Search results for: extraction tool

Authors: Marisol Rodriguez-Duarte, Aide Saenz-Galindo, Carolina Flores-Gallegos, Raul Rodriguez-Herrera, Juan Ascacio-Valdes

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The plant known as tarbush (Fluorensia cernua) is a plant originating in northern Mexico, mainly in the states of Coahuila, Durango, San Luis Potosí, Zacatecas and Chihuahua. It is a branched shrub that belongs to the family Asteraceae, has oval leaves of 6 to 11 cm in length and also has small yellow flowers. In Mexico, the tarbush is a very appreciated plant because it has been used as a traditional medicinal agent, for the treatment of gastrointestinal diseases, skin infections and as a healing agent. This plant has been used mainly as an infusion. Due to its traditional use, the content and type of phytochemicals present in the plant are currently unknown and are responsible for its biological properties, so its recovery and identification is very important because the compounds that it contains have relevant applications in the field of food, pharmaceuticals and medicine. The objective of this work was to determine the best extraction condition of phytochemical compounds (mainly polyphenolic compounds) from the leaf using ultrasound/microwave assisted extraction (U/M-AE). To reach the objective, U/M-AE extractions were performed evaluating three mass/volume ratios (1:8, 1:12, 1:16), three ethanol/water solvent concentrations (0%, 30% and 70%), ultrasound extraction time of 20 min and 5 min at 70°C of microwave treatment. All experiments were performed using a fractional factorial experimental design. Once the best extraction condition was defined, the compounds were recovered by liquid column chromatography using Amberlite XAD-16, the polyphenolic fraction was recovered with ethanol and then evaporated. The recovered polyphenolic compounds were quantified by spectrophotometric techniques and identified by HPLC/ESI/MS. The results obtained showed that the best extraction condition of the compounds was using a mass/volume ratio of 1:8 and solvent ethanol/water concentration of 70%. The concentration obtained from polyphenolic compounds using this condition was 22.74 mg/g and finally, 16 compounds of polyphenolic origin were identified. The results obtained in this work allow us to postulate the Mexican plant known as tarbush as a relevant source of bioactive polyphenolic compounds of food, pharmaceutical and medicinal interest.

Keywords: U/M-AE, tarbush, polyphenols, identification

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Authors: Mohamed Seghouani, Ahmed Tafraoui, Soltane Lebaili

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The purpose of this study widened knowledge on the use of the cutting tools out of metal carbide and to define it the influence of the elements of the mode of cut on the behavior of these tools during the machining of treated steel XC38 and untreated. This work aims at evolution determined in experiments of the wear of a cutting tool out of metal carbide with plate reported of P30 nuance for an operation of slide-lathing in turning on soaked and not hardened steel XC38 test-tubes. This research is based on the model of Taylor to determine the life span of the cutting tool according to the various parameters of cut, like the cutting speed Vc, the advance of cut a, the depth of cutting P. In order to express the operational limits of the tool for slide-lathing in a preventive way. The model makes it possible to determine the time of change of the tool and to regard it as a constraint for the respect of the roughness of the workpiece during a work of series in conventional machining.

Keywords: machining, wear, lifespan, model of Taylor, cutting tool, carburize metal

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Authors: R. L. Ujjwal, Abhishek Jain

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In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

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Authors: Yongfang Deng, Dunwen Zuo

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An attempt is made here to join 2024 aluminum alloy plate by friction stir joining (FSJ) using different types of tools. Joint surface morphology was observed, and both arc line spacing and flash were measured. Study is carried out on the effect of pin, shoulder and eccentricity of the tool on the surface topography of the joint and the formation of the joint surface topography is analyzed. It is found that, eccentric squeezing action of the tool is the mainly motive power to form arc lines contour and flash structure. Little flash appears in the advancing side but with severe deformation, while the flash in the retreating side is heavy but with soft deformation. The pin of tool has a deep impact on the flash on the advancing side of the joints. Shoulder can widen the arc lines, refine arcs structure, reduce flash in the retreat side, but will increase the flash in the advancing side. Increasing the amount of eccentricity, it has litter effect on the arc line spacing but will destroy the arc lines morphology in the joint surface and promote the formation of filamentous flash structure in the joint.

