Search results for: traditional Sawan garment technique
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10967

Search results for: traditional Sawan garment technique

6707 Implementation of CNV-CH Algorithm Using Map-Reduce Approach

Authors: Aishik Deb, Rituparna Sinha

Abstract:

We have developed an algorithm to detect the abnormal segment/"structural variation in the genome across a number of samples. We have worked on simulated as well as real data from the BAM Files and have designed a segmentation algorithm where abnormal segments are detected. This algorithm aims to improve the accuracy and performance of the existing CNV-CH algorithm. The next-generation sequencing (NGS) approach is very fast and can generate large sequences in a reasonable time. So the huge volume of sequence information gives rise to the need for Big Data and parallel approaches of segmentation. Therefore, we have designed a map-reduce approach for the existing CNV-CH algorithm where a large amount of sequence data can be segmented and structural variations in the human genome can be detected. We have compared the efficiency of the traditional and map-reduce algorithms with respect to precision, sensitivity, and F-Score. The advantages of using our algorithm are that it is fast and has better accuracy. This algorithm can be applied to detect structural variations within a genome, which in turn can be used to detect various genetic disorders such as cancer, etc. The defects may be caused by new mutations or changes to the DNA and generally result in abnormally high or low base coverage and quantification values.

Keywords: cancer detection, convex hull segmentation, map reduce, next generation sequencing

Procedia PDF Downloads 118
6706 Not so Street Theatre: Politics in Theatre of Roots

Authors: Dani Karmakar

Abstract:

In India, the journey of street theatre was started with Indian peoples Theatre Association (IPTA) as a tool for anti-establishment that was categorized as by the people and for the people. It has expressed common people’s feelings, problems, day to day life. It has brought a social change that is downtrodden. By its nature, it is based on communist ideology. Street theatre is a theatre of protest. In India, many folk theatres translate directly ‘Street Theatre’, those are Veedhi Natakam in Andhra Pradesh and Therukoothu in Tamil Nadu. But they do not covey to common definition of street theatre. There are different folk theatres of different regions in India. All folk theatres have individual characteristic, criteria, taste and flavor that can render distinctive each others. In festivals or special occasions, whole communities come together to enjoy collectively and express their feelings. The Veedhi Natakam means 'street theatre'. Theru koothu is a traditional street theatre in the northern districts of Tamilnadu. Folk theatre has potential to deliver strong messages. It has a socially significant role. At Veedhi Natakam, Vidhushaka takes part for social criticism. Gambhira is also a socio-political folk drama presentation in West Bengal.

Keywords: folk theatre, Gambhira, politics, street theatre

Procedia PDF Downloads 337
6705 The Impact of Corporate Social Responsibility on Brand Equity of the Telecommunication Industry in South Africa

Authors: Keitumetse Gaesirwe

Abstract:

This study investigated the effect of corporate social responsibility (CSR) on brand equity. Specific objectives include examining the connections between ethics and philanthropic constructs of CSR and brand loyalty in the telecommunication industry in South Africa. A convenience sampling technique was used, and closed-ended questionnaires were administered to 800 research participants across the nine provinces of South Africa. Data collected from the field was analyzed using inferential statistics (Ordinary Least Squares regression and correlation analysis) as well as descriptive statistics. Findings show positive and significant connections between the constructs of CSR and brand loyalty. The implications of the findings indicate that keeping ethical and philanthropy standards can be a source of competitive advantage and guarantee brand loyalty for telecommunication companies in South Africa.

Keywords: CSR, brand awareness, telecommunication industry, COVID-19, South Africa

Procedia PDF Downloads 94
6704 Green Technology for the Treatment of Industrial Effluent Contaminated with Dyes

Authors: Afzaal Gulzar, Shafaq Mubarak, M. Zia-Ur-Rehman

Abstract:

Industrial waste waters put environmental constrains to the water quality of aqueous reserves. Number of techniques has been used to treat them before disposal to water bodies. In this work a novel green approach is study by using poultry waste eggshells as a low cost efficient adsorbent for the dyes present in industrial effluent of textile and paper industries. The developed technique not only used to treat contaminated waters but also resulted in the utilization of poultry eggshell waste which in turn assists in solid waste management. Batch sorption studies like contact time, adsorbent dose, dye concentration, temp and pH has been conducted to find the optimum adsorption parameters.

