Search results for: whale optimization algorithm

Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

Procedia PDF Downloads 61

Authors: Inderpreet Kaur, Sukhjit Kaur, Balwinder Singh Sohi

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The design proposed in this paper mainly focuses on implementation of a single feed compact rectangular microstrip patch antenna (MSA) for single band application. The antenna presented here also works in dual band but its best performance has been obtained when optimised to work in single band mode. In this paper, a new feeding structure is applied in the patch antenna design to overcome undesirable features of the earlier multilayer feeding structures while maintaining their interesting features.To make the proposed antenna more efficient the optimization of the antenna design parameters have been done using HFSS’s optometric. For the proposed antenna one resonant frequency has been obtained at 6.03GHz, with Bandwidth of 167MHz and return loss of -33.82db. The characteristics of the designed structure are investigated by using FEM based electromagnetic solver.

Keywords: bandwidth, retun loss, parasitic lines, microstrip antenna

Procedia PDF Downloads 463

Authors: P. Sawitri, S. Cdr. Sittha, T. Kritsana

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Flow forming is widely used in many industries, especially in defence technology industries. Pressure vessels requirements are high precision, light weight, seamless and optimum strength. For large pressure vessels, flow forming by 3 rollers machine were used. In case of long range rocket motor case flow forming and welding of pressure vessels have been used for manufacturing. Due to complication of welding process, researchers had developed 4 meters length pressure vessels without weldment by 4 rollers flow forming machine. Design and preparation of preform work pieces are performed. The optimization of flow forming parameter such as feed rate, spindle speed and depth of cut will be discussed. The experimental result shown relation of flow forming parameters to quality of flow formed tube and prototype pressure vessels have been made.

Keywords: flow forming, pressure vessel, four rollers, feed rate, spindle speed, cold work

Procedia PDF Downloads 331

Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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Authors: P. Brinks, O. Kornadt, R. Oly

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This research focuses on the optimization of glazed surfaces and the assessment of possible solar gains in industrial buildings. Existing window rating methods for single windows were evaluated and a new method for a simple analysis of energy gains and losses by single windows was introduced. Furthermore extensive transient building simulations were carried out to appraise the performance of low cost polycarbonate multi-cell sheets in interaction with typical buildings for industrial applications. Mainly, energy-saving potential was determined by optimizing the orientation and area of such glazing systems in dependency on their thermal qualities. Moreover the impact on critical aspects such as summer overheating and daylight illumination was considered to ensure the user comfort and avoid additional energy demand for lighting or cooling. Hereby the simulated heating demand could be reduced by up to 1/3 compared to traditional architecture of industrial halls using mainly skylights.

Keywords: solar architecture, Passive Solar Building Design, glazing, Low-Energy Buildings, industrial buildings

Procedia PDF Downloads 236

Authors: Ilhem Ouelhazi, Mouna Elakhdar, Lakdar Kairouani

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A computer simulation model for a combined ejector-vapor compression cycle that uses working fluid R134a. A refrigeration system was developed which combines a basic vapor compression refrigeration cycle with an ejector cooling cycle. A one-dimensional mathematical model was developed using the equations governing the flow and thermodynamics based on the constant area ejector flow model. The effects of the operating parameters on the cooling capacity, the performance coefficient, and the entrainment ratio are studied. The current model is based on the NIST-REFPROP database for refrigerants properties calculations. The simulated performance is compared with the available experimental data from the literature for validation.

Keywords: combined refrigeration cycle, constant area ejector, R134a, ejector-cooling cycle, performance, mathematical simulation, vapor compression cycle

Procedia PDF Downloads 226

Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

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In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

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Authors: N. F. Jamaluddin, N. A. H. Aizam

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This paper explains the educational timetabling problem, a type of scheduling problem that is considered as one of the most challenging problem in optimization and operational research. The university examination timetabling problem (UETP), which involves assigning a set number of exams into a set number of timeslots whilst fulfilling all required conditions, has been widely investigated. The limitation of available timeslots and resources with the increasing number of examinations are the main reasons in the difficulty of solving this problem. Dynamical change in the examination scheduling system adds up the complication particularly in coping up with the demand and new requirements by the communities. Our objective is to investigate these demands and requirements with subjects taken from Universiti Malaysia Terengganu (UMT), through questionnaires. Integer linear programming model which reflects the preferences obtained to produce an effective examination timetabling was formed.

