Search results for: open dataset

Authors: K. Abuzayan, H. Alabed

Abstract:

The objectives of this study (baseline study, n = 20) were to implement Matlab procedures for quantifying selected static balance variables, establish baseline data of selected variables which characterize static balance activities in a population of healthy young adult males, and to examine any trial effects on these variables. The results indicated that the implementation of Matlab procedures for quantifying selected static balance variables was practical and enabled baseline data to be established for selected variables. There was no significant trial effect. Recommendations were made for suitable tests to be used in later studies. Specifically it was found that one foot-tiptoes tests either in static balance is too challenging for most participants in normal circumstances. A one foot-flat eyes open test was considered to be representative and challenging for static balance.

Keywords: static balance, base of support, baseline data, young adults

Procedia PDF Downloads 522

Authors: Smaran Manchala

Abstract:

Homomorphic Encryption (HE) enables computations on encrypted data without requiring decryption, mitigating data vulnerability during processing. Usable Fully Homomorphic Encryption (FHE) could revolutionize secure data operations across cloud computing, AI training, and healthcare, providing both privacy and functionality, however, the computational inefficiency of schemes like Cheon-Kim-Kim-Song (CKKS) hinders their widespread practical use. This study focuses on optimizing CKKS for faster matrix operations through the implementation of vector computation parallelization and GPU acceleration. The variable effects of vector parallelization on GPUs were explored, recognizing that while parallelization typically accelerates operations, it could introduce overhead that results in slower runtimes, especially in smaller, less computationally demanding operations. To assess performance, two neural network models, MLPN and CNN—were tested on the MNIST dataset using both ARM and x86-64 architectures, with CNN chosen for its higher computational demands. Each test was repeated 1,000 times, and outliers were removed via Z-score analysis to measure the effect of vector parallelization on CKKS performance. Model accuracy was also evaluated under CKKS encryption to ensure optimizations did not compromise results. According to the results of the trail runs, applying vector parallelization had a 2.63X efficiency increase overall with a 1.83X performance increase for x86-64 over ARM architecture. Overall, these results suggest that the application of vector parallelization in tandem with GPU acceleration significantly improves the efficiency of CKKS even while accounting for vector parallelization overhead, providing impact in future zero trust operations.

Keywords: CKKS scheme, runtime efficiency, fully homomorphic encryption (FHE), GPU acceleration, vector parallelization

Procedia PDF Downloads 24

Authors: Khadidja Mahdi, Salaheddine Doumandji

Abstract:

Among the natural enemies that reduce populations of the tomato leaf miner studied in experimental plots of National High school of agriculture (ENSA, Algeria, 36° 40’ à 36° 43’ N.; 3° 08’ à 3° 12’ E.), larval ectoparasites. Three larval ectoparasites are reported in this study namely Necrinmus Sp. and two species of indeterminate Chalcidae (Chalcidae Sp. 1 and 2). These species have significantly reduced the effectives of Tuta absoluta. The results for the parasitism of eggs, larval instars and pupae of Tuta absoluta on the open field tomato in the experimental plots of ENSA show high levels of parasite eggs with 25%. With 94.7%, the first larval instar (L1) is the most parasites. The second instar (L2) undergoes the action of parasitoids least 60%. Instars L3 and L4 and pupae remain unharmed.

Keywords: tuta absoluta, larval ectoparasites, tomato, ensa, Algeria

Procedia PDF Downloads 278

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

Abstract:

This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

Procedia PDF Downloads 215

Authors: Tsetsegmaa A., Bayarsuren B., Altantsetseg Ts.

