Search results for: fuzzy multiple objective programming

Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

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Authors: Alexander A. Tokmakov

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Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

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Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia

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This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.

Keywords: adaptive filtering, multi-rate processing, normalized subband adaptive filter, source separation

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Authors: Musse Mohamud Ahmed, Tina Linda Achilles, Mohammad Kamrul Hasan

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Deterioration of the mother nature is evident these day with clear danger of human catastrophe emanating from greenhouses (GHG) with increasing CO2 emissions to the environment. PV technology can help to reduce the dependency on fossil fuel, decreasing air pollution and slowing down the rate of global warming. The objective of this paper is to propose, develop and design the production of clean water supply to rural communities using an appropriate technology such as Internet of Things (IOT) that does not create any CO2 emissions. Additionally, maximization of solar energy power output and reciprocally minimizing the natural characteristics of solar sources intermittences during less presence of the sun itself is another goal to achieve in this work. The paper presents the development of critical automated control system for solar energy power output optimization using several new techniques. water pumping system is developed to supply clean water with the application of IOT-renewable energy. This system is effective to provide clean water supply to remote and off-grid areas using Photovoltaics (PV) technology that collects energy generated from the sunlight. The focus of this work is to design and develop a submersible solar water pumping system that applies an IOT implementation. Thus, this system has been executed and programmed using Arduino Software (IDE), proteus, Maltab and C++ programming language. The mechanism of this system is that it pumps water from water reservoir that is powered up by solar energy and clean water production was also incorporated using filtration system through the submersible solar water pumping system. The filtering system is an additional application platform which is intended to provide a clean water supply to any households in Sarawak State, Malaysia.

Keywords: IOT, automated production and control system, water filtration, automated submersible water pump, solar energy

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Authors: Abderrahmane Diaf, Kamel Benabdellaziz

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Remote arid areas of the vast expanses of the African deserts hold huge subterranean reserves of brackish water resources waiting for economic development. This work presents design guidelines as well as initial performance data of new autonomous solar desalination equipment which could help local communities produce their own fresh water using solar energy only and, why not, contribute to transforming desert lands into lush gardens. The output of solar distillation equipment is typically low and in the range of 3 l/m2/day on the average. This new design with an integrated, water-based, environmentally-friendly solar heat storage system produced 5 l/m2/day in early spring weather. Equipment output during summer exceeded 9 liters per m2 per day.

Keywords: multiple trough distillation, solar desalination, solar distillation with heat storage, water based heat storage system

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Authors: Doru Anastasiu Popescu, Raducanu Dragos Ionut

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In this paper the presentation of a tool which measures the similarity between two websites is made. The websites are compound only from webpages created with HTML. The tool uses three ways of calculating the similarity between two websites based on certain results already published. The first way compares all the webpages within a website, the second way compares a webpage with all the pages within the second website and the third way compares two webpages. Java programming language and technologies such as spring, Jsoup, log4j were used for the implementation of the tool.

Keywords: Java, Jsoup, HTM, spring

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Authors: Richard Colwell, Thomas Englert

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In cryogenic liquefaction processes, brazed aluminum core heat exchangers are used to minimize surface area/volume of the exchanger. Aluminum alloy (5083-H321; UNS A95083) piping must transition to higher melting point 304L stainless steel piping outside of the heat exchanger kettle or cold box for safety reasons. Since aluminum alloys and austenitic stainless steel cannot be directly welded to together, a transition joint consisting of 5 layers of different metals explosively bonded are used. Failures of two of these joints resulted in process shut-down and loss of revenue. Failure analyses, FEA analysis, and mock-up testing were performed by multiple teams to gain a further understanding into the failure mechanisms involved.

Keywords: explosion bonding, intermetallic compound, thermal strain, titanium-nickel Interface

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Authors: James M. Geidner

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Objective: The purpose of this meta-analysis was to examine the evidence for the effectiveness of exercise interventions on reducing metabolic components in children and/or adolescents diagnosed with Paediatric Metabolic Syndrome. Methods: A computerized search was made from four databases: PubMed, PsycInfo, SPORTDiscus, Cochrane Central Register. The analysis was restricted to children and adolescents with metabolic syndrome examining the effect of exercise interventions on metabolic components. Effect size and 95% confidence interval were calculated and the heterogeneity of the studies was estimated using Cochran’s Q-statistic and I2. Bias was assessed using multiple tools and statistical analyses. Results: Thirteen studies, consisting of 19 separate trials, were selected for the meta-analysis as they fulfilled the inclusion criteria (n=908). Exercise interventions resulted in decreased waist circumference, systolic blood pressure, diastolic blood pressure, fasting glucose, insulin resistance, triglycerides, and High-Density Lipoprotein Cholesterol (HDL-C). Conclusions: This meta-analysis provides insights into the effectiveness of exercise interventions on markers of Paediatric Metabolic Syndrome in children and adolescents.