Keywords: FSJ, surface morphology, tool, joint

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Authors: Tran Hung Tra, Hao Dinh Duong, Masakazu Okazaki

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Copper 1100 and aluminum 1050 plates with a thickness of 5.0 mm are butt-joint using friction stir welding. The tool offset is linearly varied along the welding path. Two welding regimes, using the same linear tool offset but in opposite directions, are applied for fabricating two Cu/Al plates. The material flow is dominated by both tool offset and offset history. The intermetallic compounds layer and interface morphology in each welded plate are formed in a different manner. As a result, the bonding strength and fracture behavior between two welded plates are significantly distinct. The role of interface morphology on fracture behavior is analyzed by the finite element method.

Keywords: Cu/Al dissimilar welding, offset history, interface morphology, intermetallic compounds, strength and fracture

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Authors: Fatima Mokeddem

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The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

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Authors: Janya Sainui

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As a rapid growth of digital videos and data communications, video summarization that provides a shorter version of the video for fast video browsing and retrieval is necessary. Key frame extraction is one of the mechanisms to generate video summary. In general, the extracted key frames should both represent the entire video content and contain minimum redundancy. However, most of the existing approaches heuristically select key frames; hence, the selected key frames may not be the most different frames and/or not cover the entire content of a video. In this paper, we propose a method of video summarization which provides the reasonable objective functions for selecting key frames. In particular, we apply a statistical dependency measure called quadratic mutual informaion as our objective functions for maximizing the coverage of the entire video content as well as minimizing the redundancy among selected key frames. The proposed key frame extraction algorithm finds key frames as an optimization problem. Through experiments, we demonstrate the success of the proposed video summarization approach that produces video summary with better coverage of the entire video content while less redundancy among key frames comparing to the state-of-the-art approaches.

Keywords: video summarization, key frame extraction, dependency measure, quadratic mutual information

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Authors: Oscar Corredor, Alexander Guzman, Adan Leon

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Density is a bulk physical property that indicates the quality of a petroleum fraction. It is also a useful property to estimate various physicochemical properties of fraction and petroleum fluids; however, the determination of density of extra heavy residual (EHR) fractions by standard methodologies, (ASTM D70) shows limitations for samples with higher densities than 1.0879 g/cm3. For this reason, a dilution methodology was developed in order to determinate density for those particular fractions, 87 (EHR) fractions were obtained as products of the fractionation of Colombian typical Vacuum Distillation Residual Fractions using molecular distillation (MD) and extraction with Solvent N-hexane in Supercritical Conditions (SFEF) pilot plants. The proposed methodology showed reliable results that can be demonstrated with the standard deviation of repeatability and reproducibility values of 0.0031 and 0.0061 g/ml respectively. In the same way, it was possible to determine densities in fractions EHR up to 1.1647g/cm3 and °API values obtained were ten times less than the water reference value.

Keywords: API, density, vacuum residual, molecular distillation, supercritical fluid extraction

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Authors: Sana Eid, Ahmad S. Darwish, Tarek Lemaoui, Maguy Abi Jaoude, Fawzi Banat, Shadi W. Hasan, Inas M. AlNashef

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Addressing the growing challenge of per- and polyfluoroalkyl substances (PFAS) pollution in water bodies, this study introduces natural deep eutectic solvents (NADESs) as a pioneering solution for the efficient extraction of perfluorooctanoic acid (PFOA), one of the most persistent and concerning PFAS pollutants. Among the tested NADESs, trioctylphosphine oxide: lauric acid (TOPO:LauA) in a 1:1 molar ratio was distinguished as the most effective, achieving an extraction efficiency of approximately 99.52% at a solvent-to-feed (S:F) ratio of 1:2, room temperature, and neutral pH. This efficiency is achieved within a notably short mixing time of only one min, which is significantly less than the time required by conventional methods, underscoring the potential of TOPO:LauA for rapid and effective PFAS remediation. TOPO:LauA maintained consistent performance across various operational parameters, including a range of initial PFOA concentrations (0.1 ppm to 1000 ppm), temperatures (15 °C to 100 °C), pH values (3 to 9), and S:F ratios (2:3 to 1:7), demonstrating its versatility and robustness. Furthermore, its effectiveness was consistently high over seven consecutive extraction cycles, highlighting TOPO:LauA as a sustainable, environmentally friendly alternative to hazardous organic solvents, with promising applications for reliable, repeatable use in combating persistent water pollutants such as PFOA.

