Search results for: artificial fish swarm algorithm (AFSA)

Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

Procedia PDF Downloads 454

Authors: Behnam Tavakkol

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Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters.

Keywords: clustering algorithm, fuzzy methods, kernel k-medoids, uncertain data

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Authors: Hammoudi Abderazek

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The present paper introduces a modified adaptive mixed differential evolution (MAMDE) to select the main geometry parameters of specific cylindrical spur gear. The developed algorithm used the self-adaptive mechanism in order to update the values of mutation and crossover factors. The feasibility rules are used in the selection phase to improve the search exploration of MAMDE. Moreover, the elitism is performed to keep the best individual found in each generation. For the constraints handling the normalization method is used to treat each constraint design equally. The finite element analysis is used to confirm the optimization results for the maximum bending resistance. The simulation results reached in this paper indicate clearly that the proposed algorithm is very competitive in precision gear design optimization.

Keywords: evolutionary algorithm, spur gear, tooth profile, meta-heuristics

Procedia PDF Downloads 129

Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

Procedia PDF Downloads 314

Authors: Mercy Chepkirui, Reuben Omondi, Paul Orina, Albert Getabu, Lewis Sitoki, Jonathan Munguti

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Globally, the decline in capture fisheries as a result of the growing population and increasing awareness of the nutritional benefits of white meat has led to the development of aquaculture. This is anticipated to meet the increasing call for more food for the human population, which is likely to increase further by 2050. Statistics showed that more than 50% of the global future fish diet will come from aquaculture. Aquaculture began commercializing some decades ago; this is accredited to technological advancement from traditional to modern cultural systems, including cage farming. Cage farming technology has been rapidly growing since its inception in Lake Victoria, Kenya. Currently, over 6,000 cages have been set up in Kenyan waters, and this offers an excellent opportunity for recognition of Kenya’s government tactic to eliminate food insecurity and malnutrition, create employment and promote a Blue Economy. However, being an open farming enterprise is likely to emit large bulk of waste hence altering the ecosystem integrity of the lake. This is through increased chlorophyll-a pigments, alteration of the plankton community, macroinvertebrates, fish genetic pollution, transmission of fish diseases and pathogens. Cage farming further increases the nutrient loads leading to the production of harmful algal blooms, thus negatively affecting aquatic and human life. Despite the ecological transformation, cage farming provides a platform for the achievement of the Sustainable Development Goals of 2030, especially the achievement of food security and nutrition. Therefore, there is a need for Integrated Multitrophic Aquaculture as part of Blue Transformation for ecosystem monitoring.

Keywords: aquaculture, ecosystem, blue economy, food security

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Authors: Kamel Barka, Lyamine Guezouli, Assem Rezki

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In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.

Keywords: heterogeneous wireless networks, unmanned aerial vehicles, reference point, collect data, genetic algorithm

Procedia PDF Downloads 78

Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane

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The localization information is crucial for the operation of WSN. There are principally two types of localization algorithms. The Range-based localization algorithm has strict requirements on hardware; thus, it is expensive to be implemented in practice. The Range-free localization algorithm reduces the hardware cost. However, it can only achieve high accuracy in ideal scenarios. In this paper, we locate unknown nodes by incorporating the advantages of these two types of methods. The proposed algorithm makes the unknown nodes select the nearest anchor using the Received Signal Strength Indicator (RSSI) and choose two other anchors which are the most accurate to achieve the estimated location. Our algorithm improves the localization accuracy compared with previous algorithms, which has been demonstrated by the simulating results.

Keywords: WSN, localization, DV-Hop, RSSI

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Authors: Dereje Ferede, Solomon Negash

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Artificial Intelligence (AI) is a key enabler and driver to transform and revolutionize the healthcare industries. However, utilizing AI and achieving these benefits is challenging for different sectors in wide-ranging, more difficult for developing economy healthcare. Due to this, real-world clinical execution and implementation of AI have not yet aged. We believe that examining the determinants is key to addressing these challenges. Furthermore, the literature does not yet particularize determinants of AI capabilities and ways of empowering the healthcare ecosystem to develop AI capabilities in a developing economy. Thus, this study aims to position AI as a digital transformation weapon for the healthcare ecosystem by examining AI capability determinants and providing insights on better empowering the healthcare industry to develop AI capabilities. To do so, we base on the technology-organization-environment (TOE) model and will apply a mixed research approach. We will conclude with recommendations based on findings for future practitioners and researchers.

