Search results for: wasteless method of ores processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21636

Search results for: wasteless method of ores processing

20886 Fabric Drapemeter Development towards the Analysis of Its Behavior in 3-D Design

Authors: Aida Sheeta, M. Nashat Fors, Sherwet El Gholmy, Marwa Issa

Abstract:

Globalization has raised the customer preferences not only towards the high-quality garments but also the right fitting, comfort and aesthetic apparels. This only can be accomplished by the good interaction between fabric mechanical and physical properties as well as the required style. Consequently, this paper provides an integrated review of the fabric drape terminology because it is considered as an essential feature in which the fabric can form folds with the help of the gravity. Moreover, an instrument has been fabricated in order to analyze the static and dynamic drape behaviors using different fabric types. In addition, the obtained results find out the parameters affecting the drape coefficient using digital image processing for various kind of commercial fabrics. This was found to be an essential first step in order to analyze the behavior of this fabric when it is fabricated in a certain 3-D garment design.

Keywords: cloth fitting, fabric drape nodes, garment silhouette, image processing

Procedia PDF Downloads 183
20885 An Approach to Automate the Modeling of Life Cycle Inventory Data: Case Study on Electrical and Electronic Equipment Products

Authors: Axelle Bertrand, Tom Bauer, Carole Charbuillet, Martin Bonte, Marie Voyer, Nicolas Perry

Abstract:

The complexity of Life Cycle Assessment (LCA) can be identified as the ultimate obstacle to massification. Due to these obstacles, the diffusion of eco-design and LCA methods in the manufacturing sectors could be impossible. This article addresses the research question: How to adapt the LCA method to generalize it massively and improve its performance? This paper aims to develop an approach for automating LCA in order to carry out assessments on a massive scale. To answer this, we proceeded in three steps: First, an analysis of the literature to identify existing automation methods. Given the constraints of large-scale manual processing, it was necessary to define a new approach, drawing inspiration from certain methods and combining them with new ideas and improvements. In a second part, our development of automated construction is presented (reconciliation and implementation of data). Finally, the LCA case study of a conduit is presented to demonstrate the feature-based approach offered by the developed tool. A computerized environment supports effective and efficient decision-making related to materials and processes, facilitating the process of data mapping and hence product modeling. This method is also able to complete the LCA process on its own within minutes. Thus, the calculations and the LCA report are automatically generated. The tool developed has shown that automation by code is a viable solution to meet LCA's massification objectives. It has major advantages over the traditional LCA method and overcomes the complexity of LCA. Indeed, the case study demonstrated the time savings associated with this methodology and, therefore, the opportunity to increase the number of LCA reports generated and, therefore, to meet regulatory requirements. Moreover, this approach also presents the potential of the proposed method for a wide range of applications.

Keywords: automation, EEE, life cycle assessment, life cycle inventory, massively

Procedia PDF Downloads 88
20884 Residual Power Series Method for System of Volterra Integro-Differential Equations

Authors: Zuhier Altawallbeh

Abstract:

This paper investigates the approximate analytical solutions of general form of Volterra integro-differential equations system by using the residual power series method (for short RPSM). The proposed method produces the solutions in terms of convergent series requires no linearization or small perturbation and reproduces the exact solution when the solution is polynomial. Some examples are given to demonstrate the simplicity and efficiency of the proposed method. Comparisons with the Laplace decomposition algorithm verify that the new method is very effective and convenient for solving system of pantograph equations.

Keywords: integro-differential equation, pantograph equations, system of initial value problems, residual power series method

Procedia PDF Downloads 417
20883 A Method for Improving the Embedded Runge Kutta Fehlberg 4(5)

Authors: Sunyoung Bu, Wonkyu Chung, Philsu Kim

Abstract:

In this paper, we introduce a method for improving the embedded Runge-Kutta-Fehlberg 4(5) method. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. This solution and error are obtained by solving an initial value problem whose solution has the information of the error at each integration step. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. For the assessment of the effectiveness, EULR problem is numerically solved.

