Search results for: validation techniques

Authors: Prikhil Agrawal, N. Priyanka

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With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool.

Keywords: genetic algorithm (GA), intrusion detection system (IDS), dataset, network security

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Authors: Anna Suvorova

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Classical motivation theories hold that there are two kinds of motivation, intrinsic and extrinsic. Leaders are looking for effective motivation techniques, but frequently external influences do not work or, even worse, reduce team productivity. We see only the tip of the iceberg -human behavior. However, beneath the surface of the water are factors that directly affect our behavior -desires. Believing that employees need to be motivated, companies design a motivation system based on the principle: do it and get a reward. As a matter of fact, we all have basic desires. Everybody is motivated but to different extents. Following the principle "intrinsic motivation over extrinsic rewards", we need to create an environment that will support intrinsic motivation and potential of employees, and team, rather than individual work.

Keywords: motivation profile, motivation techniques, agile HR, basic desires, agile people, human behavior, people management

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Authors: Özgür Tan

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In different fields of industry, there is a huge demand to acquire surface information in the dimension of micrometer up to centimeter in order to characterize functional behavior of products. Thanks to the latest developments, there are now different methods in surface metrology, but it is not possible to find a unique measurement technique which fulfils all the requirements. Depending on the interaction with the surface, regardless of optical or tactile, every method has its own advantages and disadvantages which are given by nature. However new concepts like ‘multi-sensor’, tools in surface metrology can be improved to solve most of the requirements simultaneously. In this paper, after having presented different optical techniques like confocal microscopy, focus variation and white light interferometry, a new approach is presented which combines white-light interferometry with chromatic confocal probing in a single product. Advantages of different techniques can be used for challenging applications.

Keywords: flatness, chromatic confocal, optical surface metrology, roughness, white-light interferometry

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Satya P. Dubey, Hrushikesh A Abhyankar, Veronica Marchante, James L. Brighton, Björn Bergmann

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Aims: To develop a mathematical model that simulates the ROP of PLA taking into account the effect of alternative energy to be implemented in a continuous reactive extrusion production process of PLA. Introduction: The production of large amount of waste is one of the major challenges at the present time, and polymers represent 70% of global waste. PLA has emerged as a promising polymer as it is compostable, biodegradable thermoplastic polymer made from renewable sources. However, the main limitation for the application of PLA is the traces of toxic metal catalyst in the final product. Thus, a safe and efficient production process needs to be developed to avoid the potential hazards and toxicity. It has been found that alternative energy sources (LASER, ultrasounds, microwaves) could be a prominent option to facilitate the ROP of PLA via continuous reactive extrusion. This process may result in complete extraction of the metal catalysts and facilitate less active organic catalysts. Methodology: Initial investigation were performed using the data available in literature for the reaction mechanism of ROP of PLA based on conventional metal catalyst stannous octoate. A mathematical model has been developed by considering significant parameters such as different initial concentration ratio of catalyst, co-catalyst and impurity. Effects of temperature variation and alternative energies have been implemented in the model. Results: The validation of the mathematical model has been made by using data from literature as well as actual experiments. Validation of the model including alternative energies is in progress based on experimental data for partners of the InnoREX project consortium. Conclusion: The model developed reproduces accurately the polymerisation reaction when applying alternative energy. Alternative energies have a great positive effect to increase the conversion and molecular weight of the PLA. This model could be very useful tool to complement Ludovic® software to predict the large scale production process when using reactive extrusion.

Keywords: polymer, poly-lactic acid (PLA), ring opening polymerization (ROP), metal-catalyst, bio-degradable, renewable source, alternative energy (AE)

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Authors: Zahir Bakiri, Saci Nacefa

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In this paper a comparison in made between two models, with and without dispersion term, and focused on the characterization of the movement of the sludge blanket in the secondary sedimentation tank using the solid flux theory and the velocity settling. This allowed us develop a one-dimensional models, with and without dispersion based on a thorough experimental study carried out in situ and the application of online data which are the mass load flow, transfer concentration, and influent characteristic. On the other hand, in the proposed model, the new settling velocity law (double-exponential function) used is based on the Vesilind function.

