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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 874 Documents
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Optical and Structural Characterization of Bi2FexNbO7 Nanoparticles for Environmental Applications Araujo Scharnberg, Allan Ramone; Carvalho de Loreto, Adrison; Kopp Alves, Annelise
Emerging Science Journal Vol 4, No 1 (2020): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01205

Abstract

Photocatalytic materials development is very important from an environmental perspective. They can be employed in clean energy production by hydrogen generation as well as in wastewater treatment by photocatalysis. One of the key subjects in this area is the advancement of materials with a low band gap, thus the catalyst can use the sunlight more efficiently. Based on this issue, this research aims to develop photocatalysts based on bismuth, niobium, and iron (Bi2FexNbO7), analyze the influence of iron concentration (x = 0, 0.8, 1, and 1.2) and characterize them through optical and structural analysis. The powder samples were synthetized by the sol-gel method. Band gap estimation was performed using UV-Vis analysis and the Kubelka-Munk method. The XRD technique was employed for phase determination and structural characterization. The catalyst with no iron (Bi2NbO7) presented a mix of three phases of reagents and a band gap of 3.14 eV. The iron addition promotes crystalline photocatalysts with high visible light absorption ability and a lower band gap, 2.09 eV. Further analysis must be performed. However, based on structural and optical proprieties, these materials can efficiently be employed both in wastewater treatment and hydrogen production.
Zeolite Based Air Electrodes for Secondary Batteries Miglena Slavova; Elena Mihaylova-Dimitrova; Emiliya Mladenova; Borislav Abrashev; Blagoy Burdin; Daria Vladikova
Emerging Science Journal Vol 4, No 1 (2020): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01206

Abstract

In recent years, secondary batteries received considerable attention as promising technology for energy storage in combination with renewable energy sources. The oxidation of carbon in conventional air electrodes reduces the life of secondary batteries. One possible solution for overcoming this problem is the replacement of carbon material with zeolite.Zeolite is a natural or synthetic porous material with crystalline structure which provides the necessary gas permeability. The required hydrophobicity of the electrode is ensured by mixing zeolite with an appropriate amount of polytetrafluoroethylene following a specially developed procedure. The main purpose of the present research is to discover the optimum level of hydrophobicity (impregnation) of zeolite. Moreover, appropriate amount of PTFE will ensure better mechanical stability and long charge/discharge cycle life.The results from this study show that the replacement of carbon with zeolite in the gas diffusion layer is a promising direction for optimization of the bi-functional air electrode. The relationship between the particle size and the hydrophobicity of the electrode was found. It was found that the mechanical stability and hydrophobicity of the electrode improved with the replacement of the emulsion powder. The gas permeability is maintained in the norms, which guarantees the good performance of the electrode. More than 200 charge/discharge cycles were reached.
Sparse Nonlinear Feature Selection Algorithm via Local Structure Learning Jiaye Li; Guoqiu Wen; Jiangzhang Gan; Leyuan Zhang; Shanwen Zhang
Emerging Science Journal Vol 3, No 2 (2019): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2019-01175

Abstract

In this paper, we propose a new unsupervised feature selection algorithm by considering the nonlinear and similarity relationships within the data. To achieve this, we apply the kernel method and local structure learning to consider the nonlinear relationship between features and the local similarity between features. Specifically, we use a kernel function to map each feature of the data into the kernel space. In the high-dimensional kernel space, different features correspond to different weights, and zero weights are unimportant features (e.g. redundant features). Furthermore, we consider the similarity between features through local structure learning, and propose an effective optimization method to solve it. The experimental results show that the proposed algorithm achieves better performance than the comparison algorithm.
Computational Fluid Dynamics Analysis of Stove Systems for Cooking and Drying of Muga Silk Anal Ranjan Sengupta; R. Gupta; A. Biswas
Emerging Science Journal Vol 3, No 5 (2019): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2019-01191

Abstract

In India, Silk industry plays an important part in textile industry. Muga silk, the golden yellow silk is quite unique to Assam, North-east India where its production is regarded as an important tool for economic development. But, outdated manufacturing technology is followed during the silk production in Assam. The existing cooking process of silk cocoons consists of boiling of silk cocoons in a stainless steel vessel along with water and soda in an open fireplace which is highly energy inefficient. Therefore, two modified systems have been designed; one having cylindrical boiling chamber (vessel) and the other having spherical boiling chamber (vessel). Both the chambers are having a cocoon heating chamber associated with them for cooking and drying of silk cocoons simultaneously. These designs are further classified into two types of designs based on channel and nozzle type combustion chambers. Therefore, the main objective of this paper is to improve the existing designs to maximize the utilization of heat carried by the combustion gases. These modified systems are analysed by using Computational Fluid Dynamics (CFD) selecting standard k–є model. From the analysis, it is seen that these new systems having nozzle type combustion chambers are more efficient than the systems having cylindrical combustion chambers and if these systems are used in silk production, it will be very beneficial for the silk industry as well as for our society.
Female Objects and Feminist Consciousness for the Purpose to Awake Readers’ Awareness: A Comparative Analysis between Angela Carter’s The Bloody Chamber and Anne Sexton’s Transformations Liu Fenglin
Emerging Science Journal Vol 4, No 1 (2020): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01207

