Search results for: restoring algorithm

Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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Authors: Othmane Bouferroum, Malika Boudraa

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In this study, a dual exponential model for CV formant transition is derived from locus theory of speech perception. Then, an algorithm for automatic vowel and consonant’s target formant frequency detection is developed and tested on real speech. The results show that vowels and consonants are detected through transitions rather than their small stable portions. Also, vowel reduction is clearly observed in our data. These results are confirmed by the observations made in perceptual experiments in the literature.

Keywords: acoustic invariance, coarticulation, formant transition, locus equation

Procedia PDF Downloads 267

Authors: Swathi Sampath, V. Kalaichelvi

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The assessment of the risk posed by a borrower to a lender is one of the common problems that financial institutions have to deal with. Consumers vying for a mortgage are generally compared to each other by the use of a number called the Credit Score, which is generated by applying a mathematical algorithm to information in the applicant’s credit report. The higher the credit score, the lower the risk posed by the candidate, and the better he is to be taken on by the lender. The objective of the present work is to use fuzzy logic and linguistic rules to create a model that generates Credit Scores.

Keywords: credit scoring, fuzzy logic, mortgage, risk assessment

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Authors: Harihara Prakash Ramanathan, Daksha Mishra, Ankita Dhaduk

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Relevance: This qualitative study will educate the clinician in putting into practice the advanced method of movement science in restoring the function. Purpose: The purpose of this study is to compare the effectiveness of Active Release Technique and myofascial release technique on range of motion, neck function and pain in patients with upper trapezius spasm. Methods/Analysis: The study was approved by the institutional Human Research and Ethics committee. This study included sixty patients of age group between 20 to 55 years with upper trapezius spasm. Patients were randomly divided into two groups receiving Active Release Technique (Group A) and Myofascial Release Technique (Group B). The patients were treated for 1 week and three outcome measures ROM, pain and functional level were measured using Goniometer, Visual analog scale(VAS), Neck disability Index Questionnaire(NDI) respectively. Paired Sample 't' test was used to compare the differences of pre and post intervention values of Cervical Range of motion, Neck disability Index, Visual analog scale of Group A and Group B. Independent't' test was used to compare the differences between two groups in terms of improvement in cervical range of motion, decrease in visual analogue scale(VAS), decrease in Neck disability index score. Results: Both the groups showed statistically significant improvements in cervical ROM, reduction in pain and in NDI scores. However, mean change in Cervical flexion, cervical extension, right side flexion, left side flexion, right side rotation, left side rotation, pain, neck disability level showed statistically significant improvement (P < 0. 05)) in the patients who received Active Release Technique as compared to Myofascial release technique. Discussion and conclusions: In present study, the average improvement immediately post intervention is significantly greater as compared to before treatment but there is even more improvement after seven sessions as compared to single session. Hence, this proves that several sessions of Manual techniques are necessary to produce clinically relevant results. Active release technique help to reduce the pain threshold by removing adhesion and promote normal tissue extensibility. The act of tensioning and compressing the affected tissue both with digital contact and through the active movement performed by the patient can be a plausible mechanism for tissue healing in this study. This study concluded that both Active Release Technique (ART) and Myofascial release technique (MFR) are equally effective in managing upper trapezius muscle spasm, but more improvement can be achieved by Active Release Technique (ART). Impact and Implications: Active Release Technique can be adopted as mainstay of treatment approach in treating trapezius spasm for faster relief and improving the functional status.

Keywords: trapezius spasm, myofascial release, active release technique, pain

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Authors: F. Boufera, F. Debbat

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This paper deals with an approach based on limit-cycles method for the problem of obstacle avoidance of mobile robots in unknown environments for any form of obstacles. The purpose of this approach is the improvement of limit-cycles method in order to obtain safe and flexible navigation. The proposed algorithm has been successfully tested in different configuration on simulation.

