Search results for: cognitive complexity metric

Authors: Rami Hashish, Manon Limousis-Gayda, Caitlin McCleery

Abstract:

Introduction: Mild traumatic brain injuries, also referred to as concussions, represent an increasing burden to society. Due to limited objective diagnostic measures, concussions are diagnosed by assessing subjective symptoms, often leading to disputes to their presence. Common biomechanical measures associated with concussion are high linear and/or angular acceleration to the head. With regards to linear acceleration, approximately 80g’s has previously been shown to equate with a 50% probability of concussion. Motor vehicle collisions (MVCs) are a leading cause of concussion, due to high head accelerations experienced. The change in velocity (delta-V) of a vehicle in an MVC is an established metric for impact severity. As acceleration is the rate of delta-V with respect to time, the purpose of this paper is to determine the relation between delta-V (and occupant parameters) with linear head acceleration. Methods: A meta-analysis was conducted for manuscripts collected using the following keywords: head acceleration, concussion, brain injury, head kinematics, delta-V, change in velocity, motor vehicle collision, and rear-end. Ultimately, 280 studies were surveyed, 14 of which fulfilled the inclusion criteria as studies investigating the human response to impacts, reporting head acceleration, and delta-V of the occupant’s vehicle. Statistical analysis was conducted with SPSS and R. The best fit line analysis allowed for an initial understanding of the relation between head acceleration and delta-V. To further investigate the effect of occupant parameters on head acceleration, a quadratic model and a full linear mixed model was developed. Results: From the 14 selected studies, 139 crashes were analyzed with head accelerations and delta-V values ranging from 0.6 to 17.2g and 1.3 to 11.1 km/h, respectively. Initial analysis indicated that the best line of fit (Model 1) was defined as Head Acceleration = 0.465

Keywords: acceleration, brain injury, change in velocity, Delta-V, TBI

Procedia PDF Downloads 235

Authors: Joan Edwards, J. Lawlor

Abstract:

Technological innovation is frequently defined in terms of bringing a new invention to market through a relatively straightforward process of diffusion. In reality, this process is complex and non-linear in nature, and includes social and cognitive factors that influence the development of an emerging technology and its related market or environment. As recent studies contend technological trajectory is part of technological paradigms, which arise from the expectations and desires of industry agents and results in co-evolution, it may be realised that social factors play a major role in the development of a technology. It is conjectured that collective social behaviour is fuelled by individual motivations and expectations, which inform the possibilities and uses for a new technology. The individual outlook highlights the issues present at the micro-level of developing a technology. Accordingly, this may be zoomed out to realise how these embedded social structures, influence activities and expectations at a macro level and can ultimately strategically shape the development and use of a technology. These social factors rely on communication to foster the innovation process. As innovation may be defined as the implementation of inventions, technological change results from the complex interactions and feedback occurring within an extended environment. The framework presented in this paper, recognises that social mechanisms provide the basis for an iterative dialogue between an innovator, a new technology, and an environment - within which social and cognitive ‘identity-shaping’ elements of the innovation process occur. Identity-shaping characteristics indicate that an emerging technology has a performative nature that transforms, alters, and ultimately configures the environment to which it joins. This identity–shaping quality is termed as ‘performative’. This paper examines how technologies evolve within a socio-technological sphere and how 'performativity' facilitates the process. A framework is proposed that incorporates the performative elements which are identified as feedback, iteration, routine, expectations, and motivations. Additionally, the concept of affordances is employed to determine how the role of the innovator and technology change over time - constituting a more conducive environment for successful innovation.

