Search results for: mixed methods approach

Authors: Chin-Chen Chang, I-Ta Lee, Tsung-Ta Ke, Wen-Kai Tai

Abstract:

Common methods for resizing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image resizing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

Keywords: energy map, visual saliency, gradient map, seam carving

Procedia PDF Downloads 464

Authors: P. Chultheera, T. Rirksomboon, S. Kulprathipanja, C. Liu, W. Chinsirikul, N. Kerddonfag

Abstract:

Gas separation by selective transport through polymeric membranes is one of the rapid growing branches of membrane technology. However, the tradeoff between the permeability and selectivity is one of the critical challenges encountered by pure polymer membranes, which in turn limits their large-scale application. To enhance gas separation performances, mixed matrix membranes (MMMs) have been developed. In this study, MMMs were prepared by a solution-coating method and tested for CO₂/CH₄ separation through permeability and selectivity using a membrane testing unit at room temperature and a pressure of 100 psig. The fabricated MMMs were composed of silicone rubber dispersed with the activated carbon individually absorbed with polyethylene glycol (PEG) as a liquid additive. PEG emulsified silicone rubber MMMs showed superior gas separation on cellulose acetate membrane with both high permeability and selectivity compared with silicone rubber membrane and alone support membrane. However, the MMMs performed limited stability resulting from the undesirable PEG leakage. To stabilize the MMMs, PEG was then incorporated into activated carbon by adsorption. It was found that the incorporation of solid and liquid was effective to improve the separation performance of MMMs.

Keywords: mixed matrix membrane, membrane, CO₂/CH₄ separation, activated carbon

Procedia PDF Downloads 314

Authors: Panumard Kaewmora, Thirasak Rirksomboon, Vissanu Meeyoo

Abstract:

Due to the globally growing demands of petroleum fuel and fossil fuels, the scarcity or even depletion of fossil fuel sources could be inevitable. Alternatively, the utilization of renewable sources, such as biomass, has become attractive to the community. Biomass can be converted into bio-oil by fast pyrolysis. In water phase of bio-oil, acetic acid which is one of its main components can be converted to hydrogen with high selectivity over effective catalysts in steam reforming process. Steam reforming of acetic acid as model compound has been intensively investigated for hydrogen production using various metal oxide supported nickel catalysts and yet they seem to be rapidly deactivated depending on the support utilized. A catalyst support such as Ce1-xZrxO2 mixed oxide was proposed for alleviating this problem with the anticipation of enhancing hydrogen yield. However, catalyst preparation methods play a significant role in catalytic activity and performance of the catalysts. In this work, Ce0.75Zr0.25O2 mixed oxide solid solution support was prepared by urea hydrolysis using microwave as heat source. After that nickel metal was incorporated at 15 wt% by incipient wetness impregnation method. The catalysts were characterized by several techniques including BET, XRD, H2-TPR, XRF, SEM, and TEM as well as tested for the steam reforming of acetic acid at various operating conditions. Preliminary results showed that a hydrogen yield of ca. 32% with a relatively high acetic conversion was attained at 650°C.

Keywords: acetic acid, steam reforming, microwave, nickel, ceria, zirconia

Procedia PDF Downloads 160

Authors: Berkan Ural, Arif Eser, Sinan Apaydin

Abstract:

Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

Procedia PDF Downloads 392

Authors: S. Nickolas, Shobha K.

Abstract:

The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

Procedia PDF Downloads 256

Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

Abstract:

Concurrent planning of project scheduling and material ordering can provide more flexibility to the project scheduling problem, as the project execution costs can be enhanced. Hence, the issue has been taken into account in this paper. To do so, a mixed-integer mathematical model is developed which considers the aforementioned flexibility, in addition to the materials quantity discount and space availability restrictions. Moreover, the activities duration has been treated as decision variables. Finally, the efficiency of the proposed model is tested by different instances. Additionally, the influence of the aforementioned parameters is investigated on the model performance.

