instruments
Procedia PDF Downloads 774000 Hazardous Vegetation Detection in Right-Of-Way Power Transmission Lines in Brazil Using Unmanned Aerial Vehicle and Light Detection and Ranging
Authors: Mauricio George Miguel Jardini, Jose Antonio Jardini
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Transmission power utilities participate with kilometers of circuits, many with particularities in terms of vegetation growth. To control these rights-of-way, maintenance teams perform ground, and air inspections, and the identification method is subjective (indirect). On a ground inspection, when identifying an irregularity, for example, high vegetation threatening contact with the conductor cable, pruning or suppression is performed immediately. In an aerial inspection, the suppression team is mobilized to the identified point. This work investigates the use of 3D modeling of a transmission line segment using RGB (red, blue, and green) images and LiDAR (Light Detection and Ranging) sensor data. Both sensors are coupled to unmanned aerial vehicle. The goal is the accurate and timely detection of vegetation along the right-of-way that can cause shutdowns.Keywords: 3D modeling, LiDAR, right-of-way, transmission lines, vegetation
Procedia PDF Downloads 1313999 Establishing Econometric Modeling Equations for Lumpy Skin Disease Outbreaks in the Nile Delta of Egypt under Current Climate Conditions
Authors: Abdelgawad, Salah El-Tahawy
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This paper aimed to establish econometrical equation models for the Nile delta region in Egypt, which will represent a basement for future predictions of Lumpy skin disease outbreaks and its pathway in relation to climate change. Data of lumpy skin disease (LSD) outbreaks were collected from the cattle farms located in the provinces representing the Nile delta region during 1 January, 2015 to December, 2015. The obtained results indicated that there was a significant association between the degree of the LSD outbreaks and the investigated climate factors (temperature, wind speed, and humidity) and the outbreaks peaked during the months of June, July, and August and gradually decreased to the lowest rate in January, February, and December. The model obtained depicted that the increment of these climate factors were associated with evidently increment on LSD outbreaks on the Nile Delta of Egypt. The model validation process was done by the root mean square error (RMSE) and means bias (MB) which compared the number of LSD outbreaks expected with the number of observed outbreaks and estimated the confidence level of the model. The value of RMSE was 1.38% and MB was 99.50% confirming that this established model described the current association between the LSD outbreaks and the change on climate factors and also can be used as a base for predicting the of LSD outbreaks depending on the climatic change on the future.Keywords: LSD, climate factors, Nile delta, modeling
Procedia PDF Downloads 2883998 Liver Tumor Detection by Classification through FD Enhancement of CT Image
Authors: N. Ghatwary, A. Ahmed, H. Jalab
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In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.
Procedia PDF Downloads 3583997 Multitemporal Satellite Images for Agriculture Change Detection in Al Jouf Region, Saudi Arabia
Authors: Ali A. Aldosari
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Change detection of Earth surface features is extremely important for better understanding of our environment in order to promote better decision making. Al-Jawf is remarkable for its abundant agricultural water where there is fertile agricultural land due largely to underground water. As result, this region has large areas of cultivation of dates, olives and fruits trees as well as other agricultural products such as Alfa Alfa and wheat. However this agricultural area was declined due to the reduction of government supports in the last decade. This reduction was not officially recorded or measured in this region at large scale or governorate level. Remote sensing data are primary sources extensively used for change detection in agriculture applications. This study is applied the technology of GIS and used the Normalized Difference Vegetation Index (NDVI) which can be used to measure and analyze the spatial and temporal changes in the agriculture areas in the Aljouf region.Keywords: spatial analysis, geographical information system, change detection
Procedia PDF Downloads 4023996 Hate Speech Detection in Tunisian Dialect
Authors: Helmi Baazaoui, Mounir Zrigui
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This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions.Keywords: hate speech detection, Tunisian Arabic, AraBERT, Bi-LSTM, Gemini annotation tool, social media moderation
Procedia PDF Downloads 113995 Fourier Transform and Machine Learning Techniques for Fault Detection and Diagnosis of Induction Motors
Authors: Duc V. Nguyen
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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.Keywords: fault detection, FFT, induction motor, predictive maintenance
Procedia PDF Downloads 1693994 Tailoring Polythiophene Nanocomposites with MnS/CoS Nanoparticles for Enhanced Surface-Enhanced Raman Spectroscopy (SERS) Detection of Mercury Ions in Water
Authors: Temesgen Geremew
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The excessive emission of heavy metal ions from industrial processes poses a serious threat to both the environment and human health. This study presents a distinct approach utilizing (PTh-MnS/CoS NPs) for the highly selective and sensitive detection of Hg²⁺ ions in water. Such detection is crucial for safeguarding human health, protecting the environment, and accurately assessing toxicity. The fabrication method employs a simple and efficient chemical precipitation technique, harmoniously combining polythiophene, MnS, and CoS NPs to create highly active substrates for SERS. The MnS@Hg²⁺ exhibits a distinct Raman shift at 1666 cm⁻¹, enabling specific identification and demonstrating the highest responsiveness among the studied semiconductor substrates with a detection limit of only 1 nM. This investigation demonstrates reliable and practical SERS detection for Hg²⁺ ions. Relative standard deviation (RSD) ranged from 0.49% to 9.8%, and recovery rates varied from 96% to 102%, indicating selective adsorption of Hg²⁺ ions on the synthesized substrate. Furthermore, this research led to the development of a remarkable set of substrates, including (MnS, CoS, MnS/CoS, and PTh-MnS/CoS) nanoparticles were created right there on SiO₂/Si substrate, all exhibiting sensitive, robust, and selective SERS for Hg²⁺ ion detection. These platforms effectively monitor Hg²⁺ concentrations in real environmental samples.Keywords: surface-enhanced raman spectroscopy (SERS), sensor, mercury ions, nanoparticles, and polythiophene.