Keywords: affordances, framework, performativity, strategic innovation

Procedia PDF Downloads 206

Authors: F. Lhafiane, A. Elbyed, M. Bouchoum

Abstract:

The design of Reverse logistics Network has attracted growing attention with the stringent pressures from both environmental awareness and business sustainability. Reverse logistical activities include return, remanufacture, disassemble and dispose of products can be quite complex to manage. In addition, demand can be difficult to predict, and decision making is one of the challenges tasks. This complexity has amplified the need to develop an integrated architecture for product return as an enterprise system. The main purpose of this paper is to design Multi agent system (MAS) architecture using the Prometheus methodology to efficiently manage reverse logistics processes. The proposed MAS architecture includes five types of agents: Gate keeping Agent, Collection Agent, Sorting Agent, Processing Agent and Disposal Agent which act respectively during the five steps of reverse logistics Network.

Keywords: reverse logistics, multi agent system, prometheus methodology

Procedia PDF Downloads 474

Authors: Muhammad M. A. S. Mahmoud

Abstract:

Natural gas sweetening process is a controlled process that must be done at maximum efficiency and with the highest quality. In this work, due to complexity and non-linearity of the process, the H₂S gas separation and the intelligent fuzzy controller, which is used to enhance the process, are simulated in MATLAB – Simulink. The new design of fuzzy control for Gas Separator is discussed in this paper. The design is based on the utilization of linear state-estimation to generate the internal knowledge-base that stores input-output pairs. The obtained input/output pairs are then used to design a feedback fuzzy controller. The proposed closed-loop fuzzy control system maintains the system asymptotically-stability while it enhances the system time response to achieve better control of the concentration of the output gas from the tower. Simulation studies are carried out to illustrate the Gas Separator system performance.

Keywords: gas separator, gas sweetening, intelligent controller, fuzzy control

Procedia PDF Downloads 472

Authors: Sumay Bhojwani, Ashutosh Chandra, Mamita Devaburman, Akriti Bhogal

Abstract:

This article uses the Material flow analysis for estimating e-wastes in the Delhi/NCR region. The Material flow analysis is based on sales data obtained from various sources. Much of the data available for the sales is unreliable because of the existence of a huge informal sector. The informal sector in India accounts for more than 90%. Therefore, the scope of this study is only limited to the formal one. Also, for projection of the sales data till 2030, we have used regression (linear) to avoid complexity. The actual sales in the years following 2015 may vary non-linearly but we have assumed a basic linear relation. The purpose of this study was to know an approximate quantity of desktop e-wastes that we will have by the year 2030 so that we start preparing ourselves for the ineluctable investment in the treatment of these ever-rising e-wastes. The results of this study can be used to install a treatment plant for e-wastes in Delhi.

Keywords: e-wastes, Delhi, desktops, estimation

Procedia PDF Downloads 260

Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

Abstract:

The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

Procedia PDF Downloads 163

Authors: Miguel Nino

Abstract:

When considering the challenges of a changing and demanding globalizing world, it is important to reflect on how university students will be prepared for the realities of internationalization, marketization and intercultural conversation. The present study is an interdisciplinary program designed to respond to the needs of the global community. The proposal bridges the humanities and science through three different fields: Languages, graphic design and computer science, specifically, fundamentals of programming such as python, java script and software animation. Therefore, the goal of the four year program is twofold: First, enable students for intercultural communication between English and other languages such as Spanish, Mandarin, French or German. Second, students will acquire knowledge in practical software and relevant employable skills to collaborate in assisted computer projects that most probable will require essential programing background in interpreted or compiled languages. In order to become inclusive and constructivist, the cognitive linguistics approach is suggested for the three different fields, particularly for languages that rely on the traditional method of repetition. This methodology will help students develop their creativity and encourage them to become independent problem solving individuals, as languages enhance their common ground of interaction for culture and technology. Participants in this course of study will be evaluated in their second language acquisition at the Intermediate-High level. For graphic design and computer science students will apply their creative digital skills, as well as their critical thinking skills learned from the cognitive linguistics approach, to collaborate on a group project design to find solutions for media web design problems or marketing experimentation for a company or the community. It is understood that it will be necessary to apply programming knowledge and skills to deliver the final product. In conclusion, the program equips students with linguistics knowledge and skills to be competent in intercultural communication, where English, the lingua franca, remains the medium for marketing and product delivery. In addition to their employability, students can expand their knowledge and skills in digital humanities, computational linguistics, or increase their portfolio in advertising and marketing. These students will be the global human capital for the competitive globalizing community.