Keywords: material ordering, project scheduling, quantity discount, space availability

Procedia PDF Downloads 349

Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

Abstract:

Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

Procedia PDF Downloads 93

Authors: Chahrazed Zouaoui

Abstract:

In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

Procedia PDF Downloads 362

Authors: Apurva Sapra

Abstract:

The aim of this research was to study and compare the nature of expected, feared and hoped-for selves in institutionalized adolescent boys in two residential settings – an observation home with children in conflict with the law, and a children’s home with children in need of care and protection. The study uses a concurrent mixed methods design, in which eight adolescent boys from each group, aged 13-17, were asked to respond to a questionnaire, followed by an in-depth interview. The questionnaire looked into the total scores on current, probable and hoped-for/feared positive and negative self-descriptors. Possible selves of both groups were found to be influenced by their unique histories, such as with their experience of violence, interaction with the police and emphasis given on education. Expected selves and hoped-for selves were similar within the two groups. However, they were more concrete and attainable in the observation home and more ambitious in the children’s home. Quantitative results showed that on the positive self-descriptors, the participants in the observation home had a slightly lower total score on the current parameter as on the probable and hoped-for parameters. The participants in the children’s home showed similar results on current and probable positive self-descriptors, with higher scores on the hoped-for parameter. For most of the negative self-descriptors, the current score for the observation home group was lower than the expected score, and for the children’s home group, they were feared slightly more than they were expected. Along with the nature of possible selves, the study also looked into threats and support to desired and feared possible selves, as well as strategies to attain the desired possible selves and avoid feared possible selves. While threats to possible selves were identified as external and internal in both groups, the participants in the children’s home tended to identify threats as external. The categories of support were similar across the two groups, although the nature of support provided differed. Strategies adopted by participants in the observation home could be clearly divided as past, present and future strategies, while those adopted by participants in the children’s home had an overlap with past and future strategies. The institution was perceived as having a negative influence for the future in the observation home group, but positive in the children’s home group. Limitations of the study and recommendations for future research, policy setting and the counselling profession are discussed.

Keywords: adolescents, expected self, feared self, hoped-for self, institutions, possible selves

Procedia PDF Downloads 216

Authors: El Hassene Osmani, Mounir Haddou, Naceurdine Bensalem

Abstract:

In this paper, we investigate optimal control problems governed by semilinear elliptic variational inequalities involving constraints on the state, and more precisely, the obstacle problem. We present a relaxed formulation for the problem using smoothing functions. Since we adopt a numerical point of view, we first relax the feasible domain of the problem, then using both mathematical programming methods and penalization methods, we get optimality conditions with smooth Lagrange multipliers. Some numerical experiments using IPOPT algorithm (Interior Point Optimizer) are presented to verify the efficiency of our approach.

Keywords: complementarity problem, IPOPT, Lagrange multipliers, mathematical programming, optimal control, smoothing methods, variationally inequalities

Procedia PDF Downloads 148

Authors: M. Z. Shazana, R. Rosazley, M. A. Izzati, A. W. Fareezal, I. Rushdan, A. B. Suriani, S. Zakaria

Abstract:

There is an increasing interest in the development of flexible energy storage for application of Carbon Nanotubes and nanofibrillated cellulose (NFC). In this study, nanocomposite is consisting of Carbon Nanotube (CNT) mixed with suspension of nanofibrillated cellulose (NFC) from Oil Palm Empty Fruit Bunch (OPEFB). The use of Carbon Nanotube (CNT) as additive nanocomposite was improved the conductivity and mechanical properties of nanocomposite from nanofibrillated cellulose (NFC). The nanocomposite were characterized for electrical conductivity and mechanical properties in uniaxial tension, which were tensile to measure the bond of fibers in nanocomposite. The processing route is environmental friendly which leads to well-mixed structures and good results as well.

