Search results for: hybrid techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8322

Search results for: hybrid techniques

5112 Comparative Analysis between Corn and Ramon (Brosimum alicastrum) Starches to Be Used as Sustainable Bio-Based Plastics

Authors: C. R. Ríos-Soberanis, V. M. Moo-Huchin, R. J. Estrada-Leon, E. Perez-Pacheco

Abstract:

Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons: firstly environmental concerns, and secondly the realization that our petroleum resources are finite. Finding new uses for agricultural commodities is also an important area of research. Therefore, it is crucial to get new sources of natural materials that can be used in different applications. Ramon tree (Brosimum alicastrum) is a tropical plant that grows freely in Yucatan countryside. This paper focuses on the seeds recollection, processing and starch extraction and characterization in order to find out about its suitability as biomaterial. Results demonstrated that it has a high content of qualities to be used not only as comestible but also as an important component in polymeric blends.

Keywords: biomaterials, characterization techniques, natural resource, starch

Procedia PDF Downloads 332
5111 Vision-Based Hand Segmentation Techniques for Human-Computer Interaction

Authors: M. Jebali, M. Jemni

Abstract:

This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

Procedia PDF Downloads 416
5110 Green Organic Chemistry, a New Paradigm in Pharmaceutical Sciences

Authors: Pesaru Vigneshwar Reddy, Parvathaneni Pavan

Abstract:

Green organic chemistry which is the latest and one of the most researched topics now-a- days has been in demand since 1990’s. Majority of the research in green organic chemistry chemicals are some of the important starting materials for greater number of major chemical industries. The production of organic chemicals has raw materials (or) reagents for other application is major sector of manufacturing polymers, pharmaceuticals, pesticides, paints, artificial fibers, food additives etc. organic synthesis on a large scale compound to the labratory scale, involves the use of energy, basic chemical ingredients from the petro chemical sectors, catalyst and after the end of the reaction, seperation, purification, storage, packing distribution etc. During these processes there are many problems of health and safety for workers in addition to the environmental problems caused there by use and deposition as waste. Green chemistry with its 12 principles would like to see changes in conventional way that were used for decades to make synthetic organic chemical and the use of less toxic starting materials. Green chemistry would like to increase the efficiency of synthetic methods, to use less toxic solvents, reduce the stage of synthetic routes and minimize waste as far as practically possible. In this way, organic synthesis will be part of the effort for sustainable development Green chemistry is also interested for research and alternatives innovations on many practical aspects of organic synthesis in the university and research labaratory of institutions. By changing the methodologies of organic synthesis, health and safety will be advanced in the small scale laboratory level but also will be extended to the industrial large scale production a process through new techniques. The three key developments in green chemistry include the use of super critical carbondioxide as green solvent, aqueous hydrogen peroxide as an oxidising agent and use of hydrogen in asymmetric synthesis. It also focuses on replacing traditional methods of heating with that of modern methods of heating like microwaves traditions, so that carbon foot print should reduces as far as possible. Another beneficiary of this green chemistry is that it will reduce environmental pollution through the use of less toxic reagents, minimizing of waste and more bio-degradable biproducts. In this present paper some of the basic principles, approaches, and early achievements of green chemistry has a branch of chemistry that studies the laws of passing of chemical reactions is also considered, with the summarization of green chemistry principles. A discussion about E-factor, old and new synthesis of ibuprofen, microwave techniques, and some of the recent advancements also considered.

Keywords: energy, e-factor, carbon foot print, micro-wave, sono-chemistry, advancement

Procedia PDF Downloads 312
5109 Investor Sentiment and Commodity Trading Advisor Fund Performance

Authors: Tian Lan

Abstract:

Arbitrageurs participate in a variety of techniques in response to the existence of fluctuating sentiment, resulting in sparse sentiment exposures. This paper found that Commodity Trading Advisor (CTA) funds in the top decile rated by sentiment beta outperformed those in the bottom decile by 0.33% per month on a risk-adjusted basis, with the difference being larger among skilled managers. This paper also discovered that around ten percent of Commodity Trading Advisor (CTA) funds could accurately predict market sentiment, which has a positive correlation with fund sentiment beta and acts as a determinant in fund performance. Instead of betting against mispricing, this research demonstrates that a competent manager can achieve remarkable returns by forecasting and reacting to shifts in investor sentiment.

