Search results for: causal realtion extraction

Authors: Jarek Krajewski, David Daxberger

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We propose a stress detection method based on an RGB camera using heart rate detection, also known as Photoplethysmography Imaging (PPGI). This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. A stationary lab setting with simulated video conferences is chosen using constant light conditions and a sampling rate of 30 fps. The ground truth measurement of heart rate is conducted with a common PPG system. The proposed approach for pulse peak detection is based on a machine learning-based approach, applying brute force feature extraction for the prediction of heart rate pulses. The statistical analysis showed good agreement (correlation r = .79, p<0.05) between the reference heart rate system and the proposed method. Based on these findings, the proposed method could provide a reliable, low-cost, and contactless way of measuring HR parameters in daily-life environments.

Keywords: heart rate, PPGI, machine learning, brute force feature extraction

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Authors: Nimisha Elsa Koshy, Varun P. Gopi, V. I. Thajudin Ahamed

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The entire visualization of GastroIntestinal (GI) tract is not possible with conventional endoscopic exams. Wireless Capsule Endoscopy (WCE) is a low risk, painless, noninvasive procedure for diagnosing diseases such as bleeding, polyps, ulcers, and Crohns disease within the human digestive tract, especially the small intestine that was unreachable using the traditional endoscopic methods. However, analysis of massive images of WCE detection is tedious and time consuming to physicians. Hence, researchers have developed software methods to detect these diseases automatically. Thus, the effectiveness of WCE can be improved. In this paper, a novel textural feature extraction method is proposed based on Contourlet transform and Log Gabor filter to distinguish ulcer regions from normal regions. The results show that the proposed method performs well with a high accuracy rate of 94.16% using Support Vector Machine (SVM) classifier in HSV colour space.

Keywords: contourlet transform, log gabor filter, ulcer, wireless capsule endoscopy

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Authors: Seyed Hossein Alavi, Farshad Ghazalian, Soghra Jamshidi

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The present study was done with the purpose of considering mental health and general purpose of describing and comparing depression level of athlete and non-athlete male students educational year of 2012 Research method in this study in proportion to the selective title, descriptive method is causative – comparative. Research samples were selected randomly from B.A students of different fields including 500 students. Average mean of research samples was between 20 to 25 years. Data collection tool is questionnaire of depression measurement of Aroun Beck (B.D.I) that analyzes and measures 21 aspects of depression in 6 ranges. Operation related to analysis of statistical data to extraction of results was done by SPSS software. To extraction of research obtained by comparison of depression level mean, show that the hypothesis of the research (H_1) based on the existence of the significance scientific difference was supported and showed that there’s a significance difference between depression level of athlete male students in comparison with depression level of non-athlete male students. Thus, depression level of athlete male students was lower in comparison with depression level of non-athlete male students.

Keywords: depression, athlete students, non-athlete students

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Bibha Kumari, Nigel P. Brunton, Dilip K. Rai, Brijesh K. Tiwari

