Search results for: interactive selection process

Authors: Sohail Ahmed, Ke Xing

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This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). This research proposed an analytical framework for ETICS, its concepts, and theory by integrating CAS methodology into the management of the technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution, and realization of the technological innovation capabilities in complex dynamic environments. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS, and summarizes the sources of technological innovation, the elements of each subject, and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions, and government agencies with the leading enterprises in industrial settings. The study was exploratory and based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of the enterprise's technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on the enterprise’s research and development personnel, investments in technological processes, and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.

Keywords: complex adaptive system, echo model, enterprise technological innovation capability system, research institutions, multi-agents

Procedia PDF Downloads 139

Authors: Bahadir Aydin

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Today it is difficult to reach accurate knowledge because of mass data. This huge data makes the environment more and more caotic. Data is a main piller of intelligence. There is a close tie between knowledge and intelligence. Information gathered from different sources can be modified, interpreted and classified by using knowledge development process. This process is applied in order to attain intelligence. Within this process the effect of knowledge is crucial. Knowledge is classified as explicit and tacit knowledge. Tacit knowledge can be seen as "only the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose for all organization is to be succesful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. By the help of process the decision-maker can be presented with a clear holistic understanding, as early as possible in the decision making process. Planning, execution and assessments are the key functions that connects to information to knowledge. Altering from the current traditional reactive approach to a proactive knowledge development approach would reduce extensive duplication of work in the organization. By new approach to this process, knowledge can be used more effectively.

Keywords: knowledge, intelligence cycle, tacit knowledge, KIDW

Procedia PDF Downloads 520

Authors: Udaya Kumar

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The aim of this paper is to discuss recent research conducted in experimental studies related to the process of the iron smelting. The paper will discuss issues related to the selection of iron ore, structure of furnace, making of tuyeres, fashioning of blowers and firing temperatures through experiments conducted recently and scientific analyses of experimental work. Experiments were conducted in order to investigate iron smelting techniques used at the Early Historic site of Nathara-Ki-Pal. (73°47’E; 24°16N is located about 70 km south-east of Udaipur city). Geographically, Nathara-Ki-Pal has located the foot hills of Aravalli’s. Iron ore and iron slag can be seen on the surface of the site. The remains of 4 broken furnaces were recovered during excavations (2007 and 2008) and the site was excavated by Prof. Pandey from the Department of Archaeology of the Institute of Rajasthan studies, Rajasthan Vidyapeeth University. This shows that the site of Nathara-Ki-Pal was a center of iron smelting. Results of experiments performed both in the field reconstruction of a bloomery furnace and in the laboratory are discussed.

Keywords: experimental studies, furnace, smelting techniques, making of tuyeres

Procedia PDF Downloads 189

Authors: M. T. Alodat

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In this paper, we propose a generalization to the Gaussian process regression(GPR) model called the extended skew Gaussian process for regression(ESGPr) model. The ESGPR model works better than the GPR model when the errors are skewed. We derive the predictive distribution for the ESGPR model at a new input. Also we apply the ESGPR model to FOREX data and we find that it fits the Forex data better than the GPR model.

Keywords: extended skew normal distribution, Gaussian process for regression, predictive distribution, ESGPr model

Procedia PDF Downloads 554

Authors: Zhanara Suleimenova, Raushan Blieva, Aigerim Zhakipbekova, Inkar Tapenbayeva, Zhanar Narmuratova

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Green processes are based on innovative technologies that do not negatively affect the environment. Industrial enzymes originated from biological systems can effectively contribute to sustainable development through being isolated from microorganisms which are fermented using primarily renewable resources. Many widespread microorganisms secrete a significant amount of biocatalysts into the environment, which greatly facilitates the task of their isolation and purification. The ability to control the enzyme production through the regulation of their biosynthesis and the selection of nutrient media and cultivation conditions allows not only to increase the yield of enzymes but also to obtain enzymes with certain properties. In this regard, large potentialities are embedded in immobilized cells. Enzyme production technology in a secreted active form enabling industrial application on an economically feasible scale has been developed. This method is based on the immobilization of enzyme producers on a solid career. Immobilizing has a range of advantages: decreasing the price of the final product, absence of foreign substances, controlled process of enzyme-genesis, the ability of various enzymes' simultaneous production, etc. Design of proposed equipment gives the opportunity to increase the activity of immobilized cell culture filtrate comparing to free cells, growing in periodic culture conditions. Such technology allows giving a 10-times raise in culture productivity, to prolong the process of fungi cultivation and periods of active culture liquid generation. Also, it gives the way to improve the quality of filtrates (to make them more clear) and exclude time-consuming processes of recharging fermentative vials, that require manual removing of mycelium.