Abstract:

To make the best decision on reducing harmful emissions from buses, we need to have a clear understanding of the current state of their actual emissions. The emissions from city buses running on high sulfur fuel, particularly particulate matter (PM) and nitrogen oxides (NOx) from the exhaust gases of conventional diesel engines, have been studied and measured with and without diesel particulate filter (DPF) in Ulaanbaatar city. The study was conducted by using the PEMS (Portable Emissions Measurement System) and gravimetric method in real traffic conditions. The obtained data were used to determine the actual emission rates and to evaluate the effectiveness of the selected particulate filters. Actual road and daily PM emissions from city buses were determined during the warm and cold seasons. A bus with an average daily mileage of 242 km was found to emit 166.155 g of PM into the city's atmosphere on average per day, with 141.3 g in summer and 175.8 g in winter. The actual PM of the city bus is 0.6866 g/km. The concentration of NOx in the exhaust gas averages 1410.94 ppm. The use of DPF reduced the exhaust gas opacity of 24 buses by an average of 97% and filtered a total of 340.4 kg of soot from these buses over a period of six months. Retrofitting an old conventional diesel engine with cassette-type silicon carbide (SiC) DPF, despite the laboriousness of cleaning, can significantly reduce particulate matter emissions. Innovation: First comprehensive road PM and NOx emission dataset and actual road emissions from public buses have been identified. PM and NOx mathematical model equations have been estimated as a function of the bus technical speed and engine revolution with and without DPF.

Keywords: conventional diesel, silicon carbide, real-time onboard measurements, particulate matter, diesel retrofit, fuel sulphur

Procedia PDF Downloads 165

Authors: Ismene Ithai Bras-Ruiz

Abstract:

Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

Procedia PDF Downloads 128

Authors: Aparna Saha, Tuhin Ahmed

Abstract:

West Bengal has a number of important rivers, each with its distinctive character and a story. Traditionally, cities have ‘divulged’ to rivers at the river edges and rivers have been an inseparable part of the urban experience. Considering the research aspect, the area is taken in Barrackpore, a small but important outgrowth of Kolkata Municipal Association, West Bengal. Barrackpore, at present, has ample inadequate public open spaces at the neighborhood level where people of different socio-cultural, economic, and religious backgrounds can come together and engage in various leisure activities, but there is no opportunity either, where people can learn about and explore the rich history of the settlement. Pertaining to these issues forms the backdrop of this research paper which has been conceptualized as a place from space that will bring people back to the river and increase community interactions and will also celebrate and commemorate towards the historical importance of the river and its edges. The entire precinct bordering the river represents the transition from pre-independence (Raj era) to Sepoy phase (Swaraj era), finally culminating into the Gandhian philosophy which is being projected into the already existing Gandhi Ghat. The ultimate aim of the paper entitled ‘Utsadhara- Rejuvenating the dead river edge into an urban activity space along the banks of river Hooghly’ is to create a socio-cultural space keeping the heritage identity intact through judicious use of the water body. Also, a balance is kept between the natural ecosystem and the cosmetic development of the surrounding open spaces. It can be duly achieved by the aforementioned methodology provided in the document, but mainly it would focus into preserving the historic ethnicity of the place by holding its character through various facts and figures as well as features. Most importantly the natural topography of the place is left intact. The second priority is given in terms of hierarchy of well connected public plazas, podiums where people from different socio-economic backgrounds irrespective of age and sex could socialize and reach towards venturing into a cordial relationship with one another. The third priority is to provide a platform for the common mass for showcasing their skills and talent through different art and craft forms which in turn would enhance their individual self and also the community as a whole through economic rise. Apart from this here some spaces are created in accordance to different age groups or class of people. The paper intends to see the river as a major multifunctional public space to attract people for different activities and re-establish the relationship of the river with the settlement. Hence, it is apprehended that the paper is not only intended to a simple riverfront conservation project but unlike others it is a place which is created for the people, by the people and of the people towards a holistic community development through a sustainable approach.

Keywords: holistic community development, public activity space, river-urban precinct, urban dead space

Procedia PDF Downloads 136

Authors: Alex Ellery

Abstract:

Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

Procedia PDF Downloads 424

Authors: Yuang Guo, Dewancker Bart

Abstract:

The primary energy consumption of buildings throughout China was approximately 814 million tons of coal equivalents in 2014, which accounts for 19.12% of China's total primary energy consumption. Also, the energy consumption of public buildings takes a bigger share than urban residential buildings and rural residential buildings among the total energy consumption. To improve the level of energy demand, various design parameters were chosen. Meanwhile, a series of simulations by Energy Plus (EP-Launch) is performed using a base case model established in Open Studio. Through the results, 16%-23% of total energy demand reductions can be found in the severe cold zone of China, and it can also provide a reference for the architectural design of other similar climate zones.