Keywords: artificial intelligence, capability, digital transformation, developing economies, healthcare

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Authors: Suneeta Kumari, Abanti Sahoo

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Industrial effluents treatment is a major problem in the world. All wastewater treatment methods have some problems in the environment. Due to this reason, today many natural biopolymers are being used in the waste water treatment because those are safe for our environment. In this study, synthesis and characterization of polyethersulfone/chitosan membranes (Thin film composite membrane) are carried out. Fish scales are used as raw materials. Different characterization techniques such as Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), scanning electron microscope (SEM) and Thermal gravimetric analysis (TGA) are analysed for the synthesized membrane. The performance of membranes such as flux, rejection, and pore size are also checked. The synthesized membrane is used for the treatment of steel industry waste water where Biochemical oxygen demand (BOD), Chemical Oxygen Demand (COD), pH, colour, Total dissolved solids (TDS), Total suspended solids (TSS), Electrical conductivity (EC) and Turbidity aspects are analysed.

Keywords: fish scale, membrane synthesis, treatment of industrial effluents, chitosan

Procedia PDF Downloads 317

Authors: Mehmet Karaata

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Given two distinct vertices (nodes) source s and target t of a graph G = (V, E), the two node-disjoint paths problem is to identify two node-disjoint paths between s ∈ V and t ∈ V . Two paths are node-disjoint if they have no common intermediate vertices. In this paper, we present an algorithm with O(m)-time complexity for finding two node-disjoint paths between s and t in arbitrary graphs where m is the number of edges. The proposed algorithm has a wide range of applications in ensuring reliability and security of sensor, mobile and fixed communication networks.

Keywords: disjoint paths, distributed systems, fault-tolerance, network routing, security

Procedia PDF Downloads 439

Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Abdulbaset Saad, Adel Younis, Zuomin Dong

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For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.

Keywords: differential evolution, engineering design, expensive computations, meta-modeling, radial basis function, optimization

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Authors: Alina Mirza, Sumrin M. Kabir, Shahzad A. Sheikh

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The Orthogonal Frequency Division Multiplexing (OFDM) with high data rate, high spectral efficiency and its ability to mitigate the effects of multipath makes them most suitable in wireless application. Impulsive noise distorts the OFDM transmission and therefore methods must be investigated to suppress this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based adaptive impulsive noise suppressor for OFDM communication system is proposed. And a comparison with another adaptive algorithm is conducted. The state space model-dependent recursive parameters of proposed scheme enables to achieve steady state mean squared error (MSE), low bit error rate (BER), and faster convergence than that of some of existing algorithm.

Keywords: OFDM, impulsive noise, SSRLS, BER

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Authors: Linyu Wang, Furui Huo, Jianhong Xiang

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The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low SNR stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.

Keywords: OFDM, doubly selective, channel estimation, compressed sensing

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

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The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

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Authors: Moung Young Lee, Chul Gyu Song

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Photoacoustic imaging is the imaging technology that combines the optical imaging and ultrasound. This provides the high contrast and resolution due to optical imaging and ultrasound imaging, respectively. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer and digital acquisition (DAQ) board. There are two types of algorithm for reconstructing the photoacoustic signal. One is back-projection algorithm, the other is FFT algorithm. Especially, we used the non-uniform FFT algorithm. To evaluate the performance of our system and algorithms, we monitored two wires that stands at interval of 2.89 mm and 0.87 mm. Then, we compared the images reconstructed by algorithms. Finally, we monitored the two hairs crossed and compared between these algorithms.

