Search results for: orange python

Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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pscmsForecasting is an open-source web service that implements a variety of time series forecasting algorithms and exposes them to the user via the ubiquitous HTTP protocol. It allows developers to enhance their applications by adding time series forecasting functionalities through an intuitive and easy-to-use interface. This paper provides some background on time series forecasting and gives details about the implemented algorithms, aiming to enhance the end user’s understanding of the underlying methods before incorporating them into their applications. A detailed description of the web service’s interface and its various parameterizations is also provided. Being an open-source project, pcsmsForecasting can also be easily modified and tailored to the specific needs of each application.

Keywords: time series, forecasting, web service, open source

Procedia PDF Downloads 46

Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

Procedia PDF Downloads 96

Authors: N. C. Okoronkwo, I. E. Mbaeyi-Nwaoha, C. P. Agbata

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Childhood malnutrition is one of the most persistent public health problems throughout developing countries, including Nigeria. Demographic and Health survey data from twenty-one developing countries indicated that poor complementary feeding of children aged 6- 23 months contributes to negative growth trends. To reduce malnutrition among children in the society, formulation of complimentary food rich in essential nutrient for optimum growth and development of infants is essential. This study focused on the evaluation of complementary food produced by solid-state fermentation of Acha and Soybean using Rhizopus oligosporus (2710) and Orange-fleshed sweet potatoes (OFSP) using Lactobacillus planterum (B-41621). The raw materials were soaked separately, each in four volumes of 0.9M acetic acid for 16 hours, rinsed with clean water, steam cooked and cooled. Solid-state fermentation (SSF) was carried out by inoculating Acha and Soybean with spore suspension (1x 10⁶spores/ml) of Rhizopus oligosporus (2710) and OFSP with spore suspension (1x 106spores/ml) of Lactobacillus planterum (B-41621). Fermentation which lasted for 72hours was carried out with 24hours sampling. The samples were blended in the following ratios: Acha and soybean 100: 100 (AS), Acha/soybean and OFSP 50: 50(ASO), made into gruel and compared with a commercial infant formula (Cerelac) which served as the control (CTRL). The samples were analyzed for proximate composition using AOAC methods and sensory attributes using a hedonic scale. Results showed that moisture, crude protein, fibre and ash content increased significantly (p<0.05) as fermentation progressed, while carbohydrate and fat content decreased. The protein, moisture, fibre and ash content ranged from 17.10-19.02%, 54.97-56.27%, 7.08-7.60% and2.09-2.38%, respectively, while carbohydrate and fat content ranged from 12.95-10.21% and 5.81-4.52%, respectively. In sensory scores, there were no significant (p>0.05) difference between the average mean scores of colours, texture and consistency of the samples. The sensory score for the overall acceptability ranged from 6.20-7.80. Sample CTRL had the highest score, while sample ASO had the least score. There was no significant (p>0.05) difference between samples CTRL and AS. Solid-state fermentation improved the nutritional content and flavour of the developed complementary food, which is needed for infant growth and development.

Keywords: Complementary food, malnutrition, proximate composition, solid-state fermentation

Procedia PDF Downloads 129

Authors: Ahmed Emad, Ahmed Salah, Abdelrahman Magdy, Omar Rashid, Mohammed Adel

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This research paper discusses vehicle-to-vehicle technology as an important application of linear algebra. This communication technology represents an efficient and promising application to help to ensure the safety of the drivers by warning them when a crash possibility is close. The major link that combines our topic with linear algebra is the Laplacian matrix. Some main definitions used in the V2V were illustrated, such as VANET and its characteristics. The V2V technology could be applied in different applications with different traffic scenarios and various ways to warn car drivers. These scenarios were simulated programs such as MATLAB and Python to test how the V2V system would respond to the different scenarios and warn the car drivers exposed to the threat of collisions.

