Search results for: Sn-Ge based
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27435

Search results for: Sn-Ge based

27015 Earnings vs Cash Flows: The Valuation Perspective

Authors: Megha Agarwal

Abstract:

The research paper is an effort to compare the earnings based and cash flow based methods of valuation of an enterprise. The theoretically equivalent methods based on either earnings such as Residual Earnings Model (REM), Abnormal Earnings Growth Model (AEGM), Residual Operating Income Method (ReOIM), Abnormal Operating Income Growth Model (AOIGM) and its extensions multipliers such as price/earnings ratio, price/book value ratio; or cash flow based models such as Dividend Valuation Method (DVM) and Free Cash Flow Method (FCFM) all provide different estimates of valuation of the Indian giant corporate Reliance India Limited (RIL). An ex-post analysis of published accounting and financial data for four financial years from 2008-09 to 2011-12 has been conducted. A comparison of these valuation estimates with the actual market capitalization of the company shows that the complex accounting based model AOIGM provides closest forecasts. These different estimates may be derived due to inconsistencies in discount rate, growth rates and the other forecasted variables. Although inputs for earnings based models may be available to the investor and analysts through published statements, precise estimation of free cash flows may be better undertaken by the internal management. The estimation of value from more stable parameters as residual operating income and RNOA could be considered superior to the valuations from more volatile return on equity.

Keywords: earnings, cash flows, valuation, Residual Earnings Model (REM)

Procedia PDF Downloads 346
27014 Ontology-Based Systemizing of the Science Information Devoted to Waste Utilizing by Methanogenesis

Authors: Ye. Shapovalov, V. Shapovalov, O. Stryzhak, A. Salyuk

Abstract:

Over the past decades, amount of scientific information has been growing exponentially. It became more complicated to process and systemize this amount of data. The approach to systematization of scientific information on the production of biogas based on the ontological IT platform “T.O.D.O.S.” has been developed. It has been proposed to select semantic characteristics of each work for their further introduction into the IT platform “T.O.D.O.S.”. An ontological graph with a ranking function for previous scientific research and for a system of selection of microorganisms has been worked out. These systems provide high performance of information management of scientific information.

Keywords: ontology-based analysis, analysis of scientific data, methanogenesis, microorganism hierarchy, 'T.O.D.O.S.'

Procedia PDF Downloads 138
27013 Development of a Mobile Image-Based Reminder Application to Support Tuberculosis Treatment in Africa

Authors: Haji Ali Haji, Hussein Suleman, Ulrike Rivett

Abstract:

This paper presents the design, development and evaluation of an application prototype developed to support tuberculosis (TB) patients’ treatment adherence. The system makes use of graphics and voice reminders as opposed to text messaging to encourage patients to follow their medication routine. To evaluate the effect of the prototype applications, participants were given mobile phones on which the reminder system was installed. Thirty-eight people, including TB health workers and patients from Zanzibar, Tanzania, participated in the evaluation exercises. The results indicate that the participants found the mobile graphic-based application is useful to support TB treatment. All participants understood and interpreted the intended meaning of every image correctly. The study findings revealed that the use of a mobile visual-based application may have potential benefit to support TB patients (both literate and illiterate) in their treatment processes.

Keywords: ICT4D, mobile technology, tuberculosis, visual-based reminder

Procedia PDF Downloads 408
27012 Relaxation Behavior of Biorenewable Waterborne Castor Oil-Based Polyurethane-Lignin Thin Films

Authors: Samy Madbouly

Abstract:

The relaxation behavior of biorenewable castor oil-based polyurethane-lignin thin films synthesized in homogenous waterborne dispersions was investigated as a function of concentration at different temperatures and frequencies using broadband dielectric relaxation spectroscopy (BDRS). The molecular dynamics of the glass relaxation process and the local relaxation process of the PU-LS thin films were studied over a wide range of temperatures (-70 to 30 ℃) and frequencies (5 × 10−2 to 0.5 × 107 Hz) for different lignin concentration. Four relaxation processes have been observed namely; ?-, β-, γ-relaxations and ionic conductivity for pure castor oil-based PU and castor oil-lignin-based PU thin films at different temperatures and frequencies ranges. The Vogel-Fulcher-Tammann equation was found to be well described the temperature dependence of the characteristic relaxation times of the ?-relaxation process. However, on the other hand, the molecular dynamics of both β- and γ-relaxation processes were given by the Arrhenius equation. The incorporation of lignin into the castor oil-based PU significantly increased the glass transition temperature and primitivity of the thin films. In addition, the broadness, intensity, and molecular dynamics of the only observed ?-relaxation process were found to be strongly dependent on lignin concentration.