Keywords: wastewater, activated sludge, sedimentation, settling velocity, settling models

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Authors: Abdelkader Anouzla, Soukaina Bouaouda, Roukaya Bouyakhsass, Salah Souabi, Abdeslam Taleb

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During storage and under the combined action of rainwater and natural fermentation, these wastes produce over 800.000 m3 of landfill leachates. Due to population growth and changing global economic activities, the amount of waste constantly generated increases, making more significant volumes of leachate. Leachate, when leaching into the soil, can negatively impact soil, surface water, groundwater, and the overall environment and human life. The leachate must first be treated because of its high pollutant load before being released into the environment. This article reviews the different leachate treatments in September 2022 techniques. Different techniques can be used for this purpose, such as biological, physical-chemical, and membrane methods. Young leachate is biodegradable; in contrast, these biological processes lose their effectiveness with leachate aging. They are characterized by high ammonia nitrogen concentrations that inhibit their activity. Most physical-chemical treatments serve as pre-treatment or post-treatment to complement conventional treatment processes or remove specific contaminants. After the introduction, the different types of pollutants present in leachates and their impacts have been made, followed by a discussion highlighting the advantages and disadvantages of the various treatments, whether biological, physicochemical, or membrane. From this work, due to their simplicity and reasonable cost compared to other treatment procedures, biological treatments offer the most suitable alternative to limit the effects produced by the pollutants in landfill leachates.

Keywords: landfill leachate, landfill pollution, impact, wastewater

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: Jan Barak, Karel Frana, Joerg Stiller

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This work presents results of moist air condensation in heat exchanger. It describes theoretical knowledge and definition of moist air. Model with geometry of square canal was created for better understanding and post processing of condensation phenomena. Different approaches were examined on this model to find suitable software and model. Obtained knowledge was applied to geometry of real heat exchanger and results from experiment were compared with numerical results. One of the goals is to solve this issue without creating any user defined function in the applied code. It also contains summary of knowledge and outlook for future work.

Keywords: condensation, exchanger, experiment, validation

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Authors: Sonia Zulfiqar, Daniele Mantione, Muhammad Ilyas Sarwar, Alexander Rothenberger, David Mecerreyes

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Climate change due to escalating carbon dioxide concentration in the atmosphere is an issue of paramount importance that needs immediate attention. CO2 capture and sequestration (CCS) is a promising route to mitigate climate change and adsorption is the most widely recognized technology owing to possible energy savings relative to the conventional absorption techniques. In this conference, the potential of a new family of solid sorbents for CO2 capture and separation will be presented. Novel pyridinium containing poly(ionic liquid)s (PILs) were synthesized with varying anions i.e bis(trifluoromethylsulfonyl)imide and hexafluorophosphate. The resulting polymers were characterized using NMR, XRD, TGA, BET surface area and microscopic techniques. Furthermore, CO2 adsorption measurements at two different temperatures were also carried out and revealed great potential of these PILs as CO2 scavengers.

Keywords: climate change, CO2 capture, poly(ionic liquid)s, CO2/N2 selectivity

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Authors: Kedarnath Awati

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Some parallels between Indian Art Music and Western Art Music, such as the identity of the basic heptatonic scale structure, are quite obvious and need no further discussion. Other parallels are far less obvious, and it is one of them that the author is interested in. Specifically, the author would like to make a serious claim that in both types of music, there is an unspoken dependence on melody. Yes, it is true that the techniques that the two systems use for elaboration are very, very different: Western music uses the techniques of harmony, counterpoint, orchestration and motivic variation, while the Indian systems, both the Hindustani and the Carnatic traditions use the technique of raagdaari. The reason that this point is barely spoken about is that both in the West as well as in India, artists tend to think of melody as something elementary or as something 'given'. The Indian musicians would much rather dwell upon this or that meend or taan or other technical device, while the West thinks that melody is passé and would rather discuss the merits and demerits of spectralism and perhaps serialism. The author would like to explore this theme further in his paper.

