Search results for: hybrid process

Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Jeff Moussodji, Dominique Drouin

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The highly complex technology requirements of today’s integrated circuits (ICs), lead to the increased use of several materials types such as metal structures, brittle and porous low-k materials which are used in both front end of line (FEOL) and back end of line (BEOL) process for wafer manufacturing. In order to singulate chip from wafer, a critical laser-grooving process, prior to blade dicing, is used to remove these layers of materials out of the dicing street. The combination of laser-grooving and blade dicing allows to reduce the potential risk of induced mechanical defects such micro-cracks, chipping, on the wafer top surface where circuitry is located. It seems, therefore, essential to have a fundamental understanding of the physics involving laser-dicing in order to maximize control of these critical process and reduce their undesirable effects on process efficiency, quality, and reliability. In this paper, the study was based on the convergence of two approaches, numerical and experimental studies which allowed us to investigate the interaction of a nanosecond pulsed laser and BEOL wafer materials. To evaluate this interaction, several laser grooved samples were compared with finite element modeling, in which three different aspects; phase change, thermo-mechanical and optic sensitive parameters were considered. The mathematical model makes it possible to highlight a groove profile (depth, width, etc.) of a single pulse or multi-pulses on BEOL wafer material. Moreover, the heat affected zone, and thermo-mechanical stress can be also predicted as a function of laser operating parameters (power, frequency, spot size, defocus, speed, etc.). After modeling validation and calibration, a satisfying correlation between experiment and modeling, results have been observed in terms of groove depth, width and heat affected zone. The study proposed in this work is a first step toward implementing a quick assessment tool for design and debug of multiple laser grooving conditions with limited experiments on hardware in industrial application. More correlations and validation tests are in progress and will be included in the full paper.

Keywords: laser-dicing, nano-second pulsed laser, wafer multi-stack, multiphysics modeling

Procedia PDF Downloads 192

Authors: Nagui A. Abdel-Khalek, Khaled A. Selim, Ahmed Hamdy

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Kaolin is naturally occurring ore predominantly containing kaolinite mineral in addition to some gangue minerals. Typical impurities present in kaolin ore are quartz, iron oxides, titanoferrous minerals, mica, feldspar, organic matter, etc. The main coloring impurity, particularly in the ultrafine size range, is titanoferrous minerals. Kaolin is used in many industrial applications such as sanitary ware, table ware, ceramic, paint, and paper industries, each of which should be of certain specifications. For most industrial applications, kaolin should be processed to obtain refined clay so as to match with standard specifications. For example, kaolin used in paper and paint industries need to be of high brightness and low yellowness. Egyptian kaolin is not subjected to any beneficiation process and the Egyptian companies apply selective mining followed by, in some localities, crushing and size reduction only. Such low quality kaolin can be used in refractory and pottery production but not in white ware and paper industries. This paper aims to study the amenability of beneficiation of an Egyptian kaolin ore of El-Teih locality, Sinai, to be suitable for different industrial applications. Attrition scrubbing and classification followed by magnetic separation are applied to remove the associated impurities. Attrition scrubbing and classification are used to separate the coarse silica and feldspars. Wet high intensity magnetic separation was applied to remove colored contaminants such as iron oxide and titanium oxide. Different variables affecting of magnetic separation process such as solid percent, magnetic field, matrix loading capacity, and retention time are studied. The results indicated that substantial decrease in iron oxide (from 1.69% to 0.61% ) and TiO2 (from 3.1% to 0.83%) contents as well as improving iso-brightness (from 63.76% to 75.21% and whiteness (from 79.85% to 86.72%) of the product can be achieved.

Keywords: Kaolin, titanoferrous minerals, beneficiation, magnetic separation, attrition scrubbing, classification

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Authors: David de Oliveira Costa, Miguel Ângelo Lellis Moreira, Carlos Francisco Simões Gomes, Daniel Augusto de Moura Pereira, Marcos dos Santos

