Search results for: dental direct digital imaging

Authors: Jitendra Singh, Vivek Kumar

Abstract:

In this paper, a susceptible infective susceptible mathematical model is proposed and analyzed where the migration of human population is given by migration function. It is assumed that the disease is transmitted by direct contact of susceptible and infective populations with constant contact rate. The equilibria and their stability are studied by using the stability theory of ordinary differential equations and computer simulation. The model analysis shows that the spread of infectious disease increases when human population immigration increases in the habitat but it decreases if emigration increases.

Keywords: SIS (Susceptible Infective Susceptible) model, migration function, susceptible, stability

Procedia PDF Downloads 242

Authors: Onur Onder, Celal Tanuca, Mahir Ozil, Halil Sen, Alkım Ozkan, Engin Ceylan, Ali Istek, Ozgur Saglam

Abstract:

White balance adjustment of LCD TVs is an important procedure which has a direct influence on quality perception. Existing methods adjust RGB gain and offset values in different white levels during production. This paper suggests an iterative method in which the gamma is pre-adjusted during the design stage, and only 80% white is adjusted during production by modifying only RGB gain values (offset values are not modified). This method reduces the white balance adjustment time, contributing to the total efficiency of the production. Experiment shows that the adjustment results are well within requirements.

Keywords: color temperature, LCD panel deviation, LCD TV manufacturing, white balance

Procedia PDF Downloads 202

Authors: Ali Abdelsattar Elshabrawy

Abstract:

The Egyptian government is struggling to build it's eGovernment project. They succeeded to build the Egyptian digital portal, which contain links for number of services provided by different ministries. For achieving such success, their are requirements necessary to build such a project such as: internet dissemination, IT literacy, Strategy, disqualification of paper based services. This paper is going to clarify the main obstacles to the Egyptian eGovernment project from both the supply and demand sides. Also will clarify the most critical requirements in this phase of the project lifecycle. This paper should be in great value for the project team and also for many other developing countries that share the same obstacles.

Keywords: the egyptian egovernment project lifecycle, supply side barriers, demand side barriers, egovernment project requirements

Procedia PDF Downloads 138

Authors: Anne Schattel, Mitja Echim, Christof Büskens

Abstract:

Trajectory planning for deep space missions has become a recent topic of great interest. Flying to space objects like asteroids provides two main challenges. One is to find rare earth elements, the other to gain scientific knowledge of the origin of the world. Due to the enormous spatial distances such explorer missions have to be performed unmanned and autonomously. The mathematical field of optimization and optimal control can be used to realize autonomous missions while protecting recourses and making them safer. The resulting algorithms may be applied to other, earth-bound applications like e.g. deep sea navigation and autonomous driving as well. The project KaNaRiA ('Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All') investigates the possibilities of cognitive autonomous navigation on the example of an asteroid mining mission, including the cruise phase and approach as well as the asteroid rendezvous, landing and surface exploration. To verify and test all methods an interactive, real-time capable simulation using virtual reality is developed under KaNaRiA. This paper focuses on the specific challenge of the guidance during the cruise phase of the spacecraft, i.e. trajectory optimization and optimal control, including first solutions and results. In principle there exist two ways to solve optimal control problems (OCPs), the so called indirect and direct methods. The indirect methods are being studied since several decades and their usage needs advanced skills regarding optimal control theory. The main idea of direct approaches, also known as transcription techniques, is to transform the infinite-dimensional OCP into a finite-dimensional non-linear optimization problem (NLP) via discretization of states and controls. These direct methods are applied in this paper. The resulting high dimensional NLP with constraints can be solved efficiently by special NLP methods, e.g. sequential quadratic programming (SQP) or interior point methods (IP). The movement of the spacecraft due to gravitational influences of the sun and other planets, as well as the thrust commands, is described through ordinary differential equations (ODEs). The competitive mission aims like short flight times and low energy consumption are considered by using a multi-criteria objective function. The resulting non-linear high-dimensional optimization problems are solved by using the software package WORHP ('We Optimize Really Huge Problems'), a software routine combining SQP at an outer level and IP to solve underlying quadratic subproblems. An application-adapted model of impulsive thrusting, as well as a model of an electrically powered spacecraft propulsion system, is introduced. Different priorities and possibilities of a space mission regarding energy cost and flight time duration are investigated by choosing different weighting factors for the multi-criteria objective function. Varying mission trajectories are analyzed and compared, both aiming at different destination asteroids and using different propulsion systems. For the transcription, the robust method of full discretization is used. The results strengthen the need for trajectory optimization as a foundation for autonomous decision making during deep space missions. Simultaneously they show the enormous increase in possibilities for flight maneuvers by being able to consider different and opposite mission objectives.