Keywords: embedded Runge-Kutta-Fehlberg method, initial value problem, EULR problem, integration step

Procedia PDF Downloads 461
20882 Semantic Processing in Chinese: Category Effects, Task Effects and Age Effects

Authors: Yi-Hsiu Lai

Abstract:

The present study aimed to elucidate the nature of semantic processing in Chinese. Language and cognition related to the issue of aging are examined from the perspective of picture naming and category fluency tasks. Twenty Chinese-speaking adults (ranging from 25 to 45 years old) and twenty Chinese-speaking seniors (ranging from 65 to 75 years old) in Taiwan participated in this study. Each of them individually completed two tasks: a picture naming task and a category fluency task. Instruments for the naming task were sixty black-and-white pictures: thirty-five object and twenty-five action pictures. Category fluency task also consisted of two semantic categories – objects (or nouns) and actions (or verbs). Participants were asked to report as many items within a category as possible in one minute. Scores of action fluency and of object fluency were a summation of correct responses in these two categories. Category effects (actions vs. objects) and age effects were examined in these tasks. Objects were further divided into two major types: living objects and non-living objects. Actions were also categorized into two major types: action verbs and process verbs. Reaction time to each picture/question was additionally calculated and analyzed. Results of the category fluency task indicated that the content of information in Chinese seniors was comparatively deteriorated, thus producing smaller number of semantic-lexical items. Significant group difference was also found in the results of reaction time. Category Effect was significant for both Chinese adults and seniors in the semantic fluency task. Findings in the present study helped characterize the nature of semantic processing in Chinese-speaking adults and seniors and contributed to the issue of language and aging.

Keywords: semantic processing, aging, Chinese, category effects

Procedia PDF Downloads 358
20881 Regulation Effect of Intestinal Microbiota by Fermented Processing Wastewater of Yuba

Authors: Ting Wu, Feiting Hu, Xinyue Zhang, Shuxin Tang, Xiaoyun Xu

Abstract:

As a by-product of yuba, processing wastewater of Yuba (PWY) contains many bioactive components such as soybean isoflavones, soybean polysaccharides and soybean oligosaccharides, which is a good source of prebiotics and has a potential of high value utilization. The use of Lactobacillus plantarum to ferment PWY can be considered as a potential biogenic element, which can regulate the balance of intestinal microbiota. In this study, firstly, Lactobacillus plantarum was used to ferment PWY to improve its content of active components and antioxidant activity. Then, the health effect of fermented processing wastewater of yuba (FPWY) was measured in vitro. Finally, microencapsulation technology was used applied to improve the sustained release of FPWY and reduce the loss of active components in the digestion process, as well as to improving the activity of FPWY. The main results are as follows: (1) FPWY presented a good antioxidant capacity with DPPH free radical scavenging ability (0.83 ± 0.01 mmol Trolox/L), ABTS free radical scavenging ability (7.47 ± 0.35 mmol Trolox/L) and iron ion reducing ability (1.11 ± 0.07 mmol Trolox/L). Compared with non-fermented processing wastewater of yuba (NFPWY), there was no significant difference in the content of total soybean isoflavones, but the content of glucoside soybean isoflavones decreased, and aglyconic soybean isoflavones increased significantly. After fermentation, PWY can effectively reduce the soluble monosaccharides, disaccharides and oligosaccharides, such as glucose, fructose, galactose, trehalose, stachyose, maltose, raffinose and sucrose. (2) FPWY can significantly enhance the growth of beneficial bacteria such as Bifidobacterium, Ruminococcus and Akkermansia, significantly inhibit the growth of harmful bacteria E.coli, regulate the structure of intestinal microbiota, and significantly increase the content of short-chain fatty acids such as acetic acid, propionic acid, butyric acid, isovaleric acid. Higher amount of lactic acid in the gut can be further broken down into short chain fatty acids. (3) In order to improve the stability of soybean isoflavones in FPWY during digestion, sodium alginate and chitosan were used as wall materials for embedding. The FPWY freeze-dried powder was embedded by the method of acute-coagulation bath. The results show that when the core wall ratio is 3:1, the concentration of chitosan is 1.5%, the concentration of sodium alginate is 2.0%, and the concentration of calcium is 3%, the embossing rate is 53.20%. In the simulated in vitro digestion stage, the release rate of microcapsules reached 59.36% at the end of gastric digestion and 82.90% at the end of intestinal digestion. Therefore, the core materials with good sustained-release performance of microcapsules were almost all released. The structural analysis results of FPWY microcapsules show that the microcapsules have good mechanical properties. Its hardness, springness, cohesiveness, gumminess, chewiness and resilience were 117.75± 0.21 g, 0.76±0.02, 0.54±0.01, 63.28±0.71 g·sec, 48.03±1.37 g·sec, 0.31±0.01, respectively. Compared with the unembedded FPWY, the infrared spectrum results showed that the microcapsules had embedded effect on the FPWY freeze-dried powder.