Keywords: industrial enzymes, immobilization, submerged fermentation, microscopic fungi

Procedia PDF Downloads 141

Authors: A. Hamidi, S. Khelladi, L. Illoul, A. Tcharkhtchi

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Reactive rotational molding (RRM) is a process to manufacture hollow plastic parts with reactive material has several advantages compared to conventional roto molding of thermoplastic powders: process cycle time is shorter; raw material is less expensive because polymerization occurs during processing and high-performance polymers may be used such as thermosets, thermoplastics or blends. However, several phenomena occur during this process which makes the optimization of the process quite complex. In this study, we have used a mixture of isocyanate and polyol as a reactive system. The chemical transformation of this system to polyurethane has been studied by thermal analysis and rheology tests. Thanks to these results of the curing process and rheological measurements, the kinetic and rheokinetik of polyurethane was identified. Smoothed Particle Hydrodynamics, a Lagrangian meshless method, was chosen to simulate reactive fluid flow in 2 and 3D configurations of the polyurethane during the process taking into account the chemical, and chemiorehological results obtained experimentally in this study.

Keywords: reactive rotational molding, simulation, smoothed particle hydrodynamics, surface tension, rheology, free surface flows, viscoelastic, interpolation

Procedia PDF Downloads 290

Authors: Ivonne Tshuma, Ralf Cord-Ruwisch, Wendell Ela

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Water crisis is a world-wide problem because of population growth and climate change. Hence, desalination is a solution to water scarcity, which threatens the world. Reverse osmosis (RO) is the most used technique for desalination; unfortunately, this process, usually requires high-pressure requirement hence requires a lot of energy about 3 – 5.5 KWhr/m³ of electrical energy. The pressure requirements of RO can be alleviated by the use of PRO (pressure retarded osmosis) to drive the RO process. This paper proposes a process of utilizing the energy directly from PRO to drive an RO process. The paper mostly analyses the PRO process parameters such as cross-flow velocity, density, and buoyancy and how these have an effect on PRO hence ultimately the RO process. The experimental study of the PRO with various feed solution concentrations and cross-flow velocities at fixed applied pressure with different orientations of the PRO cell was performed. The study revealed that without cross-flow velocity, buoyancy effects were observed but not with cross-flow velocity.

Keywords: cross-flow velocity, pressure retarded osmosis, density, buoyancy

Procedia PDF Downloads 138

Authors: Ian D. Walker

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This paper describes the creation and teaching of an undergraduate course aimed at promoting critical thinking among the students in the course. The class, Robots in Business and Society, taught at Clemson University, is open to all undergraduate students of any discipline. It is taught as part of Clemson’s online class program and is structured to promote critical thinking via a series of interactive discussion boards and assignments. Critical thinking is measured via pre- and post-testing using a benchmark standardized test. The paper will detail the class organization, and describe and discuss the results and lessons learned with respect to improvement of student critical thinking from three offerings of the class.

Keywords: critical thinking, pedagogy, robotics, undergraduate teaching

Procedia PDF Downloads 288

Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

Procedia PDF Downloads 265

Authors: Ahmed Mahmoud Ahmed Abouelmagd

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The diversity is the usual remedy of the transmitted signal level variations (Fading phenomena) in radio frequency channels. Diversity techniques utilize two or more copies of a signal and combine those signals to combat fading. The basic concept of diversity is to transmit the signal via several independent diversity branches to get independent signal replicas via time – frequency - space - and polarization diversity domains. Coding and decoding processes can be an alternative remedy for fading phenomena, it cannot increase the channel capacity, but it can improve the error performance. In this paper we propose the use of replication decoding with BCH code class, and Viterbi decoding algorithm with convolution coding; as examples of coding and decoding processes. The results are compared to those obtained from two optimized selection space diversity techniques. The performance of Rayleigh fading channel, as the model considered for radio frequency channels, is evaluated for each case. The evaluation results show that the coding and decoding approaches, especially the BCH coding approach with replication decoding scheme, give better performance compared to that of selection space diversity optimization approaches. Also, an approach for combining the coding and decoding diversity as well as the space diversity is considered, the main disadvantage of this approach is its complexity but it yields good performance results.

