Search results for: color metrics

Authors: Saahith M. S., Sivakami R.

Abstract:

In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

Procedia PDF Downloads 35

Authors: May Phyo Wai, Tanyawan Suantawee

Abstract:

The positive correlation between unhealthy diets (high in fats, sugars, carbohydrates, and low fibers) and the risk of non-communicable diseases (NCDs) like obesity, hypertension, diabetes, and heart diseases has led to a growing interest in healthier lifestyles and diets. Consequently, people are opting for foods rich in fiber and phytochemicals. Wolffia globosa, also known as duckweed or watermeal, is the smallest plant with high nutritional value, including protein, fiber, phytochemicals, and antioxidant properties. It offers numerous health benefits, such as improving gut health and lowering blood glucose levels, and it is widely available in Thailand. The purpose of this study was to develop nutritionally enhanced breadsticks utilizing vacuum heat-dried Wolffia globosa power (WP). Various concentrations of WP (0% as control, 5%, 10%, and 15 % w/w/) were added, and then the breadsticks’ physical properties (hardness, fracturability, and color), phytochemicals (total phenolic compounds: TPC and total flavonoid contents: TFC), and antioxidant properties (DPPH radical scavenging activity (DPPH) and ferric reducing antioxidant power (FRAP) assay) were investigated. Experiments were done by triplicates and data was analyzed by one-way ANOVA. The results showed that the hardness, measured by a texture analyzer, increased significantly (p<0.05) with higher WP concentrations, reaching 2,897.01 ± 77.31 g at 15% WP from 1,314.41 ± 32.52 g of the control. In contrast, the lightness (L*), redness (a*), and yellowness (b*) of the breadsticks significantly decreased (p < 0.05) in a dose-dependent manner with added WP. Incorporating WP, rich in phytochemicals and antioxidants, into the flour significantly enhanced the TPC and TFC of the breadsticks (p<0.05), with TPC and TFC increasing dose-dependently rising to 1.8-fold and 3.5-fold at 15% WP, respectively. The antioxidant power, assessed by DPPH and FRAP assays, also showed a similar trend, with significantly higher values at 10% and 15% WP (p<0.05). These results indicate that adding WP significantly boosted the TPC, TFC, DPPH, and FRAP values of the developed breadsticks. Therefore, incorporating WP into breadsticks might be a promising strategy for creating food products enriched with phytochemicals and antioxidants, offering consumers healthier options in the market.

Keywords: antioxidant properties, breadsticks, phytochemicals, Wolffia globosa

Procedia PDF Downloads 26

Authors: Nidhi Gupta, Omita Nanda, Rakhi Grover, Kanchan Saxena

Abstract:

Hybrid perovskite is new class of material which has gained much attention due to their different crystal structure and interesting optical and electrical properties. Easy fabrication, high absorption coefficient, and photoluminescence properties make them a strong candidate for various applications such as sensors, photovoltaics, photodetectors, etc. In perovskites, ions arrange themselves in a special type of crystal structure with chemical formula ABX3, where A is organic species like CH3NH3+, B is metal ion (e.g., Pb, Sn, etc.) and X is halide (Cl-, Br-, I-). In crystal structure, A is present at corner position, B at center of the crystal lattice and halide ions at the face centers. High stability and sensitivity of nanostructured perovskite make them suitable for chemical sensors. Researchers have studied sensing properties of perovskites for number of analytes such as 2,4,6-trinitrophenol, ethanol and other hazardous chemical compounds. Ammonia being highly toxic agent makes it a reason of concern for the environment. Thus the detection of ammonia is extremely important. Our present investigation deals with organic inorganic hybrid perovskite based ammonia sensor. Various methods like sol-gel, solid state synthesis, thermal vapor deposition etc can be used to synthesize Different hybrid perovskites. In the present work, a novel hybrid perovskite has been synthesized by a single step method. Ethylenediammnedihalide and lead halide were used as precursor. Formation of hybrid perovskite was confirmed by FT-IR and XRD. Morphological characterization of the synthesized material was performed using scanning electron microscopy (SEM). SEM analysis revealed the formation of one dimensional nanowire perovskite with mean diameter of 200 nm. Measurements for sensing properties of halide perovskite for ammonia vapor were carried out. Perovskite thin films showed a color change from yellow to orange on exposure of ammonia vapor. Electro-optical measurements show that sensor based on lead halide perovskite has high sensitivity towards ammonia with effective selectivity and reversibility. Sensor exhibited rapid response time of less than 20 seconds.

Keywords: hybrid perovskite, ammonia, sensor, nanostructure, thin film

Procedia PDF Downloads 271

Authors: Shinsuke Udagawa, Masato Yamagishi, Masanori Ota

Abstract:

The Schlieren method, which has been conventionally used to visualize high-speed flows, has disadvantages such as the complexity of the experimental setup and the inability to quantitatively analyze the amount of refraction of light. The Background Oriented Schlieren (BOS) method proposed by Meier is one of the measurement methods that solves the problems, as mentioned above. The refraction of light is used for BOS method same as the Schlieren method. The BOS method is characterized using a digital camera to capture the images of the background behind the observation area. The images are later analyzed by a computer to quantitatively detect the amount of shift of the background image. The experimental setup for BOS does not require concave mirrors, pinholes, or color filters, which are necessary in the conventional Schlieren method, thus simplifying the experimental setup. However, the defocusing of the observation results is caused in case of using BOS method. Since the focus of camera on the background image leads to defocusing of the observed object. The defocusing of object becomes greater with increasing the distance between the background and the object. On the other hand, the higher sensitivity can be obtained. Therefore, it is necessary to adjust the distance between the background and the object to be appropriate for the experiment, considering the relation between the defocus and the sensitivity. The purpose of this study is to experimentally clarify the effect of defocus on density field reconstruction. In this study, the visualization experiment of underexpanded jet using BOS measurement system with ronchi ruling as the background that we constructed, have been performed. The reservoir pressure of the jet and the distance between camera and axis of jet is fixed, and the distance between background and axis of jet has been changed as the parameter. The images have been later analyzed by using personal computer to quantitatively detect the amount of shift of the background image from the comparison between the background pattern and the captured image of underexpanded jet. The quantitatively measured amount of shift have been reconstructed into a density flow field using the Abel transformation and the Gradstone-Dale equation. From the experimental results, it is found that the reconstructed density image becomes blurring, and noise becomes decreasing with increasing the distance between background and axis of underexpanded jet. Consequently, it is cralified that the sensitivity constant should be greater than 20, and the circle of confusion diameter should be less than 2.7mm at least in this experimental setup.