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Edible mushrooms possess numerous functional components like homo- and hetero- β-glucans [β(1→3), β(1→4) and β(1→6) glucosidic linkages], chitins, ergosterols, bioactive polysaccharides and peptides imparting health beneficial properties to mushrooms. Some of the proven biological activities of mushroom extracts are antioxidant, antimicrobial, immunomodulatory, cholesterol lowering activity by inhibiting a key cholesterol metabolism enzyme i.e. 3-hydroxy-3-methyl-glutaryl CoA reductase (HMGCR), angiotensin I-converting enzyme (ACE) inhibition. Application of novel extraction technologies like pulsed electric field (PEF) and high power ultrasound offers clean, green, faster and efficient extraction alternatives with enhanced and good quality extracts. Sequential PEF followed by ultrasound assisted extraction (UAE) were applied to recover bioactive enriched fractions from industrial white button mushroom (Agaricus bisporus) stalk waste using environmentally friendly and GRAS solvents i.e. water and water/ethanol combinations. The PEF treatment was carried out at 60% output voltage, 2 Hz frequency for 500 pulses of 20 microseconds pulse width, using KCl salt solution of 0.6 mS/cm conductivity by the placing 35g of chopped fresh mushroom stalks and 25g of salt solution in the 4x4x4cm3 treatment chamber. Sequential UAE was carried out on the PEF pre-treated samples using ultrasonic-water-bath (USB) of three frequencies (25 KHz, 35 KHz and 45 KHz) for various treatment times (15-120 min) at 80°C. Individual treatment using either PEF or UAE were also investigation to compare the effect of each treatment along with the combined effect on the recovery and bioactivity of the crude extracts. The freeze dried mushroom stalk powder was characterised for proximate compositional parameters (dry weight basis) showing 64.11% total carbohydrate, 19.12% total protein, 7.21% total fat, 31.2% total dietary fiber, 7.9% chitin (as glucosamine equivalent) and 1.02% β-glucan content. The total phenolic contents (TPC) were determined by the Folin-Ciocalteu procedure and expressed as gallic-acid-equivalents (GAE). The antioxidant properties were ascertained using DPPH and FRAP assays and expressed as trolox-equivalents (TE). HMGCR activity and molecular mass of β-glucans will be measured using the commercial HMG-CoA Reductase Assay kit (Sigma-Aldrich) and size exclusion chromatography (HPLC-SEC), respectively. Effects of PEF, UAE and their combination on the antioxidant capacity, HMGCR inhibition and β-glucans content will be presented.

Keywords: β-glucan, mushroom stalks, pulsed electric field (PEF), ultrasound assisted extraction (UAE)

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Authors: Nadeem Akhtar, Hira Javed

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An important aspect of research is literature survey. Availability of a large amount of literature across different domains triggers the need for optimized systems which provide relevant literature to researchers. We propose a search system based on keywords for text documents. This experimental approach provides a hierarchical structure to the document corpus. The documents are labelled with keywords using KEA (Keyword Extraction Algorithm) and are automatically organized in a lattice structure using Formal Concept Analysis (FCA). This groups the semantically related documents together. The hierarchical structure, based on keywords gives out only those documents which precisely contain them. This approach open doors for multi-domain research. The documents across multiple domains which are indexed by similar keywords are grouped together. A hierarchical relationship between keywords is obtained. To signify the effectiveness of the approach, we have carried out the experiment and evaluation on Semeval-2010 Dataset. Results depict that the presented method is considerably successful in indexing of scientific papers.

Keywords: formal concept analysis, keyword extraction algorithm, scientific documents, lattice

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Authors: Hamida Y. Mostafa, Ghada E. Khedr, Dina M. Abd El-Aty

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Sulfur compound removal from petroleum fractions is a critical component of environmental protection demands. Solvent extraction, oxidative desulfurization, or hydro-treatment techniques have traditionally been used as the removal processes. While all methods were capable of eliminating sulfur compounds at moderate rates, they had some limitations. A major problem with these routes is their high running expenses, which are caused by their prolonged operation times and high energy consumption. Therefore, new methods for removing sulfur are still necessary. In the current study, a simple assisted desulfurization system for gas oil fraction has been successfully developed using acetonitrile and methanol as a solvent under microwave irradiation. The key variables affecting sulfur removal have been studied, including microwave power, irradiation time, and solvent to gas oil volume ratio. At the conclusion of the research that is being presented, promising results have been found. The results show that a microwave-assisted extractive desulfurization method had remove sulfur with a high degree of efficiency under the suitable conditions.