Keywords: back-projection, image comparison, non-uniform FFT, photoacoustic tomography

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Authors: Fairouz Beggas

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Due to the large number of exchanges in the networks, the security of communications is essential. Most ways of keeping communication secure rely on encryption. In this work, a symmetric encryption technique is offered to encrypt and decrypt simple Arabic scripts based on a multi-level security. A proposed technique uses an idea of Playfair encryption with a larger table size and an additional layer of encryption to ensure more security. The idea of the proposed algorithm aims to generate a dynamic table that depends on a secret key. The same secret key is also used to create other secret keys to over-encrypt the plaintext in three steps. The obtained results show that the proposed algorithm is faster in terms of encryption/decryption speed and can resist to many types of attacks.

Keywords: arabic data, encryption, playfair, symmetric algorithm

Procedia PDF Downloads 84

Authors: Dipo Dunsin, Mohamed C. Ghanem, Karim Ouazzane

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Digital investigators often have a hard time spotting evidence in digital information. It has become hard to determine which source of proof relates to a specific investigation. A growing concern is that the various processes, technology, and specific procedures used in the digital investigation are not keeping up with criminal developments. Therefore, criminals are taking advantage of these weaknesses to commit further crimes. In digital forensics investigations, artificial intelligence is invaluable in identifying crime. It has been observed that an algorithm based on artificial intelligence (AI) is highly effective in detecting risks, preventing criminal activity, and forecasting illegal activity. Providing objective data and conducting an assessment is the goal of digital forensics and digital investigation, which will assist in developing a plausible theory that can be presented as evidence in court. Researchers and other authorities have used the available data as evidence in court to convict a person. This research paper aims at developing a multiagent framework for digital investigations using specific intelligent software agents (ISA). The agents communicate to address particular tasks jointly and keep the same objectives in mind during each task. The rules and knowledge contained within each agent are dependent on the investigation type. A criminal investigation is classified quickly and efficiently using the case-based reasoning (CBR) technique. The MADIK is implemented using the Java Agent Development Framework and implemented using Eclipse, Postgres repository, and a rule engine for agent reasoning. The proposed framework was tested using the Lone Wolf image files and datasets. Experiments were conducted using various sets of ISA and VMs. There was a significant reduction in the time taken for the Hash Set Agent to execute. As a result of loading the agents, 5 percent of the time was lost, as the File Path Agent prescribed deleting 1,510, while the Timeline Agent found multiple executable files. In comparison, the integrity check carried out on the Lone Wolf image file using a digital forensic tool kit took approximately 48 minutes (2,880 ms), whereas the MADIK framework accomplished this in 16 minutes (960 ms). The framework is integrated with Python, allowing for further integration of other digital forensic tools, such as AccessData Forensic Toolkit (FTK), Wireshark, Volatility, and Scapy.

Keywords: artificial intelligence, computer science, criminal investigation, digital forensics

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Authors: Cagri Memis, Muzaffer Kapanoglu

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The school bus routing problem (SBRP) is a variant of the Vehicle Routing Problem (VRP) classified as a location-allocation-routing problem. In this study, the SBRP is decomposed into two sub-problems: (1) bus route generation and (2) bus stop selection to solve large instances of the SBRP in reasonable computational times. To solve the first sub-problem, we propose a genetic algorithm to generate bus routes. Once the routes have been fixed, a sub-problem remains of allocating students to stops considering the capacity of the buses and the walkability constraints of the students. While the exact method solves small-scale problems, treating large-scale problems with the exact method becomes complex due to computational problems, a deficiency that the genetic algorithm can overcome. Results obtained from the proposed approach on 150 instances up to 250 stops show that the matheuristic algorithm provides better solutions in reasonable computational times with respect to benchmark algorithms.

Keywords: genetic algorithm, matheuristic, school bus routing problem, vehicle routing problem

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Authors: Akintade O. Adeboyejo, Edwin O. Clarke, Oluwatoyin Aderinola

