Search results for: virtual Machine

Authors: Athanasia Kouroupa, Karen Irvine, Sivana Mengoni, Shivani Sharma

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Exploring parents’ preferences towards technology-based interventions for children on the autism spectrum can inform future research and support technology design. The study aimed to provide a comprehensive description of parents’ knowledge and preferences about innovative technology to support children on the autism spectrum. Survey data were collected from parents (n = 267) internationally. The survey included information about the use of conventional (e.g., smartphone, iPod, tablets) and non-conventional (e.g., virtual reality, robot) technologies. Parents appeared to prefer conventional technologies such as tablets and dislike non-conventional ones. They highlighted the positive contribution technology brought to the children’s lives during the pandemic. A few parents were equally concerned that the compulsory introduction of technology during the pandemic was associated with elongated time on devices. The data suggested that technology-based interventions are not widely known, need to be financially approachable and achieve a high standard of design to engage users.

Keywords: autism, intervention, preferences, technology

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Authors: A. Sopharak, B. Uyyanonvara, S. Barman

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Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.

Keywords: diabetic retinopathy, microaneurysm, naive Bayes classifier, SVM classifier

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Authors: Mohamed Laamim, Abdelilah Rochd, Aboubakr Benazzouz, Abderrahim El Fadili

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Smart grids have recently sparked a lot of interest in the energy sector as they allow for the modernization and digitization of the existing power infrastructure. Smart grids have several advantages in terms of reducing the environmental impact of generating power from fossil fuels due to their capacity to integrate large amounts of distributed energy resources. On the other hand, smart grid technologies necessitate many field investigations and requirements. This paper focuses on the major difficulties that governments face around the world and compares them to the situation in Morocco. Also presented in this study are the current works and projects being developed to improve the penetration of smart grid technologies into the electrical system. Furthermore, the findings of this study will be useful to promote the smart grid revolution in Morocco, as well as to construct a strong foundation and develop future needs for better penetration of technologies that aid in the integration of smart grid features.

Keywords: smart grids, microgrids, virtual power plants, digital twin, distributed energy resources, vehicle-to-grid, advanced metering infrastructure.

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Authors: Suktisuddha Goswami, Surekha Chukkali

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Metaverse is a real time rendered 3D world which is an extension of the virtual reality, augmented reality, mixed reality, and holographic reality. While using the metaverse can enhance various aspects of our lives, it might also create certain challenges. However, since the concept of the metaverse is very new, there is a lack of research on factors influencing the individual’s behavioural intentions to use it. To address this gap, this quantitative research study was conducted to understand the factors influencing the behavioural intention of individuals towards metaverse usage. This research was conducted through a large-scale questionnaire survey of 325 Indian students at three major engineering colleges. The questionnaire was adequately customized for the present study. It was found that behavioral intention towards metaverse usage differs among individuals. There were few individuals who had no intention of using metaverse in near future, while some of them were already using it and a few were significantly inclined towards using it. The findings of this study have suggested that behavioural intention was significantly and positively related to performance expectancy and effort expectancy of individuals.

Keywords: behavioral intention, effort expectancy, performance expectancy, technology, metaverse

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Authors: Elias K. Maragos, Petros E. Maravelakis

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In Dynamic Data Envelopment Analysis (DDEA), which is a subfield of Data Envelopment Analysis (DEA), the productivity of Decision Making Units (DMUs) is considered in relation to time. In this case, as it is accepted by the most of the researchers, there are outputs, which are produced by a DMU to be used as inputs in a future time. Those outputs are known as intermediates. The common models, in DDEA, do not take into account the shape of the distribution of those inputs, outputs or intermediates data, assuming that the distribution of the virtual value of them does not deviate from linearity. This weakness causes the limitation of the accuracy of the analytical power of the traditional DDEA models. In this paper, the authors, using the concept of piecewise linear inputs and outputs, propose an extended DDEA model. The proposed model increases the flexibility of the traditional DDEA models and improves the measurement of the dynamic performance of DMUs.

