Search results for: DNA extraction methods

Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Chen Wang, Qiuxiao Chen

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With the advent of the information age and the era of big data, urban planning research is no longer satisfied with the analysis and application of traditional data. Because of the limitations of traditional urban commercial center system research, big data provides new opportunities for urban research. Therefore, based on the quantitative evaluation method of big data, the commercial center system of the main city of Hangzhou is analyzed and evaluated, and the scale and hierarchical structure characteristics of the urban commercial center system are studied. In order to make up for the shortcomings of the existing POI extraction method, it proposes a POI extraction method based on adaptive adjustment of search window, which can accurately and efficiently extract the POI data of commercial business in the main city of Hangzhou. Through the visualization and nuclear density analysis of the extracted Point of Interest (POI) data, the current situation of the commercial center system in the main city of Hangzhou is evaluated. Then it compares with the commercial center system structure of 'Hangzhou City Master Plan (2001-2020)', analyzes the problems existing in the planned urban commercial center system, and provides corresponding suggestions and optimization strategy for the optimization of the planning of Hangzhou commercial center system. Then get the following conclusions: The status quo of the commercial center system in the main city of Hangzhou presents a first-level main center, a two-level main center, three third-level sub-centers, and multiple community-level business centers. Generally speaking, the construction of the main center in the commercial center system is basically up to standard, and there is still a big gap in the construction of the sub-center and the regional-level commercial center, further construction is needed. Therefore, it proposes an optimized hierarchical functional system, organizes commercial centers in an orderly manner; strengthens the central radiation to drive surrounding areas; implements the construction guidance of the center, effectively promotes the development of group formation and further improves the commercial center system structure of the main city of Hangzhou.

Keywords: business center system, business format, main city of Hangzhou, POI extraction method

Procedia PDF Downloads 128

Authors: Zin Mar Lwin

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Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

Procedia PDF Downloads 266

Authors: Nitin Rajan, Kashif Shakeel, Shashank Tiwari, Shachan Sagar

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Background: - Aegle Marmelos (Bael) leaf extract is taken twice daily to treat ophthalmia, ulcers, and intestinal worms, among other ailments. Poultice made from bael leaf is used in the treatment of eye conditions. The leaf juice has a variety of therapeutic applications, with the most notable being the treatment of diabetes. Fenugreek is used to cure red spots around the eyes, as well as to soften the throat and chest and to give relief from coughing. The use of this plant in the form of infusion, powder, pomade, and decoction has been extremely popular in Iranian traditional medicine. The plant may be used to wash one's vaginal linings. This plant is used as an emollient in the lack of appetite, treatment of pellagra, and gastrointestinal problems, as well as a general tonic. Calendula officinalis leaves are used to treat varicose veins on the outside of the body by infusing them. In Europe, the leaves are diaphoretic and resolvent in nature, while the blooms are employed as an emmenagogue and antispasmodic stimulant in Canada and the United States. The flowers were decocted and served as a posset drink when smallpox and measles were common in England, and the fresh juice was used to treat jaundice. Objective: - This study is done to compare the physicochemical parameter of the alcoholic extract of the leaves of Aegle Marmelos, Calendula Officinalis, and Fenugreek. Materials and Methods: Extraction and Isolation of Aegle Marmelos, Calendula Officinalis, Fenugreek, were done. Preliminary phytochemical study for alkaloids, cardiac glycosides, flavonoids, glycosides, phenols, resins, saponins, steroids, tannins, terpenoids of the extract was done individual by using the standard procedure. Result: - The phytochemical screening of Aegle Marmelos, Calendula Officinalis, and Fenugreek shows the presence of alkaloids, carbohydrates, total phenolics, total flavonoids, tannins, saponins gum. Conclusion: - In this study, we have found that crude aqueous and organic solvent extracts of Aegle Marmelos, Calendula Officinalis, and Fenugreek leaves contain some important bioactive compounds and it justifies their use in the traditional medicines for the treatment of different diseases.

Keywords: Aegle Marmelos, Calendula Officinalis, Fenugreek, physiochemical parameter

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Authors: Mouhamadou Dosso

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This paper presents methods of spectral dichotomy of a matrix which compute spectral projectors on the subspace associated with the eigenvalues external to the parabolas described by a general equation. These methods are modifications of the one proposed in [A. N. Malyshev and M. Sadkane, SIAM J. MATRIX ANAL. APPL. 18 (2), 265-278, 1997] which uses the spectral dichotomy method of a matrix with respect to the imaginary axis. Theoretical and algorithmic aspects of the methods are developed. Numerical results obtained by applying methods presented on matrices are reported.

