Search results for: Infiltration extraction method

Authors: Jiahao Cui

Abstract:

In the past centuries, due to climate change and intense whaling, the global whale population has dramatically declined. Among the various whale species, the fin whale experienced the most drastic drop in number due to its popularity in whaling. Under this background, identifying fin whale calls could be immensely beneficial to the preservation of the species. This paper uses feature extraction to process the input audio signal, then a network based on AlexNet and three networks based on the ResNet model was constructed to classify fin whale calls. A mixture of the DOSITS database and the Watkins database was used during training. The results demonstrate that a modified ResNet network has the best performance considering precision and network complexity.

Keywords: convolutional neural network, ResNet, AlexNet, fin whale preservation, feature extraction

Procedia PDF Downloads 122

Authors: Jasbir Arora, Indu Talwar, Daisy Sahni, Vidya Rattan

Abstract:

Introduction: Age estimation is a crucial step to build the identity of a person, both in case of deceased and alive. In adults, age can be estimated on the basis of six regressive (Attrition, Secondary dentine, Dentine transparency, Root resorption, Cementum apposition and Periodontal Disease) changes in teeth qualitatively using scoring system and quantitatively by micrometric method. The present research was designed to establish the reliability of qualitative (method 1) and quantitative (method 2) of age estimation among North Indians and to compare the efficacy of these two methods. Method: 250 single-rooted extracted teeth (18-75 yrs.) were collected from Department of Oral Health Sciences, PGIMER, Chandigarh. Before extraction, periodontal score of each tooth was noted. Labiolingual sections were prepared and examined under light microscope for regressive changes. Each parameter was scored using Gustafson’s 0-3 point score system (qualitative), and total score was calculated. For quantitative method, each regressive change was measured quantitatively in form of 18 micrometric parameters under microscope with the help of measuring eyepiece. Age was estimated using linear and multiple regression analysis in Gustafson’s method and Kedici’s method respectively. Estimated age was compared with actual age on the basis of absolute mean error. Results: In pooled data, by Gustafson’s method, significant correlation (r= 0.8) was observed between total score and actual age. Total score generated an absolute mean error of ±7.8 years. Whereas, for Kedici’s method, a value of correlation coefficient of r=0.5 (p<0.01) was observed between all the eighteen micrometric parameters and known age. Using multiple regression equation, age was estimated, and an absolute mean error of age was found to be ±12.18 years. Conclusion: Gustafson’s (qualitative) method was found to be a better predictor for age estimation among North Indians.

Keywords: forensic odontology, age estimation, North India, teeth

Procedia PDF Downloads 242

Authors: Andrey Khalov

Abstract:

The rapid growth of unstructured data necessitates advanced methods for transforming raw information into structured knowledge, particularly in domain-specific contexts such as IT service management and outsourcing. This paper presents a methodology for automatically constructing domain ontologies using the DOLCE framework as the base ontology. The research focuses on expanding ITIL-based ontologies by integrating concepts from ITSMO, followed by the extraction of entities and relationships from domain-specific texts through transformers and statistical methods like formal concept analysis (FCA). In particular, this work introduces an R-GNN-based approach for ontology mapping, enabling more efficient entity extraction and ontology alignment with existing knowledge bases. Additionally, the research explores transfer learning techniques using pre-trained transformer models (e.g., DeBERTa-v3-large) fine-tuned on synthetic datasets generated via large language models such as LLaMA. The resulting ontology, termed IT Ontology (ITO), is evaluated against existing methodologies, highlighting significant improvements in precision and recall. This study advances the field of ontology engineering by automating the extraction, expansion, and refinement of ontologies tailored to the IT domain, thus bridging the gap between unstructured data and actionable knowledge.