Keywords: processing wastewater of yuba, lactobacillus plantarum, intestinal microbiota, microcapsule

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20880 Preserving Urban Cultural Heritage with Deep Learning: Color Planning for Japanese Merchant Towns

Authors: Dongqi Li, Yunjia Huang, Tomo Inoue, Kohei Inoue

Abstract:

With urbanization, urban cultural heritage is facing the impact and destruction of modernization and urbanization. Many historical areas are losing their historical information and regional cultural characteristics, so it is necessary to carry out systematic color planning for historical areas in conservation. As an early focus on urban color planning, Japan has a systematic approach to urban color planning. Hence, this paper selects five merchant towns from the category of important traditional building preservation areas in Japan as the subject of this study to explore the color structure and emotion of this type of historic area. First, the image semantic segmentation method identifies the buildings, roads, and landscape environments. Their color data were extracted for color composition and emotion analysis to summarize their common features. Second, the obtained Internet evaluations were extracted by natural language processing for keyword extraction. The correlation analysis of the color structure and keywords provides a valuable reference for conservation decisions for this historic area in the town. This paper also combines the color structure and Internet evaluation results with generative adversarial networks to generate predicted images of color structure improvements and color improvement schemes. The methods and conclusions of this paper can provide new ideas for the digital management of environmental colors in historic districts and provide a valuable reference for the inheritance of local traditional culture.

Keywords: historic districts, color planning, semantic segmentation, natural language processing

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20879 Review of Ultrasound Image Processing Techniques for Speckle Noise Reduction

Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

Abstract:

Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

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20878 Deep Learning Application for Object Image Recognition and Robot Automatic Grasping

Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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20877 Seat Assignment Model for Student Admissions Process at Saudi Higher Education Institutions

Authors: Mohammed Salem Alzahrani

Abstract:

In this paper, student admission process is studied to optimize the assignment of vacant seats with three main objectives. Utilizing all vacant seats, satisfying all program of study admission requirements and maintaining fairness among all candidates are the three main objectives of the optimization model. Seat Assignment Method (SAM) is used to build the model and solve the optimization problem with help of Northwest Coroner Method and Least Cost Method. A closed formula is derived for applying the priority of assigning seat to candidate based on SAM.

Keywords: admission process model, assignment problem, Hungarian Method, Least Cost Method, Northwest Corner Method, SAM

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20876 Patient Safety of Eating Ready-Made Meals at Government Hospitals

Authors: Hala Kama Ahmed Rashwan

Abstract:

Ensuring the patient safety especially at intensive care units and those exposed to hospital tools and equipment is one of the most important challenges facing healthcare today. Outbreak of food poisoning as a result of food-borne pathogens has been reported in many hospitals and care homes all over the world due to hospital meals. Patient safety of eating hospital meals is a fundamental principle of healthcare; it is new healthcare disciplines that assure the food raw materials, food storage, meals processing, and control of kitchen errors that often lead to adverse healthcare events. The aim of this article is to promote any hospital in attaining the hygienic practices and better quality system during processing of the ready-to- eat meals for intensive care units patients according to the WHO safety guidelines.

Keywords: hospitals, meals, safety, intensive care

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20875 A Succinct Method for Allocation of Reactive Power Loss in Deregulated Scenario

Authors: J. S. Savier

Abstract:

Real power is the component power which is converted into useful energy whereas reactive power is the component of power which cannot be converted to useful energy but it is required for the magnetization of various electrical machineries. If the reactive power is compensated at the consumer end, the need for reactive power flow from generators to the load can be avoided and hence the overall power loss can be reduced. In this scenario, this paper presents a succinct method called JSS method for allocation of reactive power losses to consumers connected to radial distribution networks in a deregulated environment. The proposed method has the advantage that no assumptions are made while deriving the reactive power loss allocation method.