Keywords: Dynamic Data Envelopment Analysis, DDEA, piecewise linear inputs, piecewise linear outputs

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Authors: Nidhi Gopal

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Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

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Authors: Lou J. Pino, Mark Campbell, Matthew J. Kennedy, Ashleigh C. Kennedy

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A concussion is complex and nuanced, with cognitive rest being a key component of recovery. Cognitive overexertion during rehabilitation from a concussion is associated with delayed recovery. However, daily living imposes cognitive demands that may be unavoidable and difficult to quantify. Therefore, a portable tool capable of alerting patients before cognitive overexertion occurs could allow patients to maintain their quality of life while preventing symptoms and recovery setbacks. EEG allows for a sensitive measure of cognitive exertion. Clinical 32-lead EEG headsets are not practical for day-to-day concussion rehabilitation management. However, there are now commercially available and affordable portable EEG headsets. Thus, these headsets can potentially be used to continuously monitor cognitive exertion during mental tasks to alert the wearer of overexertion, with the aim of preventing the occurrence of symptoms to speed recovery times. The objective of this study was to test an algorithm for predicting cognitive exertion from EEG data collected from a portable headset. EEG data were acquired from 10 participants (5 males, 5 females). Each participant wore a portable 4 channel EEG headband while completing 10 tasks: rest (eyes closed), rest (eyes open), three levels of the increasing difficulty of logic puzzles, three levels of increasing difficulty in multiplication questions, rest (eyes open), and rest (eyes closed). After each task, the participant was asked to report their perceived level of cognitive exertion using the NASA Task Load Index (TLX). Each participant then completed a second session on a different day. A customized machine learning model was created using data from the first session. The performance of each model was then tested using data from the second session. The mean correlation coefficient between TLX scores and predicted cognitive exertion was 0.75 ± 0.16. The results support the efficacy of the algorithm for predicting cognitive exertion. This demonstrates that the algorithms developed in this study used with portable EEG devices have the potential to aid in the concussion recovery process by monitoring and warning patients of cognitive overexertion. Preventing cognitive overexertion during recovery may reduce the number of symptoms a patient experiences and may help speed the recovery process.

Keywords: cognitive activity, EEG, machine learning, personalized recovery

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Authors: Ce Liu, Wei Huo

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A nonlinear trajectory tracking controller for quadrotor helicopter based on controlled Lagrangian (CL) method is proposed in this paper. A Lagrangian system with virtual angles as generated coordinates rather than Euler angles is developed. Based on the model, the matching conditions presented by nonlinear partial differential equations are simplified and explicitly solved. Smooth tracking control laws and the range of control parameters are deduced based on the controlled energy of closed-loop system. Besides, a constraint condition for reference accelerations is deduced to identify the trackable reference trajectories by the proposed controller and to ensure the stability of the closed-loop system. The proposed method in this paper does not rely on the division of the quadrotor system, and the design of the control torques does not depend on the thrust as in backstepping or hierarchical control method. Simulations for a quadrotor model demonstrate the feasibility and efficiency of the theoretical results.

Keywords: quadrotor, trajectory tracking control, controlled lagrangians, underactuated system

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Authors: Farah Al-Fityani, Aljohara Alsowail, Shatha Bindawood, Heba Balrbeah

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Locket is a popular app that lets users share spontaneous photos with a close circle of friends. The app offers a unique way to stay connected with loved ones by allowing users to see glimpses of their day through photos displayed on a widget on their home screen. This summary outlines the process of developing an app like Locket, highlighting the importance of user privacy and security. It also details the findings of a study on user engagement with the Locket app, revealing positive sentiment towards its features and concept but also identifying areas for improvement. Overall, the summary portrays Locket as a successful app that is changing the way people connect on social media.

Keywords: locket, app, machine learning, connect

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Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

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What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

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Authors: Sisaynew Tesfaw Admassu