Keywords: spectral dichotomy method, spectral projector, eigensubspaces, eigenvalue

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Authors: Ene Rosemary Ndidiamaka, Nwangwu Florence Chinyere

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The physiochemical properties of the melon seed oil was studied to determine its potentials as viable feed stock for biodisel production. The melon seed was extracted by solvent extraction using n-hexane as the extracting solvent. In this research, methanol was the alcohol used in the production of biodiesel, although alcohols like ethanol, propanol may also be used. Sodium hydroxide was employed for the catalysis. The melon seed oil was characterized for specific gravity, pH, ash content, iodine value, acid value, saponification value, peroxide value, free fatty acid value, flash point, viscosity, and refractive index using standard methods. The melon seed oil had very high oil content. Specific gravity and flash point of the oil is satisfactory. However, moisture content of the oil exceeded the stipulated ASRTM standard for biodiesel production. The overall results indicates that the melon seed oil is suitable for single-stage transesterification process to biodiesel production.

Keywords: biodiesel, catalyst, melon seed, transesterification

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Authors: Lorena Coelho, David Ramada, Catarina Nobre, Joaquim Gaião, Juliana Duarte

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The development of processes that allows the valorization of waste and by-products generated by industries is crucial to promote symbiotic relationships between different sectors and is mandatory to “close the loop” in the circular economy paradigm. In recent years, by-products and waste from agro-food and forestry sector have attracted attention due to their potential application and technical characteristics. The extraction of bio-based active compounds to be reused is in line with the circular bioeconomy concept trends, combining the use of renewable resources with the process’s circularity, aiming the waste reduction and encouraging reuse and recycling. Among different types of bio-based materials, which are being explored and can be extracted, proteins fractions are becoming an attractive new raw material. Within this context, BioTrace4Leather project, a collaboration between two Technological Centres – CeNTI and CTIC, and a company of Tanning and Finishing of Leather – Curtumes Aveneda, aims to develop innovative and biologically sustainable solutions for leather industry and accomplish the market circularity trends. Specifically, it aims to the valorisation of waste and by-products from the tannery industry through proteins extraction and the development of an innovative and biologically sustainable materials. The achieved results show that keratin, gelatine, and collagen fractions can be successfully extracted from hair and leather bovine waste. These products could be reintegrated into the industrial manufacturing process to attain innovative and functional textile and leather substrates. ACKNOWLEDGEMENT This work has been developed under BioTrace4Leather scope, a project co-funded by Operational Program for Competitiveness and Internationalization (COMPETE) of PORTUGAL2020, through the European Regional Development Fund (ERDF), under grant agreement Nº POCI-01-0247-FEDER-039867.

Keywords: leather by-products, circular economy, sustainability, protein fractions

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Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

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Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Tarikayehu Amanuel, Abraham Mohammed

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The production of biodiesel from waste materials is becoming an increasingly important research area in the field of renewable energy. One potential waste material source is avocado, a fruit with a large seed and peel that are typically discarded after consumption. This research aims to investigate the feasibility of using avocado waste as a feedstock for the production of biodiesel. The study focuses on extracting oil from the waste material using the transesterification technique and then characterizing the properties of oil to determine its suitability for conversion to biodiesel. The study was conducted experimentally, and a maximum oil yield of 11.583% (150g of oil produced from 1.295kg of avocado waste powder) was obtained from avocado waste powder at an extraction time of 4hr. An 87% fatty acid methyl ester (biodiesel) conversion was also obtained using a methanol/oil ratio of 6:1, 1.3g NaOH, reaction time 60min, and 65°C reaction temperature. Furthermore, from 145 ml of avocado waste oil, 126.15 ml of biodiesel was produced, indicating a high percentage of conversion (87%). Conclusively, the produced biodiesel showed comparable physical and chemical characteristics to that of standard biodiesel samples considered for the study. The results of this research could help to identify a new source of biofuel production while also addressing the issue of waste disposal in the food industry.