Keywords: deep space navigation, guidance, multi-objective, non-linear optimization, optimal control, trajectory planning.

Procedia PDF Downloads 400

Authors: Farid Fahami

Abstract:

This article explores the transformative role of technology in the finance, banking, and insurance sectors. It examines key technological trends such as AI, blockchain, data analytics, and digital platforms and their impact on operations, customer experiences, and business models. The article highlights the benefits of technology adoption, including improved efficiency, cost reduction, enhanced customer experiences, and expanded financial inclusion. It also addresses challenges like cybersecurity, data privacy, and the need for upskilling. Real-world case studies demonstrate successful technology integration, and recommendations for stakeholders emphasize embracing innovation and collaboration. The article concludes by emphasizing the importance of technology in shaping the future of these sectors.

Keywords: banking, finance, insurance, technology

Procedia PDF Downloads 55

Authors: Efren Lopez Jimenez, Maria Isabel Cajero, J. Irving-Vasqueza

Abstract:

The use and processing of digital images have opened up new opportunities for the resolution of problems of various kinds, such as the calculation of different vegetation indexes, among other things, differentiating healthy vegetation from humid vegetation. However, obtaining images from which these indexes are calculated is still the exclusive subject of active research. In the present work, we propose to obtain these images using a low cost embedded system (Raspberry Pi) and its processing, using a set of libraries of open code called OpenCV, in order to obtain the Normalized Red-Green Difference Index (NGRDI).

Keywords: Raspberry Pi, vegetation index, Normalized Red-Green Difference Index (NGRDI), OpenCV

Procedia PDF Downloads 271

Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

Abstract:

Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

Procedia PDF Downloads 37

Authors: Sartaj Singh, Amar Singh, Ashok Sharma, Sandeep Kaur

Abstract:

With upcoming threats in a digital world, we need to work continuously in the area of security in all aspects, from hardware to software as well as data modelling. The rise in social media activities and hunger for data by various entities leads to cybercrime and more attack on the privacy and security of persons. Cryptography has always been employed to avoid access to important data by using many processes. Symmetric key and asymmetric key cryptography have been used for keeping data secrets at rest as well in transmission mode. Various cryptosystems have evolved from time to time to make the data more secure. In this research article, we are studying various cryptosystems in asymmetric cryptography and their application with usefulness, and much emphasis is given to Elliptic curve cryptography involving algebraic mathematics.

Keywords: cryptography, symmetric key cryptography, asymmetric key cryptography

Procedia PDF Downloads 102

Authors: Adam Bownik, Małgorzata Adamczuk, Barbara Pawlik-Skowrońska

Abstract:

Certain strains of cyanobacteria, microorganisms forming water blooms, produce toxic secondary metabolites. Although various effects of cyanotoxins in aquatic animals are known, little data can be found on the influence of some cyanobacterial oligopeptides beyond microcystins. The aim of the present study was to determine the toxicity of novel pure cyanobacterial oligopeptides: microginin FR-1 (MGFR1) and anabaenopeptin-A (ANA-A) on a transparent model rotifer Brachionus calyciflorus with the use of fluorescent double staining with Hoechst 34580 and propidium iodide. The obtained results showed that both studied oligopeptides decreased the fluorescence intensity of animals stained with Hoechst 34580 in a concentration-dependent manner. On the other hand, a concentration-dependent increase of propidium iodide fluorescence was noted in the exposed rotifers. The results suggest that MGFR-1 and ANA-A should be considered as a potent toxic agent to freshwater rotifers, and fluorescent staining with Hoechst and propidium iodide may be a valuable tool for determination of toxicity of cyanobacterial oligopeptides in rotifers.

Keywords: cyanobacteria, brachionus, oligopeptides, fluorescent staining, hoechst, propidium iodide

Procedia PDF Downloads 113

Authors: Vahid Bayrami Rad

Abstract:

In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

Procedia PDF Downloads 36

Authors: José Ramón López-Mínguez, Estrella Suárez-Corchuelo, Sergio López-Tejero, Luis Nombela-Franco, Xavier Freixa-Rofastes, Guillermo Bastos-Fernández, Xavier Millán-Álvarez, Raúl Moreno-Gómez, José Antonio Fernández-Díaz, Ignacio Amat-Santos, Tomás Benito-González, Fernando Alfonso-Manterola, Pablo Salinas-Sanguino, Pedro Cepas-Guillén, Dabit Arzamendi, Ignacio Cruz-González, Juan Manuel Nogales-Asensio

