Search results for: sequential extraction
785 Physico-Chemical and Antibacterial Properties of Neem Extracts
Authors: C. C. Igwe
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Several parts of Neem tree (Azadirachta indica) are used in traditional medicine in many West African countries for the treatment of various human diseases. The leaf, stem - bark and seed were air dried for 8, 5 and 7 days, respectively. The shells were carfully separated from the seeds, each powdered sample obtained with mechanical miller and 250 mm sieve. The neem samples were individually subjected to extraction with acetone, n-hexane for 48hr and 72 hr, respectively. Physico-chemical and antibacterial evaluation were carried out using standard methods. Results of physico - chemical analyses of the extracted oil from the seed shows that it has a brownish colour, with a smell similar to garlic while the moisture content, refractive index are 0.76% and 1.47 respectively. Other vital chemical results obtained from the neem oil such as saponification value (234.62), acid value (10.84 %), free fatty acid (5.84 %) and peroxide value (10.52%) indicated the oil extracted satisfied standard oils parameters for quality soap and cosmetics production. The antibacterial screening by disc diffusion revealed the oil demonstrated high activity against Staphylococcus aureus. Both the physio-chemical and antibacterial of samples have been certified by National Agency for Food and Drugs Administration and Control. The preliminary results of this study may validate the medicinal value of the plant. Further studies are in progress to clarify the in vivo potentials of neem extracts in the management of human communicable diseases and this is a subject of investigation in our group.Keywords: anti-bacterial, neem extract, physico-chemical analyses, staphylococcus aureus
Procedia PDF Downloads 68784 Reconstructed Phase Space Features for Estimating Post Traumatic Stress Disorder
Authors: Andre Wittenborn, Jarek Krajewski
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Trauma-related sadness in speech can alter the voice in several ways. The generation of non-linear aerodynamic phenomena within the vocal tract is crucial when analyzing trauma-influenced speech production. They include non-laminar flow and formation of jets rather than well-behaved laminar flow aspects. Especially state-space reconstruction methods based on chaotic dynamics and fractal theory have been suggested to describe these aerodynamic turbulence-related phenomena of the speech production system. To extract the non-linear properties of the speech signal, we used the time delay embedding method to reconstruct from a scalar time series (reconstructed phase space, RPS). This approach results in the extraction of 7238 Features per .wav file (N= 47, 32 m, 15 f). The speech material was prompted by telling about autobiographical related sadness-inducing experiences (sampling rate 16 kHz, 8-bit resolution). After combining these features in a support vector machine based machine learning approach (leave-one-sample out validation), we achieved a correlation of r = .41 with the well-established, self-report ground truth measure (RATS) of post-traumatic stress disorder (PTSD).Keywords: non-linear dynamics features, post traumatic stress disorder, reconstructed phase space, support vector machine
Procedia PDF Downloads 100783 Determination of Hydrolisis Condition in the Extraction of Fatty Acids from Pinchagua's (Opisthonema libertate) Heads, a By-Product of Sardine Industry
Authors: Belen Carrillo, Mauricio Mosquera
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Fatty acids are bioactive compounds widely used as nutritional supplements in the food and pharmaceutical industry. Bluefish such as sardines have a large variety of these fatty acids in their composition. The objective of this project is to extract these compounds from fishing wastes, to do this, heads of known species as Pinchagua (Opistonema libertate) were used. The conducted study represents a simplified alternative for obtaining and simultaneous saponification of oil through basic hydrolysis, which separates lipids from protein and saponifies sample all the same time to isolate the fatty acid accurately through salts formation. To do these different concentrations of sodium hydroxide were used, it was demonstrated at a concentration of 1 M the highest yield of saponified oil recovery corresponding a value of 3,64% was obtained. Subsequently, the saponified oil was subjected to an acid hydrolysis in which fatty acids were isolated. Different sulfuric acid concentrations and temperatures for the process were tested. Thus, it was shown that the great fatty acids variety were obtained at a 60 °C temperature and sulfuric acid concentration of 50% v/v. Among the obtained compounds the presence of acids such as palmitic, lauric, caproic and myristic are highlighted. Applications of this type of elements are varied and widely used in the nutritional supplements development. Thus, the described methodology proposes a simple mechanism in the revaluation of fishing industry wastes that allow directly generate high added value elements.Keywords: fatty acids, hydrolysis, Pinchagua, saponification