Keywords: demands, educational timetabling, integer linear programming, scheduling, university examination timetabling problem (UETP)

Procedia PDF Downloads 337

Authors: Muhammad Awais Kiani, Maryam Kiani

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In today's digital age, the field of electronics engineering is experiencing unprecedented growth and innovation. To keep pace with this rapidly evolving industry, effective sales and marketing strategies are crucial, especially when combined with the power of e-commerce. This study explores the significance of integrating sales and marketing techniques with e-commerce platforms in the context of electronics engineering. It highlights the benefits, challenges, and best practices in leveraging e-commerce for sales and marketing in this industry. By embracing e-commerce, electronics engineering companies can reach a wider customer base, enhance brand visibility, and personalize customer experiences. Furthermore, this abstract delves into the importance of utilizing digital marketing tools such as search engine optimization (SEO), social media marketing, and content creation to optimize online sales. Therefore, this research aims to provide insights and recommendations for electronics engineering professionals to effectively navigate the dynamic landscape of sales and marketing in conjunction with e-commerce.

Keywords: electronics engineering, marketing, sales, E-commerce

Procedia PDF Downloads 75

Authors: Markandeya Kunchi

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Usability testing (UT) is one of the vital steps in the User-centred design (UCD) process when designing a product. In an e-commerce ecosystem, UT becomes primary as new products, features, and services are launched very frequently. And, there are losses attached to the company if an unusable and inefficient product is put out to market and is rejected by customers. This paper tries to answer why UT is important in the product life-cycle of an E-commerce ecosystem. Secondary user research was conducted to find out work patterns, development methods, type of stakeholders, and technology constraints, etc. of a typical E-commerce company. Qualitative user interviews were conducted with product managers and designers to find out the structure, project planning, product management method and role of the design team in a mid-level company. The paper tries to address the usual apprehensions of the company to inculcate UT within the team. As well, it stresses upon factors like monetary resources, lack of usability expert, narrow timelines, and lack of understanding of higher management as some primary reasons. Outsourcing UT to vendors is also very prevalent with mid-level e-commerce companies, but it has its own severe repercussions like very little team involvement, huge cost, misinterpretation of the findings, elongated timelines, and lack of empathy towards the customer, etc. The shortfalls of the unavailability of a UT process in place within the team and conducting UT through vendors are bad user experiences for customers while interacting with the product, badly designed products which are neither useful and nor utilitarian. As a result, companies see dipping conversions rates in apps and websites, huge bounce rates and increased uninstall rates. Thus, there was a need for a more lean UT system in place which could solve all these issues for the company. This paper highlights on optimizing the UT process with a collaborative method. The degree of optimization and structure of collaborative method is the highlight of this paper. Collaborative method of UT is one in which the centralised design team of the company takes for conducting and analysing the UT. The UT is usually a formative kind where designers take findings into account and uses in the ideation process. The success of collaborative method of UT is due to its ability to sync with the product management method employed by the company or team. The collaborative methods focus on engaging various teams (design, marketing, product, administration, IT, etc.) each with its own defined roles and responsibility in conducting a smooth UT with users In-house. The paper finally highlights the positive results of collaborative UT method after conducting more than 100 In-lab interviews with users across the different lines of businesses. Some of which are the improvement of interaction between stakeholders and the design team, empathy towards users, improved design iteration, better sanity check of design solutions, optimization of time and money, effective and efficient design solution. The future scope of collaborative UT is to make this method leaner, by reducing the number of days to complete the entire project starting from planning between teams to publishing the UT report.

