Search results for: water cycle algorithm

Authors: Emily Kambalame

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Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions outperformed other retention allocations by identifying the optimal solution with the fewest function evaluation

Keywords: design optimization, multi-objective evolutionary, penalty-free, water distribution systems

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Authors: Raquel Salazar Moreno, Uwe Schmidt, Efrén Fitz Rodríguez, Dennis Dannehl, Abraham Rojano Aguilar, Irineo López Cruz, Gilberto Navas Gómez

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As urban areas expand, strategic and protected water reserves become more critical. In this study we investigate the water problems in Mexico City and its Metropolitan area. This region faces a complex water problem that concerns not only Mexican boundaries but also international level because is one of the biggest human concentrations in the World. The current water shortage situation raises the necessity of importing surface and groundwater from the Cutzamala River and from the Alto Rio Lerma System respectively. Water management is the real issue in this region, because waste water generation is more than aquifer overexploitation, and surface water loss in the rainfall period is greater than water imported from other regions. However, the possible solutions of the water supply schemes are complicated, there is a need to look for alternatives socially acceptable and environmentally desirable, considering first the possible solutions on the demand side. Also, it is necessary more investment in water treatment plants and hydraulic infrastructure to ensure water supply and decrease the environmental problems in the area. More studies need to be done related to water efficiency in the three sectors.

Keywords: megacities, aquifer overexploitation, environmental problems, vulnerability

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Febri Ramadhan

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Water medium is a vital necessity for the survival of fish. Fish can survive inside/outside of water medium within a certain time. By knowing the level of survival fish at outside of water medium, a person can transport the fish to a place with more efficiently. Transport of live fish from one place to another can be done with wet and dry media system. In this experiment the treatment-given the observed differences in fish species. This experiment aimed to test the degree of resilience of fish out of water media. Based on the ANOVA table is obtained, it can be concluded that the type of fish affects the level of resilience of fish outside the water (Fhit> Ftab).

Keywords: fish, transport, retention rate, fish resiliance

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Authors: Mehran Fadaeinasab, Hamed Karimian, Najihah Mohd Hashim, Hapipah Mohd Ali

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In this study, three indole alkaloids namely; rauvolfine B, macusine B, and isoreserpiline have been isolated from the dichloromethane crude extract of Rauvolfia reflexa bark (Apocynaceae). The structural elucidation of the isolated compounds has been performed using spectral methods such as UV, IR, MS, 1D, and 2D NMR. Rauvolfine B showed anti proliferation activity on HCT-116 cancer cell line, its cytotoxicity induction was observed using MTT assay in eight different cell lines. Annexin-V is serving as a marker for apoptotic cells and the Annexin-V-FITC assay was carried out to observe the detection of cell-surface Phosphatidylserine (PS). Apoptosis was confirmed by using caspase-8 and -9 assays. Cell cycle arrest was also investigated using flowcytometric analysis. rauvolfine B had exhibited significantly higher cytotoxicity against HCT-116 cell line. The treatment significantly arrested HCT-116 cells in the S phase. Together, the results presented in this study demonstrated that rauvolfine B inhibited the proliferation of HCT-116 cells and programmed cell death followed by cell cycle arrest.

Keywords: apocynacea, indole alkaloid, apoptosis, cell cycle arrest

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Authors: Yusri Yusof, Chen Wong Keong

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This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: Archit Yajnik

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Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.

Keywords: hidden markov model, natural language processing, POS tagging, viterbi algorithm

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Authors: Hussain K. Chaiel

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The development in the field of the digital signal processing (DSP) and the microelectronics technology reduces the complexity of the iterative algorithms that need large number of arithmetic operations. Virtex-Field Programmable Gate Arrays (FPGAs) are programmable silicon foundations which offer an important solution for addressing the needs of high performance DSP designer. In this work, Virtex-7 FPGA technology is used to implement an iterative algorithm to estimate the earthquake location. Simulation results show that an implementation based on block RAMB36E1 and DSP48E1 slices of Virtex-7 type reduces the number of cycles of the clock frequency. This enables the algorithm to be used for earthquake prediction.

Keywords: DSP, earthquake, FPGA, iterative algorithm

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Authors: A. Andreasyan, C. Connors

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The Elliptic Curve Digital Signature algorithm-based X509v3 certificates are becoming more popular due to their short public and private key sizes. Moreover, these certificates can be stored in Internet of Things (IoT) devices, with limited resources, using less memory and transmitted in network security protocols, such as Internet Key Exchange (IKE), Transport Layer Security (TLS) and Secure Shell (SSH) with less bandwidth. The proposed method gives another advantage, in that it increases the performance of the above-mentioned protocols in terms of key exchange by saving one scalar multiplication operation.