Keywords: mobile robot, navigation, avoidance of obstacles, limit-cycles method

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Authors: Mathuravech Thanaphon, Thephasit Nat

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The Electricity Generating Authority of Thailand (EGAT) is focusing on expanding its pumped storage hydropower (PSH) capacity to increase the reliability of the system during peak demand and allow for greater integration of renewables. To achieve this requirement, Thailand will have to double its current renewable electricity production. To address the challenges of balancing supply and demand in the grid with increasing levels of RE penetration, as well as rising peak demand, EGAT has already been studying the potential for additional PSH capacity for several years to enable an increased share of RE and replace existing fossil fuel-fired generation. In addition, the role that pumped-storage hydropower would play in fulfilling multiple grid functions and renewable integration. The proposed sites for new PSH would help increase the reliability of power generation in Thailand. However, most of the electricity generation will come from RE, chiefly wind and photovoltaic, and significant additional Energy Storage capacity will be needed. In this paper, the impact of integrating the PSH system on the adequacy of renewable rich power generating systems to reduce the thermal power generating units is investigated. The variations of system adequacy indices are analyzed for different PSH-renewables capacities and storage levels. Power Development Plan 2018 rev.1 (PDP2018 rev.1), which is modified by integrating a six-new PSH system and RE planning and development aftermath in 2030, is the very challenge. The system adequacy indices through power generation are obtained using Multi-Objective Genetic Algorithm (MOGA) Optimization. MOGA is a probabilistic heuristic and stochastic algorithm that is able to find the global minima, which have the advantage that the fitness function does not necessarily require the gradient. In this sense, the method is more flexible in solving reliability optimization problems for a composite power system. The optimization with hourly time step takes years of planning horizon much larger than the weekly horizon that usually sets the scheduling studies. The objective function is to be optimized to maximize RE energy generation, minimize energy imbalances, and minimize thermal power generation using MATLAB. The PDP2018 rev.1 was set to be simulated based on its planned capacity stepping into 2030 and 2050. Therefore, the four main scenario analyses are conducted as the target of renewables share: 1) Business-As-Usual (BAU), 2) National Targets (30% RE in 2030), 3) Carbon Neutrality Targets (50% RE in 2050), and 5) 100% RE or full-decarbonization. According to the results, the generating system adequacy is significantly affected by both PSH-RE and Thermal units. When a PSH is integrated, it can provide hourly capacity to the power system as well as better allocate renewable energy generation to reduce thermal generations and improve system reliability. These results show that a significant level of reliability improvement can be obtained by PSH, especially in renewable-rich power systems.

Keywords: pumped storage hydropower, renewable energy integration, system adequacy, power development planning, RE100, multi-objective genetic algorithm

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Authors: Peli̇n Yilmaz, Gi̇zemnur Yildiz Uysal, Emi̇ne Bi̇rci̇, Berk Özcan, Burak Koca, Ehsan Tuzcuoğlu, Fati̇h Kasap

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Development of Energy Efficient Programs (EEP) is one of the most significant trends in the wet appliance industry of the recent years. Thanks to the EEP, the energy consumption of a washing machine as one of the most energy-consuming home appliances can shrink considerably, while its washing performance and the textile hygiene should remain almost unchanged. Here in, the goal of the present study is to achieve an optimum EEP algorithm providing excellent textile hygiene results as well as cleaning performance in a domestic washing machine. In this regard, steam-pretreated cold wash approach with a combination of innovative algorithm solution in a relatively short washing cycle duration was implemented. For the parametric study, steam exposure time, washing load, total water consumption, main-washing time, and spinning rpm as the significant parameters affecting the textile hygiene and cleaning performance were investigated within a Design of Experiment study using Minitab 2021 statistical program. For the textile hygiene studies, specific loads containing the contaminated cotton carriers with Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa bacteria were washed. Then, the microbial removal performance of the designed programs was expressed as log reduction calculated as a difference of microbial count per ml of the liquids in which the cotton carriers before and after washing. For the cleaning performance studies, tests were carried out with various types of detergents and EMPA Standard Stain Strip. According to the results, the optimum EEP program provided an excellent hygiene performance of more than 2 log reduction of microorganism and a perfect Washing Efficiency Index (Iw) of 1.035, which is greater than the value specified by EU ecodesign regulation 2019/2023.

Keywords: washing machine, energy efficient programs, hygiene, washing efficiency index, microorganism, escherichia coli, staphylococcus aureus, pseudomonas aeruginosa, laundry

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Authors: Tomáš Bublík, Miroslav Virius

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This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and sub graph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.

Keywords: AST, Java, tree matching, scripthon source code recognition

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Authors: DoHyeung Kim, DaeHee Seo, ByungDoo Kim, ByungGil Lee

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As many recent researches being implemented in aviation and maritime aspects, strong doubts have been raised concerning the reliability of the estimation of collision risk. It is shown that using position and velocity of objects can lead to imprecise results. In this paper, therefore, a new approach to the estimation of collision risks using pose and shape of objects is proposed. Simulation results are presented validating the accuracy of the new criterion to adapt to collision risk algorithm based on fuzzy logic.

