Search results for: large industries

Authors: M. Bakhtaoui, L. Merahi

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The reliability of the filtered HVBK model is now investigated via some large eddy simulations of freely decaying isotropic superfluid turbulence. For homogeneous turbulence at very high Reynolds numbers, comparison of the terms in the spectral kinetic energy budget equation indicates, in the energy-containing range, that the production and energy transfer effects become significant except for dissipation. In the inertial range, where the two fluids are perfectly locked, the mutual friction maybe neglected with respect to other terms. Also the LES results for the other terms of the energy balance are presented.

Keywords: superfluid turbulence, HVBK, energy budget, Large Eddy Simulation

Procedia PDF Downloads 372

Authors: Minbale Aschale, Bitew K. Dessie, Endaweke Assegide, Yosef Abebe, Tena Alamirew, Claire L. Walsh, Gete Zeleke

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The upper Awash Basin faces pollution challenges due to urbanization, population growth, and expanding industries. It receives various pollutants from its catchments. The study aimed to assess the impact of wastewater irrigation on vegetables and inform stakeholders about pollution challenges and consequences. Eighty-two composite samples of matured vegetables were randomly collected from twenty-one agricultural farm sites. These samples were analyzed for potentially toxic elements, including Cd, Pb, Cr, Hg, As, Ni, Sr, B, Co, Cu, Mn, Fe, Zn, and Se. The results indicated significant variations in concentrations across different sites, with localized contributions from various contaminants. Cr, Cd, and Pb concentrations in most vegetables exceeded recommended levels. Pollution levels varied with metals and vegetable types. Different vegetables contribute differently to health risks. The relative contributions of Ethiopian kale, cabbage, red beet, lettuce, Swiss chard, Gurage cabbage, tomato, zucchini, carrot, onion, watermelon, and potato to the aggregated risk were 12.69%, 12.25%, 11.83%, 11.20%, 10.21%, 9.91%, 8.49%, 5.66%, 3.96%, 3.35%, 3.10%, and 2.72%, respectively. Comparison with permissible standards revealed inadequate environmental management by relevant regulatory bodies and industries. Despite good laws and standards at the federal and regional levels, they are ineffectively implemented or enforced to prevent environmental pollution. Mitigation measures are urgently recommended to address the potential health implications of toxic substances.

Keywords: pollution, upper Awash Basin, health risk, Ethiopia

Procedia PDF Downloads 46

Authors: Abbas Raza Ali

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Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 173

Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Ngonidzashe Mangoma, Caroline Marigold Sebata

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The release of cyanide-rich effluents from gold mines, and other industries, into the environment, is a global concern considering the well-known metabolic effects of cyanide in all forms of life. Such effluents need to be treated to remove cyanide, among other pollutants, before their disposal. This study aimed at investigating the possible use of bacteria in the biological removal of cyanide from cyanide-rich effluents. Firstly, cyanide-degrading bacteria were isolated from gold mine effluents and characterised. The isolates were then tested for their ability to grow in the presence of cyanide and their tolerance to increasing levels of the compound. To evaluate each isolate’s cyanide-degrading activities, isolates were grown in the simulated and actual effluent, and a titrimetric method was used to quantify residual cyanide over a number of days. Cyanide degradation efficiency (DE) was then calculated for each isolate. Identification of positive isolates involved 16S rRNA gene amplification and sequence analysis through BLAST. Six cyanide-utilising bacterial strains were isolated. Two of the isolates were identified as Klebsiella spp. while the other two were shown to be different strains of Clostridium bifermentans. All isolates showed normal growth in the presence of cyanide, with growth being inhibited at 700 mg/L cyanide and beyond. Cyanide degradation efficiency for all isolates in the simulated effluent ranged from 79% to 97%. All isolates were able to remove cyanide from actual gold mine effluent with very high DE values (90 – 94%) being recorded. Isolates obtained in this study were able to efficiently remove cyanide from both simulated and actual effluent. This observation clearly demonstrates the feasibility of the biological removal of cyanide from cyanide-rich gold mine effluents and should, therefore, motivate research towards the possible large-scale application of this technology.