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The strengthening of timber beams can be necessary for several reasons including the increase of live loads (possible in a historical building for a change of destination of use or upgrading to meet new requirements), the reduction of the resistant cross-sections following deterioration (attacks of biological agents such as fungi, and insects) or traumatic events (fires) and the excess of deflection in the members. The main purpose of strengthening an element is not merely to repair it, but also to prevent and minimize the appearance of future problems. This study did an experimental investigation on the behavior of reference and strengthened solid timber beams. The strengthening materials used in this study were CSM-450 glass fiber and steel materials for both flexural and shear strengthening techniques. Twenty-two solid timber beams of Juniperus procera (TID) species with the dimensions of 60 x 90 x 780 mm were used in the present study. The binding material to bond the strengthening materials with timber was general-purpose resin with Luperox® K10 MEKP catalyst. Three beams were used as control beams (unstrengthen beams) while the remaining nineteen beams were strengthened using the strengthening materials for flexure and shear. All the beams were tested for three points loading to failure by using a Universal Testing Machine, UTM-600kN machine. The experimental results showed that the strengthened beams performed better than the unstrengthen beams. The experimental result of flexural strengthened beams showed that the load-bearing capacity of strengthened beams increased between 16.34 – 42.55%. Four layers of Glass Fiber Reinforced polymer on the tension side of the beams was shown to be the most effective way to enhance load-bearing capacity. The strengthened beams also have an enhancement in their flexural stiffness. The stiffness of flexural strengthened beams was increased between 1.18 – 65.53% as compared to the control beams. The highest increment in stiffness has occurred on beams strengthened using 2x60 mm steel plates. The shear-strengthened beams showed a relatively small amount of performance as compared to flexural-strengthened beams; the reason is that the beams are sufficient for shear. The polyester resin used in the experimental work showed good performance in bonding agents between materials. The resin showed more effectiveness in GFRP materials than steel materials.

Keywords: heritage structures, strengthening, stiffness, adhesive, polyester resin, steel plates

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Authors: Xabier Olaz Moratinos

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

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Helee Dave

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Globalization has helped in the growth and change of the Indian economy to a great extent. The purchasing power of Indians has increased. IT Infrastructure has considerably improved in India. There is an increase in the usage of smartphones. The smartphones facilitate all sorts of work now a day, from getting groceries to planning a tour; it is just one click away. Similar is the case with equity trading. The traders in equity market can now deal with their stocks through mobile applications eliminating the middle man. The traders do not have an option but to open a dematerialization account with the banks which are compulsory enough irrespective of their mode of transaction that is online or offline. Considering that India is a young country having more than 50% of its population below the age of 25 and 65% of its population below the age of 35; this youth is comfortable with the usage of smartphones. The banking industry is also providing a virtual platform supporting equity market industry. Yet equity trading through online applications is at an infant stage. This paper primarily attempts to understand challenges and opportunities faced by equity trading through mobile apps in India.

Keywords: BPO, business process outsourcing, de-materialization account, equity, ITES, information technology enabled services

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Authors: João Pedro Albino, Ana Cláudia Pires Ferreira de Lima

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Humanity has undergone a transformation from the physical to the virtual world, generating an enormous amount of data on the world wide web, known as big data. Many facts that occur in the physical world or in the digital world are proven through records made on the internet, such as digital photographs, posts on social media, contract acceptances by digital platforms, email, banking, and messaging applications, among others. These data recorded on the internet have been used as evidence in judicial proceedings. The identification of internet users is essential for the security of legal relationships. This research was carried out on scientific articles and materials from courses and lectures, with an analysis of Brazilian legislation and some judicial decisions on the request of static data from logs and Internet Protocols (IPs) from application and connection providers. In this article, we will address the determination of authorship of data processing on the internet by obtaining the IP address and the appropriate judicial procedure for this purpose under Brazilian law.

Keywords: IP address, digital forensics, big data, data analytics, information and communication technology

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Authors: Piedad Garrido, Fernando Repulles, Andy Bloor, Julio A. Sanguesa, Jesus Gallardo, Vicente Torres, Jesus Tramullas

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With the emergence and development of Information and Communications Technologies (ICTs), Higher Education is experiencing rapid changes, not only in its teaching strategies but also in student’s learning skills. However, we have noticed that students often have difficulty when seeking innovative, useful, and interesting learning resources for their work. This is due to the lack of supervision in the selection of good query tools. This paper presents AINA, an Information Retrieval (IR) computer system aimed at providing motivating and stimulating content to both students and teachers working on different areas and at different educational levels. In particular, our proposal consists of an open virtual resource environment oriented to the vast universe of Disney comics and cartoons. Our test suite includes Disney’s long and shorts films, and we have performed some activities based on the Just In Time Teaching (JiTT) methodology. More specifically, it has been tested by groups of university and secondary school students.