Keywords: castor oil, lignin, polyurethane, dielectric, dispersions

Procedia PDF Downloads 176
27011 High Performance Ceramic-Based Phthalonitrile Micro and Nanocomposites

Authors: M. Derradji, W. B. Liu

Abstract:

The current work discusses the effects of adding various types of ceramic fillers on the curing behavior, thermal, mechanical, anticorrosion, and UV shielding properties of the bisphenol-A based phthalonitrile resins. The effects of different ceramic filler contents and sizes as well as their surface treatments are also discussed in terms of their impact on the morphology and mechanisms of enhancement. The synergistic effect obtained by these combinations extends the use of the phthalonitrile resins to more exigent applications such as aerospace and military. The presented results reveal the significant advantages that can be obtained from the preparation of hybrid materials based on phthalonitrile resins and open the way for further research in the field.

Keywords: mechanical properties, particle reinforced composites, polymer matrix composites (PMCs), thermal properties

Procedia PDF Downloads 127
27010 The Continuing Professional Development of the Assessment through Research-Based Learning in Higher Education of Thailand

Authors: P. Junpeng, A. Tungkasamit

Abstract:

Research-based learning is the key for the national research universities of Thailand. The indicator reflects the success of the study in assessing the learning outcomes of students. The development of the lecturers is the most important mechanism in driving. Nowadays the lecturers lack the knowledge and skills of assessment for learning. Therefore, this study aims to develop the knowledge and skills for lecturer’s assessment through research-based learning in higher education. The target group were lecturers who teach in higher education from Khon Kaen University of Thailand. This study was a research and development involved the concept of continuing professional development. Research was conducted in 3 phases: 1) to inspire one’s thought, to accomplish both knowledge and skill, 2) to focus on changes, and 3) to reflect the changes as well as suggest the guidelines for development. The results showed that the lecturers enhanced their knowledge and skill in assessment and emphasized on assessment for learning rather than assessment of learning.

Keywords: research-based nexus, professional development, assessment for learning, higher education

Procedia PDF Downloads 335
27009 Detectability Analysis of Typical Aerial Targets from Space-Based Platforms

Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

Abstract:

In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.

Keywords: space-based detection, aerial targets, detectability analysis, scene environment

Procedia PDF Downloads 123
27008 Instance Selection for MI-Support Vector Machines

Authors: Amy M. Kwon

Abstract:

Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

Procedia PDF Downloads 9
27007 Rest API Based System-level Test Automation for Mobile Applications

Authors: Jisoo Song

Abstract:

Today’s mobile applications are communicating with servers more and more in order to access external services or information. Also, server-side code changes are more frequent than client-side code changes in a mobile application. The frequent changes lead to an increase in testing cost increase. To reduce costs, UI based test automation can be one of the solutions. It is a common automation technique in system-level testing. However, it can be unsuitable for mobile applications. When you automate tests based on UI elements for mobile applications, there are some limitations such as the overhead of script maintenance or the difficulty of finding invisible defects that UI elements cannot represent. To overcome these limitations, we present a new automation technique based on Rest API. You can automate system-level tests through test scripts that you write. These scripts call a series of Rest API in a user’s action sequence. This technique does not require testers to know the internal implementation details, only input and expected output of Rest API. You can easily modify test cases by modifying Rest API input values and also find problems that might not be evident from the UI level by validating output values. For example, when an application receives price information from a payment server and user cannot see it at UI level, Rest API based scripts can check whether price information is correct or not. More than 10 mobile applications at our company are being tested automatically based on Rest API scripts whenever application source code, mostly server source code, is built. We are finding defects right away by setting a script as a build job in CI server. The build job starts when application code builds are completed. This presentation will also include field cases from our company.