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Strategic management is a fundamental process for global companies that intend to remain competitive in an increasingly dynamic and complex market. To do so, it is necessary to maintain alignment with their principles and values. The Balanced Scorecard (BSC) proposes to ensure that the overall business performance is based on different perspectives (financial, customer, internal processes, and learning and growth). However, relying solely on the BSC may not be enough to ensure the success of strategic management. It is essential that companies also evaluate and prioritize strategic projects that need to be implemented to ensure they are aligned with the business vision and contribute to achieving established goals and objectives. In this context, the proposition involves the incorporation of the SAPEVO-M multicriteria method to indicate the degree of relevance between different perspectives. Thus, the strategic objectives linked to these perspectives have greater weight in the classification of structural projects. Additionally, it is proposed to apply the concept of the Impact & Probability Matrix (I&PM) to structure and ensure that strategic projects are evaluated according to their relevance and impact on the business. By structuring the business's strategic management in this way, alignment and prioritization of projects and actions related to strategic planning are ensured. This ensures that resources are directed towards the most relevant and impactful initiatives. Therefore, the objective of this article is to present the proposal for integrating the BSC methodology, the SAPEVO-M multicriteria method, and the prioritization matrix to establish a concrete weighting of strategic planning and obtain coherence in defining strategic projects aligned with the business vision. This ensures a robust decision-making support process.

Keywords: MCDA process, prioritization problematic, corporate strategy, multicriteria method

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Authors: Naz Najma, Grace T. M. Dal Sasso, Maria de Lourdes de Souza

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The development of information and communication technologies and the accessibility of mobile devices has increased the possibilities of the teaching and learning process anywhere and anytime. Mobile and web application allows the production of constructive teaching and learning models in various educational settings, showing the potential for active learning in nursing. The objective of this study was to present the development of an educational technology (Savinglife®, an app) for learning cardiopulmonary resuscitation and advanced cardiovascular life support training. Savinglife® is a technological production, based on the concept of virtual learning and problem-based learning approach. The study was developed from January 2016 to November 2016, using five phases (analyze, design, develop, implement, evaluate) of the instructional systems development process. The technology presented 10 scenarios and 12 simulations, covering different aspects of basic and advanced cardiac life support. The contents can be accessed in a non-linear way leaving the students free to build their knowledge based on their previous experience. Each scenario is presented through interactive tools such as scenario description, assessment, diagnose, intervention and reevaluation. Animated ECG rhythms, text documents, images and videos are provided to support procedural and active learning considering real life situation. Accessible equally on small to large devices with or without an internet connection, Savinglife® offers a dynamic, interactive and flexible tool, placing students at the center of the learning process. Savinglife® can contribute to the student’s learning in the assessment and management of basic and advanced cardiac life support in a safe and ethical way.

Keywords: problem-based learning, cardiopulmonary resuscitation, nursing education, advanced cardiac life support, educational technology

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Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

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Authors: Sadiq Sani, Muhammad B. Ibrahim

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Watermelon rinds powder (WRP) and neem-tree leaves powder (NLP) were used as adsorbents for equilibrium adsorption isotherms studies for detoxification of methyl orange dye (MO) from simulated wastewater. The applicability of the process to various isotherm models was tested. All isotherms from the experimental data showed excellent linear reliability (R2: 0.9487-0.9992) but adsorptions onto WRP were more reliable (R2: 0.9724-0.9992) than onto NLP (R2: 0.9487-0.9989) except for Temkin’s Isotherm where reliability was better onto NLP (R2: 0.9937) than onto WRP (R2: 0.9935). Dubinin-Radushkevich’s monolayer adsorption capacities for both WRP and NLP (qD: 20.72 mg/g, 23.09 mg/g) were better than Langmuir’s (qm: 18.62 mg/g, 21.23 mg/g) with both capacities higher for adsorption onto NLP (qD: 23.09 mg/g; qm: 21.23 mg/g) than onto WRP (qD: 20.72 mg/g; qm: 18.62 mg/g). While values for Langmuir’s separation factor (RL) for both adsorbents suggested unfavourable adsorption processes (RL: -0.0461, -0.0250), Freundlich constant (nF) indicated favourable process onto both WRP (nF: 3.78) and NLP (nF: 5.47). Adsorption onto NLP had higher Dubinin-Radushkevich’s mean free energy of adsorption (E: 0.13 kJ/mol) than WRP (E: 0.08 kJ/mol) and Temkin’s heat of adsorption (bT) was better onto NLP (bT: -0.54 kJ/mol) than onto WRP (bT: -0.95 kJ/mol) all of which suggested physical adsorption.