Keywords: collaborative method, e-commerce, product management method, usability testing

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Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

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The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: auto tuning, balanced robot, closed loop identification, subspace identification

Procedia PDF Downloads 380

Authors: F. Hassaine-Sadi, S. Chelouaou

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In recent years, environmental contamination by toxic metals such as Pb, Cu, Ni, Zn ... has become a worldwide crucial problem, particularly in some areas where the population depends on groundwater for drinking daily consumption. Thus, the sources of metal ions come from the metal manufacturing industry, fertilizers, batteries, paints, pigments and so on. Solvent extraction of metal ions has given an important role in the development of metal purification processes such as the synergistic extraction of some divalent cations metals ( M²⁺), the ions metals from various sources. This work consists of a water purification technique that involves the lead and copper systems: Pb²⁺, H₃O+, Cl⁻ and Cu²⁺, H₃O⁺, Cl⁻ for diluted solutions by a mixture of tri-n-octylphosphine oxide (TOPO) or Tri-n-butylphosphate(TBP) and di (2-ethyl hexyl) phosphoric acid (HDEHP) dissolved in kerosene. The study of the fundamental parameters influencing the extraction synergism: cation exchange/extraction solvent have been examined.

Keywords: synergistic extraction, lead, copper, environment

Procedia PDF Downloads 445

Authors: Brahim Mahfoud, Ali Bendjaghlouli

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Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

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Authors: Joon-Hoon Park

Abstract:

In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

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Authors: P. Priyanka, S. Shruthi, N. Guruprasad

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Health is a common theme in most cultures. In fact all communities have their concepts of health, as part of their culture. Health continues to be a neglected entity. Planning of Human diet should be done very careful by selecting the food items or groups of food items also the composition involved. Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Linear programming techniques have been extensively used for human diet formulation for quiet good number of years. Through the process, we mainly apply “The Simplex Method” which is a very useful statistical tool based on the theorem of Elementary Row Operation from Linear Algebra and also incorporate some other necessary rules set by the Simplex Method to help solve the problem. The study done by us is an attempt to develop a programming model for optimal planning and best use of nutrient ingredients.

Keywords: diet formulation, linear programming, nutrient ingredients, optimization, simplex method

Procedia PDF Downloads 558

Authors: Pornsiri Kaewpradit, Chalisa Pourneaw

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Temperature control improvement of a membrane reactor with exothermic and reversible esterification reaction is studied in this work. It is well known that a batch membrane reactor requires different control strategies from a continuous one due to the fact that it is operated dynamically. Due to the effect of the operating temperature, the suitable control scheme has to be designed based reliable predictive model to achieve a desired objective. In the study, the optimization framework has been preliminary formulated in order to determine an optimal temperature trajectory for maximizing a desired product. In model predictive control scheme, a set of predictive models have been initially developed corresponding to the possible operating points of the system. The multiple predictive control moves have been further calculated on-line using the developed models corresponding to current operating point. It is obviously seen in the simulation results that the temperature control has been improved compared to the performance obtained by the conventional predictive controller. Further robustness tests have also been investigated in this study.

Keywords: model predictive control, batch reactor, temperature control, membrane reactor

Procedia PDF Downloads 468

Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

Procedia PDF Downloads 345

Authors: Razieh Teimouri

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Electrical modelling of Cu (In,Ga)Se₂ thin film solar cells is carried out with compositionally graded absorber and CdS buffer layer. Simulation results are compared with experimental data. Surface defect layers (SDL) are located in CdS/CIGS interface for improving open circuit voltage simulated structure through the analysis of the interface is investigated with or without this layer. When SDL removed, by optimizing the conduction band offset (CBO) position of the buffer/absorber layers with its recombination mechanisms and also shallow donor density in the CdS, the open circuit voltage increased significantly. As a result of simulation, excellent performance can be obtained when the conduction band of window layer positions higher by 0.2 eV than that of CIGS and shallow donor density in the CdS was found about 1×10¹⁸ (cm⁻³).

Keywords: CIGS solar cells, thin film, SCAPS, buffer layer, conduction band offset

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Authors: Umar Yusuf Batsari

Abstract:

Let E be a uniformly smooth and uniformly convex real Banach space and C be a nonempty, closed and convex subset of E. Let $V= \{S_i : C\to C, ~i=1, 2, 3\cdots N\}$ be a convex set of relatively nonexpansive mappings containing identity. In this paper, an iterative sequence obtained from CQ algorithm was shown to have strongly converge to a point $\hat{x}$ which is a common fixed point of relatively nonexpansive mappings in V and also solve the system of equilibrium problems in E. The result improve some existing results in the literature.

