Search results for: mitigation techniques

Authors: Yuyan Yi, Jingyi Zheng, Nedret Billor

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Independent component analysis (ICA) is one of the most commonly used blind source separation (BSS) techniques for signal pre-processing, such as noise reduction and feature extraction. The main parameter in the ICA method is the number of independent components (IC). Although there have been several methods for the determination of the number of ICs, it has not been given sufficient attentionto this important parameter. In this study, wereview the mostused methods fordetermining the number of ICs and providetheir advantages and disadvantages. Further, wepropose an improved version of column-wise ICAByBlock method for the determination of the number of ICs.To assess the performance of the proposed method, we compare the column-wise ICAbyBlock with several existing methods through different ICA methods by using simulated and real signal data. Results show that the proposed column-wise ICAbyBlock is an effective and stable method for determining the optimal number of components in ICA. This method is simple, and results can be demonstrated intuitively with good visualizations.

Keywords: independent component analysis, optimal number, column-wise, correlation coefficient, cross-validation, ICAByblock

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

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Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

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Authors: Badla Oualid

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A great number of existing buildings are designed without seismic design criteria and detailing rules for dissipative structural behavior. Thus, it is of critical importance that the structures that need seismic retrofitting are correctly identified, and an optimal retrofitting is conducted in a cost effective fashion. Among the retrofitting techniques available, steel braces can be considered as one of the most efficient solution among seismic performance upgrading methods of RC structures. This paper investigates the seismic behavior of RC buildings strengthened with different types of steel braces, X-braced, inverted V braced, ZX braced, and Zipper braced. Static non linear pushover analysis has been conducted to estimate the capacity of three story and six story buildings with different brace-frame systems and different cross sections for the braces. It is found that adding braces enhances the global capacity of the buildings compared to the case with no bracing and that the X and Zipper bracing systems performed better depending on the type and size of the cross section.

Keywords: seismic design, strengthening, RC frames, steel bracing, pushover analysis

Procedia PDF Downloads 526

Authors: Kuen-Ming Shu, Jyun-Wei Chen

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Encapsulated O-rings are specifically designed to address the problem of sealing the most hostile chemicals and extreme temperature applications. Ultrasonic vibration hot embossing and ultrasonic welding techniques provide a fast and reliable method to fabricate encapsulated O-ring. This paper performs the design and analysis method of the acoustic horns with double extrusion to process tube double side flange simultaneously. The paper deals with study through Finite Element Method (FEM) of ultrasonic stepped horn used to process a capsulated O-ring, the theoretical dimensions of horns, and their natural frequencies and amplitudes are obtained through the simulations of COMOSOL software. Furthermore, real horns were fabricated, tested and verified to proof the practical utility of these horns.

Keywords: encapsulated O-rings, ultrasonic vibration hot embossing, flange making, acoustic horn, finite element analysis

Procedia PDF Downloads 322

Authors: Srinivasulu Dasaiah, Kalyan Yakkala, Gangadhar Battala, Pavan Kumar Pindi, Ramakrishna Naidu Gurijala

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Tinospora cordifolia leaves biomass used for the removal fluoride from aqueous solutions. Batch biosorption technique was applied, pH, contact time, biosorbent dose and initial fluoride concentration was studied. The Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) techniques used to study the surface characteristics and the presence of chemical functional groups on the biosorbent. Biosorption isotherm models and kinetic models were applied to understand the sorption mechanism. Results revealed that pH, contact time, biosorbent dose and initial fluoride concentration played a significant effect on fluoride removal from aqueous solutions. The developed biosorbent derived from Tinospora cordifolia leaves biomass found to be a low-cost biosorbent and could be used for the effective removal of fluoride in synthetic as well as real water samples.

