Search results for: time-frequency feature extraction

Authors: Andrii Natochii

Abstract:

The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.

Keywords: beam monitoring, channeling, particle tracking, Timepix detector

Procedia PDF Downloads 167

Authors: Zabihullah Mahdi, Khwaja Naweed Seddiqi, Shigeo Honma

Abstract:

Through many types of research and practical studies, it has been identified that the average oil recovery factor of a petroleum reservoir is about 30 to 35 %. This study is focused on enhanced oil recovery by laboratory experiment and graphical investigation based on Buckley-Leverett theory. Horizontal oil displacement by water, in a petroleum reservoir is analyzed under the Buckley-Leverett frontal displacement theory. The extraction and prerequisite of this theory are based and pursued focusing on the key factors that control displacement. The theory is executable to the waterflooding method, which is generally employed in petroleum engineering reservoirs to sustain oil production recovery, and the techniques for evaluating the average water saturation behind the water front and the oil recovery factors in the reservoirs are presented. In this paper, the Buckley-Leverett theory handled to an experimental model and the amount of recoverable oil are investigated to be over 35%. The irreducible water saturation, viz. connate water saturation, in the reservoir is also a significant inspiration for the recovery.

Keywords: Buckley-Leverett theory, waterflooding technique, petroleum engineering, immiscible displacement

Procedia PDF Downloads 232

Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

Abstract:

Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed, with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

Procedia PDF Downloads 594

Authors: H. Imad, Q. Cheah, J. Mohammad, O. Aamera

Abstract:

The aim of this study is twofold. One is to determine the genetic structure of Iraq population and the second objective of the study was to evaluate the importance of these loci for forensic genetic purposes. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. Twenty STR loci and Amelogenin including D3S1358, D13S317, PentaE, D16S539, D18S51, D2S1338, CSF1PO, Penta D, THO1, vWA, D21S11, D7S820, TPOX, D8S1179, FGA, D2S1338, D5S818, D6S1043, D12S391, D19S433, and Amelogenin amplified by using power plex21® kit. PCR products detected by genetic analyzer 3730xL then data analyzed by PowerStatsV1.2. Based on the allelic frequencies, several statistical parameters of genetic and forensic efficiency have been estimated. This includes the homozygosity and heterozygosity, effective number of alleles (n), the polymorphism information content (PIC), the power of discrimination (DP), and the power of exclusion (PE). The power of discrimination values for all tested loci was from 75% to 96% therefore, those loci can be safely used to establish a DNA-based database for Iraq population.

Keywords: autosomal STR, genetic variation, Middle and South of Iraq, statistical parameters

Procedia PDF Downloads 369

Authors: Azlin S Azmi, Mus’ab Zainal, Sarina Sulaiman, Azura Amid, Zaki Zainudin

Abstract:

Microalgae lipid is a promising feedstock for biodiesel production. The objective of this work was to study growth factors affecting marine mutant Synechococcus sp. (PCC 7002) for high lipid production. Four growth factors were investigated; nitrogen-phosporus-potassium (NPK) concentration, light intensity, temperature and NaNO3 concentration on mutant strain growth and lipid production were studied. Design Expert v8.0 was used to design the experimental and analyze the data. The experimental design selected was Min-Run Res IV which consists of 12 runs and the response surfaces measured were specific growth rate and lipid concentration. The extraction of lipid was conducted by chloroform/methanol solvents system. Based on the study, mutant Synechococcus sp. PCC 7002 gave the highest specific growth rate of 0.0014 h-1 at 0% NPK, 2500 lux, 40oC and 0% NaNO3. On the other hand, the highest lipid concentration was obtained at 0% NPK, 3500 lux, 30°C and 1% NaNO3.