Keywords: adsorption isotherms, methyl orange, neem leaves, watermelon rinds

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Authors: Payal Patel

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Textile machinery is one of the fastest evolving areas which has an application of mechanical engineering. The modular approach towards the processing right from the stage of cotton to the fabric, allows us to observe the result of each process on its input. Cost and space being the major constraints. The flyer is a component of roving machine, which is used as a part of spinning process. In the present work using the application of Hyper Works, the flyer arm has been modified which saves the material used for manufacturing the flyer. The size optimization of the flyer is carried out with the objective of reduction in weight under the constraints of standard operating conditions. The new design of the flyer is proposed and validated using the module of HyperWorks which is equally strong, but light weighted compared to the existing design. Dynamic balancing of the optimized model is carried out to align a principal inertia axis with the geometric axis of rotation. For the balanced geometry of flyer, air resistance is obtained theoretically and with Gambit and Fluent. Static analysis of the balanced geometry has been done to verify the constraint of operating condition. Comparison of weight, deflection, and factor of safety has been made for different aluminum alloys.

Keywords: flyer, size optimization, textile, weight

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Authors: Shibo Wei, Ting Jiang

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Convolutional-recurrent neural networks (CRN) have achieved much success recently in the speech enhancement field. The common processing method is to use the convolution layer to compress the feature space by multiple upsampling and then model the compressed features with the LSTM layer. At last, the enhanced speech is obtained by deconvolution operation to integrate the global information of the speech sequence. However, the feature space compression process may cause the loss of information, so we propose to model the upsampling result of each step with the residual LSTM layer, then join it with the output of the deconvolution layer and input them to the next deconvolution layer, by this way, we want to integrate the global information of speech sequence better. The experimental results show the network model (RES-CRN) we introduce can achieve better performance than LSTM without residual and overlaying LSTM simply in the original CRN in terms of scale-invariant signal-to-distortion ratio (SI-SNR), speech quality (PESQ), and intelligibility (STOI).

Keywords: convolutional-recurrent neural networks, speech enhancement, residual LSTM, SI-SNR

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Authors: R. M. S. Sachini Amararathne

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This research is striving to develop a thermo degradable starch plastic compound/ masterbatch for industrial packaging applications. A native corn starch-modified with an esterification reaction of lauric acid is melt blent with an unsaturated elastomer (styrene-butadiene-rubber/styrene-butadiene-styrene). A trace amount of metal salt is added into the internal mixer to study the effect of pro-oxidants in a thermo oxidative environment. Then the granulated polymer composite which is consisted with 80-86% of polyolefin (LLDP/LDPE/PP) as the pivotal agent; is extruded with processing aids, antioxidants and some other additives in a co-rotating twin-screw extruder. The pelletized composite is subjected to compression molding/ Injection molding or blown film extrusion processes to acquire the samples/specimen for tests. The degradation process is explicated by analyzing the results of fourier transform infrared spectroscopy (FTIR) measurements, thermo oxidative aging studies (placing the dumb-bell specimen in an air oven at 70 °C for four weeks of exposure.) governed by tensile and impact strength test reports. Furthermore, the samples were elicited into manifold outdoors to inspect the degradation process. This industrial process is implemented to reduce the volume of fossil-based garbage by achieving the biodegradability and compostability in the natural cycle. Hence the research leads to manufacturing a degradable plastic packaging compound which is now available in the Sri Lankan market.

Keywords: blown film extrusion, compression moulding, polyolefin, pro-oxidant, styrene-butadine-rubber, styrene-butadiene-styrene, thermo oxidative aging, unsaturated elastomer

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Authors: Sahana Selladurai, Christine DeWolf

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Lung surfactant comprises a lipid-protein film that coats the alveolar surface and serves to prevent alveolar collapse upon repeated breathing cycles. Exposure of lung surfactant to high concentrations of airborne pollutants, for example tropospheric ozone in smog, can chemically modify the lipid and protein components. These chemical changes can impact the film functionality by decreasing the film’s collapse pressure (minimum surface tension attainable), altering it is mechanical and flow properties and modifying lipid reservoir formation essential for re-spreading of the film during the inhalation process. In this study, we use Langmuir monolayers spread at the air-water interface as model membranes where the compression and expansion of the film mimics the breathing cycle. The impact of ozone exposure on model lung surfactant films is measured using a Langmuir film balance, Brewster angle microscopy and a pendant drop tensiometer as a function of film and sub-phase composition. The oxidized films are analyzed using mass spectrometry where lipid and protein oxidation products are observed. Oxidation is shown to reduce surface activity, alter line tension (and film morphology) and in some cases visibly reduce the viscoelastic properties of the film when compared to controls. These reductions in functionality of the films are highly dependent on film and sub-phase composition, where for example, the effect of oxidation is more pronounced when using a physiologically relevant buffer as opposed to water as the sub-phase. These findings can lead to a better understanding on the impact of continuous exposure to high levels of ozone on the mechanical process of breathing, as well as understanding the roles of certain lung surfactant components in this process.