Keywords: biosorption, contact time, fluoride, isotherms

Procedia PDF Downloads 181

Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

Procedia PDF Downloads 327

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: Shaidatul Azdawiyah Abdul Talib, Wan Mohd Razi Idris, Liew Ju Neng, Tukimat Lihan, Muhammad Zamir Abdul Rasid

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Climate change has received great attention worldwide due to the impact of weather causing extreme events. Rainfall and temperature are crucial weather components associated with climate change. In Malaysia, increasing temperatures and changes in rainfall distribution patterns lead to drought and flood events involving agricultural areas, especially rice fields. Muda Agricultural Development Authority (MADA) is the largest rice growing area among the 10 granary areas in Malaysia and has faced floods and droughts in the past due to changing climate. Changes in rainfall and temperature patter affect rice yield. Therefore, trend analysis is important to identify changes in temperature and rainfall patterns as it gives an initial overview for further analysis. Six locations across the MADA area were selected based on the availability of meteorological station (MetMalaysia) data. Historical data (1991 to 2020) collected from MetMalaysia and future climate projection by multi-model ensemble of climate model from CMIP5 (CNRM-CM5, GFDL-CM3, MRI-CGCM3, NorESM1-M and IPSL-CM5A-LR) have been analyzed using Mann-Kendall test to detect the time series trend, together with standardized precipitation anomaly, rainfall anomaly index, precipitation concentration index and temperature anomaly. Future projection data were analyzed based on 3 different periods; early century (2020 – 2046), middle century (2047 – 2073) and late-century (2074 – 2099). Results indicate that the MADA area does encounter extremely wet and dry conditions, leading to drought and flood events in the past. The Mann-Kendall (MK) trend analysis test discovered a significant increasing trend (p < 0.05) in annual rainfall (z = 0.40; s = 15.12) and temperature (z = 0.61; s = 0.04) during the historical period. Similarly, for both RCP 4.5 and RCP 8.5 scenarios, a significant increasing trend (p < 0.05) was found for rainfall (RCP 4.5: z = 0.15; s = 2.55; RCP 8.5: z = 0.41; s = 8.05;) and temperature (RCP 4.5: z = 0.84; s = 0.02; RCP 8.5: z = 0.94; s = 0.05). Under the RCP 4.5 scenario, the average temperature is projected to increase up to 1.6 °C in early century, 2.0 °C in the middle century and 2.4 °C in the late century. In contrast, under RCP 8.5 scenario, the average temperature is projected to increase up to 1.8 °C in the early century, 3.1 °C in the middle century and 4.3 °C in late century. Drought is projected to occur in 2038 and 2043 (early century); 2052 and 2069 (middle century); and 2095, 2097 to 2099 (late century) under RCP 4.5 scenario. As for RCP 8.5 scenario, drought is projected to occur in 2021, 2031 and 2034 (early century); and 2069 (middle century). No drought is projected to occur in the late century under the RCP 8.5 scenario. Thus, this information can be used for the analysis of the impact of climate change scenarios on rice growth and yield besides other crops found in MADA area. Additionally, this study, it would be helpful for researchers and decision-makers in developing applicable adaptation and mitigation strategies to reduce the impact of climate change.

Keywords: climate projection, drought, flood, rainfall, RCP 4.5, RCP 8.5, temperature

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Authors: A. Kourou, A. Ioakeimidou, S. Hadjiefthymiades, V. Abramea