Keywords: Rayleigh fading, diversity, BCH codes, Replication decoding, ‎convolution coding, viterbi decoding, space diversity

Procedia PDF Downloads 443

Authors: Nasiru Medugu Idris

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This research is aimed at assessing the vulnerability of climate change to rural communities (farmers, herdsmen and fishermen) in Nigeria with the view to study the underlying causes and degree of vulnerability to climate change and examine the conflict between farmers and herdsmen as a result of climate change. This research employed the use of quantitative and qualitative means of data gathering techniques as well as physical observations. Six states (Kebbi, Adamawa, Nasarawa, Osun, Ebonyi, and Akwa Ibom) have been selected on the ground that they are key food production areas in the country and are therefore essential to continual food security in the country. So also, they also double as fishing communities in order to aid the comprehensive study of all the effects on climate on farmers and fishermen alike. Community focus group discussions were carried out in the various states for an interactive session and also to have firsthand information on their level of awareness on climate change. Climate data from the Nigerian Meteorological Agency over the past decade were collected for the purpose of analyzing trends in climate. The study observed that the level of vulnerability of rural dwellers most especially farmers, herdsmen and fishermen to climate change is very high due to their socioeconomic, ethnic and historical perspective of their trend. The study, therefore, recommends that urgent step needs to be put in place to help control natural hazards and man-made disasters and serious measures are also needed in order to minimize severe societal, economic and political crises; some of which may either escalate to violent conflicts or could be avoided by efforts of conflict resolution and prevention by the initiation of a process of de-escalation. So this study has recommended the best-fit adaptive and mitigation measures to climate change vulnerability in rural communities of Nigeria.

Keywords: adaptation, farmers, fishermen, herdsmen

Procedia PDF Downloads 193

Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

Procedia PDF Downloads 513

Authors: B. Vikram, Y. Anu Leena, Y. Anu Neena, M. V. Krishna Rao, V. S. S. Kumar

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The industry is often criticized for inefficiencies in outcomes such as time and cost overruns, low productivity, poor quality and inadequate customer satisfaction. To enhance the chances for construction projects to be successful, selecting an able contractor is one of the fundamental decisions to be made by clients. The selection of the most appropriate contractor is a multi-criteria decision making (MCDM) process. In this paper, multi-attribute utility theory (MAUT) is employed utilizing the multiplicative form of utility function for ranking the prequalified contractors. Performance assessment criteria covering contracting company attributes, experience record, past performance, performance potential, financial stability and project specific criteria are considered for contractor evaluation. A case study of multistoried building for which four contractors submitted bids is considered to illustrate the applicability of multiplicative approach of MAUT to rank the prequalified contractors. The proposed MAUT decision making methodology can also be employed to other decision making situations.

Keywords: multi-attribute utility theory, construction industry, prequalification, contractor

Procedia PDF Downloads 439

Authors: Kun Li, Yuzheng Liu, Xiuqi Fan

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High-security standard and high efficiency of screening seem to be contradictory to each other in the airport security check process. Improving the efficiency as far as possible while maintaining the same security standard is significantly meaningful. This paper utilizes the knowledge of Operation Research and Stochastic Process to establish mathematical models to explore this problem. We analyze the current process of airport security check and use the M/G/1 and M/G/k models in queuing theory to describe the process. Then we find the least efficient part is the pre-check lane, the bottleneck of the queuing system. To improve passenger throughput and reduce the variance of passengers’ waiting time, we adjust our models and use Monte Carlo method, then put forward three modifications: adjust the ratio of Pre-Check lane to regular lane flexibly, determine the optimal number of security check screening lines based on cost analysis and adjust the distribution of arrival and service time based on Monte Carlo simulation results. We also analyze the impact of cultural differences as the sensitivity analysis. Finally, we give the recommendations for the current process of airport security check process.

Keywords: queue theory, security check, stochatic process, Monte Carlo simulation

Procedia PDF Downloads 200

Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

Procedia PDF Downloads 92

Authors: Noshaba Dilbar, Maria Jabbar

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Medicinal plants are considered to be the richest source of drug discovery. The main cause of medicinal properties of plants is the presence of bioactive compounds in them. Phytochemical screening is the valuable process that detects bioactive compounds(secondary metabolites) in plants. The present study was carried out to determine phytochemical profile and ethnobotanical importance of Capparidaceae species. ( Capparis spinosa and Dipterygium glaucum). The selection of plants was made on basis of traditional knowledge of their usage in ayurvedic medicines. Different type of solvents(ethanol, methanol, chloroform, benzene and petroleum ether) were used to make extracts of dry and fresh plants. Phytochemical screening was made by using various standard techniques. Results reveal the presence of large range of bioactive compounds i.e alakloids, saponins, flavonoids, terpenoids, glycosides, phenols and steroids. Methanol, petroleum ether and chloroform extracts showed high extractability of bioactive compounds. The results obtained ensure these plants a reliable source of pharmacological industry and can be used in making of various biological friendly drugs.