Abstract:

Background and objectives: The treatment of patients with non-valvular atrial fibrillation (NVAF) who need coronary stenting is challenging. The objective of the study was to determine whether left atrial appendage occlusion (LAAO) could be a feasible option and benefit these patients. To this end, we studied the impact of LAAO plus antiplatelet drugs vs oral anticoagulants (OAC) (including direct OAC) plus antiplatelet drugs in these patients’ long-term outcomes. Methods: The results of 207 consecutive patients with NVAF who underwent coronary stenting were analyzed. A total of 146 patients were treated with OAC (75 with acenocoumarol, 71 with direct OAC) while 61 underwent LAAO. The median follow-up was 35 months. Patients also received antiplatelet therapy as prescribed by their cardiologist. The study received the proper ethical oversight. Results: Age (mean 75.7 years), and the past medical history of stroke were similar in both groups. However, the LAAO group had more unfavorable characteristics (history of coronary artery disease [CHA2DS2-VASc], and significant bleeding [BARC ≥ 2] and HAS-BLED). The occurrence of major adverse events (death, stroke/transient ischemic events, major bleeding) and major cardiovascular events (cardiac death, stroke/transient ischemic attack, and myocardial infarction) were significantly higher in the OAC group compared to the LAAO group: 19.75% vs 9.06% (HR, 2.18; P = .008) and 6.37% vs 1.91% (HR, 3.34; P = .037), respectively. Conclusions: In patients with NVAF undergoing coronary stenting, LAAO plus antiplatelet therapy produced better long-term outcomes compared to treatment with OAC plus antiplatelet therapy despite the unfavorable baseline characteristics of the LAAO group.

Keywords: stents, atrial fibrillation, anticoagulants, left atrial appendage occlusion

Procedia PDF Downloads 46

Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

Abstract:

The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic has not only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of normal design, construction, and operation of cities provides a unique opportunity to improve the connection between people. The Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the research contribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: data analytics, smart cities, competitive advantage, internet of things

Procedia PDF Downloads 111

Authors: Aissa Belmeguenai, Oulaya Berrak, Khaled Mansouri

Abstract:

In this work, efficiency implementation and security evaluation of the keystream generator of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written with MATLAB.7.5. First of all, two different original images are used to validate the proposed design. The developed program is used to transform the original images data into digital image file. Finally, the proposed program is implemented to encrypt and decrypt images data. Several tests are done to prove the design performance, including visual tests and security evaluation.

Keywords: Achterbahn-128, keystream generator, stream cipher, image encryption, security analysis

Procedia PDF Downloads 298

Authors: Babak Eslami

Abstract:

Bimodal and trimodal AFM have provided additional capabilities to scanning probe microscopy characterization techniques. These capabilities have specifically enhanced material characterization of surfaces and provided subsurface imaging in addition to conventional topography images. Bimodal and trimodal AFM, being different techniques of multifrequency AFM, are based on exciting the cantilever’s fundamental eigenmode with second and third eigenmodes simultaneously. Although higher eigenmodes provide a higher number of observables that can provide additional information about the sample, they cause experimental challenges. In this work, different experimental approaches for enhancing AFM images in multifrequency for different characterization goals are provided. The trade-offs between eigenmodes including the advantages and disadvantages of using each mode for different samples (ranging from stiff to soft matter) in both air and liquid environments are provided. Additionally, the advantage of performing conventional single tapping mode AFM with higher eigenmodes of the cantilever in order to reduce sample indentation is discussed. These analyses are performed on widely used polymers such as polystyrene, polymethyl methacrylate and air nanobubbles on different surfaces in both air and liquid.

Keywords: multifrequency, sensitivity, soft matter, polymer

Procedia PDF Downloads 126

Authors: Mohammad Reza Rahimi Khoygani, Reza Ghasemi

Abstract:

In this paper, designing direct adaptive neural controller is applied for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) is used for the Neural network (NN). The adaptive neural controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are the merits of this paper. The promising performance of the proposed controllers investigates in simulation results.

Keywords: adaptive control, pendulum dynamical system, nonlinear control, adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

Procedia PDF Downloads 653

Authors: Rianne Voet

Abstract:

This paper uses a literature review to search for keys of success for entrepreneurial regional media collaborations in the Netherlands and elsewhere. It specifies keys on general aspects: a digital-first strategy, innovation, a particular journalistic mission and a new role for the public. It outlines keys in practicalities: competencies, revenue model, legal structure, communication structure and organization structure. The paper elaborates on a new public function and a new concept of citizenship which, according to several authors in the literature, are required in order to be successful. Finally, it offers a model of keys for success in regional entrepreneurial media collaboration.