Keywords: cyanide effluent, bioremediation, Clostridium bifermentans, Klebsiella spp, environment

Procedia PDF Downloads 172

Authors: Poojan Vora, Hardik Pancholi, Sanket Tajane, Harsh Shah, Elias Keedy

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The global COVID-19 pandemic has affected the industry drastically in many ways. Even though the vaccine is being distributed quickly and despite the decreasing number of positive cases, testing is projected to remain a key aspect of the ‘new normal’. Improving existing plant layout and improving safety within the facility are of great importance in today’s industries because of the need to ensure productivity optimization and reduce safety risks. In practice, it is essential for any manufacturing plant to reduce nonvalue adding steps such as the movement of materials and rearrange similar processes. In the current pandemic situation, optimized layouts will not only increase safety measures but also decrease the fixed cost per unit manufactured. In our case study, we carefully studied the existing layout and the manufacturing steps of a new Texas start-up company that manufactures COVID testing kits. The effects of production rate are incorporated with the computerized relative allocation of facilities technique (CRAFT) algorithm to improve the plant layout and estimate the optimization parameters. Our work reduces the company’s material handling time and increases their daily production. Real data from the company are used in the case study to highlight the importance of colleges in fostering small business needs and improving the collaboration between college researchers and industries by using existing models to advance best practices.

Keywords: computerized relative allocation of facilities technique, facilities planning, optimization, start-up business

Procedia PDF Downloads 135

Authors: Ilkay Turk Cakir, Murat Altinli, Zekeriya Uysal, Abdulkadir Senol, Olcay Bolukbasi Yalcinkaya, Ali Yilmaz

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The Higgs boson was discovered by the ATLAS and CMS experimental groups in 2012 at the Large Hadron Collider (LHC). Production and decay properties of the Higgs boson, Standard Model (SM) couplings, and limits on effective scale of the Higgs boson’s couplings with other bosons are investigated at particle colliders. Deviations from SM estimates are parametrized by effective Lagrangian terms to investigate Higgs couplings. This is a model-independent method for describing the new physics. In this study, sensitivity to neutral gauge boson anomalous couplings with the Higgs boson is investigated using the parameters of the Large Hadron electron Collider (LHeC) and the Future Circular electron-hadron Collider (FCC-eh) with a model-independent approach. By using MadGraph5_aMC@NLO multi-purpose event generator with the parameters of LHeC and FCC-eh, the bounds on the anomalous Hγγ, HγZ and HZZ couplings in e− p → e− q H process are obtained. Detector simulations are also taken into account in the calculations.

Keywords: anomalos couplings, FCC-eh, Higgs, Z boson

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Authors: Harris Niavis, Dimitra Politaki

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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 182

Authors: Gichun Cha, Changgil Lee, Seunghee Park

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The objective of the study is to construct the shape management method contributing to the safety of the large structure. In Korea, the research of the shape management is lack because of the new attempted technology. Terrestrial Laser Scanning (TLS) is used for measurements of large structures. TLS provides an efficient way to actively acquire accurate the point clouds of object surfaces or environments. The point clouds provide a basis for rapid modeling in the industrial automation, architecture, construction or maintenance of the civil infrastructures. TLS produce a huge amount of point clouds. Registration, Extraction and Visualization of data require the processing of a massive amount of scan data. The octree can be applied to the shape management of the large structure because the scan data is reduced in the size but, the data attributes are maintained. The octree space partitioning generates the voxel of 3D space, and the voxel is recursively subdivided into eight sub-voxels. The point cloud of scan data was converted to voxel and sampled. The experimental site is located at Sungkyunkwan University. The scanned structure is the steel-frame bridge. The used TLS is Leica ScanStation C10/C5. The scan data was condensed 92%, and the octree model was constructed with 2 millimeter in resolution. This study presents octree space partitioning for handling the point clouds. The basis is created by shape management of the large structures such as double-deck tunnel, building and bridge. The research will be expected to improve the efficiency of structural health monitoring and maintenance. "This work is financially supported by 'U-City Master and Doctor Course Grant Program' and the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIP) (NRF- 2015R1D1A1A01059291)."