Keywords: deregulation, reactive power loss allocation, radial distribution systems, succinct method

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20874 Modification of Underwood's Equation to Calculate Minimum Reflux Ratio for Column with One Side Stream Upper Than Feed

Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

Abstract:

Distillation is one of the most important and utilized separation methods in the industrial practice. There are different ways to design of distillation column. One of these ways is short cut method. In short cut method, material balance and equilibrium are employed to calculate number of tray in distillation column. There are different methods that are classified in short cut method. One of these methods is Fenske-Underwood-Gilliland method. In this method, minimum reflux ratio should be calculated by underwood equation. Underwood proposed an equation that is useful for simple distillation column with one feed and one top and bottom product. In this study, underwood method is developed to predict minimum reflux ratio for column with one side stream upper than feed. The result of this model compared with McCabe-Thiele method. The result shows that proposed method able to calculate minimum reflux ratio with very small error.

Keywords: minimum reflux ratio, side stream, distillation, Underwood’s method

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20873 The Subcellular Localisation of EhRRP6 and Its Involvement in Pre-Ribosomal RNA Processing in Growth-Stressed Entamoeba histolytica

Authors: S. S. Singh, A. Bhattacharya, S. Bhattacharya

Abstract:

The eukaryotic exosome complex plays a pivotal role in RNA biogenesis, maturation, surveillance and differential expression of various RNAs in response to varying environmental signals. The exosome is composed of evolutionary conserved nine core subunits and the associated exonucleases Rrp6 and Rrp44. Rrp6p is crucial for the processing of rRNAs, other non-coding RNAs, regulation of polyA tail length and termination of transcription. Rrp6p, a 3’-5’ exonuclease is required for degradation of 5’-external transcribed spacer (ETS) released from the rRNA precursors during the early steps of pre-rRNA processing. In the parasitic protist Entamoeba histolytica in response to growth stress, there occurs the accumulation of unprocessed pre-rRNA and 5’ ETS sub fragment. To understand the processes leading to this accumulation, we looked for Rrp6 and the exosome subunits in E. histolytica, by in silico approaches. Of the nine core exosomal subunits, seven had high percentage of sequence similarity with the yeast and human. The EhRrp6 homolog contained exoribonuclease and HRDC domains like yeast but its N- terminus lacked the PMC2NT domain. EhRrp6 complemented the temperature sensitive phenotype of yeast rrp6Δ cells suggesting conservation of biological activity. We showed 3’-5’ exoribonuclease activity of EhRrp6p with in vitro-synthesized appropriate RNAs substrates. Like the yeast enzyme, EhRrp6p degraded unstructured RNA, but could degrade the stem-loops slowly. Furthermore, immunolocalization revealed that EhRrp6 was nuclear-localized in normal cells but was diminished from nucleus during serum starvation, which could explain the accumulation of 5’ETS during stress. Our study shows functional conservation of EhRrp6p in E.histolytica, an early-branching eukaryote, and will help to understand the evolution of exosomal components and their regulatory function.

Keywords: entamoeba histolytica, exosome complex, rRNA processing, Rrp6

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20872 Combination of Unmanned Aerial Vehicle and Terrestrial Laser Scanner Data for Citrus Yield Estimation

Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

Abstract:

Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

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20871 A Calibration Device for Force-Torque Sensors

Authors: Nicolay Zarutskiy, Roman Bulkin

Abstract:

The paper deals with the existing methods of force-torque sensor calibration with a number of components from one to six, analyzed their advantages and disadvantages, the necessity of introduction of a calibration method. Calibration method and its constructive realization are also described here. A calibration method allows performing automated force-torque sensor calibration both with selected components of the main vector of forces and moments and with complex loading. Thus, two main advantages of the proposed calibration method are achieved: the automation of the calibration process and universality.

Keywords: automation, calibration, calibration device, calibration method, force-torque sensors

Procedia PDF Downloads 644
20870 Relevance of Lecture Method in Modern Era: A Study from Nepal

Authors: Hari Prasad Nepal

Abstract:

Research on lecture method issues confirm that this teaching method has been practiced from the very beginnings of schooling. Many teachers, lecturers and professors are convinced that lecture still represents main tool of contemporary instructional process. The central purpose of this study is to uncover the extent of using lecture method in the higher education. The study was carried out in Nepalese context with employing mixed method research design. To obtain the primary data this study employed a questionnaire involving items with close and open answers. 120 teachers, lecturers and professors participated in this study. The findings indicated that 75 percent of the respondents use the lecture method in their classroom teaching. The study reveals that there are advantages of using lecture method such as easy to practice, less time to prepare, high pass rate, high students’ satisfaction, little comments on instructors, appropriate to large classes and high level students. In addition, the study divulged the instructors’ reflections and measures to improve the lecture method. This research concludes that the practice of lecture method is still significantly applicable in colleges and universities in Nepalese contexts. So, there are no significant changes in the application of lecture method in the higher education classroom despite the emergence of new learning approaches and strategies.