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During the last decades, the task of engaging governments, communities and citizens to reduce risk and vulnerability of the populations has made variable progress. Experience has demonstrated that lack of awareness, education and preparedness may result in significant material and other losses both on the onset of the disaster. Schools play a vital role in the community and are important elements of values and culture of the society. A proper school education not only teaches children, but also is a key factor in the promotion of a safety culture into the wider community. In Greece School Earthquake Safety Initiative has been undertaken by Earthquake Planning and Protection Ogranization with specific actions (seminars, lectures, guidelines, educational material, campaigns, national or EU projects, drills etc.). The objective of this initiative is to develop disaster-resilient school communities through awareness, self-help, cooperation and education. School preparedness requires the participation of Principals, teachers, students, parents, and competent authorities. Preparation and earthquake readiness involves: a) learning what should be done before, during, and after earthquake; b) doing or preparing to do these things now, before the next earthquake; and c) developing teachers’ and students’ skills to cope efficiently in case of an earthquake. In the above given framework this paper presents the results of a survey aimed to identify the level of education and preparedness of school community in Greece. More specifically, the survey questionnaire investigates issues regarding earthquake protection actions, appropriate attitudes and behaviors during an earthquake and existence of contingency plans at elementary and secondary schools. The questionnaires were administered to Principals and teachers from different regions of the country that attend the EPPO national training project 'Earthquake Safety at Schools'. A closed-form questionnaire was developed for the survey, which contained questions regarding the following: a) knowledge of self protective actions b) existence of emergency planning at home and c) existence of emergency planning at school (hazard mitigation actions, evacuation plan, and performance of drills). Survey results revealed that a high percentage of teachers have taken the appropriate preparedness measures concerning non-structural hazards at schools, emergency school plan and simulation drills every year. In order to improve the action-planning for ongoing school disaster risk reduction, the implementation of earthquake drills, the involvement of students with disabilities and the evaluation of school emergency plans, EPPO participates in E-PreS project. The main objective of this project is to create smart tools which define, simulate and evaluate all hazards emergency steps customized to the unique district and school. The project comes up with a holistic methodology using real-time evaluation involving different categories of actors, districts, steps and metrics. The project is supported by EU Civil Protection Financial Instrument with a duration of two years. Coordinator is the Kapodistrian University of Athens and partners are from four countries; Greece, Italy, Romania and Bulgaria.

Keywords: drills, earthquake, emergency plans, E-PreS project

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Authors: Maria C. Proença, Maria T. Rebelo, Marília Antunes, Maria J. Alves, Hugo Osório, Sofia Cunha, REVIVE team

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The environment of the mosquitoes complex Culex pipiens sl. in Portugal mainland is evaluated based in its abundance, using a data set georeferenced, collected during seven years (2006-2012) from May to October. The suitability of the different regions can be delineated using the relative abundance areas; the suitablility index is directly proportional to disease transmission risk and allows focusing mitigation measures in order to avoid outbreaks of vector-borne diseases. The interest in the Culex pipiens complex is justified by its medical importance: the females bite all warm-blooded vertebrates and are involved in the circulation of several arbovirus of concern to human health, like West Nile virus, iridoviruses, rheoviruses and parvoviruses. The abundance of Culex pipiens mosquitoes were documented systematically all over the territory by the local health services, in a long duration program running since 2006. The environmental factors used to characterize the vector habitat are land use/land cover, distance to cartographed water bodies, altitude and latitude. Focus will be on the mosquito females, which gonotrophic cycle mate-bloodmeal-oviposition is responsible for the virus transmission; its abundance is the key for the planning of non-aggressive prophylactic countermeasures that may eradicate the transmission risk and simultaneously avoid chemical ambient degradation. Meteorological parameters such as: air relative humidity, air temperature (minima, maxima and mean daily temperatures) and daily total rainfall were gathered from the weather stations network for the same dates and crossed with the standardized females’ abundance in a geographic information system (GIS). Mean capture and percentage of above average captures related to each variable are used as criteria to compute a threshold for each meteorological parameter; the difference of the mean capture above/below the threshold was statistically assessed. The meteorological parameters measured at the net of weather stations all over the country are averaged by month and interpolated to produce raster maps that can be segmented according to the meaningful thresholds for each parameter. The intersection of the maps of all the parameters obtained for each month show the evolution of the suitable meteorological conditions through the mosquito season, considered as May to October, although the first and last month are less relevant. In parallel, mean and above average captures were related to the physiographic parameters – the land use/land cover classes most relevant in each month, the altitudes preferred and the most frequent distance to water bodies, a factor closely related with the mosquito biology. The maps produced with these results were crossed with the meteorological maps previously segmented, in order to get an index of suitability for the complex Culex pipiens evaluated all over the country, and its evolution from the beginning to the end of the mosquitoes season.

