Search results for: long-term memory recall
527 Dietary Micronutritient and Health among Youth in Algeria
Authors: Allioua Meryem
Abstract:
Similar to much of the developing world, Algeria is currently undergoing an epidemiological transition. While mal- and under-nutrition and infectious diseases used to be the main causes of poor health, today there is a higher proportion of chronic, non-communicable diseases (NCDs), including cardiovascular disease, diabetes mellitus, cancer, etc. According to estimates for Algeria from the World Health Organization (WHO), NCDs accounted for 63% of all deaths in 2010. The objective of this study was the assessment of eating habits and anthropometric characteristics in a group of youth aged 15 to 19 years in Tlemcen. This study was conducted on a total effective of 806 youth enrolled in a descriptive cross-sectional study; the classification of nutritional status has been established by international standards IOTF, youth were defined as obese if they had a BMI ≥ 95th percentile, and youth with 85th ≤ BMI ≤ 95th percentile were defined as overweight. Wc is classified by the criteria HD, Wc with moderate risk ≥ 90th percentile and Wc with high risk ≥ 95th percentile. The dietary assessment was based on a 24-hour dietary recall assisted by food records. USDA’S nutrient database for Nutrinux® program was used to analyze dietary intake. Nutrients adequacy ratio was calculated by dividing daily individual intake to dietary recommended intake DRI for each nutrient. 9% of the population was overweight, 3% was obese, 7.5% had abdominal obesity, foods eaten in moderation are chips, cookies, chocolate 1-3 times/day and increased consumption of fried foods in the week, almost half of youth consume sugary drinks more than 3 times per week, we observe a decreased intake of energy, protein (P < 0.001, P = 0.003), SFA (P = 0.018), the NAR of phosphorus, iron, magnesium, vitamin B6, vitamin E, folate, niacin, and thiamin reflecting less consumption of fruit, vegetables, milk, and milk products. Youth surveyed have eating habits at risk of developing obesity and chronic disease.Keywords: food intake, health, anthropometric characteristics, Algeria
Procedia PDF Downloads 537526 Physical Interaction Mappings: Utilizing Cognitive Load Theory in Order to Enhance Physical Product Interaction
Authors: Bryan Young, Andrew Wodehouse, Marion Sheridan
Abstract:
The availability of working memory has long been identified as a critical aspect of an instructional design. Many conventional instructional procedures impose irrelevant or unrelated cognitive loads on the learner due to the fact that they were created without contemplation, or understanding, of cognitive work load. Learning to physically operate traditional products can be viewed as a learning process akin to any other. As such, many of today's products, such as cars, boats, and planes, which have traditional controls that predate modern user-centered design techniques may be imposing irrelevant or unrelated cognitive loads on their operators. The goal of the research was to investigate the fundamental relationships between physical inputs, resulting actions, and learnability. The results showed that individuals can quickly adapt to input/output reversals across dimensions, however, individuals struggle to cope with the input/output when the dimensions are rotated due to the resulting increase in cognitive load.Keywords: cognitive load theory, instructional design, physical product interactions, usability design
Procedia PDF Downloads 527525 Design and Development of Real-Time Optimal Energy Management System for Hybrid Electric Vehicles
Authors: Masood Roohi, Amir Taghavipour
Abstract:
This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.Keywords: hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time
Procedia PDF Downloads 340524 Quantum Entangled States and Image Processing
Authors: Sanjay Singh, Sushil Kumar, Rashmi Jain
Abstract:
Quantum registering is another pattern in computational hypothesis and a quantum mechanical framework has a few helpful properties like Entanglement. We plan to store data concerning the structure and substance of a basic picture in a quantum framework. Consider a variety of n qubits which we propose to use as our memory stockpiling. In recent years classical processing is switched to quantum image processing. Quantum image processing is an elegant approach to overcome the problems of its classical counter parts. Image storage, retrieval and its processing on quantum machines is an emerging area. Although quantum machines do not exist in physical reality but theoretical algorithms developed based on quantum entangled states gives new insights to process the classical images in quantum domain. Here in the present work, we give the brief overview, such that how entangled states can be useful for quantum image storage and retrieval. We discuss the properties of tripartite Greenberger-Horne-Zeilinger and W states and their usefulness to store the shapes which may consist three vertices. We also propose the techniques to store shapes having more than three vertices.Keywords: Greenberger-Horne-Zeilinger, image storage and retrieval, quantum entanglement, W states
Procedia PDF Downloads 298523 Multimodal Convolutional Neural Network for Musical Instrument Recognition
Authors: Yagya Raj Pandeya, Joonwhoan Lee
Abstract:
The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean
Procedia PDF Downloads 202522 Spatiotemporal Neural Network for Video-Based Pose Estimation
Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan
Abstract:
Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series
Procedia PDF Downloads 139521 Operating System Based Virtualization Models in Cloud Computing
Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi
Abstract:
Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization
Procedia PDF Downloads 308520 Impact of Stack Caches: Locality Awareness and Cost Effectiveness
Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang
Abstract:
Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.Keywords: hit rate, locality of program, stack cache, stack data
Procedia PDF Downloads 296519 Design of Advanced Materials for Alternative Cooling Devices
Authors: Emilia Olivos, R. Arroyave, A. Vargas-Calderon, J. E. Dominguez-Herrera
Abstract:
More efficient cooling systems are needed to reduce building energy consumption and environmental impact. At present researchers focus mainly on environmentally-friendly magnetic materials and the potential application in cooling devices. The magnetic materials presented in this project belong to a group known as Heusler alloys. These compounds are characterized by a strong coupling between their structure and magnetic properties. Usually, a change in one of them can alter the other, which implies changes in other electronic or structural properties, such as, shape magnetic memory response or the magnetocaloric effect. Those properties and its dependence with external fields make these materials interesting, both from a fundamental point of view, as well as on their different possible applications. In this work, first principles and Monte Carlo simulations have been used to calculate exchange couplings and magnetic properties as a function of an applied magnetic field on Heusler alloys. As a result, we found a large dependence of the magnetic susceptibility, entropy and heat capacity, indicating that the magnetic field can be used in experiments to trigger particular magnetic properties in materials, which are necessary to develop solid-state refrigeration devices.Keywords: ferromagnetic materials, magnetocaloric effect, materials design, solid state refrigeration
Procedia PDF Downloads 198518 General Purpose Graphic Processing Units Based Real Time Video Tracking System
Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai
Abstract:
Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.Keywords: connected components, embrace threads, local weighted kernel, structuring elements
Procedia PDF Downloads 429517 Performance Analysis of Elliptic Curve Cryptography Using Onion Routing to Enhance the Privacy and Anonymity in Grid Computing
Authors: H. Parveen Begam, M. A. Maluk Mohamed
Abstract:
Grid computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using Virtual Organization (VO). Security is a critical issue due to the open nature of the wireless channels in the grid computing which requires three fundamental services: authentication, authorization, and encryption. The privacy and anonymity are considered as an important factor while communicating over publicly spanned network like web. To ensure a high level of security we explored an extension of onion routing, which has been used with dynamic token exchange along with protection of privacy and anonymity of individual identity. To improve the performance of encrypting the layers, the elliptic curve cryptography is used. Compared to traditional cryptosystems like RSA (Rivest-Shamir-Adelman), ECC (Elliptic Curve Cryptosystem) offers equivalent security with smaller key sizes which result in faster computations, lower power consumption, as well as memory and bandwidth savings. This paper presents the estimation of the performance improvements of onion routing using ECC as well as the comparison graph between performance level of RSA and ECC.Keywords: grid computing, privacy, anonymity, onion routing, ECC, RSA
Procedia PDF Downloads 388516 Organizational Climate being Knowledge Sharing Oriented: A Fuzzy-Set Analysis
Authors: Paulo Lopes Henriques, Carla Curado
Abstract:
According to literature, knowledge sharing behaviors are influenced by organizational values and structures, namely organizational climate. The manuscript examines the antecedents of the knowledge sharing oriented organizational climate. According to theoretical expectations the study adopts the following explanatory conditions: knowledge sharing costs, knowledge sharing incentives, perceptions of knowledge sharing contributing to performance and tenure. The study confronts results considering two groups of firms: nondigital (firms without intranet) vs digital (firms with intranet). The paper applies fsQCA technique to analyze data by using fsQCA 2.5 software (www.fsqca.com) testing several conditional arguments to explain the outcome variable. Main results strengthen claims on the relevancy of the contribution of knowledge sharing to performance. Secondly, evidence brings tenure - an explanatory condition that is associated to organizational memory – to the spotlight. The study provides an original contribution not previously addressed in literature, since it identifies the sufficient conditions sets to knowledge sharing oriented organizational climate using fsQCA, which is, to our knowledge, a novel application of the technique.Keywords: fsQCA, knowledge sharing oriented organizational climate, knowledge sharing costs, knowledge sharing incentives
Procedia PDF Downloads 321515 Hong Kong Chinese-Speaking Adolescents Diagnosed with Dyslexia: What Is and Is Not Improved?