Abstract

The female object, as a symbolic image created by male authors to reduce the threat brought by females towards patriarchy, has become a method to express male sexual and domestic fantasies. However, in the fairy tale adaptation by two mid-twentieth century female authors-Angela Carter and Anne Sexton, the female object is used to evoke feminist consciousness. Although former studies have covered some feminism issues, for instance, the feminist awareness through the mirror image in Angela Carter’s The Bloody Chamber, and the direct metaphors such as “doll” and “soap pop” which lead to female objectification in Anne Sexton’s Transformations, little research has compared the distinctive psychological impacts that the narrative forms between the two mentioned texts have on readers. In the first section of this paper, how both authors deconstruct the female stereotypes and how they reinterpret modes of female agency in the original Grimm’s fairy tales have been examined. Based on the writers’ perspective, the first section would also explore the expression of female objects in their works. As for the second section, I would mainly focus on the psychoanalysis of Lacan’s mirror stages, and yet cover the awakening processes presented in the mirror images and symbols composed in the two adaptations. In the third section, the different narrative strategies utilized by Carter and Sexton in order to stimulate readers’ responses towards feminist consciousness would be illustrated.
Artificial Neural Network Model to Prediction of Eutrophication and Microcystis Aeruginosa Bloom Pawalee Srisuksomwong; Jeeraporn Pekkoh
Emerging Science Journal Vol 4, No 2 (2020): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01217

Abstract

Maekuang reservoir is one of the water resources which provides water supply, livestock, and recreational in Chiangmai city, Thailand. The water quality and Microcystis aeruginosa are a severe problem in many reservoirs. M. aeruginosa is the most widespread toxic cyanobacteria in Thailand. Difficulty prediction for planning protects Maekuang reservoirs, the artificial Neural Network (ANN) model is a powerful tool that can be used to machine learning and prediction by observation data. ANN is able to learn from previous data and has been used to predict the value in the future. ANN consists of three layers as input, hidden, and output layer. Water quality data is collected biweekly at Maekuang reservoir (1999-2000). Input data for training, including nutrients (ammonium, nitrate, and phosphorus), Secchi depth, BOD, temperature, conductivity, pH, and output data for testing as Chlorophyll a and M. aeruginosa cells. The model was evaluated using four performances, namely; mean squared error (MSE), root mean square error (RMSE), sum of square error (SSE), and percentage error. It was found that the model prediction agreed with experimental data. C01-C08 scenarios focused on M. aeruginosa bloom prediction, and ANN tested for prediction of Chlorophyll a bloom shown on M01-M09 scenarios. The findings showed, this model has been validated for prediction of Chlorophyll a and shows strong agreement for nitrate, Log cell, and Chlorophyll a. Results indicate that the ANN can be predicted eutrophication indicators during the summer season, and ANN has efficient for providing the new data set and predict the behavior of M. aeruginosa bloom process.
Effects of Chromium Doping on the Electrical Properties of ZnO Nanoparticles S. Janet Priscilla; V. Andria Judi; R. Daniel; K. Sivaji
Emerging Science Journal Vol 4, No 2 (2020): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01212