Keywords: V2V communication, vehicle to vehicle scenarios, VANET, FCW, EEBL, IMA, Laplacian matrix

Procedia PDF Downloads 119

Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

Procedia PDF Downloads 91

Authors: M. R. S. Nasuha, K. Azman, H. Azhan, S. A. Senawi, A . Mardhiah

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Sm3+ doped borotellurite glasses of the system (70-x) TeO2-20B2O3-10ZnO-xSm2O3 (where x = 0.0, 0.5, 1.0, 1.5, 2.0, and 2.5 mol%) have been prepared using melt-quenching method. Their physical properties such as density, molar volume and oxygen packing density as well as the optical measurements by mean of their absorption and emission characteristic have been carried out at room temperature using UV/VIS and photoluminescence spectrophotometer. The result of physical properties is found to vary with respect to Sm3+ ions content. Meanwhile, three strong absorption peaks are observed and are well resolved in the ultraviolet and visible regions due to transitions between the ground state and various excited state of Sm3+ ions. Thus, the photoluminescence spectra exhibit four emission bands from the initial state, which correspond to the 4G5/2 → 6H5/2, 4G5/2 → 6H7/2, 4G5/2 → 6H9/2 and 4G5/2 → 6H11/2 fluorescence transitions at 562 nm, 599 nm, 645 nm, and 706 nm, respectively.

Keywords: absorption, borotellurite, emission, optical, physical

Procedia PDF Downloads 668

Authors: K. Prabhu, K. Dinesh, M. Ranjani, M. Suhitha

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During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the five gestures will be detected when shown with their hands via the webcam, which is placed for gesture detection. The personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: nodeMCU, AI technology, gesture, patient

Procedia PDF Downloads 133

Authors: Hamsini Pulugurtha, P. V. S. L. Jagadamba

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Programmed Speech to Text and Text Summarization Using Graph-based Algorithms can be utilized in gatherings to get the short depiction of the gathering for future reference. This gives signature check utilizing Siamese neural organization to confirm the personality of the client and convert the client gave sound record which is in English into English text utilizing the discourse acknowledgment bundle given in python. At times just the outline of the gathering is required, the answer for this text rundown. Thus, the record is then summed up utilizing the regular language preparing approaches, for example, solo extractive text outline calculations

Keywords: Siamese neural network, English speech, English text, natural language processing, unsupervised extractive text summarization

Procedia PDF Downloads 183

Authors: Nisha Dhariwal, Anupama Sharma

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The synthesis of cellulose nanofibrils quaternized with 3‐chloro‐2‐hydroxypropyltrimethylammonium chloride (CHPTAC) in NaOH/urea aqueous solution has been reported. Xylenol Orange (XO) has been used as an indicator for selective detection of Sn (II) ions, by its immobilization on quaternized cellulose membrane. The effects of pH, reagent concentration and reaction time on the immobilization of XO have also been studied. The linear response, limit of detection, and interference of other metal ions have also been studied and no significant interference has been observed. The optical chemical sensor displayed good durability and short response time with negligible leaching of the reagent.

Keywords: cellulose, chemical sensor, heavy metal ions, indicator immobilization

Procedia PDF Downloads 271

Authors: Jiangbo Li, Wenqian Huang

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Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest commercialization process. The automatic and nondestructive detection of infected fruits is still a challenge for the citrus industry. At present, the visual inspection of rotten citrus fruits is commonly performed by workers through the ultraviolet induction fluorescence technology or manual sorting in citrus packinghouses to remove fruit subject with fungal infection. However, the former entails a number of problems because exposing people to this kind of lighting is potentially hazardous to human health, and the latter is very inefficient. Orange is used as a research object. This study would focus on this problem and proposed an effective method based on Vis-NIR hyperspectral imaging in the wavelength range of 400-1000 nm with a spectroscopic resolution of 2.8 nm. In this work, three normalization approaches are applied prior to analysis to reduce the effect of sample curvature on spectral profiles, and it is found that mean normalization was the most effective pretreatment for decreasing spectral variability due to curvature. Then, principal component analysis (PCA) was applied to a dataset composing of average spectra from decayed and normal tissue to reduce the dimensionality of data and observe the ability of Vis-NIR hyper-spectra to discriminate data from two classes. In this case, it was observed that normal and decayed spectra were separable along the resultant first principal component (PC1) axis. Subsequently, five wavelengths (band) centered at 577, 702, 751, 808, and 923 nm were selected as the characteristic wavelengths by analyzing the loadings of PC1. A multispectral combination image was generated based on five selected characteristic wavelength images. Based on the obtained multispectral combination image, the intensity slicing pseudocolor image processing method is used to generate a 2-D visual classification image that would enhance the contrast between normal and decayed tissue. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudocolor image coupled with a simple thresholding method. For the investigated 238 independent set samples including infected fruits infected by Penicillium digitatum and normal fruits, the total success rate is 100% and 97.5%, respectively, and, the proposed algorithm also used to identify the orange infected by penicillium italicum with a 100% identification accuracy, indicating that the proposed multispectral algorithm here is an effective method and it is potential to be applied in citrus industry.