Keywords: green technology, solid waste management, industrial effluent, eggshell waste utilization, waste water treatment

Procedia PDF Downloads 448
6703 Vaporization of a Single N-Pentane Liquid Drop in a Flowing Immiscible Liquid Media

Authors: Hameed B. Mahood, Ali Sh. Baqir

Abstract:

Vaporization of a single n-pentane drop in a direct contact with another flowing immiscible liquid (warm water) has been experimentally investigated. The experiments were carried out utilising a cylindrical Perspex tube of diameter 10 cm and height and 150 cm. Saturated liquid n-pentane and warm water at 45oC were used as the dispersed and continuous phases, respectively. Photron FASTCAM SA 1.1high speed camera (75,000f/s) with software V. 321 was implemented during the experiments. Five different continuous phase flow rates (warm water) (10, 20, 30, 40, and 46 L⁄h) were used in the study. The results indicated that the increase of the continuous phase (warm water) flow rate results in increasing of the drop/bubble diameter.

Keywords: drop evaporation, direct contact heat transfer, drop/bubble growth, experimental technique

Procedia PDF Downloads 334
6702 Enhance Engineering Pedagogy in Programming Course via Knowledge Graph-Based Recommender System

Authors: Yan Li

Abstract:

Purpose: There is a lack of suitable recommendation systems to assist engineering teaching. The existing traditional engineering pedagogies lack learning interests for postgraduate students. The knowledge graph-based recommender system aims to enhance postgraduate students’ programming skills, with a focus on programming courses. Design/methodology/approach: The case study will be used as a major research method, and the two case studies will be taken in both two teaching styles of the universities (Zhejiang University and the University of Nottingham Ningbo China), followed by the interviews. Quantitative and qualitative research methods will be combined in this study. Research limitations/implications: The case studies were only focused on two teaching styles universities, which is not comprehensive enough. The subject was limited to postgraduate students. Originality/value: The study collected and analyzed the data from two teaching styles of universities’ perspectives. It explored the challenges of Engineering education and tried to seek potential enhancement.

Keywords: knowledge graph and recommender system, engineering pedagogy, programming skills, postgraduate students

Procedia PDF Downloads 57
6701 Book Exchange System with a Hybrid Recommendation Engine

Authors: Nilki Upathissa, Torin Wirasinghe

Abstract:

This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

Procedia PDF Downloads 72
6700 Study of Chemical State Analysis of Rubidium Compounds in Lα, Lβ₁, Lβ₃,₄ and Lγ₂,₃ X-Ray Emission Lines with Wavelength Dispersive X-Ray Fluorescence Spectrometer

Authors: Harpreet Singh Kainth

Abstract:

Rubidium salts have been commonly used as an electrolyte to improve the efficiency cycle of Li-ion batteries. In recent years, it has been implemented into the large scale for further technological advances to improve the performance rate and better cyclability in the batteries. X-ray absorption spectroscopy (XAS) is a powerful tool for obtaining the information in the electronic structure which involves the chemical state analysis in the active materials used in the batteries. However, this technique is not well suited for the industrial applications because it needs a synchrotron X-ray source and special sample file for in-situ measurements. In contrast to this, conventional wavelength dispersive X-ray fluorescence (WDXRF) spectrometer is nondestructive technique used to study the chemical shift in all transitions (K, L, M, …) and does not require any special pre-preparation planning. In the present work, the fluorescent Lα, Lβ₁ , Lβ₃,₄ and Lγ₂,₃ X-ray spectra of rubidium in different chemical forms (Rb₂CO₃ , RbCl, RbBr, and RbI) have been measured first time with high resolution wavelength dispersive X-ray fluorescence (WDXRF) spectrometer (Model: S8 TIGER, Bruker, Germany), equipped with an Rh anode X-ray tube (4-kW, 60 kV and 170 mA). In ₃₇Rb compounds, the measured energy shifts are in the range (-0.45 to - 1.71) eV for Lα X-ray peak, (0.02 to 0.21) eV for Lβ₁ , (0.04 to 0.21) eV for Lβ₃ , (0.15 to 0.43) eV for Lβ₄ and (0.22 to 0.75) eV for Lγ₂,₃ X-ray emission lines. The chemical shifts in rubidium compounds have been measured by considering Rb₂CO₃ compounds taking as a standard reference. A Voigt function is used to determine the central peak position of all compounds. Both positive and negative shifts have been observed in L shell emission lines. In Lα X-ray emission lines, all compounds show negative shift while in Lβ₁, Lβ₃,₄, and Lγ₂,₃ X-ray emission lines, all compounds show a positive shift. These positive and negative shifts result increase or decrease in X-ray energy shifts. It looks like that ligands attached with central metal atom attract or repel the electrons towards or away from the parent nucleus. This pulling and pushing character of rubidium affects the central peak position of the compounds which causes a chemical shift. To understand the chemical effect more briefly, factors like electro-negativity, line intensity ratio, effective charge and bond length are responsible for the chemical state analysis in rubidium compounds. The effective charge has been calculated from Suchet and Pauling method while the line intensity ratio has been calculated by calculating the area under the relevant emission peak. In the present work, it has been observed that electro-negativity, effective charge and intensity ratio (Lβ₁/Lα, Lβ₃,₄/Lα and Lγ₂,₃/Lα) are inversely proportional to the chemical shift (RbCl > RbBr > RbI), while bond length has been found directly proportional to the chemical shift (RbI > RbBr > RbCl).