Keywords: relatively nonexpansive mappings, strong convergence, equilibrium problems, uniformly smooth space, uniformly convex space, convex set, kadec klee property

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Pallavi N., Gayatri Jadhav

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Good quality water is of prime importance for a healthy living. Fluoride is one such mineral present in water which causes many health problems in humans and specially children. Fluoride is said to be a double edge sword because lesser and higher concentration of fluoride in drinking water can cause both dental and skeletal fluorosis. Fluoride is one of the important mineral usually present at a higher concentration in ground water. There are many researches being carried out for defluoridation method. In the present research, fluoride removal is demonstrated using banana peel which is a biowaste as a biocoagulant. Response Surface Methodology (RSM) is a statistical design tool which is used to design the experiment. Central Composite Design (CCD) was used to determine the influence of the pH and dosage of the coagulant on the optimal removal of fluoride from a simulated water sample. 895 of fluoride removal were obtained in a acidic pH range of 4 – 9 and bio coagulant dosage of dosage of 18 – 20mg/L.

Keywords: Fluoride, Response Surface Methodology, Dosage, banana peel

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Authors: I. Savitskaya, A. Kistaubayeva, A. Zhubanova, I. Blavachinskaiya, D. Ibrayeva, M. Abdulzhanova, A. Otarbay, A.Isabekova

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This study was conducted for the investigation of number of cellulolytic bacteria and their ability in decomposition. Seven samples surface soil were collected on cellulose Zailiskii Alatau slopes. Cellulolitic activity of new strains of Bacillus, isolated from soil is determined. Isolated cellulose degrading bacteria were screened for determination of the highest cellulose activity by quantitative assay using Congo red, gravimetric assay and colorimetric DNS method trough of the determination of the parameters of sugar reduction. Strains are assigned to: B.subtilis, B.licheniformis, B. cereus and, В. megaterium. Bacillus strains consisting of several different types of cellulases have broad substrate specificity of cellulase complexes formed by them. Cellulolitic bacteria were recorded to have highest cellulase activity and selected for optimization of cellulase enzyme production.

Keywords: cellulose-degrading bacteria, cellulase complex, foothills soil, screening

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Authors: Poojan Gharat, Haridas Pal, Sharmistha Dutta Choudhury

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Tuning photophysical properties of guest dyes through host-guest interactions involving macrocyclic hosts are the attractive research areas since past few decades, as these changes can directly be implemented in chemical sensing, molecular recognition, fluorescence imaging and dye laser applications. Excited state intramolecular proton transfer (ESIPT) is an intramolecular prototautomerization process display by some specific dyes. The process is quite amenable to tunability by the presence of different macrocyclic hosts. The present study explores the interesting effect of p-sulfonatocalix[n]arene (SCXn) and cyclodextrin (CD) hosts on the excited-state prototautomeric equilibrium of Chrysazine (CZ), a model antitumour drug. CZ exists exclusively in its normal form (N) in the ground state. However, in the excited state, the excited N* form undergoes ESIPT along with its pre-existing intramolecular hydrogen bonds, giving the excited state prototautomer (T*). Accordingly, CZ shows a single absorption band due to N form, but two emission bands due to N* and T* forms. Facile prototautomerization of CZ is considerably inhibited when the dye gets bound to SCXn hosts. However, in spite of lower binding affinity, the inhibition is more profound with SCX6 host as compared to SCX4 host. For CD-CZ system, while prototautomerization process is hindered by the presence of β-CD, it remains unaffected in the presence of γCD. Reduction in the prototautomerization process of CZ by SCXn and βCD hosts is unusual, because T* form is less dipolar in nature than the N*, hence binding of CZ within relatively hydrophobic hosts cavities should have enhanced the prototautomerization process. At the same time, considering the similar chemical nature of two CD hosts, their effect on prototautomerization process of CZ would have also been similar. The atypical effects on the prototautomerization process of CZ by the studied hosts are suggested to arise due to the partial inclusion or external binding of CZ with the hosts. As a result, there is a strong possibility of intermolecular H-bonding interaction between CZ dye and the functional groups present at the portals of SCXn and βCD hosts. Formation of these intermolecular H-bonds effectively causes the pre-existing intramolecular H-bonding network within CZ molecule to become weak, and this consequently reduces the prototautomerization process for the dye. Our results suggest that rather than the binding affinity between the dye and host, it is the orientation of CZ in the case of SCXn-CZ complexes and the binding stoichiometry in the case of CD-CZ complexes that play the predominant role in influencing the prototautomeric equilibrium of the dye CZ. In the case of SCXn-CZ complexes, the results obtained through experimental findings are well supported by quantum chemical calculations. Similarly for CD-CZ systems, binding stoichiometries obtained through geometry optimization studies on the complexes between CZ and CD hosts correlate nicely with the experimental results. Formation of βCD-CZ complexes with 1:1 stoichiometry while formation of γCD-CZ complexes with 1:1, 1:2 and 2:2 stoichiometries are revealed from geometry optimization studies and these results are in good accordance with the observed effects by the βCD and γCD hosts on the ESIPT process of CZ dye.