Keywords: collision risk, pose, shape, fuzzy logic

Procedia PDF Downloads 525

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Ali Mohammad Mobaser Azad, Alireza Akhlaghinia

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Blockchain is changing our world and launching a new generation of decentralized networks. Meanwhile, Blockchain-based networks like Ethereum have been created and they will facilitate these processes using tools like smart contracts. The Ethereum has fundamental structures, each of which affects the activity of the nodes. Our purpose in this paper is to review similar research and examine various components to demonstrate the performance of the Ethereum network and to do this, and we used the data published by the Ethereum Foundation in different time spots to examine the number of changes that determine the status of network performance. This will help other researchers understand better Ethereum in different situations.

Keywords: blockchain, ethereum, smart contract, decentralization consensus algorithm

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Authors: Rajkumar Ghosh

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Fluoride contamination is a growing concern in various regions across the globe, including North 24 Parganas in West Bengal, India. The presence of excessive fluoride in the environment can have detrimental effects on crops, soil quality, and water resources. This note aims to shed light on the implications of fluoride contamination and its impact on the agricultural sector in North 24 Parganas. The agricultural lands in North 24 Parganas have been significantly affected by fluoride contamination, leading to adverse consequences for crop production. Excessive fluoride uptake by plants can hinder their growth, reduce crop yields, and impact the quality of agricultural produce. Certain crops, such as paddy, vegetables, and fruits, are more susceptible to fluoride toxicity, resulting in stunted growth, leaf discoloration, and reduced nutritional value. Fluoride-contaminated water, often used for irrigation, contributes to the accumulation of fluoride in the soil. Over time, this can lead to soil degradation and reduced fertility. High fluoride levels can alter soil pH, disrupt the availability of essential nutrients, and impair microbial activity critical for nutrient cycling. Consequently, the overall health and productivity of the soil are compromised, making it increasingly challenging for farmers to sustain agricultural practices. Fluoride contamination in North 24 Parganas extends beyond the soil and affects water resources as well. The excess fluoride seeps into groundwater, making it unsafe for consumption. Long-term consumption of fluoride-contaminated water can lead to various health issues, including dental and skeletal fluorosis. These health concerns pose significant risks to the local population, especially those reliant on contaminated water sources for their daily needs. Addressing fluoride contamination requires concerted efforts from various stakeholders, including government authorities, researchers, and farmers. Implementing appropriate water treatment technologies, such as defluoridation units, can help reduce fluoride levels in drinking water sources. Additionally, promoting alternative irrigation methods and crop diversification strategies can aid in mitigating the impact of fluoride on agricultural productivity. Furthermore, creating awareness among farmers about the adverse effects of fluoride contamination and providing access to alternative water sources are crucial steps toward safeguarding the health of the community and sustaining agricultural activities in the region. Fluoride contamination poses significant challenges to crop production, soil health, and water resources in North 24 Parganas, West Bengal. It is imperative to prioritize efforts to address this issue effectively and implement appropriate measures to mitigate fluoride contamination. By adopting sustainable practices and promoting awareness, the community can work towards restoring the agricultural productivity, soil quality and ensuring access to safe drinking water in the region.

