Search results for: mineral processing.

Authors: Mohammad Beyki, Justus Pawlak, Robert Patzke, Franz Renz

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In the context of planetary exploration, the MIMOS II (miniaturized Mössbauer spectrometer) serves as a proven and reliable measuring instrument. The transmission behaviour of the electronics in the Mössbauer spectroscopy is newly developed and optimized. For this purpose, the overall electronics is split into three parts. This elaboration deals exclusively with the first part of the signal chain for the evaluation of photons in experiments with gamma radiation. Parallel to the analysis of the electronics, a new method for the stability consideration of linear and non-linear systems is presented: The extended method of Lyapunov’s stability criteria. The design helps to weigh advantages and disadvantages against other simulated circuits in order to optimize the MIMOS II for the terestric and extraterestric measurment. Finally, after stability analysis, the controller design according to Ackermann is performed, achieving the best possible optimization of the output variable through a skillful pole assignment.

Keywords: Mössbauer spectroscopy, electronic signal amplifier, light processing technology, photocurrent, trans-impedance amplifier, extended Lyapunov method

Procedia PDF Downloads 99

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

Procedia PDF Downloads 182

Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu

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Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.

Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding

Procedia PDF Downloads 167

Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

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In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: churn prediction, data mining, decision-theoretic rough set, feature selection

Procedia PDF Downloads 446

Authors: Tarek M. Ahmed, Ahmed S. El Mesalamy, Amro M. Youssef, Tawfik T. El Midany

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Abrasive waterjet (AWJ) machining is considered as one of the most powerful cutting processes. It can be used for cutting heat sensitive, hard and reflective materials. Aluminum 2024 is a high-strength alloy which is widely used in aerospace and aviation industries. This paper aims to improve aluminum alloy and to investigate the effect of AWJ control parameters on surface geometry quality. Design of experiments (DoE) is used for establishing an experimental matrix. Statistical modeling is used to present a relation between the cutting parameters (pressure, speed, and distance between the nozzle and cut surface) and responses (taper angle and surface roughness). The results revealed a tangible improvement in productivity by using AWJ processing. The taper kerf angle can be improved by decreasing standoff distance and speed and increasing water pressure. While decreasing (cutting speed, pressure and distance between the nozzle and cut surface) improve the surface roughness in the operating window of cutting parameters.

Keywords: abrasive waterjet machining, machining of aluminum alloy, non-traditional cutting, statistical modeling

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Authors: Sari Elkahina, Zergoug Mourad, Benachenhou Kamel

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The main purpose of this paper is to perform a computations comparison of stress intensity factor 'SIF' evaluation in case of cracked thin plate with Aluminum alloy 7075-T6 and 2024-T3 used in aeronautics structure under uniaxial loading. This evaluation is based on finite element method with a virtual power principle through two techniques: the extrapolation and G−θ. The first one consists to extrapolate the nodal displacements near the cracked tip using a refined triangular mesh with T3 and T6 special elements, while the second, consists of determining the energy release rate G through G−θ method by potential energy derivation which corresponds numerically to the elastic solution post-processing of a cracked solid by a contour integration computation via Gauss points. The SIF obtained results from extrapolation and G−θ methods will be compared to an analytical solution in a particular case. To illustrate the influence of the meshing kind and the size of integration contour position simulations are presented and analyzed.

Keywords: crack tip, SIF, finite element method, concentration technique, displacement extrapolation, aluminum alloy 7075-T6 and 2024-T3, energy release rate G, G-θ method, Gauss point numerical integration

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

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Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: continuous query processing, dynamic database, moving object, skyline queries

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Authors: Kaoutar Ben Azzou, Hanaa Talei

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Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

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Authors: Mohamed S. Negm, Waleed S. Mandour

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The present study aims primarily at investigating words of peace (lexemes of peace) in the formal speeches of the Egyptian president Abdulfattah El-Sisi in a two-year span of time, from 2018 to 2019. This paper attempts to shed light not only on the contextual use of the antonyms, war and peace, but also it underpins quantitative analysis through the current methods of corpus linguistics. As such, the researchers have deployed a corpus-based approach in collecting, encoding, and processing 30 presidential speeches over the stated period (23,411 words and 25,541 tokens in total). Further, semantic fields and collocational networkzs are identified and compared statistically. Results have shown a significant propensity of adopting peace, including its relevant collocation network, textually and therefore, ideationally, at the expense of war concept which in most cases surfaces euphemistically through the noun conflict. The president has not justified the action of war with an honorable cause or a valid reason. Such results, so far, have indicated a positive sociopolitical mindset the Egyptian president possesses and moreover, reveal national and international fair dealing on arising issues.