Keywords: carbon nanotube (CNT), nanofibrillated cellulose (NFC), mechanical properties, electrical conductivity

Procedia PDF Downloads 313

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

Procedia PDF Downloads 254

Authors: Anyia Nduka, Aslan Bin Amad Senin

Abstract:

Organizational culture, strategic leadership and organizational resilience have gained significant attention in recent years. This study aims to examine the relationship between these factors and their combined influence on an organization's ability to adapt and thrive in the face of challenges and disruptions. A mixed-methods approach, combining quantitative survey data and qualitative interviews with leaders and employees from cohort organizations within the industry. The quantitative phase involves measuring organizational culture, strategic leadership behaviours, and organizational resilience using standardized scales. This study highlighted the significance of organizational culture and strategic leadership in building and sustaining organizational resilience. Preliminary findings suggest a strong positive relationship between a resilient organizational culture and strategic leadership practices. Secondly, Organizations can enhance their capacity to respond to disruptions, exploit opportunities, and achieve long-term success in a rapidly changing business environment. Furthermore, the qualitative analysis reveals several key themes that elucidate the link between organizational culture, strategic leadership, and resilience. This study contributes to the growing body of knowledge on organizational resilience and strategic leadership, providing insights and practical implications for leaders and practitioners seeking to strengthen their organizations' resilience capabilities. Further research is needed to explore the specific mechanisms and contextual factors that influence the relationship between these variables in different organizational contexts and industries.

Keywords: organizational culture, strategic leadership, organizational resilience, leadership

Procedia PDF Downloads 48

Authors: Guettal Djaouida, Ziadi Abdelkader

Abstract:

In this paper, we study a coupling of the Alienor method with the algorithm of Piyavskii-Shubert. The classical multidimensional global optimization methods involves great difficulties for their implementation to high dimensions. The Alienor method allows to transform a multivariable function into a function of a single variable for which it is possible to use efficient and rapid method for calculating the the global optimum. This simplification is based on the using of a reducing transformation called Alienor.

Keywords: global optimization, reducing transformation, α-dense curves, Alienor method, Piyavskii-Shubert algorithm

Procedia PDF Downloads 484

Authors: Mohadeseh Seyednezhad, Armin Rajabi, Andanastui Muchtar, Mahendra Rao Somalu

Abstract:

This work investigates the electrical properties of NiO-SDC/SDC anode sintered at about 1200 ○C for 1h through a relatively new approach, namely the microwave method. Nano powders Sm0.2Ce0.8O1.9 (SDC) and NiO were mixed by using a high-energy ball-mill and subsequent co-pressed at three different compaction pressures 200, 300 and 400 MPa. The novelty of this study consists in the effect of compaction pressure on the electrochemical performance of Ni-SDC/SDC anode, with no binder used between layers. The electrical behavior of the prepared anode has been studied by electrochemical impedance spectra (EIS) in controlled atmospheres, operating at high temperatures (600-800 °C).

Keywords: sintering, fuel cell, electrical conductivity, nanostructures, impedance spectroscopy, ceramics

Procedia PDF Downloads 447

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

Abstract:

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

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

Procedia PDF Downloads 318

Authors: Annette Cosgrove

Abstract:

The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitisation of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence based digital teaching model for use in a future pandemic. The research strategy undertaken for this PhD Study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially , feedback collected and the research instrument was edited to reflect this feedback, before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioners views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology enhanced learning and on teaching practice in a higher education institution.’ The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice . This study includes quantitative and qualitative methods to elicit data which will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments / data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers.. This research is currently being conducted across the ATU multisite campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a west of Ireland university is the focus of the study , The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi- formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning . This paper will present initial findings, reflections and data from this ongoing research study.

Keywords: TEL, DTL, digital teaching, digital assessment

Procedia PDF Downloads 48

Authors: Muhammad Naweed, Usman Tariq Murtaza, Waseem Siddique

Abstract:

A pallet body approach is a finite element-based computational approach used for the modeling and assessment of a three-dimensional surface crack. The approach is capable of inserting the crack in an engineering structure and generating high-quality hexahedral mesh in the cracked region of the structure. The approach is capable of computing the stress intensity factors along a semi-elliptical surface crack numerically. The objective of this work is to present that the stress intensity factors produced by the approach can be used with confidence for capturing the parameters during the fatigue crack growth.