Keywords: energy consumption, design parameters, indoor thermal comfort, simulation study, severe cold climate zone

Procedia PDF Downloads 156

Authors: Robert Caulk

Abstract:

A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

Procedia PDF Downloads 89

Authors: Mohamed Lotfy, Ghada Soliman

Abstract:

Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

Procedia PDF Downloads 95

Authors: Nima Pirhadi, Shao Yong Bo, Xusheng Wan, Jianguo Lu, Jilei Hu

Abstract:

Although gravels and gravelly soils are assumed to be non-liquefiable because of high conductivity and small modulus; however, the occurrence of this phenomenon in some historical earthquakes, especially recently earthquakes during 2008 Wenchuan, Mw= 7.9, 2014 Cephalonia, Greece, Mw= 6.1 and 2016, Kaikoura, New Zealand, Mw = 7.8, has been promoted the essential consideration to evaluate risk assessment and hazard analysis of seismic gravelly soil liquefaction. Due to the limitation in sampling and laboratory testing of this type of soil, in situ tests and site exploration of case histories are the most accepted procedures. Of all in situ tests, dynamic penetration test (DPT), Which is well known as the Chinese dynamic penetration test, and shear wave velocity (Vs) test, have been demonstrated high performance to evaluate seismic gravelly soil liquefaction. However, the lack of a sufficient number of case histories provides an essential limitation for developing new models. This study at first investigates recent earthquakes that caused liquefaction in gravelly soils to collect new data. Then, it adds these data to the available literature’s dataset to extend them and finally develops new models to assess seismic gravelly soil liquefaction. To validate the presented models, their results are compared to extra available models. The results show the reasonable performance of the proposed models and the critical effect of gravel content (GC)% on the assessment.

Keywords: liquefaction, gravel, dynamic penetration test, shear wave velocity

Procedia PDF Downloads 201

Authors: Mohamed Elmeshad

Abstract:

During the mid-1990's Egypt had become obliged to implement the Economic Reform and Structural Adjustment Program that included broad economic liberalization, expansion of the private sector and a contraction the size of government spending. This coincided as well with attempts to appear more democratic and open to liberalizing public space and discourse. At the same time, economic pressures and the proliferation of social media access and activism had led to increased pressure to open a mediascape and remove it from the clutches of the government, which had monopolized print and broadcast mass media for over 4 decades by that point. However, the mechanisms that governed the privatization of mass media allowed for sustained government control, even through the prism of ostensibly privately owned newspapers and television stations. These mechanisms involve barriers to entry from a financial and security perspective, as well as operational capacities of distribution and access to means of production. The power dynamics between mass media establishments and the state were moulded during this period in a novel way. Power dynamics within media establishments had also formed under such circumstances. The changes in the country's political economy itself somehow mirrored these developments. This paper will examine these dynamics and shed light on the political economy of Egypt's newly privatized mass media in the early 2000's especially. Methodology: This study will rely on semi-structured interviews from individuals involved with these changes from the perspective of the media organizations. It also will map out the process of media privatization by looking at the administrative, operative and legislative institutions and contexts in order to attempt to draw conclusions on methods of control and the role of the state during the process of privatization. Finally, a brief discourse analysis will be necessary in order to aptly convey how these factors ultimately reflected on media output. Findings and conclusion: The development of Egyptian private, “independent” mirrored the trajectory of transitions in the country’s political economy. Liberalization of the economy meant that a growing class of business owners would explore opportunities that such new markets would offer. However the regime’s attempts to control access to certain forms of capital, especially in sectors such as the media affected the structure of print and broadcast media, as well as the institutions that would govern them. Like the process of liberalisation, much of the regime’s manoeuvring with regards to privatization of media had been haphazardly used to indirectly expand the regime and its ruling party’s ability to retain influence, while creating a believable façade of openness. In this paper, we will attempt to uncover these mechanisms and analyse our findings in ways that explain how the manifestations prevalent in the context of a privatizing media space in a transitional Egypt provide evidence of both the intentions of this transition, and the ways in which it was being held back.