Keywords: BOS method, underexpanded jet, abel transformation, density field visualization

Procedia PDF Downloads 74

Authors: Li Shihao, Dieter Trau

Abstract:

Bilirubin is a yellow substance that is made when the body breaks down old red blood cells. High levels of bilirubin can cause jaundice, a condition that makes the newborn's skin and the white part of the eyes look yellow. Jaundice is a serial-killer in developing countries in Southeast Asia such as Myanmar and most parts of Africa where jaundice screening is largely unavailable. Worldwide, 60% of newborns experience infant jaundice. One in ten will require therapy to prevent serious complications and lifelong neurologic sequelae. Limitations of current solutions: - Blood test: Blood tests are painful may largely unavailable in poor areas of developing countries, and also can be costly and unsafe due to the insufficient investment and lack of access to health care systems. - Transcutaneous jaundice-meter: 1) can only provide reliable results to caucasian newborns, due to skin pigmentations since current technologies measure bilirubin by the color of the skin. Basically, the darker the skin is, the harder to measure, 2) current jaundice meters are not affordable for most underdeveloped areas in Africa like Kenya and Togo, 3) fat tissue under the skin also influences the accuracy, which will give overestimated results, 4) current jaundice meters are not reliable after treatment (phototherapy) because bilirubin levels underneath the skin will be reduced first, while overall levels may be quite high. Thus, there is an urgent need for a low-cost non-invasive device, which can be effective not only for caucasian babies but also Asian and African newborns, to save lives at the most vulnerable time and prevent any complications like brain damage. Instead of measuring bilirubin on skin, we proposed a new method to do the measurement on the sclera, which can avoid the difference of skin pigmentations and ethnicities, due to the necessity for the sclera to be white regardless of racial background. This is a novel approach for measuring bilirubin by an optical method of light reflection off the white part of the eye. Moreover, the device is connected to a smart device, which can provide a user-friendly interface and the ability to record the clinical data continuously A disposable eye cap will be provided avoiding contamination and fixing the distance to the eye.

Keywords: Jaundice, bilirubin, non-invasive, sclera

Procedia PDF Downloads 234

Authors: M. Shemis, O. Maher, G. Casterou, F. Gauffre

Abstract:

Hepatitis C virus (HCV) is a major cause of chronic liver disease with a global 170 million chronic carriers at risk of developing liver cirrhosis and/or liver cancer. Egypt reports the highest prevalence of HCV worldwide. Currently, two classes of assays are used in the diagnosis and management of HCV infection. Despite the high sensitivity and specificity of the available diagnostic assays, they are time-consuming, labor-intensive, expensive, and require specialized equipment and highly qualified personal. It is therefore important for clinical and economic terms to develop a low-tech assay for the direct detection of HCV RNA with acceptable sensitivity and specificity, short turnaround time, and cost-effectiveness. Such an assay would be critical to control HCV in developing countries with limited resources and high infection rates, such as Egypt. The unique optical and physical properties of gold nanoparticles (AuNPs) have allowed the use of these nanoparticles in developing simple and rapid colorimetric assays for clinical diagnosis offering higher sensitivity and specificity than current detection techniques. The current research aims to develop a detection assay for HCV RNA using gold nanoparticles (AuNPs). Methods: 200 anti-HCV positive samples and 50 anti-HCV negative plasma samples were collected from Egyptian patients. HCV viral load was quantified using m2000rt (Abbott Molecular Inc., Des Plaines, IL). HCV genotypes were determined using multiplex nested RT- PCR. The assay is based on the aggregation of AuNPs in presence of the target RNA. Aggregation of AuNPs causes a color shift from red to blue. AuNPs were synthesized using citrate reduction method. Different sets of probes within the 5’ UTR conserved region of the HCV genome were designed, grafted on AuNPs and optimized for the efficient detection of HCV RNA. Results: The nano-gold assay could colorimetrically detect HCV RNA down to 125 IU/ml with sensitivity and specificity of 91.1% and 93.8% respectively. The turnaround time of the assay is < 30 min. Conclusions: The assay allows sensitive and rapid detection of HCV RNA and represents an inexpensive and simple point-of-care assay for resource-limited settings.

Keywords: HCV, gold nanoparticles, point of care, viral load

Procedia PDF Downloads 204

Authors: María Teresa Baquero, Ester Higueras

Abstract:

One of the challenges facing 21st century cities, is their adaptation to the phenomenon of an ageing population. International policies have been developed, such as the "Global Network for Age-friendly Cities and Communities". These cities must recognize the diversity of the elderly population, and facilitate an active, healthy, satisfied aging and promote inclusion. In order to promote active and healthy aging, older people should be encouraged to engage in physical activity, sunbathe, socialize and enjoy the public open spaces in the city. Some studies recognize thermal comfort as one of the factors that most influence the use of public open spaces. However, although some studies have shown vulnerability to thermal extremes and environmental conditions in older people, there is little research on thermal comfort for older adults, because it is usually analyzed based on the characteristics of the ¨average young person¨ without considering the physiological, physical and psychological differences that characterize the elderly. This study analyzes the relationship between the microclimate parameters as air temperature, relative humidity, wind speed and sky view factor (SVF) with the personal thermal perception of older adults in three public spaces in Madrid, through a mixed methodology that combines weather measurements with interviews, made during the year 2018. Statistical test like Chi-square, Spearman, and analysis of variance were used to analyze the relationship between preference votes and thermal sensation votes with environmental and personal parameters. The results show that there is a significant correlation between thermal sensation and thermal preference with the measured air temperature, age, level of clothing, the color of clothing, season, time of the day and kind of space while no influence of gender or other environmental variables was detected. These data would contribute to the design of comfortable public spaces that improve the welfare of the elderly contributing to "active and healthy aging" as one of the 21st century challenges cities face.