Keywords: Cyanobacteria, lipid, mutant, marine Synechococcus sp. (PCC 7002), specific growth rate

Procedia PDF Downloads 315

Authors: Olga St. Tsiftsoglou, Diamanto M. Lazari, Eugene L. Kokkalou

Abstract:

Most of Alyssum species of Brassicaceae family have been mainly studied for their contribution in ecology. In this study, A. alyssoides was examined for its chemical substitutes. The methanol extract of its aerial parts was fractionated with liquid-liquid extraction (distribution) with four different solvents of increasing polarity: diethyl ether, ethyl acetate, 1-butanol and water. The diethyl ether and ethyl acetate extracts were further studied for their chemical composition. So far, secondary metabolites which belong to phenolics were isolated by using several chromatographic methods (C.C. and HPLC) and were identified by using spectroscopic methods (UV/Vis, NMR and MS): two phenolic acids (p-hydroxy-benzoic acid and 3-methoxy-4-hydroxy-benzoic acid (vanillic acid)), and five flavonoids, which are derivatives of flavonol: kaempferol 3-O-β-D-glucopyranoside (astragalin), kaempferol 3-O-(6′′-α-L-rhamnopyranosyl)-β-D-glucopyranoside (nicotiflorin), quercetin 3-O-β-D-glucopyranoside (isoquercetin), isorhamnetin-3-O-β-D-glucopyranoside, and isoramnetin 3-O-(6′′-α-L-rhamnopyranosyl)-β-D-glucopyranoside (narcissin).

Keywords: Alyssum, chemical substitutes, flavonoids, phenolic acids

Procedia PDF Downloads 302

Authors: Viktorija Sabaliauskaitė, Arūnas Balčiūnas, Renata Rubavičiūtė

Abstract:

Research on microplastic pollution in aquatic environments is being conducted worldwide. This presented research focused on the South-Eastern Baltic Sea, where, due to the natural conditions, algae accumulation on beaches is common. The present conditions enabled to apply and integrate of various microplastic extraction techniques: filtration, density separation, and sample aeration in order to investigate the microplastic concentrations within different beach compartments (nearshore water reference zone, nearshore algal scum zone, beach surface sand reference zone, beach wrack zone). This study demonstrates results from a total of 496 collected samples. The comparison of microplastic mean concentrations in water-based (0,016 item/cm³) and land-based (0,29 item/cm³) samples gave a clear insight into the microplastic accumulation hot spots, which pose pollution hazards to marine ecosystems and humans.

Keywords: beach wrack, marine litter, microplastics, pollution

Procedia PDF Downloads 42

Authors: Veena Nair, Srikanth Prakash, Mayuri Wijayasundara

Abstract:

Globally, the textile industry is a key contributor to the generation of solid waste which gets landfilled. Textile waste generation generally occurs in three stages, namely: producer waste, pre-consumer waste, and post-consumer waste. However, the different processes adopted in textile material extraction, manufacturing, and use have their respective impact in terms of the quantity of waste being diverted to landfills. The study is focused on assessing the value chains of the two most common textile fibres: cotton and polyester, catering to a broad categories of apparel products. This study attempts to identify and evaluate the key processes adopted by the textile industry at each of the stages in their value chain in terms of waste generation. The different processes identified in each of the stages in the textile value chains are mapped to their respective contribution in generating fibre waste which eventually gets diverted to landfill. The results of the study are beneficial for the overall industry in terms of improving the traceability of waste in the value chains and the selection of processes and behaviours facilitating the reduction of environmental impacts associated with landfills.

Keywords: textile waste, textile value chains, landfill waste, waste mapping

Procedia PDF Downloads 184

Authors: Amine Ganibardi, Cherif Arab Ali

Abstract:

This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

Procedia PDF Downloads 161

Authors: Priya Arora, Ashutosh Mishra

Abstract:

Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

Procedia PDF Downloads 122

Authors: Lee Myung-Won, Kwak Keun-Chang

Abstract:

This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

Procedia PDF Downloads 304

Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

Procedia PDF Downloads 259

Authors: Rajkumar Ghosh

Abstract:

Water scarcity is a significant challenge in urban areas, even in smart cities (Lucknow, Bangalore, Jaipur, etc.) where efficient resource management is prioritized. The depletion of groundwater resources in Gomti Nagar, Lucknow, Uttar Pradesh, India is particularly severe, posing a significant challenge for sustainable development in the region. This study focuses on addressing the water shortage by investigating the effectiveness of rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to bridge the gap between groundwater recharge and extraction. The aim of this study is to assess the effectiveness of RTRWHs in reducing aquifer depletion and addressing the water scarcity issue in the Gomti Nagar region. The research methodology involves the utilization of RTRWHs as the primary method for collecting rainwater. RTRWHs will be implemented in residential and commercial buildings to maximize the collection of rainwater. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. Statistical analysis and modelling techniques were employed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed using statistical analysis and modelling techniques to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. Widespread adoption of RTRWHs in all buildings and integration into urban planning and development processes are crucial for efficient water management in smart cities like Gomti Nagar. These findings can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis.