Keywords: cryptography, elliptic curve digital signature algorithm, key exchange, network security protocol

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Authors: Meng Wu

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Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: motion planning, gravity gradient inversion algorithm, ant colony optimization

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Authors: Jiaqi Huang, Lu Jin

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Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.

Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete

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Authors: Rose-Michelle Smith, Musandji Fuamba, Salomon Salumu

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Water is vital for life. Access to drinking water and sanitation for humans is one of the Sustainable Development Goals (specifically the sixth) approved by United Nations Member States in September 2015. There are various problems identified relating to water: insufficient fresh water, inequitable distribution of water resources, poor water management in certain places on the planet, detection of water-borne diseases due to poor water quality, and the negative impacts of climate change on water. One of the major challenges in the world is finding ways to ensure that people and the environment have enough water resources to sustain and support their existence. Thus, this research project aims to develop a tool to assess the availability, quality and needs of water in current and future situations with regard to climate change. This tool was tested using threshold values for three regions in three countries: the Metropolitan Community of Montreal (Canada), Normandie Region (France) and North Department (Haiti). The WEAP software was used to evaluate the available quantity of water resources. For water quality, two models were performed: the Canadian Council of Ministers of the Environment (CCME) and the Malaysian Water Quality Index (WQI). Preliminary results showed that the ratio of the needs could be estimated at 155, 308 and 644 m3/capita in 2023 for Normandie, Cap-Haitian and CMM, respectively. Then, the Water Quality Index (WQI) varied from one country to another. Other simulations regarding the water availability and quality are still in progress. This tool will be very useful in decision-making on projects relating to water use in the future; it will make it possible to estimate whether the available resources will be able to satisfy the needs.

Keywords: climate change, water needs, balance sheet, water quality

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Authors: Hooman Rowshanaie

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The majority of green plants have 70%-90% water, this amount depend on age of plants, species, tissues of plants and also the environmental conditions that plants growth and development on it. Because of intense plant demanding to achieve the available water for growing and developing, always plants need a water sources and also mechanisms to retention the water and reduction water loss under critical situation and water deficit conditions otherwise the yield of plants would be decreased. Decreasing the yield depend on genotypes, intense of water deficit and also growth stage. Recently the mechanisms and also compound that have major role to water stress adaption of plants would be consideration. Osmotic adjustment is one of the most important mechanisms in terms of this field that many valuable researches focused on it because the majority of organic and inorganic solutes directly or even indirectly have pivotal role in this phenomenon. The contribution of OA to prevent water loss in response to water deficit and resistance to water stress taken to consideration recently and also the organic and inorganic compounds to OA tended has a high rate of significant.

Keywords: water deficit, drought stress, osmotic adjustment, organic compound, inorganic compound, solute

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Authors: Sharon Yunger, Liat Altman, Yuval Garini, Yaron Shav-Tal

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Understanding the dynamics of transcription in living cells has improved since the development of quantitative fluorescence-based imaging techniques. We established a method for following transcription from a single copy gene in living cells. A gene tagged with MS2 repeats, used for mRNA tagging, in its 3' UTR was integrated into a single genomic locus. The actively transcribing gene was detected and analyzed by fluorescence in situ hybridization (FISH) and live-cell imaging. Several cell clones were created that differed in the promoter regulating the gene. Thus, comparative analysis could be obtained without the risk of different position effects at each integration site. Cells in S/G2 phases could be detected exhibiting two adjacent transcription sites on sister chromatids. A sharp reduction in the transcription levels was observed as cells progressed along the cell cycle. We hypothesized that a change in chromatin structure acts as a general mechanism during the cell cycle leading to down-regulation in the activity of some genes. We addressed this question by treating the cells with chromatin decondensing agents. Quantifying and imaging the treated cells suggests that chromatin structure plays a role both in regulating transcriptional levels along the cell cycle, as well as in limiting an active gene from reaching its maximum transcription potential at any given time. These results contribute to understanding the role of chromatin as a regulator of gene expression.

Keywords: cell cycle, living cells, nucleus, transcription

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Authors: Grzegorz Baranski, Piotr Kacejko, Konrad Pietrykowski, Mariusz Duk

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This paper discusses a model of a bus-driving scheme. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the mechanical energy recuperation during the Japanese JE05 Emission Test Cycle. The simulations were performed for several values of vehicle mass. The research results show that fuel economy is impacted by kinetic energy recuperation.

