Search results for: computer processing of large databases

Authors: Muhammad Usman

Abstract:

Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

Procedia PDF Downloads 221

Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

Abstract:

Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

Procedia PDF Downloads 571

Authors: Jaroslava Sucha, Martin Dolejs, Helena Pipova, Panajotis Cakirpaloglu

Abstract:

The paper introduces the research project which is focused on evaluating the level of pathological relation towards computer or video games playing (including any games played by using a screen such as a mobile or a tablet). The study involves representative sample of the Czech adolescents between ages 11 and 19. This poster presents the psychometric indicators of the new psychologic assessment method (mean, standard deviation, reliability, validity) which will be able to detect an acceptable level of games’ playing and at the same time will detect and describe the level of gaming which might be potentially risky. The prevalence of risky computer game playing at Czech adolescents in age 11 to 19 will be mentioned. The research study also aims to describe the personality profile of the problematic players with respect to the digital games. The research area will encompass risky behaviour, aggression, the level of self-esteem, impulsivity, anxiety and depression. The contribution will introduce a new test method for the assessment of pathological playing computer games. The research will give the first screening information of playing computer games in the Czech Republic by adolescents between 11-19 years. The results clarify what relationship exists between playing computer games and selected personality characteristics (it will describe personality of the gamer, who is in the category of ‘pathological playing computer games’).

Keywords: adolescence, computer games, personality traits, risk behaviour

Procedia PDF Downloads 229

Authors: Tsegay Giday Woldu, Haibin Zhang, Xin Zhang, Yemane Hailu Fissuh

Abstract:

It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms.

Keywords: conjugate gradient method, global convergence, large scale optimization, sufficient descent property

Procedia PDF Downloads 195

Authors: Manqhai Kraai, Adrian M. Shrader, Peter F. Scogings

Abstract:

For animals living in herds, competition between group members increases as herd size increases. The intensity of this competition is likely greater across poor quality landscapes and during the dry season. In contrast to wild herbivores, herd size in domestic livestock is determined by their owners. This then raises the question, how do domestic livestock, like goats, reduce competition for food within these defined herds? To explore this question, large-scale foraging behaviour of both small (12 to 28 individuals) and large (42 to 83 individuals) herds of free-ranging goats were recorded in Tugela Ferry, KwaZulu-Natal, South Africa. The study was conducted on three different landscapes that varied in both food quality and availability, during the wet and dry seasons of 2013-2014. The goats were housed in kraals overnight and let out in the mornings to forage unattended. Thus, foraging decisions were made by the goats and not by herders. The large-scale foraging behaviours focussed on included, (i) total distance travelled by goats while foraging, (ii) distance travelled before starting to feed, (iii) travel speed, and (iv) feeding duration. This was done using Garmin Foretrex 401 GPS devices harnessed to two goats per herd. Irrespective of season, there was no difference in the total distance travelled by the different sized herds across the different quality landscapes. However, both small and large herds started feeding farther from the kraal in the dry compared to the wet season. Despite this, there was no significant seasonal difference in total amount of time the herds spent feeding across the different landscapes. Finally, both small and large herds increased their travel speed across all the landscapes in the dry season, but large herds travelled faster than small herds. This increase was likely to maximise the time that large herds could spend feeding in good areas. Ultimately, these results indicate that both small and large herds were affected by declines in food quality and quantity during the dry season. However, as large herds made greater behavioural adjustments compared to smaller herds (i.e., feeding farther away from the kraal and travelling faster), it appeared that they were more affected by the seasonal increases in intra-herd competition.

Keywords: distance, feeding duration, food availability, food quality, travel speed

Procedia PDF Downloads 121

Authors: Jun-ya Nagase

Abstract:

Recently, the need of colonoscopy is increasing because of the rise of colonic disorder including cancer of the colon. However, current colonoscopy depends on doctor's skill strongly. Therefore, a large intestine endoscope that does not depend on the techniques of a doctor with high safety is required. In this research, we aim at development a novel large intestine endoscope that can realize safe insertion without specific techniques. A wheel movement type robot, a snake-like robot and an earthworm-like robot are all described in the relevant literature as endoscope robots that are currently studied. Among them, the tracked crawler robot can travel by traversing uneven ground flexibly with a crawler belt attached firmly to the ground surface. Although conventional crawler robots have high efficiency and/or high ground-covering ability, they require a comparatively large space to move. In this study, a small cylindrical crawler robot inspired by amoeba locomotion, which does not need large space to move and which has high ground-covering ability, is proposed. In addition, we developed a prototype of the large intestine endoscope using the proposed crawler mechanism. Experiments have demonstrated smooth operation and a forward movement of the robot by application of voltage to the motor. This paper reports the structure, drive mechanism, prototype, and experimental evaluation.