Keywords: suitability index, Culex pipiens, habitat evolution, GIS model

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Authors: Hadjer Didouh, Mohammed Hadj Meliani, Izzaddine Sameut Bouhaik

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This study employs a multidisciplinary approach to investigate the intricate processes governing biofilm-surface interactions. Results indicate that surface properties significantly influence initial microbial attachment, with materials characterized by increased roughness and hydrophobicity promoting enhanced biofilm adhesion. Moreover, the chemical composition of materials plays a crucial role in impacting the development of biofilms. Environmental factors, such as temperature fluctuations and nutrient availability, were identified as key determinants affecting biofilm formation dynamics. Advanced imaging techniques revealed complex three-dimensional biofilm structures, emphasizing microbial communication and cooperation within these networks. These findings offer practical implications for industries operating in crude oil environments, guiding the selection and design of materials to mitigate biofilm-related challenges and enhance operational efficiency in such settings.

Keywords: biofilm adhesion, surface properties, crude oil environments, microbial interactions, multidisciplinary investigation

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Authors: He Lingsong, Wang Junfeng, Tan Qiong, Xu Jiang

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The paper describes efforts on reconstruction methods of engineering testing and measurement technology course by applying new techniques and applications. Firstly, flipped classroom was introduced. In-class time was used for in-depth discussions and interactions while theory concept teaching was done by self-study course outside of class. Secondly, two hands-on practices of technique applications, including the program design of MATLAB Signal Analysis and the measurement application of Arduino sensor, have been covered in class. Class was transformed from an instructor-centered teaching process into an active student-centered learning process, consisting of the pre-class massive open online course (MOOC), in-class discussion and after-class practice. The third is to change sole written homework to the research-oriented application practice assignments, so as to enhance the breadth and depth of the course.

Keywords: testing and measurement, flipped classroom, MOOC, research-oriented learning, practice-oriented learning

Procedia PDF Downloads 152

Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy they produce. While various techniques exist for detecting dust to schedule cleaning, many of these methods use MATLAB image processing tools and other licensed software, which can be financially burdensome. This study will investigate the efficiency of a free open-source computer vision library using the YOLO algorithm. The proposed approach has been tested on images of solar panels with varying dust levels through an experiment setup. The experimental findings illustrated the effectiveness of using the YOLO-based image classification method and the overall dust detection approach with an accuracy of 90% in distinguishing between clean and dusty panels. This open-source solution provides a cost effective and accessible alternative to commercial image processing tools, offering solutions for optimizing solar panel maintenance and enhancing energy production.

Keywords: YOLO, openCV, dust detection, solar panels, computer vision, image processing

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Authors: Mohamed Sarrab, Hadj Bourdoucen

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Mobile applications are verified to check the correctness or evaluated to check the performance with respect to specific security properties such as availability, integrity, and confidentiality. Where they are made available to the end users of the mobile application is achievable only to a limited degree using software engineering static verification techniques. The more sensitive the information, such as credit card data, personal medical information or personal emails being processed by mobile application, the more important it is to ensure the confidentiality of this information. Monitoring non-trusted mobile application during execution in an environment where sensitive information is present is difficult and unnerving. The paper addresses the issue of monitoring and controlling the flow of confidential information during non-trusted mobile application execution. The approach concentrates on providing a dynamic and usable information security solution by interacting with the mobile users during the run-time of mobile application in response to information flow events.