Keywords: heavy duty vehicle, city bus, Japanese JE05 test cycle, kinetic energy, simulations

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In terms of security of the information signal, the meta-heuristic Penguins Search Optimization Algorithm (PeSOA) is applied to synchronize chaotic encryption communications in the case of sensitive dependence on initial conditions in chaotic generator oscillator. The objective of this paper is the use of the PeSOA algorithm to exploring search space with random and iterative processes for synchronization of symmetric keys in both transmission and reception. Simulation results show the effectiveness of the PeSOA algorithm in generating symmetric keys of the encryption process and synchronizing.

Keywords: meta-heuristic, PeSOA, chaotic systems, encryption, synchronization optimization

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Authors: Watchara Songserm, Teeradej Wuttipornpun

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This paper presents a genetic algorithm based permutation and non-permutation scheduling heuristics (GAPNP) to solve a multi-stage finite capacity material requirement planning (FCMRP) problem in automotive assembly flow shop with unrelated parallel machines. In the algorithm, the sequences of orders are iteratively improved by the GA characteristics, whereas the required operations are scheduled based on the presented permutation and non-permutation heuristics. Finally, a linear programming is applied to minimize the total cost. The presented GAPNP algorithm is evaluated by using real datasets from automotive companies. The required parameters for GAPNP are intently tuned to obtain a common parameter setting for all case studies. The results show that GAPNP significantly outperforms the benchmark algorithm about 30% on average.

Keywords: capacitated MRP, genetic algorithm, linear programming, automotive industries, flow shop, application in industry

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Authors: Vakhtang Geladze, Nana Bolashvili, Tamazi Karalashvili, Nino Machavariani, Vajha Neidze, Nana Kvirkvelia, Tamar Chichinadze

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Deficiency of fresh water is a vital global problem today. It must be taken into consideration that in the nearest future fresh water crisis will become even more acute owing to the global climate warming and fast desertification processes in the world. Georgia has signed the association agreement with Euro Union last year where the priority spheres of cooperation are the management of water resources, development of trans-boundary approach to the problem and active participation in the “Euro Union water initiative” component of “the East Europe, Caucasus and the Central Asia”. Fresh water resources are the main natural wealth of Georgia. According to the average water layer height, Georgia is behind such European countries only as Norway, Switzerland and Austria. The annual average water provision of Georgia is 4-8 times higher than in its neighbor countries Armenia and Azerbaijan. Despite abundant water resources in Georgia, there is considerable discrepancy between their volume and use in some regions because of the uneven territorial distribution. In the East Georgia, water supply of the territory and population is four times less than in the West Georgia.

Keywords: GIS, water consumption, water management, water resources

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Authors: Kun-Ping Cheng, Dong-Shang Chang, Rou-Wen Wang

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Pre-treatment of automobile paint-shop procedures are the preparation of warm water rinsing tank, hot water rinsing tank, degreasing tank, phosphate tank. The conventional boiler steam fuel is natural gas, producing steam to supply the heat exchange of each tank sink. In this study, the high-frequency soldering economizer is developed for recovering waste heat in the automotive paint-shop (RTO, Regenerative Thermal Oxidation). The heat recovery rate of the new economizer is 20% to 30% higher than the conventional embedded heat pipe. The adaptive control system responded to both RTO furnace exhaust gas and heat demands. In order to maintain the temperature range of the tanks, pre-treatment tanks are directly heated by waste heat recovery device (gas-to-water heat exchanger) through the hot water cycle of heat transfer. The performance of developed waste heat recovery system shows the annual recovery achieved to 1,226,411,483 Kcal of heat (137.8 thousand cubic meters of natural gas). Boiler can reduce fuel consumption by 20 to 30 percent compared to without waste heat recovery. In order to alleviate environmental impacts, the temperature at the end of the flue is further reduced from 160 to 110°C. The innovative waste heat recovery is helpful to energy savings and sustainable environment.