Procedia PDF Downloads 176782 Using Deep Learning Real-Time Object Detection Convolution Neural Networks for Fast Fruit Recognition in the Tree
Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli
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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture
Procedia PDF Downloads 412781 Segmentation of the Liver and Spleen From Abdominal CT Images Using Watershed Approach
Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid
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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm
Procedia PDF Downloads 488780 Prediction of Disability-Adjustment Mental Illness Using Machine
Authors: R. M. Krishna Sureddi, V. Kamakshi Prasad, R. Santosh
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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). One DALY represents the loss of the equivalent of one year of full health. DALYs for a disease or health condition are the sum of years of life lost due to premature mortality (YLLs) and years of healthy life lost due to disability (YLDs) due to prevalent cases of the disease or health condition in a population. The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population. Procedia PDF Downloads 20779 Contribution to the Development of a New Design of Dentist's Gowns: A Case Study of Using Infra-Red Technology and Pressure Sensors
Authors: Tran Thi Anh Dao, M. Arnold, L. Schacher, D. C. Adolphe, G. Reys
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During tooth extraction or implant surgery, dentists are in contact with numerous infectious germs from patients' saliva and blood. For that reason, dentist's clothes have to play their role of protection from contamination. In addition, dentist's apparels should be not only protective but also comfortable and breathable because dentists have to perform many operations and treatments on patients throughout the day with high concentration and intensity. However, this type of protective garments has not been studied scientifically, whereas dentists are facing new risks and eager for looking for a comfortable personal protective equipment. For that reason, we have proposed some new designs of dentist's gown. They were expected to diminish heat accumulation that are considered as an important factor in reducing the level of comfort experienced by users. Experiments using infra-red technology were carried out in order to compare the breathable properties between a traditional gown and a new design with open zones. Another experiment using pressure sensors was also carried out to study ergonomic aspects trough the flexibility of movements of sleeves. The sleeves-design which is considered comfortable and flexible will be chosen for the further step. The results from the two experiments provide valuable information for the development of a new design of dentists' gowns in order to achieve maximum levels of cooling and comfort for the human body.Keywords: garment, dentists, comfort, design, protection, thermal
Procedia PDF Downloads 216778 Investigating the Essentiality of Oxazolidinones in Resistance-Proof Drug Combinations in Mycobacterium tuberculosis Selected under in vitro Conditions
Authors: Gail Louw, Helena Boshoff, Taeksun Song, Clifton Barry
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Drug resistance in Mycobacterium tuberculosis is primarily attributed to mutations in target genes. These mutations incur a fitness cost and result in bacterial generations that are less fit, which subsequently acquire compensatory mutations to restore fitness. We hypothesize that mutations in specific drug target genes influence bacterial metabolism and cellular function, which affects its ability to develop subsequent resistance to additional agents. We aim to determine whether the sequential acquisition of drug resistance and specific mutations in a well-defined clinical M. tuberculosis strain promotes or limits the development of additional resistance. In vitro mutants resistant to pretomanid, linezolid, moxifloxacin, rifampicin and kanamycin were generated from a pan-susceptible clinical strain from the Beijing lineage. The resistant phenotypes to the anti-TB agents were confirmed by the broth microdilution assay and genetic mutations were identified by targeted gene sequencing. Growth of mono-resistant mutants was done in enriched medium for 14 days to assess in vitro fitness. Double resistant mutants were generated against anti-TB drug combinations at concentrations 5x and 10x the minimum inhibitory concentration. Subsequently, mutation frequencies for these anti-TB drugs in the different mono-resistant backgrounds were determined. The initial level of resistance and the mutation frequencies observed for the mono-resistant mutants were comparable to those previously reported. Targeted gene sequencing revealed the presence of known and clinically relevant mutations in