Keywords: case studies at SK Planet, introduction of rest API based test automation, limitations of UI based test automation

Procedia PDF Downloads 421
27006 Ab Initio Studies of Organic Electrodes for Li and Na Ion Batteries Based on Tetracyanoethylene

Authors: Yingqian Chen, Sergei Manzhos

Abstract:

Organic electrodes are a way to achieve high rate (high power) and environment-friendly batteries. We present a computational density functional theory study of Li and Na storage in tetracyanoethylene based molecular and crystalline materials. Up to five Li and Na atoms can be stored on TCNE chemisorbed on doped graphene (corresponding to ~1000 mAh/gTCNE), with binding energies stronger than cohesive energies of the Li and Na metals by 1-2 eV. TCNE has been experimentally shown to form a crystalline material with Li with stoichiometry Li-TCNE. We confirm this computationally and also predict that a similar crystal based of Na-TCNE is also stable. These crystalline materials have well defined channels for facile Li or Na ion insertion and diffusion. Specifically, Li and Na binding energies in Li-TCNE and Na-TCNE crystals are about 1.5 eV and stronger than the cohesive energy of Li and Na, respectively. TCNE immobilized on conducting graphene-based substrates and Li/Na-TCNE crystals could therefore become efficient anode materials for organic Li and Na ion batteries, with which it should also be possible to avoid reduction of common battery electrolytes.

Keywords: organic ion batteries, tetracyanoethylene, cohesive energies, electrolytes

Procedia PDF Downloads 609
27005 A Collaborative Learning Model in Engineering Science Based on a Cyber-Physical Production Line

Authors: Yosr Ghozzi

Abstract:

The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

Procedia PDF Downloads 71
27004 Developing a Web-Based Tender Evaluation System Based on Fuzzy Multi-Attributes Group Decision Making for Nigerian Public Sector Tendering

Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

Abstract:

Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, group decision making, tender evaluation, tender evaluation committee, UML, object-oriented methodologies, system development

Procedia PDF Downloads 239
27003 Cell-Based and Exosome Treatments for Hair Restoration

Authors: Armin Khaghani Boroujeni, Leila Dehghani, Parham Talebi Boroujeni, Sahar Rostamian, Ali Asilian

Abstract:

Background: Hair loss is a common complaint observed in both genders. Androgenetic alopecia is known pattern for hair loss. To assess new regenerative strategies (PRP, A-SC-BT, conditioned media, exosome-based treatments) compared to conventional therapies for hair loss or hair regeneration, an updated review was undertaken. To address this issue, we carried out this systematic review to comprehensively evaluate the efficacy of cell-based therapies on hair loss. Methods: The available online databases, including ISI Web of Science, Scopus, and PubMed, were searched systematically up to February 2022. The quality assessment of included studies was done using the Cochrane Collaboration's tool. Results: As a result, a total of 90 studies involving 2345 participants were included in the present study. The enrolled studies were conducted between 2010 and 2022. The subjects’ mean age ranged from 19 to 55.11 years old. Approaches using platelet rich plasma (PRP) provide a beneficial impact on hair regrowth. However, other cell-based therapies, including stem cell transplant, stem cell-derived conditioned medium, and stem cell-derived exosomes, revealed conflicting evidence. Conclusion: However, cell-based therapies for hair loss are still in their infancy, and more robust clinical studies are needed to better evaluate their mechanisms of action, efficacy, safety, benefits, and limitations. In this review, we provide the resources to the latest clinical studies and a more detailed description of the latest clinical studies concerning cell-based therapies in hair loss.

Keywords: cell-based therapy, exosome, hair restoration, systematic review

Procedia PDF Downloads 54
27002 Study of the Business Ethics Based on Daimler Bribery Case in China

Authors: Yuandi Hu, Gang Yang

Abstract:

In order to study the business ethics of the international enterprise, the thirteenth-largest car manufacturer and second-largest truck manufacturer in the world, Daimler AG was taken as research object. At first, Daimler AG is briefly introduced and the bribery affairs of Daimler AG in China are simply reviewed. Subsequently, the causes of the bribery are discussed in depth and the manifestations of the value conflict are analyzed in detail. Based on the analyzed results, the reasons why they bribe are investigated. Furthermore, some proposals for improving business ethics of international enterprises are put forward based on the study of Daimler bribery case.