Keywords: waste heat recovery system, sustainability, RTO (Regenerative Thermal Oxidation), economizer, automotive industry

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Ohud Alharbi, Emily Baines

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The animation industry is one of the creative industries that have attracted recent historiographical attention. However, there has been very limited research on Saudi Arabian and wider Arabian animation industries, while there are a large number of studies that have covered this issue for North America, Europe and East Asia. The existing studies show that developed countries such as USA, Japan and the UK have reached the Maturity stage in their animation industry life-cycle. On the other hand, developing countries that are still in the Introduction phase of the industry life-cycle face challenges to improve their industry. Saudi Arabia is one of the countries whose animation industry is still in its infancy. Thus, the aim of this paper is to address the main barriers that hinder the evolution of the industry life-cycle for Saudi animation – challenges that are also relevant to many other early stage industries in developing countries. These barriers have been analysed using the early mobility barriers defined by Porter, to provide a conceptual structure for defining recommendations to enable the transition to a strong Growth phase industry. This study utilized qualitative methods to collect data, which involved in-depth interviews, document analysis and observations. It also undertook a comparative case study approach to investigate the animation industry life-cycle, with three selected case studies that have a more developed industry than Saudi animation. Case studies include: the United Kingdom, which represents a Mature animation industry; Egypt, which represents an established Growth stage industry; and the United Arab of Emirates, which is an early Growth stage industry. This study suggests adopting appropriate strategies that arise as findings from the comparative case studies, to overcome barriers and facilitate the growth of the Saudi animation industry.

Keywords: barriers, industry life-cycle, Saudi animation, industry

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Authors: Onur Özdemir, M.Erhan ORHAN

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Knowledge Development (KD) is just one of the important phases of Knowledge Management (KM). KD is the phase in which intelligence is used to see the big picture. In order to understand whether information is important or not, we have to use the intelligence cycle that includes four main steps: aiming, collecting data, processing and utilizing. KD also needs these steps. To make a precise decision, the decision maker has to be aware of his subordinates’ ideas. If the decision maker ignores the ideas of his subordinates or participants of the organization, it is not possible for him to get the target. KD is a way of using wisdom to accumulate the puzzle. If the decision maker does not bring together the puzzle pieces, he cannot get the big picture, and this shows its effects on the battlefield. In order to understand the battlefield, the decision maker has to use the intelligence cycle. To convert information to knowledge, KD is the main means for the intelligence cycle. On the other hand, the “Z Generation” born after the millennium are really the game changers. They have different attitudes from their elders. Their understanding of life is different - the definition of freedom and independence have different meanings to them than others. Decision makers have to consider these factors and rethink their decisions accordingly. This article tries to explain the relation between KD and Generation Z. KD is the main method of target managing. But if leaders neglect their people, the world will be seeing much more movements like the Arab Spring and other insurgencies.

Keywords: knowledge development, knowledge management, generation Z, intelligence cycle

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Authors: Mamoon Masud, Suleman Mazhar

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Indus river basin’s irrigation system in Pakistan is extremely complex, spanning over 50,000 km. Maintenance and monitoring of this demands enormous resources. This paper describes the development of a streamlined and low-cost autonomous underwater vehicle (AUV) for the monitoring of irrigation canals including water quality monitoring and water theft detection. The vehicle is a hovering-type AUV, designed mainly for monitoring irrigation canals, with fully documented design and open source code. It has a length of 17 inches, and a radius of 3.5 inches with a depth rating of 5m. Multiple sensors are present onboard the AUV for monitoring water quality parameters including pH, turbidity, total dissolved solids (TDS) and dissolved oxygen. A 9-DOF Inertial Measurement Unit (IMU), GY-85, is used, which incorporates an Accelerometer (ADXL345), a Gyroscope (ITG-3200) and a Magnetometer (HMC5883L). The readings from these sensors are fused together using directional cosine matrix (DCM) algorithm, providing the AUV with the heading angle, while a pressure sensor gives the depth of the AUV. 2 sonar-based range sensors are used for obstacle detection, enabling the vehicle to align itself with the irrigation canals edges. 4 thrusters control the vehicle’s surge, heading and heave, providing 3 DOF. The thrusters are controlled using a proportional-integral-derivative (PID) feedback control system, with heading angle and depth being the controller’s input and the thruster motor speed as the output. A flow sensor has been incorporated to monitor canal water level to detect water-theft event in the irrigation system. In addition to water theft detection, the vehicle also provides information on water quality, providing us with the ability to identify the source(s) of water contamination. Detection of such events can provide useful policy inputs for improving irrigation efficiency and reducing water contamination. The AUV being low cost, small sized and suitable for autonomous maneuvering, water level and quality monitoring in the irrigation canals, can be used for irrigation network monitoring at a large scale.