the mutants resistant to linezolid, rifampicin, kanamycin and moxifloxacin. Significant growth defects were observed for mutants grown under in vitro conditions compared to the sensitive progenitor. Mutation frequencies determination in the mono-resistant mutants revealed a significant increase in mutation frequency against rifampicin and kanamycin, but a significant decrease in mutation frequency against linezolid and sutezolid. This suggests that these mono-resistant mutants are more prone to develop resistance to rifampicin and kanamycin, but less prone to develop resistance against linezolid and sutezolid. Even though kanamycin and linezolid both inhibit protein synthesis, these compounds target different subunits of the ribosome, thereby leading to different outcomes in terms of fitness in the mutants with impaired cellular function. These observations showed that oxazolidinone treatment is instrumental in limiting the development of multi-drug resistance in M. tuberculosis in vitro.Keywords: oxazolidinones, mutations, resistance, tuberculosis
Procedia PDF Downloads 156777 Recognizing Customer Preferences Using Review Documents: A Hybrid Text and Data Mining Approach
Authors: Oshin Anand, Atanu Rakshit
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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.Keywords: association mining, customer preference, frequent pattern, online reviews, text mining
Procedia PDF Downloads 384776 Diversity Indices as a Tool for Evaluating Quality of Water Ways
Authors: Khadra Ahmed, Khaled Kheireldin
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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: planktons, diversity indices, water quality index, water ways
Procedia PDF Downloads 510775 Development and Psychometric Validation of the Hospitalised Older Adults Dignity Scale for Measuring Dignity during Acute Hospital Admissions
Authors: Abdul-Ganiyu Fuseini, Bernice Redley, Helen Rawson, Lenore Lay, Debra Kerr
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Aim: The study aimed to develop and validate a culturally appropriate patient-reported outcome measure for measuring dignity for older adults during acute hospital admissions. Design: A three-phased mixed-method sequential exploratory design was used. Methods: Concept elicitation and generation of items for the scale was informed by older adults’ perspectives about dignity during acute hospitalization and a literature review. Content validity evaluation and pre-testing were undertaken using standard instrument development techniques. A cross-sectional survey design was conducted involving 270 hospitalized older adults for evaluation of construct and convergent validity, internal consistency reliability, and test–retest reliability of the scale. Analysis was performed using Statistical Package for the Social Sciences, version 25. Reporting of the study was guided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. Results: We established the 15-item Hospitalized Older Adults’ Dignity Scale that has a 5-factor structure: Shared Decision-Making (3 items); Healthcare Professional-Patient Communication (3 items); Patient Autonomy (4 items); Patient Privacy (2 items); and Respectful Care (3 items). Excellent content validity, adequate construct and convergent validity, acceptable internal consistency reliability, and good test-retest reliability were demonstrated. Conclusion: We established the Hospitalized Older Adults Dignity Scale as a valid and reliable scale to measure dignity for older adults during acute hospital admissions. Future studies using confirmatory factor analysis are needed to corroborate the dimensionality of the factor structure and external validity of the scale. Routine use of the scale may provide information that informs the development of strategies to improve dignity-related care in the future. Impact: The development and validation of the Hospitalized Older Adults Dignity Scale will provide healthcare professionals with a feasible and reliable scale for measuring older adults’ dignity during acute hospitalization. Routine use of the scale may enable the capturing and incorporation of older patients’ perspectives about their healthcare experience and provide information that informs the development of strategies to improve dignity-related care in the future.Keywords: dignity, older adults, hospitalisation, scale, patients, dignified care, acute care
Procedia PDF Downloads 84774 Vehicular Speed Detection Camera System Using Video Stream
Authors: C. A. Anser Pasha
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In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.Keywords: radar, image processing, detection, tracking, segmentation
Procedia PDF Downloads 460773 A Transformer-Based Question Answering Framework for Software Contract Risk Assessment
Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha
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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.Keywords: contract risk assessment, NLP, transfer learning, question answering