Keywords: mobile application, run-time verification, usable security, direct information flow

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: David Aveiga, Carlos Gonzalez

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Thermoforming of pre-impregnated composites (prepreg) is the most employed process to build high-performance composite structures due to their visible advantage over alternative manufacturing techniques. This method allows easy shape moulding with a simple manufacturing system and a more refined outcome. The achievement of complex geometries can be exposed to undesired defects such as wrinkles. It is known that interply and ply-mould sliding behavior governs this defect generation. This work analyses interply and ply-mould friction coefficients for UD AS4/8552 Carbon/Epoxy prepreg. Friction coefficients are determined by a pull-out test method considering actual velocity, pressure and temperature conditions employed in a thermoforming process of an aeronautical composite component. A Stribeck curve is then constructed to find a mathematical expression that relates all the friction coefficients with the test variables through the Hersey number parameter. Two expressions are proposed to model ply-ply and ply-tool friction behaviors.

Keywords: friction, prepreg composite, stribeck curve, thermoforming.

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Authors: Yunus Doğan, Ahmet Durap

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Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

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Authors: R. Benakcha, M. Omari

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Powders of La1-xMgxAlO3 (0 ≤ x ≤ 5) oxides, with large surface areas were synthesized by sol-gel process, utilizing citric acid. Heating of a mixed solution of CA, EtOH, and nitrates of lanthanum, aluminium and magnesium at 70°C gave transparent gel without any precipitation. The formation of pure perovskite La1-xMgxAlO3, occurred when the precursor was heat-treated at 800°C for 6 h. No X-ray diffraction evidence for the presence of crystalline impurities was obtained. The La1-xMgxAlO3 powders prepared by the sol-gel method have a considerably large surface area in the range of 12.9–20 m^2.g^-1 when compared with 0.3 m^2.g^-1 for the conventional solid-state reaction of LaAlO3. The structural characteristics were examined by means of conventional techniques namely X-ray diffraction, infrared spectroscopy, thermogravimetry and differential thermal (TG-DTA) and specific surface SBET. Pore diameters and crystallite sizes are in the 8.8-11.28 nm and 25.4-30.5 nm ranges, respectively. The sol-gel method is a simple technique that has several advantages. In addition to that of not requiring high temperatures, it has the potential to synthesize many kinds of mixed oxides and obtain other materials homogeneous and large purities. It also allows formatting a variety of materials: very fine powders, fibers and films.

Keywords: aluminate, lanthan, perovskite, sol-gel

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Authors: Driss Bouyahya

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During the late 1960s, Islam-oriented social movements have encroached to reach the Moroccan public spheres and mobilize huge waves of people from different walks of life under the banners of a rhetoric that resonates with the Muslim way of life away from Modernity and globalization tenets. In this respect, the present study investigates and explores some of the ways utilized by the Movement for Unity and Reform in Morocco as an Islam-oriented movement to recruit students massively at universities. The significance of this study lies in demystifying the recruitment strategies and mechanisms, considered essential for the Islam-oriented social movements to mobilize. This research paper uses a quantitative method to collect and analyze data through two different structured questionnaires. One of the major findings is that this Islam-oriented movement uses different techniques to recruit students, namely social networks, its websites and You-tube as three main modern and sophisticated means of communication. In a nutshell, this paper´s findings fill some of the gaps in the literature in regard to Islam-oriented movements ‘mobilization strategies.

Keywords: changing, ideology, Islam, party

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

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Authors: Uyi Kizito Ehigiamusoe

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The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.

Keywords: economic growth, investments, money market, money market challenges, money market instruments

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Authors: Chenine Halima, Ouinas Djamel, Bekki Hamed Essiddik

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The matrix is made up of resin mixed with fillers. However, with the growing demand to reduce CO2 emissions, the market is increasingly leaning toward eco-friendly materials. In this context, this research focuses on developing an environmentally friendly material, with or without sand, by following various stages using micro-filled resin. Three manufacturing techniques will be explored: infusion, RTM-Eco, and molding. The process begins with incorporating sand directly into the resin matrix, a critical step in creating this type of composite. To achieve this, two mixing methods will be tested: one by hand and the other using a mechanical mixer. The best method will be selected based on key criteria, such as achieving a uniform sand distribution and determining the optimal sand-to-resin ratio. The final material must meet specific requirements, including strong mechanical performance, high-temperature resistance, cost-efficiency, and outstanding durability against corrosion.