Keywords: business, mass media, political economy, power, privatisation

Procedia PDF Downloads 227

Authors: Sara Kakuk

Abstract:

Pedagogy has always been open to other disciplines that reflect about the educational process (philosophy, sociology, psychology, anthropology, technology, etc.). Its interdisciplinary openness puts education, as the subject of pedagogy within a broader context of the community, enabling the knowledge of other disciplines to contribute to a better understanding of the fundamental pedagogical notion of education. The purpose of pedagogy as a science serves humans, strives towards humans, must be for humans, and this is its ultimate goal. Humans are essentially dependent on education, which is also considered as a category of humans’ being, because through education an entire world develops in humans. Anthropological assumptions of humans as "deficient beings" see the solution in education, but they also indicate a wealth of shortcomings, because they provide an opportunity for enrichment and formation of culture, living and the self. In that context, this paper illustrates the determination of pedagogy through an anthropological conception of humans and the phenomenon of education. It presents a review of anthropological ideas about education, by providing an analysis of relevant literature dealing with the anthropological notion of humans, which provides fruitful conditions for a pedagogical reconsideration of education.

Keywords: pedagogy, education, humans, anthropology, culture

Procedia PDF Downloads 450

Authors: Jana Ismail, Layla Fallatah, Maha Alshmaisi

Abstract:

ChatGPT, a cutting-edge language model built on the GPT-3.5 architecture, has garnered attention for its profound natural language processing capabilities, holding promise for transformative applications in customer service and content creation. This study delves into ChatGPT's architecture, aiming to comprehensively understand its strengths and potential limitations. Through systematic experiments across diverse domains, such as general knowledge and creative writing, we evaluated the model's coherence, context retention, and task-specific accuracy. While ChatGPT excels in generating human-like responses and demonstrates adaptability, occasional inaccuracies and sensitivity to input phrasing were observed. The study emphasizes the impact of prompt design on output quality, providing valuable insights for the nuanced deployment of ChatGPT in conversational AI and contributing to the ongoing discourse on the evolving landscape of natural language processing in artificial intelligence.

Keywords: artificial Inelegance, chatGPT, open AI, NLP

Procedia PDF Downloads 77

Authors: Meifang Chen

Abstract:

Background: As China increased its engagement in global health affairs and research, global Health (GH) emerged as a new discipline in China after 2010. Duke Kunshan University (DKU), as a member of the Chinese Consortium of Universities for Global Health, is the first university that experiments “Western-style” liberal arts and sciences (LAS) education pedagogy in GH undergraduate and postgraduate programs in China since 2014. The COVID-19 pandemic has brought significant disruption to education across the world. At the peak of the pandemic, 45 countries in the Europe and Central Asia regions closed their schools, affecting 185 million students. DKU, as many other universities and schools, was unprepared for this sudden abruptness and were forced to build emergency remote learning systems almost immediately. This qualitative study aims to gain a deeper understanding of 1) how Chinese students and parents embrace GH training in the liberal arts and sciences education context, and 2) how the COVID pandemic influences the students’ learning experience as well as affects students and parents’ perceptions of GH-related study and career development in China. Methods: students and parents at DKU were invited and recruited for open-ended, semi-structured interviews during Sept 2021-Mar 2022. Open coding procedures and thematic content analysis were conducted using Nvivo 12 software. Results: A total of 18 students and 36 parents were interviewed. Both students and parents were fond of delivering GH education using the liberal arts and sciences pedagogy. Strengths of LAS included focusing on whole person development, allowing personal enrichment, tailoring curriculum to individual’s interest, providing well-rounded knowledge through interdisciplinary learning, and increasing self-study capacity and adaptability. Limitations of LAS included less time to dive deep into disciplines. There was a significant improvement in independence, creativity, problem solving, and team coordinating capabilities among the students. The impact of the COVID pandemic on GH learning experience included less domestic and abroad fieldwork opportunities, less in-person interactions (especially with foreign students and faculty), less timely support, less lab experience, and coordination challenges due to time-zone difference. The COVID pandemic increased the public’s awareness of the importance of GH and acceptance of GH as a career path. More job and postgraduate program opportunities were expected in near future. However, some parents expressed concerns about GH-related employment opportunities in China. Conclusion: The application of the liberal arts and science education pedagogy in GH training were well-received by the Chinese students and parents. Although global pandemic like COVID disrupted GH learning in many ways, most Chinese students and parents held optimistic attitudes toward GH study and career development.