Procedia PDF Downloads 126772 An Experimental Investigation of the Variation of Evaporator Efficiency According to Load Amount and Textile Type in Hybrid Heat Pump Dryers
Authors: Gokhan Sir, Muhammed Ergun, Onder Balioglu
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Nowadays, laundry dryers containing heaters and heat pumps are used to provide fast and efficient drying. In this system, as the drying capacity changes, the sensible and latent heat transfer rate in the evaporator changes. Therefore, the drying time measured for the unit capacity increases as the drying capacity decreases. The objective of this study is to investigate the evaporator efficiency according to load amount and textile type in hybrid heat pump dryers. Air side flow rate and system temperatures (air side and refrigeration side) were monitored instantly, and the specific moisture extraction rate (SMER), evaporator efficiency, and heat transfer mechanism between the textile and hybrid heat pump system were examined. Evaporator efficiency of heat pump dryers for cotton and synthetic based textile types in load amounts of 2, 5, 8 and 10 kg were investigated experimentally. As a result, the maximum evaporator efficiency (%72) was obtained in drying cotton and synthetic based textiles with a capacity of 5 kg; the minimum evaporator efficiency (%40) was obtained in drying cotton and synthetic based textiles with a capacity of 2 kg. The experimental study also reveals that capacity-dependent flow rate changes are the major factor for evaporator efficiency.Keywords: evaporator, heat pump, hybrid, laundry dryer, textile
Procedia PDF Downloads 134771 Electrodeposition of Silicon Nanoparticles Using Ionic Liquid for Energy Storage Application
Authors: Anjali Vanpariya, Priyanka Marathey, Sakshum Khanna, Roma Patel, Indrajit Mukhopadhyay
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Silicon (Si) is a promising negative electrode material for lithium-ion batteries (LiBs) due to its low cost, non-toxicity, and a high theoretical capacity of 4200 mAhg⁻¹. The primary challenge of the application of Si-based LiBs is large volume expansion (~ 300%) during the charge-discharge process. Incorporation of graphene, carbon nanotubes (CNTs), morphological control, and nanoparticles was utilized as effective strategies to tackle volume expansion issues. However, molten salt methods can resolve the issue, but high-temperature requirement limits its application. For sustainable and practical approach, room temperature (RT) based methods are essentially required. Use of ionic liquids (ILs) for electrodeposition of Si nanostructures can possibly resolve the issue of temperature as well as greener media. In this work, electrodeposition of Si nanoparticles on gold substrate was successfully carried out in the presence of ILs media, 1-butyl-3-methylimidazolium-bis (trifluoromethyl sulfonyl) imide (BMImTf₂N) at room temperature. Cyclic voltammetry (CV) suggests the sequential reduction of Si⁴⁺ to Si²⁺ and then Si nanoparticles (SiNs). The structure and morphology of the electrodeposited SiNs were investigated by FE-SEM and observed interconnected Si nanoparticles of average particle size ⁓100-200 nm. XRD and XPS data confirm the deposition of Si on Au (111). The first discharge-charge capacity of Si anode material has been found to be 1857 and 422 mAhg⁻¹, respectively, at current density 7.8 Ag⁻¹. The irreversible capacity of the first discharge-charge process can be attributed to the solid electrolyte interface (SEI) formation via electrolyte decomposition, and trapped Li⁺ inserted into the inner pores of Si. Pulverization of SiNs results in the creation of a new active site, which facilitates the formation of new SEI in the subsequent cycles leading to fading in a specific capacity. After 20 cycles, charge-discharge profiles have been stabilized, and a reversible capacity of 150 mAhg⁻¹ is retained. Electrochemical impedance spectroscopy (EIS) data shows the decrease in Rct value from 94.7 to 47.6 kΩ after 50 cycles of charge-discharge, which demonstrates the improvements of the interfacial charge transfer kinetics. The decrease in the Warburg impedance after 50 cycles of charge-discharge measurements indicates facile diffusion in fragmented and smaller Si nanoparticles. In summary, Si nanoparticles deposited on gold substrate using ILs as media and characterized well with different analytical techniques. Synthesized material was successfully utilized for LiBs application, which is well supported by CV and EIS data.Keywords: silicon nanoparticles, ionic liquid, electrodeposition, cyclic voltammetry, Li-ion battery
Procedia PDF Downloads 122770 Implementation of a Multimodal Biometrics Recognition System with Combined Palm Print and Iris Features
Authors: Rabab M. Ramadan, Elaraby A. Elgallad
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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)
Procedia PDF Downloads 231769 Blood Volume Pulse Extraction for Non-Contact Photoplethysmography Measurement from Facial Images
Authors: Ki Moo Lim, Iman R. Tayibnapis