Keywords: lung surfactant, oxidation, ozone, viscoelasticity

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Authors: Achim Kampker, Heiner Hans Heimes, Mathias Ordung, Nemanja Sarovic

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A key component of the drive train of electric vehicles is the lithium-ion battery system. Among various other components, such as the battery management system or the thermal management system, the battery system mostly consists of several cells which are integrated mechanically as well as electrically. Due to different vehicle concepts with regards to space, energy and power specifications, there is a variety of different battery systems. The corresponding assembly lines are specially designed for each battery concept. Minor changes to certain characteristics of the battery have a disproportionally high effect on the set-up effort in the form of high change-related costs. This paper will focus on battery systems which are made out of battery cells with a prismatic format. The product architecture and the assembly process will be analyzed in detail based on battery concepts of existing electric cars and key variety-causing drivers will be identified. On this basis, several measures will be presented and discussed on how to change the product architecture and the assembly process in order to reduce change-related costs.

Keywords: assembly, automotive industry, battery system, battery concept

Procedia PDF Downloads 285

Authors: Sangbok Lee

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There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

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Authors: T. Zlámal, J. Petrů, M. Pagáč, P. Krajkovič

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For the required function of components with the thermal spray coating, it is necessary to perform additional machining of the coated surface. The paper deals with assessing the surface integrity of Metco 2042, a plasma sprayed coating, after its machining. The selected plasma sprayed coating serves as an abradable sealing coating in a jet engine. Therefore, the spray and its surface must meet high quality and functional requirements. Plasma sprayed coatings are characterized by lamellar structure, which requires a special approach to their machining. Therefore, the experimental part involves the set-up of special cutting tools and cutting parameters under which the applied coating was machined. For the assessment of suitably set machining parameters, selected parameters of surface integrity were measured and evaluated during the experiment. To determine the size of surface irregularities and the effect of the selected machining technology on the sprayed coating surface, the surface roughness parameters Ra and Rz were measured. Furthermore, the measurement of sprayed coating surface hardness by the HR 15 Y method before and after machining process was used to determine the surface strengthening. The changes of strengthening were detected after the machining. The impact of chosen cutting parameters on the surface roughness after the machining was not proven.

Keywords: machining, plasma sprayed coating, surface integrity, strengthening

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Authors: Somaye Eskandary

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Polycyclic aromatic hydrocarbons (PAHs) are present in crude oil and its derivatives contaminate soil and also increase carcinogen and mutagen contamination, which is a concern for researchers. Land farming is one of the methods that remove pollutants from the soil by native microorganisms. It seems that this technology is cost-effective, environmentally friendly and causes less debris problem to be disposed. This study aimed to refine the polycyclic aromatic hydrocarbons from oil-contaminated soil using the land farming method. In addition to examine the concentration of polycyclic aromatic hydrocarbons by GC-FID, some characteristics such as soil microbial respiration and dehydrogenase, peroxidase, urease, acid and alkaline phosphatase enzyme concentration were also measured. The results showed that after land farming process the concentrations of some polycyclic aromatic hydrocarbons dropped to 50 percent. The results showed that the enzyme concentration is reduced by reducing the concentration of hydrocarbons and microbial respiration. These results emphasize the process of land farming for removal of polycyclic aromatic hydrocarbons from soil by indigenous microorganisms.