Keywords: curriculum, international, languages, technology

Procedia PDF Downloads 443

Authors: Marcio Bottaro, Luis Eduardo Caires, Thais Ohara de Carvalho, Paulo Futoshi Obase, Hedio Tatizawa

Abstract:

Since the primary numerical metric used to evaluate Personal Protective Equipment – PPE, including protective clothing or other equipment designs, is typically derived from a single arc rating report, researchers and occupational safety professionals have raised significant concerns regarding the reliability of assigning a safety rating based on a single thermal performance test. Moreover, questions arise about the adequacy of determining PPE conformity solely from a single arc flash test. Although it is well known that the arc rated PPE work and show unquestionable evolution in workers’ safety, a tendency to pursue every higher arc rating value is evidenced in the marketing, and in Brazil, it has been a special concern on the reliability of such practice of “select” a more convenient arc rating report to use as base parameter on final PPE test and subsequently certification process. In fact, this procedure is not forbidden and it ends up being supported and encouraged due to the way such tests are conducted according to international standards. Although commonly practiced, variations in test laboratory procedures, as well as inherent variations in materials such as textiles, introduce significant concerns regarding the reliability of higher reference values across batches of final products. This study highlights the discrepancies between claimed arc rating values and those obtained through laboratory testing over time for various textile materials. The findings reveal that focusing on the upper margins of thermal characterization can lead to adverse effects on the final versions of PPE, which are ostensibly ready for worker use. Deterministic failures such as charring, dripping, and breakopen in proof undergarments were observed, with a notable increase in the frequency of these failures in 2024 tests in Brazilian arc flash laboratory. These results underscore the urgent need for advancements in standardization processes to ensure the reliability of PPE and safety of workers.

Keywords: arc rating, arc flash protection, arc flash risk, PPE certification, PPE open arc test

Procedia PDF Downloads 5

Authors: Fernando Miguel Campos, Fernando Jesus Aguiar Campos, Pedro Filipe Campos

Abstract:

A large amount of software products offer a wide range and number of features. This is called featurities or creeping featurism and tends to rise with each release of the product. Feautiris often adds unnecessary complexity to software, leading to longer learning curves and overall confusing the users and degrading their experience. We take a look to a new design approach tendency that has been coming up, the so-called “What You Get Is What You Need” concept that argues that products should be very focused, simple and with minimalistic interfaces in order to help users conduct their tasks in distraction-free ambiances. This is not as simple to implement as it might sound and the developers need to cut down features. Our contribution illustrates and evaluates this design method through a novel distraction-free diagramming tool named Delineato Pro for Mac OS X in which the user is confronted with an empty canvas when launching the software and where tools only show up when really needed.

Keywords: diagramming, HCI, usability, user interface

Procedia PDF Downloads 528

Authors: César Garza

Abstract:

In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

Procedia PDF Downloads 133

Authors: Jiangping Wang

Abstract:

This presentation describes the design and implementation of PaaS (platform as a service) cloud-based labs that are used in database-related courses to teach students practical skills. Traditionally, all labs are implemented in a desktop-based environment where students have to install heavy client software to access database servers. In order to release students from that burden, we have successfully deployed the cloud-based solution to support database-related courses, from which students and teachers can practice and learn database topics in various database courses via cloud access. With its development environment, execution runtime, web server, database server, and collaboration capability, it offers a shared pool of configurable computing resources and comprehensive environment that supports students’ needs without the complexity of maintaining the infrastructure.