Procedia PDF Downloads 773993 Enhancing Fall Detection Accuracy with a Transfer Learning-Aided Transformer Model Using Computer Vision
Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias
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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.Keywords: healthcare, fall detection, transformer, transfer learning
Procedia PDF Downloads 1443992 Protein Remote Homology Detection and Fold Recognition by Combining Profiles with Kernel Methods
Authors: Bin Liu
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Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)
Procedia PDF Downloads 1613991 Implementation of a Method of Crater Detection Using Principal Component Analysis in FPGA
Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata
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We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time
Procedia PDF Downloads 5543990 Early Detection of Damages in Railway Steel Truss Bridges from Measured Dynamic Responses
Authors: Dinesh Gundavaram
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This paper presents an investigation on bridge damage detection based on the dynamic responses estimated from a passing vehicle. A numerical simulation of steel truss bridge for railway was used in this investigation. The bridge response at different locations is measured using CSI-Bridge software. Several damage scenarios are considered including different locations and severities. The possibilities of dynamic properties of global modes in the identification of structural changes in truss bridges were discussed based on the results of measurement.Keywords: bridge, damage, dynamic responses, detection
Procedia PDF Downloads 2713989 VideoAssist: A Labelling Assistant to Increase Efficiency in Annotating Video-Based Fire Dataset Using a Foundation Model
Authors: Keyur Joshi, Philip Dietrich, Tjark Windisch, Markus König
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In the field of surveillance-based fire detection, the volume of incoming data is increasing rapidly. However, the labeling of a large industrial dataset is costly due to the high annotation costs associated with current state-of-the-art methods, which often require bounding boxes or segmentation masks for model training. This paper introduces VideoAssist, a video annotation solution that utilizes a video-based foundation model to annotate entire videos with minimal effort, requiring the labeling of bounding boxes for only a few keyframes. To the best of our knowledge, VideoAssist is the first method to significantly reduce the effort required for labeling fire detection videos. The approach offers bounding box and segmentation annotations for the video dataset with minimal manual effort. Results demonstrate that the performance of labels annotated by VideoAssist is comparable to those annotated by humans, indicating the potential applicability of this approach in fire detection scenarios.Keywords: fire detection, label annotation, foundation models, object detection, segmentation
Procedia PDF Downloads 63988 Biostimulation and Muscular Ergogenic Effect of Ozone Therapy on Buttock Augmentation: A Case Report and Literature Review
Authors: Ferreira R., Rocha K.