Keywords: 3D scan data, octree space partitioning, shape management, structural health monitoring, terrestrial laser scanning

Procedia PDF Downloads 295

Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

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Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

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Authors: Dinesh Kumar Sharma, Sanjay Sharma

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Textile manufacturing industry uses a substantial amount of chemicals not only in the production processes but also in manufacturing the raw materials. Dyes are the most significant raw material which provides colour to the fabric and yarn. Dyes are produced by using a large amount of chemicals both organic and inorganic in nature. Dyes are further classified as Reactive or Vat Dyes which are mostly used in cotton textiles. In the process of application of dyes to the cotton fiber, yarn or fabric, several auxiliary chemicals are also used in the solution called dyebath to improve the absorption of dyes. There is a very little absorption of dyes and auxiliary chemicals and a residual amount of all these substances is released as the spent dye bath effluent. Because of the wide variety of chemicals used in cotton textile dyes, there is always a risk of harmful effects which may not be apparent immediately but may have an irreversible impact in the long term. Colour imparted by the dyes to the water also has an adverse effect on its public acceptability and the potability. This study has been conducted with an objective to assess the feasibility of reuse of the spent dye bath. Studies have been conducted in two independent industries manufacturing dyed cotton yarn and dyed cotton fabric respectively. These have been referred as Unit-I and Unit-II. The studies included assessment of reduction in pollution levels and the economic benefits of such reuse. The study conclusively establishes that the reuse of spent dyebath results in prevention of pollution, reduction in pollution loads and cost of effluent treatment & production. This pollution prevention technique presents a good preposition for pollution prevention in cotton textile industry.

Keywords: dyes, dyebath, reuse, toxic, pollution, costs

Procedia PDF Downloads 388

Authors: Asma Shaheen, Javed Iqbal

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The water resources are depleting due to an intrusion of industrial pollution. There are clusters of industries including leather tanning, textiles, batteries, and chemical causing contamination. These industries use bulk quantity of water and discharge it with toxic effluents. The penetration of heavy metals through irrigation from industrial effluent has toxic effect on soil and groundwater. There was strong positive significant correlation between all the heavy metals in three media of industrial effluent, soil and groundwater (P < 0.001). The metal to the metal association was supported by dendrograms using cluster analysis. The geospatial variability was assessed by using geographically weighted regression (GWR) and pollution model to identify the simulation of carcinogenic elements in soil and groundwater. The principal component analysis identified the metals source, 48.8% variation in factor 1 have significant loading for sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), chromium (Cr), nickel (Ni), lead (Pb) and zinc (Zn) of tannery effluent-based process. In soil and groundwater, the metals have significant loading in factor 1 representing more than half of the total variation with 51.3 % and 53.6 % respectively which showed that pollutants in soil and water were driven by industrial effluent. The cumulative eigen values for the three media were also found to be greater than 1 representing significant clustering of related heavy metals. The results showed that heavy metals from industrial processes are seeping up toxic trace metals in the soil and groundwater. The poisonous pollutants from heavy metals turned the fresh resources of groundwater into unusable water. The availability of fresh water for irrigation and domestic use is being alarming.

Keywords: groundwater, geostatistical, heavy metals, industrial effluent

Procedia PDF Downloads 226

Authors: Megat Zuhairy, Megat Tajuddin, Hadijah Iberahim, Noraini Ismail

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This paper aims to discuss the impact of external networking on innovation and organizational performance in the construction industry. In Malaysia, the construction industry is known to be one of the industries that contribute significantly towards her economic growth. The construction industry is described as a fragmented and complex product system as construction projects implementation requires involvement of varying combination of large and small organizations across the supply chain spectrum. The innovation and performance of Malaysian construction industry are reported to be at underachieving and efforts for its improvement have inspired this study initiative. External networking among industry players is capable in bringing them to work together as a team, reducing the adversarial relationships among them for innovation effort and greater performance. The instrument in measuring innovation and organizational performance specific to the construction industry was developed by adapting measures introduced by several scholars in these fields. Contractors and consulting companies were the sampling frames of this study representing the construction industry in Malaysia. The population lists were developed from the lists provided by CIDB, BEM, BOA and BQSM. The samples were selected based on a stratified sampling method to gauge representation of the different groups in the population. Regression analysis was performed in this quantitative study to assess relationships amongst variables. The results revealed that principally, external networking is significant in influencing both innovation and organizational performance. Nevertheless, external networking with different industry players has a different impact on innovation and organizational performance. The study revealed that external networking with project players is significant on project performance but not on innovation. On the other hand, external networking with government agencies, academic institutions and professional bodies is significant in influencing innovation but not on organizational performance.