Keywords: metabolic syndrome, syndrome x, pediatric, meta-analysis

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: Sadegh Sadeghi, Negar Shabani

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From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature thermodynamic cycles due to their suitable boiling characteristics. In this study, performance of a low-temperature Kalina cycle with R717/water working fluid used in different existing power plants is mathematically investigated. To analyze the behavior of the cycle, mass conservation, energy conservation, and exergy balance equations are presented. With regard to the similarity in molar mass of R717 (17.03 gr/mol) and water (18.01 gr/mol), there is no need to alter the size of Kalina system components such as turbine and pump. To optimize the cycle energy and exergy efficiencies simultaneously, a constrained multi-objective optimization is carried out applying an Artificial Bee Colony algorithm. The main motivation behind using this algorithm lies on its robustness, reliability, remarkable precision and high–speed convergence rate in dealing with complicated constrained multi-objective problems. Convergence rates of the algorithm for calculating the optimal energy and exergy efficiencies are presented. Subsequently, due to the importance of exergy concept in Kalina cycles, exergy destructions occurring in the components are computed. Finally, the impacts of pressure, temperature, mass fraction and mass flow rate on the energy and exergy efficiencies are elaborately studied.

Keywords: artificial bee colony algorithm, binary zeotropic mixture, constrained multi-objective optimization, energy efficiency, exergy efficiency, Kalina cycle

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Authors: Shih-Wen Hsiao, Yi-Cheng Tsao

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In the field of reverse engineering and creative industries, applying 3D scanning process to obtain geometric forms of the objects is a mature and common technique. For instance, organic objects such as faces and nonorganic objects such as products could be scanned to acquire the geometric information for further application. However, although the data resolution of 3D scanning device is increasing and there are more and more abundant complementary applications, the penetration rate of 3D scanning for the public is still limited by the relative high price of the devices. On the other hand, Kinect, released by Microsoft, is known for its powerful functions, considerably low price, and complete technology and database support. Therefore, related studies can be done with the applying of Kinect under acceptable cost and data precision. Due to the fact that Kinect utilizes optical mechanism to extracting depth information, limitations are found due to the reason of the straight path of the light. Thus, various angles are required sequentially to obtain the complete 3D information of the object when applying a single Kinect for 3D scanning. The integration process which combines the 3D data from different angles by certain algorithms is also required. This sequential scanning process costs much time and the complex integration process often encounter some technical problems. Therefore, this paper aimed to apply multiple Kinects simultaneously on the field of developing a rapid 3D mannequin scan platform and proposed suggestions on the number and angles of Kinects. In the content, a method of establishing the coordination based on the relation between mannequin and the specifications of Kinect is proposed, and a suggestion of angles and number of Kinects is also described. An experiment of applying multiple Kinect on the scanning of 3D mannequin is constructed by Microsoft API, and the results show that the time required for scanning and technical threshold can be reduced in the industries of fashion and garment design.

Keywords: 3D scan, depth sensor, fashion and garment design, mannequin, multiple Kinect sensor

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Authors: Kiurski S. Jelena, Aksentijević M. Snežana, Kecić S. Vesna, Oros B. Ivana

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The prosperity of electronic equipment in photocopying environment not only has improved work efficiency, but also has changed indoor air quality. Considering the number of photocopying employed, indoor air quality might be worse than in general office environments. Determining the contribution from any type of equipment to indoor air pollution is a complex matter. Non-methane hydrocarbons are known to have an important role of air quality due to their high reactivity. The presence of hazardous pollutants in indoor air has been detected in one photocopying shop in Novi Sad, Serbia. Air samples were collected and analyzed for five days, during 8-hr working time in three-time intervals, whereas three different sampling points were determined. Using multiple linear regression model and software package STATISTICA 10 the concentrations of occupational hazards and micro-climates parameters were mutually correlated. Based on the obtained multiple coefficients of determination (0.3751, 0.2389, and 0.1975), a weak positive correlation between the observed variables was determined. Small values of parameter F indicated that there was no statistically significant difference between the concentration levels of non-methane hydrocarbons and micro-climates parameters. The results showed that variable could be presented by the general regression model: y = b0 + b1xi1+ b2xi2. Obtained regression equations allow to measure the quantitative agreement between the variation of variables and thus obtain more accurate knowledge of their mutual relations.