Keywords: intermolecular proton transfer, macrocyclic hosts, quantum chemical studies, photophysical studies

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Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

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First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

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Authors: Manjinder Bajwa, Mahipal Singh, Manish Nagpal

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This research paper aims to propose a novel approach using ANOVA technique for the strategic investigation of process parameters and their effects on the mechanical properties of Aluminium alloy cast. The two process parameters considered here were permeability of sand and pouring temperature of aluminium alloy. ANOVA has been employed for the first time to determine the effects of these selected parameters on the impact strength of alloy. The experimental results show that this proposed technique has great potential for analyzing sand casting process. Using this approach we have determined the treatment mean square, response mean square and mean square of error as 8.54, 8.255 and 0.435 respectively. The research concluded that at the 5% level of significance, permeability of sand is the more significant parameter influencing the impact strength of cast alloy.

Keywords: aluminium alloy, pouring temperature, permeability of sand, impact strength, ANOVA

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Authors: Sungho Kim, Dae Shik Kim, Jong Min Lee

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Fluid catalytic cracking (FCC) process is one of the most important process in modern refinery industry. This paper focuses on the fluid catalytic cracking (FCC) process. As the FCC process is difficult to model well, due to its non linearities and various interactions between its process variables, rigorous process modeling of whole FCC plant is demanded for control and plant-wide optimization of the plant. In this study, a process design for the FCC plant includes riser reactor, main fractionator, and gas processing unit was developed. A reactor model was described based on four-lumped kinetic scheme. Main fractionator, gas processing unit and other process units are designed to simulate real plant data, using a process flow sheet simulator, Aspen PLUS. The custom reactor model was integrated with the process flow sheet simulator to develop an integrated process model.

Keywords: fluid catalytic cracking, simulation, plant data, process design

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Authors: Yeon-Jong Jeong, Mok-Tan Ahn, Seok-Hyeon Park, Seong-Hun Ha, Joon-Hong Park, Jong-Bae Park

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Multi-stage drawing process is an important technique for forming a shape that cannot be molded in a single process. multi-stage drawing process in number of passes and the shape of the die are an important factors influencing the productivity and formability of the product. The number and shape of the multi-path in the mold of the drawing process is very influencing the productivity and formability of the product. Half angle of the die and mandrel affects the drawing force and it also affects the completion of the final shape. Thus reducing the number of pass and the die shape optimization are necessary to improve the formability of the billet. Analyzing the load on the die through the FEM analysis and in consideration of the formability of the material presents a die model.

Keywords: multi-pass shape drawing, equivalent stress, FEM, finite element method, optimum shape

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Authors: Katherine Carl Payne, Moshe Dror

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The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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Authors: Akbar Esmaeili, Fateme Dadashi

Abstract:

Bismuth can increase radiation and reduce the dose of radiotherapy. On the other hand, hyaluronic acid plays a role in healing damaged cells, and melittin has been used to destroy cancer cells. This research aims to destroy eye cancer cells and accelerate the recovery of damaged healthy cells during treatment. In this research, we used this nanoparticle, the sol-gel method. According to the optimization process that was carried out, we obtained the optimal value of the desired variables for the manufacture of nanoparticles. The advantage of doing this is reducing the amount of medicine used, as a result of reducing the number of side effects during the treatment and using melittin as an anti-eye cancer drug and the presence of hyaluronic acid to accelerate the recovery of cells, as well as coating the bismuth nanoparticle with chitosan to increase the half-life of the nanoparticle and prevent its adhesion.

Keywords: synthesis, nanoparticles, coated, cancer

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Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

Abstract:

In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

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