Keywords: innovation, external networking, organizational performance, construction industry

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Authors: Kayondoamunmose Kamafrika

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Experimental based Engineering education approach plays a vital role in the development of student’s deep understanding of both social and physical sciences. Experimental based education approach through laboratory class activities prepare students to meet national demand for high-tech skilled individuals in the government and private sector. However, students across the country are faced with difficulties in classes that involve laboratory activities: poor experimental based exposure in their early development of student’s education-life-cycle, lack of student engagement in scientific method practical thinking approach, lack of communication between students and the instructor during class, a large number of students in one classroom, lack of instruments and improper equipment calibration. The purpose of this paper is to help students develop their own scientific knowledge and understanding, develop their methodologies in the design of experiments, collect and analyze data, write laboratory reports, present and explain their findings. Experimental based laboratory activities allow students to learn with high-level understanding as well as engage in the design processes of constructing knowledge through practical means of doing science. Experimental based education systems approach will act as a catalyst in the development of practical-based-educational methodologies in social and physical science and engineering domain of learning; thereby, converting laboratory classes into pilot industries and students into professional experts in finding a solution for complex problems, research, and development of super high- tech systems.

Keywords: experimental, engineering, innovation, practicability

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Authors: Yanxue Shang, Jingbin Zeng

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Chlorobenzene homologues (CBHs) are a category of environmental pollutants that can not be ignored. They can stay in the environment for a long period and are potentially carcinogenic. The traditional degradation method of CBHs is dechlorination followed by sample preparation and analysis. This is not only time-consuming and laborious, but the detection and analysis processes are used in conjunction with large-scale instruments. Therefore, this can not achieve rapid and low-cost detection. Compared with traditional sensing methods, colorimetric sensing is simpler and more convenient. In recent years, chromaticity sensors based on fluorescence have attracted more and more attention. Compared with sensing methods based on changes in fluorescence intensity, changes in color gradients are easier to recognize by the naked eye. Accordingly, this work proposes to use single drop microextraction (SDME) technology to solve the above problems. After the dechlorination reaction was completed, the organic droplet extracts Cl⁻ and realizes fluorescence colorimetric sensing at the same time. This method was integrated sample processing and visual in-situ detection, simplifying the detection process. As a fluorescence colorimetric sensor material, CsPbBr₃ was encapsulated in MOF-5 to construct CsPbBr₃@MOF-5 fluorescence colorimetric composite. Then the fluorescence colorimetric sensor was constructed by dispersing the composite in SDME organic droplets. When the Br⁻ in CsPbBr₃ exchanges with Cl⁻ produced by the dechlorination reactions, it is converted into CsPbCl₃. The fluorescence color of the single droplet of SDME will change from green to blue emission, thereby realizing visual observation. Therein, SDME can enhance the concentration and enrichment of Cl⁻ and instead of sample pretreatment. The fluorescence color change of CsPbBr₃@MOF-5 can replace the detection process of large-scale instruments to achieve real-time rapid detection. Due to the absorption ability of MOF-5, it can not only improve the stability of CsPbBr₃, but induce the adsorption of Cl⁻. Simultaneously, accelerate the exchange of Br- and Cl⁻ in CsPbBr₃ and the detection process of Cl⁻. The absorption process was verified by density functional theory (DFT) calculations. This method exhibits exceptional linearity for Cl⁻ in the range of 10⁻² - 10⁻⁶ M (10000 μM - 1 μM) with a limit of detection of 10⁻⁷ M. Whereafter, the dechlorination reactions of different kinds of CBHs were also carried out with this method, and all had satisfactory detection ability. Also verified the accuracy by gas chromatography (GC), and it was found that the SDME we developed in this work had high credibility. In summary, the in-situ visualization method of dechlorination reaction detection was a combination of sample processing and fluorescence colorimetric sensing. Thus, the strategy researched herein represents a promising method for the visual detection of dechlorination reactions and can be extended for applications in environments, chemical industries, and foods.

Keywords: chlorobenzene homologues, colorimetric sensor, metal halide perovskite, metal-organic frameworks, single drop microextraction

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Authors: M. Tabatabaee, R. Mohebat, M. Baranian