Keywords: deep eutectic solvents, natural deep eutectic solvents, perfluorooctanoic acid, water remediation

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Authors: Jian Qu, Akira Shimazu

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OOV (Out Of Vocabulary) terms are terms that cannot be found in many dictionaries. Although it is possible to translate such OOV terms, the translations do not provide any real information for a user. We present an OOV term definition extraction method by using information available from the Internet. We use features such as occurrence of the synonyms and location distances. We apply machine learning method to find the correct definitions for OOV terms. We tested our method on both biomedical type and name type OOV terms, our work outperforms existing work with an accuracy of 86.5%.

Keywords: information retrieval, definition retrieval, OOV (out of vocabulary), biomedical information retrieval

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Authors: Jennifer F. Moore

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The wellness wheel as a tool for school growth and change is currently being piloted by a startup school in Chicago, IL. In this case study, members of the school community engaged in the appreciative inquiry process to plan their organizational development around the wellness wheel. The wellness wheel (comprised of physical, emotional, social, spiritual, environmental, cognitive, and financial wellness) is used as a planning tool by teachers, students, parents, and administrators. Through the appreciative inquiry method of change, the community is reflecting on their individual level of wellness and developing organizational structures to ensure the well being of children and adults. The goal of the case study is to test the appropriateness of the use of appreciative inquiry (as a method) and the wellness wheel (as a tool) for school growth and development. Findings of the case study will be realized by the conference. The research is in process now.

Keywords: education, schools, well being, wellness

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Authors: Bazaraliyeva Aigerim Bakytzhanovna, Turgumbayeva Aknur Amanbekovna

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The phytosubstance from garlic was obtained by extraction with liquid carbon dioxide under critical conditions. Methods of processing raw materials are proposed, and the chemical composition of garlic is studied by gas chromatography and mass spectrometry. The garlic extract's composition was determined using gas chromatography (GC) and gas chromatography-mass spectrophotometry (GC-MS). The phytosubstance had 54 constituents. The extract included the following main compounds: Manool (39.56%), Viridifrolol (7%), Podocarpa-1,8,11,13-tetraen-3-one, 14-isopropyl-1,13-dimethoxy- 5,15 percent, (+)-2-Bornanone (4.29%), Thujone (3.49%), Linolic acid ethyl ester (3.41%), and 12-O-Methylcarn.

Keywords: allium sativum, bioactive compounds of garlic, carbon dioxide extraction of garlic, GS-MS method

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Authors: Abu Harera Nadeem, Kingsley Donkor

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Tea is a popular beverage due to its flavour, aroma and antioxidant properties—with the most consumed varieties being green and black tea. Antioxidants in tea can lower the risk of Alzheimer’s and heart disease and obesity. However, these teas contain heavy metals such as Hg, Cd, or Pb, which can cause autoimmune diseases like Graves disease. In this study, 11 heavy metals in various commercial green, black, and oolong tea samples were determined using inductively coupled plasma-mass spectrometry (ICP-MS). Two methods of sample preparation were compared for accuracy and precision, which were microwave-assisted digestion and ultrasonic-assisted extraction. The developed method was further validated by detection limit, precision, and accuracy. Results showed that the proposed method was highly sensitive with detection limits within parts-per-billion levels. Reasonable method accuracy was obtained by spiked experiments. The findings of this study can be used to delve into the link between tea consumption and disease and to provide information for future studies on metal determination in tea.