Keywords: citrus fruit, early rotten, fungal infection, hyperspectral imaging

Procedia PDF Downloads 270

Authors: M. A. Ferhat, M. N. Boukhatem, F. Chemat

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Lycopene extraction with petroleum derivatives as solvents has caused safety, health, and environmental concerns everywhere. Thus, finding a safe alternative solvent will have a strong and positive impact on environments and general health of the world population. d-limonene from the orange peel was extracted through a steam distillation procedure followed by a deterpenation process and combining this achievement by using it as a solvent for extracting lycopene from tomato fruit as a substitute of dichloromethane. Lycopene content of fresh tomatoes was determined by high-performance liquid chromatography after extraction. Yields obtained for both extractions showed that yields of d-limonene’s extracts were almost equivalent to those obtained using dichloromethane. The proposed approach using a green solvent to perform extraction is useful and can be considered as a nice alternative to conventional petroleum solvent where toxicity for both operator and environment is reduced.

Keywords: alternative solvent, d-limonene, extraction, lycopene

Procedia PDF Downloads 383

Authors: P. Revathi, T. Mrunalini, K. Padma Priya, P. Ramya, R. Saranya

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During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the 5 gestures will be detected when shown with their hands via a webcam which is placed for gesture detection. A personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: onion harvesting, automatic pluging, camera, raspberry pi

Procedia PDF Downloads 168

Authors: Tanmaya Pradhan, K. Midhun, M. Joy Thomas

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Increasing the shelf life and improving the quality are important objectives for the success of packaged liquid food industry. One of the methods by which this can be achieved is by deactivating the micro-organisms present in the liquid food through pasteurization. Pasteurization is done by heating, but some serious disadvantages such as the reduction in food quality, flavour, taste, colour, etc. were observed because of heat treatment, which leads to the development of newer methods instead of pasteurization such as treatment using UV radiation, high pressure, nuclear irradiation, pulsed electric field, etc. In recent years the use of the pulsed electric field (PEF) for inactivation of the microbial content in the food is gaining popularity. PEF uses a very high electric field for a short time for the inactivation of microorganisms, for which we require a high voltage pulsed power source. Pulsed power sources used for PEF treatments are usually in the range of 5kV to 50kV. Different pulse shapes are used, such as exponentially decaying and square wave pulses. Exponentially decaying pulses are generated by high power switches with only turn-on capacity and, therefore, discharge the total energy stored in the capacitor bank. These pulses have a sudden onset and, therefore, a high rate of rising but have a very slow decay, which yields extra heat, which is ineffective in microbial inactivation. Square pulses can be produced by an incomplete discharge of a capacitor with the help of a switch having both on/off control or by using a pulse forming network. In this work, a pulsed power-based system is designed with the help of high voltage capacitors and solid-state switches (IGBT) for the inactivation of pathogenic micro-organism in liquid food such as fruit juices. The high voltage generator is based on the Marx generator topology, which can produce variable amplitude, frequency, and pulse width according to the requirements. Liquid food is treated in a chamber where pulsed electric field is produced between stainless steel electrodes using the pulsed output voltage of the supply. Preliminary bacterial inactivation tests were performed by subjecting orange juice inoculated with Escherichia Coli bacteria. With the help of the developed pulsed power source and the chamber, the inoculated orange has been PEF treated. The voltage was varied to get a peak electric field up to 15kV/cm. For a total treatment time of 200µs, a 30% reduction in the bacterial count has been observed. The detailed results and analysis will be presented in the final paper.