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The present study is on the sub-lethal toxicity of industrial effluents (IE) from the environment of Ologe Lagoon, Lagos, Nigeria on the African catfish fingerlings Clarias gariepinus. The fish were cultured in varying concentrations of industrial effluents: 0% (control), 5%, 15%, 25%, and 35%. Trials were carried out in triplicates for twelve (12) weeks. The culture system was a static renewable bioassay and was carried out in the fisheries laboratory of the Lagos State University, Ojo-Lagos. Weekly physico-chemical parameters: Temperature (0C), pH, Conductivity (ppm) and Dissolved Oxygen (DO in mg/l) were measured in each treatment tank. Length (cm) and weight (g) data were obtained weekly and used to calculate various growth parameters: mean weight gain (MWG), percentage weight gain (PWG), daily weight gain (DWG), specific growth rate (SGR) and survival. Haematological (Packed Cell Volume (PCV), Red blood cells (RBC), White Blood Cell (WBC), Neutrophil and Lymphocytes etc) and histological alterations were measured after 12 weeks. The physico-chemical parameters showed that the pH ranged from 7.82±0.25–8.07±0.02. DO range from 1.92±0.66-4.43±1.24 mg/l. The conductivity values increased with increase in concentration of I.E. While the temperature remained stable with mean value range between 26.08±2.14–26.38±2.28. The DO showed significant differences at P<0.05. There was progressive increase in length and weight of fish during the culture period. The fish placed in the control had highest increase in both weight and length while fish in 35% had the least. MWG ranged from 16.59–35.96, DWG is from 0.3–0.48, SGR varied from 1.0–1.86 and survival was 100%. Haematological results showed that C. gariepinus had PCV ranging from 13.0±1.7-27.7±0.6, RBC ranged from 4.7±0.6–9.1±0.1, and Neutrophil ranged from 26.7±4.6–61.0±1.0 amongst others. The highest values of these parameters were obtained in the control and lowest at 35%. While the reverse effects were observed for WBC and lymphocytes. This study has shown that effluents may affect the health status of the test organism and impair vital processes if exposure continues for a long period of time. The histological examination revealed several lesions as expressed by the gills and livers. The histopathology of the gills in the control tanks had normal tissues with no visible lesion, but at higher concentrations, there were: lifting of epithelium, swollen lamellae and gill arch infiltration, necrosis and gill arch destruction. While in the liver: control (0%) show normal liver cells, at higher toxic level, there were: vacoulation, destruction of the hepatic parenchyma, tissue becoming eosinophilic (i.e. tending towards Carcinogenicity) and severe disruption of the hepatic cord architecture. The study has shown that industrial effluents from the study area may affect fish health status and impair vital processes if exposure continues for a long period of time even at lower concentrations (Sublethal).

Keywords: sublethal toxicity, industrial effluents, clarias gariepinus, ologe lagoon

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Authors: Sawsan Eissa, Momen Gharib, Omnia Kabbany

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A flushing numerical study has been performed for intended artificial islands on the Persian Gulf coast in Abu Dhabi, UAE. The island masterplan was tested for flushing using the DELFT 3D hydrodynamic model, and it was found that its residence time exceeds the acceptable PIANC flushing Criteria. Therefore, a number of mitigation measures were applied and tested one by one using the flushing model. Namely, changing the location of the entrance opening, dredging, removing part of the mangrove existing in the near vicinity to create a channel, removing the mangrove altogether, using culverts of different numbers and locations, and pumping at selected points. The pumping option gave the best solution, but it was disregarded due to high capital and running costs. Therefore, it opted for a combination of other solutions, including removing mangroves, introducing culverts, and adjusting island boundaries and types of protection.

Keywords: hydrodynamics, flushing, delft 3d, Persian Gulf, artificial islands.

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Authors: Sirwe Ghaderpour, Nasrollah Ahmadifard, Naser Agh, Zakaria Vahabzadeh