Keywords: micro-charging of sand particles, laminated composites, polymer, resin, corrosion

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Authors: Phalaunnaphat Siriwongs

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The classroom of the 21st century is an ever-changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not a cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pinpoint an exact number, it is clear that in this case, more does not mean better. By looking into the success and pitfalls of classroom size, the true advantages of smaller classes becomes clear. Previously, one class was comprised of 50 students. Since they were seventeen- and eighteen-year-old students, it was sometimes quite difficult for them to stay focused. To help students understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: multiple intelligences, role play, performance assessment, formative assessment

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Mohamed A. Adam Abakar, Abdullah M. Asiri, Sher Bahadar Khan

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In this paper, nickel oxide-zinc oxide (NiO-ZnO) catalyst was embedded in an alginate polymer (Na alg/NiO-ZnO), a nanocomposite that was used as a nano-catalyst for catalytic conversion of deleterious contaminants such as organic dyes (Acridine Orange “ArO”, Methylene Blue “MB”, Methyl Orange “MO”) and 4-Nitrophenol “4-NP” as well. FESEM, EDS, FTIR and XRD techniques were used to identify the shape and structure of the nano-catalyst (Na alg/NiO-ZnO). UV spectrophotometry is used to collect the results and it showed greater and faster reduction rate for MB (illustrated in figures 2, 3, 4 and 5). Data recorded and processed, drawing and analysis of graphs achieved by using Origin 2018. Reduction percentage of MB was assessed to be 95.25 % in just 13 minutes. Furthermore, the catalytic property of Na alg/NiO-ZnO in the reduction of organic dyes was investigated using various catalyst amounts, dye types, reaction times and reducing agent dosages at room temperature (rt). NaBH4-assisted reduction of organic dyes was studied using alg/NiO-ZnO as a potential catalyst.

Keywords: Alginate, metal oxides, nanocomposites-based, catalysts, reduction, photocatalytic degradation, water treatment

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Authors: Berhane Tewelday Weldhiwot

Abstract:

This research investigates the pivotal role of modular forms in modern cryptographic systems, particularly focusing on their applications in secure communications and data integrity. Modular forms, which are complex analytic functions with rich arithmetic properties, have gained prominence due to their connections to number theory and algebraic geometry. This study begins by outlining the fundamental concepts of modular forms and their historical development, followed by a detailed examination of their applications in cryptographic protocols such as elliptic curve cryptography and zero-knowledge proofs. By employing techniques from analytic number theory, the research delves into how modular forms can enhance the efficiency and security of cryptographic algorithms. The findings suggest that leveraging modular forms not only improves computational performance but also fortifies security measures against emerging threats in digital communication. This work aims to contribute to the ongoing discourse on integrating advanced mathematical theories into practical applications, ultimately fostering innovation in cryptographic methodologies.

Keywords: modular forms, cryptography, elliptic curves, applications, mathematical theory

Procedia PDF Downloads 27

Authors: Pei-Shan Liang

Abstract:

Objective: This article explores the nursing experience of caring for a patient with terminal gastric cancer complicated by an abdominal aortic aneurysm. The patient experienced physical discomfort due to the disease, initially unable to accept the situation, leading to anxiety, and eventually accepting the need for surgery. Methods: The nursing period was from June 6 to June 10, 2024. Through observation, direct care, conversations, and physical assessments, and using Gordon's eleven functional health patterns for a one-on-one holistic assessment, interdisciplinary team meetings were held with the critical care team and family. Three nursing health issues were identified: pain related to the disease and invasive procedures, anxiety related to uncertainty about disease recovery, and decreased cardiac tissue perfusion related to hemodynamic instability. Results: Open communication techniques and empathetic care were employed to establish a trusting nurse-patient relationship, and patient-centered nursing interventions were developed. Pain was assessed using a 10-point pain scale, and pain medications were adjusted by a pharmacist. Initially, Fentanyl 500mcg with pump run at 1ml/hr was administered, later changed to Ultracet 37.5mg/325mg, 1 tablet every 6 hours orally, reducing the pain score to 3. Lavender aromatherapy and listening to crystal music were used as distractions to alleviate pain, allowing the patient to sleep uninterrupted for at least 7 hours. The patient was encouraged to express feelings and fears through LINE messages or drawings, and a psychologist was invited to provide support. Family members were present at least twice a day for over an hour each time, reducing psychological distress and uncertainty about the prognosis. According to the Beck Anxiety Inventory, the anxiety score dropped from 17 (moderate anxiety) to 6 (no anxiety). Focused nursing care was implemented with close monitoring of vital signs maintaining systolic blood pressure between 112-118 mmHg to ensure adequate myocardial perfusion. The patient was encouraged to get out of bed for postoperative rehabilitation and to strengthen cardiopulmonary function. A chest X-ray showed no abnormalities, and breathing was smooth with Triflow use, maintaining at least 5 seconds with 2 balls four times a day, and SpO2 >96%. Conclusion: The care process highlighted the importance of addressing psychological care in addition to maintaining life when the patient’s condition changes. The presence of family often provided the greatest source of comfort for the patient, helping to reduce anxiety and pain. Nurses must play multiple roles, including advocate, coordinator, educator, and consultant, using various communication techniques and fostering hope by listening to and accepting the patient’s emotional responses. It is hoped that this report will provide a reference for clinical nursing staff and contribute to improving the quality of care.

Keywords: intensive care, gastric cancer, aortic aneurysm, quality of care

Procedia PDF Downloads 38

Authors: Kaddi Mohammed, A. Benatiallah, D. Benatiallah

Abstract:

Data grid is a technology that has full emergence of new challenges, such as the heterogeneity and availability of various resources and geographically distributed, fast data access, minimizing latency and fault tolerance. Researchers interested in this technology address the problems of the various systems related to the industry such as task scheduling, load balancing and replication. The latter is an effective solution to achieve good performance in terms of data access and grid resources and better availability of data cost. In a system with duplication, a coherence protocol is used to impose some degree of synchronization between the various copies and impose some order on updates. In this project, we present an approach for placing replicas to minimize the cost of response of requests to read or write, and we implement our model in a simulation environment. The placement techniques are based on a cost model which depends on several factors, such as bandwidth, data size and storage nodes.

Keywords: response time, query, consistency, bandwidth, storage capacity, CERN

Procedia PDF Downloads 276

Authors: Leandro Moura da Silva

Abstract:

The international community has strived to create legal mechanisms to protect their biodiversity, but this can represent, sometimes, particularly in the case of regulatory regime on access to genetic resources, an excessive nationalism which transforms itself into a significant obstacle to scientific progress causing damages to the country and to local farmers. Although it has been poorly publicized in the media, the international legal system was marked, in 2014, by the entry into force of the Nagoya Protocol, which regulates the access and benefit sharing of genetic resources of the States Party to that legal instrument. However, it’s not reasonable to think of regulating access to genetic resources without reflecting on the links of this important subject with other related issues, such as family farming and agribusiness, food safety, food security, intellectual property rights (on seeds, genetic material, new plant varieties, etc.), environmental sustainability, biodiversity, and biosafety.

Keywords: international law, regulation on agriculture, agronomy techniques, sustainability, genetic resources and new crop varieties, CBD, Nagoya Protocol, ITPGRFA

Procedia PDF Downloads 505