Keywords: investment sentiment, CTA fund, market timing, fund performance

Procedia PDF Downloads 88
5108 Carbon Electrode Materials for Supercapacitors

Authors: Yu. Mateyshina, A. Ulihin, N. Uvarov

Abstract:

Supercapacitors are one of the most promising devices for energy storage applications as they can provide higher power density than batteries and higher energy density than conventional dielectric capacitors. Carbon materials with various microtextures are considered as main candidates for supercapacitors in terms of high surface area, interconnected pore structure, controlled pore size, high electrical conductivity and environmental friendliness. The specific capacitance (C) of the electrode material of the Electrochemical Double Layer Capacitors (EDLC) is known to depend on the specific surface area (Ss) and the pore structure. Activated carbons are most commonly used in supercapacitors because of their high surface area (Ss ≥ 1000 m2/g), good adhesion to electrolytes and low cost. In this work, electrochemical properties of new microporous and mesoporous carbon electrode materials were studied. The aim of the work was to investigate the relationship between the specific capacitance and specific surface area in a series of materials prepared from different organic precursors.. As supporting matrixes different carbon samples with Ss = 100-2000 m2/g were used. The materials were modified by treatment in acids (H2SO4, HNO3, acetic acid) in order to enable surface hydrophilicity. Then nanoparticles of transition metal oxides (for example NiO) were deposited on the carbon surfaces using methods of salts impregnation, mechanical treatment in ball mills and the precursors decomposition. The electrochemical characteristics of electrode hybrid materials were investigated in a symmetrical two-electrode cell using an impedance spectroscopy, voltammetry in both potentiodynamic and galvanostatic modes. It was shown that the value of C for the materials under study strongly depended on the preparation method of the electrode and the type of electrolyte (1 M H2SO4, 6 M KOH, 1 M LiClO4 in acetonitryl). Specific capacity may be increased by the introduction of nanoparticles from 50-100 F/g for initial carbon materials to 150-300 F/g for nanocomposites which may be used in supercapacitors. The work is supported by the по SC-14.604.21.0013.

Keywords: supercapacitors, carbon electrode, mesoporous carbon, electrochemistry

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5107 Cultural Studies in the Immigration Movements: Memories and Social Collectives

Authors: María Eugenia Peltzer, María Estela Rodríguez

Abstract:

This work presents an approach to the cultural aspects of the Immigrants as part of the Cultural Intangible Heritage of Argentina. The intangible cultural heritage consists of the manifestations, practices, uses, representations, expressions, knowledge, techniques and cultural spaces that communities and groups recognize as an integral part of their cultural heritage. This heritage generates feelings of identity and establishes links with the collective memory, as well as being transmitted and recreated over time according to its environment, its interaction with nature and its history contributing to promote respect for cultural diversity and Human creativity. The Immigrants brings together those who came from other lands and their descendants, thus maintaining their traditions through time and linking the members of each cultural group with a strong sense of belonging through a communicative and effective process.

Keywords: cultural, immigration, memories, social

Procedia PDF Downloads 443
5106 Modelling Vehicle Fuel Consumption Utilising Artificial Neural Networks

Authors: Aydin Azizi, Aburrahman Tanira

Abstract:

The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.

Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel

Procedia PDF Downloads 408
5105 Review of Suitable Advanced Oxidation Processes for Degradation of Organic Compounds in Produced Water during Enhanced Oil Recovery

Authors: Smita Krishnan, Krittika Chandran, Chandra Mohan Sinnathambi

Abstract:

Produced water and its treatment and management are growing challenges in all producing regions. This water is generally considered as a nonrevenue product, but it can have significant value in enhanced oil recovery techniques if it meets the required quality standards. There is also an interest in the beneficial uses of produced water for agricultural and industrial applications. Advanced Oxidation Process is a chemical technology that has been growing recently in the wastewater treatment industry, and it is highly recommended for non-easily removal of organic compounds. The efficiency of AOPs is compound specific, therefore, the optimization of each process should be done based on different aspects.