Keywords: CADS, collocation network, corpus linguistics, critical discourse analysis

Procedia PDF Downloads 155

Authors: Ramón Aparicio-García, Gustavo Juárez Gracia, Jesús Álvarez Cedillo

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A research line of the computer science that involve the study of the Human-Computer Interaction (HCI), which search to recognize and interpret the user intent by the storage and the subsequent analysis of the electrical signals of the brain, for using them in the control of electronic devices. On the other hand, the affective computing research applies the human emotions in the HCI process helping to reduce the user frustration. This paper shows the results obtained during the hardware and software development of a Brain Computer Interface (BCI) capable of recognizing the human emotions through the association of the brain electrical activity patterns. The hardware involves the sensing stage and analogical-digital conversion. The interface software involves algorithms for pre-processing of the signal in time and frequency analysis and the classification of patterns associated with the electrical brain activity. The methods used for the analysis and classification of the signal have been tested separately, by using a database that is accessible to the public, besides to a comparison among classifiers in order to know the best performing.

Keywords: affective computing, interface, brain, intelligent interaction

Procedia PDF Downloads 388

Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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Authors: Mansour Hadji Hosseinlou, Alireza Mahdavi

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Transportation is one of any society's needs which have developed after improving economically and socially and is one of civilization symbols today. Although it is so useful for human, it leads to many serious harms and injuries. The development of communication system and building new roads has resulted in increasing the rate of accidents; therefore, in practice, this increasing rate has decreased the advantages of transportation. Traffic accidents are one of the causes of death, serious financial and bodily harms and its significant social, economic and cultural consequences threatens the societies seriously. Iran's ground transportation system is one of the most eventful transportation systems in the world and mortality rate and financial harms cost too much for the country in national aspect. Therefore, we have presented a data collection by referring to recorded statistics of the accidents occurred in freeways from 2013 to 2015. These statistics are recorded in different related databases, generally police and road transportation system. The data is separated and arranged in tables and after preparing, processing and prioritizing the factors, the achieved collection is presented to the departments, managers and researchers to help them suggest practical solutions.

Keywords: freeways’ accidents, humane causes, death, tiredness, drowsiness

Procedia PDF Downloads 193

Authors: Godswill Nwabuisi Osuafor, Sonto Maria Maputle

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Background: Abounding studies found that religiosity and social factors modulate alcohol use among university students. However, there is a scarcity of empirical studies examining the protective effects of religiosity and other social factors on alcohol use and abuse in South African universities. The aim of this study was therefore to assess the protective effects of religiosity and roles of social factors on alcohol use among university students. Methodology: A survey on the use of alcohol among 416 university students was conducted using structured questionnaire in 2014. Data were sourced on religiosity and contextual variables. Students were classified as practicing intrinsic religiosity or extrinsic religiosity based on the response to the measures of religiosity. Descriptive, chi square and binary logistic analyses were used in processing the data. Result: Results revealed that alcohol use was associated with religiosity, religion, sex, family history of alcohol use and experimenting with alcohol. Reporting alcohol abuse was significantly predicted by sex, family history of alcohol use and experimenting with alcohol. Religiosity mediated lower alcohol use whereas family history of alcohol use and experimenting with alcohol promoted alcohol use and abuse. Conclusion: Families, religious groups and societal factors may be the specific niches for intervention on alcohol use among university students.