Keywords: soil contamination, gas chromatography, native microorganisms, soil enzymes, microbial respiration, carcinogen

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Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

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Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: multi objective optimization, pareto front, composite patch, cracked pipe

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Authors: Barry Majeed, Eka Febriana, Seto Julianto

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Kepulauan Seribu National Parks is a marine preservation region in Indonesia. It is located in 5°23' - 5°40' LS, 106°25' - 106°37' BT North of Jakarta City. Covered with area 107,489 ha, Kepulauan Seribu has a lot of tourism spots such as cluster islands, fringing reef and many more. Kepulauan Seribu is also nominated as Strategic Tourism Region In Indonesia (KSPN). So, these islands have a lot of potential sides more than preservation function as a national park, hence the development of sustainable geotourism. The aim of this study is for enhancing the development of eco-geotourism in Kepulauan Seribu. This study concern for three main aspect of eco-geotourism such as tourism, form and process. Study for the tourism aspect includes attractions, accommodations, tours, activities, interpretation, and planning & management in Kepulauan Seribu. Study for the form aspect focused on the carbonate platform situated between two islands. Primarily in carbonate reef such as head coral, branchy coral, platy coral that created the carbonate sequence in Kepulauan Seribu. Study for the process aspect primarily discussed the process of forming of carbonate from carbonate factory later becomes Kepulauan Seribu. Study for the regional geology of Kepulauan Seribu has been conducted and suggested that Kepulauan Seribu lithologies are mainly quarternary limestone. In this study, primary data was taken from an observation of quarternary carbonate platform between two islands from Hati Island, Macan Island, Bulat Island, Ubi Island and Kelapa Island. From this observation, the best routes for tourist have been made from Island to Island. Qualitative methods such as depth interview to the local people in purposive sampling also have been made. Finally, this study also giving education about geological site – carbonate sequence - in Kepulauan Seribu for the local wisdom so that this study can support the development of sustainable eco-geotourism in Kepulauan Seribu.

Keywords: carbonate factory, carbonate platform, geotourism, Kepulauan Seribu

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Authors: Hassan Zare, Mohammad Jahedi, Mohammad Reza Toroghinejad, Mahmoud Meratian, Marko Knezevic

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In this study, the carbon nanotube (CNT) reinforced Al matrix nanocomposites were fabricated by ECAP. Equal Channel Angular Pressing (ECAP) process is one of the most important methods for powder densification due to the presence of shear strain. This method samples with variety passes (one, two, four and eight passes) in C route were prepared at room temperature. A few study about metal matrix nanocomposite reinforced carbon nanotube done, the reaction intersection of interface and carbon nanotube cause to reduce the efficiency of nanocomposite. In this paper, we checked mechanical and physical properties of aluminum-CNT composite that manufactured by ECAP when the composite is deformed. The non-agglomerated CNTs were distributed homogeneously with 2% consolidation in the Aluminum matrix. The ECAP process was performed on the both monolithic and composite with distributed CNT samples for 8 passes.

Keywords: powder metallurgy, ball mill attrition, ultrasonic, consolidation

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Authors: Dmytro Symak

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Drying is a complex technologic, thermal and energy process. Energy cost of drying processes in many cases is the most costly stage of production, and can be over 50% of total costs. As we know, in Ukraine over 85% of Portland cement is produced moist, and the finished product energy costs make up to almost 60%. During the wet cement production, energy costs make up over 5500 kJ / kg of clinker, while during the dry only 3100 kJ / kg, that is, switching to a dry Portland cement will allow result into double cutting energy costs. Therefore, to study raw materials drying process in the manufacture of Portland cement is very actual task. The fine ferrous materials drying (small pyrites, red mud, clay Kyoko) is recommended to do by filtration method, that is one of the most intense. The essence of filtration method drying lies in heat agent filtering through a stationary layer of wet material, which is located on the perforated partition, in the "layer-dispersed material - perforated partition." For the optimum drying purposes, it is necessary to establish the dependence of pressure loss in the layer of dispersed material, and the values of heat and mass transfer, depending on the speed of the gas flow filtering. In our research, the experimentally determined pressure loss in the layer of dispersed material was generalized based on dimensionless complexes in the form and coefficients of heat exchange. We also determined the relation between the coefficients of mass and heat transfer. As a result of theoretic and experimental investigations, it was possible to develop a methodology for calculating the optimal parameters for the thermal agent and the main parameters for the filtration drying installation. The comparison of calculated by known operating expenses methods for the process of small pyrites drying in a rotating drum and filtration method shows to save up to 618 kWh per 1,000 kg of dry material and 700 kWh during filtration drying clay.