Keywords: ICP-MS, green tea, black tea, microwave-assisted acid digestion, ultrasound-assisted extraction

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Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Fumitake Nishimura, Jaiyeop Lee

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This study aimed to compare two pre-treatment and two RNA extraction methods, namely PEG, and Nano bubble, Viral RNA Soil, and Mini Kit, in terms of their efficiency in detecting SARS-CoV-2 and PMMoV in influent and 1st sedimentation samples from a wastewater treatment plant. The extracted RNA samples were quantified and evaluated for purity, yield, and integrity. The results indicated that the nanobubble PEG method provided the highest yield of RNA, while the QIAamp Viral RNA Mini Kit produced the purest RNA samples. In terms of sensitivity and specificity, all these methods were able to detect SARS-CoV-2 and PMMoV in both influent and 1st sedimentation samples. However, the nanobubble PEG method showed slightly higher sensitivity compared to the other methods. These findings suggest that the choice of RNA extraction method should depend on the downstream application and the quality of the RNA required. The study also highlights the potential of wastewater-based epidemiology as an effective and non-invasive method for monitoring the spread of infectious diseases in a community.

Keywords: influent, PMMoV, SARS-CoV-2, wastewater based epidemiology

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Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: Prandesha Govender, Chris Cloete

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Purpose: The objective of the paper is to develop a tool for the evaluation of the financial risk of a shopping center. Methodology: Important factors that indicate the success of a shopping center were identified from the available literature. Weights were allocated to these factors and a risk rating was calculated for 505 shopping centers in the largest province in South Africa by taking the factor scores, factor weights, and category weights into account. The ratings for ten randomly selected shopping centers were correlated with consumer feedback and standardized against the ECAI (External Credit Assessment Institutions) data for the same centers. The ratings were also mapped to corporates with the same risk rating to provide a better intuitive assessment of the meaning of the inherent risk of each center. Results: The proposed risk tool shows a strong linear correlation with consumer views and can be compared to expert opinions, such as that of fund managers and REITs. Interpretation of the tool was also illustrated by correlating the risk rating of selected shopping centers to the risk rating of reputable and established entities. Conclusions: The proposed Shopping Centre Risk Tool, used in conjunction with financial inputs from the relevant center, should prove useful to an investor when the desirability of investment in or expansion, renovation, or purchase of a shopping center is being considered.

Keywords: risk, shopping centres, risk modelling, investment, rating tool, rating scale

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Authors: Kamal Amarouche, Houda Benbrahim, Ismail Kassou

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Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone...); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic.

Keywords: opinion mining, product feature extraction, sentiment analysis, SentiWordNet

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Authors: Jui-Pin Hung, Qiao-Wen Chang, Kung-Da Wu, Yong-Run Chen

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This study was aimed to investigate the machining stability of a spindle tool with different preloaded amount. To this end, the vibration tests were conducted on the spindle unit with different preload to assess the dynamic characteristics and machining stability of the spindle unit. Current results demonstrate that the tool tip frequency response characteristics and the machining stabilities in X and Y direction are affected to change for spindle with different preload. As can be found from the results, a high preloaded spindle tool shows higher limited cutting depth at mid position, while a spindle with low preload shows a higher limited depth. This implies that the machining stability of spindle tool system is affected to vary by the machine frame structure. Besides, such an effect is quite different and varied with the preload of the spindle.

Keywords: bearing preload, dynamic compliance, machining stability, spindle

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Authors: Simon Peter Wafula, Ziporah Nakabazzi Kitooke

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Graphene is a carbon allotrope made of a two-dimensional shape. This material has got a number of materials researchers’ interest due to its properties that are special compared to ordinary material. Graphene is thought to enhance a number of material properties in the manufacturing, energy, and construction industries. Many studies consider graphene to be a wonder material, just like plastic in the 21st century. This shows how much should be invested in graphene research. This review highlights the status of graphene extracted from various biomass sources together with their appropriate extraction techniques, including the pretreatment methods for a better product. The functional groups and structure of graphene extracted using several common methods of synthesis are in this paper as well. The review explores methods like chemical vapor deposition (CVD), hydrothermal, chemical exfoliation method, liquid exfoliation, and Hummers. Comparative analysis of the various extraction techniques gives an insight into each of their advantages, challenges, and potential scalability. The review also highlights the pretreatment process for biomass before carbonation for better quality of bio-graphene. The various graphene modes, as well as their applications, are in this study. Recommendations for future research for improving the efficiency and sustainability of bio-graphene are highlighted.