Abstract

Nanostructured ZnO has gained a considerable amount of attention due to its unique physical and chemical properties and due to its remarkable performance in the fields of optics, photonics and electronics. The scope of this work is to study the Structural, Optical and Electronic properties of Pure Zinc Oxide (ZnO) and Chromium doped Zinc Oxide nanoparticles. These nanoparticles were synthesized by low-temperature precipitation method at various concentrations in the range (Zn1-xCrxO; (x = 0, 0.1& 0.3)). The precursors used were analytical grade Zinc Nitrate Hexahydrate and Chromium Nitrate Nona hydrate. The synthesized nanoparticles were annealed at 400°C. The Structural property of the synthesized nanoparticles was analysed by XRD (X-Ray diffraction) and was confirmed to exhibit a crystalline hexagonal wurtzite structure with an average crystallite size of 55nm. The functional groups were analysed using FTIR (Fourier Transformed Infra-red spectroscopy). The Morphology was analysed by FESEM (Field Emission Scanning Electron Microscope) and a change in morphology from spherical to spindle like structure was observed. The Optical properties were analysed using UV-Vis spectroscopy, the absorption spectrum for electromagnetic spectrum was observed and the changes in the optical band gap of ZnO nanoparticles with Chromium dopant addition were calculated to be in the range of 3.6 eV. The Electrical property of the synthesised nanoparticles was analysed using Electrochemical Impedance Spectroscopy (EIS) and the conductivity was calculated to be in the range of 1.1e-07S/m.
Application of Predictive Maintenance in Hospital Heating, Ventilation and Air Conditioning Facilities Gonzalo Sánchez-Barroso; Justo García Sanz-Calcedo
Emerging Science Journal Vol 3, No 5 (2019): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2019-01196

Abstract

The variety of a hospital’s users leads to different levels of requirements relating to indoor environmental conditions. The responsibility for generating these favourable conditions for the pathologies treated in the different areas of a hospital lies with heating, ventilating and air-conditioning (HVAC) system. They carry out the control of nosocomial infections. Consequently, establishing adequate maintenance plans for these facilities will have a high positive impact on economic and environmental management, on the one hand, and on people's health, on the other. The aim of this work is to analyse foreseeable information and results generated after applying condition-based maintenance (CBM) techniques. The Weibull distribution was used to model the distribution of equipment failures and the potential of the information obtained from applying the CBM methodology was highlighted. The results of this work represent an improvement in the working practise of the HVAC facilities hospital maintenance departments. They dispose of information to decide on investment in equipment taking into account maintenance costs. In addition, this allow analyse data to know current status of a piece of equipment or unit, thus establishing an optimized maintenance plan considering asset’s remaining useful life and associated maintenance costs.
The H2020 OCRE Project Opens the Gates of the Commercial Cloud and EO Services Usage to the Research Community José Manuel Delgado Blasco; Antonio Romeo; David Heyns; Joao Fernandes; Rob Carrillo; Natassa Antoniou; Lefteris Mamais; Marc-Elian Begin
Emerging Science Journal Vol 4, No 2 (2020): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01213

Abstract

Cloud and Earth Observation (EO) based services offer the European Research community a wealth of powerful tools. However, for many researchers these tools are currently out of reach. It is difficult to find and select suitable services. Establishing agreements with cloud and EO service providers and ensuring legal and technical compliance requires specialist skills and takes an inordinate amount of time. Equally, service providers find it difficult to reach and meet the needs of the research community in technical, financial and legal areas. The Open Clouds for Research Environments consortium (OCRE) will change this, by putting in place an easy adoption route. In the autumn of 2019, OCRE will run a pan-European tender and establish framework agreements with service providers who meet the requirements of the research community. 10.000 European research and education institutes will be able to directly consume these offerings via the European Open Science Cloud service catalogue, through ready-to-use agreements. They will not have to run a tender of their own. In addition, to stimulate usage, OCRE will make available 9.5 million euro in service credits (vouchers), through adoption funds from the European Commission. OCRE is a pioneer project without precedence, with potentially high impact in the future EO market activities and evolution of service offering, with the objective to burst the usage of EO commercial services by the research environment.
Residential Mortgage Loans Delinquencies Analysis and Risk Drivers Assessment Aivars Spilbergs
Emerging Science Journal Vol 4, No 2 (2020): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/esj-2020-01214

Abstract

Residential mortgage loans play an important role in improving living conditions in developed countries. In Latvia, however, residential mortgage volumes have declined throughout the post-crisis year’s and were at the end of 2018 12% below the end 2008 level, while the house price index ca. 25% below pre-crisis level. The main reasons for this are banks credit losses, which resulted in a revision of credit granting standards and a deteriorating in their availability. On the other hand, households have experienced increased uncertainty, both as a result of financial difficulties, experienced during the crisis years and political instability in the post-crisis years. It is therefore essential to identify the true risk drivers and to analyse them. Based on existing researches in other countries, the author has identified several dozen macro-economic indicators, such as the unemployment rate, wage growth, housing price index, etc. and micro factors such as the age of the borrower, total debt to income, loan-to-value, etc., have developed univariate and multivariate econometric models and have examined their statistical stability. Consequently, through a consistent application, it is possible to take sound credit decisions, both in banks and by households, and to contribute to the sustainable development of the housing market.

Page 12 of 88 | Total Record : 874

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