Keywords: tracked-crawler, endoscopic robot, narrow path, amoeba locomotion.

Procedia PDF Downloads 379

Authors: Maher Aburrous, Adel Khelifi, Manar Abu Talib

Abstract:

Transactions performed by financial institutions on daily basis require XML encryption on large scale. Encrypting large volume of message fully will result both performance and resource issues. In this paper a novel approach is presented for securing financial XML transactions using classification data mining (DM) algorithms. Our strategy defines the complete process of classifying XML transactions by using set of classification algorithms, classified XML documents processed at later stage using element-wise encryption. Classification algorithms were used to identify the XML transaction rules and factors in order to classify the message content fetching important elements within. We have implemented four classification algorithms to fetch the importance level value within each XML document. Classified content is processed using element-wise encryption for selected parts with "High", "Medium" or “Low” importance level values. Element-wise encryption is performed using AES symmetric encryption algorithm and proposed modified algorithm for AES to overcome the problem of computational overhead, in which substitute byte, shift row will remain as in the original AES while mix column operation is replaced by 128 permutation operation followed by add round key operation. An implementation has been conducted using data set fetched from e-banking service to present system functionality and efficiency. Results from our implementation showed a clear improvement in processing time encrypting XML documents.

Keywords: XML transaction, encryption, Advanced Encryption Standard (AES), XML classification, e-banking security, fuzzy classification, cryptography, intelligent encryption

Procedia PDF Downloads 403

Authors: Thomas Ousterhout

Abstract:

In an effort to test the ability of a commercial grade EEG headset to effectively measure the N400 ERP, a replication study was conducted to see if similar results could be produced as that which used a medical grade EEG. Pictures of meaningful and meaningless hand postures were borrowed from the original author and subjects were required to perform a semantic discrimination task. The N400 was detected indicating semantic processing of the meaningfulness of the hand postures. The results corroborate those of the original author and support the use of some commercial grade EEG headsets for non-critical research applications.

Keywords: EEG, ERP, N400, semantics, congruency, gestures, emotiv

Procedia PDF Downloads 261

Authors: Nicolò Vaiana, Mariacristina Spizzuoco, Giorgio Serino

Abstract:

In this paper, the results of experimental tests performed on a Helical Wire Rope Isolator (HWRI) are presented in order to describe the dynamic and static behavior of the selected metal device in three different displacements ranges, namely small, relatively large, and large displacements ranges, without and under the effect of a vertical load. A testing machine, allowing to apply horizontal displacement or load histories to the tested bearing with a constant vertical load, has been adopted to perform the dynamic and static tests. According to the experimental results, the dynamic behavior of the tested device depends on the applied displacement amplitude. Indeed, the HWRI displays a softening and a hardening stiffness at small and relatively large displacements, respectively, and a stronger nonlinear stiffening behavior at large displacements. Furthermore, the experimental tests reveal that the application of a vertical load allows to have a more flexible device with higher damping properties and that the applied vertical load affects much less the dynamic response of the metal device at large displacements. Finally, a decrease in the static to dynamic effective stiffness ratio with increasing displacement amplitude has been observed.

Keywords: base isolation, earthquake engineering, experimental hysteresis loops, wire rope isolators

Procedia PDF Downloads 426

Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

Abstract:

Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

Procedia PDF Downloads 128

Authors: Micah J. Dobson

Abstract:

After-school programs of physical education provide children with opportunities to engage in physical activities while developing healthy habits. To ensure that these programs are inclusive, diverse, and engaging, however, schools must consider various factors when designing and implementing them. This study sought to bring out efficient strategies for structuring after-school programs of physical education. The literature review was conducted using various databases and search engines. Some databases that index the journals include ERIC, Google Scholar, Scopus, Web of Science, and EBSCOhost. The search terms were combinations of keywords such as “after-school,” “physical education,” “inclusion,” “diversity,” “engagement,” “program design,” “program implementation,” “program effectiveness,” and “best practices.” The findings of this study suggest that schools that desire inclusivity must consider four key factors when designing and implementing after-school physical education programs. First, the programs must be designed with variety and fun by incorporating activities such as dance, sports, and games that appeal to all students. Second, instructors must be trained to create supportive and positive environments that foster student engagement while promoting physical literacy. Third, schools must collaborate with community stakeholders and organizations to ensure that programs are culturally inclusive and responsive. Fourth, schools can incorporate technology into their programs to enhance engagement and provide additional growth and learning opportunities.In conclusion, this study provides valuable insights into efficient strategies for structuring after-school programs of physical education that are inclusive, diverse, and engaging for all students. By considering these factors when designing and implementing their programs, schools can promote physical activity while supporting students’ overall well-being and health.