Keywords: Indian art music, Western art music, melody, raagdaari, motivic variation.

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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Authors: Gebreegziabher Hailu

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This paper presents the development of residual power series methods aimed at efficiently solving stiff differential equations, which pose significant challenges in numerical analysis due to their rapid changes in solution behavior. The RPSM is a numerical approach that generates polynomial-based approximate solutions without the need for linearization, discretization, or perturbation techniques, making it straightforward to implement and less prone to computational errors. We introduce an approach that utilizes power series expansions combined with residual minimization techniques to enhance convergence and stability. By analyzing the theoretical foundations of stiffness, we delve into the formulation of the residual power series method, detailing how it effectively captures the dynamics of stiff systems while maintaining computational efficiency. Numerical experiments demonstrate the method's superiority in terms of accuracy and computational cost when compared to traditional methods like implicit Runge-Kutta or multistep techniques. We also explore adaptive strategies within our framework to automatically adjust parameters based on the stiffness characteristics of the problem at hand. Ultimately, our findings contribute to the broader toolkit for tackling stiff differential equations, offering a robust alternative that promises to streamline computational workflows in various applied mathematics and engineering contexts.

Keywords: residual power series methods, stiff differential equoations, numerical approach, Runge Kutta methods

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Sabuj Mallik

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The emerging approaches to sustainable manufacturing are considered to be solution-oriented with the aim of addressing the environmental, economic and social issues holistically. However, the analysis of the interdependencies amongst the three sustainability dimensions has not been fully captured in the literature. In a recent review of approaches to sustainable manufacturing, two categories of techniques are identified: 1) Sustainable Product Development (SPD), and 2) Sustainability Performance Assessment (SPA) techniques. The challenges of the approaches are not only related to the arguments and misconceptions of the relationships between the techniques and sustainable development but also to the inability to capture and integrate the three sustainability dimensions. This requires a clear definition of some of the approaches and a road-map to the development of a holistic approach that supports sustainability decision-making. In this context, eco-innovation, social impact assessment, and life cycle sustainability analysis play an important role. This paper deployed an integrative approach that enabled amalgamation of sustainable manufacturing approaches and the theories of reciprocity and motivation into a holistic simulation-based impact analysis framework. The findings in this research have the potential to guide sustainability analysts to capture the aspects of the three sustainability dimensions into an analytical model. Additionally, the research findings presented can aid the construction of a holistic simulation model of a sustainable manufacturing and support effective decision-making.

Keywords: life cycle sustainability analysis, sustainable manufacturing, sustainability performance assessment, sustainable product development

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Authors: Tosin Ige

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Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

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Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

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Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

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As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: Juan Jose Filgueira, Daniela Londono-Serna, Liliana Maria Hoyos

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Carnation (Dianthus caryophyllus) is one of the most important products of exportation in the floriculture industry worldwide. Fusariosis is the disease that causes the highest losses on farms, in particular the one produced by Fusarium oxysporum f.sp. dianthi, called vascular wilt. Gene identification and metabolic routes of the genes that participate in the building of the plant response to Fusarium are some of the current targets in the carnation breeding industry. The techniques for the identifying of resistant genes in the plants, is the analysis of the transcriptome obtained during the host-pathogen interaction. In this work, we report the cell transcriptome of different varieties of carnation that present differential response from Fusarium oxysporum f.sp. dianthi attack. The cells of the different hybrids produced in the outbreeding program were cultured in vitro and elicited with the parasite in a dual culture. The isolation and purification of mRNA was achieved by using affinity chromatography Oligo dT columns and the transcriptomes were obtained by using Illumina NGS techniques. A total of 85,669 unigenes were detected in all the transcriptomes analyzed and 31,000 annotations were found in databases, which correspond to 36.2%. The library construction of genic expression techniques used, allowed to recognize the variation in the expression of genes such as Germin-like protein, Glycosyl hydrolase family and Cinnamate 4-hydroxylase. These have been reported in this study for the first time as part of the response mechanism to the presence of Fusarium oxysporum.