Keywords: bioactive compounds, Capparidaceae, phytochemical screening, secondary metabolites

Procedia PDF Downloads 176

Authors: Amit Bhattacharyya

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The economic scenario of any region does not show the real picture for the measurement of overall development. Therefore, economic development must be accompanied by social development to be able to make an assessment to measure the level of development. The spatial variation with respect to social development has been discussed taking into account the quality of functioning of a social system in a specific area. In this paper, an attempt has been made to study the spatial distribution of social infrastructural facilities and analyze the magnitude of regional disparities at inter- block level in Barddhman district. It starts with the detailed account of the selection process of social infrastructure indicators and describes the methodology employed in the empirical analysis. Analyzing the block level data, this paper tries to identify the disparity among the blocks in the levels of social development. The results have been subsequently explained using both statistical analysis and geo spatial technique. The paper reveals that the social development is not going on at the same rate in every part of the district. Health facilities and educational facilities are concentrated at some selected point. So overall development activities come to be concentrated in a few centres and the disparity is seen over the blocks.

Keywords: disparity, inter-block, social development, spatial variation

Procedia PDF Downloads 169

Authors: Radhey Sham Rajoria

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Pressure to increase the competitiveness in the manufacturing sector and for the survival in the market has led to the development of machining centres, which enhance productivity, improve quality, shorten the lead time, and reduce the manufacturing cost. With the innovation of machining centres in the manufacturing sector the production lines have been replaced by these machining centers, having the ability to machine various processes and multiple tooling with automatic tool changer (ATC) for the same part. Also the process plans can be easily generated for complex components. Some means are required to utilize the machining center at its best. The present work is concentrated on the automated part program generation, and in turn automated process plan generation for the turned components on Denford “MIRAC” 8 stations ATC lathe machining centre. A package in C++ on DOS platform is developed which generates the complete CNC part program, process plan and process sequence for the turned components. The input to this system is in the form of a blueprint in graphical format with machining parameters and variables, and the output is the CNC part program which is stored in a .mir file, ready for execution on the machining centre.

Keywords: CNC, MIRAC, ATC, process planning

Procedia PDF Downloads 270

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 147

Authors: Suleiman Obeidat, Nabeel Mandahawi

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In this work, the packaging process for a move is improved. The customers of this move need their household stuff to be moved from their current house to the new one with minimum damage, in an organized manner, on time and with the minimum cost. Our goal was to improve the process between 10% and 20% time efficiency, 90% reduction in damaged parts and an acceptable improvement in the cost of the total move process. The expected ROI was 833%. Many improvement techniques have been used in terms of the way the boxes are prepared, their preparation cost, packing the goods, labeling them and moving them to a place for moving out. DMAIC technique is used in this work: SIPOC diagram, value stream map of “As Is” process, Root Cause Analysis, Maps of “Future State” and “Ideal State” and an Improvement Plan. A value of ROI=624% is obtained which is lower than the expected value of 833%. The work explains the techniques of improvement and the deficiencies in the old process.

Keywords: packaging, lean tools, six sigma, DMAIC methodology, SIPOC

Procedia PDF Downloads 428

Authors: Kiurski S. Jelena, Ranogajec G. Jonjaua, Kecić S. Vesna, Oros B. Ivana

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The present study investigates the effectiveness of newly designed clayey pellets (fired clay pellets diameter sizes of 5 and 8 mm, and unfired clay pellets with the diameter size of 15 mm) as the beds in the column adsorption process. The adsorption experiments in the batch mode were performed before the column experiment with the purpose to determine the order of adsorbent package in the column which was to be designed in the investigation. The column experiment was performed by using a known mass of the clayey beds and the volume of the waste printing developer, which was purified. The column was filled in the following order: fired clay pellets of the diameter size of 5 mm, fired clay pellets of the diameter size of 8 mm, and unfired clay pellets of the diameter size of 15 mm. The selected order of the adsorbents showed a high removal efficiency for zinc (97.8%) and copper (81.5%) ions. These efficiencies were better than those in the case of the already existing mode adsorption. The obtained experimental data present a good basis for the selection of an appropriate column fill, but further testing is necessary in order to obtain more accurate results.