Keywords: information retrieval, animation, educational resources, JiTT

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Patricia P. M. C. Lourenco, Javier Bringué Sala, Anaisa D. A. de Sena

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Almost everyone in Dramaland knows the names of big Korean stars that grace their computer screens on a roll through social media and video streaming platforms that enable awareness of Korean dramas and lifestyle at a click. A surface culture instilled with notions of belonging has redefined the meaning of friendship and challenged deep inner values. Not everyone, however, knows Chinese Dramas or their stars, which is a consequence of Dramaland's focus on Korean dramas and promoting the Korean experience. Despite a parity in terms of production quality, star power, scripts and compelling visual settings, Chinese Dramas have been playing catch up to their famous counterparts. While they might have a strong competitive soft power for international drama fans, the soft power of Korean dramas is imbued with substantial societal values that they want to share with others. Those values are portrayed in an artistic way that connects with audiences who experience loneliness in the non-virtual world contrary to the way Chinese Dramas are perceived.

Keywords: Chinese dramas, fandom, Korean dramas, participatory culture, value perception, soft power, surface culture

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Authors: Sanjay M. Tailor, Urmila H. Patel

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Phthalyl Sulfacetamide belongs to well-known member of antimicrobial sulfonamide family. It is a potent antitumor drug. Structural characteristics of 4-amino-N-(2quinoxalinyl) benzene-sulfonamides (Phthalyl Sulfacetamide), C14H12N4O2S has been studied by method of X-ray crystallography. The compound crystallizes in monoclinic space group P21/n with unit cell parameters a= 7.9841 Ǻ, b= 12.8208 Ǻ, c= 16.6607 Ǻ, α= 90˚, β= 93.23˚, γ= 90˚and Z=4. The X-ray based three-dimensional structure analysis has been carried out by direct methods and refined to an R-value of 0.0419. The crystal structure is stabilized by intermolecular N-H…N, N-H…O and π-π interactions. The Hirshfeld surfaces and consequently the fingerprint analysis have been performed to study the nature of interactions and their quantitative contributions towards the crystal packing. An analysis of Hirshfeld surfaces and fingerprint plots facilitates a comparison of intermolecular interactions, which are the key elements in building different supramolecular architectures. Docking is used for virtual screening for the prediction of the strongest binders based on various scoring functions. Docking studies are carried out on Phthalyl Sulfacetamide for better activity, which is important for the development of a new class of inhibitors.

Keywords: phthalyl sulfacetamide, crystal structure, hirshfeld surface analysis, docking

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Authors: Kornchanok Chidchaisuwan

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This project is a study of learning activities through experience to enhance career skills and technical abilities on the creative strategies for advertising course of undergraduate students. This instructional model consisted of study learning approaches: 1) Simulation-based learning: used to create virtual learning activities plans for work like working at advertising companies. 2) Project-based learning: Actual work based on the processed creating and focus on producing creative works to present on new media channels. The results of learning management found that there were effects on the students in various areas, including 1) The learners have experienced in the step by step of advertising work process. 2) The learner has the skills to work from the actual work (Learning by Doing), allowing the ability to create, present, and produce the campaign accomplished achievements and published on online media at a better level.

Keywords: technical, advertising, presentation, career skills, experience, simulation based learning

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: K. Sangeeth, P. Rekha, P. Preeja, P. Divya, R. Arya, R. Maneesha

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Wireless sensor networks (WSN) are small or tiny devices that consists of different sensors to sense physical parameters like air pressure, temperature, vibrations, movement etc., process these data and sends it to the central data center to take decisions. The WSN domain, has wide range of applications such as monitoring and detecting natural hazards like landslides, forest fire, avalanche, flood monitoring and also in healthcare applications. With such different applications, it is being taught in undergraduate/post graduate level in many universities under department of computer science. But the cost and infrastructure required to purchase WSN nodes for having the students getting hands on expertise on these devices is expensive. This paper gives overview about the remote triggered lab that consists of more than 100 WSN nodes that helps the students to remotely login from anywhere in the world using the World Wide Web, configure the nodes and learn the WSN concepts in intuitive way. It proposes new way called over the air programming (OTAP) and its internals that program the 100 nodes simultaneously and view the results without the nodes being physical connected to the computer system, thereby allowing for sparse deployment.