Keywords: exfoliation, nanomaterials, biochar, large-scale, two-dimension

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Authors: Alicja Kot-Niewiadomska

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Securing sustainable access to raw materials is vital for the growth of the European economy and for the goals laid down in Strategy Europe 2020. One of the most important sources of mineral raw materials are primary deposits. The efficient management of them, including extraction, will ensure competitiveness of the European economy. A critical element of this approach is mineral deposits safeguarding and the most important tool - spatial planning. The safeguarding of deposits should be understood as safeguarding of land access, and safeguarding of area against development, which may (potential) prevent the use of the deposit and the necessary mining activities. Many European Union countries successfully integrated their mineral policy and spatial policy, which has ensured the proper place of mineral deposits in their spatial planning systems. These, in turn, are widely recognized as the most important mineral deposit safeguarding tool, the essence of which is to ensure long-term access to its resources. The examples of Austria, Portugal, Slovakia, Czech Republic, Sweden, and the United Kingdom, discussed in the paper, are often mentioned as examples of good practices in this area. Although none of these countries managed to avoid cases of social and environmental conflicts related to mining activities, the solutions they implement certainly deserve special attention. And for many countries, including Poland, they can be a potential source of solutions aimed at improving the protection of mineral deposits.

Keywords: mineral deposits, land use planning, mineral deposit safeguarding, European practices

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Miguel Mariano Rivera Galvan

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The purpose of this research was to create a digital tool by which users can obtain an immediate and accurate solution of the angular characteristics of an irregular quadrilateral. The development of this project arose because of the frequent absence of a polygon’s geometric information in land ownership accreditation documents. The researcher created a mathematical model using a linear approximation iterative method, employing various disciplines and techniques including trigonometry, geometry, algebra, and topography. This mathematical model uses as input data the surface of the quadrilateral, as well as the length of its sides, to obtain its interior angles and make possible its representation in a coordinate system. The results are as accurate and reliable as the user requires, offering the possibility of using this tool as a support to develop future engineering and architecture projects quickly and reliably.

Keywords: digital tool, geometry, mathematical model, quadrilateral, solution

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Authors: David Downey

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With the introduction of additive manufacturing (3D printing) to produce titanium (Ti6Al4V) components in the medical/aerospace and automotive industries, intricate geometries can be produced with virtually complete design freedom. However, the consideration of microstructural anisotropy resulting from the additive manufacturing process becomes necessary due to this design flexibility and the need to print a geometric shape that can consist of numerous angles, radii, and swept surfaces. A femoral knee implant serves as an example of a 3D-printed near-net-shaped product. The mechanical properties of the printed components, and consequently, their machinability, are affected by microstructural anisotropy. Currently, finish-machining operations performed on titanium printed parts using selective laser melting (SLM) utilize the same cutting tools employed for processing wrought titanium components. Cutting forces for components manufactured through SLM can be up to 70% higher than those for their wrought counterparts made of Ti6Al4V. Moreover, temperatures at the cutting interface of 3D printed material can surpass those of wrought titanium, leading to significant tool wear. Although the criteria for tool wear may be similar for both 3D printed and wrought materials, the rate of wear during the machining process may differ. The impact of these issues on the choice of cutting tool material and tool lifetimes will be discussed.

Keywords: additive manufacturing, build orientation, microstructural anisotropy, printed titanium Ti6Al4V, tool wear

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Authors: Hasnizan Aksah, Adi Irfan Che Ani

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Refurbished historic government buildings should perform as intended to support the organization’s goals that enhance occupant satisfaction. However, these buildings may have issues associated with functional performance evaluation. The aim of this study is to develop a Post Occupancy Evaluation (POE) sustainability assessment tool for functional performance evaluation of refurbished historic government buildings. Developing an assessment tool requires a strategic methodology for a logical and cohesive tool that incorporating relevant theories and practical experiences. In this study, mixed method approaches use to collect all necessary data to achieve the objectives of this study. The design of sampling involves are interviews and survey questionnaires to relevant professionals in order to evaluate the criteria and problem encircled in functional performance evaluation. Then, the involvement of expert panels is required in establishing the assessment tool. During the process of investigation on the functional performance criteria, it was discovered that is seen to be critical in aspects of comfort, safety, and services. The proposed assessment tool has a significant role in providing opportunities for the improvement of building performance especially on functional performance for the future historic government building refurbishment project. It is hoped that the tool developed from this study will give benefits to related professionals, public agencies, local municipality, and relevant interested parties in historic building management.

