Search results for: Multiple Criteria Fuzzy Optimization

Authors: Mohamed Ben Aouicha, Mohamed Tmar, Mohand Boughanem, Mohamed Abid

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This paper presents an information retrieval model on XML documents based on tree matching. Queries and documents are represented by extended trees. An extended tree is built starting from the original tree, with additional weighted virtual links between each node and its indirect descendants allowing to directly reach each descendant. Therefore only one level separates between each node and its indirect descendants. This allows to compare the user query and the document with flexibility and with respect to the structural constraints of the query. The content of each node is very important to decide weither a document element is relevant or not, thus the content should be taken into account in the retrieval process. We separate between the structure-based and the content-based retrieval processes. The content-based score of each node is commonly based on the well-known Tf × Idf criteria. In this paper, we compare between this criteria and another one we call Tf × Ief. The comparison is based on some experiments into a dataset provided by INEX1 to show the effectiveness of our approach on one hand and those of both weighting functions on the other.

Keywords: XML retrieval, INEX, Tf × Idf, Tf × Ief

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Authors: Kaihong Zhao

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In this paper, the existence of 2n positive periodic solutions for n species non-autonomous Lotka-Volterra cooperative systems with harvesting terms is established by using Mawhin-s continuation theorem of coincidence degree theory and matrix inequality. An example is given to illustrate the effectiveness of our results.

Keywords: Multiple positive periodic solutions, Nonautonomous Lotka-Volterra cooperative system, Coincidence degree, Harvesting term.

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Authors: Anuja Vyas, Aikel Indurkhya, Hari Krishna Garg

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Nearly 25 years have passed since the landmark publication of the Human Genome Project, yet scientists have only begun to scratch the surface of its potential benefits. To bridge this gap, a personalized genomic application has been envisioned as a transformative tool accessible to people worldwide. This innovative solution proposes an integrated framework combining blockchain technology, genome-specific applications, and data compression techniques, ensuring operations to be swift, secure, transparent, and space-efficient. The software harnesses advanced Artificial Intelligence and Machine Learning methodologies, such as neural networks, evaluation matrices, fuzzy logic, and expert systems, to analyze individual genomic data. It generates personalized reports by comparing a user's genome with a reference genome, highlighting significant differences. Blockchain technology, with its inherent security, encryption, and immutability features, is leveraged for robust data transport and storage. In addition, a 'Data Abbreviation' technique ensures that genetic data and reports occupy minimal space. This integrated approach promises to be a significant leap forward, potentially transforming human health and well-being on a global scale.

Keywords: Artificial intelligence in genomics, blockchain technology, data abbreviation, data compression, data security in genomics, data storage, expert systems, fuzzy logic, genome applications, genomic data analysis, human genome project, neural networks, personalized genomics.

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Authors: M. S. Salimi, H. Kiamanesh, N. Hedayat

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In this survey the process of crack propagation at the toe of concrete gravity dam is investigated by applying principals and criteria of linear elastic fracture mechanic. Simulating process of earthquake conditions for three models of dam with different geometrical condition, in empty reservoir under plain stress is calculated through special fracture mechanic software FRANNC2D [1] for determining fracture mechanic criteria. The outcomes showed that in spite of the primary expectations, the simultaneous existence of fillet in both toe and heel area (model 3), the rate of maximum principal stress has not been decreased; however, even the maximum principal stress has increased, so it caused stress intensity factors increase which is undesirable. On the other hand, the dam with heel fillet has shown the best attitude and it is because of items like decreasing the rates of maximum and minimum principal stresses and also is related to decreasing the rates of stress intensity factors for 1st & 2nd modes of the model.

Keywords: Stress intensity factor, concrete gravity dam, numerical analysis, geometry of toe.

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.

Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.