Keywords: chemical shift in L emission lines, bond length, electro-negativity, effective charge, intensity ratio, Rubidium compounds, WDXRF spectrometer

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6699 EHD Effect on the Dynamic Characteristics of a Journal Bearing Lubricated with Couple Stress Fluids

Authors: B. Chetti, W. A. Crosby

Abstract:

This paper presents a numerical analysis for the dynamic performance of a finite journal bearing lubricated with couple stress fluid taking into account the effect of the deformation of the bearing liner. The modified Reynolds equation has been solved by using finite difference technique. The dynamic characteristics in terms of stiffness coefficients, damping coefficients, critical mass and whirl ratio are evaluated for different values of eccentricity ratio and elastic coefficient for a journal bearing lubricated with a couple stress fluids and a Newtonian fluid. The results show that the dynamic characteristics of journal bearings lubricated with couple stress fluids are improved compared to journal bearings lubricated with Newtonian fluids.

Keywords: journal bearing, elastohydrodynamic, stability, couple stress

Procedia PDF Downloads 354
6698 Attenuation of Pancreatic Histology, Hematology and Biochemical Parameters in Type 2 Diabetic Rats Treated with Azadirachta excelsa

Authors: S. Nurdiana, A. S. Nor Haziqah, M. K. Nur Ezwa Khairunnisa, S. Nurul Izzati, Y. Siti Amna M. J. Norashirene, I. Nur Hilwani

Abstract:

Azadirachta excelsa or locally known as sentang are frequently used as a traditional medicine by diabetes patients in Malaysia. However, less attention has been given to their toxicity effect. Thus, the study is an attempt to examine the protective effect of A. excelsa on the pancreas and to determine possible toxicity mediated by the extract. Diabetes was induced experimentally in rats by high-fat-diet for 16 weeks followed by intraperitoneal injection of streptozotocin at dosage of 35 mg/kg of body weight. Declination of the fasting blood glucose level was observed after continuous administration of A. excelsa for 14 days twice daily. This is due to the refining structure of the pancreas. However, surprisingly, the plant extract reduced the leukocytes, erythrocytes, hemoglobin, MCHC and lymphocytes. In addition, the rat treated with the plant extract exhibited increment in AST and eosinocytes level. Overall, the finding shows that A. excelsa possesses antidiabetic activity by improving the structure of pancreatic islet of Langerhans but involved in ameliorating of hematology and biochemical parameters.

Keywords: Azadirachta excelsa, diabetes, pancreas, hemato-biochemical parameters

Procedia PDF Downloads 403
6697 Diagnosis of Diabetes Using Computer Methods: Soft Computing Methods for Diabetes Detection Using Iris

Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

Procedia PDF Downloads 385
6696 Compact Low-Voltage Biomedical Instrumentation Amplifiers

Authors: Phanumas Khumsat, Chalermchai Janmane

Abstract:

Low-voltage instrumentation amplifier has been proposed for 3-lead electrocardiogram measurement system. The circuit’s interference rejection technique is based upon common-mode feed-forwarding where common-mode currents have cancelled each other at the output nodes. The common-mode current for cancellation is generated by means of common-mode sensing and emitter or source followers with resistors employing only one transistor. Simultaneously this particular transistor also provides common-mode feedback to the patient’s right/left leg to further reduce interference entering the amplifier. The proposed designs have been verified with simulations in 0.18-µm CMOS process operating under 1.0-V supply with CMRR greater than 80dB. Moreover ECG signals have experimentally recorded with the proposed instrumentation amplifiers implemented from discrete BJT (BC547, BC558) and MOSFET (ALD1106, ALD1107) transistors working with 1.5-V supply.