Keywords: non-methane hydrocarbons, photocopying process, multiple regression analysis, indoor air quality, pollutant emission

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Authors: S. A. N. Danushka, T. A. Weerasinghe

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The diverse necessities of instruction could be addressed effectively with the support of new dimensions of ICT integrated learning such as blended learning –which is a combination of face-to-face and online instruction which ensures greater flexibility in student learning and congruity of course delivery. As blended learning has been the ‘new normality' in education, many experimental and quasi-experimental research studies provide ample of evidence on its successful implementation in many fields of studies, but it is hard to justify whether blended learning could work similarly in the delivery of technology-teacher development programmes (TTDPs). The present study is bound with the particular research uncertainty, and having considered existing research approaches, the study methodology was set to decide the efficient instructional strategies for flipped classroom learning in TTDPs. In a quasi-experimental pre-test and post-test design with a mix-method research approach, the major study objective was tested with two heterogeneous samples (N=135) identified in a virtual learning environment in a Sri Lankan university. Non-randomized informal ‘before-and-after without control group’ design was employed, and two data collection methods, identical pre-test and post-test and Likert-scale questionnaires were used in the study. Selected two instructional strategies, self-directed learning (SDL) and self-regulated learning (SRL), were tested in an appropriate instructional framework with two heterogeneous samples (pre-service and in-service teachers). Data were statistically analyzed, and an efficient instructional strategy was decided via t-test, ANOVA, ANCOVA. The effectiveness of the two instructional strategy implementation models was decided via multiple linear regression analysis. ANOVA (p < 0.05) shows that age, prior-educational qualifications, gender, and work-experiences do not impact on learning achievements of the two diverse groups of learners through the instructional strategy is changed. ANCOVA (p < 0.05) analysis shows that SDL is efficient for two diverse groups of technology-teachers than SRL. Multiple linear regression (p < 0.05) analysis shows that the staged self-directed learning (SSDL) model and four-phased model of motivated self-regulated learning (COPES Model) are efficient in the delivery of course content in flipped classroom learning.

Keywords: COPES model, flipped classroom learning, self-directed learning, self-regulated learning, SSDL model

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Authors: Sandeep Santosh, O. P. Sahu

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We simulate an efficient multiple wideband and nonstationary source localization algorithm by exploiting both the non-stationarity of the signals and the array geometric information.This algorithm is based on joint diagonalization structure (JDS) of a set of short time power spectrum matrices at different time instants of each frequency bin. JDS can be used for quick and accurate multiple non-stationary source localization. The JDS algorithm is a one stage process i.e it directly searches the Direction of arrivals (DOAs) over the continuous location parameter space. The JDS method requires that the number of sensors is not less than the number of sources. By observing the simulation results, one can conclude that the JDS method can localize two sources when their difference is not less than 7 degree but the Wideband MUSIC is able to localize two sources for difference of 18 degree.

Keywords: joint diagonalization structure (JDS), wideband direction of arrival (DOA), wideband MUSIC

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Authors: Leonid Borisov, Yuri Orlov

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We obtain explicit formulas of finitely multiple approximations of the equilibrium density matrix for the case of the harmonic oscillator using Chernoff's theorem and the notion of semigroup which is Chernoff equivalent to average semigroup. Also we found explicit formulas for the corresponding approximate Wigner functions and average values of the observable. We consider a superposition of τ -quantizations representing a wide class of linear quantizations. We show that the convergence of the approximations of the average values of the observable is not uniform with respect to the Gibbs parameter. This does not allow to represent approximate expression as the sum of the exact limits and small deviations evenly throughout the temperature range with a given order of approximation.