Keywords: business ethics, Daimler AG, bribe, cultural conflict

Procedia PDF Downloads 351
27001 A Review of Methods for Handling Missing Data in the Formof Dropouts in Longitudinal Clinical Trials

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 391
27000 Spatially Distributed Rainfall Prediction Based on Automated Kriging for Landslide Early Warning Systems

Authors: Ekrem Canli, Thomas Glade

Abstract:

The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

Procedia PDF Downloads 263
26999 Comparative Analysis of Control Techniques Based Sliding Mode for Transient Stability Assessment for Synchronous Multicellular Converter

Authors: Rihab Hamdi, Amel Hadri Hamida, Fatiha Khelili, Sakina Zerouali, Ouafae Bennis

Abstract:

This paper features a comparative study performance of sliding mode controller (SMC) for closed-loop voltage control of direct current to direct current (DC-DC) three-cells buck converter connected in parallel, operating in continuous conduction mode (CCM), based on pulse-width modulation (PWM) with SMC based on hysteresis modulation (HM) where an adaptive feedforward technique is adopted. On one hand, for the PWM-based SM, the approach is to incorporate a fixed-frequency PWM scheme which is effectively a variant of SM control. On the other hand, for the HM-based SM, oncoming an adaptive feedforward control that makes the hysteresis band variable in the hysteresis modulator of the SM controller in the aim to restrict the switching frequency variation in the case of any change of the line input voltage or output load variation are introduced. The results obtained under load change, input change and reference change clearly demonstrates a similar dynamic response of both proposed techniques, their effectiveness is fast and smooth tracking of the desired output voltage. The PWM-based SM technique has greatly improved the dynamic behavior with a bit advantageous compared to the HM-based SM technique, as well as provide stability in any operating conditions. Simulation studies in MATLAB/Simulink environment have been performed to verify the concept.

Keywords: DC-DC converter, hysteresis modulation, parallel multi-cells converter, pulse-width modulation, robustness, sliding mode control

Procedia PDF Downloads 143
26998 A Data-Driven Monitoring Technique Using Combined Anomaly Detectors

Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

Abstract:

Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

Procedia PDF Downloads 273
26997 Effect of N2 Pretreatment on the Properties of Tungsten Based Catalysts in Metathesis of Ethylene and 2-Butene

Authors: Kriangkrai Aranyarat

Abstract:

The effect of N2 pretreatment on the catalytic activity of tungsten-based catalysts was investigated in the metathesis of ethylene and trans-2-butene at 450oC and atmospheric pressure. The presence of tungsten active species was confirmed by UV-Vis and Raman spectroscopy. Compared to the WO3-based catalysts treated in air, higher amount of WO42- tetrahedral species and lower amount of WO3 crystalline species were observed on the N2-treated ones. These contribute to the higher conversion of 2-butene and propylene selectivity during 10 h time-on-stream. Moreover, N2 treatment led to lower amount of coke formation as revealed by TPO of the spent catalysts.

Keywords: metathesis, pretreatment, propylene, tungsten

Procedia PDF Downloads 442
26996 Farm Diversification and the Corresponding Policy for Its Implementation in Georgia

Authors: E. Kharaishvili

Abstract:

The paper shows the necessity of farm diversification in accordance with the current trends in agricultural sector of Georgia. The possibilities for the diversification and the corresponding economic policy are suggested. The causes that hinder diversification of farms are revealed, possibilities of diversification are suggested and the ability of increasing employment through diversification is proved. Index of harvest diversification is calculated based on the areas used for cereals and legumes, potatoes and vegetables and other food crops. Crop and livestock production indexes are analyzed, correlation between crop capacity index and value-added per one worker and one ha is studied. Based on the research farm diversification strategies and priorities of corresponding economic policy are presented. Based on the conclusions relevant recommendations are suggested.