Keywords: drying, cement, heat and mass transfer, filtration method

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Authors: Martha Lilia Del Rio Duque, Michelle Bonatti, Katharina Loehr, Marcos Lana, Tatiana Rodriguez, Stefan Sieber

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Nowadays, most agricultural practices can reduce the ability of ecosystems to provide goods and services. To enhance environmentally friendly food production and to maximize social and economic benefits, sustainable land use systems (SLUS) are one of the most critical strategies increasingly/strongly promoted by donors organizations, international agencies, and policymakers. This process involves the question of how SLUS can be scaled out also large-scale landscapes and not merely isolated experiments. As SLUS are context-specific strategies, diffusion and replication of successful SLUS in Colombia required the identification of main factors that facilitate this scaling out process. We applied a case study approach to investigate the scaling out process of SLUS in cocoa and livestock sector within peacebuilding territories in Colombia, specifically, in Cesar and Caqueta region. These two regions are contrasting, but both have a current trend of increasing land degradation. Presently in Colombia, Caqueta is one of the most deforested departments, and Cesar has some most degraded soils. Following a qualitative research approach, 19 semi-structured interviews and 2 focus groups were conducted with agroforestry experts in both regions to analyze (1) what does it mean a sustainable land use system in Cocoa/Livestock, specifically in Caqueta or Cesar and (2) to identify the key elements at the level of the following dimensions: biophysical, economic and profitability, market, social, policy and institutions that can explain how and why SLUS are replicated and spread among more producers. The Interviews were coded and analyzed using MAXQDA to identify, analyze and report patterns (themes) within data. As the results show, key themes, among which: premium market, solid regional markets and price stability, water availability and management, generational renewal, land use knowledge and diversification, producer organization and certifications are crucial to understand how the SLUS can have an impact across large-scale landscapes and how the scaling out process can be set up best in order to be successful across different contexts. The analysis further reveals which key factors might affect SLUS efficiency.

Keywords: agroforestry, cocoa sector, Colombia, livestock sector, sustainable land use system

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Authors: Lamzira Ebralidze, Aleksandre Tsertsvadze, Dali Berashvili, Aliosha Bakuridze

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Nowadays, there is an increasing demand for biologically active substances from vegetable, animal, and mineral resources. In terms of the use of natural compounds, pharmaceutical, cosmetic, and nutrition industry has big interest. The biggest drawback of conventional extraction methods is the need to use a large volume of organic extragents. The removal of the organic solvent is a multi-stage process. And their absolute removal cannot be achieved, and they still appear in the final product as impurities. A large amount of waste containing organic solvent damages not only human health but also has the harmful effects of the environment. Accordingly, researchers are focused on improving the extraction methods, which aims to minimize the use of organic solvents and energy sources, using alternate solvents and renewable raw materials. In this context, green extraction principles were formed. Green Extraction is a need of today’s environment. Green Extraction is the concept, and it totally corresponds to the challenges of the 21st century. The extraction of biologically active compounds based on green extraction principles is vital from the view of preservation and maintaining biodiversity. Novel technologies of green extraction are known, such as "cold methods" because during the extraction process, the temperature is relatively lower, and it doesn’t have a negative impact on the stability of plant compounds. Novel technologies provide great opportunities to reduce or replace the use of organic toxic solvents, the efficiency of the process, enhance excretion yield, and improve the quality of the final product. The objective of the research is the development of green technologies of flavonoids containing preparations. Methodology: At the first stage of the research, flavonoids containing preparations (Tincture Herba Leonuri, flamine, rutine) were prepared based on conventional extraction methods: maceration, bismaceration, percolation, repercolation. At the same time, the same preparations were prepared based on green technologies, microwave-assisted, UV extraction methods. Product quality characteristics were evaluated by pharmacopeia methods. At the next stage of the research technological - economic characteristics and cost efficiency of products prepared based on conventional and novel technologies were determined. For the extraction of flavonoids, water is used as extragent. Surface-active substances are used as co-solvent in order to reduce surface tension, which significantly increases the solubility of polyphenols in water. Different concentrations of water-glycerol mixture, cyclodextrin, ionic solvent were used for the extraction process. In vitro antioxidant activity will be studied by the spectrophotometric method, using DPPH (2,2-diphenyl-1- picrylhydrazyl) as an antioxidant assay. The advantage of green extraction methods is also the possibility of obtaining higher yield in case of low temperature, limitation extraction process of undesirable compounds. That is especially important for the extraction of thermosensitive compounds and maintaining their stability.