Keywords: advanced oxidation process, photochemical processes, degradation, organic contaminants

Procedia PDF Downloads 509
5104 Proposal for a Web System for the Control of Fungal Diseases in Grapes in Fruits Markets

Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso

Abstract:

Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.

Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow

Procedia PDF Downloads 88
5103 By-Line Analysis of Determinants Insurance Premiums : Evidence from Tunisian Market

Authors: Nadia Sghaier

Abstract:

In this paper, we aim to identify the determinants of the life and non-life insurance premiums of different lines for the case of the Tunisian insurance market over a recent period from 1997 to 2019. The empirical analysis is conducted using the linear cointegration techniques in the panel data framework, which allow both long and short-run relationships. The obtained results show evidence of long-run relationship between premiums, losses, and financial variables (stock market indices and interest rate). Furthermore, we find that the short-run effect of explanatory variables differs across lines. This finding has important implications for insurance tarification and regulation.

Keywords: insurance premiums, lines, Tunisian insurance market, cointegration approach in panel data

Procedia PDF Downloads 202
5102 Cloud Computing Impact on e-Government Adoption

Authors: Ali Elshabrawy

Abstract:

Cloud computing is expected to be important for e Government in near future. Governments need it for solving some of its e Government, financial, infrastructure, legacy systems and integration problems. It reduces information technology (IT) infrastructure needs and support costs, and offers on-demand infrastructure and computational power, improved collaboration capabilities, which are important for e Government projects start up and sustainability. Budget pressures will continue to drive more and more government IT to hybrid and even public clouds, and more cooperation between cloud service providers and governmental agencies are expected, Or developing governmental private, community clouds. Motivation to convince governments to use cloud computing services, will create a pressure on cloud service providers to cope with government's requirements for interoperability, security standards, open data and integration between their cloud systems There will be significant legal action arising out of governmental uses of cloud computing, and legislation addressing both IT and business needs and consumer fears and protections. Cloud computing is a considered a revolution for IT and E business in general and e commerce, e Government in particular. As governments faces increasing challenges regarding IT infrastructure required for e Government projects implementation. As a result of Lack of required financial resources allocated for e Government projects in developed and developing countries. Cloud computing can play a major role to solve some of e Government projects challenges such as, lack of financial resources, IT infrastructure, Human resources trained to manage e Government applications, interoperability, cost efficiency challenges. If we could solve some security issues related to cloud computing usage which considered critical for e Government projects. Pretty sure it’s Just a matter of time before cloud service providers will find out solutions to attract governments as major customers for their business.

Keywords: cloud computing, e-government, adoption, supply side barriers, e-government requirements, challenges

Procedia PDF Downloads 351
5101 Motion Planning and Posture Control of the General 3-Trailer System

Authors: K. Raghuwaiya, B. Sharma, J. Vanualailai

Abstract:

This paper presents a set of artificial potential field functions that improves upon; in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general 3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.

Keywords: artificial potential fields, 3-trailer systems, motion planning, posture

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5100 Ionic Liquid Effects on Metal Ion-Based Extractions of Olefin/Paraffin Hydrocarbon

Authors: Ellen M. Lukasik

Abstract:

In coordination and support of the Center for Innovative and Strategic Transformation of Alkane Resources (CISTAR) Research Experience for Teachers (RET) at the University of Texas at Austin and under the guidance and direction of Professor Joan Brennecke, this study examined the addition of silver in an ionic liquid used to separate cyclohexane from cyclohexene. We recreated the liquid-liquid separation experimental results from the literature on cyclohexene, cyclohexane, and [allylmim][Tf2N] to verify our method, then evaluated the separation performance of silver - ionic liquid (IL) mixtures by various characterization techniques. To introduce the concepts of this research in high school education, a lesson plan was developed to instruct students on the principles of liquid-liquid separation.

