Search results for: green extraction

Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: artificial neural networks, digital image processing, pattern recognition, phytosanitary

Procedia PDF Downloads 323

Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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Authors: Hyehyeon Lee, Juwon Yu, Juwon Kim, Raquel Kristina Leoni Tumiar, Taewon Kim, Juae Kim, Hongsuk Suh

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Recently, the development of photovoltaics is rapidly accelerating as one of green energy sources. So we designed pyrimidine-based polymers with 2-{3-[4,6-bis-(4-hexyl-thiophen-2-yl)-pyrimidin-2-yl]-phenyl}-thiazolo[5,4-b]pyridine (mPTP), as active layer substances for polymer solar cells. Polymers with push-pull types, mPTPBDT-12, mPTPBDT-EH, mPTPBDTT-EH and mPTPTTI, are comprised of electron pushing unit using benzo[1,2-b;3,4-b’]dithiophene (BDT) or 4,8-bis(5-thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene (BDTT) or 6-(2-thienyl)-4H-thieno[3,2-b]indole(TTI) and electron pulling unit using mPTP. The device including mPTPTTI-12 indicated a VOC of 0.67 V, a JSC of 2.16 mA/cm², and a fill factor (FF) of 0.30, giving a power conversion efficiency (PCE) of 0.43%. The device including mPTPBDT-EH indicated a VOC of 0.56 V, a JSC of 2.64 mA/cm², and an FF of 0.30, giving a PCE of 0.44%. The device including mPTPBDTT-EH indicated a VOC of 0.44 V, a JSC of 2.45 mA/cm², and an FF of 0.29, giving a PCE of 0.31%. The device including mPTPTTI indicated a VOC of 0.72 V, a JSC of 4.95 mA/cm², and an FF of 0.32, giving a PCE of 1.15%. Therefore, mPTPBDT-12, mPTPBDT-EH, mPTPBDTT-EH and mPTPTTI were fabricated by Stille polymerization. Their optical properties were measured and the results show that pyrimidine-based polymers have a great promise to act as donor of active layer.

Keywords: polymer solar cells, photovoltaics, thiazolopyridine, conjugated polymer

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Authors: Hussain Ali Bekhet, Nor Salwati Othman

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Malaysia has achieved remarkable economic growth since 1957, moving toward modernization from a predominantly agriculture base to manufacturing and—now—modern services. The development policies (i.e., New Economic Policy [1970–1990], the National Development Policy [1990–2000], and Vision 2020) have been recognized as the most important drivers of this transformation. The transformation of the economic structure has moved along with rapid gross domestic product (GDP) growth, urbanization growth, and greater demand for energy from mainly fossil fuel resources, which in turn, increase CO2 emissions. Malaysia faced a great challenge to bring down the CO2 emissions without compromising economic development. Solid policies and a strategy to reduce dependencies on fossil fuel resources and reduce CO2 emissions are needed in order to achieve sustainable development. This study provides an overview of the Malaysian economic, energy, and environmental situation, and explores the existing policies and strategies related to energy and the environment. The significance is to grasp a clear picture on what types of policies and strategies Malaysia has in hand. In the future, this examination should be extended by drawing a comparison with other developed countries and highlighting several options for sustainable development.

Keywords: energy policies, energy efficiency, renewable energy, green building, Malaysia, sustainable development

Procedia PDF Downloads 240

Authors: C. C. Igwe

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Several parts of Neem tree (Azadirachta indica) are used in traditional medicine in many West African countries for the treatment of various human diseases. The leaf, stem - bark and seed were air dried for 8, 5 and 7 days, respectively. The shells were carfully separated from the seeds, each powdered sample obtained with mechanical miller and 250 mm sieve. The neem samples were individually subjected to extraction with acetone, n-hexane for 48hr and 72 hr, respectively. Physico-chemical and antibacterial evaluation were carried out using standard methods. Results of physico - chemical analyses of the extracted oil from the seed shows that it has a brownish colour, with a smell similar to garlic while the moisture content, refractive index are 0.76% and 1.47 respectively. Other vital chemical results obtained from the neem oil such as saponification value (234.62), acid value (10.84 %), free fatty acid (5.84 %) and peroxide value (10.52%) indicated the oil extracted satisfied standard oils parameters for quality soap and cosmetics production. The antibacterial screening by disc diffusion revealed the oil demonstrated high activity against Staphylococcus aureus. Both the physio-chemical and antibacterial of samples have been certified by National Agency for Food and Drugs Administration and Control. The preliminary results of this study may validate the medicinal value of the plant. Further studies are in progress to clarify the in vivo potentials of neem extracts in the management of human communicable diseases and this is a subject of investigation in our group.