Keywords: healthy ageing, older adults, outdoor public space, thermal perception

Procedia PDF Downloads 131

Authors: Mahshid Arabi

Abstract:

In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

Procedia PDF Downloads 38

Authors: Abhay Asthana, Shally Toshkhani, Gyati Shilakari

Abstract:

The objective of the present research work is to develop a topical biodegradable dermal patch based formulation to aid accelerated wound healing. It is always better for patient compliance to be able to reduce the frequency of dressings with improved drug delivery and overall therapeutic efficacy. In present study optimized formulation using biodegradable components was obtained evaluating polymers and excipients (HPMC K4M, Ethylcellulose, Povidone, Polyethylene glycol and Gelatin) to impart significant folding endurance, elasticity, and strength. Molten gelatin was used to get a mixture using ethylene glycol. Chitosan dissolved in acidic medium was mixed with stirring to Gelatin mixture. With continued stirring to the mixture Curcumin was added with the aid of DCM and Methanol in an optimized ratio of 60:40 to get homogenous dispersion. Polymers were dispersed with stirring in the final formulation. The mixture was sonicated casted to get the film form. All steps were carried out under strict aseptic conditions. The final formulation was a thin uniformly smooth textured film with dark brown-yellow color. The film was found to have folding endurance was around 20 to 21 times without a crack in an optimized formulation at RT (23°C). The drug content was in range 96 to 102% and it passed the content uniform test. The final moisture content of the optimized formulation film was NMT 9.0%. The films passed stability study conducted at refrigerated conditions (4±0.2°C) and at room temperature (23 ± 2°C) for 30 days. Further, the drug content and texture remained undisturbed with stability study conducted at RT 23±2°C for 45 and 90 days. Percentage cumulative drug release was found to be 80% in 12h and matched the biodegradation rate as tested in vivo with correlation factor R2>0.9. In in vivo study administration of one dose in equivalent quantity per 2 days was applied topically. The data demonstrated a significant improvement with percentage wound contraction in contrast to control and plain drug respectively in given period. The film based formulation developed shows promising results in terms of stability and in vivo performance.

Keywords: wound healing, biodegradable, polymers, patch

Procedia PDF Downloads 474

Authors: Aiman Zehra, Sajad Mohd Wani

Abstract:

Packaging has a vital role as it contains and protects the food that moves from the supply chain to the consumer. Chitosan (CH) has been extensively used in food packaging applications among the plentiful natural macromolecules, including all the polysaccharide class, owing to its easy film-forming capacity, biodegradability, better oxygen and water vapour barrier ability and good mechanical strength. Compared to synthetic films, the films produced from chitosan present poor barrier and mechanical properties. To overcome its deficient qualities, a number of modification procedures are required to enhance the mechanical and physical properties. Various additives such as plasticizers (e.g., glycerol and sorbitol), crosslinkers (e.g.,CaCl₂, ZnO), fillers (nanoclay), and antimicrobial agents (e.g. thyme essential oil) have been used to improve the mechanical, thermal, morphological, antimicrobial properties and emulsifying agents for the stability and elasticity of chitosan-based biodegradable films. Different novel biocomposite films based on chitosan incorporated with thyme essential oil and different additives (ZnO, CaCl₂, NC, and PEG) were successfully prepared and used as packaging material for carrot candy. The chitosan film incorporated with crosslinkers was capable of forming a protective barrier on the surface of the candy to maintain moisture content, water activity, TSS, total sugars, and titratable acidity. ZnO +PEG +NC +CaCl₂ remarkably promotes a synergistic effect on the barrier properties of the film. The combined use of ZnO +PEG +NC +CaCl₂ in CH-TO films was more effective in preventing the moisture gain in candies. The lowest a𝓌 (0.624) was also observed for the candies stored in treatment. The color values L*, a*, b* of the candies were also retained in the film containing all the additives during the 6th month of storage. The value for L*, a*, and b* observed for T was 42.72, 9.89, and 10.84, respectively. The candies packaged in film retained TSS and acidity. The packaging film significantly p≤0.05 conserved sensory qualities and inhibited microbial activity during storage. Carrot candy was found microbiologically safe for human consumption even after six months of storage in all the packaging materials.

Keywords: chitosan, biodegradable films, antimicrobial activity, thyme essential oil, crosslinkers

Procedia PDF Downloads 91

Authors: Feng Yue, Fei Dai

Abstract:

With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture

Procedia PDF Downloads 159

Authors: Ali Bahkali, Rayan Yousef Booq, Mohammad Khiyami

Abstract:

Soil samples were collected from five different regions in the Kingdom of Saudi Arabia. Microbiological methods included dilution methods and pour plates to isolate and purify bacteria soil. The ability of isolates to develop biopolymer was investigated on petri dishes containing elements and substance concentrations stimulating developing biopolymer. Fluorescent stains, Nile red and Nile blue were used to stain the bacterial cells developing biopolymers. In addition, Sudan black was used to detect biopolymers in bacterial cells. The isolates which developed biopolymers were identified based on their gene sequence of 1 6sRNA and their ability to grow and synthesize PHAs on mineral medium supplemented with 1% dates molasses as the only carbon source under nitrogen limitation. During the study 293 bacterial isolates were isolated and detected. Through the initial survey on the petri dishes, 84 isolates showed the ability to develop biopolymers. These bacterial colonies developed a pink color due to accumulation of the biopolymers in the cells. Twenty-three isolates were able to grow on dates molasses, three strains of which showed the ability to accumulate biopolymers. These strains included Bacillus sp., Ralstonia sp. and Microbacterium sp. They were detected by Nile blue A stain with fluorescence microscopy (OLYMPUS IX 51). Among the isolated strains Ralstonia sp. was selected after its ability to grow on molasses dates in the presence of a limited nitrogen source was detected. The optimum conditions for formation of biopolymers by isolated strains were investigated. Conditions studied included, best incubation duration (2 days), temperature (30°C) and pH (7-8). The maximum PHB production was raised by 1% (v1v) when using concentrations of dates molasses 1, 2, 3, 4 and 5% in MSM. The best inoculated with 1% old inoculum (1= OD). The ideal extraction method of PHA and PHB proved to be 0.4% sodium hypochlorite solution, producing a quantity of polymer 98.79% of the cell's dry weight. The maximum PHB production was 1.79 g/L recorded by Ralstonia sp. after 48 h, while it was 1.40 g/L produced by R.eutropha ATCC 17697 after 48 h.

Keywords: bacteria forming polyhydroxyalkanoate, detection, molecular, Saudi Arabia

Procedia PDF Downloads 345

Authors: Yu-Ju Hsieh, Lin-Hung Lin, Wen-Hui Chang

Abstract:

This study was designed as an interventional research and intended to validate whether the introduction of drinking vinegar every day can reduce and even prevent urinary tract infection in Taiwan home stayed disabilities who using indwelling catheter. The data was collected from the subjects who have received home care case at northern Taiwan, according to the questionnaire and a medical records retroactive methodology, the subjects were informed and consent to drink 15ml of table vinegar in a daily diet, and through routine urine testing and culture study. Home care nurses would assist collecting urine at the point of before and after a meal from total 35 studied subjects per month, and total collected 4 times for testing. The results showed that when the average age of study subjects was 65.46 years and catheter indwelling time was 15 years, drinking table vinegar could inhibit the activity of E. coli O157: H7 and reduce its breeding. Before drinking table vinegar daily, the subjects’ urine pH value was 7.0-8.0, and the average was 7.5, and the urine PH value dropped to 6.5 after drinking table vinegar for a month. There were two purple urine cases whose urine were changed from purple to normal color after two weeks of drinking, and the protein and bacteria values of urine gradually improved. Urine smell unpleasant before attending to this study, and the symptom improved significantly only after 1 week, and the urine smell returned to normal ammonia and became clean after 1 month later. None of these subjects received treatment in a hospital due to urinary tract infection, and there were no signs of bleeding in all cases during this study. The subjects of this study are chronic patients with a long-term bedridden catheterization; drinking cranberry juice is an economic burden for them, and also highly prohibited for diabetes patients. By adapting to use cheaper table vinegar to acidified urine and improve its smell and ease Purple Urine Syndrome, to furthermore, proven urinary tract infection, it can also to reduce the financial burden on families, the cost of social resources and the rate of re-admission.

Keywords: table vinegar, urinary tract infection, disability patients, long-term indwelling catheter

Procedia PDF Downloads 256

Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

Abstract:

Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

Procedia PDF Downloads 180

Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

Abstract:

Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

Procedia PDF Downloads 157

Authors: Elyas Palantei, Dewiani, Farid Armin, Ardiansyah

Abstract:

High precision of printed microwave sensor utilized for sensing and monitoring the potential breast cancer existed in women breast tissue was optimally computed. The single element of UWB printed sensor that successfully modeled through several numerical optimizations was multiple fabricated and incorporated with woman bra to form the spherical sensors array. One sample of UWB microwave sensor obtained through the numerical computation and optimization was chosen to be fabricated. In overall, the spherical sensors array consists of twelve stair patch structures, and each element was individually measured to characterize its electrical properties, especially the return loss parameter. The comparison of S11 profiles of all UWB sensor elements is discussed. The constructed UWB sensor is well verified using HFSS programming, CST programming, and experimental measurement. Numerically, both HFSS and CST confirmed the potential operation bandwidth of UWB sensor is more or less 4.5 GHz. However, the measured bandwidth provided is about 1.2 GHz due to the technical difficulties existed during the manufacturing step. The configuration of UWB microwave sensing and monitoring system implemented consists of 12 element UWB printed sensors, vector network analyzer (VNA) to perform as the transceiver and signal processing part, the PC Desktop/Laptop acting as the image processing and displaying unit. In practice, all the reflected power collected from whole surface of artificial breast model are grouped into several numbers of pixel color classes positioned on the corresponding row and column (pixel number). The total number of power pixels applied in 2D-imaging process was specified to 100 pixels (or the power distribution pixels dimension 10x10). This was determined by considering the total area of breast phantom of average Asian women breast size and synchronizing with the single UWB sensor physical dimension. The interesting microwave imaging results were plotted and together with some technical problems arisen on developing the breast sensing and monitoring system are examined in the paper.

Keywords: UWB sensor, UWB microwave imaging, spherical array, breast cancer monitoring, 2D-medical imaging

Procedia PDF Downloads 189

Authors: Mohd Maniruzzaman, Md. Monjurul Alam, Md. Hafezur Rahaman, Anika Amir Mohona

Abstract:

The consumption of water by various industries is increasing day by day, and the wastewaters from them are increasing as well. These wastewaters consist of various kinds of color, dissolved solids, toxic heavy metals, residual chlorine, and other non-degradable organic materials. If these wastewaters are exposed directly to the environment, it will be hazardous for the environment and personal health. So, it is very necessary to treat these wastewaters before exposing into the environment. In this research, we have demonstrated the successful processing and utilization of fully bio-based cellulose micro crystal (CMC) composite for the removal of heavy metals, dyes, and salinity from industrial wastewaters. Banana rachis micro-cellulose were prepared by acid hydrolysis (H₂SO₄) of banana (Musa acuminata L.) rachis fiber, and Bijoypur raw clay were treated by organic solvent tri-ethyl amine. Composites were prepared with varying different composition of banana rachis nano-cellulose and modified Bijoypur (north-east part in Bangladesh) clay. After the successful characterization of cellulose micro crystal (CMC) and modified clay, our targeted filter was fabricated with different composition of cellulose micro crystal and clay in the locally fabricated packing column with 7.5 cm as thickness of composites fraction. Waste-water was collected from local small textile industries containing basic yellow 2 as dye, lead (II) nitrate [Pb(NO₃)₂] and chromium (III) nitrate [Cr(NO₃)₃] as heavy metals and saline water was collected from Khulna to test the efficiency of banana rachis cellulose micro crystal-clay composite for removing the above impurities. The filtering efficiency of wastewater purification was characterized by Fourier transforms infrared spectroscopy (FTIR), X-ray diffraction (X-RD), thermo gravimetric analysis (TGA), atomic absorption spectrometry (AAS), scanning electron microscopy (SEM) analyses. Finally, our all characterizations data are shown with very high expected results for in industrial application of our fabricated filter.

Keywords: banana rachis, bio-based filter, cellulose micro crystal-clay composite, wastewaters, synthetic dyes, heavy metal, water salinity

Procedia PDF Downloads 123

Authors: Aneal Khan, Elleine Allapitan, Desmond Koo, Katherine-Ann Piedalue, Shaneel Pathak, Utkarsh Subnis

Abstract:

Background: Disease management of metabolic, genetic disorders is long-term and can be cumbersome to patients and caregivers. Patient-Reported Outcome Measures (PROMs) have been a useful tool in capturing patient perspectives to help enhance treatment compliance and engagement with health care providers, reduce utilization of emergency services, and increase satisfaction with their treatment choices. Currently, however, PROMs are collected during infrequent and decontextualized clinic visits, which makes translation of patient experiences challenging over time. The GRIT study aims to evaluate a digital health journal application called Zamplo that provides a personalized health diary to record self-reported health outcomes accurately and efficiently in patients with metabolic, genetic disorders. Methods: This is a randomized controlled trial (RCT) (1:1) that assesses the efficacy of Zamplo to increase patient activation (primary outcome), improve healthcare satisfaction and confidence to manage medications (secondary outcomes), and reduce costs to the healthcare system (exploratory). Using standardized online surveys, assessments will be collected at baseline, 1 month, 3 months, 6 months, and 12 months. Outcomes will be compared between patients who were given access to the application versus those with no access. Results: Seventy-seven patients were recruited as of November 30, 2021. Recruitment for the study commenced in November 2020 with a target of n=150 patients. The accrual rate was 50% from those eligible and invited for the study, with the majority of patients having Fabry disease (n=48) and the remaining having Pompe disease and mitochondrial disease. Real-time clinical responses, such as pain, are being measured and correlated to disease-modifying therapies, supportive treatments like pain medications, and lifestyle interventions. Engagement with the application, along with compliance metrics of surveys and journal entries, are being analyzed. An interim analysis of the engagement data along with preliminary findings from this pilot RCT, and qualitative patient feedback will be presented. Conclusions: The digital self-care journal provides a unique approach to disease management, allowing patients direct access to their progress and actively participating in their care. Findings from the study can help serve the virtual care needs of patients with metabolic, genetic disorders in North America and the world over.

Keywords: eHealth, mobile health, rare disease, patient outcomes, quality of life (QoL), pain, Fabry disease, Pompe disease

Procedia PDF Downloads 149

Authors: Abdelrahman Mohamed

Abstract:

Copyright law is a branch of the Intellectual Property Law that gives authors exclusive rights to copy, display, perform, and distribute copyrightable works. In theory, copyright law aims to promote the welfare of society by granting exclusive rights to the creators in exchange for the works that these creators produce for society. Thus, there are two different types of rights that a just regime should balance between them which are owners' rights and users' rights. The paper argues that there is a conflict between the current international copyright regime and the Islamic Social Justice Theory. This regime is unjust from the Islamic Social Justice Theory's perspective regarding access to educational materials because this regime was unjustly established by the colonizers to protect their interests, starting from the Berne Convention for the Protection of Literary and Artistic Works 1886 and reaching to the Trade-Related Aspects of Intellectual Property Rights 1994. Consequently, the injustice of this regime was reflected in the regulations of these agreements and led to an imbalance between the owners' rights and the users' rights in favor of the former at the expense of the latter. As a result, copyright has become a barrier to access to knowledge and educational materials. The paper starts by illustrating the concept of justice in Islamic sources such as the Quran, Sunnah, and El-Maslha-Elmorsalah. Then, social justice is discussed by focusing on the importance of access to knowledge and the right to education. The theory assumes that the right to education and access to educational materials are necessities; thus, to achieve justice in this regime, the users' rights should be granted regardless of their region, color, and financial situation. Then, the paper discusses the history of authorship protection under the Islamic Sharia and to what extent this right was recognized even before the existence of copyright law. According to this theory, the authors' rights should be protected, however, this protection should not be at the expense of the human's rights to education and the right to access to educational materials. Moreover, the Islamic Social Justice Theory prohibits the concentration of wealth among a few numbers of people, 'the minority'. Thus, if knowledge is considered an asset or a good, the concentration of knowledge is prohibited from the Islamic perspective, which is the current situation of the copyright regime where a few countries control knowledge production and distribution. Finally, recommendations will be discussed to mitigate the injustice of the current international copyright regime and to fill the gap between the current international copyright regime and the Islamic Social Justice Theory.