Keywords: ionic liquids, liquid-liquid separation, hydrocarbon, research experience for teachers

Procedia PDF Downloads 109
5099 Parallel Computing: Offloading Matrix Multiplication to GPU

Authors: Bharath R., Tharun Sai N., Bhuvan G.

Abstract:

This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

Procedia PDF Downloads 63
5098 Design, Development and Analysis of Combined Darrieus and Savonius Wind Turbine

Authors: Ashish Bhattarai, Bishnu Bhatta, Hem Raj Joshi, Nabin Neupane, Pankaj Yadav

Abstract:

This report concerns the design, development, and analysis of the combined Darrieus and Savonius wind turbine. Vertical Axis Wind Turbines (VAWT's) are of two type's viz. Darrieus (lift type) and Savonius (drag type). The problem associated with Darrieus is the lack of self-starting while Savonius has low efficiency. There are 3 straight Darrieus blades having the cross-section of NACA(National Advisory Committee of Aeronautics) 0018 placed circumferentially and a helically twisted Savonius blade to get even torque distribution. This unique design allows the use of Savonius as a method of self-starting the wind turbine, which the Darrieus cannot achieve on its own. All the parts of the wind turbine are designed in CAD software, and simulation data were obtained via CFD(Computational Fluid Dynamics) approach. Also, the design was imported to FlashForge Finder to 3D print the wind turbine profile and finally, testing was carried out. The plastic material used for Savonius was ABS(Acrylonitrile Butadiene Styrene) and that for Darrieus was PLA(Polylactic Acid). From the data obtained experimentally, the hybrid VAWT so fabricated has been found to operate at the low cut-in speed of 3 m/s and maximum power output has been found to be 7.5537 watts at the wind speed of 6 m/s. The maximum rpm of the rotor blade is recorded to be 431 rpm(rotation per minute) at the wind velocity of 6 m/s, signifying its potentiality of wind power production. Besides, the data so obtained from both the process when analyzed through graph plots has shown the similar nature slope wise. Also, the difference between the experimental and theoretical data obtained has shown mechanical losses. The objective is to eliminate the need for external motors for self-starting purposes and study the performance of the model. The testing of the model was carried out for different wind velocities.

Keywords: VAWT, Darrieus, Savonius, helical blades, CFD, flash forge finder, ABS, PLA

Procedia PDF Downloads 215
5097 Towards a Conscious Design in AI by Overcoming Dark Patterns

Authors: Ayse Arslan

Abstract:

One of the important elements underpinning a conscious design is the degree of toxicity in communication. This study explores the mechanisms and strategies for identifying toxic content by avoiding dark patterns. Given the breadth of hate and harassment attacks, this study explores a threat model and taxonomy to assist in reasoning about strategies for detection, prevention, mitigation, and recovery. In addition to identifying some relevant techniques such as nudges, automatic detection, or human-ranking, the study suggests the use of major metrics such as the overhead and friction of solutions on platforms and users or balancing false positives (e.g., incorrectly penalizing legitimate users) against false negatives (e.g., users exposed to hate and harassment) to maintain a conscious design towards fairness.

Keywords: AI, ML, algorithms, policy, system design

Procedia PDF Downloads 124
5096 Detect QOS Attacks Using Machine Learning Algorithm

Authors: Christodoulou Christos, Politis Anastasios

Abstract:

A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

Procedia PDF Downloads 65
5095 Overview and Future Opportunities of Sarcasm Detection on Social Media Communications

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

Abstract:

Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

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5094 Interpreting Ecclesiastical Heritage: Meaning Making and Contentious Conversations

Authors: Alexis Thouki

Abstract:

In our post-Christian societies, ecclesiastical heritage acquired a new extrovert profile aiming to reach out an increasingly diverse audience. In this context, the various motivations, interests, personalities and cultural exchanges, found in the ‘post-modern pilgrimage’, bequeath a hybrid and multidimensional character to religious tourism education. In consequence, churches have acquired the challenging role of enriching visitors cultural and spiritual capital. Despite this promising diversification to relate, reveal and provoke constructive discourses, due to the various ‘conflicting interests’, practitioners attempt to tame the rich in symbolism and meanings religious environment through ‘neutral interpretations’. This paper aims to present the results of an ongoing developing strategy related to the presentation of contentious meanings in English churches. The paper will explore some of the underlying issues related to the capacity of ‘neutrality’ to spark, downplay or eliminate contentious conversations relating to the cultural, religious, and social dimension of Christian cultural heritage thematology. In an effort to understand this issue, the paper examines the concept of neutrality and what it stands for, executing a discourse analysis in the semantic context in which the theological lexicon is interwoven with the cultural and social meanings of sacred sites. Following that, the paper examines whether the preferable interpretive strategies meet the post-modern interpretative framework which is marked by polysemy and critical active engagement. The ultimate aim of the paper is to investigate the hypothesis that the preferable neutral strategies, managing the ‘conflicting’ demands of worshippers and visitors, result in the uneven treatment of both, the religious and historical spirit of the place.

Keywords: contentious dialogue, interpretation, meaning making, religious tourism

Procedia PDF Downloads 161
5093 AI-Enabled Smart Contracts for Reliable Traceability in the Industry 4.0

Authors: Harris Niavis, Dimitra Politaki

Abstract:

The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

Procedia PDF Downloads 194
5092 Perceptions and Experiences of Students and Their Instructors on Online versus Face-To-Face Classrooms

Authors: Rahime Filiz Kiremit

Abstract:

This study involves investigating the comparisons of both online and face-to-face classes, along with providing their respective differences. The research project contains information pertaining to the two courses, provided with testimony from students and instructors alike. There were a total of 37 participants involved within the study from San Jacinto College; 35 students and the two instructors of their respective courses. The online instructor has a total of four years of teaching experience, while the face-to-face instructor has accrued 11 years of instructional education. The both instructors were interviewed and the samples were collected from three different classes - TECA 1311-702 (Educating Young Children 13 week distance learning), TECA 1311-705 (Educating Young Children 13 week distance learning) and TECA 1354 (Child Growth and Development). Among all three classes, 13 of the 29 students enrolled in either of the online courses considered participation within the survey, while 22 of the 28 students enrolled in the face-to-face course elected to do the same thing. With regards to the students’ prior class enrollment, 25 students had taken online classes previously, 9 students had taken early-childhood courses, 4 students had taken general classes, 11 students had taken both types of classes, 10 students had not yet taken online classes, and only 1 of them had taken a hybrid course. 10 of the participants professed that they like face-to-face classes, because they find that they can interact with their classmates and teachers. They find that online classes have more work to do, because they need to read the chapters and instructions on their own time. They said that during the face-to-face instruction, they could take notes and converse concerns with professors and fellow peers. They can have hands-on activities during face-to-face classes, and, as a result, improve their abilities to retain what they have learned within that particular time. Some of the students even mentioned that they are supposed to discipline themselves, because the online classes require more work. According to the remaining six students, online classes are easier than face-to-face classes. Most of them believe that the easiness of a course is dependent on the types of classes, the instructors, and the respective subjects of which they teach. With considerations of all 35 students, almost 63% of the students agreed that they interact more with their classmates in face-to-face classes.