Keywords: media collaboration, factors of success, keys of success, regional media cooperation

Procedia PDF Downloads 252

Authors: E.A. Kuchma

Abstract:

Photodynamic therapy (PDT) is considered an alternative and minimally invasive cancer treatment modality compared to chemotherapy and radiation therapy. PDT includes three main components: a photosensitizer (PS), oxygen, and a light source. PS is injected into the patient's body and then selectively accumulates in the tumor. However, the light used in PDT (spectral range 400–700 nm) is limited to superficial lesions, and the light penetration depth does not exceed a few cm. The problem of PDT (poor visible light transmission) can be solved by using X-rays. The penetration depth of X-rays is ten times greater than that of visible light. Therefore, X-ray radiation easily penetrates through the tissues of the body. The aim of this work is to develop universal nanocomposites for X-ray photodynamic therapy of deep and superficial tumors using scintillation nanoparticles of gadolinium fluoride (GdF3), doped with Tb3+, coated with a biocompatible coating (PEG) and photosensitizer RB (Rose Bengal). PEG@GdF3:Tb3+(15%) – RB could be used as an effective X-ray, UV, and photoluminescent mediator to excite a photosensitizer for generating reactive oxygen species (ROS) to kill tumor cells via photodynamic therapy. GdF3 nanoparticles can also be used as contrast agents for computed tomography (CT) and magnetic resonance imaging (MRI).

Keywords: X-ray induced photodynamic therapy, scintillating nanoparticle, radiosensitizer, photosensitizer

Procedia PDF Downloads 65

Authors: Tahir Iqbal, Mumtaz Ali, Syed Wajahat Kareem, Muhammad Harris

Abstract:

Digital information is expanding in exponential order in our life. Information that is residing online and offline are stored in huge repositories relating to every aspect of our lives. Getting the required information is a task of retrieval systems. Content based image retrieval (CBIR) is a retrieval system that retrieves the required information from repositories on the basis of the contents of the image. Time is a critical factor in retrieval system and using indexed views with CBIR system improves the time efficiency of retrieved results.

Keywords: content based image retrieval (CBIR), indexed view, color, image retrieval, cross correlation

Procedia PDF Downloads 453

Authors: Ziyad S. Haidar

Abstract:

Background: Saliva plays a major role in maintaining oral, dental, and general health and well-being; where it normally bathes the oral cavity acting as a clearing agent. This becomes more apparent when the amount and quality of saliva are significantly reduced due to medications, salivary gland neoplasms, disorders such as Sjögren’s syndrome, and especially ionizing radiation therapy for tumors of the head and neck, the 5th most common malignancy worldwide, during which the salivary glands are included within the radiation field/zone. Clinically, patients affected by salivary gland dysfunction often opt to terminate their radiotherapy course prematurely as they become malnourished and experience a significant decrease in their QoL. Accordingly, the formulation of a radio-protection/-prevention modality and development of an alternative Rx to restore damaged salivary gland tissue is eagerly awaited and highly desirable. Objectives: Assess the pre-clinical radio-protective effect and reparative/regenerative potential of layer-by-layer self-assembled lipid-polymer-based core-shell nanocapsules designed and fine-tuned for the sequential (ordered) release of dual cytokines, following a single local administration (direct injection) into a murine sub-mandibular salivary gland model of irradiation. Methods: The formulated core-shell nanocapsules were characterized by physical-chemical-mechanically pre-/post-loading with the drugs, followed by optimizing the pharmaco-kinetic profile. Then, nanosuspensions were administered directly into the salivary glands, 24hrs pre-irradiation (PBS, un-loaded nanocapsules, and individual and combined vehicle-free cytokines were injected into the control glands for an in-depth comparative analysis). External irradiation at an elevated dose of 18Gy was exposed to the head-and-neck region of C57BL/6 mice. Salivary flow rate (un-stimulated) and salivary protein content/excretion were regularly assessed using an enzyme-linked immunosorbent assay (3-month period). Histological and histomorphometric evaluation and apoptosis/proliferation analysis followed by local versus systemic bio-distribution and immuno-histochemical assays were then performed on all harvested major organs (at the distinct experimental end-points). Results: Monodisperse, stable, and cytocompatible nanocapsules capable of maintaining the bioactivity of the encapsulant within the different compartments with the core and shell and with controlled/customizable pharmaco-kinetics, resulted, as is illustrated in the graphical abstract (Figure) below. The experimental animals demonstrated a significant increase in salivary flow rates when compared to the controls. Herein, salivary protein content was comparable to the pre-irradiation (baseline) level. Histomorphometry further confirmed the biocompatibility and localization of the nanocapsules, in vivo, into the site of injection. Acinar cells showed fewer vacuoles and nuclear aberration in the experimental group, while the amount of mucin was higher in controls. Overall, fewer apoptotic activities were detected by a Terminal deoxynucleotidyl Transferase (TdT) dUTP Nick-End Labeling (TUNEL) assay and proliferative rates were similar to the controls, suggesting an interesting reparative and regenerative potential of irradiation-damaged/-dysfunctional salivary glands. The Figure below exemplifies some of these findings. Conclusions: Biocompatible, reproducible, and customizable self-assembling layer-by-layer core-shell delivery system is formulated and presented. Our findings suggest that localized sequential bioactive delivery of dual cytokines (in specific dose and order) can prevent irradiation-induced damage via reducing apoptosis and also has the potential to promote in situ proliferation of salivary gland cells; maxSALIVA is scalable (Good Manufacturing Practice or GMP production for human clinical trials) and patent-pending.