Keywords: colonization, copyright, intellectual property, Islamic sharia, social justice

Procedia PDF Downloads 14

Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

Procedia PDF Downloads 118

Authors: Beyza Sukran Isik, Gokce Altin, Ipek Yalcinkaya, Evren Demircan, Asli Can Karaca, Beraat Ozcelik

Abstract:

Turmeric (Curcuma longa L.), is used as a food additive (spice), preservative and coloring agent in Asian countries, including China and South East Asia. It is also considered as a medicinal plant. Traditional Indian medicine evaluates turmeric powder for the treatment of biliary disorders, rheumatism, and sinusitis. It has rich polyphenol content. Turmeric has yellow color mainly because of the presence of three major pigments; curcumin 1,7-bis(4-hydroxy-3-methoxyphenyl)-1, 6-heptadiene-3,5-dione), demethoxy-curcumin and bis demothoxy-curcumin. These curcuminoids are recognized to have high antioxidant activities. Curcumin is the major constituent of Curcuma species. Method: To prepare turmeric tea, 0.5 gram of turmeric powder was brewed with 250 ml of water at 90°C, 10 minutes. 500 grams of fresh turmeric washed and shelled prior to squeezing. Both turmeric tea and turmeric juice pass through 45 lm filters and stored at -20°C in the dark for further analyses. Curcumin was extracted from 20 grams of turmeric powder by 70 ml ethanol solution (95:5 ethanol/water v/v) in a water bath at 80°C, 6 hours. Extraction was contributed for 2 hours at the end of 6 hours by addition of 30 ml ethanol. Ethanol was removed by rotary evaporator. Remained extract stored at -20°C in the dark. Total phenolic content and phenolic profile were determined by spectrophotometric analysis and ultra-fast liquid chromatography (UFLC), respectively. Results: The total phenolic content of ethanolic extract of turmeric, turmeric juice, and turmeric tea were determined 50.72, 31.76 and 29.68 ppt, respectively. The ethanolic extract of turmeric, turmeric juice, and turmeric tea have been injected into UFLC and analyzed for curcumin contents. The curcumin content in ethanolic extract of turmeric, turmeric juice, and turmeric tea were 4067.4, 156.7 ppm and 1.1 ppm, respectively. Significance: Turmeric is known as a good source of curcumin. According to the results, it can be stated that its tea is not sufficient way for curcumin consumption. Turmeric juice can be preferred to turmeric tea for higher curcumin content. Ethanolic extract of turmeric showed the highest content of turmeric in both spectrophotometric and chromatographic analyses. Nonpolar solvents and carriers which have polar binding sites have to be considered for curcumin consumption due to its nonpolar nature.

Keywords: phenolic compounds, spectrophotometry, turmeric, UFLC

Procedia PDF Downloads 196

Authors: Tracey Jean Boisseau

Abstract:

Recently, the rise of concerted right-wing and authoritarian movements has put feminists as well as women, queer, trans, and non-binary folk, immigrants, refugees, the global poor, and people of color in their crosshairs. The U.S. is seeing unprecedented attacks on liberal democratic institutions, escalating “culture wars,” and increased anti-intellectual vitriol specifically targeting feminist and anti-racist educators and scholars. Such vitriol has fueled new legislation curtailing or outright banning of “gender studies” for its ideological commitment to theorizing gender identity as a cultural construct and an inherently political project rather than a “natural” binary that can not be contested or interrogated. At the same time, across the globe—in Afghanistan, Argentina, Brazil, France, Haiti, Hungary, Kenya, Nicaragua, Nigeria, Pakistan, the Philippines, Poland, Russia, South Korea, Sweden, Turkey, Uganda, the United Kingdom, and elsewhere—emergent anti-feminist, nativist, and white-supremacist political parties, as well as established autocratic and authoritarian regimes, have instituted blatantly misogynistic, anti-queer, and anti-trans legislation, often accompanied by governmental and extra-governmental policies explicitly intended to marginalize, erase, suppress, or extinguish gender studies as a legitimate academic discipline, topic of research, and teaching field. This paper considers the origins and effects of such legislation -as well as the strategies exhibited by practitioners of gender studies to counter these effects and resist erasure- from a cross-cultural perspective. The research underpinning this paper’s conclusions includes a survey of nearly 2000 gender studies programs in the U.S. and interviews with dozens of gender studies scholars and administrative leaders of gender-studies programs located worldwide. The goal of this paper is to illuminate distinctions, continuities, and global connections between anti-gender studies legislation that emanates from within national borders but arises from rightwing movements that supercede those borders, and that, ultimately, require globalist responses.

Keywords: anti-feminist, anti-LGBTQ, legislation, criminalization, authoritarianism, globalization

Procedia PDF Downloads 74

Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

Abstract:

Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency

Procedia PDF Downloads 26

Authors: Mladen Milicevic

Abstract:

This presentation will address how the statistical analysis of digitized popular music influences the music creation and emotionally manipulates consumers.Furthermore, it will deal with semiological aspect of uniformization of musical taste in order to predict the potential revenues generated by popular music sales. In the USA, we live in an age where most of the popular music (i.e. music that generates substantial revenue) has been digitized. It is safe to say that almost everything that was produced in last 10 years is already digitized (either available on iTunes, Spotify, YouTube, or some other platform). Depending on marketing viability and its potential to generate additional revenue most of the “older” music is still being digitized. Once the music gets turned into a digital audio file,it can be computer-analyzed in all kinds of respects, and the similar goes for the lyrics because they also exist as a digital text file, to which any kin of N Capture-kind of analysis may be applied. So, by employing statistical examination of different popular music metrics such as tempo, form, pronouns, introduction length, song length, archetypes, subject matter,and repetition of title, the commercial result may be predicted. Polyphonic HMI (Human Media Interface) introduced the concept of the hit song science computer program in 2003.The company asserted that machine learning could create a music profile to predict hit songs from its audio features Thus,it has been established that a successful pop song must include: 100 bpm or more;an 8 second intro;use the pronoun 'you' within 20 seconds of the start of the song; hit the bridge middle 8 between 2 minutes and 2 minutes 30 seconds; average 7 repetitions of the title; create some expectations and fill that expectation in the title. For the country song: 100 bpm or less for a male artist; 14-second intro; uses the pronoun 'you' within the first 20 seconds of the intro; has a bridge middle 8 between 2 minutes and 2 minutes 30 seconds; has 7 repetitions of title; creates an expectation,fulfills it in 60 seconds.This approach to commercial popular music minimizes the human influence when it comes to which “artist” a record label is going to sign and market. Twenty years ago,music experts in the A&R (Artists and Repertoire) departments of the record labels were making personal aesthetic judgments based on their extensive experience in the music industry. Now, the computer music analyzing programs, are replacing them in an attempt to minimize investment risk of the panicking record labels, in an environment where nobody can predict the future of the recording industry.The impact on the consumers taste through the narrow bottleneck of the above mentioned music selection by the record labels,created some very peculiar effects not only on the taste of popular music consumers, but also the creative chops of the music artists as well. What is the meaning of this semiological shift is the main focus of this research and paper presentation.