Keywords: religiosity, alcohol use, protective factors, university students

Procedia PDF Downloads 397

Authors: Mostafa Rezaee Saraji, Ali Keshavarz Panahi

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In this work, the processing steps for producing alumina parts using powder injection molding (PIM) technique and nano-powder were investigated and the thermal conductivity and flexural strength of samples were determined as a function of sintering temperature and holding time. In the first step, the feedstock with 58 vol. % of alumina nano-powder with average particle size of 100nm was prepared using Extrumixing method to obtain appropriate homogeneity. This feedstock was injection molded into the two cavity mold with rectangular shape. After injection molding step, thermal and solvent debinding methods were used for debinding of molded samples and then these debinded samples were sintered in different sintering temperatures and holding times. From the results, it was found that the flexural strength and thermal conductivity of samples increased by increasing sintering temperature and holding time; in sintering temperature of 1600ºC and holding time of 5h, the flexural strength and thermal conductivity of sintered samples reached to maximum values of 488MPa and 40.8 W/mK, respectively.

Keywords: alumina nano-powder, thermal conductivity, flexural strength, powder injection molding

Procedia PDF Downloads 329

Authors: Ali Bayati, Jamileh Azarnoush

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities shows one of the large challenges in consumption sources management. Nowadays, everyone considered about the consumption of fossil fuels and also Reduction of consumption civil energy in megacities that play a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming and damage ozone layer. In the construction industry, we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials and the adaptation with the environment is critical. Otherwise, the isolation should be use and mention in the long term. Accordingly, in this article we investigates the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: building design, construction masonry, insulation, sustainable construction

Procedia PDF Downloads 540

Authors: Alireza Ansariyar, Mansoureh Jeihani

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Light Detection and Ranging (LiDAR) sensors are capable of recording traffic data including the number of passing vehicles and bicyclists, the speed of vehicles and bicyclists, and the number of conflicts among both road users. In order to collect real-time traffic data and investigate the safety of different road users, a LiDAR sensor was installed at Cold Spring Ln – Hillen Rd intersection in Baltimore City. The frequency and severity of collected real-time conflicts were analyzed and the results highlighted that 122 conflicts were recorded over a 10-month time interval from May 2022 to February 2023. By using an innovative image-processing algorithm, a new safety Measure of Effectiveness (MOE) was proposed to recognize the critical zones for bicyclists entering each zone. Considering the trajectory of conflicts, the results of the analysis demonstrated that conflicts in the northern approach (zone N) are more frequent and severe. Additionally, sunny weather is more likely to cause severe vehicle-bike conflicts.

Keywords: LiDAR sensor, post encroachment time threshold (PET), vehicle-bike conflicts, a measure of effectiveness (MOE), weather condition

Procedia PDF Downloads 236

Authors: Malaiphan Pansap, Surasit Vithayarat

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The purpose of this study was to study the relationship between internal organization communications’ effectiveness and employee’s performance of Faculty of Management Science, Suan Sunandha Rajabhat University. Study on solutions of communication were carried out within the organization. Questionnaire was used to collect information from 136 people of staff and instructor and data were analyzed by using frequency, percentage, mean and standard deviation and then data processing statistic programs. The result found that organization communication that affects their employee’s performance is sender which lack the skills for speaking and writing to convince audiences ready before taking message and the message which organizations are not always informed. The employees believe the behavior of good organization communication has a positive impact on the development of organization because the employees feel involved and be a part of the organization, by the cooperation in working to achieve the goal, the employees can work in the same direction and meet goal quickly.

Keywords: employee’s performance, faculty of management science, internal organization communications’ effectiveness, management accounting, Suan Sunandha Rajabhat University

Procedia PDF Downloads 239

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

Procedia PDF Downloads 332

Authors: Valeria Corinaldesi, Nicola Generosi, Daniele Berdini

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In this study, wood waste from processing by-products was used by replacing natural sand for producing bio-based lightweight mortars. Manufacturers of wood products and furniture usually generate sawdust and pieces of side-cuts. These are produced by cutting, drilling, and milling operations as well. Three different percentages of substitution of quartz sand were tried: 2.5%, 5%, and 10% by volume. Wood by-products were pre-soaked in calcium hydroxide aqueous solution in order to obtain wood mineralization to avoid undesirable effects on the bio-based building materials. Bio-based mortars were characterized by means of compression and bending tests, free drying shrinkage tests, resistance to water vapour permeability, water capillary absorption, and, finally, thermal conductivity measurements. Results obtained showed that a maximum dosage of 5% wood by-products should be used in order to avoid an excessive loss of bio-based mortar mechanical strength. On the other hand, by adding the proper dosage of water-reducing admixture, adequate mechanical performance can be achieved even with 10% wood waste addition.