Keywords: PaaS, database environment, e-learning, web server

Procedia PDF Downloads 268

Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

Abstract:

The automated epileptic seizure detection research field has emerged in the recent years; this involves analyzing the Electroencephalogram (EEG) signals instead of the traditional visual inspection performed by expert neurologists. In this study, a Support Vector Machine (SVM) that uses Weighted Permutation Entropy (WPE) as the input feature is proposed for classifying normal and seizure EEG records. WPE is a modified statistical parameter of the permutation entropy (PE) that measures the complexity and irregularity of a time series. It incorporates both the mapped ordinal pattern of the time series and the information contained in the amplitude of its sample points. The proposed system utilizes the fact that entropy based measures for the EEG segments during epileptic seizure are lower than in normal EEG.

Keywords: electroencephalogram (EEG), epileptic seizure detection, weighted permutation entropy (WPE), support vector machine (SVM)

Procedia PDF Downloads 373

Authors: Cecile Laval, Harriet Lowe

Abstract:

Processing Instruction is a psycholinguistic pedagogical approach drawing insights from the Input Processing Model which establishes the initial innate strategies used by second language learners to connect form and meaning of linguistic features. With the ever-growing use of technology in Second Language Acquisition research, the present study uses eye-tracking to measure the effectiveness of Processing Instruction in the acquisition of French and its effects on learner’s cognitive strategies. The experiment was designed using a TOBII Pro-TX300 eye-tracker to measure participants’ default strategies when processing French linguistic input and any cognitive changes after receiving Processing Instruction treatment. Participants were drawn from lower intermediate adult learners of French at the University of Greenwich and randomly assigned to two groups. The study used a pre-test/post-test methodology. The pre-tests (one per linguistic item) were administered via the eye-tracker to both groups one week prior to instructional treatment. One group received full Processing Instruction treatment (explicit information on the grammatical item and on the processing strategies, and structured input activities) on the primary target linguistic feature (French past tense imperfective aspect). The second group received Processing Instruction treatment except the explicit information on the processing strategies. Three immediate post-tests on the three grammatical structures under investigation (French past tense imperfective aspect, French Subjunctive used for the expression of doubt, and the French causative construction with Faire) were administered with the eye-tracker. The eye-tracking data showed the positive change in learners’ processing of the French target features after instruction with improvement in the interpretation of the three linguistic features under investigation. 100% of participants in both groups made a statistically significant improvement (p=0.001) in the interpretation of the primary target feature (French past tense imperfective aspect) after treatment. 62.5% of participants made an improvement in the secondary target item (French Subjunctive used for the expression of doubt) and 37.5% of participants made an improvement in the cumulative target feature (French causative construction with Faire). Statistically there was no significant difference between the pre-test and post-test scores in the cumulative target feature; however, the variance approximately tripled between the pre-test and the post-test (3.9 pre-test and 9.6 post-test). This suggests that the treatment does not affect participants homogenously and implies a role for individual differences in the transfer-of-training effect of Processing Instruction. The use of eye-tracking provides an opportunity for the study of unconscious processing decisions made during moment-by-moment comprehension. The visual data from the eye-tracking demonstrates changes in participants’ processing strategies. Gaze plots from pre- and post-tests display participants fixation points changing from focusing on content words to focusing on the verb ending. This change in processing strategies can be clearly seen in the interpretation of sentences in both primary and secondary target features. This paper will present the research methodology, design and results of the experimental study using eye-tracking to investigate the primary effects and transfer-of-training effects of Processing Instruction. It will then provide evidence of the cognitive benefits of Processing Instruction in Second Language Acquisition and offer suggestion in second language teaching of grammar.

Keywords: eye-tracking, language teaching, processing instruction, second language acquisition

Procedia PDF Downloads 280

Authors: Majed Al Otaibi, Melissa Lessard-Beaudoin, Amel Loudghi, Raphael Chouinard-Watkins, Melanie Plourde, Frederic Calon, C. Alexandre Castellano, Stephen Cunnane, Helene Payette, Pierrette Gaudreau, Denis Gris, Rona K. Graham

Abstract:

Introduction: Alzheimer disease (AD) is a chronic disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction, and also alterations in attention, planning, language and overall cognitive function. Olfactory dysfunction is a common symptom of several neurological disorders including AD. Studying the mechanisms underlying the olfactory dysfunction may therefore lead to the discovery of potential biomarkers and/or treatments for neurodegenerative diseases. Objectives: To determine if olfactory dysfunction predicts future cognitive impairment in the aging population and to characterize the olfactory system in a murine model expressing a genetic factor of AD. Method: For the human study, quantitative olfactory tests (UPSIT and OMT) have been done on 93 subjects (aged 80 to 94 years) from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) cohort accepting to participate in the ORCA secondary study. The telephone Modified Mini Mental State examination (t-MMSE) was used to assess cognition levels, and an olfactory self-report was also collected. In a separate cohort, olfactory cortical volume was calculated using MRI results from healthy old adults (n=25) and patients with AD (n=18) using the AAL single-subject atlas and performed with the PNEURO tool (PMOD 3.7). For the murine study, we are using Western blotting, RT-PCR and immunohistochemistry. Result: Human Study: Based on the self-report, 81% of the participants claimed to not suffer from any problem with olfaction. However, based on the UPSIT, 94% of those subjects showed a poor olfactory performance and different forms of microsmia. Moreover, the results confirm that olfactory function declines with age. We also detected a significant decrease in olfactory cortical volume in AD individuals compared to controls. Murine study: Preliminary data demonstrate there is a significant decrease in expression levels of the proform of caspase-3 and the caspase substrate STK3, in the olfactory bulb of mice expressing human APOE4 compared with controls. In addition, there is a significant decrease in the expression level of the caspase-9 proform and caspase-8 active fragment. Analysis of the mature neuron marker, NeuN, shows decreased expression levels of both isoforms. The data also suggest that Iba-1 immunostaining is increased in the olfactory bulb of APOE4 mice compared to wild type mice. Conclusions: The activation of caspase-3 may be the cause of the decreased levels of STK3 through caspase cleavage and may play role in the inflammation observed. In the clinical study, our results suggest that seniors are unaware of their olfactory function status and therefore it is not sufficient to measure olfaction using the self-report in the elderly. Studying olfactory function and cognitive performance in the aging population will help to discover biomarkers in the early stage of the AD.

Keywords: Alzheimer's disease, APOE4, cognition, caspase, brain atrophy, neurodegenerative, olfactory dysfunction

Procedia PDF Downloads 258

Authors: Wafula Simon Peter, Kimuli Nabayego Ibtihal, Nabaggala Kimuli Nashua

Abstract:

The worldwide use of information and communications technology (ICT) equipment and other electronic equipment is growing and consequently, there is a growing amount of equipment that becomes waste after its time in use. This growth is expected to accelerate since equipment lifetime decreases with time and growing consumption. As a result, e-waste is one of the fastest-growing waste streams globally. The United Nations University (UNU) calculates in its second Global E-waste Monitor 44.7 million metric tonnes (Mt) of e-waste were generated globally in 2016. The study population was 80 respondents, from which a sample of 69 respondents was selected using simple and purposive sampling techniques. This research was carried out to investigate the problem of e-waste and come up with a framework to improve e-waste management. The objective of the study was to develop a framework for improving e-waste management at the College of Engineering, Design, Art and Technology (CEDAT). This was achieved by breaking it down into specific objectives, and these included the establishment of the policy and other Regulatory frameworks being used in e-waste management at CEDAT, the determination of the effectiveness of the e-waste management practices at CEDAT, the establishment of the critical challenges constraining e-waste management at the College, development of a framework for e-waste management. The study reviewed the e-waste regulatory framework used at the college and then collected data which was used to come up with a framework. The study also established that weak policy and regulatory framework, lack of proper infrastructure, improper disposal of e-waste and a general lack of awareness of the e-waste and the magnitude of the problem are the critical challenges of e-waste management. In conclusion, the policy and regulatory framework should be revised, localized and strengthened to contextually address the problem. Awareness campaigns, the development of proper infrastructure and extensive research to establish the volumes and magnitude of the problems will come in handy. The study recommends a framework for the improvement of e-waste.