Keywords: COVID, global health, liberal arts and sciences pedagogy, China

Procedia PDF Downloads 115

Authors: Alexandre Marin, Alexandra Bac, Laurent Astart

Abstract:

New numerical methods for PDE resolution (such as Finite Volumes (FV) or Virtual Elements Method (VEM)) open new needs in terms of meshing of domains of interest, and in particular, polyhedral meshes have many advantages. One way to build such meshes consists of constructing Restricted Voronoi Diagrams (RVDs) whose boundaries respect the domain of interest. By minimizing a function defined for RVDs, the shapes of cells can be controlled, e.g., elongated according to user-defined directions or adjusted to comply with given aspect ratios (anisotropy) and density variations. In this paper, our contribution is threefold: First, we introduce a new gradient formula for the Voronoi tessellation energy under a continuous anisotropy field. Second, we describe a meshing algorithm based on the optimisation of this function that we validate against state-of-the-art approaches. Finally, we propose a hierarchical approach to speed up our meshing algorithm.

Keywords: anisotropic Voronoi diagrams, meshes for numerical simulations, optimisation, volumic polyhedral meshing

Procedia PDF Downloads 116

Authors: Sira Suren, Soorathep Kheawhom

Abstract:

This work focuses the development of thin and flexible zinc-air battery. The battery with an overall thickness of about 300 μm was fabricated by an inexpensive screen-printing technique. Commercial nano-silver ink was used as both current collectors and catalyst layer. Carbon black ink was used to fabricate cathode electrode. Polypropylene membrane was used as the cathode substrate and separator. 9 M KOH was used as the electrolyte. A mixture of Zn powder and ZnO was used to prepare the anode electrode. Types of conductive materials (Bi2O3, Na2O3Si and carbon black) for the anode and its concentration were investigated. Results showed that the battery using 29% carbon black showed the best performance. The open-circuit voltage and energy density observed were 1.6 V and 694 Wh/kg, respectively. When the battery was discharged at 10 mA/cm2, the potential voltage observed was 1.35 V. Furthermore, the battery was tested for its flexibility. Upon bending, no significant loss in performance was observed.

Keywords: flexible, Gel Electrolyte, screen printing, thin battery, Zn-Air battery

Procedia PDF Downloads 210

Authors: Prakash Persad, Kelvin Loutan, Trichelle Seepersad

Abstract:

The Finite Element Method is commonly used in the analysis of flexible manipulators to predict elastic displacements and develop joint control schemes for reducing positioning error. In order to preserve simplicity, regular geometries, ideal joints and connections are assumed. This paper presents the dynamic FE analysis of a 4- degrees of freedom open chain manipulator, intended for striking a curved 3D surface percussion musical instrument. This was done utilizing the new MultiBody Dynamics Module in COMSOL, capable of modeling the elastic behavior of a body undergoing rigid body type motion.

Keywords: dynamic modeling, entertainment robots, finite element method, flexible robot manipulators, multibody dynamics, musical robots

Procedia PDF Downloads 337

Authors: Lican Wang, Rongqian Chen, Yancheng You, Ruofan Qiu

Abstract:

In the applications of jet engine, open-jet wind tunnel and airframe, there wildly exists a shear layer formed by the velocity and temperature gradients between jet flow and surrounded medium. The presence of shear layer will refract and reflect the sound path that consequently influences the measurement results in far-field. To investigate and evaluate the shear layer effect, a gradient term suppression and filtering method is adopted to simulate sound propagation through a steady sheared flow in three dimensions. Two typical configurations are considered: one is an incompressible and cold jet flow in wind tunnel and the other is a compressible and hot jet flow in turbofan engine. A numerically linear microphone array is used to localize the position of given sound source. The localization error is presented and linearly fitted.