Keywords: bio-based mortar, energy efficiency, lightweight mortar, thermal insulation, wood waste

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 146

Authors: Mokhtar Nikgoo

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Definition of Concrete and Concreting: Concrete (in French: Béton) in a broad sense is any substance or combination that consists of a sticky substance with the property of cementation. In general, concrete refers to concrete made by Portland cement, which is produced by mixing fine and coarse aggregates, Portland cement and water. After enough time, this mixture turns into a stone-like substance. During the hardening or processing of the concrete, cement is chemically combined with water to form strong crystals that bind the aggregates together, a process called hydration. During this process, significant heat is released called hydration heat. Additionally, concrete shrinks slightly, especially as excess water evaporates, a phenomenon known as drying shrinkage. The process of hardening and the gradual increase in concrete strength that occurs with it does not end suddenly unless it is artificially interrupted. Instead, it decreases more over long periods of time, although, in practical applications, concrete is usually set after 28 days and is considered at full design strength. Concrete may be made from different types of cement as well as pozzolans, furnace slag, additives, additives, polymers, fibers, etc. It may also be used in the way it is made, heating, water vapor, autoclave, vacuum, hydraulic pressures and various condensers.

Keywords: concrete, RCC, batching, cement, Pozzolan, mixing plan

Procedia PDF Downloads 98

Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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Authors: Babar Khan, Wang Zhijie

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Machine Vision has been playing a significant role in Industrial Automation, to imitate the wide variety of human functions, providing improved safety, reduced labour cost, the elimination of human error and/or subjective judgments, and the creation of timely statistical product data. Despite the intensive research, there have not been any attempts to classify fabric prints based on printed texture and colour, most of the researches so far encompasses only black and white or grey scale images. We proposed a biologically inspired processing architecture to classify fabrics w.r.t. the fabric print texture and colour. We created a texture descriptor based on the HMAX model for machine vision, and incorporated colour descriptor based on opponent colour channels simulating the single opponent and double opponent neuronal function of the brain. We found that our algorithm not only outperformed the original HMAX algorithm on classification of fabric print texture and colour, but we also achieved a recognition accuracy of 85-100% on different colour and different texture fabric.

Keywords: automatic classification, texture descriptor, colour descriptor, opponent colour channel

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Authors: Lamzira Ebralidze, Aleksandre Tsertsvadze, Dali Berashvili, Aliosha Bakuridze

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Nowadays, there is an increasing demand for biologically active substances from vegetable, animal, and mineral resources. In terms of the use of natural compounds, pharmaceutical, cosmetic, and nutrition industry has big interest. The biggest drawback of conventional extraction methods is the need to use a large volume of organic extragents. The removal of the organic solvent is a multi-stage process. And their absolute removal cannot be achieved, and they still appear in the final product as impurities. A large amount of waste containing organic solvent damages not only human health but also has the harmful effects of the environment. Accordingly, researchers are focused on improving the extraction methods, which aims to minimize the use of organic solvents and energy sources, using alternate solvents and renewable raw materials. In this context, green extraction principles were formed. Green Extraction is a need of today’s environment. Green Extraction is the concept, and it totally corresponds to the challenges of the 21st century. The extraction of biologically active compounds based on green extraction principles is vital from the view of preservation and maintaining biodiversity. Novel technologies of green extraction are known, such as "cold methods" because during the extraction process, the temperature is relatively lower, and it doesn’t have a negative impact on the stability of plant compounds. Novel technologies provide great opportunities to reduce or replace the use of organic toxic solvents, the efficiency of the process, enhance excretion yield, and improve the quality of the final product. The objective of the research is the development of green technologies of flavonoids containing preparations. Methodology: At the first stage of the research, flavonoids containing preparations (Tincture Herba Leonuri, flamine, rutine) were prepared based on conventional extraction methods: maceration, bismaceration, percolation, repercolation. At the same time, the same preparations were prepared based on green technologies, microwave-assisted, UV extraction methods. Product quality characteristics were evaluated by pharmacopeia methods. At the next stage of the research technological - economic characteristics and cost efficiency of products prepared based on conventional and novel technologies were determined. For the extraction of flavonoids, water is used as extragent. Surface-active substances are used as co-solvent in order to reduce surface tension, which significantly increases the solubility of polyphenols in water. Different concentrations of water-glycerol mixture, cyclodextrin, ionic solvent were used for the extraction process. In vitro antioxidant activity will be studied by the spectrophotometric method, using DPPH (2,2-diphenyl-1- picrylhydrazyl) as an antioxidant assay. The advantage of green extraction methods is also the possibility of obtaining higher yield in case of low temperature, limitation extraction process of undesirable compounds. That is especially important for the extraction of thermosensitive compounds and maintaining their stability.