Keywords: fluoride contamination, drinking water, toxicity, soil health

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Adriana Anselmo Oliveira

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The present project showcases a tile work from the Franco-Portuguese artist Maria Helena Vieira da Silva (1908-1992). It is a set of 8 panels composed of figurative and geometric tiles, with extra tiles framing nearby doors and windows in a study room in the (UFRRJ, Universidade Federal Rural do Rio de Janeiro). The aforementioned work was created between 1942 and 1943, during the artist's 6 year exile in the Brazilian city. This one-of-a-kind tileset was designed and made by Vieira da Silva between 1942 and 1943. Over the years, several units were lost, which led to their replacement in the nineties. However, these replacements don't do justice to the original work of art. In 2007, a project was initiated to fully repair and maintain the set. Three panels are removed and restored, but the project is halted. To this day, the three fully restored panels remain in boxes. In 2016 a new restoration project is submitted by the (Faculdade de Belas Artes da Universidade de Lisboa) in collaboration with de (Fundacão Árpád Szenes-Vieira da Silva). There are many varied opinions on restoring and conserving older pieces of art, however, we have the moral duty to safeguard the original materials used by the artist along with the artists original vision and also to care for the future generations of students who will use the space in which the tile-work was inserted. Many tiles have been replaced by white tiles, tiles with a divergent colour pallet and technique, and in a few cases, the incorrect place or way around. These many factors make it increasingly difficult to maintain the artists original vision and destroy and chance of coherence within the artwork itself. The conservative technician cannot make new images to fill the empty spaces or mark the remaining images with their own creative input. with reliable photographic documentation that can provide us with the necessary vision to allow us to proceed with an accurate reconstruction, we have the obligation to proceed and return the piece of art to its true form, as in its current state, it is impossible to maintain its original glory. Using the information we have, we must find a way to differentiate the original tiles from the reconstructions in order to recreate and reclaim the original message from the artist. The objective of this project is to understand the significance of tiles in Vieira da Silva's art as well as the influence they had on the artist's pictorial language since the colour definition on tile work is vastly different from the painting process as the materials change during their merger. Another primary goal is to understand what the previous interventions achieved besides increasing the artworks durability. The main objective is to submit a proposal that can salvage the artist's visual intention and supports it for posteriority. In summary, this proposal goes further than the usual conservative interventions as it intends to recreate the original artistic worth, prioritising the aesthetics and keeping its soul alive.

Keywords: Vieira da Silva, tiles, conservation, restoration

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Authors: R. Loukil, M. Chtourou, T. Damak

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This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.

Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state

Procedia PDF Downloads 566

Authors: Chin-Chen Chang, I-Ta Lee, Tsung-Ta Ke, Wen-Kai Tai

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Common methods for resizing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image resizing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

Keywords: energy map, visual saliency, gradient map, seam carving

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Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

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Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

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Authors: Apurva Patil, Maithilee Kulkarni, Ashay Aswale

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This paper proposes an algorithm to develop the kinematic model of a 5 DOF robot arm. The formulation of the problem is based on finding the D-H parameters of the arm. Brute Force iterative method is employed to solve the system of non linear equations. The focus of the paper is to obtain the accurate solutions by reducing the root mean square error. The result obtained will be implemented to grip the objects. The trajectories followed by the end effector for the required workspace coordinates are plotted. The methodology used here can be used in solving the problem for any other kinematic chain of up to six DOF.

Keywords: 5 DOF robot arm, D-H parameters, inverse kinematics, iterative method, trajectories

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Authors: Bououden Soraya

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This paper aims to study the existence of the change of coordinates which permits to transform a class of nonlinear dynamical systems into the so-called nonlinear observer canonical form (NOCF). Moreover, an algorithm to construct such a change of coordinates is given. Based on this form, we can design an observer with a linear error dynamic. This enables us to estimate the state of a nonlinear dynamical system. A concrete example (biological model) is provided to illustrate the feasibility of the proposed results.

Keywords: nonlinear observer canonical form, observer, design, gene regulation, gene expression

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Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: Mohammad Esmaeilpour

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One of the important open problems in the field of medical image processing is detection and quantification of small changes. In this poster, we try to investigate that, how the algebraic decomposition techniques can be used for semiautomatically detecting and quantifying subtle changes in Magnetic Resonance (MR) neuroimaging volumes. We mostly focus on the low-rank values of the matrices achieved from decomposing MR image pairs during a period of time. Besides, a skillful neuroradiologist will help the algorithm to distinguish between noises and small changes.

Keywords: magnetic resonance neuroimaging, subtle change detection and quantification, algebraic decomposition, basis functions

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Authors: Tagel Gebrehiwot, Carolina Castilla