Keywords: instructors, learning approaches, learning strategies, lecture method

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20869 High Resolution Sandstone Connectivity Modelling: Implications for Outcrop Geological and Its Analog Studies

Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

Abstract:

Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

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20868 Motion Detection Method for Clutter Rejection in the Bio-Radar Signal Processing

Authors: Carolina Gouveia, José Vieira, Pedro Pinho

Abstract:

The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: bio-signals, DC component, Doppler effect, ellipse fitting, radar, SDR

Procedia PDF Downloads 139
20867 A Method of the Semantic on Image Auto-Annotation

Authors: Lin Huo, Xianwei Liu, Jingxiong Zhou

Abstract:

Recently, due to the existence of semantic gap between image visual features and human concepts, the semantic of image auto-annotation has become an important topic. Firstly, by extract low-level visual features of the image, and the corresponding Hash method, mapping the feature into the corresponding Hash coding, eventually, transformed that into a group of binary string and store it, image auto-annotation by search is a popular method, we can use it to design and implement a method of image semantic auto-annotation. Finally, Through the test based on the Corel image set, and the results show that, this method is effective.

Keywords: image auto-annotation, color correlograms, Hash code, image retrieval

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20866 High Motivational Salient Face Distractors Slowed Target Detection: Evidence from Behavioral Studies

Authors: Rashmi Gupta

Abstract:

Rewarding stimuli capture attention involuntarily as a result of an association process that develops quickly during value learning, referred to as the reward or value-driven attentional capture. It is essential to compare reward with punishment processing to get a full picture of value-based modulation in visual attention processing. Hence, the present study manipulated both valence/value (reward as well as punishment) and motivational salience (probability of an outcome: high vs. low) together. Series of experiments were conducted, and there were two phases in each experiment. In phase 1, participants were required to learn to associate specific face stimuli with a high or low probability of winning or losing points. In the second phase, these conditioned stimuli then served as a distractor or prime in a speeded letter search task. Faces with high versus low outcome probability, regardless of valence, slowed the search for targets (specifically the left visual field target) and suggesting that the costs to performance on non-emotional cognitive tasks were only driven by motivational salience (high vs. loss) associated with the stimuli rather than the valence (gain vs. loss). It also suggests that the processing of motivationally salient stimuli is right-hemisphere biased. Together, results of these studies strengthen the notion that our visual attention system is more sensitive to affected by motivational saliency rather than valence, which termed here as motivational-driven attentional capture.

Keywords: attention, distractors, motivational salience, valence

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20865 Radiochemical Purity of 68Ga-BCA-Peptides: Separation of All 68Ga Species with a Single iTLC Strip

Authors: Anton A. Larenkov, Alesya Ya Maruk

Abstract:

In the present study, highly effective iTLC single strip method for the determination of radiochemical purity (RCP) of 68Ga-BCA-peptides was developed (with no double-developing, changing of eluents or other additional manipulation). In this method iTLC-SG strips and commonly used eluent TFAaq. (3-5 % (v/v)) are used. The method allows determining each of the key radiochemical forms of 68Ga (colloidal, bound, ionic) separately with the peaks separation being no less than 4 σ. Rf = 0.0-0.1 for 68Ga-colloid; Rf = 0.5-0.6 for 68Ga-BCA-peptides; Rf = 0.9-1.0 for ionic 68Ga. The method is simple and fast: For developing length of 75 mm only 4-6 min is required (versus 18-20 min for pharmacopoeial method). The method has been tested on various compounds (including 68Ga-DOTA-TOC, 68Ga-DOTA-TATE, 68Ga-NODAGA-RGD2 etc.). The cross-validation work for every specific form of 68Ga showed good correlation between method developed and control (pharmacopoeial) methods. The method can become convenient and much more informative replacement for pharmacopoeial methods, including HPLC.