Keywords: clay materials, fix bed adsorption column, metal ions, printing developer

Procedia PDF Downloads 325

Authors: Aurore Lechevallier, Mohend Chaouche, Jerome Soudier, Guillaume Renaudin

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The cement industry accounts for 8% of the global CO₂ emissions, and approximately 60% of these emissions are associated with the Portland cement clinker production from the decarbonization of limestone (CaCO3). Their impact on the greenhouse effect results in growing social awareness. Therefore, CO2 footprint becomes a product selection choice, and substituting Portland cement with a lower CO2-footprint alternative binder is sought. In this context, new hydraulic binders have been studied as a potential Ordinary Portland Cement substitute. Many of them are composed of iron oxides and aluminum oxides, present in the Ca₄Al₂-xFe₂+ₓO₁₀-like phase and forming Ca-LDH (i.e. AFM) as a hydration product. It has become essential to study the possible existence of Fe/Al AFM solid solutions to characterize the hydration process properly. Ca₂Al₂-xFex(OH)₆.X.nH₂O layered AFM samples intercalated with either nitrate or chloride X anions were synthesized based on the co-precipitation method under a nitrogen atmosphere to avoid the carbonation effect.AFM samples intercalated with carbonate anions were synthesized based on the anionic exchange process, using AFM-NO₃ as the source material. These three AFM samples were synthesized with varying Fe/Al molar ratios. The experimental conditions were optimized to make possible the formation of Al-AFM and Fe-AFM using the same parameters (namely pH value and salt concentration). Rietveld refinements were performed to demonstrate the existence of a solid solution between the two trivalent metallic end members. Spectroscopic analyses were used to confirm the intercalation of the targeted anion; secondary electron images were taken to analyze the AFM samples’ morphology, and energy dispersive X-ray spectroscopy (EDX) was carried out to determine the elemental composition of the AFM samples. Results of this study make it possible to quantify the Al/Fe ratio of the AFM phases precipitated in our hydraulic binder, thanks to the determined Vegard's law characteristic to the corresponding solid solutions

Keywords: AFm phase, iron-rich binder, low-carbon cement, solid solution

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Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

Procedia PDF Downloads 136

Authors: S. Mahovic Poljacek, T. Tomasegovic, T. Cigula, D. Donevski, R. Szentgyörgyvölgyi, S. Jakovljevic

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In this paper, a degradation of the photopolymeric material (PhPM), used as printing plate in the flexography reproduction technique, caused by accelerated aging has been observed. Since the basis process for production of printing plates from the PhPM is a radical cross-linking process caused by exposing to UV wavelengths, the assumption was that improper storage or irregular handling of the PhPM plate can change the surface and structure characteristics of the plates. Results have shown that the aging process causes degradation in the structure and changes in the surface of the PhPM printing plate.

Keywords: aging process, artificial treatment, flexography, photopolymeric material (PhPM)

Procedia PDF Downloads 349

Authors: A. Soualem

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The design of multi stage deep drawing processes requires the evaluation of many process parameters such as the intermediate die geometry, the blank shape, the sheet thickness, the blank holder force, friction, lubrication etc..These process parameters have to be determined for the optimum forming conditions before the process design. In general sheet metal forming may involve stretching drawing or various combinations of these basic modes of deformation. It is important to determine the influence of the process variables in the design of sheet metal working process. Especially, the punch and die corner for deep drawing will affect the formability. At the same time the prediction of sheet metals springback after deep drawing is an important issue to solve for the control of manufacturing processes. Nowadays, the importance of this problem increases because of the use of steel sheeting with high stress and also aluminum alloys. The aim of this paper is to give a better understanding of the springback and its effect in various sheet metals forming process such as expansion and restraint deep drawing in the cup drawing process, by varying radius die, lubricant for two commercially available materials e.g. galvanized steel and Aluminum sheet. To achieve these goals experiments were carried out and compared with other results. The original of our purpose consist on tests which are ensured by adapting a U-type stretching-bending device on a tensile testing machine, where we studied and quantified the variation of the springback.

Keywords: springback, deep drawing, expansion, restricted deep drawing

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Authors: C. V. Aravinda, H. N. Prakash

Abstract:

In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

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Authors: Sudha T., Naveen C.