Keywords: e-waste, treatment, disposal, computers, model, management policy and guidelines

Procedia PDF Downloads 79

Authors: Mahdieh Farzin Asanjan, Erkan Unal Mumcuoglu

Abstract:

Mitochondria are cytoplasmic organelles of the cell, which have a significant role in the variety of cellular metabolic functions. Mitochondria act as the power plants of the cell and are surrounded by two membranes. Significant morphological alterations are often due to changes in mitochondrial functions. A powerful technique in order to study the three-dimensional (3D) structure of mitochondria and its alterations in disease states is Electron microscope tomography. Detection of mitochondria in electron microscopy images due to the presence of various subcellular structures and imaging artifacts is a challenging problem. Another challenge is that each image typically contains more than one mitochondrion. Hand segmentation of mitochondria is tedious and time-consuming and also special knowledge about the mitochondria is needed. Fully automatic segmentation methods lead to over-segmentation and mitochondria are not segmented properly. Therefore, semi-automatic segmentation methods with minimum manual effort are required to edit the results of fully automatic segmentation methods. Here two editing tools were implemented by applying spline surface dragging and interactive live-wire segmentation tools. These editing tools were applied separately to the results of fully automatic segmentation. 3D extension of these tools was also studied and tested. Dice coefficients of 2D and 3D for surface dragging using splines were 0.93 and 0.92. This metric for 2D and 3D for live-wire method were 0.94 and 0.91 respectively. The root mean square symmetric surface distance values of 2D and 3D for surface dragging was measured as 0.69, 0.93. The same metrics for live-wire tool were 0.60 and 2.11. Comparing the results of these editing tools with the results of automatic segmentation method, it shows that these editing tools, led to better results and these results were more similar to ground truth image but the required time was higher than hand-segmentation time

Keywords: medical image segmentation, semi-automatic methods, transmission electron microscopy, surface dragging using splines, live-wire

Procedia PDF Downloads 169

Authors: C. Benjbara, A. Habbani

Abstract:

Wireless networks are getting more and more used in every new technology or feature, especially those without infrastructure (Ad hoc mode) which provide a low cost alternative to the infrastructure mode wireless networks and a great flexibility for application domains such as environmental monitoring, smart cities, precision agriculture, and so on. These application domains present a common characteristic which is the need of coexistence and intercommunication between modules belonging to different types of ad hoc networks like wireless sensor networks, mesh networks, mobile ad hoc networks, vehicular ad hoc networks, etc. This vision to bring to life such heterogeneous networks will make humanity duties easier but its development path is full of challenges. One of these challenges is the communication complexity between its components due to the lack of common or compatible protocols standard. This article proposes a new patented routing protocol based on the OLSR standard in order to resolve the heterogeneous ad hoc networks communication issue. This new protocol is applied on a specific network architecture composed of MANET, VANET, and FANET.

Keywords: Ad hoc, heterogeneous, ID-Node, OLSR

Procedia PDF Downloads 217

Authors: F. Saptouw

Abstract:

This paper briefly reviews the range of curatorial interventions made to preserve and display the Timbuktu Manuscripts. The government of South Africa and Mali collaborated to preserve the manuscripts, and brief notes will be presented about the value of archives in those specific spaces. The research initiatives of the Tombouctou Manuscripts Project, based at the University of Cape Town, feature prominently in the text. A brief overview of the history of the archive will be presented and its preservation as a key turning point in curating the intellectual history of the continent. ­­­The strategies of preservation, curation, publication and digitization are presented as complimentary interventions. Each materialization of the manuscripts contributes something significant; the complexity of the contribution is dependent primarily on the format of presentation. This integrated reading of the manuscripts is presented as a means to gain a more nuanced understanding of the past, which greatly surpasses how much information would be gleaned from relying on a single media format.