Keywords: biodiesel, avocado, transesterification, soxhlet extraction

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Authors: Musoke Ivan, Birungi Racheal

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The construction trend is characterized by increased use of modern methods yet traditional methods are cheaper in terms of costs, in addition to the benefits it offers to the construction sector, like providing more jobs that could have been worked with the intensive machines. The purpose of this research was to assess the influence of using Traditional methods of construction (TMC) on the costs and quality of building structures and determine the different ways. Traditional methods of construction (TMC) can be applicable and integrated into the construction trend, and propose ways how this can be a success. The study adopted a quantitative method approach targeting various construction professionals like Architects, Quantity surveyors, Engineers, and Construction Managers. Questionnaires and analyses of literature were used to obtain research data and findings. Simple random sampling was used to select 40 construction professionals to which questionnaires were administered. The data was then analyzed using Microsoft Excel. The findings of the research indicate that Traditional methods of construction (TMCs) in Uganda are cheaper in terms of costs, but the quality is still low. This is attributed to a lack of skilled labour and efficient supervision while undertaking tasks leading to low quality. The study identifies strategies that would improve Traditional methods of construction (TMC), which include the employment of skilled manpower and effective supervision. It also identifies the need by stakeholders like the government, clients, and professionals to appreciate Traditional methods of construction (TMCs) and allow for a levelled ground for Traditional Methods of Construction and Modern methods of construction (MMCs).

Keywords: traditional methods of construction, integration, cost, quality

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

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Authors: Amal Machtalay

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In this survey, we aim to review the rapidly growing literature on numerical methods to solve different forms of mean field problems, namely mean field games (MFG), mean field controls (MFC), potential MFGs, and master equations, as well as their corresponding recent applications. Here, we distinguish two families of numerical methods: iterative methods based on mesh generation and those called mesh-free, normally related to neural networking and learning frameworks.

Keywords: mean-field games, numerical schemes, partial differential equations, complex systems, machine learning

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Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

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The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

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Authors: Kenia Martínez, Geniel Talavera, Juan Alonso

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Moringa oleifera is a plant containing many nutrients that are mostly concentrated within the leaves. Commonly, the separation process of these nutrients involves solid-liquid extraction followed by evaporation and drying to obtain a concentrated extract, which is rich in proteins, vitamins, carbohydrates, and other essential nutrients that can be used in the food industry. In this work, three drying methods were used, which involved very different temperature and pressure conditions, to evaluate the effect of each method on the vitamin C content and the antioxidant efficiency of the extracts. Solid-liquid extractions of Moringa leaf (LE) were carried out by employing an ethanol solution (35% v/v) at 50 °C for 2 hours. The resulting extracts were then dried i) in a convective oven (CO) at 100 °C and at an atmospheric pressure of 750 mbar for 8 hours, ii) in a vacuum evaporator (VE) at 50 °C and at 300 mbar for 2 hours, and iii) in a freeze-drier (FD) at -40 °C and at 0.050 mbar for 36 hours. The antioxidant capacity (EC₅₀, mg solids/g DPPH) of the dry solids was calculated by the free radical inhibition method employing DPPH˙ at 517 nm, resulting in a value of 2902.5 ± 14.8 for LE, 3433.1 ± 85.2 for FD, 3980.1 ± 37.2 for VE, and 8123.5 ± 263.3 for CO. The calculated antioxidant efficiency (AE, g DPPH/(mg solids·min)) was 2.920 × 10^-5 for LE, 2.884 × 10^-5 for FD, 2.512 × 10^-5 for VE, and 1.009 × 10^-5 for CO. Further, the content of vitamin C (mg/L) determined by HPLC was 59.0 ± 0.3 for LE, 49.7 ± 0.6 for FD, 45.0 ± 0.4 for VE, and 23.6 ± 0.7 for CO. The results indicate that the convective drying preserves vitamin C and antioxidant efficiency to 40% and 34% of the initial value, respectively, while vacuum drying to 76% and 86%, and freeze-drying to 84% and 98%, respectively.

Keywords: antioxidant efficiency, convective drying, freeze-drying, Moringa oleifera, vacuum drying, vitamin C content

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Authors: Manish Kumar Thakur, Subrata Kumar Ghosh

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Various types of particles found in lubricant may be characterized by their fractal dimension. Some of the available methods are: yard-stick method or structured walk method, box-counting method. This paper presents a review of the developments and progress in fractal dimension computing methods as applied to characteristics the surface of wear particles. An overview of these methods, their implementation, their advantages and their limits is also present here. It has been accepted that wear particles contain major information about wear and friction of materials. Morphological analysis of wear particles from a lubricant is a very effective way for machine condition monitoring. Fractal dimension methods are used to characterize the morphology of the found particles. It is very useful in the analysis of complexity of irregular substance. The aim of this review is to bring together the fractal methods applicable for wear particles.