Keywords: farm diversification, diversification index, agricultural development policy

Procedia PDF Downloads 442
26995 Probabilistic Model for Evaluating Seismic Soil Liquefaction Based on Energy Approach

Authors: Hamid Rostami, Ali Fallah Yeznabad, Mohammad H. Baziar

Abstract:

The energy-based method for evaluating seismic soil liquefaction has two main sections. First is the demand energy, which is dissipated energy of earthquake at a site, and second is the capacity energy as a representation of soil resistance against liquefaction hazard. In this study, using a statistical analysis of recorded data by 14 down-hole array sites in California, an empirical equation was developed to estimate the demand energy at sites. Because determination of capacity energy at a site needs to calculate several site calibration factors, which are obtained by experimental tests, in this study the standard penetration test (SPT) N-value was assumed as an alternative to the capacity energy at a site. Based on this assumption, the empirical equation was employed to calculate the demand energy for 193 liquefied and no-liquefied sites and then these amounts were plotted versus the corresponding SPT numbers for all sites. Subsequently, a discrimination analysis was employed to determine the equations of several boundary curves for various liquefaction likelihoods. Finally, a comparison was made between the probabilistic model and the commonly used stress method. As a conclusion, the results clearly showed that energy-based method can be more reliable than conventional stress-based method in evaluation of liquefaction occurrence.

Keywords: energy demand, liquefaction, probabilistic analysis, SPT number

Procedia PDF Downloads 343
26994 Divalent Iron Oxidative Process for Degradation of Carbon and Nitrogen Based Pollutants from Dye Intermediate Industrial Wastewater

Authors: Nibedita Pani, Vishnu Tejani, T. S. Anantha Singh

Abstract:

Water pollution resulting from discharge of partial/not treated textile wastewater containing high carbon and nitrogen pollutants pose a huge threat to the environment, ecosystem, and human health. It is essential to remove carbon- and nitrogen-based organic pollutants more effectively from industrial wastewater before discharging. The present study focuses on removal of carbon-based pollutant in particular COD (chemical oxygen demand) and nitrogen-based pollutants, in particular, ammoniacal nitrogen by Fenton oxidation process using Fe²⁺ and H₂O₂ as reagents. The study was carried out with high strength wastewater containing initial COD 5632 mg/L and NH⁴⁺-N 1372 mg/L. The major operating condition like pH was varied between 1.0 to 4.0. The maximum degradation was obtained at pH 3.0 taking the molar ratio of Fe²⁺/H₂O₂ as 1:1. At this pH, the removal efficiencies of COD and ammoniacal nitrogen were found to be 77.27% and 74.9%, respectively. The Fenton process can be the best alternative for the simultaneous removal of COD and NH4+-N from industrial wastewater.

Keywords: ammoniacal nitrogen, COD, Fenton oxidation, industrial wastewater

Procedia PDF Downloads 165
26993 Cooperative Cross Layer Topology for Concurrent Transmission Scheduling Scheme in Broadband Wireless Networks

Authors: Gunasekaran Raja, Ramkumar Jayaraman

Abstract:

In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

Procedia PDF Downloads 233
26992 Towards a Goal-Question-Metric Based Approach to Assess Social Sustainability of Software Systems

Authors: Rahma Amri, Narjès Bellamine Ben Saoud

Abstract:

Sustainable development or sustainability is one of the most urgent issues in actual debate in almost domains. Particularly the significant way the software pervades our live should make it in the center of sustainability concerns. The social aspects of sustainability haven’t been well studied in the context of software systems and still immature research field that needs more interest among researchers’ community. This paper presents a Goal-Question-Metric based approach to assess social sustainability of software systems. The approach is based on a generic social sustainability model taken from Social sciences.