Keywords: the autonomous underwater vehicle, irrigation canal monitoring, water quality monitoring, underwater line tracking

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Authors: Kaiping Xu, Aiju You, Lei Hua

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In view of the ecological environmental problems and protection needs of mountainous rivers in Zhejiang province, a suitable ecological water demand evaluation system was established based on investigation and monitoring. Taking the Kaihua river as an example, the research on ecological water demand and the current situation evaluation were carried out. The main types of ecological water demand in Majin River are basic ecological flow and lake wetland outside the river, and instream flow and water demands for water quality in Zhongcun river. In the wet season, each ecological water demand is 18.05m3/s and 2.56m3 / s, and in the dry season is 3.00m3/s and 0.61m3/s. Three indexes of flow, duration and occurrence time are used to evaluate the ecological water demand. The degree of ecological water demand in the past three years is low level of satisfaction. Meanwhile, the existing problems are analyzed, and put forward reasonable and operable safeguards and suggestions.

Keywords: Zhejiang province, mountainous river, ecological water demand, Kaihua river, evaluation

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Authors: T. Wanyama, B. Far

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Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

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Authors: Ketseas Dimitris

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In this work, we investigate the effect of noise on a classical two-degree-of-freedom pitch-plunge aeroelastic system. The inlet velocity of the flow is modelled as a stochastically varying parameter by the Ornstein-Uhlenbeck (OU) stochastic process. The system is a 2D airfoil, and the elastic problem is simulated using linear springs. We study the manifestation of Limit Cycle Oscillations (LCO) that correspond to the varying fluid velocity under the dynamic stall regime. We aim to delve into the unexplored facets of the classical pitch-plunge aeroelastic system, seeking a comprehensive understanding of how parametric noise influences the occurrence of LCO and expands the boundaries of its known behavior.

Keywords: aerodynamics, aeroelasticity, computational fluid mechanics, stall flutter, stochastical processes, limit cycle oscillation

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Authors: Firas Al-Mahmoud, Jean-Michel Mechling, Mohamed Shaban

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The long-term durability of fibre reinforced polymer (FRP) composites is often stated as being the main reason for the use of these materials. Indeed, structures externally or Near Surface Mounted (NSM) reinforced with Carbon Fibre Reinforcement Polymer CFRP are often in contact with temperature cycles and salt water immersion and other environmental conditions that reduce the expected durability of the system. Bond degradation is a frequent cause of premature failure of structural elements and environmental conditions are known to relate to such failures. The purpose of this study is to investigate the effect of environmental exposure on the bond for different CFRP strengthening systems. Bending tests were conducted to evaluate the bond with and without environmental exposure. The specimens were strengthened with CFRP sheets, CFRP plates and NSM CFRP rods embedded in two filling materials: epoxy resin and mortar. Then, they were exposed to up to 300 freeze–thaw cycles. One freeze–thaw cycle consisted of four stages according to ASTM or immersed in 3.5% salted tap water. A total of thirty-six specimens were prepared for this purpose. Results showed a decrease in ultimate bond strength for specimens strengthened by CFRP sheets that were immersed in salt water for 120 days, while a reduction was shown for CFRP sheet and plate bonded specimens that were subjected to 300 freeze–thaw cycles. Exposing NSM CFRP rod strengthened specimens, embedded in resin or mortar, to freeze–thaw cycles or to immersion in salt water does not affect the bond strength.

Keywords: durability, strengthening, FRP, bond, freeze–thaw

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

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Authors: Siamak Jamshidi

Abstract:

The Caspian Sea is the Earth's largest inland body of water. One of the most important issues related to the sea is water level changes. For measuring and recording Caspian Sea water level, there are at least three gauges and radar equipment in Anzali, Nowshahr and Amirabad Ports along the southern boundary of the Caspian Sea. It seems that evaporation, hotter surface air temperature, and in general climate change is the main reasons for its water level fluctuations. Gorgan Bay in the eastern part of the southern boundary of the Caspian Sea is one of the areas under the effect of water level fluctuation. Based on the results of field measurements near the Gorgan Bay mouth temperature ranged between 24°C–28°C and salinity was about 13.5 PSU in midsummer while temperature changed between 10-11.5°C and salinity mostly was 15-16.5 PSU in mid-winter. The decrease of Caspian Sea water level and rivers outflow are the two most important factors for the increase in water salinity of the Gorgan Bay. Results of field observations showed that, due to atmospheric factors, climate changes and decreasing of precipitation over the southern basin of the Caspian Sea during last decades, the water level of bay was reduced around 0.5 m.

Keywords: Caspian Sea, Gorgan Bay, water level fluctuation, climate changes

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