Keywords: pallet body approach, semi-elliptical surface crack, stress intensity factors, fatigue crack growth

Procedia PDF Downloads 86

Authors: Sijo S. Thomas, S. Hridya, Manoj Mohan, Bibin Jacob, Hysen Thomas

Abstract:

Ferrites are iron based oxides with technologically significant magnetic properties and have widespread applications in medicine, technology, and industry. There has been a growing interest in the study of magnetic, electrical and structural properties of mixed ferrites. In the present work, structural and magnetic properties of Nickel and Calcium substituted Fe₃O₄ nanoparticles were investigated. NiₓCa₁₋ₓFe₂O₄ nanoparticles (x = 0, 0.1, 0.3, 0.5, 0.7, 0.9) were synthesized by chemical co-precipitation method and the samples were subsequently sintered at 900°C. The magnetic and structural properties of NiₓCa₁₋ₓFe₂O₄ were investigated using Vibrating Sample Magnetometer and X-Ray diffraction. The XRD results revealed that the synthesized particles have nanometer size and it varies from 46-72 nm as the calcium concentration diminishes. The variation is explained based on the increase in the reaction rate with Ni concentration which favors the formation of ultrafine particles of mixed ferrites. VSM results show pure CaFe₂O₄ exhibit paramagnetic behavior with low saturation value. As the concentration of Ca decreases, a transition occurs from paramagnetic state to ferromagnetic state. When the concentration of Ni becomes dominant, magnetic saturation, coercivity, and retentivity become high, indicating near ferromagnetic behavior of the compound.

Keywords: co-precipitation, ferrites, magnetic behavior, structure

Procedia PDF Downloads 219

Authors: Kenneth N. Ohei, Roelien Brink

Abstract:

For decades, teaching and learning processes have centered on the traditional approach (Web 1.0) that promoted teacher-directed pedagogical practices. Currently, there is a realization that the traditional approach is not adequate to effectively address and improve all student-learning outcomes. The subsequent incorporation of social software, Information, and Communication Technology (ICT) tools in universities may serve as complementary to support educational goals, offering students the affordability and opportunity to educational choices and learning platforms. Consequently, educators’ inability to incorporate these instructional ICT tools in their teaching and learning practices remains a challenge. This will signify that educators still lack the ICT skills required to administer lectures and bridging learning gaps. This study probes a methodological concept with the aim of developing a framework towards the adoption of social software in HES to help facilitate business processes and can build social presence among students. A mixed method will be appropriate to develop a comprehensive framework needed in Higher Educational System (HES). After research have been conducted, the adoption of social software will be based on the developed comprehensive framework which is supposed to impact positively on education and approach of delivery, improves learning experience, engagement and finally, increases educational opportunities and easy access to educational contents.

Keywords: blended and integrated learning, learning experience and engagement, higher educational system, HES, information and communication technology, ICT, social presence, Web 1.0, Web 2.0, Web 3.0

Procedia PDF Downloads 143

Authors: Sophie Whittle

Abstract:

Prior to present day, English syntax historically exhibited an inconsistent verb-second (V2) rule, which saw the verb move to the second position in the sentence following the fronting of a type of phrase. There was a high amount of variation throughout the history of English with regard to the ordering of subject and verb, and many explanations attempting to account for this variation have been documented in previous literature. However, these attempts have been contradictory, with many accounts positing the effect of previous syntactic changes as the main motivations behind the decline of V2. For instance, morphosyntactic changes, such as the loss of clitics and the loss of empty expletives, have been loosely connected to changes in frequency for the loss of V2. The questions surrounding the development of non-V2 in English have, therefore, yet to be answered. The current paper aims to bring together a number of explanations from different linguistic fields to determine the factors driving the changes in English V2. Using historical corpus-based methods, the study analyses both quantitatively and qualitatively the changes in frequency for the history of V2 in the Old, Middle, and Modern English periods to account for the variation in a range of sentential environments. These methods delve into the study of information structure, prosody and language contact to explain variation within different contexts. The analysis concludes that these factors, in addition to changes within the syntax, are responsible for the position of verb movement. The loss of V2 serves as an exemplar study within the field of historical linguistics, which combines a number of factors in explaining language change in general.