Keywords: extractive desulfurization, microwave assisted extraction, petroleum fractions, acetonitrile and methanol

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Authors: Reza Pashaei, Reda Dzingelevičienė

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An efficient, reliable, and sensitive multiclass analytical method has been expanded to simultaneously determine 15 human pharmaceutical residues in fish and shrimp tissue samples by ultra-high-performance liquid chromatography-tandem mass spectrometry. The investigated compounds comprise ten classes, namely analgesic, antibacterial, anticonvulsant, cardiovascular, fluoroquinolones, macrolides, nonsteroidal anti-inflammatory, penicillins, stimulant, and sulfonamide. A simple liquid extraction procedure based on 0.1% formic acid in methanol was developed. Chromatographic conditions were optimized, and mobile phase namely 0.1 % ammonium acetate (A), and acetonitrile (B): 0 – 2 min, 15% B; 2 – 5 min, linear to 95% B; 5 – 10 min, 95% B; and 10 – 12 min was obtained. Limits of detection and quantification ranged from 0.017 to 1.371 μg/kg and 0.051 to 4.113 μg/kg, respectively. Finally, amoxicillin, azithromycin, caffeine, carbamazepine, ciprofloxacin, clarithromycin, diclofenac, erythromycin, furosemide, ibuprofen, ketoprofen, naproxen, sulfamethoxazole, tetracycline, and triclosan were quantifiable in fish and shrimp samples.

Keywords: fish, liquid chromatography, mass spectrometry, pharmaceuticals, shrimp, solid-phase extraction

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Authors: Ibrahim Watad, Ibrahim Abdulhalim

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Conventional spectroscopic surface plasmon resonance (SPR) sensors are widely used, both in fundamental research and environmental monitoring as well as healthcare diagnostics. However, they still lack the low limit of detection (LOD) and there still a place for improvement. SPR conventional sensors are based on the detection of a dip in the reflectivity spectrum which is relatively wide. To improve the performance of these sensors, many techniques and methods proposed either to reduce the width of the dip or to increase the sensitivity. Together with that, profiting from the sharp jump in the phase spectrum under SPR, several works suggested the extraction of the phase of the reflected wave. However, existing phase measurement setups are in general more complicated compared to the conventional setups, require more stability and are very sensitive to external vibrations and noises. In this study, a simple polarimetric technique for phase extraction under SPR is presented, followed by a theoretical error analysis and an experimental verification. The advantages of the proposed technique upon existing techniques will be elaborated, together with conclusions regarding the best polarimetric function, and its corresponding optimal metal layer range of thicknesses to use under the conventional Kretschmann-Raether configuration.

Keywords: plasmonics, polarimetry, thin films, optical sensors

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Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

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Authors: C. C. Igwe, C. E. Ogbuadike

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Bryophyllum pinnatum is a tropical plant used by the indigenous people of South-East Nigeria as a medicinal plant for the treatment of skin ulcer and is being explored for the production of topical herbal skin ointments. This preliminary study involves the extraction and characterization of bioactive compounds from this plant for anti-skin ulcer, antimicrobial, and antioxidant activity, as well as formulating topical herbal medications for skin ulcer. Thus extraction, percentage yield, moisture content analysis, solvent-solvent fractionation and GC-MS has been carried out on processed leaves sample of B. pinnatum. GC-MS analysis revealed the presence of seven compounds, namely: 1-Octene, 3, 7-dimethyl, 1-Tridecene, E-14-Hexadecenal, 3-Eicosene (E)-, 11-Tricosene, 1-Tridecyn-4-ol and Butanamide. Standardized herbal products have been produced from B. pinnatum extracts. The products are being evaluated for safety and efficacy tests to ascertain their toxicity (if any), anti-ulcer, antibiotic and antioxidant properties. Further work is on-going to characterize the bioactive principles present in the plant extracts.

Keywords: anti-microbial, bioactive compounds, bryophyllum pinnatum, skin ulcer

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Authors: Perumalsamy Muthiah, Murugesan Thanapalan

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The remains of cheese production contain nutritional value added proteins viz., α-Lactalbumin, β-Lactoglobulin representing 80- 90% of the total volume of milk entering the process. Although several possibilities for cheese-whey exploitation have been assayed, approximately half of world cheese-whey production is not treated but is discarded as effluent. It is necessary to develop an effective and environmentally benign extraction process for the recovery of value added cheese whey proteins. Recently aqueous two phase system (ATPS) have emerged as potential separation process, particularly in the field of biotechnology due to the mild conditions of the process, short processing time, and ease of scale-up. In order to design an ATPS process for the recovery of cheese whey proteins, development of phase diagram and the effect of system parameters such as pH, types and the concentrations of the phase forming components, temperature, etc., on the partitioning of proteins were addressed in order to maximize the recovery of proteins. Some of the practical problems encountered in the application of aqueous two-phase systems for the recovery of Cheese whey proteins were also discussed.