Keywords: anti-bacterial, neem extract, physico-chemical analyses, staphylococcus aureus

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Authors: Mohammad Ali Farrokhpour

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In the current decade and sustainable transportation systems, scooter sharing has attracted widespread attention as an environmentally-friendly means of public transportation which can help develop public transportation. The combination of scooters and subway in the area of sustainable transportation systems can provide a great many opportunities for developing access to public transportation. Of the challenges which have arisen and initiated discussions of interest about the implementation of a scooter-subway system to replace personal vehicles is the issue of routing in the aforementioned system. This has been chosen as the main subject of the present paper. Thus, the present paper provides an account for routing in this system. Because the issue of routing includes multiple factors such as time, costs, traffic, green spaces, etc., the above-mentioned problem is considered to be a multi-objective NP-hard optimization problem. For this purpose, the hybrid optimization approach of PSO-GA has been put forward in the present paper for the provided answers to be of higher accuracy and validity than those of normal optimization methods. The results obtained from modeling and problem solving for the case study in the MATLAB software are indicative of the efficiency and desirability of the model and the proposed approach for solving the model

Keywords: route planning, scooter sharing, public transportation, sharing system

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Authors: Italo Luigi de Paoli

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The use of synthetic soil for the vegetables cultivation in conditions of limited water consumption The separate collection of urban organic waste and green waste for the countries of the European Union averages 100 kg / inhabitant x year with an annual growth of about 10%. The production of quality compost averages 38% - 40% of the production of organic waste material. Most of the compost produced is used as an organic soil improver in those nutrient-poor soils in order to improve its quality. This study seeks to enhance the production of quality compost by creating a synthetic soil, where the percentages of compost on average oscillate between 50% and 60% in which, with appropriate precautions, different species of horticultural can be grown in conditions of high environmental safety without the use of pesticides and with a consumption of water used for irrigation limited to the actual evaporation of the plants. The project started in 2018 and is still ongoing, confirms its validity through a series of different horticultural productions, especially if this technology is applied where the availability of land suitable for the cultivation of vegetables is limited and where the use of water for irrigation represents a cultural criticality. Furthermore, the creation of "open field" crops, together with their automation, represents a further possibility in the concrete development of such technologies, giving the final product organoleptic characteristics equal if not superior to what the market offers today for human nutrition.

Keywords: water scarcity, compost, vegetable foods, syntetic soil

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Authors: Esra Cebeci

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As a result of acceleration of globalization in the 21st century economic boundaries are removed. With liberalization of capital and foreign trade, not only developed countries but also developing countries get into rapid growth efforts. In developing countries, one of the most important problem is insufficient capital accumulation. For reduce this deficit, one of the general approaches that is offered increasing amount of foreign direct investments. Also, in developing countries saving rates are low. So, foreign direct investments make possible an increase for domestic savings. In this regard, the multinational corporations are capable of these investments have importance. By providing micro-macro effects for countries, demand for these firms are many. These effects in general positive, some negative effects may able to come into being especially for developing countries. Foreign direct investments are performed buying an existing corporation, merging or greenfield investments. In recent, foreign direct investments are performed as a green field investments for developing countries. The study aims to analysis foreign direct investment trends for 2000-2013 years. In the first part of this study, the importance of foreign direct investments and their determinants are explained. In the second part, the article also shows that comparative analysis of the inward and outward investments for developing and developed countries. In conclusion, while developed countries can stand competition against other countries with these investments, developing countries can provide a sustainable growth with capital inflows.

Keywords: foreign direct investments, multinational corporations, determinants of FDI, FDI trend

Procedia PDF Downloads 398

Authors: Andre Wittenborn, Jarek Krajewski

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Trauma-related sadness in speech can alter the voice in several ways. The generation of non-linear aerodynamic phenomena within the vocal tract is crucial when analyzing trauma-influenced speech production. They include non-laminar flow and formation of jets rather than well-behaved laminar flow aspects. Especially state-space reconstruction methods based on chaotic dynamics and fractal theory have been suggested to describe these aerodynamic turbulence-related phenomena of the speech production system. To extract the non-linear properties of the speech signal, we used the time delay embedding method to reconstruct from a scalar time series (reconstructed phase space, RPS). This approach results in the extraction of 7238 Features per .wav file (N= 47, 32 m, 15 f). The speech material was prompted by telling about autobiographical related sadness-inducing experiences (sampling rate 16 kHz, 8-bit resolution). After combining these features in a support vector machine based machine learning approach (leave-one-sample out validation), we achieved a correlation of r = .41 with the well-established, self-report ground truth measure (RATS) of post-traumatic stress disorder (PTSD).