Authors: Kevin Kien Hoa Chung
Abstract:
The present study was to investigate cognitive-linguistic skills that might distinguish the improved dyslexics from the non-improved dyslexics. Twenty-eight improved dyslexics and 28 non-improved dyslexics were selected from a pool of 254 students diagnosed as dyslexics in Grade 1 to 2. These students were administered measures: morphological skills, visual-orthographic skills, rapid naming skills, working memory, reading comprehension, writing, word reading, word dictation, and one-minute word reading. Findings showed that the improved dyslexics performed better than the non-improved dyslexics in visual-orthographic skills, word reading, one-minute reading, writing, and reading comprehension. Furthermore, the improved dyslexics showed fewer cognitive-linguistic deficits compared with the non-improved dyslexics. Among the 4 cognitive-linguistic measures, morphological skills and visual-orthographic skills showed the greatest power in discriminating the improved and non-improved dyslexics. Results underscore the importance of cognitive-linguistic skills underlying the manifestations of the improved and non-improved dyslexia in Chinese adolescents.Keywords: adolescents, chinese language, improved dyslexics, non-improved dyslexics
Procedia PDF Downloads 385514 Monitoring System for Electronic Procurement Systems
Authors: Abdulah Fajar
Abstract:
Electronic Procurement System has been implemented at government institution in Indonesia. This system has been developed centrally at Institution of National Procurement Policy (LKPP) and implemented autonomously at either local or national government institution. The lack of competency at many institution on Information Technology Management arise several major problems. The main concern of LKPP to local administrator is assured that the system is running normally and always be able to serve the needs of its users. Monitoring system has been identified as the one of solution to prevent the problems appeared. Monitoring system is developed using Simple Network Management Protocol (SNMP) and implemented at LKPP. There are two modules; Main Dashboard and Local Agent. Main Dashboard is intended for LKPP and Local Agent is intended to implement at local autonomous e-procurement system (LPSE). There are several resources that must be monitored such as computation, memory and network traffic. Agile paradigm is applied to this project to assure user and system requirement is met. The length of project is the one of reason why agile paradigm has been chosen. The system has been successfully delivered to LKPP.Keywords: procurement system, SNMP, LKPP, LPSE
Procedia PDF Downloads 416513 Design, Control and Autonomous Trajectory Tracking of an Octorotor Rotorcraft
Authors: Seyed Jamal Haddadi, M. Reza Mehranpour, Roya Sadat Mortazavi, Zahra Sadat Mortazavi
Abstract:
Principal aim of this research is trajectory tracking, attitude and position control scheme in real flight mode by an Octorotor helicopter. For more stability, in this Unmanned Aerial Vehicle (UAV), number of motors is increased to eight motors which end of each arm installed two coaxial counter rotating motors. Dynamic model of this Octorotor includes of motion equation for translation and rotation. Utilized controller is proportional-integral-derivative (PID) control loop. The proposed controller is designed such that to be able to attenuate an effect of external wind disturbance and guarantee stability in this condition. The trajectory is determined by a Global Positioning System (GPS). Also an ARM CortexM4 is used as microprocessor. Electronic board of this UAV designed as able to records all of the sensors data, similar to an aircraft black box in external memory. Finally after auto landing of Octorotor, flight data is shown in MATLAB software and Experimental results of the proposed controller show the effectiveness of our approach on the Autonomous Quadrotor in real conditions.Keywords: octorotor, design, PID controller, autonomous, trajectory tracking
Procedia PDF Downloads 294512 Reading Out of Curiosity: Making Undergraduates Competent in English
Authors: Ruwan Gunawardane
Abstract:
Second language teaching and learning is a complex process in which various factors are identified as having a negative impact on the competency in English among undergraduates of Sri Lanka. One such issue is the lack of intrinsic motivation among them to learn English despite the fact that they all know the importance of English. This study attempted to ascertain how the intrinsic motivation of undergraduates to learn English can be improved through reading out of curiosity. Humans are curious by nature, and cognitive psychology says that curiosity facilitates learning, memory, and motivation. The researcher carried out this study during the closure of universities due to the outbreak of the coronavirus through ‘Online Reading Café’, an online reading programme introduced by himself. He invited 1166 students of the Faculty of Science, University of Ruhuna, to read 50 articles taken from CNN and the BBC and posted at least two to three articles on the LMS of the faculty almost every day over a period of 23 days. The themes of the articles were based on the universe, exploration of planets, scientific experiments, evolution, etc., and the students were encouraged to collect as many words, phrases, and sentence structures as possible while reading and to form meaningful sentences using them. The data obtained through the students’ feedback was qualitatively analyzed. It was found that these undergraduates were interested in reading something out of curiosity, due to which intrinsic motivation is enhanced, and it facilitates competence in L2.Keywords: English, competence, reading, curiosity
Procedia PDF Downloads 132511 Image Captioning with Vision-Language Models
Authors: Promise Ekpo Osaine, Daniel Melesse
Abstract:
Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score
Procedia PDF Downloads 65510 Variations of Metaphors: Wittgenstein's Contribution to Literary Studies
Authors: Dorit Lemberger
Abstract:
Wittgenstein directly used the term "metaphor" only infrequently and with reservations, but his writings include a number of metaphors that have become imprinted in the philosophical memory of Western thought. For example, the ladder in his book Tractatus, or in Philosophical investigations - the ancient city, the beetle in a box, the fly in the fly-bottle, and the duck-rabbit. In light of Wittgenstein's stressing, throughout his investigations, that the only language that exists is ordinary language, and that there is no "second-order" language, the question should be asked: How do these metaphors function, specifically, and in general, how are we to relate to language use that exceeds the normal? Wittgenstein did not disregard such phenomena, but he proposed viewing them in a different way, that would enable understanding them as uses in ordinary language, without necessarily exceeding such language. Two important terms that he coined in this context are "secondary sense" and "experience of meaning". Each denotes language use as reflective of a subjective element characteristic of the speaker, such as intent, experience, or emphasis of a certain aspect. More recent Wittgenstein scholars added the term "quasi-metaphor", that refers to his discussion of the possibility of aesthetic judgment. This paper will examine how, according to Wittgenstein, these terms function without exceeding ordinary language, and will illustrate how they can be applied, in an analysis of the poem "Butterfly" by Nelly Sachs.Keywords: metaphor, quasi-metaphor, secondary sense, experience of meaning
Procedia PDF Downloads 431509 Physical Activity Patterns and Status of Adolescent Learners from Low and Middle Socio-Economic Status Communities in Kwazulu-Natal Province
Authors: Patrick Mkhanyiseli Zimu
Abstract:
A sedentary lifestyle and insufficient physical activity (PA) increases the risk of developing chronic non-communicable diseases (NCDs). Knowing the PA levels and patterns of adolescents from different socio-economic backgrounds is important to direct programs at schools and in communities to prevent NCDs risk factors, which can have long-term effects on the health of the adolescents. The study aimed to investigate adolescent PA levels, patterns, and influencing factors (age, gender, socio-economic status). The 353 participants (203 females and 150 males) from eight low socio-economic (LSES) and middle socio-economic (MSES) public secondary schools completed a Physical Activity Questionnaire for Adolescents (PAQ-A). The PAQ-A is a seven day recall instrument that assesses general estimates of PA levels and patterns for high school learners in Grades 9-12 and provides a summary of physical activity scores derived from seven items, each scored on a 5-point Likert scale. The seven items were PA during spare time and five domains (during physical education, lunch break, after school, in the evenings, on the weekend) and selecting one statement that described participant’s physical activity behaviour. The PA Levels (x̄=2.61, SD=.74) were below the international PA cut-off points of x̄=2.75. Physical education (PE) showed the highest PA score (x̄=3.05, SD=1.21) and lunch break showed the lowest PA score (x̄=2.09, SD=1.14). Positive correlations occurred between PA levels and SES (r=.122, p=0.022), and PA and gender (r=.223, p= 0.0001). LSES participant’s PA score was significantly lower (x̄=2.52; SD=.73) than those from MSES (x̄=2.70; SD=.74, p=0.022). Adolescents from low and middle socio-economic status communities are not sufficiently active. Their average PA score of 2.61 is below the PAQ-A global criterion referenced cut-off points of 2.75, which is considered sufficiently physically active for adolescents to ensure both short- and long-term health benefits. As adolescents are not sufficiently active, collaborative school and community PA programs need to be implemented to supplement physical education in order to prevent short- and long-term health problems.Keywords: adolescents, health promotion, physical activity, physical education