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Food insecurity and child malnutrition are among the most critical issues in Ethiopia. Accordingly, different reform programs have been carried to improve household food security. The Food Security Program (FSP) (among others) was introduced to combat the persistent food insecurity problem in the country. The FSP combines a safety net component called the Productive Safety Net Program (PSNP) started in 2005. The goal of PSNP is to offer multi-annual transfers, such as food, cash or a combination of both to chronically food insecure households to break the cycle of food aid. Food or cash transfers are the main elements of PSNP. The case for cash transfers builds on the Sen’s analysis of ‘entitlement to food’, where he argues that restoring access to food by improving demand is a more effective and sustainable response to food insecurity than food aid. Cash-based schemes offer a greater choice of use of the transfer and can allow a greater diversity of food choice. It has been proven that dietary diversity is positively associated with the key pillars of food security. Thus, dietary diversity is considered as a measure of household’s capacity to access a variety of food groups. Studies of dietary diversity among Ethiopian rural households are somewhat rare and there is still a dearth of evidence on the impact of PSNP on household dietary diversity. In this paper, we examine the impact of the Ethiopia’s PSNP on household dietary diversity and child nutrition using panel household surveys. We employed different methodologies for identification. We exploit the exogenous increase in kebeles’ PSNP budget to identify the effect of the change in the amount of money households received in transfers between 2012 and 2014 on the change in dietary diversity. We use three different approaches to identify this effect: two-stage least squares, reduced form IV, and generalized propensity score matching using a continuous treatment. The results indicate the increase in PSNP transfers between 2012 and 2014 had no effect on household dietary diversity. Estimates for different household dietary indicators reveal that the effect of the change in the cash transfer received by the household is statistically and economically insignificant. This finding is robust to different identification strategies and the inclusion of control variables that determine eligibility to become a PSNP beneficiary. To identify the effect of PSNP participation on children height-for-age and stunting we use a difference-in-difference approach. We use children between 2 and 5 in 2012 as a baseline because by then they have achieved long-term failure to grow. The treatment group comprises children ages 2 to 5 in 2014 in PSNP participant households. While changes in height-for-age take time, two years of additional transfers among children who were not born or under the age of 2-3 in 2012 have the potential to make a considerable impact on reducing the prevalence of stunting. The results indicate that participation in PSNP had no effect on child nutrition measured as height-for-age or probability of beings stunted, suggesting that PSNP should be designed in a more nutrition-sensitive way.

Keywords: continuous treatment, dietary diversity, impact, nutrition security

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Authors: Benzegaou Ali, Brani Benabderrahmane

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This work describes a numerical study of the TOX–clinching process using diffuse elements. A computer code baptized SEMA "Static Explicit Method Analysis" is developed to simulate the clinch joining process. The FE code is based on an Updated Lagrangian scheme. The used resolution method is based on an explicit static approach. The integration of the elasto-plastic behavior law is realized with an algorithm of Simo and Taylor. The tools are represented by plane facets.

Keywords: diffuse elements, numerical simulation, clinching, contact, large deformation

Procedia PDF Downloads 357

Authors: Noorulain Khalid, Unsaar Hayat, Muhammad Chaudhary, Christos Iosifidis, Felipe Dhawahir-Scala, Fiona Carley

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Dry eye disease (DED) is a common condition seen in the emergency eye department (EED) at Manchester Royal Eye Hospital (MREH). However, there is variability in the prescription of lubricating eye drops among different healthcare providers. The aim of this study was to develop an up-to-date, standardized algorithm for the prescription of lubricating eye drops in the EED at MREH based on international and national guidelines. The study also aimed to assess the impact of implementing the guideline on the rate of inappropriate lubricant prescriptions. Primarily, the impact was to be assessed in the form of the appropriateness of prescriptions for patients’ DED. The impact was secondary to be assessed through analysis of the cost to the hospital. Data from 845 patients who attended the EED over a 3-month period were analyzed, and 157 patients met the inclusion and exclusion criteria. After conducting a review of the literature and collaborating with the corneal team, an algorithm for the prescription of lubricants in the EED was developed. Three plan-do-study-act (PDSA) cycles were conducted, with interventions such as emails, posters, in-person reminders, and education for incoming trainees. The appropriateness of prescriptions was evaluated against the guidelines. Data were collected from patient records and analyzed using statistical methods. The appropriateness of prescriptions was assessed by comparing them to the guidelines and by clinical correlation with a specialized registrar. The study found a substantial improvement in the number of appropriate prescriptions, with an increase from 55% to 93% over the three PDSA cycles. There was additionally a 51% reduction in expenditure on lubricant prescriptions, resulting in cost savings for the hospital (approximate saving of £50/week). Theoretical importance: Appropriate prescription of lubricating eye drops improves disease management for patients and reduces costs for the hospital. The development and implementation of a standardized guideline facilitate the achievement of these goals. Conclusion: This study highlights the inconsistent management of DED in the EED and the potential lack of training in this area for healthcare providers. The implementation of a standardized, easy-to-follow guideline for lubricating eye drops can help to improve disease management while also resulting in cost savings for the hospital.