Keywords: software assessment approach, social sustainability, goal-question-metric paradigm, software project metrics

Procedia PDF Downloads 368
26991 Efficient Frequent Itemset Mining Methods over Real-Time Spatial Big Data

Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

Abstract:

In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

Procedia PDF Downloads 133
26990 Shared Decision-Making in Holistic Healthcare: Integrating Evidence-Based Medicine and Values-Based Medicine

Authors: Ling-Lang Huang

Abstract:

Research Background: Historically, the evolution of medicine has not only aimed to extend life but has also inadvertently introduced suffering in the process of maintaining life, presenting a contemporary challenge. We must carefully assess the conflict between the length of life and the quality of living. Evidence-Based Medicine (EBM) exists primarily to ensure the quality of cures. However, EBM alone does not fulfill our ultimate medical goals; we must also evaluate Value-Based Medicine (VBM) to find the best treatment for patients. Research Methodology: We can attempt to integrate EBM with VBM. Within the five steps of EBM, the first three steps (Ask—Acquire—Appraise) focus on the physical aspect of humans. However, in the fourth and fifth steps (Apply—Assess), the focus shifts from the physical to applying evidence-based treatment to the patient and assessing its effectiveness, considering a holistic approach to the individual. To consider VBM for patients, we can divide the process into three steps: The first step is "awareness," recognizing that each patient inhabits a different life-world and possesses unique differences. The second step is "integration," akin to the hermeneutic concept of the Fusion of Horizons. This means being aware of differences and also understanding the origins of these patient differences. The third step is "respect," which involves setting aside our adherence to medical objectivity and scientific rigor to respect the ultimate healthcare decisions made by individuals regarding their lives. Discussion and Conclusion: After completing these three steps of VBM, we can return to the fifth step of EBM: Assess. Our assessment can now transcend the physical treatment focus of the initial steps to align with a holistic care philosophy.

Keywords: shared decision-making, evidence-based medicine, values-based medicine, holistic healthcare

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26989 Attention Based Fully Convolutional Neural Network for Simultaneous Detection and Segmentation of Optic Disc in Retinal Fundus Images

Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

Abstract:

Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: attention-based fully convolutional network, optic disc detection and segmentation, retinal fundus image, screening of ocular diseases

Procedia PDF Downloads 112
26988 Implementation of Computer-Based Technologies into Foreign Language Teaching Process

Authors: Golovchun Aleftina, Dabyltayeva Raikhan

Abstract:

Nowadays, in the world of widely developing cross-cultural interactions and rapidly changing demands of the global labor market, foreign language teaching and learning has taken a special role not only in school education but also in everyday life. Cognitive Lingua-Cultural Methodology of Foreign Language Teaching originated in Kazakhstan brings a communicative approach to the forefront in foreign language teaching that gives raise a variety of techniques to make the language learning a real communication. One of these techniques is Computer Assisted Language Learning. In our article, we aim to: demonstrate what learning benefits students are likely to get by teachers having implemented computer-based technologies into foreign language teaching process; prove that technology-based classroom serves as the best tool for interactive and efficient language learning; give examples of classroom sufficient organization with computer-based activities.

Keywords: computer assisted language learning, learning benefits, foreign language teaching process, implementation, communicative approach

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26987 Ready Student One! Exploring How to Build a Successful Game-Based Higher Education Course in Virtual Reality

Authors: Robert Jesiolowski, Monique Jesiolowski

Abstract:

Today more than ever before, we have access to new technologies which provide unforeseen opportunities for educators to pursue in online education. It starts with an idea, but that needs to be coupled with the right team of experts willing to take big risks and put in the hard work to build something different. An instructional design team was empowered to reimagine an Introduction to Sociology university course as a Game-Based Learning (GBL) experience utilizing cutting edge Virtual Reality (VR) technology. The result was a collaborative process that resulted in a type of learning based in Game theory, Method of Loci, and VR Immersion Simulations to promote deeper retention of core concepts. The team deconstructed the way that university courses operated, in order to rebuild the educational process in a whole learner-centric manner. In addition to a review of the build process, this paper will explore the results of in-course surveys completed by student participants.

Keywords: higher education, innovation, virtual reality, game-based learning, loci method

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26986 A Chinese Nested Named Entity Recognition Model Based on Lexical Features

Authors: Shuo Liu, Dan Liu

Abstract:

In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.

Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm

Procedia PDF Downloads 102