Procedia PDF Downloads 89508 The Underground Ecosystem of Credit Card Frauds
Authors: Abhinav Singh
Abstract:
Point Of Sale (POS) malwares have been stealing the limelight this year. They have been the elemental factor in some of the biggest breaches uncovered in past couple of years. Some of them include • Target: A Retail Giant reported close to 40 million credit card data being stolen • Home Depot : A home product Retailer reported breach of close to 50 million credit records • Kmart: A US retailer recently announced breach of 800 thousand credit card details. Alone in 2014, there have been reports of over 15 major breaches of payment systems around the globe. Memory scrapping malwares infecting the point of sale devices have been the lethal weapon used in these attacks. These malwares are capable of reading the payment information from the payment device memory before they are being encrypted. Later on these malwares send the stolen details to its parent server. These malwares are capable of recording all the critical payment information like the card number, security number, owner etc. All these information are delivered in raw format. This Talk will cover the aspects of what happens after these details have been sent to the malware authors. The entire ecosystem of credit card frauds can be broadly classified into these three steps: • Purchase of raw details and dumps • Converting them to plastic cash/cards • Shop! Shop! Shop! The focus of this talk will be on the above mentioned points and how they form an organized network of cyber-crime. The first step involves buying and selling of the stolen details. The key point to emphasize are : • How is this raw information been sold in the underground market • The buyer and seller anatomy • Building your shopping cart and preferences • The importance of reputation and vouches • Customer support and replace/refunds These are some of the key points that will be discussed. But the story doesn’t end here. As of now the buyer only has the raw card information. How will this raw information be converted to plastic cash? Now comes in picture the second part of this underground economy where-in these raw details are converted into actual cards. There are well organized services running underground that can help you in converting these details into plastic cards. We will discuss about this technique in detail. At last, the final step involves shopping with the stolen cards. The cards generated with the stolen details can be easily used to swipe-and-pay for purchased goods at different retail shops. Usually these purchases are of expensive items that have good resale value. Apart from using the cards at stores, there are underground services that lets you deliver online orders to their dummy addresses. Once the package is received it will be delivered to the original buyer. These services charge based on the value of item that is being delivered. The overall underground ecosystem of credit card fraud works in a bulletproof way and it involves people working in close groups and making heavy profits. This is a brief summary of what I plan to present at the talk. I have done an extensive research and have collected good deal of material to present as samples. Some of them include: • List of underground forums • Credit card dumps • IRC chats among these groups • Personal chat with big card sellers • Inside view of these forum owners. The talk will be concluded by throwing light on how these breaches are being tracked during investigation. How are credit card breaches tracked down and what steps can financial institutions can build an incidence response over it.Keywords: POS mawalre, credit card frauds, enterprise security, underground ecosystem
Procedia PDF Downloads 433507 Identification of Some Factors Influencing Serum Uric Acid Concentration in Individuals With Metabolic Syndrome
Authors: Munkhtuul G., Bolortsetseg Z., Lutzul M., Sugar N., Nyamdorj D., Nomundari B., Zesemdorj O., Erdenebayar N., Lkhagvasuren T. S., Munkhbayarlakh S., Bayasgalan T. Uurtuya S. H.