Keywords: electrocardiogram, common-mode feedback, common-mode feedforward, communication engineering

Procedia PDF Downloads 366
6695 Research on Straightening Process Model Based on Iteration and Self-Learning

Authors: Hong Lu, Xiong Xiao

Abstract:

Shaft parts are widely used in machinery industry, however, bending deformation often occurred when this kind of parts is being heat treated. This parts needs to be straightened to meet the requirement of straightness. As for the pressure straightening process, a good straightening stroke algorithm is related to the precision and efficiency of straightening process. In this paper, the relationship between straightening load and deflection during the straightening process is analyzed, and the mathematical model of the straightening process has been established. By the mathematical model, the iterative method is used to solve the straightening stroke. Compared to the traditional straightening stroke algorithm, straightening stroke calculated by this method is much more precise; because it can adapt to the change of material performance parameters. Considering that the straightening method is widely used in the mass production of the shaft parts, knowledge base is used to store the data of the straightening process, and a straightening stroke algorithm based on empirical data is set up. In this paper, the straightening process control model which combine the straightening stroke method based on iteration and straightening stroke algorithm based on empirical data has been set up. Finally, an experiment has been designed to verify the straightening process control model.

Keywords: straightness, straightening stroke, deflection, shaft parts

Procedia PDF Downloads 315
6694 Investigating the Flow Physics within Vortex-Shockwave Interactions

Authors: Frederick Ferguson, Dehua Feng, Yang Gao

Abstract:

No doubt, current CFD tools have a great many technical limitations, and active research is being done to overcome these limitations. Current areas of limitations include vortex-dominated flows, separated flows, and turbulent flows. In general, turbulent flows are unsteady solutions to the fluid dynamic equations, and instances of these solutions can be computed directly from the equations. One of the approaches commonly implemented is known as the ‘direct numerical simulation’, DNS. This approach requires a spatial grid that is fine enough to capture the smallest length scale of the turbulent fluid motion. This approach is called the ‘Kolmogorov scale’ model. It is of interest to note that the Kolmogorov scale model must be captured throughout the domain of interest and at a correspondingly small-time step. In typical problems of industrial interest, the ratio of the length scale of the domain to the Kolmogorov length scale is so great that the required grid set becomes prohibitively large. As a result, the available computational resources are usually inadequate for DNS related tasks. At this time in its development, DNS is not applicable to industrial problems. In this research, an attempt is made to develop a numerical technique that is capable of delivering DNS quality solutions at the scale required by the industry. To date, this technique has delivered preliminary results for both steady and unsteady, viscous and inviscid, compressible and incompressible, and for both high and low Reynolds number flow fields that are very accurate. Herein, it is proposed that the Integro-Differential Scheme (IDS) be applied to a set of vortex-shockwave interaction problems with the goal of investigating the nonstationary physics within the resulting interaction regions. In the proposed paper, the IDS formulation and its numerical error capability will be described. Further, the IDS will be used to solve the inviscid and viscous Burgers equation, with the goal of analyzing their solutions over a considerable length of time, thus demonstrating the unsteady capabilities of the IDS. Finally, the IDS will be used to solve a set of fluid dynamic problems related to flow that involves highly vortex interactions. Plans are to solve the following problems: the travelling wave and vortex problems over considerable lengths of time, the normal shockwave–vortex interaction problem for low supersonic conditions and the reflected oblique shock–vortex interaction problem. The IDS solutions obtained in each of these solutions will be explored further in efforts to determine the distributed density gradients and vorticity, as well as the Q-criterion. Parametric studies will be conducted to determine the effects of the Mach number on the intensity of vortex-shockwave interactions.