Keywords: Chernoff theorem, Feynman formulas, finitely multiple approximation, harmonic oscillator, Wigner function

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Authors: Jordan Georgiev Deliversky

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Fight against migrant smuggling has been put as a priority issues at the European Union policy agenda for more than a decade. The trafficked person, who has been targeted as the object of criminal exploitation, is specifically unique for human trafficking. Generally, the beginning of human trafficking activities is related to profit from the victim’s exploitation. The objective of this paper is to present measures that could result in the limitation of corruption mainly through analyzing the existing legislation framework against corruption in Europe. The analysis is focused on exploring the multiple origins of factors influencing migration processes in Europe, as corruption could be characterized as one of the most significant reasons for refugees to flee their countries. The main results show that law enforcement must turn the focus on the financing of the organized crime groups that are involved in migrant smuggling activities. Corruption has a significant role in managing smuggling operations and in particular when criminal organizations and networks are involved. Illegal migrants and refugees usually represent significant sources of additional income for officials involved in the process of boarding protection and immigration control within the European Union borders.

Keywords: corruption, influence, human smuggling, legislation, migration

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Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

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Authors: Anne Schattel, Mitja Echim, Christof Büskens

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Trajectory planning for deep space missions has become a recent topic of great interest. Flying to space objects like asteroids provides two main challenges. One is to find rare earth elements, the other to gain scientific knowledge of the origin of the world. Due to the enormous spatial distances such explorer missions have to be performed unmanned and autonomously. The mathematical field of optimization and optimal control can be used to realize autonomous missions while protecting recourses and making them safer. The resulting algorithms may be applied to other, earth-bound applications like e.g. deep sea navigation and autonomous driving as well. The project KaNaRiA ('Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All') investigates the possibilities of cognitive autonomous navigation on the example of an asteroid mining mission, including the cruise phase and approach as well as the asteroid rendezvous, landing and surface exploration. To verify and test all methods an interactive, real-time capable simulation using virtual reality is developed under KaNaRiA. This paper focuses on the specific challenge of the guidance during the cruise phase of the spacecraft, i.e. trajectory optimization and optimal control, including first solutions and results. In principle there exist two ways to solve optimal control problems (OCPs), the so called indirect and direct methods. The indirect methods are being studied since several decades and their usage needs advanced skills regarding optimal control theory. The main idea of direct approaches, also known as transcription techniques, is to transform the infinite-dimensional OCP into a finite-dimensional non-linear optimization problem (NLP) via discretization of states and controls. These direct methods are applied in this paper. The resulting high dimensional NLP with constraints can be solved efficiently by special NLP methods, e.g. sequential quadratic programming (SQP) or interior point methods (IP). The movement of the spacecraft due to gravitational influences of the sun and other planets, as well as the thrust commands, is described through ordinary differential equations (ODEs). The competitive mission aims like short flight times and low energy consumption are considered by using a multi-criteria objective function. The resulting non-linear high-dimensional optimization problems are solved by using the software package WORHP ('We Optimize Really Huge Problems'), a software routine combining SQP at an outer level and IP to solve underlying quadratic subproblems. An application-adapted model of impulsive thrusting, as well as a model of an electrically powered spacecraft propulsion system, is introduced. Different priorities and possibilities of a space mission regarding energy cost and flight time duration are investigated by choosing different weighting factors for the multi-criteria objective function. Varying mission trajectories are analyzed and compared, both aiming at different destination asteroids and using different propulsion systems. For the transcription, the robust method of full discretization is used. The results strengthen the need for trajectory optimization as a foundation for autonomous decision making during deep space missions. Simultaneously they show the enormous increase in possibilities for flight maneuvers by being able to consider different and opposite mission objectives.

Keywords: deep space navigation, guidance, multi-objective, non-linear optimization, optimal control, trajectory planning.

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Authors: Abhishek N. Srivastava, Rahul Singh, Sumedha Chakma