Keywords: WSN, over the air programming, virtual lab, AT45DB

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Monapat Sasingha, Suttisak Soralump

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This research presents the behavior of slope of the road along the canal stabilized by short piles. In this investigation, the centrifuge machine was used, modelling the condition of the water levels in the canal. The centrifuge tests were performed at 35 g. To observe the movement of the soil, visual analysis was performed to evaluate the failure behavior. Conclusively, the use of short piles to stabilize the canal slope proved to be an effective solution. However, the certain amount of settlement was found behind the short pile rows.

Keywords: centrifuge test, slope failure, embankment, stability of slope

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Authors: Ahmad Taghinia, Negar Gholamishaker

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GaAs (gallium arsenide) solar cells have gained significant attention for their use in space applications. These solar cells have the potential for efficient energy conversion and are being explored as potential power sources for electronic devices, satellites, and telecommunication equipment. In this study, the aim is to investigate the effect of adding a window layer and a back surface field (BSF) layer made of InₓGa₍₁₋ₓ₎P material to a GaAs single junction solar cell. In this paper, we first obtain the important electrical parameters of a single-junction GaAs solar cell by utilizing a two-dimensional simulator software for virtual investigation of the solar cell; then, we analyze the impact of adding a window layer and a back surface field layer made of InₓGa₍₁₋ₓ₎P on the solar cell. The results show that the incorporation of these layers led to enhancements in Jsc, Voc, FF, and the overall efficiency of the solar cell.

Keywords: back surface field layer, solar cell, GaAs, InₓGa₍₁₋ₓ₎P, window layer

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Authors: Edwin Cartledge, Jack Clark, Mazaher Molaei-Chalchooghi

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The mixing in the crystallization step of active pharmaceutical ingredient manufacturers was studied via advanced modeling tools to enable a successful scale-up. A virtual representation of the vessel was created, and computational fluid dynamics were used to simulate multiphase flow and, thus, the mixing environment within this vessel. The study identified a significant dead zone in the vessel underneath the impeller and found that increasing the impeller speed and power did not improve the mixing. A series of sensitivity analyses found that to improve mixing, the vessel had to be redesigned, and found that optimal mixing could be obtained by adding two extra cylindrical baffles. The same two baffles from the simulated environment were then constructed and added to the process vessel. By identifying these potential issues before starting the manufacture and modifying the vessel to ensure good mixing, this study mitigated a failed crystallization and potential batch disposal, which could have resulted in a significant loss of high-value material.

Keywords: active pharmaceutical ingredient, baffles, computational fluid dynamics, mixing, modelling

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Authors: Abdulatif Abdulsalam, Mohamed Shaban

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This paper introduces interfacing and replication of electronic tools based on the MATLAB/ SIMULINK mock-up package. Mock-up components contain dc-dc converters, power issue rectifiers, motivation machines, dc gear, synchronous gear, and more entire systems. Power issue rectifier model includes solid state device models. The tools are the clear-cut structure and mock-up of complex energetic systems connecting with power electronic machines.

Keywords: power electronics, machine, MATLAB, simulink

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Authors: Hoda Abugharsa

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In this paper we propose to design a sorter circuit using insertion sorting algorithm. The circuit will be designed using Algorithmic State Machines (ASM) method. That means converting the insertion sorting flowchart into an ASM chart. Then the ASM chart will be used to design the sorter circuit and the control unit.

Keywords: insert sorting algorithm, ASM chart, sorter circuit, state machine, control unit

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Authors: S. Vanaja, P. Panneerselvam, S. Santhanakarthikeyan

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Cloud Computing is a latest trend in Libraries. Entering in to cloud services, Librarians can suit the present information handling and they are able to satisfy needs of the knowledge society. Libraries are now in the platform of universalizing all its information to users and they focus towards clouds which gives easiest access to data and application. Cloud computing is a highly scalable platform promising quick access to hardware and software over the internet, in addition to easy management and access by non-expert users. In this paper, we discuss the cloud’s features and its potential applications in the library and information centers, how cloud computing actually works is illustrated in this communication and how it will be implemented. It discuss about what are the needs to move to cloud, process of migration to cloud. In addition to that this paper assessed the practical problems during migration in libraries, advantages of migration process and what are the measures that Libraries should follow during migration in to cloud. This paper highlights the benefits and some concerns regarding data ownership and data security on the cloud computing.

Keywords: cloud computing, cloud-service, cloud based-ILS, cloud-providers, discovery service, IaaS, PaaS, SaaS, virtualization, Web scale access

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Authors: Essam Al Daoud

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Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

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