Keywords: non-linear dynamics features, post traumatic stress disorder, reconstructed phase space, support vector machine

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Authors: Chamindi Dilkushi Senaratne

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Staff development both formal and informal, structured and unstructured is universally accepted as fundamental to the growth of individuals and institutions. This study is based on feedback summaries collected from 2014 to 2017 from 240 participants of the staff development programme for probationary lecturers at the University of Kelaniya, Sri Lanka. It also contains data from interviews conducted with the resource persons in the programme. The study further includes observations from experts involved in staff training in higher education institutions in Sri Lanka The data reveals that though the programme has many aspects that can be improved, the selected topics in the curriculum and new topics that were incorporated had positive impacts to enhance continuing professional development of staff in Sri Lankan universities. The participants also believe that the programme has an impact on professional development, teaching, and management of classroom and curricula and research skills. Based on the findings, the study recommends the addition of new topics to the curriculum such as continuing professional development, code of conduct in universities, gender awareness and the green concept. The study further recommends programmes for senior academic staff in universities to assist them to reach higher levels in their career by focusing on areas such as teaching, research, and administrative skills.

Keywords: staff development, higher education, curriculum, research

Procedia PDF Downloads 225

Authors: Belen Carrillo, Mauricio Mosquera

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Fatty acids are bioactive compounds widely used as nutritional supplements in the food and pharmaceutical industry. Bluefish such as sardines have a large variety of these fatty acids in their composition. The objective of this project is to extract these compounds from fishing wastes, to do this, heads of known species as Pinchagua (Opistonema libertate) were used. The conducted study represents a simplified alternative for obtaining and simultaneous saponification of oil through basic hydrolysis, which separates lipids from protein and saponifies sample all the same time to isolate the fatty acid accurately through salts formation. To do these different concentrations of sodium hydroxide were used, it was demonstrated at a concentration of 1 M the highest yield of saponified oil recovery corresponding a value of 3,64% was obtained. Subsequently, the saponified oil was subjected to an acid hydrolysis in which fatty acids were isolated. Different sulfuric acid concentrations and temperatures for the process were tested. Thus, it was shown that the great fatty acids variety were obtained at a 60 °C temperature and sulfuric acid concentration of 50% v/v. Among the obtained compounds the presence of acids such as palmitic, lauric, caproic and myristic are highlighted. Applications of this type of elements are varied and widely used in the nutritional supplements development. Thus, the described methodology proposes a simple mechanism in the revaluation of fishing industry wastes that allow directly generate high added value elements.

Keywords: fatty acids, hydrolysis, Pinchagua, saponification

Procedia PDF Downloads 177

Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

Procedia PDF Downloads 412

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

Procedia PDF Downloads 489

Authors: Azeez O. Idris, Benjamin O. Orimolade, Potlako J. Mafa, Alex T. Kuvarega, Usisipho Feleni, Bhekie B. Mamba

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We report a simple and cheaper method for the electrochemical detection of Se(IV) using carbon nanodots (CNDTs) prepared from oat. The carbon nanodots were synthesised by green and facile approach and characterised using scanning electron microscopy, high-resolution transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and Raman spectroscopy. The CNDT was used to fabricate an electrochemical sensor for the quantification of Se(IV) in water. The modification of glassy carbon electrode (GCE) with carbon nanodots led to an increase in the electroactive surface area of the electrode, which enhances the redox current peak of [Fe(CN)₆]₃₋/₄‒ in comparison to the bare GCE. Using the square wave voltammetry, the detection limit and quantification limit of 0.05 and 0.167 ppb were obtained under the optimised parameters using deposition potential of -200 mV, 0.1 M HNO₃ electrolyte, electrodeposition time of 60 s, and pH 1. The results further revealed that the GCE-CNDT was not susceptible to many interfering cations except Cu(II) and Pb(II), and Fe(II). The sensor fabrication involves a one-step electrode modification and was used to detect Se(IV) in a real water sample, and the result obtained is in agreement with the inductively coupled plasma technique. Overall, the electrode offers a cheap, fast, and sensitive way of detecting selenium in environmental matrices.