Keywords: fractal dimension, morphological analysis, wear, wear particles

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Authors: S. U. Kunya, S. Abdulkadir, M. A. Anas, L. Z. Adam

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Procurement methods is described as systems of contractual arrangements used by the contractor in order to secure the design and construction services based on the stipulated cost and within the required time and quality. Despite that, major projects in the Nigerian construction industry failed because of wrong procurement methods with major consequences leads to cost overrun which needs to find lasting solution. The aim of the study is to evaluate the influence of procurement methods on cost performance of building projects in Gombe State, Nigeria. Study adopts descriptive and explorative design approach. Data were collected through administering of one hundred questionnaire using convenient sampling techniques. Data analyses using percentages, mean value and Anova analysis. Major finding show that more than fifty percent (50%) of procurement methods available are mainly utilized in the study area and the top procurement methods that have high impacts on cost performance as compare with the other methods is project management and direct labour procurement methods. The results of hypothesis’ tests with pvalue 0.12 and 0.07 validated that there was no significant variation in the perception of stakeholders’ on the impacts of procurements methods on cost performance. Therefore, the study concluded that projects management and direct labour are the most appropriate procurement methods that will ensure successful completion of project at stipulated cost in building projects.

Keywords: cost, effects, performance, procurement, projects

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Authors: Zaida Perez-Bassart, Berta Polanco-Estibalez, Maria Jose Fabra, Amparo Lopez-Rubio, Antonio Martinez-Abad

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Mushroom production has enormously increased in recent years, not only as food products but also for applications in pharmaceuticals, nutraceuticals, and cosmetics. Consequently, interest in its chemical composition, nutritional value, and therapeutic properties has also increased. Fungi are rich in bioactive compounds such as polysaccharides, polyphenols, glycopeptides, and ergosterol, of great medicinal value, but within polysaccharides, β-glucans are the most prominent molecules. They are formed by D-glucose monomers, linked by β-glucosidic bonds β-(1,3) with side chains linked by β-(1,6) bonds. The number and position of the β-(1,6) branches strongly influence the arrangement of the tertiary structure, which, together with the molecular weight, determine the different attributed bioactivities (immunostimulating, anticancer, antimicrobial, prebiotic, etc.) and physico-chemical properties (solubility, bioaccessibility, viscosity or emulsifying). On the other hand, there is a growing interest in the study of fungi as an alternative source of chitin obtained from the by-products of the fungal industry. In this work, a cascade extraction process using aqueous neutral and alkaline treatments was carried out for Grifola frondosa and Lentinula edodes, and the compositional analysis and functional properties of each fraction were characterized. Interestingly, the first fraction obtained by using aqueous treatment at room temperature was the richest in polysaccharides, proteins, and polyphenols, thus obtaining a greater antioxidant capacity than in the other fractions. In contrast, the fractions obtained by alkaline treatments showed a higher degree of β-glucans purification compared to aqueous extractions but a lower extraction yield. Results revealed the different structural recalcitrance of β-glucans, preferentially linked to proteins or chitin depending on the fungus type, which had a direct impact on the functionalities and bioactivities of each fraction.

Keywords: fungi, mushroom, β-glucans, chitin

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.

Keywords: EEG, epilepsy, phase correlation, seizure

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Authors: U. P. L. Wijayarathne, P. W. Vidanage, H. K. D. Jayampath, K. W. P. M. Kothalawala

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Feasibility of utilizing Empty Bunch (EB) fibre, a solid waste of palm oil extraction process, as an adsorbent is analysed in this study. Empty bunch fibre is generated after the extraction of retained oil in the sterilized and threshed empty fruit bunches. Besides the numerous characteristics of EB fibre, which enable its utilization as a fuel, a bio-composite material, or mulch, EB fibre also shows exceptional characteristics of a good adsorbent. Fixed bed adsorption method is used to study the adsorptivity of EB fibre using a continuous adsorption column with Methyl-blue (1.13ppm) as the feed. Adsorptivity is assumed to be solely dependent on the bed porosity keeping other parameters (feed flow rate, bed height, bed diameter, and operating temperature) constant. Bed porosity is changed by means of compact ratio and the variation of the feed concentration is analysed using a photometric method. Break through curves are plotted at different porosity levels and optimum bed porosity is identified for a given feed stream. Feasibility of using the EB fibre as an inexpensive and an abundant adsorbent in wastewater treatment facilities, where the effluent colour reduction is adamant, is also discussed.