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According to WHO estimation, 38 out of 56 million (68%) global deaths in 2012, were due to noncommunicable diseases (NCDs). To avert NCD, one of the solutions is early detection of diseases. In order to do that, we developed 'U-Healthcare Mirror', which is able to measure vital sign such as heart rate (HR) and respiration rate without any physical contact and consciousness. To measure HR in the mirror, we utilized digital camera. The camera records red, green, and blue (RGB) discoloration from user's facial image sequences. We extracted blood volume pulse (BVP) from the RGB discoloration because the discoloration of the facial skin is accordance with BVP. We used blind source separation (BSS) to extract BVP from the RGB discoloration and adaptive filters for removing noises. We utilized singular value decomposition (SVD) method to implement the BSS and the adaptive filters. HR was estimated from the obtained BVP. We did experiment for HR measurement by using our method and previous method that used independent component analysis (ICA) method. We compared both of them with HR measurement from commercial oximeter. The experiment was conducted under various distance between 30~110 cm and light intensity between 5~2000 lux. For each condition, we did measurement 7 times. The estimated HR showed 2.25 bpm of mean error and 0.73 of pearson correlation coefficient. The accuracy has improved compared to previous work. The optimal distance between the mirror and user for HR measurement was 50 cm with medium light intensity, around 550 lux.Keywords: blood volume pulse, heart rate, photoplethysmography, independent component analysis
Procedia PDF Downloads 324768 Unstructured-Data Content Search Based on Optimized EEG Signal Processing and Multi-Objective Feature Extraction
Authors: Qais M. Yousef, Yasmeen A. Alshaer
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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization
Procedia PDF Downloads 171767 Isolation and Screening of Fungal Strains for β-Galactosidase Production
Authors: Parmjit S. Panesar, Rupinder Kaur, Ram S. Singh
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Enzymes are the biocatalysts which catalyze the biochemical processes and thus have a wide variety of applications in the industrial sector. β-Galactosidase (E.C. 3.2.1.23) also known as lactase, is one of the prime enzymes, which has significant potential in the dairy and food processing industries. It has the capability to catalyze both the hydrolytic reaction for the production of lactose hydrolyzed milk and transgalactosylation reaction for the synthesis of prebiotics such as lactulose and galactooligosaccharides. These prebiotics have various nutritional and technological benefits. Although, the enzyme is naturally present in almonds, peaches, apricots and other variety of fruits and animals, the extraction of enzyme from these sources increases the cost of enzyme. Therefore, focus has been shifted towards the production of low cost enzyme from the microorganisms such as bacteria, yeast and fungi. As compared to yeast and bacteria, fungal β-galactosidase is generally preferred as being extracellular and thermostable in nature. Keeping the above in view, the present study was carried out for the isolation of the β-galactosidase producing fungal strain from the food as well as the agricultural wastes. A total of more than 100 fungal cultures were examined for their potential in enzyme production. All the fungal strains were screened using X-gal and IPTG as inducers in the modified Czapek Dox Agar medium. Among the various isolated fungal strains, the strain exhibiting the highest enzyme activity was chosen for further phenotypic and genotypic characterization. The strain was identified as Rhizomucor pusillus on the basis of 5.8s RNA gene sequencing data.Keywords: beta-galactosidase, enzyme, fungal, isolation
Procedia PDF Downloads 246766 Development of Mg-Containing Hydroxyapatite-Based Bioceramics From Phosphate Rock for Bone Applications
Authors: Sara Mercedes Barroso Pinzón, Álvaro Jesús Caicedo Castro, Antonio Javer Sánchez Herencia
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In recent years there has been increased academic and industrial research into the development of orthopaedic implants with structural properties and functionality similar to mechanical strength, osseointegration, thermal stability and antibacterial capacity similar to bone structure. Hydroxyapatite has been considered for decades as an ideal biomaterial for bone regeneration due to its chemical and crystallographic similarity to the mineral structure bioapatites. However, the lack of trace elements in the hydroxyapatite structure confers very low mechanical and biological properties. Under this scenario, the objective of the research is the synthesis of hydroxyapatite with Mg from the francolite mineral present in phosphate rock from the central-eastern region of Colombia, taking advantage of the extraction of mineral species as natural precursors of Ca, P and Mg. The minerals present were studied, fluorapatite as the mineral of interest associated with magnesium carbonates and quartz. The chemical and mineralogical composition was determined by X-ray fluorescence (XRF) and X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX); the optimum conditions were established using the acid leaching mechanism in the wet concentration process. From the products obtained and characterised by XRD, XRF, SEM, FTIR, RAMAN, HAp-Mg biocomposite scaffolds are fabricated and the influence of Mg on morphometric parameters, mechanical and biological properties in the formed materials is evaluated.Keywords: phosphate rock, hydroxyapatite, magnesium, biomaterials