Keywords: carbon nanodots, square wave voltammetry, nanomaterials, selenium, sensor

Procedia PDF Downloads 84

Authors: Tran Thi Anh Dao, M. Arnold, L. Schacher, D. C. Adolphe, G. Reys

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During tooth extraction or implant surgery, dentists are in contact with numerous infectious germs from patients' saliva and blood. For that reason, dentist's clothes have to play their role of protection from contamination. In addition, dentist's apparels should be not only protective but also comfortable and breathable because dentists have to perform many operations and treatments on patients throughout the day with high concentration and intensity. However, this type of protective garments has not been studied scientifically, whereas dentists are facing new risks and eager for looking for a comfortable personal protective equipment. For that reason, we have proposed some new designs of dentist's gown. They were expected to diminish heat accumulation that are considered as an important factor in reducing the level of comfort experienced by users. Experiments using infra-red technology were carried out in order to compare the breathable properties between a traditional gown and a new design with open zones. Another experiment using pressure sensors was also carried out to study ergonomic aspects trough the flexibility of movements of sleeves. The sleeves-design which is considered comfortable and flexible will be chosen for the further step. The results from the two experiments provide valuable information for the development of a new design of dentists' gowns in order to achieve maximum levels of cooling and comfort for the human body.

Keywords: garment, dentists, comfort, design, protection, thermal

Procedia PDF Downloads 217

Authors: Oshin Anand, Atanu Rakshit

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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

Procedia PDF Downloads 384

Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

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Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

Procedia PDF Downloads 366

Authors: Khadra Ahmed, Khaled Kheireldin

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: planktons, diversity indices, water quality index, water ways

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Authors: Ahmad E. Aldousaria, Abdulla Al Kafy

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Urbanization is an incessant process that involves the transformation of land use/land cover (LULC), resulting in a reduction of cool land covers and thermal comfort zones (TCZs). This study explores the directional shrinkage of TCZs in Kuwait using Landsat satellite data from 1991 – 2021 to predict the future LULC and TCZ distribution for 2026 and 2031 using cellular automata (CA) and artificial neural network (ANN) algorithms. Analysis revealed a rapid urban expansion (40 %) in SE, NE, and NW directions and TCZ shrinkage in N – NW and SW directions with 25 % of the very uncomfortable area. The predicted result showed an urban area increase from 44 % in 2021 to 47 % and 52 % in 2026 and 2031, respectively, where uncomfortable zones were found to be concentrated around urban areas and bare lands in N – NE and N – NW directions. This study proposes an effective and sustainable framework to control TCZ shrinkage, including zero soil policies, planned landscape design, manmade water bodies, and rooftop gardens. This study will help urban planners and policymakers to make Kuwait an eco–friendly, functional, and sustainable country.

Keywords: land cover change, thermal environment, green cover loss, machine learning, remote sensing

Procedia PDF Downloads 222

Authors: C. A. Anser Pasha

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In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

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Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

Procedia PDF Downloads 128

Authors: Osama M. Darwesh, Sahar H. Hassan, Abd El-Raheem R. El-Shanshoury, Shawky Z. Sabae

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Nanotechnology as multidisciplinary technology is growing rapidly with important applications in several sectors. Also, nanobiotechnology is known for the use of microorganisms for the synthesis of targeted nanoparticles. The present study deals with the green synthesis of silver nanoparticles using aquatic bacteria and the development of a biogenic nanocomposite for environmental applications. Twenty morphologically different colonies were isolated from the collected water samples from eight different locations at the Rosetta branch of the Nile Delta, Egypt. The obtained results illustrated that the most effective bacterial isolate (produced the higher amount of AgNPs after 24 h of incubation time) is isolate R3. Bacillus tequilensis was the strongest extracellular bio-manufactory of AgNPs. Biosynthesized nanoparticles had a spherical shape with a mean diameter of 2.74 to 28.4 nm. The antimicrobial activity of silver nanoparticles against many pathogenic microbes indicated that the produced AgNPs had high activity against all tested multi-antibiotic resistant pathogens. Also, the stabilized prepared AgNPs-SA nanocomposite has greater catalytic activity for the decolourization of some dyes like Methylene blue (MB) and Crystal violet. Such results represent a promising stage for producing eco-friendly, cost-effective, and easy-to-handle devices for the bioremediation of contaminated industrial wastewater.