Keywords: DOTA-TATE, 68Ga, quality control, radiochemical purity, radiopharmaceuticals, TLC

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20864 Comparing Numerical Accuracy of Solutions of Ordinary Differential Equations (ODE) Using Taylor's Series Method, Euler's Method and Runge-Kutta (RK) Method

Authors: Palwinder Singh, Munish Sandhir, Tejinder Singh

Abstract:

The ordinary differential equations (ODE) represent a natural framework for mathematical modeling of many real-life situations in the field of engineering, control systems, physics, chemistry and astronomy etc. Such type of differential equations can be solved by analytical methods or by numerical methods. If the solution is calculated using analytical methods, it is done through calculus theories, and thus requires a longer time to solve. In this paper, we compare the numerical accuracy of the solutions given by the three main types of one-step initial value solvers: Taylor’s Series Method, Euler’s Method and Runge-Kutta Fourth Order Method (RK4). The comparison of accuracy is obtained through comparing the solutions of ordinary differential equation given by these three methods. Furthermore, to verify the accuracy; we compare these numerical solutions with the exact solutions.

Keywords: Ordinary differential equations (ODE), Taylor’s Series Method, Euler’s Method, Runge-Kutta Fourth Order Method

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20863 Deep Learning-Based Approach to Automatic Abstractive Summarization of Patent Documents

Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty

Abstract:

A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.

Keywords: abstractive summarization, deep learning, natural language Processing, patent document

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20862 A Study of Effective Stereo Matching Method for Long-Wave Infrared Camera Module

Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

Abstract:

In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

Procedia PDF Downloads 411
20861 A Text Classification Approach Based on Natural Language Processing and Machine Learning Techniques

Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

Abstract:

Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

Procedia PDF Downloads 98
20860 Optimizing Data Transfer and Processing in Multi-Cloud Environments for Big Data Workloads

Authors: Gaurav Kumar Sinha

Abstract:

In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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20859 Embedded Electrochemistry with Miniaturized, Drone-Based, Potentiostat System for Remote Detection Chemical Warfare Agents

Authors: Amer Dawoud, Jesy Motchaalangaram, Arati Biswakarma, Wujan Mio, Karl Wallace

Abstract:

The development of an embedded miniaturized drone-based system for remote detection of Chemical Warfare Agents (CWA) is proposed. The paper focuses on the software/hardware system design of the electrochemical Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) signal processing for future deployment on drones. The paper summarizes the progress made towards hardware and electrochemical signal processing for signature detection of CWA. Also, the miniature potentiostat signal is validated by comparing it with the high-end lab potentiostat signal.

Keywords: drone-based, remote detection chemical warfare agents, miniaturized, potentiostat

Procedia PDF Downloads 134
20858 Mapping of Geological Structures Using Aerial Photography

Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

Abstract:

Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

Procedia PDF Downloads 685
20857 Optimizing CNC Production Line Efficiency Using NSGA-II: Adaptive Layout and Operational Sequence for Enhanced Manufacturing Flexibility

Authors: Yi-Ling Chen, Dung-Ying Lin

Abstract:

In the manufacturing process, computer numerical control (CNC) machining plays a crucial role. CNC enables precise machinery control through computer programs, achieving automation in the production process and significantly enhancing production efficiency. However, traditional CNC production lines often require manual intervention for loading and unloading operations, which limits the production line's operational efficiency and production capacity. Additionally, existing CNC automation systems frequently lack sufficient intelligence and fail to achieve optimal configuration efficiency, resulting in the need for substantial time to reconfigure production lines when producing different products, thereby impacting overall production efficiency. Using the NSGA-II algorithm, we generate production line layout configurations that consider field constraints and select robotic arm specifications from an arm list. This allows us to calculate loading and unloading times for each job order, perform demand allocation, and assign processing sequences. The NSGA-II algorithm is further employed to determine the optimal processing sequence, with the aim of minimizing demand completion time and maximizing average machine utilization. These objectives are used to evaluate the performance of each layout, ultimately determining the optimal layout configuration. By employing this method, it enhance the configuration efficiency of CNC production lines and establish an adaptive capability that allows the production line to respond promptly to changes in demand. This will minimize production losses caused by the need to reconfigure the layout, ensuring that the CNC production line can maintain optimal efficiency even when adjustments are required due to fluctuating demands.

Keywords: evolutionary algorithms, multi-objective optimization, pareto optimality, layout optimization, operations sequence

Procedia PDF Downloads 18