Keywords: after-school programs of physical education, community partnership, inclusivity, instructor training, technology

Procedia PDF Downloads 72

Authors: Dian Nur Amalia, Rifqi Dhiemas Aji, Tri Septa Wahyuningsih, Endang Wahyuni

Abstract:

Kepel fruit (Stelechocarpus burahol) is a scarce fruit that belongs as a logogram of Daerah Istimewa Yogyakarta. Kepel fruit can be used as substance of beauty treatment product, such as deodorant and good for skin health, and also contains antioxidant compound. Otherwise, this fruit is scarcely cultivated by people because of its image as a palace fruit and also the flesh percentage just a little, so it has low economic value. The flesh of kepel fruit is about 49% of its whole fruit. This little part as supporting point why kepel fruit has to be extracted and processed with the other product. Yoghurt is milk processing product that also have a role as functional food. Economically, the price of yoghurt is higher than whole milk or other milk processing product. Yoghurt is usually added with flavor of dye from plant or from chemical substance. Kepel fruit has a role as flavor in yoghurt, besides as product that good for digestion, yoghurt with kepel also has function as “beauty” food. Writing method that used is literature study by looking for the potential of kepel fruit as a local fruit of Yogyakarta and yoghurt as milk processing product. The process just like making common yoghurt because kepel fruit just have a role as flavor substance, so it does not affect to the other processing of yoghurt. Food diversification can be done as an effort to increase the value of local resources that proper to compete in Asean Economic Community (AEC), one of the way is producing kepel yoghurt.

Keywords: kepel, yoghurt, Daerah Istimewa Yogyakarta, functional food

Procedia PDF Downloads 312

Authors: Yangze Lan, Ruihua Xv, Feng Zhou, Yijia Shan, Longhao Zhang, Qinghui Xv

Abstract:

Receiving and dispatching trains is an important part of railroad organization, and the risky evaluation of operating personnel is still reflected by scores, lacking further excavation of wrong answers and operating accidents. With natural language processing (NLP) technology, this study extracts the keywords and key phrases of 40 relevant risk events about receiving and dispatching trains and reclassifies the risk events into 8 categories, such as train approach and signal risks, dispatching command risks, and so on. Based on the historical risk data of personnel, the K-Means clustering method is used to classify the risk level of personnel. The result indicates that the high-risk operating personnel need to strengthen the training of train receiving and dispatching operations towards essential trains and abnormal situations.

Keywords: receiving and dispatching trains, natural language processing, risk evaluation, K-means clustering

Procedia PDF Downloads 79

Authors: Marta Cordero-Gracia, Mariola Gomez, Olivier Blesbois, Marina Carrion

Abstract:

One of the difficulties in icing simulations is for extended periods of exposure, when very large ice shapes are created. As well as being large, they can have complex shapes, such as a double horn. For icing simulations, these configurations are currently computed in several steps. The icing step is stopped when the ice shapes become too large, at which point a new mesh has to be created to allow for further CFD and ice growth simulations to be performed. This can be very costly, and is a limiting factor in the simulations that can be performed. A way to avoid the costly human intervention in the re-meshing step of multistep icing computation is to use mesh deformation instead of re-meshing. The aim of the present work is to apply an interpolation method based on Radial Basis Functions (RBF) to transfer deformations from surface mesh to volume mesh. This deformation tool has been developed specifically for icing problems. It is able to deal with localized, sharp and large deformations, unlike the tools traditionally used for more smooth wing deformations. This tool will be presented along with validation on typical two-dimensional icing shapes.

Keywords: ice accretion, interpolation, mesh deformation, radial basis functions

Procedia PDF Downloads 308

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

Abstract:

Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

Procedia PDF Downloads 75

Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

Abstract:

Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

Procedia PDF Downloads 114

Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

Abstract:

Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

Procedia PDF Downloads 170

Authors: Zainab Bibi, Afsheen Aman, Shah Ali Ul Qader

Abstract:

Endo-β-1,4-xylanases [EC 3.2.1.8] are one of the major groups of enzymes that are involved in degradation process of xylan and have several applications in food, textile and paper processing industries. Due to broad utility of endo-β-1,4-xylanase, researchers are focusing to increase the productivity of this hydrolase from various microbial species. Harsh industrial condition, faster reaction rate and efficient hydrolysis of xylan with low risk of contamination are critical requirements of industry that can be fulfilled by synthesizing the enzyme with efficient properties. In the current study, a newly isolated thermophile Geobacillus stearothermophilus KIBGE-IB29 was used in order to attain the maximum production of endo-1,4-β-xylanase. Bacterial culture was isolated from soil, collected around the blast furnace site of a steel processing mill, Karachi. Optimization of various nutritional and physical factors resulted the maximum synthesis of endo-1,4-β-xylanase from a thermophile. High production yield was achieved at 60°C and pH-6.0 after 24 hours of incubation period. Various nitrogen sources viz. peptone, yeast extract and meat extract improved the enzyme synthesis with 0.5%, 0.2% and 0.1% optimum concentrations. Dipotassium hydrogen phosphate (0.25%), potassium dihydrogen phosphate (0.05%), ammonium sulfate (0.05%) and calcium chloride (0.01%) were noticed as valuable salts to improve the production of enzyme. The thermophilic nature of isolate, with its broad pH stability profile and reduced fermentation time indicates its importance for effective xylan saccharification and for large scale production of endo-1,4-β-xylanase.

Keywords: geobacillus, optimization, production, xylanase

Procedia PDF Downloads 306

Authors: David M Gilstrap

Abstract:

In an online course with a large enrollment, the potential exists for the instructor to become overburdened with having to respond to students’ emails, which consequently decreases the instructor’s efficiency in teaching the course. Repetition of instructions is an effective way of reducing confusion among students, which in turn increases their efficiencies, as well. World of Turf is the largest online course at Michigan State University, which employs Brightspace as its management system (LMS) software. Recently, the LMS upgraded its capabilities to utilize agents, which are auto generated email notifications to students based on certain criteria. Agents are additional tools that can enhance course design. They can be run on-demand or according to a schedule. Agents can be timed to effectively remind students of approaching deadlines. The content of these generated emails can also include reinforced instructions. With a large online course, even a small percentage of students that either do not read or do not comprehend the course syllabus or do not notice instructions on course pages can result in numerous emails to the instructor, often near the deadlines for assignments. Utilizing agents to decrease the number of emails from students has enabled the instructor to efficiently instruct more than one thousand students per semester without any graduate student teaching assistants.

Keywords: agents, Brightspace, large enrollment, learning management system, repetition of instructions

Procedia PDF Downloads 200

Authors: Asharaf Abdul Salam

Abstract:

Arabian Gulf countries have norms and rules different from others: having an exodus of male immigrant labor contract holders of age 20-60 years as a floating population. Such a demographic scenario camouflages population ageing. However, it is observed on examining vigilantly, not only in the native population but also in the general population. This research on population ageing in the Arabian Gulf examines ageing scenario and concerns through analyses of international databases (US Census Bureau and United Nations) and national level databases (Censuses and Surveys) apart from a review of published research. Transitions in demography and epidemiology lead to gains in life expectancy and thereby reductions in fertility, leading to ageing of the population in the region. Even after bringing adult immigrants, indices and age pyramids show an increasing ageing trend in the total population, demonstrating an ageing workforce. Besides, the exclusive native population analysis reveals a trend of expansive pyramids (pre-transitional stage) turning to constrictive (transition stage) and cylindrical (post-transition stage) shapes. Age-based indices such as the index of ageing, age dependency ratio, and median age confirm this trend. While the feminine nature of ageing is vivid, gains in life expectancy and causes of death in old age, indicating co-morbidity compression, are concerns to ageing. Preparations are in demand to cope with ageing from different dimensions, as explained in the United Nations Plans of Action. A strategy of strengthening informal care with supportive semi-formal and supplementary formal care networks would alleviate this crisis associated with population ageing.

Keywords: total versus native population, indices of ageing, age pyramids, feminine nature, comorbidity compression, strategic interventions

Procedia PDF Downloads 90

Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

Abstract:

The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

Procedia PDF Downloads 420

Authors: Berihun Dachew, Abdullah Mamun, Joemer Maravilla, Rosa Alati

Abstract:

Background: Hypertensive disorders of pregnancy are a major cause of maternal and childhood morbidity and mortality worldwide. However, its effect on offspring mental and behavioural disorders is unclear. Aims:The aim of this study was to provide the best scientific evidence regarding the association between hypertensive disorders of pregnancy and offspring mental and behavioural problems. Methods: We systematically searched Scopus, PubMed, Cochrane, EMBASE, CINAH and PsycINFO databases. A total of 23 studies (11 included in meta-analysis) were identified. A qualitative analysis was conducted by summarizing, comparing, and contrasting the abstracted data for all included studies. For quantitative analysis, relative risk (RR) with 95% confidence interval (95% CI) was used as pooled effect size. Heterogeneity was assessed by measuring Cochran’s Q and I2 test statistics. Results: Of the 23 studies included in this review, 15 studies found that hypertensive disorders of pregnancy had a negative impact for at least one mental or behavioural problem. The pooled effect of 11 studies included in the meta-analysis showed that preeclampsia was associated with increased risk of offspring schizophrenia (RR=1.37; 95% CI, 1.08-1.72). Conclusions: Intrauterine exposure to pre-eclampsia increased the risk of schizophrenia among offspring. However, we found inconclusive finding on the effect of hypertensive disorders of pregnancy and other mental and behavioural problems. Further high quality, large sample, mother child cohort studies are needed to further progress this area of research.

Keywords: behavioural disorders, hypertensive disorders of pregnancy, mental disorders, offspring

Procedia PDF Downloads 233

Authors: Olabamiji J. Onifade, Peter O. Ajayi, Paul O. Jegede

Abstract:

This study aimed at investigating the preparedness of the undergraduate final year students of Computer Science as the next entrants into the workplace. It assessed their self-efficacy in computational tasks and examined the relationship between their self-efficacy and their learning experiences in Southwest Nigerian universities. The study employed a descriptive survey research design. The population of the study comprises all the final year students of Computer Science. A purposive sampling technique was adopted in selecting a representative sample of interest from the final year students of Computer Science. The Students’ Computational Task Self-Efficacy Questionnaire (SCTSEQ) was used to collect data. Mean, standard deviation, frequency, percentages, and linear regression were used for data analysis. The result obtained revealed that the final year students of Computer Science were averagely confident in performing computational tasks, and there is a significant relationship between the learning experiences of the students and their self-efficacy. The study recommends that the curriculum be improved upon to accommodate industry experts as lecturers in some of the courses, make provision for more practical sessions, and the learning experiences of the student be considered an important component in the undergraduate Computer Science curriculum development process.

Keywords: computer science, learning experiences, self-efficacy, students

Procedia PDF Downloads 136

Authors: Silvina Caíno-Lores, Jesús Carretero

Abstract:

Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

Procedia PDF Downloads 254

Authors: Alfonso Ippolito, Cristiana Bartolomei

Abstract:

A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

Procedia PDF Downloads 418

Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

Abstract:

Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

Procedia PDF Downloads 67

Authors: E. Al Daoud

Abstract:

In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Keywords: Feynman rules, hadrons, Lagrangian, Monte Carlo, simulation

Procedia PDF Downloads 311

Authors: Taraneh Estedlal

Abstract:

The objective of this study was to review in-vivo and in-vitro studies to compare the effectiveness of bulk-fill and conventional resin composites with regard to marginal adaptation, polymerization shrinkage, and other mechanical properties.PubMed and Scopus databases was investigated for in-vitro studies and randomized clinical trials comparing incidence of fractures, color stability, marginal adaptation, pain and discomfort, recurrent caries, occlusion, pulpal reaction, and proper proximal contacts of restorations made with conventional and bulk resins. The failure rate of conventional and flowable bulk-fill resin composites was not significantly different to sculptable bulk-fill resin composites. The objective of this study was to review in-vivo and in-vitro studies to compare the effectiveness of bulk-fill and conventional resin composites with regard to marginal adaptation, polymerization shrinkage, and other mechanical properties. PubMed and Scopus databases was investigated for in-vitro studies and randomized clinical trials comparing one of the pearlier mentioned properties between bulk-fill and control composites. Despite differences in physical and in-vitro properties, failure rate of conventional and flowable bulk-fill resin composites was not significantly different to sculptable bulk-fill resin composites.

Keywords: polymerization shrinkage, color stability, marginal adaptation, recurrent caries, occlusion, pulpal reaction

Procedia PDF Downloads 143

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

Abstract:

Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

Procedia PDF Downloads 333

Authors: Chun-Shien Lu

Abstract:

Privacy-preserving query has recently received considerable attention in the signal processing and multimedia community. It is also a critical step in wireless sensor network for retrieval of sensitive data. The purposes of privacy-preserving query in both the areas of signal processing and sensor network are the same, but the similarity and difference of the adopted technologies are not fully explored. In this paper, we first review the recently developed methods of privacy-preserving query, and then describe in a comprehensive manner what we can learn from the mutual of both areas.

Keywords: encryption, privacy-preserving, search, security

Procedia PDF Downloads 249