Keywords: aqueous two-phase system, phase diagram, extraction, cheese whey

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Authors: Patricia Jiménez, Rafael Corchuelo, Hassan A. Sleiman

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Web mining is gaining importance at an increasing pace. Currently, there are many complementary research topics under this umbrella. Their common theme is that they all focus on applying knowledge discovery techniques to data that is gathered from the Web. Sometimes, these data are relatively easy to gather, chiefly when it comes from server logs. Unfortunately, there are cases in which the data to be mined is the data that is displayed on a web document. In such cases, it is necessary to apply a pre-processing step to first extract the information of interest from the web documents. Such pre-processing steps are performed using so-called information extractors, which are software components that are typically configured by means of rules that are tailored to extracting the information of interest from a web page and structuring it according to a pre-defined schema. Paramount to getting good mining results is that the technique used to extract the source information is exact, which requires to evaluate and compare the different proposals in the literature from an empirical point of view. According to Google Scholar, about 4 200 papers on information extraction have been published during the last decade. Unfortunately, they were not evaluated within a homogeneous framework, which leads to difficulties to compare them empirically. In this paper, we report on an original information extraction evaluation method. Our contribution is three-fold: a) this is the first attempt to provide an evaluation method for proposals that work on semi-structured documents; the little existing work on this topic focuses on proposals that work on free text, which has little to do with extracting information from semi-structured documents. b) It provides a method that relies on statistically sound tests to support the conclusions drawn; the previous work does not provide clear guidelines or recommend statistically sound tests, but rather a survey that collects many features to take into account as well as related work; c) We provide a novel method to compute the performance measures regarding unsupervised proposals; otherwise they would require the intervention of a user to compute them by using the annotations on the evaluation sets and the information extracted. Our contributions will definitely help researchers in this area make sure that they have advanced the state of the art not only conceptually, but from an empirical point of view; it will also help practitioners make informed decisions on which proposal is the most adequate for a particular problem. This conference is a good forum to discuss on our ideas so that we can spread them to help improve the evaluation of information extraction proposals and gather valuable feedback from other researchers.

Keywords: web information extractors, information extraction evaluation method, Google scholar, web

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Authors: Annalakshmi G., Sakthivel Murugan S.

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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

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Authors: Marji Umil, Miane Karyle Urolaza, Ian Winston Dale Uy, John Charle Magne Valdez, Karen Elizabeth Valdez, Ervin Charles Valencia, Cheryleen Tan-Chua

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Objective: Distraction techniques can be successful in reducing the anxiety of children during medical procedures. Dental procedures, in particular, are associated with dental anxiety which has been identified as a significant and common problem in children, however, only limited studies were conducted to address such problem. Thus, this study determined the effectiveness of computer video games on the levels of anxiety of children between 5-12 years old scheduled for tooth extraction. Methods: A pre-test post-test quasi-experimental study was conducted involving 30 randomly-assigned subjects, 15 in the experimental and 15 in the control. Subjects in the experimental group played computer video games for a maximum of 15 minutes, however, no intervention was done on the control. The modified Yale Pre-operative Anxiety Scale (m-YPAS) with a Cronbach’s alpha of 0.9 was used to assess anxiety at two different points: upon arrival in the clinic (pre-test anxiety) and 15 minutes after the first measurement (post-test anxiety). Paired t-test and ANCOVA were used to analyze the gathered data. Results: Results showed that there is a significant difference between the pre-test and post-test anxiety scores of the control group (p=0.0002) which indicates an increased anxiety. A significant difference was also noted between the pre-test and post-test anxiety scores of the experimental group (p=0.0002) which indicates decreased anxiety. Comparatively, the experimental group showed lower anxiety score (p=<0.0001) than the control. Conclusion: The use of computer video games is effective in reducing the pre-operative anxiety among children and can be an alternative non-pharmacological management in giving pre-operative care.

