Search results for: grasshopper optimization algorithm

Authors: Edlira Donefski, Tina Donefski, Lorenc Ekonomi

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Edgeworth Approximation, Bootstrap, and Monte Carlo Simulations have considerable impacts on achieving certain results related to different problems taken into study. In our paper, we have treated a financial case related to the effect that has the components of a cash-flow of one of the most successful businesses in the world, as the financial activity, operational activity, and investment activity to the cash and cash equivalents at the end of the three-months period. To have a better view of this case, we have created a vector autoregression model, and after that, we have generated the impulse responses in the terms of asymptotic analysis (Edgeworth Approximation), Monte Carlo Simulations, and residual bootstrap based on the standard errors of every series created. The generated results consisted of the common tendencies for the three methods applied that consequently verified the advantage of the three methods in the optimization of the model that contains many variants.

Keywords: autoregression, bootstrap, edgeworth expansion, Monte Carlo method

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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: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

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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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Authors: G. R. Kavitha, T. S. Indumathi

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With the constantly rising demands of the multimedia services, the requirements of long haul transport network are constantly changing in the area of optical network. Maximum data transmission using optimization of the communication channel poses the biggest challenge. Although there has been a constant focus on this area from the past decade, there was no evidence of a significant result that has been accomplished. Hence, after reviewing some potential design of optical network from literatures, it was understood that optical signal to noise ratio was one of the elementary attributes that can define the performance of the optical network. In this paper, we propose a framework termed as ECON (Enhanced Constraint-based Optical Network) that primarily optimize the optical signal to noise ratio using ROADM. The simulation is performed in Matlab and optical signal to noise ratio is extracted considering the system matrix. The outcome of the proposed study shows that optimized OSNR as compared to the existing studies.

Keywords: component, optical network, reconfigurable optical add-drop multiplexer, optical signal-to-noise ratio

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Authors: S. Jurado, E. Pazmino

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Determination of the medial axis of a porous media sample is a non-trivial problem of interest for several disciplines, e.g., hydrology, fluid dynamics, contaminant transport, filtration, oil extraction, etc. However, the computational tools available for researchers are limited and restricted. The primary aim of this work was to develop a series of algorithms to extract porosity, medial axis structure, and pore-throat size distributions from porous media domains. A complementary objective was to provide the algorithms as free computational software available to the academic community comprising researchers and students interested in 3D data processing. The burn algorithm was tested on porous media data obtained from High-Resolution X-Ray Microtomography (HRXMT) and idealized computer-generated domains. The real data and idealized domains were discretized in voxels domains of 550³ elements and binarized to denote solid and void regions to determine porosity. Subsequently, the algorithm identifies the layer of void voxels next to the solid boundaries. An iterative process removes or 'burns' void voxels in sequence of layer by layer until all the void space is characterized. Multiples strategies were tested to optimize the execution time and use of computer memory, i.e., segmentation of the overall domain in subdomains, vectorization of operations, and extraction of single burn layer data during the iterative process. The medial axis determination was conducted identifying regions where burnt layers collide. The final medial axis structure was refined to avoid concave-grain effects and utilized to determine the pore throat size distribution. A graphic user interface software was developed to encompass all these algorithms, including the generation of idealized porous media domains. The software allows input of HRXMT data to calculate porosity, medial axis, and pore-throat size distribution and provide output in tabular and graphical formats. Preliminary tests of the software developed during this study achieved medial axis, pore-throat size distribution and porosity determination of 100³, 320³ and 550³ voxel porous media domains in 2, 22, and 45 minutes, respectively in a personal computer (Intel i7 processor, 16Gb RAM). These results indicate that the software is a practical and accessible tool in postprocessing HRXMT data for the academic community.

Keywords: medial axis, pore-throat distribution, porosity, porous media

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Authors: Ghorbanali Mohammadi

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New approaches to sequencing mixed-model manufacturing systems are present. These approaches have attracted considerable attention due to their potential to deal with difficult optimization problems. This paper presents Multi-Objective Simulated Annealing Algorithms (MOSAA) approaches to the Just-In-Time (JIT) sequencing problem where workload-smoothing (WL) and the number of set-ups (St) are to be optimized simultaneously. Mixed-model assembly lines are types of production lines where varieties of product models similar in product characteristics are assembled. Moreover, this type of problem is NP-hard. Two annealing methods are proposed to solve the multi-objective problem and find an efficient frontier of all design configurations. The performances of the two methods are tested on several problems from the literature. Experimentation demonstrates the relative desirable performance of the presented methodology.