Keywords: ontology mapping, knowledge graphs, R-GNN, ITIL, NER

Procedia PDF Downloads 15

Authors: Zuhal Kurt, Meral Kurt, Bilge T. Bal, Kemal Ozkan

Abstract:

Shade matching and reproduction is the most important element of success in prosthetic dentistry. Until recently, shade matching procedure was implemented by dentists visual perception with the help of shade guides. Since many factors influence visual perception; tooth shade matching using visual devices (shade guides) is highly subjective and inconsistent. Subjective nature of this process has lead to the development of instrumental devices. Nowadays, colorimeters, spectrophotometers, spectroradiometers and digital image analysing systems are used for instrumental shade selection. Instrumental devices have advantages that readings are quantifiable, can obtain more rapidly and simply, objectively and precisely. However, these devices have noticeable drawbacks. For example, translucent structure and irregular surfaces of teeth lead to defects on measurement with these devices. Also between the results acquired by devices with different measurement principles may make inconsistencies. So, its obligatory to search for new methods for dental shade matching process. A computer-aided system device; digital camera has developed rapidly upon today. Currently, advances in image processing and computing have resulted in the extensive use of digital cameras for color imaging. This procedure has a much cheaper process than the use of traditional contact-type color measurement devices. Digital cameras can be taken by the place of contact-type instruments for shade selection and overcome their disadvantages. Images taken from teeth show morphology and color texture of teeth. In last decades, a new method was recommended to compare the color of shade tabs taken by a digital camera using color features. This method showed that visual and computer-aided shade matching systems should be used as concatenated. Recently using methods of feature extraction techniques are based on shape description and not used color information. However, color is mostly experienced as an essential property in depicting and extracting features from objects in the world around us. When local feature descriptors with color information are extended by concatenating color descriptor with the shape descriptor, that descriptor will be effective on visual object recognition and classification task. Therefore, the color descriptor is to be used in combination with a shape descriptor it does not need to contain any spatial information, which leads us to use local histograms. This local color histogram method is remain reliable under variation of photometric changes, geometrical changes and variation of image quality. So, coloring local feature extraction methods are used to extract features, and also the Scale Invariant Feature Transform (SIFT) descriptor used to for shape description in the proposed method. After the combination of these descriptors, the state-of-art descriptor named by Color-SIFT will be used in this study. Finally, the image feature vectors obtained from quantization algorithm are fed to classifiers such as Nearest Neighbor (KNN), Naive Bayes or Support Vector Machines (SVM) to determine label(s) of the visual object category or matching. In this study, SVM are used as classifiers for color determination and shade matching. Finally, experimental results of this method will be compared with other recent studies. It is concluded from the study that the proposed method is remarkable development on computer aided tooth shade determination system.

Keywords: classifiers, color determination, computer-aided system, tooth shade matching, feature extraction

Procedia PDF Downloads 444

Authors: Sanaa I. Abu Alasal, Madleen M. Esbeih, Eman R. Fayyad, Rami S. Gharaibeh, Mostafa Z. Ali, Ahmed A. Freewan, Monther M. Jamhawi

Abstract:

This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Keywords: meshes, point clouds, surface reconstruction protocols, 3D reconstruction

Procedia PDF Downloads 457

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

Procedia PDF Downloads 78

Authors: I. Berger, N. Machour, F. Portet-Koltalo

Abstract:

Polycyclic aromatic hydrocarbons (PAHs) are toxic and carcinogenic pollutants produced in majority by incomplete combustion processes in industrialized and urbanized areas. After being emitted in atmosphere, these persistent contaminants are deposited to soils or sediments. Even if persistent, some can be partially degraded (photodegradation, biodegradation, chemical oxidation) and they lead to oxygenated metabolites (oxy-PAHs) which can be more toxic than their parent PAH. Oxy-PAHs are less measured than PAHs in sediments and this study aims to compare different analytical tools in order to extract and quantify a mixture of four hydroxylated PAHs (OH-PAHs) and four carbonyl PAHs (quinones) in sediments. Methodologies: Two analytical systems – HPLC with on-line UV and fluorescence detectors (HPLC-UV-FLD) and GC coupled to a mass spectrometer (GC-MS) – were compared to separate and quantify oxy-PAHs. Microwave assisted extraction (MAE) was optimized to extract oxy-PAHs from sediments. Results: First OH-PAHs and quinones were analyzed in HPLC with on-line UV and fluorimetric detectors. OH-PAHs were detected with the sensitive FLD, but the non-fluorescent quinones were detected with UV. The limits of detection (LOD)s obtained were in the range (2-3)×10-4 mg/L for OH-PAHs and (2-3)×10-3 mg/L for quinones. Second, even if GC-MS is not well adapted to the analysis of the thermodegradable OH-PAHs and quinones without any derivatization step, it was used because of the advantages of the detector in terms of identification and of GC in terms of efficiency. Without derivatization, only two of the four quinones were detected in the range 1-10 mg/L (LODs=0.3-1.2 mg/L) and LODs were neither very satisfying for the four OH-PAHs (0.18-0.6 mg/L). So two derivatization processes were optimized, comparing to literature: one for silylation of OH-PAHs, one for acetylation of quinones. Silylation using BSTFA/TCMS 99/1 was enhanced using a mixture of catalyst solvents (pyridine/ethyle acetate) and finding the appropriate reaction duration (5-60 minutes). Acetylation was optimized at different steps of the process, including the initial volume of compounds to derivatize, the added amounts of Zn (0.1-0.25 g), the nature of the derivatization product (acetic anhydride, heptafluorobutyric acid…) and the liquid/liquid extraction at the end of the process. After derivatization, LODs were decreased by a factor 3 for OH-PAHs and by a factor 4 for quinones, all the quinones being now detected. Thereafter, quinones and OH-PAHs were extracted from spiked sediments using microwave assisted extraction (MAE) followed by GC-MS analysis. Several mixtures of solvents of different volumes (10-25 mL) and using different extraction temperatures (80-120°C) were tested to obtain the best recovery yields. Satisfactory recoveries could be obtained for quinones (70-96%) and for OH-PAHs (70-104%). Temperature was a critical factor which had to be controlled to avoid oxy-PAHs degradation during the MAE extraction process. Conclusion: Even if MAE-GC-MS was satisfactory to analyze these oxy-PAHs, MAE optimization has to be carried on to obtain a most appropriate extraction solvent mixture, allowing a direct injection in the HPLC-UV-FLD system, which is more sensitive than GC-MS and does not necessitate a previous long derivatization step.

Keywords: derivatizations for GC-MS, microwave assisted extraction, on-line HPLC-UV-FLD, oxygenated PAHs, polluted sediments

Procedia PDF Downloads 287

Authors: F. Pedron, M. Grifoni, G. Petruzzelli, M. Barbafieri, I. Rosellini, B. Pezzarossa

Abstract:

Lead contamination of agricultural land mainly vegetated with perennial ryegrass (Lolium perenne) has been investigated. The metal derived from the discharge of sludge from a ceramic industry in the past had used lead paints. The results showed very high values of lead concentration in many soil samples. In order to assess the lead soil contamination, a sequential extraction with H₂O, KNO₃, EDTA was performed, and the chemical forms of lead in the soil were evaluated. More than 70% of lead was in a potentially bioavailable form. Analysis of Lolium perenne showed elevated lead concentration. A Freundlich-like model was used to describe the transferability of the metal from the soil to the plant.

Keywords: bioavailability, Freundlich-like equation, sequential extraction, soil lead contamination

Procedia PDF Downloads 310

Authors: Lila Boulekbache-Makhlouf, Brahmi Fatiha

Abstract:

This study was carried out with the aim of enriching fresh cheese with the food by-products, which are the leaves of shallots and the peels of potatoes. Firstly, the conditions for extracting the total polyphenols (TPP) using ultrasound are optimized. Then, the contents of PPT, flavonoids, and antioxidant activity were evaluated for the extracts obtained by adopting the optimal parameter. On the other hand, we have carried out some physico-chemical, microbiological, and sensory analyzes of the cheese produced. The maximum PPT value of 70.44 mg GAE/g DM of shallot leaves was reached with 40% (v/v) ethanol, an extraction time of 90 min, and a temperature of 10°C. Meanwhile, the maximum TPP content of potato peels of 45.03 ± 4.16 mg GAE/g DM was obtained using an ethanol/water mixture (40%, v/v), a time of 30 min, and a temperature of 60°C and the flavonoid contents were 13.99 and 7.52 QE/g DM, respectively. From the antioxidant tests, we deduced that the potato peels present a higher antioxidant power with IC50s of 125.42 ± 2.78 μg/mL for DPPH, of 87.21 ± 7.72 μg/mL for phosphomolybdate and 200.77 ± 13.38 μg/mL for iron chelation, compared with the results obtained for shallot leaves which were 204.29 ± 0.09, 45.85 ± 3,46 and 1004.10 ± 145.73 μg/mL, respectively. The results of the physico-chemical analyzes have shown that the formulated cheese was compliant with standards. Microbiological analyzes show that the hygienic quality of the cheese produced was satisfactory. According to the sensory analyzes, the experts liked the cheese enriched with the powder and pieces of the leaves of the shallots.