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The rapid urbanization in the developing countries is generating an enormous amount of waste leading to the creation of unregulated landfill sites at various places at its disposal. The liquid waste, known as leachate, produced from these landfills sites is severely affecting the surrounding water quality. The water quality in the proximity areas of the landfill is found affected by various physico-chemical parameters of leachate such as pH, alkalinity, total hardness, conductivity, chloride, total dissolved solids (TDS), total suspended solids (TSS), sulphate, nitrate, phosphate, fluoride, sodium and potassium, biological parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), Faecal coliform, and heavy metals such as cadmium (Cd), lead (Pb), iron (Fe), mercury (Hg), arsenic (As), cobalt (Co), manganese (Mn), zinc (Zn), copper (Cu), chromium (Cr), nickel (Ni). However, all these parameters are distributive in leachate that produced according to the nature of waste being dumped at various landfill sites, therefore, it becomes very difficult to predict the main responsible parameter of leachate for water quality contamination. The present study is endeavour the comparative analysis of the physical, chemical and biological parameters of various landfills in India viz. Okhla landfill, Ghazipur landfill, Bhalswa ladfill in NCR Delhi, Deonar landfill in Mumbai, Dhapa landfill in Kolkata and Kodungayaiyur landfill, Perungudi landfill in Chennai. The statistical analysis of the parameters was carried out using the Statistical Packages for the Social Sciences (SPSS) and LandSim 2.5 model to simulate the long term effect of various parameters on different time scale. Further, the uncertainties characterization of various input parameters has also been analysed using fuzzy alpha cut (FAC) technique to check the sensitivity of various water quality parameters at the proximity of numerous landfill sites. Finally, the study would help to suggest the best method for the prevention of pollution migration from the landfill sites on priority basis.

Keywords: landfill leachate, water quality, LandSim, fuzzy alpha cut

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Authors: Zhu-Qing Jia, Tao Lin, Tong Zhou

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The recognition method of Optical Character Recognition has been expensively utilized, while it is rare to be employed specifically in recognition of electronic components. This paper suggests a high-effective algorithm on appearance identification of integrated circuit components based on the existing methods of character recognition, and analyze the pros and cons.

Keywords: optical character recognition, fuzzy page identification, mutual correlation matrix, confidence self-adaptation

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Authors: Ebitisam K. Elberkawi, Mohamed M. Elammari

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Graphical User Interface (GUI) is essential to programming, as is any other characteristic or feature, due to the fact that GUI components provide the fundamental interaction between the user and the program. Thus, we must give more interest to GUI during building and development of systems. Also, we must give a greater attention to the user who is the basic corner in the dealing with the GUI. This paper introduces an approach for designing GUI from one of the models of business workflows which describe the workflow behavior of a system, specifically through activity diagrams (AD).

Keywords: activity diagram, graphical user interface, GUI components, program

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Authors: Roberto Cerchione, Emilio Esposito, Mario Raffa

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The relevance and the strategic importance of engineering skills in innovation and in the development of businesses and organizations push to investigate the role of the engineer in society today. In the twentieth century the emergence of a variety of technical and scientific knowledge has led to the rise of new areas of skills going from a "all-comprehensive" engineering to an engineering characterized by many specializations. Organizational and structural changes within companies and the emergence of an industrial society based on multiple interrelationships led to the transformation of engineering education. The objective of this work is to report main steps and many pioneering experiences, both national and international, that have led to establish a graduate degree program in Engineering Management and its subsequent evolution in Entrepreneurial Engineering. The first section of this article focuses on the origins and precursors of Engineering Management education. The second section concerns main Italian education programs. Then the attention is focused on the evolution of Engineering Management in Naples, on the intersectoral nature of this degree program, on the relationship with business community, associations, labor market, small businesses and environment. Finally, the discussion of recent years about the skills that characterize entrepreneurial engineer in society are presented.

Keywords: education, engineering management, entrepreunerial engineering, engineering skills, managerial skills, entrepreneurial skills

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Authors: Kostas Metaxiotis

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Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: evolutionary algorithms, portfolio optimization, skewness, stock selection

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Authors: Rafael Ricieri, Rogerio Barros, Francisco Clovis

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Objective– The Objective of this is study is to report a rare case of dermoid cyst, with a sublingual location and cutaneous fistula in a 4 year-old child.Methods: This study is a case report. The main study instrument was the medical record and the radiological and intraoperative image bank. Results: Infants with congenital cervical lesions eventually need tomography for diagnostic elucidation, and health services should be structured to perform sedation and thin tomographic sections in order to reduce morbidity.