Keywords: adsorption, fixed bed, break through time, methylene blue, oil palm fibre

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Authors: Recep Karadag

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Natural dyeing had started since pre-historical times for dyeing of textile materials. The natural dyeing had continued to beginning of 20th century. At the end of 19th century some synthetic dyes were synthesized. Although development of dyeing technologies and methods, natural dyeing was not developed in recent years. Despite rapid advances of synthetic dyestuff industries, natural dye processes have not developed. Therefore natural dyeing was not competed against synthetic dyes. At the same time, it was very difficult that large quantities of coloured textile was dyed with natural dyes And it was very difficult to get reproducible results in the natural dyeing using classical and traditional processes. However, natural dyeing has used slightly in the textile handicraft up to now. It is very important view that re-using of natural dyes to create awareness in textiles in recent years. Natural dyes have got many awareness and sustainability properties. Natural dyes are more eco-friendly than synthetic dyes. A lot of natural dyes have got antioxidant, antibacterial, antimicrobial, antifungal and anti –UV properties. It had been known that were obtained limited numbers colours with natural dyes in the past. On the contrary, colour scale is too wide with natural dyes. Except fluorescent colours, numerous colours can be obtained with natural dyes. Fastnesses of dyed textiles with natural dyes are good that there are light, washing, rubbing, etc. The fastness values can be improved depend on dyeing processes. Thanks to these properties mass production can be made with natural dyes in textiles. Therefore fabric dyeing machine was designed. This machine is too suitable for natural dyeing and mass production. Also any dyeing machine can be modified for natural dyeing. Although dye extraction and dyeing are made separately in the traditional natural dyeing processes and these procedures are become by designed this machine. Firstly, colouring compounds are extracted from natural dye resources, then dyeing is made with extracted colouring compounds. The colouring compounds are moderately dissolved in water. Less water is used in the extraction of colouring compounds from dye resources and dyeing with this new technique on the contrary much quantity water needs to use for dissolve of the colouring compounds in the traditional dyeing. This dyeing technique is very useful method for mass productions with natural dyes in traditional natural dyeing that use less energy, less dye materials, less water, etc. than traditional natural dyeing techniques. In this work, cotton, silk, linen and wool fabrics were dyed with some natural dye plants by the technique. According to the analysis very good results were obtained by this new technique. These results are shown sustainability and awareness of natural dyes for textiles.

Keywords: antibacterial, antimicrobial, natural dyes, sustainability

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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Authors: Wided Bakari, Patrice Bellot, Omar Trigui, Mahmoud Neji

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This article constitutes an opening to think of the modeling and analysis of Arabic texts in the context of a question-answer system. It is a question of exceeding the traditional approaches focused on morphosyntactic approaches. Furthermore, we present a new approach that analyze a text in order to extract correct answers then transform it to logical predicates. In addition, we would like to represent different levels of information within a text to answer a question and choose an answer among several proposed. To do so, we transform both the question and the text into logical forms. Then, we try to recognize all entailment between them. The results of recognizing the entailment are a set of text sentences that can implicate the user’s question. Our work is now concentrated on an implementation step in order to develop a system of question-answering in Arabic using techniques to recognize textual implications. In this context, the extraction of text features (keywords, named entities, and relationships that link them) is actually considered the first step in our process of text modeling. The second one is the use of techniques of textual implication that relies on the notion of inference and logic representation to extract candidate answers. The last step is the extraction and selection of the desired answer.

Keywords: NLP, Arabic language, question-answering, recognition text entailment, logic forms

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Authors: Reza Mollapourasl, Majid Haghi

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In this study, we develop local meshfree methods known as radial basis function-generated finite difference (RBF-FD) method and Hermite finite difference (RBF-HFD) method to design stencil weights and spatial discretization for Helmholtz equation. The convergence and stability of schemes are investigated numerically in three dimensions with irregular shaped domain. These localized meshless methods incorporate the advantages of the RBF method, finite difference and Hermite finite difference methods to handle the ill-conditioning issue that often destroys the convergence rate of global RBF methods. Moreover, numerical illustrations show that the proposed localized RBF type methods are efficient and applicable for problems with complex geometries. The convergence and accuracy of both schemes are compared by solving a test problem.