Keywords: refurbished historic government buildings, functional performance, Post Occupancy Evaluation, sustainability

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Authors: Nasar Aldian Ambark Shashoa

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Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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Authors: Jafar W. Al-Badarneh, Abdalkareem R. Al-Hawary, Abdulmalik M. Morghem, Mostafa Z. Ali, Rami S. Al-Gharaibeh

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Archeological heritage is at the heart of each country’s national glory. Moreover, it could develop into a source of national income. Heritage management requires socially-responsible marketing that achieves high visitor satisfaction while maintaining high site conservation. We have developed an Augmented Reality (AR) experience for heritage and cultural reservation at Dar-As-Saraya museum in Jordan. Our application of this notion relied on markerless-based tracking approach. This approach uses keypoints extraction technique where features of the environment are identified and defined into the system as keypoints. A set of these keypoints forms a tracker for an augmented object to be displayed and overlaid with a real scene at Dar As-Saraya museum. We tested and compared several techniques for markerless tracking and then applied the best technique to complete a mosaic artifact with AR content. The successful results from our application open the door for applications in open archeological sites where markerless tracking is mostly needed.

Keywords: augmented reality, cultural heritage, keypoints extraction, virtual recreation

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Authors: Natela Gerliani, Mohammed Aider

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Nowadays, the interest of using sustainable technologies for protein extraction from underutilized oilseeds is growing. Currently, a major disposal problem for the oil industry is by-products of plant food processing such as soybean meal. That is why valorization of soybean meal is important for the oil industry since it contains high-quality proteins and other valuable components. Generally, soybean meal is used in livestock and poultry feed but is rarely used in human feed. Though chemical composition of this meal compensate nutritional deficiency and can be used to balance protein in human food. Regarding the efficiency of soybean meal valorization, extraction is a key process for obtaining enriched protein ingredient, which can be incorporated into the food matrix. However, most of the food components such as proteins extracted from oilseeds by-products imply the utilization of organic and inorganic chemicals (e.g. acids, bases, TCA-acetone) having a significant environmental impact. In a context of sustainable production, the use of an electro-activation technology seems to be a good alternative. Indeed, the electro-activation technology requires only water, food grade salt and electricity as main materials. Moreover, this innovative technology helps to avoid special equipment and trainings for workers safety as well as transport and storage of hazardous materials. Electro-activation is a technology based on applied electrochemistry for the generation of acidic and alkaline solutions on the basis of the oxidation-reduction reactions that occur at the vicinity electrode/solution interfaces. It is an eco-friendly process that can be used to replace the conventional acidic and alkaline extraction. In this research, the electro-activation technology for protein extraction from soybean meal was carried out in the electro-activation reactor. This reactor consists of three compartments separated by cation and anion exchange membranes that allow creating non-contacting acidic and basic solutions. Different current intensities (150 mA, 300 mA and 450 mA) and treatment durations (10 min, 30 min and 50 min) were tested. The results showed that the extracts obtained by the electro-activation method have good quality in comparison to conventional extracts. For instance, extractability obtained with electro-activation method was 55% whereas with the conventional method it was only 36%. Moreover, a maximum protein quantity of 48 % in the extract was obtained with the electro-activation technology comparing to the maximum amount of protein obtained by conventional extraction of 41 %. Hence, the environmentally sustainable electro-activation technology seems to be a promising type of protein extraction that can replace conventional extraction technology.