Keywords: shallots leaves, potato peels, ultrasound extraction, phenolic, cheese

Procedia PDF Downloads 184

Authors: Naser Safdarian, Nader Jafarnia Dabanloo

Abstract:

In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.

Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition

Procedia PDF Downloads 455

Authors: Gredson Keif Souza, Nehemias Curvelo Pereira

Abstract:

Kernel oil from Macaúba is an important source of essential fatty acids. Thus, a new knowledge of the oil of this species could be used in new applications, such as pharmaceutical drugs based in the manufacture of cosmetics, and in various industrial processes. The aim of this study was to characterize the kernel oil of macaúba (Acrocomia Totai) at different times of their maturation. The physico-chemical characteristics were determined in accordance with the official analytical methods of oils and fats. It was determined the content of water and lipids in kernel, saponification value, acid value, water content in the oil, viscosity, density, composition in fatty acids by gas chromatography and molar mass. The results submitted to Tukey test for significant value to 5%. Found for the unripe fruits values superior to unsaturated fatty acids.

Keywords: extraction, characterization, kernel oil, acrocomia totai

Procedia PDF Downloads 356

Authors: Maha Jazouli

Abstract:

Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

Procedia PDF Downloads 188

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

Procedia PDF Downloads 82

Authors: Soo Hyung Park, Seong Beom Kim, Wontae Lee, Jin Chul Joo, Jungmin Lee, Jongsoo Choi

Abstract:

A newly-developed electromagnetically vibrated solid-phase microextraction (SPME) device for extracting nonpolar organic compounds from aqueous matrices was evaluated in terms of sorption equilibrium time, precision, and detection level relative to three other more conventional extraction techniques involving SPME, viz., static, magnetic stirring, and fiber insertion/retraction. Electromagnetic vibration at 300~420 cycles/s was found to be the most efficient extraction technique in terms of reducing sorption equilibrium time and enhancing both precision and linearity. The increased efficiency for electromagnetic vibration was attributed to a greater reduction in the thickness of the stagnant-water layer that facilitated more rapid mass transport from the aqueous matrix to the SPME fiber. Electromagnetic vibration less than 500 cycles/s also did not detrimentally impact the sustainability of the extracting performance of the SPME fiber. Therefore, electromagnetically vibrated SPME may be a more powerful tool for rapid sampling and solvent-free sample preparation relative to other more conventional extraction techniques used with SPME.

Keywords: electromagnetic vibration, organic compounds, precision, solid-phase microextraction (SPME), sorption equilibrium time

Procedia PDF Downloads 254

Authors: Thelma Palaoag, Melanie Basa, Jezreel Mark Panilo

Abstract:

Checking short-answer questions and essays, whether it may be paper or electronic in form, is a tiring and tedious task for teachers. Evaluating a student’s output require wide array of domains. Scoring the work is often a critical task. Several attempts in the past few years to create an automated writing assessment software but only have received negative results from teachers and students alike due to unreliability in scoring, does not provide feedback and others. The study aims to create an application that will be able to check short-answer questions which incorporate information extraction. Information extraction is a subfield of Natural Language Processing (NLP) where a chunk of text (technically known as unstructured text) is being broken down to gather necessary bits of data and/or keywords (structured text) to be further analyzed or rather be utilized by query tools. The proposed system shall be able to extract keywords or phrases from the individual’s answers to match it into a corpora of words (as defined by the instructor), which shall be the basis of evaluation of the individual’s answer. The proposed system shall also enable the teacher to provide feedback and re-evaluate the output of the student for some writing elements in which the computer cannot fully evaluate such as creativity and logic. Teachers can formulate, design, and check short answer questions efficiently by defining keywords or phrases as parameters by assigning weights for checking answers. With the proposed system, teacher’s time in checking and evaluating students output shall be lessened, thus, making the teacher more productive and easier.