Keywords: scheduling, just-in-time, mixed-model assembly line, sequencing, simulated annealing

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Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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Authors: Zaid Almahmoud, Rana Mahmoud

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To mitigate the environmental impacts of throwing away plastic waste, there has been a recent interest in manufacturing and producing biodegradable plastics. Here, we study a new class of biodegradable plastics which are mixed with external natural additives, including catalytic additives that lead to a successful degradation of the resulting material. To recommend the best alternative among multiple materials, we propose a multi-objective AI model that evaluates the material against multiple objectives given the material properties. As a proof of concept, the AI model was implemented in an expert system and evaluated using multiple materials. Our findings showed that Polyethylene Terephalate is potentially the best biodegradable plastic substitute based on its material properties. Therefore, it is recommended that governments shift the attention to the use of Polyethylene Terephalate in the manufacturing of bottles to gain a great environmental and sustainable benefits.

Keywords: plastic bottles, expert systems, multi-objective model, biodegradable substitutes

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Authors: Mohammad H. Fattahi

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Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. The noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: chaotic behavior, wavelet, noise reduction, river flow

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Authors: Mok-Tan Ahn, Hyeok Choi, Joon-Hong 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 factor influencing the productivity and moldability of the product. The number and shape of the multi-path in the mold of the drawing process is very influencing the productivity and moldability 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. The purpose of this study, Analyzing the load on the die through the FEM analysis and in consideration of the formability of the material presents a die model.

Keywords: automotive reinforcing agent, multi-pass shape drawing, automotive parts, FEM analysis

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Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Raj Kumari Bahl, Sotirios Sabanis

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In this paper, we are concerned with the valuation of the first Catastrophic Mortality Bond that was launched in the market namely the Swiss Re Mortality Bond 2003. This bond encapsulates the behavior of a well-defined mortality index to generate payoffs for the bondholders. Pricing this bond is a challenging task. We adapt the payoff of the terminal principal of the bond in terms of the payoff of an Asian put option and present an approach to derive model-independent bounds exploiting comonotonic theory. We invoke Jensen’s inequality for the computation of lower bounds and employ Lagrange optimization technique to achieve the upper bound. The success of these bounds is based on the availability of compatible European mortality options in the market. We carry out Monte Carlo simulations to estimate the bond price and illustrate the strength of these bounds across a variety of models. The fact that our bounds are model-independent is a crucial breakthrough in the pricing of catastrophic mortality bonds.

Keywords: mortality bond, Swiss Re Bond, mortality index, comonotonicity

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Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

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Authors: Mohamed Elbehery

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Historical textiles in the burial environment or in museums are exposed to many types of stains and dirt that are associated with historical textiles by multiple chemical bonds that cause damage to historical textiles. The cleaning process must be carried out with great care, with no irreversible damage, and sediments removed without affecting the original material of the surface being cleaned. Science and technology continue to provide innovative systems in the bio-cleaning process (using pure enzymes) of historical textiles and artistic surfaces. Lipase and α-amylase were immobilized on nanoparticles of alginate/κ-carrageenan nanoparticle complex and used in historical textiles cleaning. Preparation of nanoparticles, activation, and enzymes immobilization were characterized. Optimization of loading time and units of the two enzymes were done. It was found that, the optimum time and units of amylase were 4 hrs and 25U, respectively. While, the optimum time and units of lipase were 3 hrs and 15U, respectively. The methods used to examine the fibers using a scanning electron microscope equipped with an X-ray energy dispersal unit: SEM with EDX unit.

Keywords: nanoparticles, enzymes, immobilization, textiles

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Authors: Victor Emeli, Akansel Cosgun

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This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).