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Ozone therapy is indicated for improving skin aesthetics, bio-stimulating and ergogenic effect. This paper aims to carry out a case report that demonstrates the positive results of ozone therapy in buttock augmentation. The application showed positive results for skin bio stimulating, neocollagenesis, adipogenesis, and ergogenic muscle effect in the reported case, demonstrating to be a viable clinical technique. Buttock augmentation with ozone therapy is a promising aesthetic therapeutic modality with fast and safe results as an aesthetic therapeutic option for buttock augmentation.Keywords: bio-stimulating effect, ozone therapy, muscular ergogenic, buttock augmentation
Procedia PDF Downloads 2943987 Phishing Detection: Comparison between Uniform Resource Locator and Content-Based Detection
Authors: Nuur Ezaini Akmar Ismail, Norbazilah Rahim, Norul Huda Md Rasdi, Maslina Daud
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A web application is the most targeted by the attacker because the web application is accessible by the end users. It has become more advantageous to the attacker since not all the end users aware of what kind of sensitive data already leaked by them through the Internet especially via social network in shake on ‘sharing’. The attacker can use this information such as personal details, a favourite of artists, a favourite of actors or actress, music, politics, and medical records to customize phishing attack thus trick the user to click on malware-laced attachments. The Phishing attack is one of the most popular attacks for social engineering technique against web applications. There are several methods to detect phishing websites such as Blacklist/Whitelist based detection, heuristic-based, and visual similarity-based detection. This paper illustrated a comparison between the heuristic-based technique using features of a uniform resource locator (URL) and visual similarity-based detection techniques that compares the content of a suspected phishing page with the legitimate one in order to detect new phishing sites based on the paper reviewed from the past few years. The comparison focuses on three indicators which are false positive and negative, accuracy of the method, and time consumed to detect phishing website.Keywords: heuristic-based technique, phishing detection, social engineering and visual similarity-based technique
Procedia PDF Downloads 1773986 Training of Future Computer Science Teachers Based on Machine Learning Methods
Authors: Meruert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova
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The article highlights and describes the characteristic features of real-time face detection in images and videos using machine learning algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As a result, the advantages and disadvantages of Haar Cascade (Haar Cascade OpenCV), HoG SVM (Histogram of Oriented Gradients, Support Vector Machine), and MMOD CNN Dlib (Max-Margin Object Detection, convolutional neural network) detectors used for face detection were determined. Dlib is a general-purpose cross-platform software library written in the programming language C++. It includes detectors used for determining face detection. The Cascade OpenCV algorithm is efficient for fast face detection. The considered work forms the basis for the development of machine learning methods by future computer science teachers.Keywords: algorithm, artificial intelligence, education, machine learning
Procedia PDF Downloads 733985 Colorimetric Detection of Ceftazdime through Azo Dye Formation on Polyethylenimine-Melamine Foam
Authors: Pajaree Donkhampa, Fuangfa Unob
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Ceftazidime is an antibiotic drug commonly used to treat several human and veterinary infections. However, the presence of ceftazidime residues in the environment may induce microbial resistance and cause side effects to humans. Therefore, monitoring the level of ceftazidime in environmental resources is important. In this work, a melamine foam platform was proposed for simultaneous extraction and colorimetric detection of ceftazidime based on the azo dye formation on the surface. The melamine foam was chemically modified with polyethyleneimine (PEI) and characterized by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). Ceftazidime is a sample that was extracted on the PEI-modified melamine foam and further reacted with nitrite in an acidic medium to form an intermediate diazonium ion. The diazotized molecule underwent an azo coupling reaction with chromotropic acid to generate a red-colored compound. The material color changed from pale yellow to pink depending on the ceftazidime concentration. The photo of the obtained material was taken by a smartphone camera and the color intensity was determined by Image J software. The material fabrication and ceftazidime extraction and detection procedures were optimized. The detection of a sub-ppm level of ceftazidime was achieved without using a complex analytical instrument.Keywords: colorimetric detection, ceftazidime, melamine foam, extraction, azo dye
Procedia PDF Downloads 1673984 Prognosis, Clinical Outcomes and Short Term Survival Analyses of Patients with Cutaneous Melanomas
Authors: Osama Shakeel