Keywords: vortex dominated flows, shockwave interactions, high Reynolds number, integro-differential scheme

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6693 A Review of Spatial Analysis as a Geographic Information Management Tool

Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

Abstract:

Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

Procedia PDF Downloads 297
6692 Application of Fuzzy Multiple Criteria Decision Making for Flooded Risk Region Selection in Thailand

Authors: Waraporn Wimuktalop

Abstract:

This research will select regions which are vulnerable to flooding in different level. Mathematical principles will be systematically and rationally utilized as a tool to solve problems of selection the regions. Therefore the method called Multiple Criteria Decision Making (MCDM) has been chosen by having two analysis standards, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and AHP (Analytic Hierarchy Process). There are three criterions that have been considered in this research. The first criterion is climate which is the rainfall. The second criterion is geography which is the height above mean sea level. The last criterion is the land utilization which both forest and agriculture use. The study found that the South has the highest risk of flooding, then the East, the Centre, the North-East, the West and the North, respectively.

Keywords: multiple criteria decision making, TOPSIS, analytic hierarchy process, flooding

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6691 Towards the Rapid Synthesis of High-Quality Monolayer Continuous Film of Graphene on High Surface Free Energy Existing Plasma Modified Cu Foil

Authors: Maddumage Don Sandeepa Lakshad Wimalananda, Jae-Kwan Kim, Ji-Myon Lee

Abstract:

Graphene is an extraordinary 2D material that shows superior electrical, optical, and mechanical properties for the applications such as transparent contacts. Further, chemical vapor deposition (CVD) technique facilitates to synthesizing of large-area graphene, including transferability. The abstract is describing the use of high surface free energy (SFE) and nano-scale high-density surface kinks (rough) existing Cu foil for CVD graphene growth, which is an opposite approach to modern use of catalytic surfaces for high-quality graphene growth, but the controllable rough morphological nature opens new era to fast synthesis (less than the 50s with a short annealing process) of graphene as a continuous film over conventional longer process (30 min growth). The experiments were shown that high SFE condition and surface kinks on Cu(100) crystal plane existing Cu catalytic surface facilitated to synthesize graphene with high monolayer and continuous nature because it can influence the adsorption of C species with high concentration and which can be facilitated by faster nucleation and growth of graphene. The fast nucleation and growth are lowering the diffusion of C atoms to Cu-graphene interface, which is resulting in no or negligible formation of bilayer patches. High energy (500W) Ar plasma treatment (inductively Coupled plasma) was facilitated to form rough and high SFE existing (54.92 mJm-2) Cu foil. This surface was used to grow the graphene by using CVD technique at 1000C for 50s. The introduced kink-like high SFE existing point on Cu(100) crystal plane facilitated to faster nucleation of graphene with a high monolayer ratio (I2D/IG is 2.42) compared to another different kind of smooth morphological and low SFE existing Cu surfaces such as Smoother surface, which is prepared by the redeposit of Cu evaporating atoms during the annealing (RRMS is 13.3nm). Even high SFE condition was favorable to synthesize graphene with monolayer and continuous nature; It fails to maintain clean (surface contains amorphous C clusters) and defect-free condition (ID/IG is 0.46) because of high SFE of Cu foil at the graphene growth stage. A post annealing process was used to heal and overcome previously mentioned problems. Different CVD atmospheres such as CH4 and H2 were used, and it was observed that there is a negligible change in graphene nature (number of layers and continuous condition) but it was observed that there is a significant difference in graphene quality because the ID/IG ratio of the graphene was reduced to 0.21 after the post-annealing with H2 gas. Addition to the change of graphene defectiveness the FE-SEM images show there was a reduction of C cluster contamination of the surface. High SFE conditions are favorable to form graphene as a monolayer and continuous film, but it fails to provide defect-free graphene. Further, plasma modified high SFE existing surface can be used to synthesize graphene within 50s, and a post annealing process can be used to reduce the defectiveness.