Keywords: extraction, green technologies, natural resources, flavonoids

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Authors: Surinder Pal, Ajay Gupta, Johny Khajuria

Abstract:

Casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals are, however, a very complex phenomenon that is difficult to simulate correctly by conventional computational techniques, especially when the part geometry is intricate and the required inputs (like thermo-physical properties and heat transfer coefficients) are not available. Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome. The all casting simulation software has own requirements, like magma cast has only best for crack simulation. The latest generation software Auto CAST developed at IIT Bombay provides a host of functions to support method engineers, including part thickness visualization, core design, multi-cavity mold design with common gating and feeding, application of various feed aids (feeder sleeves, chills, padding, etc.), simulation of mold filling and casting solidification, automatic optimization of feeders and gating driven by the desired quality level, and what-if cost analysis. IIT Bombay has developed a set of applications for the foundry industry to improve casting yield and quality. Casting simulation is a fast and efficient solution for process for advanced tool which is the result of more than 20 years of collaboration with major industrial partners and academic institutions around the world. In this paper the process of casting simulation is studied.

Keywords: casting simulation software’s, simulation technique’s, casting simulation, processes

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Authors: Bilal Bhat, M. Masroor A. Khan, Moin Uddin, M. Naeem

Abstract:

Aromatic herb, peppermint (Mentha piperita L.), is a natural hybrid (M. aquatica × M. spicata) with immense therapeutic uses, apart from other potential uses. Peppermint oil is one of the most popular and widely used essential oil (EO), because of its main components menthol and menthone. In view of enhancing growth, yield and quality of this medicinally important herb, a pot experiment was conducted in the net-house of the department. The experiment was aimed at studying the effect of graded levels of N, P, and K on growth, biochemical characteristics, and content and composition of EO in Mentha piperita L. Six NPK treatments (viz. N0P0K0, N20P20K20, N40P40K40, N20+20 P20+20 K20+20, N60P60K60, and N30+30 P30+30 K30+30) were tested. The plants were harvested 150 days after transplanting. The crop performance was assessed in terms of growth attributes, physiological activities, herbage yield and content as well as yield of active constituents of Mentha piperita L. Biochemical parameters were analyzed spectrophotometrically. The EO was extracted using Clevenger’s apparatus and the active constituents of the oil were determined using Gas Chromatography. Split-dose application of N, P and K (N30+30 P30+30 K30+30) ameliorated most of the parameters significantly including, fresh and dry weight of plant, NPK content, chlorophyll and carotenoids content, and the activities of carbonic anhydrase and nitrate reductase in the leaves. It also enhanced the EO content (44.0%), EO yield (91.0%), menthol content (14.1%), menthone content (34.0%), menthyl acetate content (16.9%) and 1, 8-cineole content (43.7%) but decreased the pulegone content (36.8%). Conclusively, the fertilization proved useful in enhancing the EO content, yield and other EO components of the plant. Thus, the yield and quality of EO of peppermint may be improved by this agricultural strategy.

Keywords: mentha piperita, menthol, menthone, EO

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Authors: Alma Gómez-Loredo, José González-Valdez, Jorge Benavides, Marco Rito-Palomares

Abstract:

Fucoxanthin is a carotenoid that exerts multiple beneficial effects on human health, including antioxidant, anti-cancer, antidiabetic and anti-obesity activity; making the development of a whole process for its production and recovery an important contribution. In this work, the lab-scale production and purification of fucoxanthin in Isocrhysis galbana have been studied. In batch cultures, low light intensities (13.5 μmol/m2s) and bubble agitation were the best conditions for production of the carotenoid with product yields of up to 0.143 mg/g. After fucoxanthin ethanolic extraction from biomass and hexane partition, further recovery and purification of the carotenoid has been accomplished by means of alcohol – salt Aqueous Two-Phase System (ATPS) extraction followed by an ultrafiltration (UF) step. An ATPS comprised of ethanol and potassium phosphate (Volume Ratio (VR) =3; Tie-line Length (TLL) 60% w/w) presented a fucoxanthin recovery yield of 76.24 ± 1.60% among the studied systems and was able to remove 64.89 ± 2.64% of the carotenoid and chlorophyll pollutants. For UF, the addition of ethanol to the original recovered ethanolic ATPS stream to a final relation of 74.15% (w/w) resulted in a reduction of approximately 16% of the protein contents, increasing product purity with a recovery yield of about 63% of the compound in the permeate stream. Considering the production, extraction and primary recovery (ATPS and UF) steps, around a 45% global fucoxanthin recovery should be expected. Although other purification technologies, such as Centrifugal Partition Chromatography are able to obtain fucoxanthin recoveries of up to 83%, the process developed in the present work does not require large volumes of solvents or expensive equipment. Moreover, it has a potential for scale up to commercial scale and represents a cost-effective strategy when compared to traditional separation techniques like chromatography.