Keywords: congenital, sublingual dermoid cyst, fistula, pediatric surgery, head and kneck surgery

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Authors: Kim Kennedy, Daren Gibson, Stephanie Flukes, Chandra Diwakarla, Lisa Spalding, Leanne Pilkington, Andrew Redfern

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Introduction: It is well known that patients with Head and Neck Cancer (HNC) are at increased risk of subsequent head and neck cancers due to various aetiologies. Aim: We sought to determine the factors contributing to an increased risk of subsequent HNC primaries, and also to evaluate whether Aboriginal patients are at increased risk. Methods: We performed a retrospective cohort analysis of 320 HNC patients from a single centre in Western Australia, identifying 80 Aboriginal patients and 240 non-Aboriginal patients matched on a 1:3 ratio by site, histology, rurality, and age. We collected patient data including smoking and alcohol consumption, tumour and treatment data, and data on subsequent HNC primaries. Results: A subsequent HNC primary was seen in 37 patients (11.6%) overall. There was no significant difference in the rate of second primary HNCs between Aboriginal patients (12.5%) and nonAboriginal patients (11.2%) (p=0.408). Subsequent HNCs, were strongly associated with smoking and alcohol consumption however, with 95% of patients with a second primary being ever-smokers, and 54% of patients with a second primary having a history of excessive alcohol consumption. In the 37 patients with multiple HNC primaries, there were a total of 57 HNCs, with 29 patients having two primaries, six patients having 3 HNC primaries, one patient with four, and one with six. 54 out of the 57 cancers were in ever smokers (94.7%). There were only two multiple HNC primaries in a never smoker, non-drinker, and these cases were of unknown etiology with HPV/p16 status unknown in both cases. In the whole study population, there were 32 HPV-positive HNCs, and 67 p16-positive HNCs, with only two 2 nd HNCs in a p16-positive case, giving a rate of 3% in the p16+ population, which is actually much lower than the rate of second primaries seen in the overall population (11.6%), and was highest in the p16-negative population (15.7%). This suggests that p16-positivity is not a strong risk factor for subsequent primaries, and in fact p16-negativity appeared to be associated with increased risk, however this data is limited by the large number of patients without documented p16 status (45.3% overall, 12% for oropharyngeal, and 59.6% for oral cavity primaries had unknown p16 status). Summary: Subsequent HNC primaries were strongly associated with smoking and alcohol excess. Second and later HNC primaries did not appear to occur at increased rates in Aboriginal patients compared with non-Aboriginal patients, and p16-positivity did not predict increased risk, however p16-negativity was associated with an increased risk of subsequent HNCs.

Keywords: head and neck cancer, multiple primaries, aboriginal, p16 status, smoking, alcohol

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Authors: Nicholas Abdilmasih, Habib Rezanejad

Abstract:

This study investigates the gene expression induction efficiency of single versus multiple guide RNAs (gRNAs) targeting the NGN3 gene using the CRISPR activation system in HEK293 cells. Our study aimed to contribute to optimizing the use of gRNAs in gene therapy applications, particularly in treating diseases like diabetes, where precise gene regulation is essential. The experimental design involves culturing HEK293 cells, and once they reach approximately 70-80% confluence, cells were transfected with specific gRNAs targeting the NGN3 gene promoter. Specific gRNAs targeting the NGN3 promoter that was previously designed, incorporated into plasmid clone cassettes and introduced into HEK293 cells through co-transfection using pCAG-DDdCas9-VP192-EGFP transactivator. Post-transfection, cell viability, and fluorescence were monitored to assess transfection efficiency. RNA was extracted, converted to cDNA, and analyzed via qPCR to measure NGN3 expression levels. Results indicated that specific combinations of fewer gRNAs led to higher NGN3 activation compared to multiple gRNAs, challenging the assumption that more gRNAs result in synergistic gene activation. These findings suggest that optimized gRNA combinations can enhance gene therapy efficiency, potentially leading to more effective treatments for conditions like diabetes.

Keywords: CRISPR activation, Diabetes mellitus, gene therapy, guide RNA, Neurogenin3

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Authors: Younis Jabarzadeh, Rahim Sarvari, Negar Ahmadi Alghalandis

Abstract:

Entrepreneurship at both individual and organizational level is one of the most driving forces in economic development and leads to growth and competition, job generation and social development. Especially in developing countries, the role of entrepreneurship in economic and social prosperity is more emphasized. But the effect of global economic development on the environment is undeniable, especially in negative ways, and there is a need to rethink current business models and the way entrepreneurs act to introduce new businesses to address and embed environmental issues in order to achieve sustainable development. In this paper, green or sustainable entrepreneurship is addressed in Iran to identify challenges and barriers entrepreneurs in the economic and social sectors face in developing green business solutions. Sustainable or green entrepreneurship has been gaining interest among scholars in recent years and addressing its challenges and barriers need much more attention to fill the gap in the literature and facilitate the way those entrepreneurs are pursuing. This research comprised of two main phases: qualitative and quantitative. At qualitative phase, after a thorough literature review, fuzzy Delphi method is utilized to verify those challenges and barriers by gathering a panel of experts and surveying them. In this phase, several other contextually related factors were added to the list of identified barriers and challenges mentioned in the literature. Then, at the quantitative phase, Interpretive Structural Modeling is applied to construct a network of interactions among those barriers identified at the previous phase. Again, a panel of subject matter experts comprised of academic and industry experts was surveyed. The results of this study can be used by policymakers in both the public and industry sector, to introduce more systematic solutions to eliminate those barriers and help entrepreneurs overcome challenges of sustainable entrepreneurship. It also contributes to the literature as the first research in this type which deals with the barriers of sustainable entrepreneurship and explores their interaction.