Abstract:

Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Zarema Urustamova, Chunsheng Shi, Ghulam Mujtaba Kayani 

Abstract:

This research paper helps to understand the comparative analysis of recruitment problems which majorly faced by HRD of Public/Semi-Govt. and private sectors of Russia. The natures of different recruitment problems faced by HRD are different in both sector of Russia. Recruitment is one of very critical and important decision taken by HR department and some recruitment problems are highly faced by HR department of public/semi Govt. sector but are not major problems for private sector. Moreover, some problems are majorly influence in private sector but are not major problems in public/semi-govt. sector of Russia in recruitment. It is also identified that some recruitment problems are majorly affect in recruitment in both sectors. This paper helps to understand the recruitment problems faced by HR department while recruiting the new employee in both sectors. This paper also identified that “environment” and “prejudice” in public sector have higher affect and considered as a major problems in employee recruitment and “reference”, “selection standards” are considered as a least affecting problems of recruitment in public sector. Further, in private sector, “prejudice” and “culture” are major issues and “selection standards” and “reference” is considered as least affecting recruitment problems in private sector of Russia. So, HR department will be able to hire right person on right time, and it is possible when different HR departments focus to overcome these recruitment problems more efficiently and effectively.

Keywords: Govt. /Semi-Govt. vs. private sector, HR department, recruitment problems, Russia

Procedia PDF Downloads 381

Authors: Muhammad Izzam Bin Mohd Khazar, Nur Adibah Binti Zainudin

Abstract:

Islamic banking as one of the financial institutions is highly required to maintain a prudent approach to ensure that any financing given is able to generate income to their respective shareholders. As the default payment of customers is probably occurred in the financing, having a prudent approach in the recovery process is a must to ensure that financing losses are within acceptable limits. The objective of this research is to provide the best practice of recovery which is anticipated to benefit both bank and customers. This study will address arising issue on the current practice of recovery process and followed by providing humanising recovery solutions in the light of the Maqasid Shariah. The study identified main issues pertaining to Islamic recovery process which can be categorized into knowledge crisis, process issues, specific treatment cases and system issues. Knowledge crisis is related to direct parties including judges, solicitors and salesperson, while the recovery process issues include the process of issuance of reminder, foreclosure and repossession of asset. Furthermore, special treatment for particular cases also should be observed since different contracts in Islamic banking products will need different treatment. Finally, issues in the system used in the recovery process are still unresolved since the existing technology is still young in this area to embraced Islamic finance requirements and nature of calculation. In order to humanize the financial services in Islamic banking recovery process, we have highlighted four main recommendation to be implemented by Islamic Financial Institutions namely; 1) early deterrent by improving the awareness, 2) improvement of the internal process, 3) reward mechanism, and 4) creative penalty to provide awareness to all stakeholders.

Keywords: humanizing financial services, Islamic Finance, Maqasid Syariah, recovery process

Procedia PDF Downloads 207

Authors: Husam Mohammed Saleh Alziyadi

Abstract:

The drilling fluid has a significant impact on drilling efficiency. Drilling fluids have several functions which make them most important within the drilling process, such as lubricating and cooling the drill bit, removing cuttings from down of hole, preventing formation damage, suspending drill bit cuttings, , and also removing permeable formation as a result, the flow of fluid into the formation process is delayed. In the oil and gas sector, unconventional shale reserves have been a central player in meeting world energy demands. Oil-based drilling fluids (OBM) are generally favored for drilling shale plays due to negligible chemical interactions. Nevertheless, the industry has been inspired by strict environmental regulations to design water-based drilling fluids (WBM) capable of regulating shale-water interactions to boost their efficiency. However, traditional additives are too large to plug the micro-fractures and nanopores of the shale. Recently, nanotechnology in the oil and gas industries has shown a lot of promise, especially with drilling fluids based on nanoparticles. Nanotechnology has already made a huge contribution to technical developments in the energy sector. In the drilling industry, nanotechnology can make revolutionary changes. Nanotechnology creates nanomaterials with many attractive properties that can play an important role in improving the consistency of mud cake, reducing friction, preventing differential pipe sticking, preserving the stability of the borehole, protecting reservoirs, and improving the recovery of oil and gas. The selection of suitable nanomaterials should be based on the shale formation characteristics intended for drilling. The size, concentration, and stability of the NPs are three more important considerations. The effects of the environment are highly sensitive to these materials, such as changes in ionic strength, temperature, or pH, all of which occur under downhole conditions. This review paper focused on the previous research and recent development of environmentally friendly drilling fluids according to the regulatory environment and cost challenges.

Keywords: nanotechnology, WBM, Drilling Fluid, nanofluids

Procedia PDF Downloads 127