Keywords: corpora, English, language change, mixed-methods, syntax, verb-second

Procedia PDF Downloads 117

Authors: Van Huong Mai, Kanokwan Nithiratphat, Adool Booncham

Abstract:

The Movement of Contemporary Life consisted of two purposes, which were to study the movement and development of the modern life and to create the visual arts, which were paintings expressed via the form of apartment buildings was used from mixed media (digital printing and acrylic painting on canvas) which conveyed the rapid pace of modern life leading to diverse movements in viewer’s feeling. The operation of this creation was collected field data, documentary data, and influence from creative work. The data analysis was analyzed in order to theme, form, technique, and process to satisfy of concept and special character of the pieces.

Keywords: movement, contemporary life, visual art, acrylic painting, digital art, urban space

Procedia PDF Downloads 78

Authors: C. E. Nugraheni, L. Abednego

Abstract:

This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as meta-heuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: hyper-heuristics, evolutionary algorithms, production scheduling, meta-heuristic

Procedia PDF Downloads 366

Authors: Sadia Siddiqa, Z. Khan, M. A. Hossain

Abstract:

In this article, the effect of thermal radiation on mixed convection boundary layer flow of a viscous fluid along a highly heated vertical flat plate is considered with varying density and volumetric expansion coefficient. The density of the fluid is assumed to vary exponentially with temperature, however; volumetric expansion coefficient depends linearly on temperature. Boundary layer equations are transformed into convenient form by introducing primitive variable formulations. Solutions of transformed system of equations are obtained numerically through implicit finite difference method along with Gaussian elimination technique. Results are discussed in view of various parameters, like thermal radiation parameter, volumetric expansion parameter and density variation parameter on the wall shear stress and heat transfer rate. It is concluded from the present investigation that increase in volumetric expansion parameter decreases wall shear stress and enhances heat transfer rate.

Keywords: thermal radiation, mixed convection, variable density, variable volumetric expansion coefficient

Procedia PDF Downloads 352

Authors: P. Paengkoum, S. C. Chen, S. Paengkoum

Abstract:

Six male growing Thai-indigenous beef cattle with body weight (BW) of 154±13.2 kg were randomly assigned in replicated 3×3 Latin square design, and fed with different levels of crude protein (CP) in total mixed ration (TMR) diets. CP levels in diets were 4.3%, 7.3% and 10.3% base on dry matter (DM). Ruminal ammonia nitrogen (NH3-N) and blood urea nitrogen (BUN) concentrations increased (P<0.01) with increasing CP levels. Moreover, there is a positive relationship between BUN and ruminal NH3-N. Rumen pH, total volatile fatty acid (VFA), molar proportions of acetate, propionate and butyrate were not affected by CP levels (P>0.05).

Keywords: Thai-indigenous beef cattle, crude protein, volatile fatty acid (VFA), total mixed ration (TMR) diets

Procedia PDF Downloads 260

Authors: Anita Vidacs, Csaba Vagvolgyi, Judit Krisch

Abstract:

The attachment of microorganisms to different surfaces and the development of biofilms can lead to outbreaks of food-borne diseases and economic losses due to perished food. In food processing environments, bacterial communities are generally formed by mixed cultures of different species. Plants are sources of several antimicrobial substances that may be potential candidates for the development of new disinfectants. We aimed to investigate cinnamon (Cinnamomum zeylanicum), marjoram (Origanum majorana), and thyme (Thymus vulgaris). Essential oils and their major components (cinnamaldehyde, terpinene-4-ol, and thymol) on four-species biofilms of E. coli, L. monocytogenes, P. putida, and S. aureus. Experiments had three parts: (i) determination of minimum bactericide concentration and the killing time with microdilution methods; (ii) elimination of the four-species 24– and 168-hours old biofilm from stainless steel, polypropylene, tile and wood surfaces; and (iii) comparing the disinfectant effect with industrial used per-acetic based sanitizer (HC-DPE). E. coli and P. putida were more resistant to investigated essential oils and their main components in biofilm, than L. monocytogenes and S. aureus. These Gram-negative bacteria were detected on the surfaces, where the natural based disinfectant had not total biofilm elimination effect. Most promoted solutions were the cinnamon essential oil and the terpinene-4-ol that could eradicate the biofilm from stainless steel, polypropylene and even from tile, too. They have a better disinfectant effect than HC-DPE. These natural agents can be used as alternative solutions in the battle against bacterial biofilms.

Keywords: biofilm, essential oils, surfaces, terpinene-4-ol

Procedia PDF Downloads 85

Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

Abstract:

At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

Procedia PDF Downloads 162

Authors: A. Satty, H. Mwambi

Abstract:

Much clinical trials data-based research are characterized by the unavoidable problem of dropout as a result of missing or erroneous values. This paper aims to review some of the various techniques to address the dropout problems in longitudinal clinical trials. The fundamental concepts of the patterns and mechanisms of dropout are discussed. This study presents five general techniques for handling dropout: (1) Deletion methods; (2) Imputation-based methods; (3) Data augmentation methods; (4) Likelihood-based methods; and (5) MNAR-based methods. Under each technique, several methods that are commonly used to deal with dropout are presented, including a review of the existing literature in which we examine the effectiveness of these methods in the analysis of incomplete data. Two application examples are presented to study the potential strengths or weaknesses of some of the methods under certain dropout mechanisms as well as to assess the sensitivity of the modelling assumptions.

Keywords: incomplete longitudinal clinical trials, missing at random (MAR), imputation, weighting methods, sensitivity analysis

Procedia PDF Downloads 395

Authors: Omer Yeni

Abstract:

Ground strata failure or fall-of-ground is one of the underground mines' most prominent catastrophic risks. Mining companies use various methods/technics to prevent and critically control the associated risks. Some of those are safety by design, excavation methods, ground support, training, and competency, which all require quality control and assurance activities to confirm their efficiencies and performances and identify improvement opportunities through monitoring. However, many mining companies use quality control (QC) methods without quality assurance (QA), and they call it QA/QC together as a habit. From a simple definition, QC is a method of detecting defects, and QA is a method of preventing defects. Testing the final products at the end of the production line is not the way of proper QA/QC application but testing every component before assembly and the final product once completed. The installed ground support elements are some final products mining companies use to prevent ground strata failure. Testing the final product (i.e., rock bolt pull testing, shotcrete strength test, etc.) with QC methods only while those areas are already accessible; is not like testing an airplane full of passengers right after the production line or testing a car after the sale. Can only QC methods be called QA/QC? Can QA/QC activities be numerically scored for each critical control implemented to assess ground strata failure potential? Can numerical scores be used to identify Geotechnical Risk Rating (GRR) to determine the ground strata failure risk and its probability? This paper sets out to provide a specific QA/QC methodology to manage and confirm efficiencies and performances of the implemented critical controls and a numerical approach through the Geotechnical Risk Rating (GRR) process to assess ground strata failure risk to determine the gaps where proactive action is required to evaluate the probability of ground strata failures in underground mines.

Keywords: fall of ground, ground strata failure, QA/QC, underground

Procedia PDF Downloads 63

Authors: Muthukumarasamy Govindarajan

Abstract:

Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

Procedia PDF Downloads 118