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Authors: E. Hosseini, M. Kadivar, M. Shahedi

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Malting is usually carried out on intact barley seed, while hull is still attached to it. In this study, oat grain with and without hull was subjected to controlled germination to optimize its enzymes activity, in such a way that lipase has the lowest and α- amylase and proteinase the highest activities. Since pH has a great impact on the activity of the enzymes, the pH of germination media was set up to 3 to 8. In dehulled oats, lipase and α-amylase had the lowest and highest activities in pHs 3 and 6, respectively whereas the highest proteinase activity was evidenced at pH 7 and 4 in the oats with and without hull respectively. While measurements indicated that the effect of hull on the enzyme activities particularly in lipase and amylase at each level of the pH are significantly different, the best results were obtained in those samples in which their hull had been removed. However, since the similar lipase activity in germinated dehulled oat were recorded at the pHs 4 and 5, therefore it was concluded that pH 5 in dehulled oat seed may provide the optimum enzyme activity for all the enzymes.

Keywords: Enzyme activity, malting, oat, optimization.

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Authors: Irina Eglite, Andrei A. Kolyshkin

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The effect of small non-parallelism of the base flow on the stability of slightly curved mixing layers is analyzed in the present paper. Assuming that the instability wavelength is much smaller than the length scale of the variation of the base flow we derive an amplitude evolution equation using the method of multiple scales. The proposed asymptotic model provides connection between parallel flow approximations and takes into account slow longitudinal variation of the base flow.

Keywords: shallow water, parallel flow assumption, weaklynonlinear analysis, method of multiple scales

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Authors: M. Siosemarde, M. Byzedi

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Saturated hydraulic conductivity of Soil is an important property in processes involving water and solute flow in soils. Saturated hydraulic conductivity of soil is difficult to measure and can be highly variable, requiring a large number of replicate samples. In this study, 60 sets of soil samples were collected at Saqhez region of Kurdistan province-IRAN. The statistics such as Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean Bias Error (MBE) and Mean Absolute Error (MAE) were used to evaluation the multiple linear regression models varied with number of dataset. In this study the multiple linear regression models were evaluated when only percentage of sand, silt, and clay content (SSC) were used as inputs, and when SSC and bulk density, Bd, (SSC+Bd) were used as inputs. The R, RMSE, MBE and MAE values of the 50 dataset for method (SSC), were calculated 0.925, 15.29, -1.03 and 12.51 and for method (SSC+Bd), were calculated 0.927, 15.28,-1.11 and 12.92, respectively, for relationship obtained from multiple linear regressions on data. Also the R, RMSE, MBE and MAE values of the 10 dataset for method (SSC), were calculated 0.725, 19.62, - 9.87 and 18.91 and for method (SSC+Bd), were calculated 0.618, 24.69, -17.37 and 22.16, respectively, which shows when number of dataset increase, precision of estimated saturated hydraulic conductivity, increases.

Keywords: dataset, precision, saturated hydraulic conductivity, soil and statistics.

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Authors: J. Kala, V. Salajka, P. Hradil

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Many footbridges have natural frequencies that coincide with the dominant frequencies of the pedestrian-induced load and therefore they have a potential to suffer excessive vibrations under dynamic loads induced by pedestrians. Some of the design standards introduce load models for pedestrian loads applicable for simple structures. Load modeling for more complex structures, on the other hand, is most often left to the designer. The main focus of this paper is on the human induced forces transmitted to a footbridge and on the ways these loads can be modeled to be used in the dynamic design of footbridges. Also design criteria and load models proposed by widely used standards were introduced and a comparison was made. The dynamic analysis of the suspension bridge in Kolin in the Czech Republic was performed on detailed FEM model using the ANSYS program system. An attempt to model the load imposed by a single person and a crowd of pedestrians resulted in displacements and accelerations that are compared with serviceability criteria.

Keywords: Footbridge, Serviceability, Pedestrian action, Numerical analysis.

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Authors: Roshan Sharma, Bjørn Glemmestad

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In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share gas from a common source to maximize total oil production. One of the objectives of the paper is to show that a linear MPC consisting of a control objective and an economic objective can be used both as an optimizer and a controller for gas lifted systems. The MPC is based on linearized model of the oil field developed from first principles modeling. Simulation results show that the total oil production is increased by 3.4%. Difficulties in accurately measuring the bottom hole pressure using sensors in harsh operating conditions can be resolved by using an Unscented Kalman Filter (UKF) for estimation. In oil fields where input disturbance (total supply of gas) is not measured, UKF can also be used for disturbance estimation. Increased total oil production due to optimization leads to increased profit.