Keywords: information extraction, short-answer question, natural language processing, application

Procedia PDF Downloads 428

Authors: Pranjali Avinash Yadav-Deshmukh

Abstract:

Remarkable development of the Internet along with the new technological innovation, such as high-speed systems and affordable large storage space have led to a tremendous increase in the amount and accessibility to digital records. For any person, studying of all these data is tremendously time intensive, so there is a great need to access effective multi-document summarization (MDS) systems, which can successfully reduce details found in several records into a short, understandable summary or conclusion. For semantic representation of textual details in ontology area, as a theoretical design, our system provides a significant structure. The stability of using the ontology in fixing multi-document summarization problems in the sector of catastrophe control is finding its recommended design. Saliency ranking is usually allocated to each phrase and phrases are rated according to the ranking, then the top rated phrases are chosen as the conclusion. With regards to the conclusion quality, wide tests on a selection of media announcements are appropriate for “Jammu Kashmir Overflow in 2014” records. Ontology centered multi-document summarization methods using “NLP centered extraction” outshine other baselines. Our participation in recommended component is to implement the details removal methods (NLP) to enhance the results.

Keywords: disaster management, extraction technique, k-means, multi-document summarization, NLP, ontology, sentence extraction

Procedia PDF Downloads 386

Authors: Alexandre Chagnes

Abstract:

Lithium-ion battery is the technology of choice in the development of electric vehicles. This technology is now mature, although there are still many challenges to increase their energy density while ensuring an irreproachable safety of use. For this goal, it is necessary to develop new cathodic materials that can be cycled at higher voltages and electrolytes compatible with these materials. But the challenge does not only concern the production of efficient batteries for the electrochemical storage of energy since lithium-ion battery technology relies on the use of critical and/or strategic value resources. It is, therefore, crucial to include Lithium-ion batteries development in a circular economy approach very early. In particular, optimized recycling and reuse of battery components must both minimize their impact on the environment and limit geopolitical issues related to tensions on the mineral resources necessary for lithium-ion battery production. Although recycling will never replace mining, it reduces resource dependence by ensuring the presence of exploitable resources in the territory, which is particularly important for countries like France, where exploited or exploitable resources are limited. This conference addresses the development of a new hydrometallurgical process combining leaching of cathodic material from spent lithium-ion battery in acidic chloride media and solvent extraction process. Most of recycling processes reported in the literature rely on the sulphate route, and a few studies investigate the potentialities of the chloride route despite many advantages and the possibility to develop new chemistry, which could get easier the metal separation. The leaching mechanisms and the solvent extraction equilibria will be presented in this conference. Based on the comprehension of the physicochemistry of leaching and solvent extraction, the present study will introduce a new hydrometallurgical process for the production of cobalt, nickel, manganese and lithium from spent cathodic materials.

Keywords: lithium-ion battery, recycling, hydrometallurgy, leaching, solvent extraction

Procedia PDF Downloads 80

Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi

Abstract:

In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.

Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture

Procedia PDF Downloads 432

Authors: Amir Ngah, Masita Abdul Jalil, Zailani Abdullah

Abstract:

The aim of software maintenance is to maintain the software system in accordance with advancement in software and hardware technology. One of the early works on software maintenance is to extract information at higher level of abstraction. In this paper, we present the process of how to design an information extraction tool for software maintenance. The tool can extract the basic information from old program such as about variables, based classes, derived classes, objects of classes, and functions. The tool have two main part; the lexical analyzer module that can read the input file character by character, and the searching module which is user can get the basic information from existing program. We implemented this tool for a patterned sub-C++ language as an input file.

Keywords: extraction tool, software maintenance, reverse engineering, C++

Procedia PDF Downloads 491

Authors: H. Mayton, X. Yan, A. G. Taylor

Abstract:

Infested tomato seeds were used to investigate the influence of Xanthomonas euvesicatoria on germination and seed to seedling transmission in a controlled environment and greenhouse assays in an effort to develop effective seed treatments and characterize seed borne transmission of bacterial leaf spot of tomato. Bacterial leaf spot of tomato, caused by four distinct Xanthomonas species, X. euvesicatoria, X. gardneri, X. perforans, and X. vesicatoria, is a serious disease worldwide. In the United States, disease prevention is expensive for commercial growers in warm, humid regions of the country, and crop losses can be devastating. In this study, four different infested tomato seed lots were extracted from tomato fruits infected with bacterial leaf spot from a field in New York State in 2017 that had been inoculated with X. euvesicatoria. In addition, vacuum infiltration at 61 kilopascals for 1, 5, 10, and 15 minutes and seed soaking for 5, 10, 15, and 30 minutes with different bacterial concentrations were used to artificially infest seed in the laboratory. For controlled environment assays, infested tomato seeds from the field and laboratory were placed othe n moistened blue blotter in square plastic boxes (10 cm x 10 cm) and incubated at 20/30 ˚C with an 8/16 hour light cycle, respectively. Infested tomato seeds from the field and laboratory were also planted in small plastic trays in soil (peat-lite medium) and placed in the greenhouse with 24/18 ˚C day and night temperatures, respectively, with a 14-hour photoperiod. Seed germination was assessed after eight days in the laboratory and 14 days in the greenhouse. Polymerase chain reaction (PCR) using the hrpB7 primers (RST65 [5’- GTCGTCGTTACGGCAAGGTGGTG-3’] and RST69 [5’-TCGCCCAGCGTCATCAGGCCATC-3’]) was performed to confirm presence or absence of the bacterial pathogen in seed lots collected from the field and in germinating seedlings in all experiments. For infested seed lots from the field, germination was lowest (84%) in the seed lot with the highest level of bacterial infestation (55%) and ranged from 84-98%. No adverse effect on germination was observed from artificially infested seeds for any bacterial concentration and method of infiltration when compared to a non-infested control. Germination in laboratory assays for artificially infested seeds ranged from 82-100%. In controlled environment assays, 2.5 % were PCR positive for the pathogen, and in the greenhouse assays, no infected seedlings were detected. From these experiments, X. euvesicatoria does not appear to adversely influence germination. The lowest rate of germination from field collected seed may be due to contamination with multiple pathogens and saprophytic organisms as no effect of artificial bacterial seed infestation in the laboratory on germination was observed. No evidence of systemic movement from seed to seedling was observed in the greenhouse assays; however, in the controlled environment assays, some seedlings were PCR positive. Additional experiments are underway with green fluorescent protein-expressing isolates to further characterize seed to seedling transmission of the bacterial leaf spot pathogen in tomato.

Keywords: bacterial leaf spot, seed germination, tomato, Xanthomonas euvesicatoria

Procedia PDF Downloads 134

Authors: Reut Lanyado, David Mendlovic

Abstract:

Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.

Keywords: authentication, feature extraction, hand recognition, security, signal processing

Procedia PDF Downloads 126

Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

Abstract:

This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: microwave filter, scattering parameter, coupling matrix, intelligent tuning

Procedia PDF Downloads 311

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

Abstract:

Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

Procedia PDF Downloads 76

Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

Abstract:

Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

Procedia PDF Downloads 226

Authors: Ahmed Fradi

Abstract:

In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

Procedia PDF Downloads 540

Authors: Rajesh S. Mony, Vaidyaratnam Oushadhasala

Abstract:

An attempt is made in this study to evolve a drug development modality based on classical Ayurvedic knowledge base as well as on modern scientific methodology. The present study involves (a) identification of a specific ailment condition, (b) the selection of a polyherbal formulation, (c) deciding suitable extraction procedure, (d) confirming the efficacy of the combination by in-vitro trials and (e) fixing up the recommended dose. The ailment segment selected is arthritic condition. The selected herbal combination is Kunturushka, Vibhitaki, Guggulu, Haridra, Maricha and Nirgundi. They were selected as per Classical Ayurvedic references, Authentified as per API (Ayurvedic Pharmacopeia of India), Extraction of each drug was done by different ratios of Hydroalcoholic menstrums, Invitro assessment of each extract after removing residual solvent for anti-Inflammatory, anti-arthritic activities (by UV-Vis. Spectrophotometer with positive control), Invitro assessment of each extract for COX enzyme inhibition (by UV-Vis. Spectrophotometer with positive control), Selection of the extracts was made having good in-vitro activity, Performed the QC testing of each selected extract including HPTLC, that is the in process QC specifications, h. Decision of the single dose with mixtures of selected extracts was made as per the level of in-vitro activity and available toxicology data, Quantification of major groups like Phenolics, Flavonoids, Alkaloids and Bitters was done with both standard Spectrophotometric and Gravimetric methods, Method for Marker assay was developed and validated by HPTLC and a good resolved HPTLC finger print was developed for the single dosage API (Active Pharmaceutical Ingredient mixture of extracts), Three batches was prepared to fix the in process and API (Active Pharmaceutical Ingredient) QC specifications.