Keywords: lubrication, dry eye disease, guideline, prescription

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Authors: Ali Bagherinia

Abstract:

Efficient task scheduling method can meet users' requirements, and improve the resource utilization, then increase the overall performance of the cloud computing environment. Cloud computing has new features, such as flexibility, virtualization and etc., in this paper we propose a two levels task scheduling method based on load balancing in cloud computing. This task scheduling method meet user's requirements and get high resource utilization, that simulation results in CloudSim simulator prove this.

Keywords: cloud computing, task scheduling, virtualization, SLA

Procedia PDF Downloads 397

Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad

Abstract:

This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.

Keywords: MANET, AODV, malicious node, OPNET

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Authors: Xabier Olaz Moratinos

Abstract:

Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina

Abstract:

In this paper, we propose heuristic for dynamic communications mapping that considers the placement of communications in order to optimize the overall performance. The mapping technique uses a newly proposed Algorithm to place communications between the tasks. The placement we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed mapping approach provides significant performance improvements when compared to those using static routing.

Keywords: Multi-Processor Systems-on-Chip (MPSoCs), Network-on-Chip (NoC), heterogeneous architectures, dynamic mapping heuristics

Procedia PDF Downloads 526

Authors: Lisa Tragbar

Abstract:

Since the Rio declaration, the agreement resulting from the Earth Summit in 1992, the UN member states acknowledge that peace and environmental protection are deeply linked to each other. It has also been made clear by Contemporary Peace research since the early 2000 that the lack of natural resources increases conflicts, as well as potential war conflicts (general environmental conflict thesis). I argue that peace ethics need to reconsider the role of the environment in peace ethics, from conflict prevention to peacebuilding. Sumak kawsay is a concept that offers a non-anthropocentric perspective on the subject. Several Contemporary Peace Ethicists don’t take environmental peace sufficiently into account. 1. The Peace theorist Johan Galtung famously argues that positive peace depends mostly on social, economic and political factors, as institutional structures establish peace. Galtung has a relational approach to peace, yet only between human interactors. 2. Michael Fox claims in his anti-war argument to consider nonhuman entities in conflicts. Because of their species interrelation, humans cannot decide on the fate of other species. 3. Although Mark Woods considers himself a peace ecologist, following Reichberg and Syse, and argues from a duty-based perspective towards nature, he mostly focuses on the protection of the environment during war conflicts. I want to focus on a non-anthropocentric view to argue that the environment is an entity of human concern in order to construct peace. Based on the premises that the lack of natural resources create tensions that play a significant part in international conflicts and these conflicts are potential war conflicts, I argue that a non-anthropocentric account to peace ethics is an indispensable perspective towards the recovery of these resources and therefore the reduction of war conflicts. Sumak kawsay is an approach contributing to a peaceful environment, which can play a crucial role in international peacekeeping operations. To emphasize sumak kawsay in peace ethics, it is necessary to explain what this principle includes and how it renews Contemporary Peace ethics. The indigenous philosophy of life of the Andean Quechua philosophy in Ecuador and varities from other countries from the Global South include a holistic real-world vision that contains concepts like the de-hierarchization of humans and nature as well as the reciprocity principle towards nature. Sumak kawsay represents the idea of the intrinsic value of nature and an egalitarian way of life and interconnectedness between human and nonhuman entities, which has been widely neglected in Traditional War and Peace Ethics. If sumak kawsay is transferred to peacekeeping practices, peacekeepers have restorative duties not only towards humans, but also towards nature. Resource conservation and environmental protection are the first step towards a positive peace. By recognising that healthy natural resources contribute to peacebuilding, by restoring balance through compensatory justice practices like recovery, by fostering dialogue between peacekeeping forces and by entitling ecosystems with rights natural resources and environmental conflicts are more unlikely to happen. This holistic approach pays nature sufficient attention and can contribute to a positive peace.

Keywords: environment, natural resources, peace, Sumak Kawsay

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Authors: Kenza Aida Amara, Bachir Djebbar

Abstract:

We treat the two-dimensional bin packing problem which involves packing a given set of rectangles into a minimum number of larger identical rectangles called bins. This combinatorial problem is NP-hard. We propose a pretreatment for the oriented version of the problem that allows the valorization of the lost areas in the bins and the reduction of the size problem. A heuristic method based on the strategy first-fit adapted to this problem is presented. We present an approach of resolution by bee colony optimization. Computational results express a comparison of the number of bins used with and without pretreatment.

Keywords: bee colony optimization, bin packing, heuristic algorithm, pretreatment

Procedia PDF Downloads 629