Keywords: Escherichia coli bacteria, high voltage generator, microbial inactivation, pulsed electric field, pulsed forming line, solid-state switch

Procedia PDF Downloads 151

Authors: María Rojo Granados

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This work presents an empirical investigation of the performance of pink and purple petunia petals and orange and red geranium petals on a linen fabric using the Eco Print technique. This theoretical and practical approach represents an advance in the textile world towards sustainable dyeing and printing methods. It is understood that the possibility of mass printing or dyeing through these methods in fashion is complex, but it can be an approach toward a more sustainable industry. The research consists of twenty-two empirical tests where different processes and methods are applied and explained at different temperatures and using different mordants. The test results allow the selection of which printing and dyeing methods can be applied to the fashion industry in an environmentally consistent way.

Keywords: dyeing, empirical tests, petals, performance, printing, sustainably

Procedia PDF Downloads 69

Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

Procedia PDF Downloads 53

Authors: Yasmin Tantawi, Mary Beth Rosson

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In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: computer-mediated communication, content analysis, paralinguistics, sociology

Procedia PDF Downloads 142

Authors: Hategekimana Jean Paul, Irakoze Josiane, Ishimweyizerwe Valentin, Iradukunda Dieudonne, Uwanyirigira Jeannette

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Orange fleshed sweet potatoes (OFSP) are highly grown and are available plenty in rural and urban local markets and its contribution in reduction of food insecurity in Rwanda is considerable. But the postharvest loss of this commodity is a critical challenge due to its high perishability. Several research activities have been conducted on how fresh food commodities can be transformed into extended shelf life food products for prevention of post-harvest losses. However, such activity was not yet well studied in Rwanda. The aim of the present study was the processing of backed products from (OFSP)combined with wheat composite flour and assess the nutritional content and consumer acceptability of new developed products. The perishability of OFSP and their related lack during off season can be eradicated by producing cake, doughnut and bread with OFSP puree or flour. The processing for doughnut and bread were made by making OFSP puree and other ingredients then a dough was made followed by frying and baking while for cake OFSP was dried through solar dryer to have a flour together with wheat flour and other ingredients to make dough cake and baking. For each product, one control and three experimental samples, (three products in three different ratios (30,40 and50%) of OFSP and the remaining percentage of wheat flour) were prepared. All samples including the control were analyzed for the consumer acceptability (sensory attributes). Most preferred samples (One sample for each product with its control sample and for each OFSP variety) were analyzed for nutritional composition along with control sample. The Cake from Terimbere variety and Bread from Gihingumukungu supplemented with 50% OFSP flour or Puree respectively were most acceptable except Doughnut from Vita variety which was highly accepted at 50% of OFSP supplementation. The moisture, ash, protein, fat, fiber, Total carbohydrate, Vitamin C, reducing sugar and minerals (Sodium, Potassium and Phosphorus.) content was different among products. Cake was rich in fibers (14.71%), protein (6.590%), and vitamin c(19.988mg/100g) compared to other samples while bread found to be rich in reducing sugar with 12.71mg/100g compared to cake and doughnut. Also doughnut was found to be rich in fat content with 6.89% compared to other samples. For sensory analysis, doughnut was highly accepted in ratio of 60:40 compared to other products while cake was least accepted at ratio of 50:50. The Proximate composition and minerals content of all the OFSP products were significantly higher as compared to the control samples.

Keywords: post-harvest loss, OFSP products, wheat flour, sensory evaluation, proximate composition

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Authors: Fares Hedayatit, Arnauld Joly, Panagiotis Papadimitriou

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Many machine learning tasks such as text annotation usually require training over very big datasets, e.g., millions of web documents, that can be represented in a sparse input space. State-of the-art tree-based ensemble algorithms cannot scale to such datasets, since they include operations whose running time is a function of the input space size rather than a function of the non-zero input elements. In this paper, we propose an efficient splitting algorithm to leverage input sparsity within decision tree methods. Our algorithm improves training time over sparse datasets by more than two orders of magnitude and it has been incorporated in the current version of scikit-learn.org, the most popular open source Python machine learning library.