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Rotifers are used in many hatcheries for feeding the earliest stages of fish larvae and crustaceans due to their small size, slow movements, fast reproduction, and easy cultivation. One of the disadvantages of using rotifers as live prey is their lower content of some nutrients compared to copepods, so it is necessary to increase the amounts of these nutrients by means of enrichment. Minerals are a group of micro-elements, essential to fish, that is lacking in the rotifers, for example, selenium (30 fold) and zinc (5 fold) are present in lower quantities than the minimum amounts found in copepods. In this study, the condensed Isochrysis aff. galbana (T-ISO) and Nannochloropsis oculata were suspended at concentration of 18 × 109 cell mL⁻¹ of water with 20 ppt of salinity. Four different levels (0, 1000, 2000, and 4000 mg L⁻¹) of each Na₂SeO₃ and ZnSO₄.7H₂O separately were prepared, and 1 mL of each stock was poured to the algae enrichment vessels for 1 h simultaneously. After that, the material was centrifuged (at 4000 rpm for 5 min), and the precipitated enriched algae was used for rotifer feeding. The contents of Se, Zn, Cu, and Mn were determined in enriched microalgae and rotifer by Atomic absorption. The highest content of both minerals was observed in 0.4 Zn + 0.4 Se treatment and also rotifer enriched with these enriched microalgae. The enrichment of microalgae with Zn and Se does not affect the content of Cu in the microalgae. Also, the content of Cu in rotifer fed with the enriched microalgae showed the highest Cu content in the treatments than the control. But, the enrichment with both minerals had a negative effect on the content Mn in enriched mixed microalgae except 0.4 Zn + 0.4 Se. The Mn content in enriched rotifer decreased in the treatments than the control except for 0.1 Zn + 0.1 Se. There was no significant effect on rotifer growth in combined enrichment with both minerals (p < 0.05). Overall, rotifers enrichment with Se and Zn mixed microalgae resulted in increasing Se, Zn, and Cu. This will allow Se and Zn microalgae enriched rotifers to be used as the minerals delivery method for fish larvae nutritional requirements.

Keywords: enrichment, larvae, microalgae, mineral, rotifer

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Authors: Dewan Ali Ahsan

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Hilsa (Tenualosa ilisha) is one of the most important anadromous fish species of the trans-boundary ecosystem of Bangladesh, India and Myanmar. Hilsa is not only an economically important species specially for Bangladesh and India, but also for the integral part of the culture of the Bangladesh and India. This flag-ship species in Bangladesh contributed alone of 10.82% of the total fish production of the country and about 75% of world’s total catch of hilsa comes from Bangladesh alone. As hilsa is an anadromous fish, it migrates from the Bay of Bengal to rivers for spawning, nursing and growing and for all of these purposes hilsa needs freshwaters. Ripe broods prefer turbid, fast flowing freshwater for spawning but young prefer clear and slow flowing freshwater. Climate change (salinity intrusion, sea level rise, temperature rise, impact of fresh water flow), unplanned developmental activities and other anthropogenic activities all together are severely damaging the hilsa stock and its habitats. So, climate change and human interferences are predicted to have a range of direct and indirect impacts on marine and freshwater hilsa fishery, with implications for fisheries-dependent economies, coastal communities and fisherfolk. The present study identified that salinity intrusion, siltation in river bed, decrease water flow from upstream, fragmentation of river in dry season, over exploitation, use of small mesh nets are the major reasons to affect the upstream migration of hilsa and its sustainable management. It has been also noticed that Bangladesh government has taken some actions for hilsa management. Government is trying to increase hilsa production not only by conserving jatka (juvenile hilsa) but also protecting the brood hilsa during the breeding seasons by imposing seasonal ban on fishing, restricted mesh size etc. Unfortunately, no such management plans are available for Indian and Myanmar territory. As hilsa is a highly migratory trans-boundary fish in the Bay of Bengal (and all of these countries share the same stock), it is essential to adopt a joint management policy (by Bangladesh-India-Myanmar) for the sustainable management for the hilsa stock.

Keywords: hilsa, climate change, south-east Asia, fishery management

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Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

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Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: agricultural mobile robot, image processing, path recognition, hough transform

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Authors: Amirhossein Safi

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Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Keywords: internet of things, security, hybrid algorithm, privacy

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Authors: Keri Alhadi Ighwela, Aziz Bin Ahmad, A. B. Abol-Munafi

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Three purified diets were formulated using fish meal, soya bean, wheat flour, palm oil, minerals and maltose. The carbohydrate in the diets was increased from 5 to 15% by changing the cellulose content to study the effect of dietary carbohydrate level on the growth parameters of Nile tilapia Oreochromis niloticus.The protein and the lipid contents were kept constant in all the diets. The results showed that, weight gain, protein efficiency ratio, net protein utilisation and hepatosomatic index of fish fed the diet containing 15% cellulose were the lowest among all groups. Addition, the fish fed the diet containing 5% cellulose had the best specific growth rate, and food conversion ratio. While, there was no effect of the dietary cellulose levels on condition factor and survival rate. These results indicate that Nile tilapia fingerlings are able to utilize dietary cellulose does not exceed 10% in their feed for optimum growth.