Keywords: gas lift, MPC, oil production, optimization, Unscented Kalman filter.

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.

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Authors: H. Bouhamed, A. Rebai, T. Lecroq, M. Jaoua

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The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.

Keywords: Data-organization, data-optimization, automatic knowledge discovery, Multi-Entities Bayesian networks, score merging.

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Authors: Mehdi Nasri, Hossein Nezamabadi-pour, Malihe Maghfoori

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This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral-derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modelled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.

Keywords: Brushless DC motor, Particle swarm optimization, PID Controller, Optimal control.

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. For example rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: Rubber bumper, data acquisition, finite element analysis, support vector regression.

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Authors: P. Gnanasekar, A. Nagappan, S. Sharavanan, O. Saravanan, D. Vinodkumar, T. Elayabharathi, G. Karthik

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In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..

Keywords: ACO Ant Colony Optimization, Correlogram, CCM Co-Occurrence Matrix, RTS Rough-Set theory

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Authors: Leila Jafari, Viliam Makis

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In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: Condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand.

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Authors: Farhad Namdari, Reza Sedaghati

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Economic dispatch (ED) has been considered to be one of the key functions in electric power system operation which can help to build up effective generating management plans. The practical ED problem has non-smooth cost function with nonlinear constraints which make it difficult to be effectively solved. This paper presents a novel heuristic and efficient optimization approach based on the new Bat algorithm (BA) to solve the practical non-smooth economic dispatch problem. The proposed algorithm easily takes care of different constraints. In addition, two newly introduced modifications method is developed to improve the variety of the bat population when increasing the convergence speed simultaneously. The simulation results obtained by the proposed algorithms are compared with the results obtained using other recently develop methods available in the literature.

Keywords: Non-smooth, economic dispatch, bat-inspired, nonlinear practical constraints, modified bat algorithm.

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Authors: Tetsuya Furukawa, Masahiro Kuzunishi

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Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.

Keywords: Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels

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Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif

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Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.

Keywords: Routing protocols, energy optimization, clustering.

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Authors: N. Hussain, G. Jaffery, A.N. Sabri, S. Hasnain

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The main aim is to perform mutational analysis of CTLA4 gene Exon 1 in SLE patients. A total of 61 SLE patients fulfilling “American College of Rheumatology (ACR) criteria" and 61 controls were enrolled in this study. The region of CTLA4 gene exon 1 was amplified by using Step-down PCR technique. Extracted DNA of band 354 bp was sequenced to analyze mutations in the exon-1 of CTLA-4 gene. Further, protein sequences were identified from nucleotide sequences of CTLA4 Exon 1 by using Expasy software and through Blast P software it was found that CTLA4 protein sequences of Pakistani SLE patients were similar to that of Chinese SLE population. No variations were found after patients sequences were compared with that of the control sequence. Furthermore it was found that CTLA4 protein sequences of Pakistani SLE patients were similar to that of Chinese SLE population. Thus CTLA4 gene may not be responsible for an autoimmune disease SLE.

Keywords: American College of Rheumatology criteria, autoimmune disease, Cytotoxic T Lymphocyte Antigen-4, Polymerase Chain Reaction, Systemic Lupus Erythematosus

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cécile Donzé

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Multiple Sclerosis (MS) is a disease which affects the central nervous system and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. 40 volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and 2 types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: Balance, multiple sclerosis, nonlinear analysis, postural sway.