Keywords: extraction, green technologies, natural resources, flavonoids

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Authors: Bernard Bladergroen, David Vlotman, Bradley Cerff

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The agricultural sector is one which requires and consumes large amounts of water globally. Commercial wine production, in particular, uses extensive volumes of fresh water and generates significant volumes of wastewater through various processes. The wastewater produced by wineries typically exhibits elevated levels of chemical oxygen demand (COD), total suspended solids (TSS), total dissolved solids (TDS), acidic pH and varying salinity and nutrient contents. This study investigates the performance of a shear-enhanced flotation separation (SEFS) pilot plant as a primary treatment stage during winery wastewater processing by modifying a conventional Dissolved Air Flotation (DAF) system. The SEFS pilot plant achieved a 99% reduction in both turbidity and TSS in comparison to the 97% achieved with the conventional DAF system. The COD was reduced by 66% and 51% for the SEFS and DAF systems, respectively. SEFS shows the advantages of hydrodynamic shear to enhance the coagulation and subsequent flocculation processes with a significant reduction of coagulant and flocculant (36% and 31%, respectively).

Keywords: shear enhanced flotation, suspended solids, primary wastewater treatment, zeta potential

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Authors: Ashraf Ward

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Effect of calving interval on 305 day milk yield for first three lactations was studied in order to increase efficiency of selection schemes and to more efficiently manage Holstein cows that have been raised on small farms in Libya. Results obtained by processing data of 1476 cows, managed in 935 small scale farms, pointed out that current calving interval significantly affects on milk production for first three lactations (p<0.05). Preceding calving interval affected 305 day milk yield (p<0.05) in second lactation only. Linear regression model accounted for 20-25 % of the total variance of 305 day milk yield. Extension of calving interval over 420, 430, 450 days for first, second and third lactations respectively, did not increase milk production when converted to 305 day lactation. Stochastic relations between calving interval and calving age and month are moderated. Values of Pierson’s correlation coefficients ranged 0.38 to 0.69. Adjustment of milk production in order to reduce effect of calving interval on total phenotypic variance of milk yield is valid for first lactation only. Adjustment of 305 day milk yield for second and third lactations in order to reduce effects of factors “calving age and month” brings about, at the same time, elimination of calving interval effect.