Keywords: drug development, antiinflammatory, quality stardardisation, planar chromatography

Procedia PDF Downloads 99

Authors: Majid Forghani, Michael Khachay

Abstract:

In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition

Procedia PDF Downloads 154

Authors: Omasan Urhie Urhie, Adenipekun C. O, Eke W., Ogwu K., Erinle K. O

Abstract:

Polychlorinated Biphenyls (PCBs) are Persistent organic pollutants (POPs) that are very toxic; they possess ability to accumulate in soil and in human tissues hence resulting in health issues like birth defect, reproductive disorder and cancer. The air is polluted by PCBs through volatilization and dispersion; they also contaminate soil and sediments and are not easily degraded. Soil samples were collected from a depth of 0-15 cm from three substations (Warri, Ughelli and Ibadan) of Power Holding Company of Nigeria (PHCN) where old transformers were dumped in Nigeria. Extraction and cleanup of soil samples were conducted using Accelerated Solvent Extraction (ASE) with Pressurized Liquid extraction (PLE). The concentration of PCBs was determined using gsas chromatography/mass spectrometry (GC/MS). Mean total PCB concentrations in the soil samples increased in the order Ughelli ˂ Ibadan˂ Warri, 2.457757ppm Ughelli substation 4.198926ppm, for Ibadan substation and 14.05065ppm at Warri substation. In the Warri samples, PCB-167 was the most abundant at about 30% (4.28086ppm) followed by PCB-157 at about 20% (2.77871), of the total PCB concentrations (14.05065ppm). Of the total PCBs in the Ughelli and Ibadan samples, PCB-156 was the most abundant at about 44% and 40%, respectively. This study provides a baseline report on the presence of PCBs in the vicinity of abandoned electrical power facilities in different cities in Nigeria.

Keywords: polychlorintated biphenyls, persistent organic pollutants, soil, transformer

Procedia PDF Downloads 139

Authors: Yi Anson Lam, Siu Ming Yiu, Kam Pui Chow

Abstract:

Digital evidence has been tendering to courts at an exponential rate in recent years. As an industrial practice, most digital evidence is extracted and preserved using specialized and well-accepted forensics tools. On the other hand, the advancement in technologies enables the creation of quite a few emerging platforms such as Telegram, Signal etc. Existing (well-accepted) forensics tools were not designed to extract evidence from these emerging platforms. While new forensics tools require a significant amount of time and effort to be developed and verified, this paper tries to address how to fill this gap using quick-fix alternative methods for digital evidence collection (e.g., based on APIs provided by Apps) and discuss issues related to the admissibility of this evidence to courts with support from international courts’ stance and the circumstances of accepting digital evidence using these proposed alternatives.

Keywords: extraction, digital evidence, laws, investigation

Procedia PDF Downloads 67

Authors: Marivane Turim Koschevic, Maycon dos Santos, Marcello Lima Bertuci, Farayde Matta Fakhouri, Silvia Maria Martelli

Abstract:

Natural fibers are rich raw materials in cellulose and abundant in the world, its use for the cellulose nanocrystals extraction is promising as an example cited is the cattail, macrophyte native weed in South America. This study deals with the pre-treatment cattail of crushed fibers, at six different methods of mercerization, followed by the use of bleaching. As a result, have found The positive effects of treating fibers by means of optical microscopy and spectroscopy, Fourier transform (FTIR). The sample selected for future testing of cellulose nanocrystals extraction was treated in 2.5% NaOH for 2 h, 60 °C in the first stage and 30vol H2O2, NaOH 5% in the proportion 30/70% (v/v) for 1 hour 60 °C, followed by treatment at 50/50% (v/v) 15 minutes, 50°C, with the same constituents of the solution.

Keywords: cellulose nanocrystal, chemical treatment, mercerization, natural fibers

Procedia PDF Downloads 293