Keywords: Carnation, Fusarium, vascular wilt, transcriptome

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Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

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Authors: Mohammad Hossain Mohammadi, Saif Al Ameri, Sana Ziaei, Jinane Mounsef

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Automated enumeration of the number of hand fingers is widely used in several motion gaming and distance control applications, and is discussed in several published papers as a starting block for hand recognition systems. The automated finger enumeration technique should not only be accurate, but also must have a fast response for a moving-picture input. The high performance of video in motion games or distance control will inhibit the program’s overall speed, for image processing software such as Matlab need to produce results at high computation speeds. Since an automated finger enumeration with minimum error and processing time is desired, a comparative study between two finger enumeration techniques is presented and analyzed in this paper. In the pre-processing stage, various image processing functions were applied on a real-time video input to obtain the final cleaned auto-cropped image of the hand to be used for the two techniques. The first technique uses the known morphological tool of skeletonization to count the number of skeleton’s endpoints for fingers. The second technique uses a radial distance method to enumerate the number of fingers in order to obtain a one dimensional hand representation. For both discussed methods, the different steps of the algorithms are explained. Then, a comparative study analyzes the accuracy and speed of both techniques. Through experimental testing in different background conditions, it was observed that the radial distance method was more accurate and responsive to a real-time video input compared to the skeletonization method. All test results were generated in Matlab and were based on displaying a human hand for three different orientations on top of a plain color background. Finally, the limitations surrounding the enumeration techniques are presented.

Keywords: comparative study, hand recognition, fingertip detection, skeletonization, radial distance, Matlab

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Authors: Chayaporn Kaensar

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Recently, Job Recommender Systems have gained much attention in industries since they solve the problem of information overload on the recruiting website. Therefore, we proposed Extended Personalized Job System that has the capability of providing the appropriate jobs for job seeker and recommending some suitable information for them using Data Mining Techniques and Dynamic User Profile. On the other hands, company can also interact to the system for publishing and updating job information. This system have emerged and supported various platforms such as web application and android mobile application. In this paper, User profiles, Implicit User Action, User Feedback, and Clustering Techniques in WEKA libraries have gained attention and implemented for this application. In additions, open source tools like Yii Web Application Framework, Bootstrap Front End Framework and Android Mobile Technology were also applied.

Keywords: recommendation, user profile, data mining, web and mobile technology

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Authors: Ilias Katsanis, Paraskevas Papanikos, Nikolas Zacharopoulos, Vassilis C. Moulianitis, Evgenios Scourboutis, Diamantis T. Panagiotarakos

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This paper presents aspects of the detailed design of an automated biomethane potential measurement system using CAD techniques. First, the design specifications grouped in eight sets that are used to design the design alternatives are briefly presented. Then, the major components of the final concept, as well as the design of the test, are presented. The material selection process is made using ANSYS EduPack database software. The mechanical behavior of one component developed in Creo v.5 is evaluated using finite element analysis. Finally, aspects of software development that integrate the BMP test is finally presented. This paper shows the advantages of CAD techniques in product design applied in the design of a mechatronic product.

Keywords: automated biomethane test, detail mechatronics design, materials selection, mechanical analysis

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Authors: Ahmed Amin Mousa, M. Abd El Salam

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The current study presents a proposed program for acquisition the skills and techniques needed to produce concept cartoon. The proposed program has been prepared for non-specialist students who have never used neither graphics nor animating software. It was presented to postgraduates in Faculty of Education for Early Childhood, Cairo University, during the spring term of the 2014-2015 academic year. The program works in three different aspects: Drawing and images editing, sound manipulation, and creating animation. In addition, the researchers have prepared a questionnaire for measuring the quality of the concept cartoons produced by the students. The questionnaire was used as a pre-test and post-test, and at the end of the study, a significant difference was determined in favour of post-test results.