Abstract:
Background: Elevated serum uric acid (SUA) levels are observed in metabolic and cardiovascular conditions as an early predictor of metabolic syndrome (MS). Hyperuricemia, characterised by high uric acid levels in serum, increases the risk of developing MS by 1.6 times. Being overweight and obese significantly contributes to developing MS and cardiovascular disorders. In Mongolia, the prevalence of overweight and obesity is reaching 48.8% among individuals aged 15 to 49 years, indicating a potential surge in the incidence of MS, cardiovascular disorders, diabetes mellitus, and gout.Objective: This study aimed to determine the SUA levels in men diagnosed with MS and investigate the factors influencing these levels.Methods: A total of 119 men aged 30-60, who underwent preventive examinations and resided in Ulaanbaatar city, were included in the study. The criteria established by the International Diabetes Federation (IDF), American Heart Association (AHA), and the National Heart, Lung, and Blood Institute (NHLBI) were employed to define metabolic syndrome. Hyperuricemia was defined as SUA levels ≥7 mg/dL. Dietary intake was evaluated through the 24-hour recall method.Results: The study revealed that the prevalence of MS among the participants was 42.9% (n=51), with hyperuricemia observed in 16.8% (n=20) of the individuals. Among men diagnosed with MS, 21.3% (n=10) exhibited hyperuricemia. The mean SUA levels were as follows: 4.7±0.8 mg/dL in the healthy group, 5.9±1.1 mg/dL in men without MS but presenting central obesity, and 6.2±1.3 mg/dL in men with MS. After adjusting for age and body mass index (BMI), a positive correlation was observed between SUA levels and triglycerides (β=0.93) as well as lipid accumulation product (LAP) (β=0.92) in men with MS. In the central obesity group, SUA levels exhibited a positive correlation with triglycerides (β=0.91), visceral adiposity index (VAI) (β=0.73), LAP (β=0.92), and cardiometabolic index (CMI) (β=0.69). The risk of hyperuricemia increased by 3.29 times with elevated triglycerides and 3.53 times with an increased LAP.Conclusion: The findings indicate that abdominal fat accumulation, as indicated by elevated triglyceride levels and LAP, is associated with increased SUA levels in men with MS. However, no significant relationship was observed between SUA levels and dietary intake.Keywords: central obesity, obesity, triglycerides, hyperuricemia
Procedia PDF Downloads 53506 The Effects of Normal Aging on Reasoning Ability: A Dual-Process Approach
Authors: Jamie A. Prowse Turner, Jamie I. D. Campbell, Valerie A. Thompson
Abstract:
The objective of the current research was to use a dual-process theory framework to explain these age-related differences in reasoning. Seventy-two older (M = 80.0 years) and 72 younger (M = 24.6 years) adults were given a variety of reasoning tests (i.e., a syllogistic task, base rate task, the Cognitive Reflection Test, and a perspective manipulation), as well as independent tests of capacity (working memory, processing speed, and inhibition), thinking styles, and metacognitive ability, to account for these age-related differences. It was revealed that age-related differences were limited to problems that required Type 2 processing and were related to differences in cognitive capacity, individual difference factors, and strategy choice. Furthermore, older adults’ performance can be improved by reasoning from another’s’ perspective and cannot, at this time, be explained by metacognitive differences between young and older adults. All of these findings fit well within a dual-process theory of reasoning, which provides an integrative framework accounting for previous findings and the findings presented in the current manuscript.Keywords: aging, dual-process theory, performance, reasoning ability
Procedia PDF Downloads 183505 Cyber Security Enhancement via Software Defined Pseudo-Random Private IP Address Hopping
Authors: Andre Slonopas, Zona Kostic, Warren Thompson
Abstract:
Obfuscation is one of the most useful tools to prevent network compromise. Previous research focused on the obfuscation of the network communications between external-facing edge devices. This work proposes the use of two edge devices, external and internal facing, which communicate via private IPv4 addresses in a software-defined pseudo-random IP hopping. This methodology does not require additional IP addresses and/or resources to implement. Statistical analyses demonstrate that the hopping surface must be at least 1e3 IP addresses in size with a broad standard deviation to minimize the possibility of coincidence of monitored and communication IPs. The probability of breaking the hopping algorithm requires a collection of at least 1e6 samples, which for large hopping surfaces will take years to collect. The probability of dropped packets is controlled via memory buffers and the frequency of hops and can be reduced to levels acceptable for video streaming. This methodology provides an impenetrable layer of security ideal for information and supervisory control and data acquisition systems.Keywords: moving target defense, cybersecurity, network security, hopping randomization, software defined network, network security theory
Procedia PDF Downloads 175504 A Machine Learning Based Method to Detect System Failure in Resource Constrained Environment
Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay
Abstract:
Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.Keywords: machine learning, system performance, performance metrics, IoT, edge
Procedia PDF Downloads 186503 The Integration of Patient Health Record Generated from Wearable and Internet of Things Devices into Health Information Exchanges
Authors: Dalvin D. Hill, Hector M. Castro Garcia
Abstract:
A growing number of individuals utilize wearable devices on a daily basis. The usage and functionality of these wearable devices vary from user to user. One popular usage of said devices is to track health-related activities that are typically stored on a device’s memory or uploaded to an account in the cloud; based on the current trend, the data accumulated from the wearable device are stored in a standalone location. In many of these cases, this health related datum is not a factor when considering the holistic view of a user’s health lifestyle or record. This health-related data generated from wearable and Internet of Things (IoT) devices can serve as empirical information to a medical provider, as the standalone data can add value to the holistic health record of a patient. This paper proposes a solution to incorporate the data gathered from these wearable and IoT devices, with that a patient’s Personal Health Record (PHR) stored within the confines of a Health Information Exchange (HIE).Keywords: electronic health record, health information exchanges, internet of things, personal health records, wearable devices, wearables
Procedia PDF Downloads 119502 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach
Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini
Abstract:
Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing
Procedia PDF Downloads 158501 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach
Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini
Abstract:
Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanismsKeywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing
Procedia PDF Downloads 145500 Development of a Real-Time Brain-Computer Interface for Interactive Robot Therapy: An Exploration of EEG and EMG Features during Hypnosis
Authors: Maryam Alimardani, Kazuo Hiraki
Abstract:
This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.Keywords: hypnosis, EEG, robotherapy, brain-computer interface (BCI)
Procedia PDF Downloads 249499 Improvements and Implementation Solutions to Reduce the Computational Load for Traffic Situational Awareness with Alerts (TSAA)
Authors: Salvatore Luongo, Carlo Luongo
Abstract:
This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilitiesKeywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification
Procedia PDF Downloads 270498 Voices of Dissent: Case Study of a Digital Archive of Testimonies of Political Oppression
Authors: Andrea Scapolo, Zaya Rustamova, Arturo Matute Castro
Abstract:
The “Voices in Dissent” initiative aims at collecting and making available in a digital format, testimonies, letters, and other narratives produced by victims of political oppression from different geographical spaces across the Atlantic. By recovering silenced voices behind the official narratives, this open-access online database will provide indispensable tools for rewriting the history of authoritarian regimes from the margins as memory debates continue to provoke controversy among academic and popular transnational circles. In providing an extensive database of non-hegemonic discourses in a variety of political and social contexts, the project will complement the existing European and Latin-American studies, and invite further interdisciplinary and trans-national research. This digital resource will be available to academic communities and the general audience and will be organized geographically and chronologically. “Voices in Dissent” will offer a first comprehensive study of these personal accounts of persecution and repression against determined historical backgrounds and their impact on collective memory formation in contemporary societies. The digitalization of these texts will allow to run metadata analyses and adopt comparatist approaches for a broad range of research endeavors. Most of the testimonies included in our archive are testimonies of trauma: the trauma of exile, imprisonment, torture, humiliation, censorship. The research on trauma has now reached critical mass and offers a broad spectrum of critical perspectives. By putting together testimonies from different geographical and historical contexts, our project will provide readers and scholars with an extraordinary opportunity to investigate how culture shapes individual and collective memories and provides or denies resources to make sense and cope with the trauma. For scholars dealing with the epistemological and rhetorical analysis of testimonies, an online open-access archive will prove particularly beneficial to test theories on truth status and the formation of belief as well as to study the articulation of discourse. An important aspect of this project is also its pedagogical applications since it will contribute to the creation of Open Educational Resources (OER) to support students and educators worldwide. Through collaborations with our Library System, the archive will form part of the Digital Commons database. The texts collected in this online archive will be made available in the original languages as well as in English translation. They will be accompanied by a critical apparatus that will contextualize them historically by providing relevant background information and bibliographical references. All these materials can serve as a springboard for a broad variety of educational projects and classroom activities. They can also be used to design specific content courses or modules. In conclusion, the desirable outcomes of the “Voices in Dissent” project are: 1. the collections and digitalization of political dissent testimonies; 2. the building of a network of scholars, educators, and learners involved in the design, development, and sustainability of the digital archive; 3. the integration of the content of the archive in both research and teaching endeavors, such as publication of scholarly articles, design of new upper-level courses, and integration of the materials in existing courses.Keywords: digital archive, dissent, open educational resources, testimonies, transatlantic studies
Procedia PDF Downloads 101