Keywords: big data, sparsely representable data, tree-based models, scalable learning

Procedia PDF Downloads 236

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: S. Raeis Farshid, B. Raeis Farshid

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Ag-TiO₂ nanocomposites were prepared by the sol-gel method with and without additives such as carboxy methyl cellulose (CMC), polyethylene glycol (PEG), polyvinyl pyrrolidone (PVP), and hydroxyl propyl cellulose (HPC). The characteristics of the prepared Ag-TiO₂ nanocomposites were identified by Fourier Transform Infra-Red spectroscopy (FTIR), X-Ray Diffraction (XRD), and scanning electron microscopy (SEM) methods. The additives have a significant effect on the particle size distribution and photocatalytic activity of Ag-TiO₂ nanocomposites. SEM images have shown that the particle size distribution of Ag-TiO₂ nanocomposite in the presence of HPC was the best in comparison to the other samples. The photocatalytic activity of the synthesized nanocomposites was investigated for decolorization of methyl orange (MO) in water under UV-irradiation in a batch reactor, and the results showed that the photocatalytic activity of the nanocomposites had been increased by CMC, PEG, PVP, and HPC, respectively.

Keywords: sol-gel method, Ag-TiO₂, decolorization, photocatalyst, nanocomposite

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Authors: Antonio J. Melendez-Martinez

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Beyond their role as natural colorants, some carotenoids are provitamins A and may be involved in health-promoting biological actions and contribute to reducing the risk of developing non-communicable diseases, including several types of cancer, cardiovascular disease, eye conditions, skin disorders or metabolic disorders. Given the versatility of carotenoids, the COST-funded European network to advance carotenoid research and applications in agro-food and health (EUROCAROTEN) is aimed at promoting health through the diet and increasing well-being by means. Stakeholders from 38 countries participate in this network, and one of its main objectives is to promote research on little-studied carotenoids. In this contribution, recent advances of our research group and collaborators in the study of two such understudied carotenoids, namely phytoene and phytofluene, the colorless carotenoids, are outlined. The study of these carotenoids is important as they have been largely neglected despite they are present in our diets, fluids, and tissues, and evidence is accumulating that they may be involved in health-promoting actions. More specifically, studies on their levels in diverse tomato and orange varieties were carried out as well as on their potential bioavailability from different dietary sources. Furthermore, the potential effect of these carotenoids on an animal model subjected to oxidative stress was evaluated. The tomatoes were grown in research greenhouses, and some of them were subjected to regulated deficit irrigation, a sustainable agronomic practice. The citrus samples were obtained from an experimental field. The levels of carotenoids were assessed using HPLC according to routine methodologies followed in our lab. Regarding the potential bioavailability (bioaccessibility) studies, different products containing colorless carotenoids, like fruits, juices, were subjected to simulated in vitro digestions, and their incorporation into mixed micelles was assessed. The effect of the carotenoids on oxidative stress was evaluated on the Caenorhabditis elegans model. For that purpose, the worms were subjected to oxidative stress by means of a hydrogen peroxide challenge. In relation to the presence of colorless carotenoids in tomatoes and orange varieties, it was observed that they are widespread in such products and that there are mutants with very high quantities of them, for instance, the Cara Cara or Pinalate mutant oranges. The studies on their bioaccessibility revealed that, in general, phytoene and phytofluene are more bioaccessible than other common dietary carotenoids, probably due to their distinctive chemical structure. About the in vivo antioxidant capacity of phytoene and phytofluene, it was observed that they both exerted antioxidant effects at certain doses. In conclusion, evidence on the importance of phytoene and phytofluene as dietary easily bioavailable and antioxidant carotenoids has been obtained in recent studies from our group, which can be important shortly to innovate in health-promotion through the development of functional foods and related products.

Keywords: carotenoids, health, functional foods, nutrition, phytoene, phytofluene

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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Authors: Mary Chriselda A

Abstract:

This paper deals with the fact that the Hubble's parameter is not constant and tends to vary stochastically with time. This premise has been proven by converting it to a stochastic differential equation using the Ornstein-Uhlenbeck process. The formulated stochastic differential equation is further solved analytically using the Euler and the Kolmogorov Forward equations, thereby obtaining the probability density function using the Fourier transformation, thereby proving that the Hubble's parameter varies stochastically. This is further corroborated by simulating the observations using Python and R-software for validation of the premise postulated. We can further draw conclusion that the randomness in forces affecting the white noise can eventually affect the Hubble’s Parameter leading to scale invariance and thereby causing stochastic fluctuations in the density and the rate of expansion of the Universe.