Keywords: dietary cellulose, growth parameters, oreochromis niloticus, purified diets

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Authors: G. O. Fakunmoju, F. A. Fakunmoju

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The experiment was conducted to evaluate the growth response of African giant catfish (Clarias gariepinus) fed with varying levels of Galawaste based diet, 300 clarias gariepinus fingerlings with mean body weight 10 ± 0.1g were assigned to five (treatment levels in which Gala waste meal replaced maize at 0, 25, 50, 75, 100% respectively in a completely randomized design. The trial fish were fed at 5% body weight daily for a period of 84 days. Data collected showed that body weight gain increased with an increase gala waste meal in the diet (P<0.05). The similar observation was recorded for feed intake but there was no significant (P>0.05) difference in feed conversion ratio among the treatments. All the fish fed the test ingredients performed better than the control groups hence, Gala waste meal could be recommended as a dietary supplement in the diet of African Giant Catfish.

Keywords: Galawaste meal, Clarias gariepinus, replacement, growth performance, diets

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Authors: Redhouane Benfares, Kamel Boudjemaa, Affaf Kord, Sonia Messis, Linda Farai, Belkacem Guenachi, Kherarba Maha, Jaroslava ŠVarc-Gajić

Abstract:

In recent years valorization of biowaste has attracted a lot of attention worldwide owing to its high nutritional value and low price. In this work, biowaste of animal (sardines) and plant (tomato) biowaste was used to formulate a new feed for red tilapia that showed to be competitive in its price, and zootechnical performance in comparison to commercially available tilapia feeds. Mathematical modelling was used to formulate optimal feed composition with favorable chemical composition and the lowest price. Formulated feed had high protein content (40.76%) and an energy value of 279.6 Kcal/100 g. Optimised feed was manufactured and compared to commercially available reference feed with respect to feeding intake, feed efficiency, the specific growth rate of fingerlings of Tilapia sp, and, most important, zootechnical parameters. With a fish survival rate of 100% calculated feed conversion index for the formulated feed was 2.7.

Keywords: conversion index, fish waste, formulated feed, tomato waste

Procedia PDF Downloads 147

Authors: Soumitr Sanjay Dubey, Shubhajit Roy Chowdhury, Rahul Shrestha

Abstract:

In this paper, we have presented a novel approach of calculating eigenvalues of any matrix for the first time on Field Programmable Gate Array (FPGA) using Triangular Systolic Arra (TSA) architecture. Conventionally, additional computation unit is required in the architecture which is compliant to the algorithm for determining the eigenvalues and this in return enhances the delay and power consumption. However, recently reported works are only dedicated for symmetric matrices or some specific case of matrix. This works presents an architecture to calculate eigenvalues of any matrix based on QR algorithm which is fully implementable on FPGA. For the implementation of QR algorithm we have used TSA architecture, which is further utilising CORDIC (CO-ordinate Rotation DIgital Computer) algorithm, to calculate various trigonometric and arithmetic functions involved in the procedure. The proposed architecture gives an error in the range of 10−4. Power consumption by the design is 0.598W. It can work at the frequency of 900 MHz.

Keywords: coordinate rotation digital computer, three angle complex rotation, triangular systolic array, QR algorithm

Procedia PDF Downloads 407

Authors: Rachid Dehini, Brahim Berbaoui

Abstract:

The main objectives of shunt active power filter (SAPF) is to preserve the power system from unwanted harmonic currents produced by nonlinear loads, as well as to compensate the reactive power. The aim of this paper is to present a (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: SAPF, harmonics current, photovoltaic cells, MPPT, artificial neural networks (ANN)

Procedia PDF Downloads 329