Keywords: bioremediation, AgNPs, AgNPs-SA nanocomposite, Bacillus tequilensis, nanobiotechnology

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Authors: Gokhan Sir, Muhammed Ergun, Onder Balioglu

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Nowadays, laundry dryers containing heaters and heat pumps are used to provide fast and efficient drying. In this system, as the drying capacity changes, the sensible and latent heat transfer rate in the evaporator changes. Therefore, the drying time measured for the unit capacity increases as the drying capacity decreases. The objective of this study is to investigate the evaporator efficiency according to load amount and textile type in hybrid heat pump dryers. Air side flow rate and system temperatures (air side and refrigeration side) were monitored instantly, and the specific moisture extraction rate (SMER), evaporator efficiency, and heat transfer mechanism between the textile and hybrid heat pump system were examined. Evaporator efficiency of heat pump dryers for cotton and synthetic based textile types in load amounts of 2, 5, 8 and 10 kg were investigated experimentally. As a result, the maximum evaporator efficiency (%72) was obtained in drying cotton and synthetic based textiles with a capacity of 5 kg; the minimum evaporator efficiency (%40) was obtained in drying cotton and synthetic based textiles with a capacity of 2 kg. The experimental study also reveals that capacity-dependent flow rate changes are the major factor for evaporator efficiency.

Keywords: evaporator, heat pump, hybrid, laundry dryer, textile

Procedia PDF Downloads 134

Authors: Stephen Eyije Abechi, Casimir Emmanuel Gimba, Zaharaddeen Nasiru Garba, Sani Shamsudeen, David Ebuka Authur

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Corrosion inhibition of mild steel in acid medium using Acalypha chamaedrifolia leaves extract as potential green inhibitor was investigated. Gravimetric (weight loss) technique was used for the corrosion studies. Mild steel coupons of 2cm × 1cm × 0.27 cm dimensions were exposed for varying durations of between 24 to 120 hours, in 1M HCl medium containing a varying concentrations of the leaves extract (0.25g/L, - 1.25g/L). The results show that corrosion rates dropped from a value of 0.49 mgcm-2hr-1 for the uninhibited medium to a value of 0.15 mgcm-2hr-1 for the inhibited medium of 1M HCl in 0.25 g/l of the extract. Values of corrosion inhibition efficiencies of 70.38-85.11% were observed as the concentration of the inhibitor were increased from 0.25g/L, - 1.25g/L. Corrosion Inhibition was found to increase with increase in immersion time and temperature. The magnitude of the Ea indicates that the interaction between the metal surface and the inhibitor was chemisorptions. The Adsorption process fit into the Langmuir isotherm model with a correlation coefficient of 0.97. Evidence from molecular dynamics model shows that Methyl stearate (Line 5) and (3Z, 13Z)-2-methyloctadeca-3,13-dien-1-ol (line 11) were found to have the highest binding energy of -197.69 ± 3.12 and-194.56 ± 10.04 in kcal/mol respectively. The binding energy of these compounds indicates that they would be a very good corrosion inhibitor for mild steel and other Fe related materials.

Keywords: binding energy, corrosion, inhibitor, langmuir isotherm, mild steel

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Authors: Gizachew Belay Adugna, Yu-Tai Tao

Abstract:

Perovskite solar cells (PSCs) have been gaining impressive progress with excellent power conversion efficiency (PCE) of 25.5% in small-area devices. However, the conventional film coating approach is not applicable to large-area module fabrication. Meniscus-guided coating, including blade coating, slot-die coating, and bar coating, is solution processing and promising for large-area and cost-effective film coating to industrial-scale PSCs. Here, we develop simple and scalable solution shearing (SS) and bar coating (BC) methods to coat all layers on large-area (10x10 cm²) substrate in FTO/c-TiO₂/mp-TiO₂/ CH₃NH₃PbI₃/Spiro-OMeTAD/Ag device structure, except the Ag electrode. All solution-sheared PSC exhibited a champion power conversion efficiency of 15.89% in the conational DMF/DMSO solvent. Whereas a very high PCE of 20.30% compared to the controlled spin-coated device (SC, 17.60%) was achieved from the large area sheared perovskite film in a green ACN/MA solvent. Similarly, a remarkable PCE of 18.50% was achieved for a device fabricated from a large-area perovskite film in a simpler and more compatible Bar-coating system. This strategy demonstrates the huge potential for module fabrication and future PSC commercialization.