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Textile industries produce large volumes of colored dye effluents which are toxic and non-biodegradable. Earlier studies have shown that a wide range of organic substrates can be completely photo mineralized in the presence of photocatalysts and oxidant agents. ZnO and TiO2 are important photocatalysts with high catalytic activity that have attracted much research attention. Zinc sulfide is one of the semiconductor nanomaterials that can be used for the production of optical sensitizers, photocatalysts, electroluminescent materials, optical sensors and for solar energy conversion. The synthesis of ZnS nanoparticles has been tried by various methods and sulfide sources. Elementary sulfur powder, H2S or Na2S are used as sulfide sources for synthesis of ZnS nano particles. Recently, solar energy is has been successfully used for photocatalytic degradation of dye pollutant. Studies have shown that the use of metal oxides or sulfides with ZnO or TiO2 can significantly enhance the photocatalytic activity of them. In this research, Nano-sized zinc sulfide was synthesized successfully by a simple method using thioasetamide as sulfide source in the presence of polyethylene glycol (PEG 2000). X-ray diffraction (XRD) spectroscopy scanning electron microscope (SEM) was used to characterize the structure and morphology synthesized powder. The effect of photocatalytic activity of prepared ZnS and ZnS/ZnO, on degradation of direct Black19 under UV and sunlight irradiation was investigated. The effects of various parameters such as amount of photocatalyst, pH, initial dye concentration and irradiation time on decolorization rate were systematically investigated. Results show that more than 80% of 500 mgL-1 of dye decolorized in 60-min reaction time under UV and solar irradiation in the presence of ZnS nanoparticles. Whereas, mixed ZnS/ZnO (50%) can decolorize more than 80% of dye in the same conditions.

Keywords: zinc sulfide, nano articles, photodegradation, solar light

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Authors: Lalita Panchal, Zulfiya Sheikh

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Fluoride is essential for teeth and bones development not only for human beings but also for animals. But excess intake of fluoride causes harmful effects on health. Fluorosis is a worldwide health hazard and India is also one of the endemic countries. Udaipur district of Rajasthan is also prone to fluorosis and superphosphate industries are aggravating fluoride toxicity in this area. Grazing fields for animals in the close vicinity of the industries, fodder and water are fluoride contaminated. Fluoride toxicity in the form of dental fluorosis was observed in domestic animals, inhabiting industrial area near Udaipur, where superphosphate fertilizer plants are functioning and releasing fluoride and fumes and effluents into the surroundings. These fumes and gases directly affect the vegetation of grazing field, thus allowing entry of fluoride into the food chain. A survey was conducted in this area to assess the severity of fluorosis, in 2015-16. It was a house to house survey and animal owners were asked for their fodder and water supply. Anterior teeth of the animal were observed. Domestic animals exhibited mild to severe signs of dental fluorosis. Teeth showed deep brown staining, patches, lines and abrasions. Even immature animals were affected badly. Most of the domestic animals were affected, but goats of this area showed chronic symptoms of fluorosis. Due to abrasion of teeth and paining teeth their chewing or grazing capacity and appetite reduced. Eventually, it reduced the life span of animals and increased the mortality rate.

Keywords: domestic animals, fluoride toxicity, industrial fluorosis, superphosphate fertilizers

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Authors: Alma Khasenovna Zhakina, Arnt Oxana Vasilievna, Vasilets Evgeny Petrovich

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The aim of this project is to develop methods for obtaining new molecularly imprinted polymers from coal waste to study their structure, structural and morphological features and properties. Recently, the development of molecularly imprinted polymers has become one of the hot topics for researchers. Modern research indicates the broad prospects of rapidly developing molecular imprinting technologies for creating a new generation of sorption materials. The attractiveness of this area of research lies in the fact that the use of imprinted polymers is not limited to scientific research; they are already being introduced in the chemical, pharmaceutical and biotechnological industries, primarily at the stages of purification of the final product. For the use of molecularly imprinted polymers in the development of sorption material, their ability to selectively remove pollutants, including trace concentrations, is of fundamental importance, and the exceptional stability of polymeric materials under harsh conditions makes it possible to simplify the process of water purification as a whole. The scientific and technical effect is associated with the development of technologies for the production of new molecularly imprinted polymers, the establishment of optimal conditions for their production and the creation of effective imprinted sorbents on their basis for wastewater treatment from heavy metals. The social effect is due to the fact that the use of coal waste as a feedstock for the production of imprinted sorbents will make it possible in the future to create new industries with additional jobs and obtain competitive multi-purpose products. The economic and multiplier effect is associated with the low cost of the final product due to the involvement of local coal waste in the production, reduction of transport, customs and other costs.