Keywords: milk yield, Holstien, non genetic, calving

Procedia PDF Downloads 417

Authors: W. S. Mohamed, A. A. Hammam

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Sandy soils under arid and semi-arid conditions are characterized by poor physical and biochemical properties such as low water retention, rapid organic matter decomposition, low nutrients use efficiency, and limited crop productivity. Addition of organic amendments is crucial to develop soil properties and consequently enhance nutrients use efficiency and lessen organic carbon decomposition. Two years field experiments were developed to investigate the feasibility of using poultry manure and its derived biochar integrated with different levels of N fertilizer as a soil amendment for newly reclaimed sandy soils in Western Desert of El-Minia Governorate, Egypt. Results of this research revealed that poultry manure and its derived biochar addition induced pronounced effects on soil moisture content at saturation point, field capacity (FC) and consequently available water. Data showed that application of poultry manure (PM) or PM-derived biochar (PMB) in combination with inorganic N levels had caused significant changes on a range of the investigated sandy soil biochemical properties including pH, EC, mineral N, dissolved organic carbon (DOC), dissolved organic N (DON) and quotient DOC/DON. Overall, the impact of PMB on soil physical properties was detected to be superior than the impact of PM, regardless the inorganic N levels. In addition, the obtained results showed that PM and PM application had the capacity to stimulate vigorous growth, nutritional status, production levels of wheat and sorghum, and to increase soil organic matter content and N uptake and recovery compared to control. By contrast, comparing between PM and PMB at different levels of inorganic N, the obtained results showed higher relative increases in both grain and straw yields of wheat in plots treated with PM than in those treated with PMB. The interesting feature of this research is that the biochar derived from PM increased treated sandy soil organic carbon (SOC) 1.75 times more than soil treated with PM itself at the end of cropping seasons albeit double-applied amount of PM. This was attributed to the higher carbon stability of biochar treated sandy soils increasing soil persistence for carbon decomposition in comparison with PM labile carbon. It could be concluded that organic manures applied to sandy soils under arid and semi-arid conditions are subjected to high decomposition and mineralization rates through crop seasons. Biochar derived from organic wastes considers as a source of stable carbon and could be very hopeful choice for substituting easily decomposable organic manures under arid conditions. Therefore, sustainable agriculture and productivity in newly reclaimed sandy soils desire one high rate addition of biochar derived from organic manures instead of frequent addition of such organic amendments.

Keywords: biochar, dissolved organic carbon, N-uptake, poultry, sandy soil

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Authors: P. Senthil Kumari

Abstract:

Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

Procedia PDF Downloads 508

Authors: Julien Baillet

Abstract:

In light of 30 years of scientific research, InCorporer Method was created in 2019 as a new approach to heal traumatic, developmental, and dissociative injuries. Following natural nervous system functions, InCorporer aims to heal, develop, and update the different defensive mammalian subsystems: fight, flight, freeze, feign death, cry for help, & energy regulator. The dimensions taken into account are: (i) Heal the traumatic injuries who are still bleeding, (ii) Develop the systems that never received the security, attention, and affection they needed. (iii) Update the parts that stayed stuck in the past, ignoring for too long that they are out of danger now. Through the Present Part and its caregiving skills, InCorporer method enables a balanced, soothed, and collaborative personality system. To be as integrative as possible, InCorporer method has been designed according to several fields of research, such as structural dissociation theory, attachment theory, and information processing theory. In this paper, the author presents how the internal caregiver is developed and trained to heal all the different parts/subsystems of our clients through mindful attention and reflex movement integration.

Keywords: PTSD, attachment, dissociation, part work

Procedia PDF Downloads 77

Authors: Reyhan Özdoğan, Özgür Ceylan, Mehmet Arif Kaya, Mithat Çelebi

Abstract:

Food packaging is important for the food industry. Bioplastics have been used as food packaging materials. According to the European Bioplastics organization, bioplastics can be defined as plastics based on renewable resources (bio-based) or as plastics which are biodegradable and/or compostable. Poly(lactic acid) (PLA) has an industrially importance of bioplastic polymers. PLA is a family of biodegradable thermoplastic polyester made from renewable resources. It is produced by conversion of corn, or other carbohydrate sources, into dextrose, followed by fermentation into lactic acid through direct polycondensation of lactic acid monomers or through ring-opening polymerization of lactide. The processing possibilities of this transparent material are very wide, ranging from injection molding and extrusion over cast film extrusion to blow molding and thermoforming. In this study, PLA films were prepared by solution casting method. PLAs which are different molecular weights were plasticized with glycerol and the morphology of films was monitored by optical microscopy. Properties of mechanical and film of PLA were researched with the mechanical testing machine.

Keywords: biodegradable, bioplastics, morphology, solution casting, poly(lactic acid)

Procedia PDF Downloads 378