Keywords: cartoon, concept cartoon, kindergarten, animation

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Authors: Shin Ku Kim, Yun Ah Oh, Eun Hee Seo, Chang Min Dae, Yun Jung Bae

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Objectives: The commonly used PRESS technique in magnetic resonance spectroscopy (MRS) has a limitation of incomplete water suppression. The recently developed sLASER technique is known for its improved effectiveness in suppressing water signal. However, no prior study has compared both sequences in a normal human brain. In this study, we firstly aimed to compare the performances of both techniques in brain MRS. Materials and methods: From January 2023 to July 2023, thirty healthy participants (mean age 38 years, 17 male, 13 female) without underlying neurological diseases were enrolled in this study. All participants underwent single-voxel MRS using both PRESS and sLASER techniques on 3T MRI. Two regions-of-interest were allocated in the left medial thalamus and left parietal white matter (WM) by a single reader. The SpectroView Analysis (SW5, Philips, Netherlands) provided automatic measurements, including signal-to-noise ratio (SNR) and peak_height of water, N-acetylaspartate (NAA)-water/Choline (Cho)-water/Creatine (Cr)-water ratios, and NAA-Cr/Cho-Cr ratios. The measurements from PRESS and sLASER techniques were compared using paired T-tests and Bland-Altman methods, and the variability was assessed using coefficients of variation (CV). Results: SNR and peak_heights of the water were significantly lower with sLASER compared to PRESS (left medial thalamus, sLASER SNR/peak_height 2092±475/328±85 vs. PRESS 2811±549/440±105); left parietal WM, 5422±1016/872±196 vs. 7152±1305/1150±278; all, P<0.001, respectively). Accordingly, NAA-water/Cho-water/Cr-water ratios and NAA-Cr/Cho-Cr ratios were significantly higher with sLASER than with PRESS (all, P< 0.001, respectively). The variabilities of NAA-water/Cho-water/Cr-water ratios and Cho-Cr ratio in the left medial thalamus were lower with sLASER than with PRESS (CV, sLASER vs. PRESS, 19.9 vs. 58.1/19.8 vs. 54.7/20.5 vs. 43.9 and 11.5 vs. 16.2) Conclusion: The sLASER technique demonstrated enhanced background water suppression, resulting in increased signals and reduced variability in brain metabolite measurements of MRS. Therefore, sLASER could offer a more precise and stable method for identifying brain metabolites.

Keywords: Magnetic resonance spectroscopy, Brain, sLASER, PRESS

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Authors: Mircea Ivanescu, Nirvana Popescu, Decebal Popescu, Dorin Popescu

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This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.

Keywords: distributed model, flexible manipulator, observer, robot control

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Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid

Abstract:

Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.

Keywords: optimization, harmony search algorithm, MATLAB, electronic

Procedia PDF Downloads 463

Authors: Hyun-Woo Cho

Abstract:

Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

Procedia PDF Downloads 388

Authors: Faisal Alsaaq

Abstract:

Hydrographic surveys have traditionally relied on the availability of tide information for the reduction of sounding observations to a common datum. In most cases, tide information is obtained from tide gauge observations and/or tide predictions over space and time using local, regional or global tide models. While the latter often provides a rather crude approximation, the former relies on tide gauge stations that are spatially restricted, and often have sparse and limited distribution. A more recent method that is increasingly being used is Global Navigation Satellite System (GNSS) positioning which can be utilised to monitor height variations of a vessel or buoy, thus providing information on sea level variations during the time of a hydrographic survey. However, GNSS heights obtained under the dynamic environment of a survey vessel are affected by “non-tidal” processes such as wave activity and the attitude of the vessel (roll, pitch, heave and dynamic draft). This research seeks to examine techniques that separate the tide signal from other non-tidal signals that may be contained in GNSS heights. This requires an investigation of the processes involved and their temporal, spectral and stochastic properties in order to apply suitable recovery techniques of tide information. In addition, different post-mission and near real-time GNSS positioning techniques will be investigated with focus on estimation of height at ocean. Furthermore, the study will investigate the possibility to transfer the chart datums at the location of tide gauges.

Keywords: hydrography, GNSS, datum, tide gauge

Procedia PDF Downloads 265