Keywords: archive, curatorship, cultural heritage, museum practice, Timbuktu manuscripts

Procedia PDF Downloads 115

Authors: Angelis P. Barlampas

Abstract:

The purpose of this study is to inform the reader, about the various applications of artificial intelligence (AI), in cardiac imaging. AI grows fast and its role is crucial in medical specialties, which use large amounts of digital data, that are very difficult or even impossible to be managed by human beings and especially doctors.Artificial intelligence (AI) refers to the ability of computers to mimic human cognitive function, performing tasks such as learning, problem-solving, and autonomous decision making based on digital data. Whereas AI describes the concept of using computers to mimic human cognitive tasks, machine learning (ML) describes the category of algorithms that enable most current applications described as AI. Some of the current applications of AI in cardiac imaging are the follows: Ultrasound: Automated segmentation of cardiac chambers across five common views and consequently quantify chamber volumes/mass, ascertain ejection fraction and determine longitudinal strain through speckle tracking. Determine the severity of mitral regurgitation (accuracy > 99% for every degree of severity). Identify myocardial infarction. Distinguish between Athlete’s heart and hypertrophic cardiomyopathy, as well as restrictive cardiomyopathy and constrictive pericarditis. Predict all-cause mortality. CT Reduce radiation doses. Calculate the calcium score. Diagnose coronary artery disease (CAD). Predict all-cause 5-year mortality. Predict major cardiovascular events in patients with suspected CAD. MRI Segment of cardiac structures and infarct tissue. Calculate cardiac mass and function parameters. Distinguish between patients with myocardial infarction and control subjects. It could potentially reduce costs since it would preclude the need for gadolinium-enhanced CMR. Predict 4-year survival in patients with pulmonary hypertension. Nuclear Imaging Classify normal and abnormal myocardium in CAD. Detect locations with abnormal myocardium. Predict cardiac death. ML was comparable to or better than two experienced readers in predicting the need for revascularization. AI emerge as a helpful tool in cardiac imaging and for the doctors who can not manage the overall increasing demand, in examinations such as ultrasound, computed tomography, MRI, or nuclear imaging studies.

Keywords: artificial intelligence, cardiac imaging, ultrasound, MRI, CT, nuclear medicine

Procedia PDF Downloads 79

Authors: Djehich Mohamed Yousri

Abstract:

The field of political science is one of the sciences in which there is much controversy, in terms of the multiplicity of schools, trends, and goals. This overlap and complexity in the interpretation of the political phenomenon in political science has been linked to other disciplines associated with it, and the science of international relations and the huge amount of theories that have found a wide range and a decisive position after the national tide in the history of Western political thought, especially after the Westphalia Conference 1648, and as a result was approved The new foundations of international politics, the most important of which is respect for state sovereignty. Historical events continued and coincided with scientific, intellectual, and economic developments following the emergence of the industrial revolution, followed by the technological revolutions in all their contents, which led to the rooting and establishment of a comprehensive political system that is more complex and overlapping than it was in the past during the First and Second World Wars. The international situation has become dependent on the digital revolution and its aspirations in The comprehensive transformation witnessed by international political relations after the Cold War.

Keywords: theorizing, international relations, approaches to international relations, political science, the political system

Procedia PDF Downloads 105

Authors: Vinicius Binotte, Guilherme Baldo, Christiane Goulart, Carlos Valadão, Eliete Caldeira, Teodiano Bastos

Abstract:

Socially assistive robotic has become increasingly active and it is present in therapies of people affected for several neurobehavioral conditions, such as Autism Spectrum Disorder (ASD). In fact, robots have played a significant role for positive interaction with children with ASD, by stimulating their social and cognitive skills. This work introduces a mobile socially-assistive robot, which was built for interaction with children with ASD, using non-linear control techniques for this interaction.