Keywords: play therapy, preoperative anxiety, tooth extraction, video games

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Authors: Urvah-Til-Vusqa, Unsa Noreen, Ayesha Hussain, Abdul Hafeez, Rafia Asghar, Sidrat Nasir

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Natural dyes offer an alternative better application in textiles than synthetic ones. The present study will be aimed to employ natural dye extracted from Cordyline terminalis plant and its application into viscose under the influence of gamma radiations. The colorant extraction will be done by boiling dracaena leaves powder in aqueous, alkaline and ethyl acetate mediums. Both dye powder and fabric will be treated with different doses (5-20 kGy) of gamma radiations. The antioxidant, antimicrobial and hemolytic activities of the extracts will also be determined. Different tests of fabric characterization (before and after radiations treatment) will be employed. Dyeing variables just as time, temperature and M: L will be applied for optimization. Standard methods for ISO to evaluate color fastness to light, washing and rubbing will be employed for improvement of color strength 1.5-15.5% of Al, Fe, Cr, and Cu as mordants will be employed through pre, post and meta mordanting. Color depth % & L*, a*, b* and L*, C*, h values will be recorded using spectra flash SF650.

Keywords: natural dyes, gamma radiations, Cordyline terminalis, ecofriendly dyes

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Authors: Muhammad Usman

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Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: René Davids

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Some Western countries are abandoning coal and finding cleaner alternatives, such as solar, wind, hydroelectric, biomass, and geothermal, for the production of energy. As a consequence, industries have closed, and the toxic contaminated slag heaps formed essentially of discarded rock that did not contain coal are being colonized by spontaneously generated plant communities. In becoming green hiking territory, goat farms, viewing platforms, vineyards, great staging posts for species experiencing, and skiing slopes, many of the formerly abandoned hills of refuse have become delightful amenities to the surrounding communities. Together with the transformation of many industrial facilities into cultural venues, these changes to the slag hills have allowed the old coal districts to develop a new identity, but in the process, they have also literally buried the past. This essay reviews a few case studies to analyze the different ways slag heaps have contributed to the cultural landscape in the ex-coal county while arguing that it is important when deciding on their future, that we find ways to make the environmental damage that the extraction industry caused visibly and honor the lives of the people that worked under often appalling conditions in them.

Keywords: slag-heaps, mines, extraction, remediation, pollution

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: B. Mendonça, D. Sandwell

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The Metropolitan Region of Sao Paulo (MRSP) has suffered from serious water scarcity. Consequently, the most convenient solution has been building wells to extract groundwater from local aquifers. However, it requires constant vigilance to prevent over extraction and future events that can pose serious threat to the population, such as subsidence. Radar imaging techniques (InSAR) have allowed continuous investigation of such phenomena. The analysis of data in the present study consists of 23 SAR images dated from October 2007 to March 2011, obtained by the ALOS-1 spacecraft. Data processing was made with the software GMTSAR, by using the InSAR technique to create pairs of interferograms with ground displacement during different time spans. First results show a correlation between the location of 102 wells registered in 2009 and signals of ground displacement equal or lower than -90 millimeters (mm) in the region. The longest time span interferogram obtained dates from October 2007 to March 2010. As a result, from that interferogram, it was possible to detect the average velocity of displacement in millimeters per year (mm/y), and which areas strong signals have persisted in the MRSP. Four specific areas with signals of subsidence of 28 mm/y to 40 mm/y were chosen to investigate the phenomenon: Guarulhos (Sao Paulo International Airport), the Greater Sao Paulo, Itaquera and Sao Caetano do Sul. The coverage area of the signals was between 0.6 km and 1.65 km of length. All areas are located above a sedimentary type of aquifer. Itaquera and Sao Caetano do Sul showed signals varying from 28 mm/y to 32 mm/y. On the other hand, the places most likely to be suffering from stronger subsidence are the ones in the Greater Sao Paulo and Guarulhos, right beside the International Airport of Sao Paulo. The rate of displacement observed in both regions goes from 35 mm/y to 40 mm/y. Previous investigations of the water use at the International Airport highlight the risks of excessive water extraction that was being done through 9 deep wells. Therefore, it is affirmed that subsidence events are likely to occur and to cause serious damage in the area. This study could show a situation that has not been explored with proper importance in the city, given its social and economic consequences. Since the data were only available until 2011, the question that remains is if the situation still persists. It could be reaffirmed, however, a scenario of risk at the International Airport of Sao Paulo that needs further investigation.