Keywords: motion planning, path planning, push planning, robot navigation

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Authors: M. Khouil, N. Saber, M. Mestari

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This study aimed to propose, a different architecture of a Path Planning using the NECMOP. where several nonlinear objective functions must be optimized in a conflicting situation. The ability to detect and avoid collision is very important for mobile intelligent machines. However, many artificial vision systems are not yet able to quickly and cheaply extract the wealth information. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons linear and threshold logic, which simplified the actual implementation of all the networks proposed. This article represents a comprehensive algorithm that determine through the AMAXNET network a measure (a mini-maximum point) in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: path planning, collision detection, convex polyhedron, neural network

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Authors: Neetesh Saxena, Narendra S. Chaudhari

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Nowadays, SMS is a very popular mobile service and even the poor, illiterate people and those living in rural areas use SMS service very efficiently. Although many mobile operators have already started 3G and 4G services, 2G services are still being used by the people in many countries. In 2G (GSM), only encryption provided is between the MS and the BTS, there is no end-to-end encryption available. Sometimes we all need to send some confidential message to other person containing bank account number, some password, financial details, etc. Normally, a message is sent in plain text only to the recipient and it is not an acceptable standard for transmitting such important and confidential information. Authors propose an end-to-end encryption approach by proposing a terminal for sending/receiving a secure message. An asymmetric key exchange algorithm is used in order to transmit secret shared key securely to the recipient. The proposed approach with terminal device provides authentication, confidentiality, integrity and non-repudiation.

Keywords: AES, DES, Diffie-Hellman, ECDH, A5, SMS

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Authors: G. Khasaev, S. Ashmarina , A. Zotova

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The priority of Russian enterprises development has been given to the optimization process of industrial enterprise activity for their sustainable development in a long-term period. The assessment of sustainable development level as one of the most efficient instruments of sustainable development management at the industrial enterprise gives a complex view of its state. In order to perform accurate analysis of the current state of the industrial enterprise, it is necessary to perform the assessment of its sustainable development and using its results to elaborate the further tactic of enterprise functioning. The assessment of sustainable development level of the enterprise may help the effective management of strategy development only if the corresponding indicators system is created. The elaboration and usage the sustainable development indicators allows the enterprise to implement analysis of its activity results and monitoring of sustainable enterprise functioning. The authors’ methods are based on general aspects of the industrial enterprise functioning such as finance, customers, inner economic process, and staff system.

Keywords: assessment methods, indicators system, industrial enterprise, sustainable development

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Authors: Stephane Maingard, Babu Paturi, Maura Daly, Finnola Armstrong

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Background: Perinatal optimization involves the implementation of twelve intervention bundles of care at Our Lady of Lourdes Hospital, reliably delivering evidence-based interventions in the antenatal, intrapartum, and neonatal period to improve preterm outcomes. These key interventions (e.g. Antenatal steroids, Antenatal counselling, Optimal cord management, Respiratory management etc.) are based on WHO (World Health Organization, BAPM (British Association of Perinatal Medicine), and the latest 2022 European Consensus guidelines recommendations. Methodology: In February 2023, a quality improvement project team (pediatricians, neonatologists, obstetricians, clinical skills managers) was established, and a project implementation plan was developed. The Program Study Act implemented the following: 1. Antenatal consultation pathway, 2. Creation and implementation of a perinatal checklist for preterm births less than 34 weeks of gestation, 3. Process changes to ensure the checklist is completed, 4. Completion of parent and staff surveys, 5. Ongoing training. We collected and compared a range of data before and after implementation. Results: Preliminary analysis so far at 1 month demonstrates improvement in the following areas: 50% increase in antenatal counselling. Right place of birth increased from 85% to 100%. Magnesium sulphate increased from 56% to 100%. No change was observed in buccal colostrum administration (28%), delayed cord clamping (75%), caffeine administration (100%), blood glucose level at one hour of life > 2,6mmol (85%). There was also no change noted in respiratory support at resuscitation, CPAP only (47%), IPPV with CPAP (45%), IPPV with intubation (20%), and surfactant administration (28%). A slight decrease in figures was noted in the following: steroid administration from 80% to 75% and thermal care obtaining optimal temperature on admission (65% to 50%). Discussion: Even though the findings are preliminary, the directional improvement shows promise. Improved communication has been achieved between all stakeholders, including our patients, who are key team members. Adherence to the bundles of care will help to improve survival and neurodevelopmental outcomes as well as reduce the length of stay, thereby overall reducing the financial cost, considering the lifetime cost of cerebral palsy is estimated at €800,000 and reducing the length of stay can result in savings of up to €206,000. Conclusion: Preliminary results demonstrate improvements across a range of patient, process, staff, and financial outcomes. Our future goal is a seamless pathway of patient centered care for babies and their families. This project is an interdisciplinary collaboration to implement best practices for a vulnerable patient cohort. Our two main challenges are changing our organization’s culture as well as ensuring the sustainability of the project.