Keywords: chemical vapor deposition, graphene, morphology, plasma, surface free energy

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6690 Constructing the Density of States from the Parallel Wang Landau Algorithm Overlapping Data

Authors: Arman S. Kussainov, Altynbek K. Beisekov

Abstract:

This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

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6689 InP/ZnS Core-Shell and InP/ZnS/ZnS Core-Multishell Quantum Dots for Improved luminescence Efficiency

Authors: Imen Harabi, Hanae Toura, Safa Jemai, Bernabe Mari Soucase

Abstract:

A promising alternative to traditional Quantum Dots QD materials, which contain toxic heavy elements such as lead and cadmium, sheds light on indium phosphide quantum dots (InP QDs) Owing to improve the quantum yields of photoluminescence and other properties. InP, InP/ZnS core/shell and InP/ZnS/ZnS core/shell/shell Quantum Dots (QDs) were synthetized by the hot injection method. The optical and structural properties of the core InP QDs, InP/ZnS QDs, and InP/ZnS/ZnS QDs have being considered by several techniques such as X-ray diffraction, transmission electron microscopy, optical spectroscopy, and photoluminescence. The average diameter of InP, InP/ZnS, and InP/ZnS/ZnS Quantum Dots (QDs) was varying between 10 nm, 5.4 nm, and 4.10 nm. This experience revealed that the surface morphology of the Quantum Dots has a more regular spherical form with color variation of the QDs in solution. The emission peak of colloidal InP Quantum Dots was around 530 nm, while in InP/ZnS, the emission peak is displayed and located at 598 nm. whilst for InP/ZnS/ZnS is placed at 610 nm. Furthermore, an enhanced PL emission due to a passivation effect in the ZnS-covered InP QDs was obtained. Add the XRD information FWHM of the principal peak of InP QDs was 63 nm, while for InP/ZnS was 41 nm and InP/ZnS/ZnS was 33 nm. The effect of the Zinc stearate precursor concentration on the optical, structural, surface chemical of InP and InP/ZnS and InP/ZnS/ZnS QDs will be discussed.

Keywords: indium phosphide, quantum dot, nanoparticle, core-shell, multishell, luminescence

Procedia PDF Downloads 148
6688 Barriers to Competitive Tenders in Building Conservation Works

Authors: Yoke-Mui Lim, Yahaya Ahmad

Abstract:

Conservation works in Malaysia that is procured by public organisation usually follow the traditional approach where the works are tendered based on Bills of Quantities (BQ). One of the purposes of tendering is to enable the selection of a competent contractor that offers a competitive price. While competency of the contractors are assessed by their technical knowledge, experience and track records, the assessment of pricing will be dependent on the tender amount. However, the issue currently faced by the conservation works sector is the difficulty in assessing the competitiveness and reasonableness of the tender amount due to the high variance between the tenders amount. Thus, this paper discusses the factors that cause difficulty to the tenderers in pricing competitively in a bidding exercise for conservation tenders. Data on tendering is collected from interviews with conservation works contractors to gain in-depth understanding of the barriers faced in pricing tenders of conservation works. Findings from the study lent support to the contention that the variance of tender amount is very high amongst tenderers. The factors identified in the survey are the format of BQ, hidden works, experience and labour and material costs.

Keywords: building conservation, Malaysia, bill of quantities, tender

Procedia PDF Downloads 365
6687 Identity Verification Using k-NN Classifiers and Autistic Genetic Data

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 237
6686 New Approaches for the Handwritten Digit Image Features Extraction for Recognition

Authors: U. Ravi Babu, Mohd Mastan

Abstract:

The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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6685 Low Cost Inertial Sensors Modeling Using Allan Variance

Authors: A. A. Hussen, I. N. Jleta

Abstract:

Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to the low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effect of these random errors, they must be accurately modeled. Where the key is the successful implementation that depends on how well the noise statistics of the inertial sensors is selected. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.

Keywords: Allan variance, accelerometer, gyroscope, stochastic errors

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6684 Machine Learning Approach for Automating Electronic Component Error Classification and Detection

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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6683 Matching Farmer Competence and Farm Resources with the Transformation of Agri-Food Marketing Systems

Authors: Bhawat Chiamjinnawat

Abstract:

The agri-food market transformation has implied market growth for the fruit industry in Thailand. This article focuses on analysis of farmer competence and farm resources which affect market strategies used by fruit farmers in Chanthaburi province of Thailand. The survey data were collected through the use of face-to-face interviews with structured questionnaires. This study identified 14 drivers related to farmer competence and farm resources of which some had significant effect on the decision to use either high-value markets or traditional markets. The results suggest that farmers who used high-value markets were better educated and they had longer experience and larger sized business. Identifying the important factors that match with the market transformation provides policy with opportunities to support the fruit farmers to increase their market power. Policies that promote business expansion of agricultural cooperatives and knowledge sharing among farmers are recommended to reduce limitations due to limited knowledge, low experience, and small business sizes.