Keywords: ground subsidence, Interferometric Satellite Aperture Radar (InSAR), metropolitan region of Sao Paulo, water extraction

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Authors: M. Maatar, M. Mekadem, M. Medale, B. Hadjed, B. Imine

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In this paper, numerical simulations have been carried out to study the performances of a flapping wing used as an energy collector. Metamodeling and genetic algorithms are used to detect the optimal configuration, improving power coefficient and/or efficiency. Radial basis functions and genetic algorithms have been applied to solve this problem. Three optimization factors are controlled, namely dimensionless heave amplitude h₀, pitch amplitude θ₀ and flapping frequency f. ANSYS FLUENT software has been used to solve the principal equations at a Reynolds number of 1100, while the heave and pitch motion of a NACA0015 airfoil has been realized using a developed function (UDF). The results reveal an average power coefficient and efficiency of 0.78 and 0.338 with an inexpensive low-fidelity model and a total relative error of 4.1% versus the simulation. The performances of the simulated optimum RBF-NSGA-II have been improved by 1.2% compared with the validated model.

Keywords: numerical simulation, flapping wing, energy extraction, power coefficient, efficiency, RBF, NSGA-II

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Authors: L. Richter, J. Lübkemann, P. Nyhuis

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In order to remain competitive in what is a turbulent environment; businesses must be able to react rapidly to change. The past response to volatile market conditions was to introduce an element of flexibility to production. Nowadays, what is often required is a redesign of factory structures in order to cope with the state of constant flux. The Institute of Production Systems and Logistics is currently developing a descriptive and causal model for the redesign of plant structures as part of an ongoing research project. This article presents the first research findings attained in devising this model.

Keywords: change driven factory redesign, factory planning, plant structure, flexibility

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Authors: Nour S. Abdelrahman, Seunghyun Hong, Hassan A. Arafat, Daniel Choi, Faisal Al Marzooqi

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Abstract—The advancement of lithium extraction methods from water sources, particularly saltwater brine, is gaining prominence in the lithium recovery industry due to its cost-effectiveness. Traditional techniques like recrystallization, chemical precipitation, and solvent extraction for metal recovery from seawater or brine are energy-intensive and exhibit low efficiency. Moreover, the extensive use of organic solvents poses environmental concerns. As a result, there's a growing demand for environmentally friendly lithium recovery methods. Membrane-based separation technology has emerged as a promising alternative, offering high energy efficiency and ease of continuous operation. In our study, we explored the potential of lithium-selective sieve channels constructed from layers of 2D graphene oxide and MXene (transition metal carbides and nitrides), integrated with surface – SO₃₋ groups. The arrangement of these 2D sheets creates interplanar spacing ranging from 0.3 to 0.8 nm, which forms a barrier against multivalent ions while facilitating lithium-ion movement through nano capillaries. The introduction of the sulfonate group provides an effective pathway for Li⁺ ions, with a calculated binding energy of Li⁺ – SO³⁻ at – 0.77 eV, the lowest among monovalent species. These modified membranes demonstrated remarkably rapid transport of Li⁺ ions, efficiently distinguishing them from other monovalent and divalent species. This selectivity is achieved through a combination of size exclusion and varying binding affinities. The graphene oxide channels in these membranes showed exceptional inter-cation selectivity, with a Li⁺/Mg²⁺ selectivity ratio exceeding 104, surpassing commercial membranes. Additionally, these membranes achieved over 94% rejection of MgCl₂.