Keywords: imprinted polymers, coal waste, polymerization, template, customized sorbents

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Authors: Nor Azlina Ab.Rahman, Salwana Hassan, Zuraeda Ibrahim, Normah Omar, Jamaliah Said

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Revolution in the business environment has crucial growing changes on most globalized markets. Numerous of organizations are necessitating towards producing more proactive entrepreneurs with a dynamic teams, who can run and steer their business to victory. Revolutionizing on business strategy and entrepreneurial skills, also implementing innovation and practices to enhance its performance is necessary for these organizations to be more cost-efficient and increase their efficiency. The study aims to clarify issues of whether measurement has a positive effect on different aspects of innovation and best practices. The study contributes to the current understanding in three ways; first by presenting the important aspects of organizational innovation and best practices. Second by showing the importance of measurement in promoting different aspects of innovation and best practices. Third is to examine the link between innovation, best practices and sustainability in microfinance. The study has been executed by conducting a qualitative study toward the microfinance industry. A representative of management and employees in each company was selected through an invitation to participate in getting information for data collection purpose in the study. The study contains a comprehensive description of the impacts of measurement on different aspects of innovation and best practices towards sustainability in both microfinance industries and SMEs. Findings from this study shows that performance measurement has positive effects on issues related to innovation and best practices. The measurement for several aspects of innovation and best practices is good potential in microfinance industries. Additionally, measurement on innovation and best practices shows a positively related with each other to enhance organization performance. The study suggests that both academics and practitioners should focus on the development of new methods and practices to describe and scrutinize further understanding for measuring issues which is related to innovation and best practices, in order to better develop innovation and best practices towards sustainability. This effort would not only contribute to firm’s success, but also toward the development of the nation in the developing countries.

Keywords: best practices, innovation, microfinance, sustainability

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Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

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In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

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Authors: Fatima Faiza Ahmed, Syed Farrukh Hussain

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The last few decades have seen a large proportion of our population bending towards e-learning technologies, starting from learning tools used in primary and elementary schools to competency based e-learning systems specifically designed for applications like finance and marketing. The huge diversity in this crowd brings about a large number of challenges for the designers of these e-learning systems, one of which is the adaptability of such systems. This paper focuses on adaptability in the learning material in an e-learning course and how artificial intelligence and the semantic web can be used as an effective tool for this purpose. The study proved that the semantic web, still a hot topic in the area of computer science can prove to be a powerful tool in designing and implementing adaptable e-learning systems.

Keywords: adaptable e-learning, HTMLParser, information extraction, semantic web

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Authors: Bhumika Gupta, Jeayaram Subramanian, Hardik Vachhrajani, Avinash Shivdas

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Indian food processing industry is one of the largest in the world in terms of production, consumption, exports and growth opportunities. SMEs play a crucial role within this. Large manufacturing firms largely dominate innovation studies in India. Innovation sources used by SMEs are often different from that of large firms. This paper focuses on exploring various sources of innovation adopted by food processing SMEs in Kerala, South India. Outcome suggests that SMEs use various sources like suppliers, competitors, employees, government/research institutions and customers to get new ideas.

Keywords: food processing, innovation, SMEs, sources of innovation

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Authors: Teo Yen Nee, Tham Siew Yean, Andrew Kam Jia Yi

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There are growing concerns about the effect of increasing outward foreign direct investment (OFDI) from Malaysia. These concerns emerged when OFDI surpassed inward FDI for the first time in 2007 and in the subsequent years as well. From a theoretical point of view, the effect of OFDI on exports remains inconclusive depending on the types and/or motivations of investment. Therefore, the objective of this paper is to investigate the effect of Malaysia’s OFDI on manufacturing exports, using a reduced form exports model. The manufacturing data used in this study covered 24 manufacturing industries for the period 2003-2010. The manufacturing sector is the fourth largest sector invested by Malaysia’s OFDI abroad. However, this sector is chosen for this study because total manufacturing trade contributed significantly to Malaysia’s economy growth as reflected by its significant share in the country’s gross domestic product (138.7%) in 2013. Furthermore, Malaysia’s exports are dominated by manufacturing goods. Consequently, the drastic increase in OFDI added concerns about its impact on the country’s exports. Since OFDI activities are still relatively new in Malaysia, this study is exploratory in nature due to a lack of firm level data. Using industry level panel data, the value added of this paper is to meet the research gap by examining the effect of Malaysia’s outward FDI on manufacturing exports. Overall, the findings show that lagged inward FDI, technology development, and industry size are found to positive and significantly influence manufacturing exports as compared to other factors. The insignificant impact of OFDI on manufacturing exports suggests market seeking investment is the main form of OFDI from Malaysia and the destination markets are not served by exports before so that there are no new exports created or displacement of exports. While the results show that there is no need to worry about OFDI’s negative impact on exports, policies should be undertaken to encourage OFDI from Malaysia to create new exports for the country.