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The objective of the paper is to study the clinic-pathological factors, survival analyses, recurrence rate, metastatic rate, risk factors and the management of cutaneous malignant melanoma at Shaukat Khanum Memorial Cancer Hospital and Research Center. Methodology: From 2014 to 2017, all patients with a diagnosis of cutaneous malignant melanoma (CMM) were included in the study. Demographic variables were collected. Short and long term oncological outcomes were recorded. All data were entered and analyzed in SPSS version 21. Results: A total of 28 patients were included in the study. Median age was 46.5 +/-15.9 years. There were 16 male and 12 female patients. The family history of melanoma was present in 7.1% (n=2) of the patients. All patients had a mean survival of 13.43+/- 9.09 months. Lower limb was the commonest site among all which constitutes 46.4%(n=13). On histopathological analyses, ulceration was seen in 53.6% (n=15) patients. Unclassified tumor type was present in 75%(n=21) of the patients followed by nodular 21.4% (n=6) and superficial spreading 3.5%(n=1). Clark level IV was the commonest presentation constituting 46.4%(n=13). Metastases were seen in 50%(n=14) of the patients. Local recurrence was observed in 60.7%(n=17). 64.3%(n=18) lived after one year of treatment. Conclusion: CMM is a fatal disease. Although its disease of fair skin individuals, however, the incidence of CMM is also rising in this part of the world. Management includes early diagnoses and prompt management. However, mortality associated with this disease is still not favorable.Keywords: malignant cancer of skin, cutaneous malignant melanoma, skin cancer, survival analyses
Procedia PDF Downloads 1703983 An Electrochemical DNA Biosensor Based on Oracet Blue as a Label for Detection of Helicobacter pylori
Authors: Saeedeh Hajihosseini, Zahra Aghili, Navid Nasirizadeh
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An innovative method of a DNA electrochemical biosensor based on Oracet Blue (OB) as an electroactive label and gold electrode (AuE) for detection of Helicobacter pylori, was offered. A single–stranded DNA probe with a thiol modification was covalently immobilized on the surface of the AuE by forming an Au–S bond. Differential pulse voltammetry (DPV) was used to monitor DNA hybridization by measuring the electrochemical signals of reduction of the OB binding to double– stranded DNA (ds–DNA). Our results showed that OB–based DNA biosensor has a decent potential for detection of single–base mismatch in target DNA. Selectivity of the proposed DNA biosensor was further confirmed in the presence of non–complementary and complementary DNA strands. Under optimum conditions, the electrochemical signal had a linear relationship with the concentration of the target DNA ranging from 0.3 nmol L-1 to 240.0 nmol L-1, and the detection limit was 0.17 nmol L-1, whit a promising reproducibility and repeatability.Keywords: DNA biosensor, oracet blue, Helicobacter pylori, electrode (AuE)
Procedia PDF Downloads 2663982 Biomechanical Analysis on Skin and Jejunum of Chemically Prepared Cat Cadavers Used in Surgery Training
Authors: Raphael C. Zero, Thiago A. S. S. Rocha, Marita V. Cardozo, Caio C. C. Santos, Alisson D. S. Fechis, Antonio C. Shimano, FabríCio S. Oliveira
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Biomechanical analysis is an important factor in tissue studies. The objective of this study was to determine the feasibility of a new anatomical technique and quantify the changes in skin and the jejunum resistance of cats’ corpses throughout the process. Eight adult cat cadavers were used. For every kilogram of weight, 120ml of fixative solution (95% 96GL ethyl alcohol and 5% pure glycerin) was applied via the external common carotid artery. Next, the carcasses were placed in a container with 96 GL ethyl alcohol for 60 days. After fixing, all carcasses were preserved in a 30% sodium chloride solution for 60 days. Before fixation, control samples were collected from fresh cadavers and after fixation, three skin and jejunum fragments from each cadaver were tested monthly for strength and displacement until complete rupture in a universal testing machine. All results were analyzed by F-test (P <0.05). In the jejunum, the force required to rupture the fresh samples and the samples fixed in alcohol for 60 days was 31.27±19.14N and 29.25±11.69N, respectively. For the samples preserved in the sodium chloride solution for 30 and 60 days, the strength was 26.17±16.18N and 30.57±13.77N, respectively. In relation to the displacement required for the rupture of the samples, the values of fresh specimens and those fixed in alcohol for 60 days was 2.79±0.73mm and 2.80±1.13mm, respectively. For the samples preserved for 30 and 60 days with sodium chloride solution, the displacement was 2.53±1.03mm and 2.83±1.27mm, respectively. There was no statistical difference between the samples (P=0.68 with respect to strength, and P=0.75 with respect to displacement). In the skin, the force needed to rupture the fresh samples and the samples fixed for 60 days in alcohol was 223.86±131.5N and 211.86±137.53N respectively. For the samples preserved in sodium chloride solution for 30 and 60 days, the force was 227.73±129.06 and 224.78±143.83N, respectively. In relation to the displacement required for the rupture of the samples, the values of fresh specimens and those fixed in alcohol for 60 days were 3.67±1.03mm and 4.11±0.87mm, respectively. For the samples preserved for 30 and 60 days with sodium chloride solution, the displacement was 4.21±0.93mm and 3.93±0.71mm, respectively. There was no statistical difference between the samples (P=0.65 with respect to strength, and P=0.98 with respect to displacement). The resistance of the skin and intestines of the cat carcasses suffered little change when subjected to alcohol fixation and preservation in sodium chloride solution, each for 60 days, which is promising for use in surgery training. All experimental procedures were approved by the Municipal Legal Department (protocol 02.2014.000027-1). The project was funded by FAPESP (protocol 2015-08259-9).Keywords: anatomy, conservation, fixation, small animal
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