Keywords: aeroacoustic, linearized Euler equation, acoustic propagation, source localization

Procedia PDF Downloads 205

Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

Abstract:

Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

Procedia PDF Downloads 317

Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

Procedia PDF Downloads 156

Authors: Leonard Mike McNelly Longwa, Divine Kusosa Musiku, Dieudonne Nahum Kabeya

Abstract:

In this paper, the bifurcation analysis of oilfields in the Democratic Republic of Congo is presented in order to enhance petroleum production in an intense tectonic evolution characterized by distinct compressive and extensive phases and the digenetic transformation in the reservoirs during burial geological configuration. The use of porous media in the Makelekese MS-25 field has been established to simulate the boundaries within 3 sedimentary basins open to exploration including the coastal basin with an area of 5992 km², a central basin with an area of 800,000 km², the western branch of the East African Rift in which there are 50,000 km². The fractal characterization of complex hydro-dynamic fractures in oilfields is developed to facilitate the oil production process based on the reservoirs bifurcation model.

Keywords: reservoir bifurcation, fractal characterization, permeability, conductivity, skin effect

Procedia PDF Downloads 131

Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

Abstract:

This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

Procedia PDF Downloads 227

Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Ella Quigley, Kevin Tinkham

Abstract:

Fire performance is a crucial aspect to consider when designing cladding products, and testing this performance is extremely expensive. Appropriate use of numerical simulation of fire performance has the potential to reduce the total number of fire tests required when designing a product by eliminating poor-performing design ideas early in the design phase. Due to the complexity of fire and the large spectrum of failures it can cause, multi-disciplinary models are needed to capture the complex fire behavior and its structural effects on its surroundings. Working alongside Tata Steel U.K., the authors have focused on completing a coupled CFD-FEA simulation model suited to test Polyisocyanurate (PIR) based sandwich panel products to gain confidence before costly experimental standards testing. The sandwich panels are part of a thermally insulating façade system primarily for large non-domestic buildings. The work presented in this paper compares two coupling methodologies of a replicated physical experimental standards test LPS 1181-1, carried out by Tata Steel U.K. The two coupling methodologies that are considered within this research are; one-way and two-way. A one-way coupled analysis consists of importing thermal data from the CFD solver into the FEA solver. A two-way coupling analysis consists of continuously importing the updated changes in thermal data, due to the fire's behavior, to the FEA solver throughout the simulation. Likewise, the mechanical changes will also be updated back to the CFD solver to include geometric changes within the solution. For CFD calculations, a solver called Fire Dynamic Simulator (FDS) has been chosen due to its adapted numerical scheme to focus solely on fire problems. Validation of FDS applicability has been achieved in past benchmark cases. In addition, an FEA solver called ABAQUS has been chosen to model the structural response to the fire due to its crushable foam plasticity model, which can accurately model the compressibility of PIR foam. An open-source code called FDS-2-ABAQUS is used to couple the two solvers together, using several python modules to complete the process, including failure checks. The coupling methodologies and experimental data acquired from Tata Steel U.K are compared using several variables. The comparison data includes; gas temperatures, surface temperatures, and mechanical deformation of the panels. Conclusions are drawn, noting improvements to be made on the current coupling open-source code FDS-2-ABAQUS to make it more applicable to Tata Steel U.K sandwich panel products. Future directions for reducing the computational cost of the simulation are also considered.

Keywords: fire engineering, numerical coupling, sandwich panels, thermo fluids

Procedia PDF Downloads 90

Authors: Hasan Al Dabbas

Abstract:

In this paper, it is addressed that the mechanical machinery captures a major share of innovation in drilling and milling chucks technology. Users demand higher speeds in milling because they are cutting more aluminum and are relying on higher speeds to eliminate secondary finishing operations. To meet that demand, milling-machine builders have enhanced their machine’s rigidity. Moreover, faster cutting has caught up with boring mills. Cooling these machine’s internal components is a challenge at high speeds. Another trend predicted that it is more use of controlled axes to let the machines do many more operations on 5 sides without having to move or re-fix the work. Advances of technology in mechanical engineering have helped to make high-speed machining equipment. To accompany these changes in milling and drilling machines chucks, the demand of easiest software is increased. An open architecture controller is being sought that would allow flexibility and information exchange.