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Authors: Salma Ainine, Colin Ritchie, Tracey McFee

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Background: The societal impact of antibiotic resistance is a major public health concern. The increase in incidence of resistant bacteria can ultimately be fatal. Objective: To analyse the appropriateness of antibiotic prescribing in Dundee Dental Hospital, ultimately improving the safety and quality of patient care. Methods: Two examiners independently crosschecked approximately fifty consecutive prescriptions, and corresponding patient case notes, for three data collection cycles between August 2014 – September 2015. The Scottish Dental Clinical Effectiveness Program (SDCEP) Drug Prescribing for Dentistry guidelines was the standard utilised. The criteria: clinical justification, regime justification and review arrangements was measured, and compared to the standard. Results: Cycle one revealed 42% of antibiotic prescriptions were appropriate. Interventions included: multiple staff meetings, introduction of a checklist attached to the prescription pack, and production of patient leaflets explaining indications for antibiotics. Cycle two and three revealed 44%, and 30% compliance, respectively. Conclusion: The results of the audit have yet to meet target standards set out in prescribing guidelines. However, steps are being taken and change has occurred on a cultural level.

Keywords: Antibiotic resistance, antibiotic stewardship, dental infection and hygiene standards.

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Authors: Y. Bentoutou, A.M. Si Mohammed

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This paper presents a review of an 8-year study on radiation effects in commercial memory devices operating within the main on-board computer system OBC386 of the Algerian microsatellite Alsat-1. A statistical analysis of single-event upset (SEU) and multiple-bit upset (MBU) activity in these commercial memories shows that the typical SEU rate at alsat-1's orbit is 4.04 × 10-7 SEU/bit/day, where 98.6% of these SEUs cause single-bit errors, 1.22% cause double-byte errors, and the remaining SEUs result in multiple-bit and severe errors.

Keywords: Radiation effects, error detection and correction, satellite computer, small satellite mission.

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Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: Connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks.

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Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

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A method of effective planning and control of industrial facility energy consumption is offered. The method allows optimally arranging the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: Energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics.

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Authors: T. Kero, R. Söderberg, M. Andersson, L. Lindkvist

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Within dental-guided surgery, there has been a lack of analytical methods for optimizing the treatment of the rehabilitation concepts regarding geometrical variation. The purpose of this study is to find the source of the greatest geometrical variation contributor and sensitivity contributor with the help of virtual variation simulation of a dental drill- and implant-guided surgery process using a methodical approach. It is believed that lower geometrical variation will lead to better patient security and higher quality of dental drill- and implant-guided surgeries. It was found that the origin of the greatest contributor to the most variation, and hence where the foci should be set, in order to minimize geometrical variation was in the assembly category (surgery). This was also the category that was the most sensitive for geometrical variation.

Keywords: Variation Simulation, Process Optimization, Guided Surgeries, Dental Prosthesis.

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: Satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization.

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Authors: Hilal A. Fadhil, Thanaa Hussein Abd, Hamza M. R. Al-Khafaji, S. A. Aljunid

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This paper presents a comparison between Spectrum- Sliced Wavelength Division Multiplexing (SS-WDM) and Spectrum Amplitude Coding Optical Code Division Multiple Access (SAC Optical CDMA) systems for different light sources. The performance of the system is shown in the simulated results of the bit error rate (BER) and the eye diagram of both systems. The comparison results indicate that the Multiple Access Interference (MAI) effects have a significant impact on SS-WDM over SAC Optical CDMA systems. Finally, in terms of spectral efficiency at constant BER of 10-12, SSWDM offers higher spectral efficiency than optical CDMA since no bandwidth expansion in needed.

Keywords: WDM, OCDMA, BER, RD code

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Authors: M. H. Omar

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Cheating on standardized tests has been a major concern as it potentially minimizes measurement precision. One major way to reduce cheating by collusion is to administer multiple forms of a test. Even with this approach, potential collusion is still quite large. A Latin-square treatment structure for distributing multiple forms is proposed to further reduce the colluding potential. An index to measure the extent of colluding potential is also proposed. Finally, with a simple algorithm, the various Latin-squares were explored to find the best structure to keep the colluding potential to a minimum.

Keywords: Colluding pairs, Scale for Colluding Potential, Latin-Square Structure, Minimization of Cheating.

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Authors: Zhenhuan Zhu, David Mulvaney, Vassilios Chouliaras

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A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.

Keywords: Genetic algorithms, genetic hardware, machinelearning.

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