Procedia PDF Downloads 48765 Principle Component Analysis on Colon Cancer Detection
Authors: N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Rita Magdalena, R. D. Atmaja, Sofia Saidah, Ocky Tiaramukti
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Colon cancer or colorectal cancer is a type of cancer that attacks the last part of the human digestive system. Lymphoma and carcinoma are types of cancer that attack human’s colon. Colon cancer causes deaths about half a million people every year. In Indonesia, colon cancer is the third largest cancer case for women and second in men. Unhealthy lifestyles such as minimum consumption of fiber, rarely exercising and lack of awareness for early detection are factors that cause high cases of colon cancer. The aim of this project is to produce a system that can detect and classify images into type of colon cancer lymphoma, carcinoma, or normal. The designed system used 198 data colon cancer tissue pathology, consist of 66 images for Lymphoma cancer, 66 images for carcinoma cancer and 66 for normal / healthy colon condition. This system will classify colon cancer starting from image preprocessing, feature extraction using Principal Component Analysis (PCA) and classification using K-Nearest Neighbor (K-NN) method. Several stages in preprocessing are resize, convert RGB image to grayscale, edge detection and last, histogram equalization. Tests will be done by trying some K-NN input parameter setting. The result of this project is an image processing system that can detect and classify the type of colon cancer with high accuracy and low computation time.Keywords: carcinoma, colorectal cancer, k-nearest neighbor, lymphoma, principle component analysis
Procedia PDF Downloads 199764 Automatic Early Breast Cancer Segmentation Enhancement by Image Analysis and Hough Transform
Authors: David Jurado, Carlos Ávila
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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis
Procedia PDF Downloads 74763 Cytotoxic Activity of Extracts from Hibiscus sabdariffa Leaves against Women’s Cancer Cell Lines
Authors: Patsorn Worawattananutai, Srisopa Ruangnoo, Arunporn Itharat
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Hibiscus sabdariffa (HS) leaves are vegetables which are extensively used as blood tonic and laxatives in Thai traditional medicine. They are popularly used as healthy sour soup for prevention of chronic diseases such as cancer. Therefore, the cytotoxic activity of different extracts of fresh and dried Hibiscus sabdariffa leaves were investigated via the sulforhodamine B (SRB) assay against three types of women’s cancer cell lines, namely the human cervical adenocarcinoma cell line (HeLa), the human ovarian adenocarcinoma cell line (SKOV-3), and the human breast adenocarcinoma cell line (MCF-7). Extraction methods were squeezing, boiling with water and maceration with 95% or 50% ethanol. The 95% ethanolic extracts of Hibiscus sabdariffa dry leaves (HSDE95) showed the highest cytotoxicity against all types of women’s cancer cell lines with the IC50 values in range 7.51±0.33 to 12.13±1.85 µg/ml. Its IC50 values against SKOV-3, HeLa and MCF-7 were 7.51±0.33, 9.44±1.41 and 12.13±1.85 µg/ml, respectively. In these results, this extract can be classified as “active” according to the NCI guideline which indicated that IC50 values of the active cytotoxic plant extracts have to be beneath 20 µg/ml. Thus, HSDE95 was concluded to be a potent cytotoxic drug for all women’s cancer cells. This extract should be further investigated to isolate active compounds against women’s cancer cells.Keywords: breast adenocarcinoma, cervical adenocarcinoma, cytotoxic activity, Hibiscus sabdariffa, ovarian adenocarcinoma
Procedia PDF Downloads 591762 Traumatic Brachiocephalic Artery Pseudoaneurysm
Authors: Sally Shepherd, Jessica Wong, David Read