Keywords: drilling, milling, chucks, cutting edges, tools, machines

Procedia PDF Downloads 572

Authors: Ajab G. Majidi, Bilal Bingölbali, Adem Akpınar

Abstract:

This study aims to investigate the amount of energy (economic wave energy potential) that can be obtained from the existing wave energy converters in the high wave energy potential region of the Black Sea in terms of wave energy potential and their performance at different depths in the region. The data needed for this purpose were obtained using the calibrated nested layered SWAN wave modeling program version 41.01AB, which was forced with Climate Forecast System Reanalysis (CFSR) winds from 1979 to 2009. The wave dataset at a time interval of 2 hours was accumulated for a sub-grid domain for around Karaburun beach in Arnavutkoy, a district of Istanbul city. The annual sea state characteristic matrices for the five different depths along with a vertical line to the coastline were calculated for 31 years. According to the power matrices of different wave energy converter systems and characteristic matrices for each possible installation depth, the probability distribution tables of the specified mean wave period or wave energy period and significant wave height were calculated. Then, by using the relationship between these distribution tables, according to the present wave climate, the energy that the wave energy converter systems at each depth can produce was determined. Thus, the economically feasible potential of the relevant coastal zone was revealed, and the effect of different depths on energy converter systems is presented. The Oceantic at 50, 75 and 100 m depths and Oyster at 5 and 25 m depths presents the best performance. In the 31-year long period 1998 the most and 1989 is the least dynamic year.

Keywords: annual power production, Black Sea, efficiency, power production performance, wave energy converter

Procedia PDF Downloads 133

Authors: Rachida Houssa, Hassan Rhinane, Fadoumo Ali Malouw, Amina Oulmaalem

Abstract:

Since the early 70s, the Moroccan Atlantic sea was subjected to the pressure of the bottom trawling, one of the most destructive techniques seabed that cause havoc on fishing catch, nonselective, and responsible for more than half of all releases of fish around the world. The present paper aims to map and assess the impact of the activity of the bottom trawling of the Moroccan Atlantic coast. For this purpose, a dataset of thirty years, between 1962 and 1999, from foreign fishing vessels using bottom trawling, has been used and integrated in a GIS. To estimate the extent and the importance of the geographical distribution of the trawling effort, the Moroccan Atlantic area was divided into a grid of cells of 25 km2 (5x5 km). This grid was joined to the effort trawling data, creating a new entity with a table containing spatial overlay grid with the polygon of swept surfaces. This mapping model allowed to quantify the used fishing effort versus time and to generate the trace indicative of trawling efforts on the seabed. Indeed, for a given year, a grid cell may have a swept area equal to 0 (never been touched by the trawl) or 25 km2 (the trawled area is similar to the cell size) or may be 100 km2 indicating that for this year, the scanned surface is four times the cell area. The results show that the total cumulative sum of trawled area is approximately 28,738,326 km2, scattered throughout the Atlantic coast. 95% of the overall trawling effort is located in the southern zone, between 29°N and 20°30'N. Nearly 5% of the trawling effort is located in the northern coastal region, north of 33°N. The center area between 33°N and 29°N is the least swept by Russian commercial vessels because in this region the majority of the area is rocky, and non trawlable.

Keywords: GIS, Moroccan Atlantic Ocean, seabed, trawling

Procedia PDF Downloads 329

Authors: Sultan Alanazi, Adwan Alanazi

Abstract:

Social applications consist of powerful tools that allow people to connect and interact with each other. However, its negative use cannot be ignored. Cyberbullying is a new and serious Internet problem. Cyberbullying is one of the most common risks for teenagers to go online. More than half of young people report that they do not tell their parents when this will occur, which can have significant physiological consequences. Cyberbullying involves the deliberate use of digital media on the Internet to convey false or embarrassing information about others. Therefore, this article provides a way to detect cyber-bullying in social media applications for parents. The purpose of our work is to develop an architectural model for identifying and measuring the state of Cyberbullying faced by children on social media applications. For parents, this will be a good tool for monitoring their children without invading their privacy. Finally, some interesting open-ended questions were raised, suggesting promising ideas for starting new research in this new field.

Keywords: cyberbullying, cyber bullying, internet crimes, social media security, E-crimes

Procedia PDF Downloads 139

Authors: S. Boria

Abstract:

In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: composite material, crashworthiness, finite element analysis, optimization

Procedia PDF Downloads 256