Keywords: ion permeation, lithium extraction, membrane-based separation, nanotechnology

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Authors: Yagya Raj Pandeya, Joonwhoan Lee

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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

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Authors: Alma Gómez-Loredo, José González-Valdez, Jorge Benavides, Marco Rito-Palomares

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Fucoxanthin is a carotenoid that exerts multiple beneficial effects on human health, including antioxidant, anti-cancer, antidiabetic and anti-obesity activity; making the development of a whole process for its production and recovery an important contribution. In this work, the lab-scale production and purification of fucoxanthin in Isocrhysis galbana have been studied. In batch cultures, low light intensities (13.5 μmol/m2s) and bubble agitation were the best conditions for production of the carotenoid with product yields of up to 0.143 mg/g. After fucoxanthin ethanolic extraction from biomass and hexane partition, further recovery and purification of the carotenoid has been accomplished by means of alcohol – salt Aqueous Two-Phase System (ATPS) extraction followed by an ultrafiltration (UF) step. An ATPS comprised of ethanol and potassium phosphate (Volume Ratio (VR) =3; Tie-line Length (TLL) 60% w/w) presented a fucoxanthin recovery yield of 76.24 ± 1.60% among the studied systems and was able to remove 64.89 ± 2.64% of the carotenoid and chlorophyll pollutants. For UF, the addition of ethanol to the original recovered ethanolic ATPS stream to a final relation of 74.15% (w/w) resulted in a reduction of approximately 16% of the protein contents, increasing product purity with a recovery yield of about 63% of the compound in the permeate stream. Considering the production, extraction and primary recovery (ATPS and UF) steps, around a 45% global fucoxanthin recovery should be expected. Although other purification technologies, such as Centrifugal Partition Chromatography are able to obtain fucoxanthin recoveries of up to 83%, the process developed in the present work does not require large volumes of solvents or expensive equipment. Moreover, it has a potential for scale up to commercial scale and represents a cost-effective strategy when compared to traditional separation techniques like chromatography.

Keywords: aqueous two-phase systems, fucoxanthin, Isochrysis galbana, microalgae, ultrafiltration

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Authors: Tamrat Tesfaye, Bruce Sithole

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Box-Behnken Response surface methodology was used to determine the optimum processing conditions that give maximum extraction yield and whiteness index from mango seed. The steeping time ranges from 2 to 12 hours and slurring of the steeped seed in sodium metabisulphite solution (0.1 to 0.5 w/v) was carried out. Experiments were designed according to Box-Behnken Design with these three factors and a total of 15 runs experimental variables of were analyzed. At linear level, the concentration of sodium metabisulphite had significant positive influence on percentage yield and whiteness index at p<0.05. At quadratic level, sodium metabisulphite concentration and sodium metabisulphite concentration2 had a significant negative influence on starch yield; sodium metabisulphite concentration and steeping time*temperature had significant (p<0.05) positive influence on whiteness index. The adjusted R2 above 0.8 for starch yield (0.906465) and whiteness index (0.909268) showed a good fit of the model with the experimental data. The optimum sodium metabisulphite concentration, steeping hours, and temperature for starch isolation with maximum starch yield (66.428%) and whiteness index (85%) as set goals for optimization with the desirability of 0.91939 was 0.255w/v concentration, 2hrs and 50 °C respectively. The determined experimental value of each response based on optimal condition was statistically in accordance with predicted levels at p<0.05. The Mango seeds are the by-products obtained during mango processing and possess disposal problem if not handled properly. The substitution of food based sizing agents with mango seed starch can contribute as pertinent resource deployment for value-added product manufacturing and waste utilization which might play significance role of food security in Ethiopia.