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Traumatic brachiocephalic artery aneurysm is a rare injury that typically occurs as a result of a blunt chest injury. A 19-year-old female sustained a head-on, high speed motor vehicle crash into a tree. Upon release after 45 minutes of entrapment, she was tachycardic but normotensive, with a significant seatbelt sign across her chest and open deformed right thigh with weak pulses in bilateral lower limbs. A chest XR showed mild upper mediastinal widening. A CT trauma series plus gated CT chest revealed a grade 3a aortic arch transection with brachiocephalic pseudoaneurysm. Endovascular repair of the brachiocephalic artery was attempted post-presentation but was unsuccessful as the first stent migrated to the infrarenal abdominal aorta and the second stent across the brachiocephalic artery origin had a persistent leak at the base. She was transferred to Intensive Care for strict blood pressure control. She returned to theatre 5 hours later for a median sternotomy, aortic arch repair with an 8mm graft extraction, and excision of the innominate artery pseudoaneurysm. She had an uncomplicated post-operative recovery. This case highlights that brachiocephalic artery injury is a rare but potentially lethal injury as a result of blunt chest trauma. Safe management requires a combined Vascular and Cardiothoracic team approach, as stenting alone may be insufficient.Keywords: blunt chest injury, Brachiocephalic aneurysm, innominate artery, trauma
Procedia PDF Downloads 227761 Experimental Modeling and Simulation of Zero-Surface Temperature of Controlled Water Jet Impingement Cooling System for Hot-Rolled Steel Plates
Authors: Thomas Okechukwu Onah, Onyekachi Marcel Egwuagu
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Zero-surface temperature, which controlled the cooling profile, was modeled and used to investigate the effect of process parameters on the hot-rolled steel plates. The parameters include impingement gaps of 40mm to 70mm; pipe diameters of 20mm to 45mm feeding jet nozzle with 30 holes of 8mm diameters each; and flow rates within 2.896x10-⁶m³/s and 3.13x10-⁵m³/s. The developed simulation model of the Zero-Surface Temperature, upon validation, showed 99% prediction accuracy with dimensional homogeneity established. The evaluated Zero-Surface temperature of Controlled Water Jet Impingement Steel plates showed a high cooling rate of 36.31 Celsius degree/sec at an optimal cooling nozzle diameter of 20mm, impingement gap of 70mm and a flow rate of 1.77x10-⁵m³/s resulting in Reynold's number 2758.586, in the turbulent regime was obtained. It was also deduced that as the nozzle diameter was increasing, the impingement gap was reducing. This achieved a faster rate of cooling to an optimum temperature of 300oC irrespective of the starting surface cooling temperature. The results additionally showed that with a tested-plate initial temperature of 550oC, a controlled cooling temperature of about 160oC produced a film and nucleated boiling heat extraction that was particularly beneficial at the end of controlled cooling and influenced the microstructural properties of the test plates.Keywords: temperature, mechanistic-model, plates, impingements, dimensionless-numbers
Procedia PDF Downloads 30760 Effects of Certain Natural Food Additives (Pectin, Gelatin and Whey Proteins) on the Qualities of Fermented Milk
Authors: Abderrahim Cheriguene, Fatiha Arioui
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The experimental study focuses on the extraction of pectin, whey protein and gelatin, and the study of their functional properties. Microbiological, physicochemical and sensory approach integrated has been implanted to study the effect of the incorporation of these natural food additives in the matrix of a fermented milk type set yogurt, to study the stability of the product during the periods of fermentation and post-acidification over a period of 21 days at 4°C. Pectin was extracted in hot HCl solution. Thermo-precipitation was carried out to obtain the whey proteins while the gelatin was extracted by hydrolysis of the collagen from bovine ossein. The fermented milk was prepared by varying the concentration of the incorporated additives. The measures and controls carried performed periodically on fermented milk experimental tests were carried out: pH, acidity, viscosity, the enumeration of Streptococcus thermophilus, cohesiveness, adhesiveness, taste, aftertaste, whey exudation, and odor. It appears that the acidity, viscosity, and number of Streptococcus thermophilus increased with increasing concentration of additive added in the experimental tests. Indeed, it seems clear that the quality of fermented milk and storability is more improved than the incorporation rate is high. The products showed a better test and a firmer texture limiting the whey exudation.Keywords: fermented milk, pectin, gelatin, whey proteins, functional properties, quality, conservation, valorization
Procedia PDF Downloads 133759 The Design of a Mixed Matrix Model for Activity Levels Extraction and Sub Processes Classification of a Work Project (Case: Great Tehran Electrical Distribution Company)
Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini
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Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process
Procedia PDF Downloads 488758 Environmental Cost and Benefits Analysis of Different Electricity Option: A Case Study of Kuwait
Authors: Mohammad Abotalib, Hamid Alhamadi