Keywords: aqueous two-phase systems, fucoxanthin, Isochrysis galbana, microalgae, ultrafiltration

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Authors: Liang Fang

Abstract:

The development of the large suburban residential area is a product of the leap development during the rapid urbanization process in China. On the process of the large-scale development of large settlements in a short time, various problems arose in the suburban residential area, such as spatial layout being disorder, basic facilities construction lagging behind and being unreasonable, residential neighborhood space and street culture missing. Aimed at the contradictions mentioned above, exploring a way is imminent to construct appropriate residential area. We select a typical Liangzhu Culture Village in Hangzhou and put forward functional composite residential area of fine development strategy, along which business promotes and assists community autonomy and then a good community culture is constructed. All in all, the development and construction mode, contributing to an all-people and full-time participation, is beneficial to create a harmonious community of sustainable development, which gives good implication to a single enterprise development city real estate projects.

Keywords: community autonomy, development and construction mode, functional composite, suburban large residential area

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Authors: Yas Barzegaar, Atrin Barzegar

Abstract:

The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

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Authors: Lina Lauciene, Vaida Andruleviciute, Ingrida Sinkeviciene, Mindaugas Malakauskas, Loreta Serniene

Abstract:

Dairy product manufacturers constantly are looking for new markets for their production. And in most cases, the problem of product compliance with the composition requirements of foreign products is highlighted. This is especially true of the composition of milk fat in dairy products. It is well known that there are many factors such as feeding ratio, season, cow breed, stage of lactation that affect the fatty acid composition in milk. However, there is less evidence on the impact of the technological process on the composition of fatty acids in raw milk and products made from it. In this study the influence of the technological process on fat composition in 82% fat butter, 15% fat curd, 3.6% fat yogurt and 2.5% fat UHT milk was determined. The samples were collected at each stage of production, starting with raw milk and ending with the final product in the Lithuanian milk-processing company. Fatty acids methyl esters were quantified using a GC (Clarus 680, Perkin Elmer) equipped with flame ionization detector (FID) and a capillary column SP-2560, 100 m x 0.25 mm id x 0.20 µm. Fatty acids peaks were identified using Supelco® 37 Component FAME Mix. The concentration of each fatty acid was expressed in percent of the total fatty acid amount. In the case of UHT milk production, it was compared raw milk, cream, milk mixture, and UHT milk but significant differences were not estimated between these stages. Analyzing stages of the yogurt production (raw milk, pasteurized milk, and milk with a starter culture and yogurt), no significant changes were detected between stages as well. A slight difference was observed with C4:0 - a percentage of this fatty acid was less (p=0.053) in the final stage than in milk with the starter culture. During butter production, the composition of fatty acids in raw cream, buttermilk, and butter did not change significantly. Only C14:0 decreased in the butter then compared to buttermilk. The curd fatty acid analysis showed the increase of C6:0, C8:0, C10:0, C11:0, C12:0 C14:0 and C17:0 at the final stage when compared to raw milk, cream, milk mixture, and whey. Meantime the increase of C18:1n9c (in comparison with milk mixture and curd) and C18:2n6c (in comparison with raw milk, milk mixture, and curd) was estimated in cream. The results of this study suggest that the technological process did not affect the composition of fatty acids in UHT milk, yogurt, butter, and curd but had the impact on the concentration of individual fatty acids. In general, all of the fatty acids from the raw milk were converted into the final product, only some of them slightly changed the concentration. Therefore, in order to ensure an appropriate composition of certain fatty acids in the final product, producers must carefully choose the raw milk. Acknowledgment: This research was funded by Lithuanian Ministry of Agriculture (No. MT-17-13).

Keywords: dairy products, fat composition, fatty acids, technological process

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