Keywords: mango, synthetic sizing agent, starch, extraction, textile, sizing

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Authors: Sadam Elayah

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Background: One of the most critical competencies in advanced dentistry is alveolar ridge preservation after exodontia. The aim of this clinical trial was to assess the impact of autologous concentrated growth factor (CGF) as a socket-filling material and its ridge preservation properties following the lower third molar extraction. Materials and Methods: A total of 60 sides of 30 participants who had completely symmetrical bilateral impacted lower third molars were enrolled. The short-term outcome variables were wound healing, swelling and pain, clinically assessed at different time intervals (1st, 3rd & 7th days). While the long-term outcome variables were bone height & width, bone density and socket surface area in the coronal section. Cone beam computed tomography images were obtained immediately after surgery and three months after surgery as a temporal measure. Randomization was achieved by opaque, sealed envelopes. Follow-up data were compared to baseline using Paired & Unpaired t-tests. Results: The wound healing index was significantly better in the test sides (P =0.001). Regarding the facial swelling, the test sides had significantly fewer values than the control sides, particularly on the 1st (1.01±.57 vs 1.55 ±.56) and 3rd days (1.42±0.8 vs 2.63±1.2) postoperatively. Nonetheless, the swelling disappeared within the 7th day on both sides. The pain scores of the visual analog scale were not a statistically significant difference between both sides on the 1st day; meanwhile, the pain scores were significantly lower on the test sides compared with the control sides, especially on the 3rd (P=0.001) and 7th days (P˂0.001) postoperatively. Regarding long-term outcomes, CGF sites had higher values in height and width when compared to Control sites (Buccal wall 32.9±3.5 vs 29.4±4.3 mm, Lingual wall 25.4±3.5 vs 23.1±4 mm, and Alveolar bone width 21.07±1.55vs19.53±1.90 mm) respectively. Bone density showed significantly higher values in CGF sites than in control sites (Coronal half 200±127.3 vs -84.1±121.3, Apical half 406.5±103 vs 64.2±158.6) respectively. There was a significant difference between both sites in reducing periodontal pockets. Conclusion: CGF application following surgical extraction provides an easy, low-cost, and efficient option for alveolar ridge preservation. Thus, dentists may encourage using CGF during dental extractions, particularly when alveolar ridge preservation is required.

Keywords: platelet, extraction, impacted teeth, alveolar ridge, regeneration, CGF

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Authors: Abraham Dayan

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Remediation of soil containing volatile contaminants is often conducted by vapor extraction (SVE) technique. The operation is based on injection of air at ambient temperatures with or without thermal soil warming. Thermal enhancements of soil vapor extraction (TESVE) processes are usually conducted by soil heating, sometimes assisted by added steam injections. The current study addresses a technique which has not received adequate attention and is based on using exclusively hot air as an alternative to the common TESVE practices. To demonstrate the merit of the hot air TESVE technique, a sandy soil containing contaminated water is studied. Numerical and analytical tools were used to evaluate the rate of decontamination processes for various geometries and operating conditions. The governing equations are based on the Darcy law and are applied to an expanding compressible flow within a sandy soil. The equations were solved to determine the minimal time required for complete soil remediation. An approximate closed form solution was developed based on the assumption of local thermodynamic equilibrium and on a linearized representation of temperature dependence of the vapor to air density ratio. The solution is general in nature and offers insight into the governing processes of the soil remediation operation, where self-similar temperature profiles under certain conditions may exist, and the noticeable role of the contaminants evaporation and recondensation processes in affecting the remediation time. Based on analyses of the hot air TESVE technique, it is shown that it is sufficient to heat the air during a certain period of the decontamination process without compromising its full advantage, and thereby, entailing a minimization of the air-heating-energy requirements. This in effect is achieved by regeneration, leaving the energy stored in the soil during the early period of the remediation process to heat the subsequently injected ambient air, which infiltrates through it for the decontamination of the remaining untreated soil zone. The characteristic time required to complete SVE operations are calculated as a function of, both, the injected air temperature and humidity. For a specific set of conditions, it is demonstrated that elevating the injected air temperature by 20oC, the hot air injection technique reduces the soil remediation time by 50%, while requiring 30% of additional energy consumption. Those evaluations clearly unveil the advantage of the hot air SVE process, which for insignificant cost of added air heating energy, the substantial cost expenditures for manpower and equipment utilization are reduced.

Keywords: Porous Media, Soil Decontamination, Hot Air, Vapor Extraction

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