Keywords: music, semiology, commercial, taste

Procedia PDF Downloads 390

Authors: A. Atli, K. Candelier, J. Alteyrac

Abstract:

Environmental and sustainability concerns push the industries to manufacture alternative materials having less environmental impact. The Wood Plastic Composites (WPCs) produced by blending the biopolymers and natural fillers permit not only to tailor the desired properties of materials but also are the solution to meet the environmental and sustainability requirements. This work presents the elaboration and characterization of the fully green WPCs prepared by blending a biopolymer, BIOPLAST® GS 2189 and spruce sawdust used as filler with different amounts. Since both components are bio-based, the resulting material is entirely environmentally friendly. The mechanical, thermal, structural properties of these WPCs were characterized by different analytical methods like tensile, flexural and impact tests, Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). Their water absorption properties and resistance to the termite and fungal attacks were determined in relation with different wood filler content. The tensile and flexural moduli of WPCs increased with increasing amount of wood fillers into the biopolymer, but WPCs became more brittle compared to the neat polymer. Incorporation of spruce sawdust modified the thermal properties of polymer: The degradation, cold crystallization, and melting temperatures shifted to higher temperatures when spruce sawdust was added into polymer. The termite, fungal and water absorption resistance of WPCs decreased with increasing wood amount in WPCs, but remained in durability class 1 (durable) concerning fungal resistance and quoted 1 (attempted attack) in visual rating regarding to the termites resistance except that the WPC with the highest wood content (30 wt%) rated 2 (slight attack) indicating a long term durability. All the results showed the possibility to elaborate the easy injectable composite materials with adjustable properties by incorporation of BIOPLAST® GS 2189 and spruce sawdust. Therefore, lightweight WPCs allow both to recycle wood industry byproducts and to produce a full ecologic material.

Keywords: biodegradability, color measurements, durability, mechanical properties, melt flow index, MFI, structural properties, thermal properties, wood-plastic composites, WPCs

Procedia PDF Downloads 134

Authors: Sireetorn Kuharat, Anwar Beg

Abstract:

In this study, multi-mode heat transfer characteristics of spacecraft solar collectors are investigated computationally. Two-dimensional steady-state incompressible laminar Newtonian viscous convection-radiative heat transfer in a rectangular solar collector geometry. The ANSYS FLUENT finite volume code (version 17.2) is employed to simulate the thermo-fluid characteristics. Several radiative transfer models are employed which are available in the ANSYS workbench, including the classical Rosseland flux model and the more elegant P1 flux model. Mesh-independence tests are conducted. Validation of the simulations is conducted with a computational Harlow-Welch MAC (Marker and Cell) finite difference method and excellent correlation. The influence of aspect ratio, Prandtl number (Pr), Rayleigh number (Ra) and radiative flux model on temperature, isotherms, velocity, the pressure is evaluated and visualized in color plots. Additionally, the local convective heat flux is computed and solutions are compared with the MAC solver for various buoyancy effects (e.g. Ra = 10,000,000) achieving excellent agreement. The P1 model is shown to better predict the actual influence of solar radiative flux on thermal fluid behavior compared with the limited Rosseland model. With increasing Rayleigh numbers the hot zone emanating from the base of the collector is found to penetrate deeper into the collector and rises symmetrically dividing into two vortex regions with very high buoyancy effect (Ra >100,000). With increasing Prandtl number (three gas cases are examined respectively hydrogen gas mixture, air and ammonia gas) there is also a progressive incursion of the hot zone at the solar collector base higher into the solar collector space and simultaneously a greater asymmetric behavior of the dual isothermal zones. With increasing aspect ratio (wider base relative to the height of the solar collector geometry) there is a greater thermal convection pattern around the whole geometry, higher temperatures and the elimination of the cold upper zone associated with lower aspect ratio.

Keywords: thermal convection, radiative heat transfer, solar collector, Rayleigh number

Procedia PDF Downloads 114

Authors: Ana Beltran Sanahuja, A. Valdés García, Saray Lopez De Pablo Gallego, Maria Soledad Prats Moya

Abstract:

Tomato consumption has greatly increased worldwide in the last few years, mostly due to a growing demand for products like sofrito. In this sense, regular consumption of tomato-based products has been consistently associated with a reduction in the incidence of chronic degenerative diseases. The sofrito is a homemade tomato sauce typical of the Mediterranean area, which contains as main ingredients: tomato, onion, garlic and olive oil. There are also sofrito’s variations by adding other spices which bring at the same time not only color, flavor, smell and or aroma; they also provide medicinal properties, due to their antioxidant power. This protective effect has mainly been attributed to the predominant bioactive compounds present in sofrito, such as lycopene and other carotenoids as well as more than 40 different polyphenols. Regarding the cooking process, it is known that it can modify the properties and the availability of nutrients in sofrito; however, there is not enough information regarding this issue. For this reason, the aim of the present work is to evaluate the cooking effect on the antioxidant capacity of different variants of tomato-based sofrito combined with other spices, through the analysis of total phenols content (TPC) and to evaluate the antioxidant capacity by using the method of free radical 2,2-diphenyl-1-picrylhydrazyl (DPPH). Based on the results obtained, it can be confirmed that the basic sofrito composed of tomato, onion, garlic and olive oil and the sofrito with 1 g of rosemary added, are the ones with the highest content of phenols presenting greater antioxidant power than other industrial sofrito, and that of other variables of sofrito with added thyme or higher amounts of garlic. Moreover, it has been observed that in the elaboration of the tomato-based sofrito, it is possible to cook until 60 minutes, since the cooking process increases the bioavailability of the carotenoids when breaking the cell walls, which weakens the binding forces between the carotenoids and increases the levels of antioxidants present, confirmed both with the TPC and DPPH methods. It can be concluded that the cooking process of different variants of tomato-based sofrito, including spices, can improve the antioxidant capacity. The synergistic effects of different antioxidants may have a greater protective effect; increasing, also, the digestibility of proteins. In addition, the antioxidants help to deactivate the free radicals of diseases such as atherosclerosis, aging, immune suppression, cancer, and diabetes.

Keywords: antioxidants, cooking process, phenols sofrito

Procedia PDF Downloads 136

Authors: Abdul Ghaffar Memon, Xiao Hong Zhou, Yunpeng Xing, Ruoyu Wang, Miao He

Abstract:

Due to deleterious environmental and health effects of the Hg²⁺ ions, various online, detection methods apart from the traditional analytical tools have been developed by researchers. Biosensors especially, label, label-free, colorimetric and optical sensors have advanced with sensitive detection. However, there remains a gap of ultrasensitive quantification as noise interact significantly especially in the AuNP based label-free colorimetry. This study reported an amplification strategy using Exo-III enzyme for target recycling of Hg²⁺ ions in a T-rich hairpin loop metallobase label-free colorimetric nanosensor with an improved sensitivity using unmodified gold nanoparticles (uGNPs) as an indicator. The two T-rich metallobase hairpin loop structures as 5’- CTT TCA TAC ATA GAA AAT GTA TGT TTG -3 (HgS1), and 5’- GGC TTT GAG CGC TAA GAA A TA GCG CTC TTT G -3’ (HgS2) were tested in the study. The thermodynamic properties of HgS1 and HgS2 were calculated using online tools (http://biophysics.idtdna.com/cgi-bin/meltCalculator.cgi). The lab scale synthesized uGNPs were utilized in the analysis. The DNA sequence had T-rich bases on both tails end, which in the presence of Hg²⁺ forms a T-Hg²⁺-T mismatch, promoting the formation of dsDNA. Later, the Exo-III incubation enable the enzyme to cleave stepwise mononucleotides from the 3’ end until the structure become single-stranded. These ssDNA fragments then adsorb on the surface of AuNPs in their presence and protect AuNPs from the induced salt aggregation. The visible change in color from blue (aggregation stage in the absence of Hg²⁺) and pink (dispersion state in the presence of Hg²⁺ and adsorption of ssDNA fragments) can be observed and analyzed through UV spectrometry. An ultrasensitive quantitative nanosensor employing Exo-III assisted target recycling of mercury ions through label-free colorimetry with nanomolar detection using uGNPs have been achieved and is further under the optimization to achieve picomolar range by avoiding the influence of the environmental matrix. The proposed strategy will supplement in the direction of uGNP based ultrasensitive, rapid, onsite, label-free colorimetric detection.

Keywords: colorimetric, Exo-III, gold nanoparticles, Hg²⁺ detection, label-free, signal amplification

Procedia PDF Downloads 307

Authors: Hamitri-Guerfi Fatiha, Madani Khodir, Hadjal Samir, Kati Djamel, Youyou Ahcene

Abstract:

Date palm (Phoenix dactylifera) is a principal fruit that is grown in many regions of the world, resulting in a surplus production of dates. Algeria is considered to be one of the date producing countries. Date seeds (pits) have been a problem to the date industry as a waste stream. However, finding a way to make a profit on the pits would benefit date farmers substantially. This work concentrated on the valorization of date seed oils. A preliminary study was carried out on three varieties (soft, half soft, and dry) and we selected the dry variety. This work concerns the valorization of the date seed oil of the dry variety: ‘Mech Degla’ by its incorporation in a food formulation: margarine of table. Lipid extraction was carried out by hot extraction with the soxhlet; the extracts obtained are rich in fat contents, the results gave outputs of 13.21±0.21 %. The antioxidant activity of extracted oils was studied by the test of DPPH, the content polyphenols as well as the anti-radicalaire activity. The analysis of fatty acids was made by CPG. Thus, it comes out from our results that the recovered fat contents are interesting and considerable. A formulation of the margarine ‘BIO’ was elaborated on the scale industrialist by the addition of the extracts of date seeds ‘Mech-Degla’ oil in order to substitute a synthetic additive. The physicochemical characteristics of the elaborate margarines prove to be in conformity with the standards set by the Algerian companies. The texture of the elaborate margarine has an acceptable color, an aspect brilliant and homogeneous, it is plastic and easy to paste having an index of required SFC and the margarine melts easily in the mouth. Moreover, the evaluation of oxidative stability is carried out by the test of Rancimat. The result obtained reported that the margarine enriched with date seed oil, proved more resistant to oxidation, than the margarine without extract, which is improved much during incorporation of the extracts simultaneously. By conclusion, considering the content of polyphénols noted in the two extracts (aqueous and oily), we can exhort the scientific community to become aware of the treasures of our country especially the wonders of the south which are the dates and theirs under products (pits).

Keywords: antioxydant activity, date seed oil, quality characteristics, margarine

Procedia PDF Downloads 412

Authors: Dor Oppenheim, Yael Edan, Guy Shani

Abstract:

This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

Procedia PDF Downloads 322