Keywords: water scarcity, urban areas, smart cities, resource management, groundwater depletion, rooftop rainwater harvesting systems, sustainable development, sustainable water management, mitigating water scarcity

Procedia PDF Downloads 55

Authors: Adeolu O. Dairo

Abstract:

Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

Procedia PDF Downloads 163

Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

Procedia PDF Downloads 255

Authors: Seonaid Hume, Gordon Dobie, Graeme West

Abstract:

Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

Procedia PDF Downloads 184

Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

Abstract:

Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

Procedia PDF Downloads 319

Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

Abstract:

In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

Procedia PDF Downloads 165

Authors: Wu Yufeng, Gu Yifan, Wang Hengguang, Gongyu, Zuo Tieyong

Abstract:

Indium is one the scarce resources which can be only used less than 30 years, and more than 70% of the indium is used for the production of the LCD. The benefit of recycling Indium from waste LCD is large. Take the LCD-TV for example, the yield of which was close to 90 million units in 2010. If it was available to recycle the indium effectively, the yield of the secondary-indium could reach up to 110 metric ton, which accounted for one third of the primary indium production in China. And compared with the dispersion and long process extraction of the primary indium resources, secondary indium concentrates in the waste LCD, the exploitation has great economic and environmental benefits. However, the potential benefits were indefinite, resulting in China’s government did not pay enough attention to the indium recycling industry. In our study, an estimation model was constructed to analyze the potential of the indium in the waste LCD. The different types of LCD were detected to find out the content of indium. Then, the potential of the indium in the waste LCD was estimated in China. Furthermore, the pollution emissions of the product process of the primary and secondary indium was analyzed respectively to calculate the economic and environmental benefits of the indium recycling from the waste LCD in China.

Keywords: indium recycling, waste liquid crystal displays, benefits, China

Procedia PDF Downloads 399

Authors: Alexander Hudson, Shaogang Gong

Abstract:

Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

Procedia PDF Downloads 115

Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

Abstract:

Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

Procedia PDF Downloads 99

Authors: K. Fellah, H. Benmehdi, A. Amrouche, H. Malainine, F. Memmou, H. Dalile, W. Siata

Abstract:

This work aims to evaluate the antioxidant of flavonoids extracted from the leaves of Prunus persica L. A phytochemical screening allowed us to highlight the different phytochemicals present in the leaves of the studied plant. The selective extraction of flavonoids gave yields of 0.71, 1.5, and 4.8% for the fractions ethyl ether, ethyl acetate and n- butanol, respectively. The reading of the antioxidant activity of different extracts of flavonoids by HPLTC method revealed positive reaction (yellow spots) on the TLC plates sprayed with DPPH. Using the DPPH method, the fractions of flavonoids (bunanol, ethyl acetate and Diethyl ether) showed a potent scavenging activity with IC50 = 0.22; 0.27 and 0.76 mg / ml, respectively. Furthermore, our findings revealed the extracts under study exhibited higher reducing potential which depends upon extract concentration. These results obtained from this investigation confirm that the Prunus persica remains a major resource of bioactive molecules.

Keywords: Prunus persica L., phytochemical study, flavonoids, antioxidant activity, TLC bioautographic, FRAP, DPPH

Procedia PDF Downloads 466

Authors: Bin Liu

Abstract:

As one of the most important tasks in protein sequence analysis, protein remote homology detection has been studied for decades. Currently, the profile-based methods show state-of-the-art performance. Position-Specific Frequency Matrix (PSFM) is widely used profile. However, there exists noise information in the profiles introduced by the amino acids with low frequencies. In this study, we propose a method to remove the noise information in the PSFM by removing the amino acids with low frequencies called Top frequency profile (TFP). Three new matrix transformation methods, including Autocross covariance (ACC) transformation, Tri-gram, and K-separated bigram (KSB), are performed on these profiles to convert them into fixed length feature vectors. Combined with Support Vector Machines (SVMs), the predictors are constructed. Evaluated on two benchmark datasets, and experimental results show that these proposed methods outperform other state-of-the-art predictors.