Keywords: green entrepreneurship, barriers, fuzzy Delphi method, interpretive structural modeling

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Authors: Zainab S. Mahmood, Aisha H. Hashim, Wan Haslina Hassan, Farhat Anwar

Abstract:

The wide use of the internet-based applications bring many challenges to the researchers to guarantee the continuity of the connections needed by the mobile hosts and provide reliable Internet access for them. One of proposed solutions by Internet Engineering Task Force (IETF) is to connect the local, multi-hop, and infrastructure-less Mobile Ad hoc Network (MANET) with Internet structure. This connection is done through multi-interface devices known as Internet Gateways. Many issues are related to this connection like gateway discovery, hand off, address auto-configuration and selecting the optimum gateway when multiple gateways exist. Many studies were done proposing gateway selection schemes with a single selection criterion or weighted multiple criteria. In this research, a review of some of these schemes is done showing the differences, the features, the challenges and the drawbacks of each of them.

Keywords: Internet Gateway, MANET, mobility, selection criteria

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Authors: Musthaya Patchanee

Abstract:

This research aimed to study form of traffic distribution and environmental factors of road that affect traffic accidents in Dusit District, only areas responsible of Samsen Police Station. Data used in this analysis is the secondary data of traffic accident case from year 2011. Observed area units are 15 traffic lines that are under responsible of Samsen Police Station. Technique and method used are the Cartographic Method, the Correlation Analysis, and the Multiple Regression Analysis. The results of form of traffic accidents show that, the Samsen Road area had most traffic accidents (24.29%), second was Rachvithi Road (18.10%), third was Sukhothai Road (15.71%), fourth was Rachasrima Road (12.38%), and fifth was Amnuaysongkram Road (7.62%). The result from Dusit District, only areas responsible of Samsen police station, has suggested that the scale of accidents have high positive correlation with statistic significant at level 0.05 and the frequency of travel (r=0.857). Traffic intersection point (r=0.763)and traffic control equipments (r=0.713) are relevant factors respectively. By using the Multiple Regression Analysis, travel frequency is the only one that has considerable influences on traffic accidents in Dusit district only Samsen Police Station area. Also, a factor in frequency of travel can explain the change in traffic accidents scale to 73.40 (R2 = 0.734). By using the Multiple regression summation from analysis was Y ̂=-7.977+0.044X6.

Keywords: form of traffic distribution, environmental factors of road, traffic accidents, Dusit district

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Authors: Espinosa-Garza G., Loera-Hernandez I., Antonyan N.

Abstract:

To innovate, it is necessary to perform projects directed towards the search of improvement. The agricultural technique and the design of greenhouses have been studied by undergraduate engineering students from the Tecnológico de Monterrey using the campus areas. The purpose of this project was to incite students to create innovations and help rural populations of the state to solve one of the problems that they are dealing with nowadays. The main objective of the project was to search for an alternative technique that will allow the planting of the “chile piquín” plant, also known as Capsicum annuum, to grow quicker as it germinates. The “chile piquín” is one of the original crops of Mexico and forms the basis of the Mesoamerican cultures’ diet since the pre-hispanic era. To fulfill with today’s demand, it is required to implement new alternative methods to increase the “chile piquín’s” growth. The project lasted one semester with the participation of engineering students from multiple majors. The most important results from this academic experience were that, from the proposed goal, the students could analyze the needs of their town and were capable of introducing new and innovative ideas with the aim of resolving them. In the present article the pedagogic methodologies that allowed to carry out this project will be discussed.

Keywords: academic experience, chile piquín, engineering education, greenhouse design, innovation

Procedia PDF Downloads 150