Keywords: Chapman Kolmogorov forward differential equations, fourier transformation, hubble's parameter, ornstein-uhlenbeck process , stochastic differential equations

Procedia PDF Downloads 174

Authors: Vishnu Varthan Vaithiyalingam Jagannathan, Lakshmi Karunanidhi Santhanalakshmi, Srividya Ammayappan Rajam

Abstract:

Formononetin is the O-Methoxy Flavonol that has many pharmacological activities, which belongs to the flavonoid family. In the current study, activity of this molecule was evaluated in lung cancer cell lines. In general, flavonoids possess certain anticancer mechanism. Being a flavonoid subfamily, this molecule was subjected to evaluate cytotoxicity assay by MTT ((3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide)) stain, mode of cell death assay stained by acridine orange and ethidium bromide and Evaluation of Apoptosis pathway (extrinsic or intrinsic) by Caspase 3/7 stain and Rhodamine-123 stain. From the results, we could able to confirm that the investigatory molecule formononetin has anticancer activity and in future, the study will propose to evaluate the formononetin action against genetic changes occurs during lung cancer progression.

Keywords: Caspase 3/7, formononetin, lung cancer, Rhodamine-123

Procedia PDF Downloads 183

Authors: Mehdi Ghommem, Daniel Garcia, Nathan Collier, Victor Calo

Abstract:

We develop a fast, user-friendly implementation of a potential flow solver based on the unsteady vortex lattice method (UVLM). The computational framework uses the Python programming language which has easy integration with the scripts requiring computationally-expensive operations written in Fortran. The mixed-language approach enables high performance in terms of solution time and high flexibility in terms of easiness of code adaptation to different system configurations and applications. This computational tool is intended to predict the unsteady aerodynamic behavior of multiple moving bodies (e.g., flapping wings, rotating blades, suspension bridges...) subject to an incoming air. We simulate different aerodynamic problems to validate and illustrate the usefulness and effectiveness of the developed computational tool.

Keywords: unsteady aerodynamics, numerical simulations, mixed-language approach, potential flow

Procedia PDF Downloads 265

Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

Abstract:

Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

Procedia PDF Downloads 82

Authors: Yi-Wei Huang

Abstract:

Eileen Chang is a well-known writer of modern Chinese literature. She is also a translator that publishes her self-translation The Rice Sprout Song. The purpose of the study is to identify the style of Eileen Chang’s self-translations by corpora, especially in the case of The Rice Sprout Song. The Rice Sprout Song is first written in English and then translated into Chinese by the author herself. The procedure of translation is complicated due to the bilingual transition by the same person. Therefore, the aim of the study is to identify Eileen Chang’s style on her self-translation by comparing her works The Old Man and the Sea, The Rice Sprout Song, and The Rouge of The North. The study uses computer-aided software like AntConc, Notepad++, StanfordCoreNLP, and Python to analyze the style of the works, especially focuses on reduplications and the composition of the sentences. Reduplications are commonly seen in Eileen Chang’s works, and they often appear with colors or onomatopoeia. With these criteria, the style of self-translating can be detected and analyzed.

Keywords: corpora, Eileen Chang, reduplications, self-translation

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Authors: Chaima Babi, Said Gadri

Abstract:

The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

Procedia PDF Downloads 45

Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

Abstract:

The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

Procedia PDF Downloads 47

Authors: M. Chiliza, H. P. Mbukwane, P Masita, H. Rutto

Abstract:

Acid mine drainage (AMD) one of the main pollutants of water in many countries that have mining activities. AMD results from the oxidation of pyrite and other metal sulfides. When these metals gets exposed to moisture and oxygen, leaching takes place releasing sulphate and Iron. Acid drainage is often noted by 'yellow boy,' an orange-yellow substance that occurs when the pH of acidic mine-influenced water raises above pH 3, so that the previously dissolved iron precipitates out. The possibility of using environmentally friendly silane and phosphate based coatings on pyrite to remediate acid mine drainage and prevention at source was investigated. The results showed that both coatings reduced chemical oxidation of pyrite based on Fe and sulphate release. Furthermore, it was found that silane based coating performs better when coating synthesis take place in a basic hydrolysis than in an acidic state.

Keywords: acid mine drainage, pyrite, silane, phosphate

Procedia PDF Downloads 320