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In Kuwait, electricity is generated from two primary sources that are heavy fuel combustion and natural gas combustion. As Kuwait relies mainly on petroleum-based products for electricity generation, identifying and understanding the environmental trade-off of such operations should be carefully investigated. The life cycle assessment (LCA) tool is applied to identify the potential environmental impact of electricity generation under three scenarios by considering the material flow in various stages involved, such as raw-material extraction, transportation, operations, and waste disposal. The three scenarios investigated represent current and futuristic electricity grid mixes. The analysis targets six environmental impact categories: (1) global warming potential (GWP), (2) acidification potential (AP), (3) water depletion (WD), (4) acidification potential (AP), (4) eutrophication potential (EP), (5) human health particulate matter (HHPM), and (6) smog air (SA) per one kWh of electricity generated. Results indicate that one kWh of electricity generated would have a GWP (881-1030) g CO₂-eq, mainly from the fuel combustion process, water depletion (0.07-0.1) m³ of water, about 68% from cooling processes, AP (15.3-17.9) g SO₂-eq, EP (0.12-0.14) g N eq., HHPA (1.13- 1.33)g PM₂.₅ eq., and SA (64.8-75.8) g O₃ eq. The variation in results depend on the scenario investigated. It can be observed from the analysis that introducing solar photovoltaic and wind to the electricity grid mix improves the performance of scenarios 2 and 3 where 15% of the electricity comes from renewables correspond to a further decrease in LCA results.Keywords: energy, functional uni, global warming potential, life cycle assessment, energy, functional unit
Procedia PDF Downloads 129757 Impact of Wastewater from Outfalls of River Ganga on Germination Percentage and Growth Parameters of Bitter Gourd (Momordica charantia L.) with Antioxidant Activity Study
Authors: Sayanti Kar, Amitava Ghosh, Pritam Aitch, Gupinath Bhandari
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An extensive seasonal analysis of wastewater had been done from outfalls of river Ganga in Howrah, Hooghly, 24 PGS (N) District, West Bengal, India during 2017. The morphological parameters of Bitter gourd (Momordica charantia L.) were estimated under wastewater treatment. An approach to study the activity within the range of low molecular weight peptide 3-0.5 kDa were taken through its extraction and purification by ion exchange resin column, cation, and anion exchanger. HPLC analysis had been done for both in wastewater treated and untreated plants. The antioxidant activity by using DPPH and germination percentage in control and treated plants were also determined in relation to wastewater effect. The inhibition of growth and its parameters were maximum in pre-monsoon in comparing to post-monsoon and monsoon season. The study also helped to explore the effect of wastewater on the peptidome of Bitter gourd (Momordica charantia L.). Some of these low molecular weight peptide(s) (3-0.5 kDa) also inhibited during wastewater treatment. Expression of particular peptide(s) or absence of some peptide(s) in chromatogram indicated the adverse effects on plants which may be the indication of stressful condition. Pre monsoon waste water was found to create more impact than other two.Keywords: bitter gourd (Momordica charantia l.), low molecular weight peptide, river ganga, waste water
Procedia PDF Downloads 119756 Physicochemical Characterization of Waste from Vegetal Extracts Industry for Use as Briquettes
Authors: Maíra O. Palm, Cintia Marangoni, Ozair Souza, Noeli Sellin
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Wastes from a vegetal extracts industry (cocoa, oak, Guarana and mate) were characterized by particle size, proximate and ultimate analysis, lignocellulosic fractions, high heating value, thermal analysis (Thermogravimetric analysis – TGA, and Differential thermal analysis - DTA) and energy density to evaluate their potential as biomass in the form of briquettes for power generation. All wastes presented adequate particle sizes to briquettes production. The wastes showed high moisture content, requiring previous drying for use as briquettes. Cocoa and oak wastes had the highest volatile matter contents with maximum mass loss at 310 ºC and 450 ºC, respectively. The solvents used in the aroma extraction process influenced in the moisture content of the wastes, which was higher for mate due to water has been used as solvent. All wastes showed an insignificant loss mass after 565 °C, hence resulting in low ash content. High carbon and hydrogen contents and low sulfur and nitrogen contents were observed ensuring a low generation of sulfur and nitrous oxides. Mate and cocoa exhibited the highest carbon and lignin content, and high heating value. The dried wastes had high heating value, from 17.1 MJ/kg to 20.8 MJ/kg. The results indicate the energy potential of wastes for use as fuel in power generation.Keywords: agro-industrial waste, biomass, briquettes, combustion
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