Keywords: OFDI, manufacturing industries, exports, Malaysia

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Authors: Mohammed Fathima Shahanaaz, Shaik Fayazuddin, M. Uday Kiran

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Groundwater quality is deteriorating day by day in different parts of the world due to various reasons, toxic chemicals are being discharged without proper treatment into inland water bodies and land which in turn add pollutants to the groundwater. In this kind of situation, the rural communities which do not have municipal drinking water have to rely on groundwater though it is polluted for various uses. Tannery industry is one of the major industry which provides economy and employment to India. Since most of the developed countries stopped using chemicals which are toxic, the tanning industry which uses chromium as its major element are being shifted towards developing countries. Most of the tanning industries in India can be found in clusters concentrated mainly in states of Tamilnadu, West Bengal, Uttar Pradesh and limited places of Punjab. Limited work is present in the case of tanneries of Warangal. There exists 18 group of tanneries in Desaipet, Enamamula region of Warangal, out of which 4 are involved in dry process and are low responsible for groundwater pollution. These units of tanneries are discharging their effluents after treatment into Sai Cheruvu. Though the treatment effluents are being discharged, the Sai Cheruvu is turned in to Pink colour, with higher levels of BOD, COD, chromium, chlorides, total hardness, TDS and sulphates. An attempt was made to analyse the groundwater samples around this polluted Sai Cheruvu region since literature shows that a single tannery can pollute groundwater to a radius of 7-8 kms from the point of disposal. Sample are collected from 6 different locations around Sai Cheruvu. Analysis was performed for determining various constituents in groundwater such as pH, EC, TDS, TH, Ca+2, Mg+2, HCO3-, Na+, K+, Cl-, SO42-, NO3-, F and Cr+6. The analysis of these constitutes gave values greater than permissible limits. Even chromium is also present in groundwater samples which is exceeding permissible limits People in Paidepally and Sardharpeta villages already stopped the usage of groundwater. They are buying bottle water for drinking purpose. Though they are not using groundwater for drinking purpose complaints are made about using this water for washing also. So treatment process should be adopted for groundwater which should be simple and efficient. In this study rice husk silica (RHS) is used to treat pollutants in groundwater with varying dosages of RHS and contact time. Rice husk is treated, dried and place in a muffle furnace for 6 hours at 650°C. Reduction is observed in total hardness, chlorides and chromium levels are observed after the application RHS. Pollutants reached permissible limits for 27.5mg/l and 50 mg/l of dosage for a contact time of 130 min at constant pH and temperature.

Keywords: chromium, groundwater, rice husk silica, tanning industries

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Authors: Ramesh Kumar Behera, Md. Izhar Hassan

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Accident investigation and analysis are useful to identify deficiencies in plant, process, and management practices and formulate preventive strategies for injury elimination. In India and other parts of the world, industrial accidents are investigated to know the causes and also to fulfill legal compliances. However, findings of investigation are seldom used appropriately to strengthen Occupational Safety and Health (OSH) in expected lines. The mineral rich state of Odisha in eastern coast of India; known as a hub for Iron and Steel industries, witnessed frequent accidents during 2005-2009. This article based on study of 982 fatal ‘factory-accidents’ occurred in Odisha during the period 2001-2016, discusses the ‘turnaround-story’ resulting in reduction of fatal accident from 122 in 2009 to 45 in 2016. This paper examines various factors causing incidents; accident pattern in steel and chemical sector; role of climate and harsh weather conditions on accident causation. Software such as R, SQL, MS-Excel and Tableau were used for analysis of data. It is found that maximum fatality is caused due to ‘fall from height’ (24%); steel industries are relatively more accident prone; harsh weather conditions of summer increase chances of accident by 20%. Further, the study suggests that enforcement of partial work-restriction around lunch time during peak summer, screening and training of employees reduce accidents due to fall from height. The study indicates that learning from accident investigation and analysis can be used as a method to reduce work related accidents in the journey towards ‘Vision Zero’.