Keywords: distance education, face-to-face education, online classroom, students' perceptions

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5091 Automatic Aggregation and Embedding of Microservices for Optimized Deployments

Authors: Pablo Chico De Guzman, Cesar Sanchez

Abstract:

Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

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5090 Study of a Developed Model Describing a Vacuum Membrane Distillation Unit Coupled to Solar Energy

Authors: Fatma Khaled, Khaoula Hidouri, Bechir Chaouachi

Abstract:

Desalination using solar energy coupled with membrane techniques such as vacuum membrane distillation (VMD) is considered as an interesting alternative for the production of pure water. During this work, a developed model of a polytetrafluoroethylene (PTFE) hollow fiber membrane module of a VMD unit of seawater was carried out. This simulation leads to establishing a comparison between the effects of two different equations of the vaporization latent heat on the membrane surface temperature and on the unit productivity. Besides, in order to study the effect of putting membrane modules in series on the outlet fluid temperature and on the productivity of the process, a simulation was executed.

Keywords: vacuum membrane distillation, membrane module, membrane temperature, productivity

Procedia PDF Downloads 197
5089 A Metacognitive Strategy to Improve Saudi EFL Learners’ Lecture Comprehension

Authors: Abdul Wahed Al Zumor

Abstract:

Saudi EFL Students majoring in English face difficulties in academic lectures listening comprehension in content courses like linguistics, applied linguistics or literature theories. To validate this assumption, a questionnaire assessing students' lecture comprehension experience was administered. The findings have shown that Saudi EFL learners face a great challenge in lecture comprehension at advanced levels. Literature has suggested a myriad of techniques which can enhance academic lecture comprehension. This study has used "reciprocal peer-questioning and responding technique" as an integral part of the academic lecture occupying the last ten minutes. Improvement in experimental students' scores in these courses has been noticed.

Keywords: EFL learners, lecture comprehension, content courses, peer questioning

Procedia PDF Downloads 601
5088 Investigation of Modified Microporous Materials for Environmental Depollution

Authors: Souhila Bendenia, Chahrazed Bendenia, Hanaa Merad-Dib, Sarra Merabet, Samia Moulebhar, Sid Ahmed Khantar

Abstract:

Today, environmental pollution is a major concernworldwide, threateninghumanhealth. Various techniques have been used, includingdegradation, filtration, advancedoxidationprocesses, ion exchange, membrane processes, and adsorption. The latter is one of the mostsuitablemethods, usinghighly efficient materials. In this study, NaX zeolite was modified with Cu or Ni at various rates. Following ion exchange, the samples were characterized by XRD, BET and SEM/EDX. After characterization, the exchanged zeolites were used for adsorption of various pollutants as CO2. Different thermodynamic parameters were studied such as Qst. XRD results show that the most intense peaks characteristic of 13X persist after the exchange reaction for all samples. The SEM images of our samples have uniform and regular crystal shapes. The results show that ion exhange with Cu or Ni affect the textural properties of X zeolites and prove that the exchange zeolites can be used as an adsorbent for depollution.

Keywords: X zeolites (NaX), ion exchange, characterization, adsorption

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5087 Cooperative CDD Scheme Based On Hierarchical Modulation in OFDM System

Authors: Seung-Jun Yu, Yeong-Seop Ahn, Young-Min Ko, Hyoung-Kyu Song

Abstract:

In order to achieve high data rate and increase the spectral efficiency, multiple input multiple output (MIMO) system has been proposed. However, multiple antennas are limited by size and cost. Therefore, recently developed cooperative diversity scheme, which profits the transmit diversity only with the existing hardware by constituting a virtual antenna array, can be a solution. However, most of the introduced cooperative techniques have a common fault of decreased transmission rate because the destination should receive the decodable compositions of symbols from the source and the relay. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that uses hierarchical modulation. This scheme is free from the rate loss and allows seamless cooperative communication.

Keywords: MIMO, cooperative communication, CDD, hierarchical modulation

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5086 Comparison of MODIS-Based Rice Extent Map and Landsat-Based Rice Classification Map in Determining Biomass Energy Potential of Rice Hull in Nueva Ecija, Philippines

Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang

Abstract:

The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.

Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy

Procedia PDF Downloads 483
5085 A Feature Clustering-Based Sequential Selection Approach for Color Texture Classification

Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

Abstract:

Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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5084 Assessing the Spatial Distribution of Urban Parks Using Remote Sensing and Geographic Information Systems Techniques

Authors: Hira Jabbar, Tanzeel-Ur Rehman

Abstract:

Urban parks and open spaces play a significant role in improving physical and mental health of the citizens, strengthen the societies and make the cities more attractive places to live and work. As the world’s cities continue to grow, continuing to value green space in cities is vital but is also a challenge, particularly in developing countries where there is pressure for space, resources, and development. Offering equal opportunity of accessibility to parks is one of the important issues of park distribution. The distribution of parks should allow all inhabitants to have close proximity to their residence. Remote sensing and Geographic information systems (GIS) can provide decision makers with enormous opportunities to improve the planning and management of Park facilities. This study exhibits the capability of GIS and RS techniques to provide baseline knowledge about the distribution of parks, level of accessibility and to help in identification of potential areas for such facilities. For this purpose Landsat OLI imagery for year 2016 was acquired from USGS Earth Explorer. Preprocessing models were applied using Erdas Imagine 2014v for the atmospheric correction and NDVI model was developed and applied to quantify the land use/land cover classes including built up, barren land, water, and vegetation. The parks amongst total public green spaces were selected based on their signature in remote sensing image and distribution. Percentages of total green and parks green were calculated for each town of Lahore City and results were then synchronized with the recommended standards. ANGSt model was applied to calculate the accessibility from parks. Service area analysis was performed using Network Analyst tool. Serviceability of these parks has been evaluated by employing statistical indices like service area, service population and park area per capita. Findings of the study may contribute in helping the town planners for understanding the distribution of parks, demands for new parks and potential areas which are deprived of parks. The purpose of present study is to provide necessary information to planners, policy makers and scientific researchers in the process of decision making for the management and improvement of urban parks.

Keywords: accessible natural green space standards (ANGSt), geographic information systems (GIS), remote sensing (RS), United States geological survey (USGS)

Procedia PDF Downloads 345
5083 Development of Hybrid Materials Combining Biomass as Fique Fibers with Metal-Organic Frameworks, and Their Potential as Mercury Adsorbents

Authors: Karen G. Bastidas Gomez, Hugo R. Zea Ramirez, Manuel F. Ribeiro Pereira, Cesar A. Sierra Avila, Juan A. Clavijo Morales

Abstract:

The contamination of water sources with heavy metals such as mercury has been an environmental problem; it has generated a high impact on the environment and human health. In countries such as Colombia, mercury contamination due to mining has reached levels much higher than the world average. This work proposes the use of fique fibers as adsorbent in mercury removal. The evaluation of the material was carried out under five different conditions (raw, pretreated by organosolv, functionalized by TEMPO oxidation, fiber functionalized plus MOF-199 and fiber functionalized plus MOF-199-SH). All the materials were characterized using FTIR, SEM, EDX, XRD, and TGA. Regarding the mercury removal, it was done under room pressure and temperature, also pH = 7 for all materials presentations, followed by Atomic Absorption Spectroscopy. The high cellulose content in fique is the main particularity of this lignocellulosic biomass since the degree of oxidation depends on the number of hydroxyl groups on the surface capable of oxidizing into carboxylic acids, a functional group capable of increasing ion exchange with mercury in solution. It was also expected that the impregnation of the MOF would increase the mercury removal; however, it was found that the functionalized fique achieved a greater percentage of removal, resulting in 81.33% of removal, 44% for the fique with the MOF-199 and 72% for the MOF-199-SH with. The pretreated fiber and raw also showed 74% and 56%, respectively, which indicates that fique does not require considerable modifications in its structure to achieve good performances. Even so, the functionalized fiber increases the percentage of removal considerably compared to the pretreated fique, which suggests that the functionalization process is a feasible procedure to apply with the purpose of improving the removal percentage. In addition, this is a procedure that follows a green approach since the reagents involved have low environmental impact, and the contribution to the remediation of natural resources is high.

Keywords: biomass, nanotechnology, science materials, wastewater treatment

Procedia PDF Downloads 120