Keywords: Perovskite solar cells, larger area film coating, meniscus-guided film coating, solution-shearing, bar-coating, power conversion efficiency

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Authors: Zeljko Crljen, Predrag Lazic

Abstract:

Graphene has attracted a tremendous interest in the field of nanoelectronics and spintronics due to its exceptional electronic properties. However, pristine graphene has no band gap, a feature needed in building some of the electronic elements. Recently, a growing attention has been given to a class of carbon allotropes of graphene with honeycomb structures, in particular to graphyne and graphdiyne. They are characterized with a single and double acetylene bonding chains respectively, connecting the nearest-neighbor hexagonal rings. With an electron density comparable to that of graphene and a prominent gap in electronic band structures they appear as promising materials for nanoelectronic components. We studied the electronic structure and transport of infinite sheets of graphyne and graphdiyne and compared them with graphene. The method based on the non-equilibrium Green functions and density functional theory has been used in order to obtain a full ab initio self-consistent description of the transport current with different electrochemical bias potentials. The current/voltage (I/V) characteristics show a semi-conducting behavior with prominent nonlinearities at higher voltages. The calculated band gaps are 0.52V and 0.59V, respectively, and the effective masses are considerably smaller compared to typical semiconductors. We analyzed the results in terms of transmission eigenchannels and showed that the difference in conductance is directly related to the difference of the internal structure of the allotropes.

Keywords: electronic transport, graphene-like structures, nanoelectronics, two-dimensional materials

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

Abstract:

With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

Abstract:

Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

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Authors: Parmjit S. Panesar, Rupinder Kaur, Ram S. Singh

Abstract:

Enzymes are the biocatalysts which catalyze the biochemical processes and thus have a wide variety of applications in the industrial sector. β-Galactosidase (E.C. 3.2.1.23) also known as lactase, is one of the prime enzymes, which has significant potential in the dairy and food processing industries. It has the capability to catalyze both the hydrolytic reaction for the production of lactose hydrolyzed milk and transgalactosylation reaction for the synthesis of prebiotics such as lactulose and galactooligosaccharides. These prebiotics have various nutritional and technological benefits. Although, the enzyme is naturally present in almonds, peaches, apricots and other variety of fruits and animals, the extraction of enzyme from these sources increases the cost of enzyme. Therefore, focus has been shifted towards the production of low cost enzyme from the microorganisms such as bacteria, yeast and fungi. As compared to yeast and bacteria, fungal β-galactosidase is generally preferred as being extracellular and thermostable in nature. Keeping the above in view, the present study was carried out for the isolation of the β-galactosidase producing fungal strain from the food as well as the agricultural wastes. A total of more than 100 fungal cultures were examined for their potential in enzyme production. All the fungal strains were screened using X-gal and IPTG as inducers in the modified Czapek Dox Agar medium. Among the various isolated fungal strains, the strain exhibiting the highest enzyme activity was chosen for further phenotypic and genotypic characterization. The strain was identified as Rhizomucor pusillus on the basis of 5.8s RNA gene sequencing data.

Keywords: beta-galactosidase, enzyme, fungal, isolation

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Authors: Sara Mercedes Barroso Pinzón, Álvaro Jesús Caicedo Castro, Antonio Javer Sánchez Herencia

Abstract:

In recent years there has been increased academic and industrial research into the development of orthopaedic implants with structural properties and functionality similar to mechanical strength, osseointegration, thermal stability and antibacterial capacity similar to bone structure. Hydroxyapatite has been considered for decades as an ideal biomaterial for bone regeneration due to its chemical and crystallographic similarity to the mineral structure bioapatites. However, the lack of trace elements in the hydroxyapatite structure confers very low mechanical and biological properties. Under this scenario, the objective of the research is the synthesis of hydroxyapatite with Mg from the francolite mineral present in phosphate rock from the central-eastern region of Colombia, taking advantage of the extraction of mineral species as natural precursors of Ca, P and Mg. The minerals present were studied, fluorapatite as the mineral of interest associated with magnesium carbonates and quartz. The chemical and mineralogical composition was determined by X-ray fluorescence (XRF) and X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX); the optimum conditions were established using the acid leaching mechanism in the wet concentration process. From the products obtained and characterised by XRD, XRF, SEM, FTIR, RAMAN, HAp-Mg biocomposite scaffolds are fabricated and the influence of Mg on morphometric parameters, mechanical and biological properties in the formed materials is evaluated.

Keywords: phosphate rock, hydroxyapatite, magnesium, biomaterials

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