Keywords: farmer competence, farm resources, fruit industry, high-value markets, Thailand

Procedia PDF Downloads 151
6682 Eco Scale: A Tool for Assessing the Greenness of Pharmaceuticals Analysis

Authors: Heba M. Mohamed

Abstract:

Owing to scientific and public concern about health and environment and seeking for a better quality of life; “Green”, “Environmentally” and “Eco” friendly practices have been presented and implemented in different research areas. Subsequently, researchers’ attention is drawn in the direction of greening the analytical methodologies and taking the Green Analytical Chemistry principles (GAC) into consideration. It is of high importance to appraise the environmental impact of each of the implemented green approaches. Compared to the other traditional green metrics (E-factor, Atom economy and the process profile), the eco scale is the optimum choice to assess the environmental impact of the analytical procedures used for pharmaceuticals analysis. For analytical methodologies, Eco-Scale is calculated by allotting penalty points to any factor of the used analytical procedure which disagree and not match with the model green analysis, where the perfect green analysis has its Eco-Scale value of 100. In this work, calculation and comparison of the Eco-Scale for some of the reported green analytical methods was done, to accentuate their greening potentials. Where the different scores can reveal how green the method is, compared to the ideal value. The study emphasizes that greenness measurement is not only about the waste quantity determination but also dictates a holistic scheme, considering all factors.

Keywords: eco scale, green analysis, environmentally friendly, pharmaceuticals analysis

Procedia PDF Downloads 415
6681 Strategic Asset Allocation Optimization: Enhancing Portfolio Performance Through PCA-Driven Multi-Objective Modeling

Authors: Ghita Benayad

Abstract:

Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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6680 Jean-Francois Lyotrard's Concept of Different and the Conceptual Problems of Beauty in Philosophy of Contemporary Art

Authors: Sunandapriya Bhikkhu, Shimo Sraman

Abstract:

The main objective of this research is to analytically study the concept of Lyotard’s different that rejects the monopoly criteria and single rule with the incommensurable, which can explain about conceptual problems of beauty in the philosophy of contemporary art. In Lyotard’s idea that basic value judgment of human should be a value like a phrase that is a small unit and an individual such as the aesthetic value that to explain the art world. From the concept of the anti-war artist that rejects the concept of the traditional aesthetic which cannot be able to explain the changing in contemporary society but emphasizes the meaning of individual beauty that is at the beginning of contemporary art today. In the analysis of the problem, the researcher supports the concept of Lyotard’s different that emphasizes the artistic expression which opens the space of perception and beyond the limitations of language process. Art is like phrase or small units that can convey a sense of humanity through the aesthetic value of the individual, not social criteria or universal. The concept of Lyotard’s different awakens and challenge us to the rejection of the single rule that is not open the social space to minorities by not accepting the monopoly criteria.

Keywords: difference, Jean-Francois Lyotard, postmodern, beauty, contemporary art

Procedia PDF Downloads 289
6679 A Gauge Repeatability and Reproducibility Study for Multivariate Measurement Systems

Authors: Jeh-Nan Pan, Chung-I Li

Abstract:

Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries. Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries.

Keywords: gauge repeatability and reproducibility, multivariate measurement system analysis, precision-to-tolerance ratio, Gauge repeatability

Procedia PDF Downloads 247
6678 Unravelling the Impact of Job Resources: Alleviating Job-Related Anxiety to Forster Employee Creativity Within the Oil and Gas Industry

Authors: Nana Kojo Ayimadu Baafi, Kwesi Amponsah-Tawiah

Abstract:

The study investigated the relationship between job-related anxiety and employee creativity. The study further explored the role of job resources in moderating the relationship between job-related anxiety and employee creativity within the oil and gas industries. The study utilized a cross-sectional survey design. A non-probability sampling technique, specifically convenience sampling, was used to sample 1200 participants from multiple companies within the oil and gas industries. The collected data were analyzed using Regression analysis and PROCESS macro for the moderation analysis. The study empirically demonstrated a negative significant relationship between job-related anxiety and employee creativity. It also exhibited that job resources moderated the relationship between job-related anxiety and creativity. This study addresses gaps in previous studies by highlighting the significance of job resources in how job-related anxiety affects employee creativity.

Keywords: employee creativity, job-related anxiety, job resource, human resources

Procedia PDF Downloads 23