Keywords: socially assistive robotics, mobile robot, autonomous control, autism

Procedia PDF Downloads 503

Authors: Man-Yun Liu, Emily Chia-Yu Su

Abstract:

Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

Procedia PDF Downloads 324

Authors: Zine-Eddine Bouras, Abdelouaheb Talai

Abstract:

During the last two decades, the software evolution community has intensively tackled the software merging issue whose main objective is to merge in a consistent way different versions of software in order to obtain a new version. Well-established approaches, mainly based on the dependence analysis techniques, have been used to bring suitable solutions. These approaches concern the source code or software architectures. However, these solutions are more expensive due to the complexity and size. In this paper, we overcome this problem by operating at a high level of abstraction. The objective of this paper is to investigate the software merging at the level of UML activity diagrams, which is a new interesting issue. Its purpose is to merge activity diagrams instead of source code. The proposed approach, based on dependence analysis techniques, is illustrated through an appropriate case study.

Keywords: activity diagram, activity diagram slicing, dependency analysis, software merging

Procedia PDF Downloads 330

Authors: David Bakker, Nikki Rickard

Abstract:

Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

Procedia PDF Downloads 272

Authors: Mohammadsadegh Zanganehfar

Abstract:

Since the introduction of fractal geometry in 1970, numerous efforts have been made by architects and researchers to transfer this area of mathematical knowledge in the discipline of architecture and postmodernist discourse. The discourse of complexity and architecture is one of the most significant ongoing discourses in the discipline of architecture from the '70s until today and has generated significant styles such as deconstructivism and parametrism in architecture. During these years, several projects were designed and presented by designers and architects using fractal geometry, but due to the lack of sufficient knowledge and appropriate comprehension of the features and characteristics of this nonlinear geometry, none of the fractal-based designs have been successful and satisfying. Fractal geometry as a geometric technology has a long presence in the history of architecture. The current research attempts to identify and discover the characteristics, features, potentials, and functionality of fractals despite their aesthetic aspect by examining case studies of pre-modern architecture in Asia and investigating the function of fractals.

Keywords: Asian architecture, fractal geometry, fractal technique, geometric properties

Procedia PDF Downloads 258

Authors: Mohammad Reza Ebrahimi, Behnaz Mahdaviani

Abstract:

Increasing renewable sources such photovoltaic are the reason of environmental pollution. Because photovoltaic generates power in low voltage, first, generated power should increase. Usually, distributed generation injects their power to AC-Grid, hence after voltage increasing an inverter is needed to convert DC power to AC power. This results in utilization two series converter that grows cost, complexity, and low efficiency. In this paper a single stage inverter is utilized to boost and invert in one stage. Control of this scheme is easier, and its initial cost decreases comparing to conventional double stage inverters. A simple control scheme is used to control active power as well as minimum total harmonic distortion (THD) in injected current. Simulations in MATLAB demonstrate better outputs comparing with conventional approaches.

Keywords: maximum power point tracking, boost inverter, control strategy, three phase inverter

Procedia PDF Downloads 375

Authors: Debneil Saha Roy

Abstract:

Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

Procedia PDF Downloads 178

Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

Abstract:

With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

Procedia PDF Downloads 452

Authors: Sabri Arik

Abstract:

In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.

Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis

Procedia PDF Downloads 529

Authors: Aleksey Fedorov

Abstract:

Building a scalable platform for quantum computing remains one of the most challenging tasks in quantum science and technologies. However, the implementation of most important quantum operations with qubits (quantum analogues of classical bits), such as multiqubit Toffoli gate, requires either a polynomial number of operation or a linear number of operations with the use of ancilla qubits. Therefore, the reduction of the number of operations in the presence of scalability is a crucial goal in quantum information processing. One of the most elegant ideas in this direction is to use qudits (multilevel systems) instead of qubits and rely on additional levels of qudits instead of ancillas. Although some of the already obtained results demonstrate a reduction of the number of operation, they suffer from high complexity and/or of the absence of scalability. We show a strong reduction of the number of operations for the realization of the Toffoli gate by using qudits for a scalable multi-qudit processor. This is done on the basis of a general relation between the dimensionality of qudits and their topology of connections, that we derived.

Keywords: quantum computing, qudits, Toffoli gates, gate decomposition

Procedia PDF Downloads 148