Keywords: protein remote homology detection, protein fold recognition, top frequency profile, support vector machines

Procedia PDF Downloads 106

Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

Abstract:

Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

Procedia PDF Downloads 347

Authors: Hanan Moawad, Naglaa M. Abd EL-Rahman

Abstract:

Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.

Keywords: ultrasound, classical extract, biological control, Erwinia carotovora, Hyphaene thebaica

Procedia PDF Downloads 505

Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

Abstract:

Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

Procedia PDF Downloads 277

Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

Abstract:

The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

Procedia PDF Downloads 270

Authors: Hyunho Shin, Jaekwang Jung, Jeongho Park, Sungwon Hwang

Abstract:

For the application of graphene quantum dots (GQDs) to optoelectronic nanodevices, it is of critical importance to understand the mechanisms which result in novel phenomena of their light absorption/emission. The optical transitions are known to be available up to ~6 eV in GQDs, especially useful for ultraviolet (UV) photodetectors (PDs). Here, we present size-dependent shape/edge-state variations of GQDs and visible photoluminescence (PL) showing anomalous size dependencies. With varying the average size (da) of GQDs from 5 to 35 nm, the peak energy of the absorption spectra monotonically decreases, while that of the visible PL spectra unusually shows nonmonotonic behaviors having a minimum at diameter ∼17 nm. The PL behaviors can be attributed to the novel feature of GQDs, that is, the circular-to-polygonal-shape and corresponding edge-state variations of GQDs at diameter ∼17 nm as the GQD size increases, as demonstrated by high resolution transmission electron microscopy. We believe that such a comprehensive scheme in designing device architecture and the structural formulation of GQDs provides a device for practical realization of environmentally benign, high performance flexible devices in the future.

Keywords: graphene, quantum dot, size, photoluminescence

Procedia PDF Downloads 274

Authors: Juliane P. De Oliveira, Carlos H. Dos Santos, Marcia Shoji, Maria E. C. Ferreira, Natalia U. Yamaguchi

Abstract:

The construction sector is considered a major generator of environmental impacts due to the high consumption of natural resources and waste generation. Thus, this article aims to evaluate the performance of a concrete produced by the partial and total replacement of natural coarse aggregate by recycled coarse aggregate, derived from the concrete residue of buildings and demolitions. The study was made by comparing the compressive strength and absorption of three different concrete traces, keeping the water/cement factor of 0.60 and changing only the proportions of recycled coarse aggregate between 0%, 50% and 100%. Traces 50% and 100% obtained good results by comparing the actual specific mass, because the material used is lighter to the natural coarse aggregate. It was concluded that the concrete produced with recycled aggregates, even with inferior results, can be used where it is not needed a structural function, giving an adequate destination to the construction and demolition waste and consequently reducing the extraction and consumption of natural resources.

Keywords: green concrete, recycled aggregate, recycling, sustainable development

Procedia PDF Downloads 133

Authors: Latifah Putti Tiananda, Sasti Khoirunnisa, Taniadiana Yapwito, Jessica Noviena

Abstract:

Innovations are often met with two responses, acceptance or rejection. In the past few years, Indonesia is experiencing a revolution of transportation service, which utilizes online platform for its operation. Such improvement is welcomed by consumers and challenged by conventional or ‘non-online’ transportation providers simultaneously. Conflicts arise as the existence of this online transportation mode results in declining income of non-online transportation workers. Physical confrontations and demonstrations demand policing from central authority. However, the obscurity of legal measures from the government persists the social instability. Bandung, a city in West Java with the highest rate of online transportation usage, has recently issued a recommendation withholding the operation of online transportation services to maintain peace and order. Thus, this paper seeks to elaborate the social unrest between the two contesting transportation actors in Bandung and explore community-based approaches to solve this problem. Using qualitative research method, this paper will also feature in-depth interviews with directly involved sources from Bandung.

Keywords: Bandung, market competition, online transportation services, social unrest

Procedia PDF Downloads 256