Keywords: by-products, eco-friendly technology, electro-activation, soybean meal

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Authors: Damien Rinsant, Eugen Andreiadis, Michael Carboni, Daniel Meyer

Abstract:

Different types of materials have been developed for the solid/liquid uranium extraction processes, such as functionalized organic polymers, hybrid silica or inorganic adsorbents. In general, these materials exhibit a moderate affinity for uranyl ions and poor selectivity against impurities like iron, vanadium or molybdenum. Moreover, the structural organization deficiency of these materials generates ion diffusion issues inside the material. Therefore, the aim of our study is to developed efficient and organized materials, stable in the acid media encountered in uranium extraction processes. Metal organic frameworks (MOFs) are hybrid crystalline materials consisting of an inorganic part (cluster or metal ions) and tailored organic linkers connected via coordination bonds. These hierarchical materials have exceptional surface area, thermal stability and a large variety of tunable structures. However, due to the reversibility of constitutive coordination bonds, MOFs have moderate stability in strongly complexing or acidic media. Only few of them are known to be stable in aqueous media and only one example is described in strong acidic media. However, these conditions are very often encountered in the environmental pollution remediation of mine wastewaters. To tackle the challenge of developing MOFs adapted for uranium extraction from acid mine waters, we have investigated the stability of several materials. To ensure a good stability we have synthetized and characterized different materials based on highly coordinated metal clusters, such as LnOFs and Zirconium based materials. Among the latter, the UiO family shows a great stability in sulfuric acid media even in the presence of 1.4 M sodium sulfate at pH 2. However, the stability in phosphoric media is reduced due to the high affinity between zirconium and phosphate ligand. Based on these results, we have developed a tertiary amine functionalized MOF denoted UiO-68-NMe2 particularly adapted for the extraction of anionic uranyl (VI) sulfate complexes mainly present in the acid mine solutions. The adsorption capacity of the material has been determined upon varying total sulfate concentration, contact time and uranium concentration. The extraction tests put in evidence different phenomena due to the complexity of the extraction media and the interaction between the MOF and sulfate anion. Finally, the extraction mechanisms and the interaction between uranyl and the MOF structure have been investigated. The functionalized material UiO-68-NMe2 has been characterized in the presence and absence of uranium by FT-IR, UV and Raman techniques. Moreover, the stability of the protonated amino functionalized MOF has been evaluated. The synthesis, characterization and evaluation of this type of hybrid material, particularly adapted for uranium extraction in sulfuric acid media by an anionic exchange mechanism, paved the way for the development of metal organic frameworks functionalized by different other chelating motifs, such as bifunctional ligands showing an enhanced affinity and selectivity for uranium in acid and complexing media. Work in this direction is currently in progress.

Keywords: extraction, MOF, ligand, uranium

Procedia PDF Downloads 139

Authors: Sujata S. Kulkarni

Abstract:

Effective and efficient texture feature extraction and classification is an important problem in image understanding and recognition. This paper gives a review on effective texture classification method. The objective of the problem of texture representation is to reduce the amount of raw data presented by the image, while preserving the information needed for the task. Texture analysis is important in many applications of computer image analysis for classification include industrial and biomedical surface inspection, for example for defects and disease, ground classification of satellite or aerial imagery and content-based access to image databases.

Keywords: compressed sensing, feature extraction, image classification, texture analysis

Procedia PDF Downloads 409

Authors: Ke Ren, Huiruo Shi, Linsen Li, Baoshuai Wang, Yu Zhou

Abstract:

Since some discriminative features are required for ground moving targets classification, we propose a new feature extraction method based on micro-Doppler signature. Firstly, the time-frequency analysis of measured data indicates that the time-frequency spectrograms of the three kinds of ground moving targets, i.e., single walking person, two people walking and a moving wheeled vehicle, are discriminative. Then, a three-dimensional time-frequency feature vector is extracted from the time-frequency spectrograms to depict these differences. At last, a Support Vector Machine (SVM) classifier is trained with the proposed three-dimensional feature vector. The classification accuracy to categorize ground moving targets into the three kinds of the measured data is found to be over 96%, which demonstrates the good discriminative ability of the proposed micro-Doppler feature.

Keywords: micro-doppler, time-frequency analysis, feature extraction, radar target classification

Procedia PDF Downloads 384