Keywords: perinatal, optimization, antenatal, counselling, IPPV

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Authors: Yeshona Sewsynker

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This study presents three microwave-assisted alkalic salt pretreatments to enhance delignification and enzymatic saccharification of corn cobs. The effects of process parameters of salt concentration (0-15%), microwave power intensity (0-800 W) and pretreatment time (2-8 min) on reducing sugar yield from corn cobs were investigated. Pretreatment models were developed with the high coefficient of determination values (R2>0.85). Optimization gave a maximum reducing sugar yield of 0.76 g/g. Scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR) showed major changes in the lignocellulosic structure after pretreatment. A 7-fold increase in the sugar yield was observed compared to previous reports on the same substrate. The developed pretreatment strategy was effective for enhancing enzymatic saccharification from lignocellulosic wastes for microbial biofuel production processes and value-added products.

Keywords: pretreatment, lignocellulosic biomass, enzymatic hydrolysis, delignification

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Authors: Mafel Obhuo, Dodeye I. Igbong, Duabari S. Aziaka, Pericles Pilidis

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An important feature of the exploitation of associated gas as fuel for gas turbine engines is a declining supply. So when exploiting this resource, the divestment of prime movers is very important as the fuel supply diminishes with time. This paper explores the influence of engine degradation on the timing of divestments. Hypothetical but realistic gas turbine engines were modelled with Turbomatch, the Cranfield University gas turbine performance simulation tool. The results were deployed in three degradation scenarios within the TERA (Techno-economic and environmental risk analysis) framework to develop economic models. An optimisation with Genetic Algorithms was carried out to maximize the economic benefit. The results show that degradation will have a significant impact. It will delay the divestment of power plants, while they are running less efficiently. Over a 20 year investment, a decrease of $0.11bn, $0.26bn and $0.45bn (billion US dollars) were observed for the three degradation scenarios as against the clean case.

Keywords: economic return, flared associated gas, net present value, optimization

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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Authors: F. G Okibe, C. E Gimba, V. O Ajibola, I. G Ndukwe, E. D. Paul

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A full factorial experimental design technique at two levels and four factors (24) was used to optimize the adsorption at 615 nm of Xylene Cyanol ff in aqueous solutions onto activated carbon prepared from brachystegia eurycoma seed hulls by chemical carbonization method. The effect of pH (3 and 5), initial dye concentration (20 and 60 mg/l), adsorbent dosage (0.01 and 0.05 g), and contact time (30 and 60 min) on removal efficiency of the adsorbent for the dye were investigated at 298K. From the analysis of variance, response surface and cube plot, adsorbent dosage was observed to be the most significant factor affecting the adsorption process. However, from the interaction between the variables studied, the optimum removal efficiency was 96.80 % achieved with adsorbent dosage of 0.05 g, contact time 45 minutes, pH 3, and initial dye concentration 60 mg/l.

Keywords: factorial experimental design, adsorption, optimization, brachystegia eurycoma, xylene cyanol ff

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Authors: N. Arslanoglu

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This paper deals with the optimum tilt angle for the solar collector in order to collect the maximum solar radiation. The optimum angle for tilted surfaces varying from 0^◦ to 90^◦ in steps of 1^◦ was computed. In present study, a theoretical model is used to predict the global solar radiation on a tilted surface and to obtain the optimum tilt angle for a solar collector in Bursa, Turkey. Global solar energy radiation on the solar collector surface with an optimum tilt angle is calculated for specific periods. It is determined that the optimum slope angle varies between 0^◦ (June) and 59^◦ (December) throughout the year. In winter (December, January, and February) the tilt should be 55^◦, in spring (March, April, and May) 19.6^◦, in summer (June, July, and August) 5.6^◦, and in autumn (September, October, and November) 44.3^◦. The yearly average of this value was obtained to be 31.1^◦ and this would be the optimum fixed slope throughout the year.