Keywords: radial basis functions, Hermite finite difference, Helmholtz equation, stability

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Authors: Pilar Cornejo Ulloa, Guy Willems, Steffen Fieuws, Kim Quintelier, Wim Van Neer, Patrick Thevissen

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Dental age estimation can be performed both in living and deceased individuals. In anthropology, few studies have tested the reliability of dental age estimation methods complementary to the usually applied osteological methods. Objectives: In this study, destructive and non-destructive dental age estimation methods were applied on an archeological sample in order to compare them with the previously obtained anthropological age estimates. Materials and Methods: One hundred and thirty-four teeth from 24 individuals were analyzed using Kvaal, Kvaal and Solheim, Bang and Ramm, Lamendin, Gustafson, Maples, Dalitz and Johanson’s methods. Results: A high variability and wider age ranges than the ones previously obtained by the anthropologist could be observed. Destructive methods had a slightly higher agreement than the non-destructive. Discussion: Due to the heterogeneity of the sample and the lack of the real age at death, the obtained results were not representative, and it was not possible to suggest one dental age estimation method over another.

Keywords: archeology, dental age estimation, forensic anthropology, forensic dentistry

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Authors: B. Kabane, G. G. Redhi

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An ammonium based ionic liquid (methyltrioctylammonium chloride) [N_{8 8 8 1}] [Cl] was investigated as an extraction potential solvent for volatile organic solvents (in this regard, solutes), which includes alkenes, alkanes, ketones, alkynes, aromatic hydrocarbons, tetrahydrofuran (THF), alcohols, thiophene, water and acetonitrile based on the experimental activity coefficients at infinite THF measurements were conducted by the use of gas-liquid chromatography at four different temperatures (313.15 to 343.15) K. Experimental data of activity coefficients obtained across the examined temperatures were used in order to calculate the physicochemical properties at infinite dilution such as partial molar excess enthalpy, Gibbs free energy and entropy term. Capacity and selectivity data for selected petrochemical extraction problems (heptane/thiophene, heptane/benzene, cyclohaxane/cyclohexene, hexane/toluene, hexane/hexene) were computed from activity coefficients data and compared to the literature values with other ionic liquids. Evaluation of activity coefficients at infinite dilution expands the knowledge and provides a good understanding related to the interactions between the ionic liquid and the investigated compounds.

Keywords: separation, activity coefficients, methyltrioctylammonium chloride, ionic liquid, capacity

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Oluwasanmi Teniola, Abraham Adeleke, Ademola Ibitoye, Moshood Shitu

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To establish an economical and efficient process for the recovery of gold metal from refractory gold ore obtained from Esperando axis of Osun state Nigeria, the adsorption of gold (III) from aqua reqia leached solution of the ore using bagasse nanoparticles has been studied under various experimental variables using batch technique. The extraction percentage of gold (III) on the prepared bagasse nanoparticles was determined from its distribution coefficients as a function of solution pH, contact time, adsorbent, adsorbate concentrations, and temperature. The rate of adsorption of gold (III) on the prepared bagasse nanoparticles is dependent on pH, metal concentration, amount of adsorbate, stirring rate, and temperature. The adsorption data obtained fit into the Langmuir and Freundlich equations. Three different temperatures were used to determine the thermodynamic parameters of the adsorption of gold (III) on bagasse nanoparticles. The heat of adsorption was measured to be a positive value ΔHo = +51.23kJ/mol, which serves as an indication that the adsorption of gold (III) on bagasse nanoparticles is endothermic. Also, the negative value of ΔGo = -0.6205 kJ/mol at 318K shows the spontaneity of the process. As the temperature was increased, the value of ΔGo becomes more negative, indicating that an increase in temperature favors the adsorption process. With the application of optimal adsorption variables, the adsorption capacity of gold was 0.78 mg/g of the adsorbent, out of which 0.70 mg of gold was desorbed with 0.1 % thiourea solution.

Keywords: adsorption, bagasse, extraction, nanoparticles, recovery

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Authors: B. I. Zhumagaliyev, L. Sh. Balgabayeva, G. S. Nabiyeva, B. A. Tulegenova, P. Oralkhan, B. S. Kalenova, S. S. Akhmetov

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The article describes an approach to build competence in research of Bachelor and Master, which is now an important feature of modern specialist in the field of engineering. Provides an example of methodical teaching methods with the research aspect, is including the formulation of the problem, the method of conducting experiments, analysis of the results. Implementation of methods allows the student to better consolidate their knowledge and skills at the same time to get research. Knowledge on the part of the media requires some training in the subject area and teaching methods.

Keywords: professional competence, model of it-specialties, teaching methods, educational technology, decision making

Procedia PDF Downloads 427