Keywords: accident investigation and analysis, fatal accidents in India, fall from height, vision zero

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Authors: Zainab Bibi, Afsheen Aman, Shah Ali Ul Qader

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Endo-β-1,4-xylanases [EC 3.2.1.8] are one of the major groups of enzymes that are involved in degradation process of xylan and have several applications in food, textile and paper processing industries. Due to broad utility of endo-β-1,4-xylanase, researchers are focusing to increase the productivity of this hydrolase from various microbial species. Harsh industrial condition, faster reaction rate and efficient hydrolysis of xylan with low risk of contamination are critical requirements of industry that can be fulfilled by synthesizing the enzyme with efficient properties. In the current study, a newly isolated thermophile Geobacillus stearothermophilus KIBGE-IB29 was used in order to attain the maximum production of endo-1,4-β-xylanase. Bacterial culture was isolated from soil, collected around the blast furnace site of a steel processing mill, Karachi. Optimization of various nutritional and physical factors resulted the maximum synthesis of endo-1,4-β-xylanase from a thermophile. High production yield was achieved at 60°C and pH-6.0 after 24 hours of incubation period. Various nitrogen sources viz. peptone, yeast extract and meat extract improved the enzyme synthesis with 0.5%, 0.2% and 0.1% optimum concentrations. Dipotassium hydrogen phosphate (0.25%), potassium dihydrogen phosphate (0.05%), ammonium sulfate (0.05%) and calcium chloride (0.01%) were noticed as valuable salts to improve the production of enzyme. The thermophilic nature of isolate, with its broad pH stability profile and reduced fermentation time indicates its importance for effective xylan saccharification and for large scale production of endo-1,4-β-xylanase.

Keywords: geobacillus, optimization, production, xylanase

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Authors: Sipho Mbatha, Anne Mastament-Mason

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The Multi-Fibre Arrangement (MFA) which regulated all trade in the Apparel Manufacturing Industries (AMI) for four decades was dissolved in 2005. Since 2005, the Apparel Manufacturing Industry of South Africa (AMISA) has been battling to adjust to an environment of liberalised trade, mainly due to strategic, infrastructural and skills factors. In developing competitive advantage strategy for the AMISA, the study aimed to do the following (1) to apply Porter’s diamond model’s determinant “Factor Condition” as framework to develop competitive advantage strategies. (2) Examine the effectiveness of government policy Industrial Policy Action Plan (IPAP 2007) in supporting AMISA. (3) Examine chance events that could be used as bases for competitive advantage strategies for the AMISA. This study found that the lack of advanced skills and poor infrastructure are affecting the competitive advantage of AMISA. The then Clothing, Textiles, Leather and Footwear Sector Education and Training Authority (CTLF-SETA) has also fallen short of addressing the skills gap within the apparel manufacturing industries. The only time that AMISA have shown signs of competitive advantage was when they made use of government grants and incentives available to only compliant AMISA. The findings have shown that the apparel retail groups have shown support for the AMISA by shouldering raw material costs, making it easier to manufacture the required apparel at acceptable lead times. AMISA can compete in low end apparel, provided quick response is intensified, the development of local textiles and raw materials is expedited.

Keywords: compliance rule, apparel manufacturing idustry, factor conditions, advance skills, industrial policy action plan of South Africa

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Bib Paruhum Silalahi, Djihad Wungguli, Sugi Guritman

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Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions.

Keywords: steepest descent, line search, iteration, running time, unconstrained optimization, convergence

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Authors: P. Larpsomboonchai

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Agro-industry is one of major industries that has strong impacts on national economic incomes, growth, stability, and sustainable development. Moreover, this industry also has strong influences on social, cultural and political issues. Furthermore, this industry, as producing primary and secondary products, is facing challenges from such diverse factors such as demand inconsistency, intense international competition, technological advancements and new competitors. In order to maintain and to improve industry’s competitiveness in both domestics and international markets, science and technology are key factors. Besides hard sciences and technologies, modern industrial engineering concepts such as Just in Time (JIT) Total Quality Management (TQM), Quick Response (QR), Supply Chain Management (SCM) and Lean can be very effective to supportant to increase efficiency and effectiveness of these agricultural products on world stage. Onion is one of Thailand’s major export products which brings back national incomes. But, it also facing challenges in many ways. This paper focused its interests in onion packing process and its related activities such as storage and shipment from one of major packing plant and storage in Mae Wang District, Chiang Mai, Thailand, by applying Toyota Production System (TPS) or Lean concepts, to improve process capability throughout the entire packing and distribution process which will be profitable for the whole onion supply chain. And it will be beneficial to other related agricultural products in Thailand and other ASEAN countries.

Keywords: packing process, Toyota Production System (TPS), lean concepts, waste reduction, lean in agro-industries activities

Procedia PDF Downloads 271