Keywords: Bursa, global solar radiation, optimum tilt angle, tilted surface

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Authors: Lihua Zhu, Jianfeng Du, Yu Wang, Zhiqiang Wu

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Collision avoidance problems of a swarm of unmanned air vehicles (UAVs) flying in an obstacle-laden environment are investigated in this paper. Given that the UAV swarm needs to adapt to the obstacle distribution in dynamic operation, a priority configuration is designed to guide the UAVs to pass through the obstacles in turn. Based on the collision cone approach and the prediction of the collision time, a collision evaluation model is established to judge the urgency of the imminent collision of each UAV, and the evaluation result is used to assign the priority of each UAV to further instruct them going through the obstacles in descending order. At last, the simulation results provide the promising validation in terms of the efficiency and scalability of the proposed approach.

Keywords: UAV swarm, collision avoidance, complex environment, online priority design

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Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

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In this paper, we propose a new encryption system for security issues medical images. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity, and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every new session of encryption, that will be used to encrypt each frame of the medical image basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, medical images, encryption, decryption, key, correlation

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Authors: Carla E. O. de Moraes, Gladson O. Antunes, Mauro A. Rincon

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The aim of this paper is to study the internal stabilization of the Bernoulli-Euler equation numerically. For this, we consider a square plate subjected to a feedback/damping force distributed only in a subdomain. An algorithm for obtaining an approximate solution to this problem was proposed and implemented. The numerical method used was the Finite Difference Method. Numerical simulations were performed and showed the behavior of the solution, confirming the theoretical results that have already been proved in the literature. In addition, we studied the validation of the numerical scheme proposed, followed by an analysis of the numerical error; and we conducted a study on the decay of the energy associated.

Keywords: Bernoulli-Euler plate equation, numerical simulations, stability, energy decay, finite difference method

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Authors: Fatemeh Jaferi, Moslem Parsa, Seyed Mehdi Sajadi

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The project-oriented organizations are more appropriate for sustainable environments. Any effective project-oriented organization should institutionalize its project management processes in such a manner to yield the greatest possible profits. The aim of this paper is to study the relationship between the project management PMBOK guideline (Project Management Body of Knowledge) and simulation technology in project-oriented organizations. The methodology involves using five steps for applying these two tools aimed at enhancing project management processes in the Lorestan Gas Corporation, as one of the project-oriented organization. Results show the implementation of such management approach leads to a 5% performance improvement and using PMBOK can be instrumental in effective delay management. The implementation of the aforementioned improvement package was effective in improving the efficiency of organizational processes; in terms of optimizing the resource utilization that has manifested itself in resource losses and cost reductions.

Keywords: project-orientation, processes, PMBOK, optimization, organization, management

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Authors: Roukia Hammoudi, Chabrouk Farid, Dehak Karima, Mahfoud Hadj Mahammed, Mohamed Didi Ouldelhadj

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The objective of this study was to optimise the extraction conditions for phenolic compounds from Deverra scoparia Coss and Dur. Apiaceae plant by ultrasound assisted extraction (UAE). The effects of solvent type (acetone, ethanol and methanol), solvent concentration (%), extraction time (mins) and extraction temperature (°C) on total phenolic content (TPC) were determined. The optimum extraction conditions were found to be acetone concentration of 80%, extraction time of 25 min and extraction temperature of 25°C. Under the optimized conditions, the value for TPC was 9.68 ± 1.05 mg GAE/g of extract. The study of the antioxidant power of these oils was performed by the method of DPPH. The results showed that antioxidant activity of the Deverra scoparia essential oil was more effective as compared to ascorbic acid and trolox.

Keywords: Deverra scoparia, phenolic compounds, ultrasound assisted extraction, total phenolic content, antioxidant activity

Procedia PDF Downloads 603