Keywords: cancer, head and neck, oncology, drug development, drug delivery systems, nanotechnology, nanoncology

Procedia PDF Downloads 61

Authors: Abdul Ganiyu Iddrisu

Abstract:

Digitization is the process of transforming analog material into digital form, especially for storage and use in a computer. Significant development of information and communication technology (ICT) over the past years has encouraged many researchers to investigate its contribution to promoting economic growth, and reducing poverty. Yet compelling empirical evidence on the effects of digitization on economic growth remains weak, particularly in Africa. This is because extant studies that explicitly evaluate digitization and economic growth nexus are mostly reports and desk reviews. This points out an empirical knowledge gap in the literature. Hypothetically, digitization influences financial sector development which in turn influences economic growth. Digitization has changed the financial sector and its operating environment. Obstacles to access to financing, for instance, physical distance, minimum balance requirements, low-income flows among others can be circumvented. Savings have increased, micro-savers have opened bank accounts, and banks are now able to price short-term loans. This has the potential to develop the financial sector, however, empirical evidence on digitization-financial development nexus is dearth. On the other hand, a number of studies maintained that financial sector development greatly influences growth of economies. We therefore argue that financial sector development is one of the transmission mechanisms through which digitization affects economic growth. Employing macro-country-level data from African countries and using fixed effects, random effects and Hausman-Taylor estimation approaches, this paper contributes to the literature by analysing economic growth in Africa focusing on the role of digitization, and financial sector development. First, we assess how digitization influence financial sector development in Africa. From an economic policy perspective, it is important to identify digitization determinants of financial sector development so that action can be taken to reduce the economic shocks associated with financial sector distortions. This nexus is rarely examined empirically in the literature. Secondly, we examine the effect of domestic credit to private sector and stock market capitalization as a percentage of GDP as used to proxy for financial sector development on 2 economic growth. Digitization is represented by the volume of digital/ICT equipment imported and GDP growth is used to proxy economic growth. Finally, we examine the effect of digitization on economic growth in the light of financial sector development. The following key results were found; first, digitalization propels financial sector development in Africa. Second, financial sector development enhances economic growth. Finally, contrary to our expectation, the results also indicate that digitalization conditioned on financial sector development tends to reduce economic growth in Africa. However, results of the net effects suggest that digitalization, overall, improves economic growth in Africa. We, therefore, conclude that, digitalization in Africa does not only develop the financial sector but unconditionally contributes the growth of the continent’s economies.

Keywords: digitalization, economic growth, financial sector development, Africa

Procedia PDF Downloads 87

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

Abstract:

Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

Procedia PDF Downloads 133

Authors: Parag Nihawan, Ravinder Singh Bhatia, Dinesh Kumar Jain

Abstract:

Industrial drives are source of serious power quality problems. In this, two typical industrial drives have been dealt with, namely, FOC induction motor drives and DTC induction motor drive. The Z-source inverter is an emerging topology of power electronic converters which is capable of buck boost characteristics. The performances of different control methods based Z-source inverters feeding these industrial drives have been investigated, in this work. The test systems have been modeled and simulated in MATLAB/SIMULINK. The results obtained after carrying out these simulations have been used to draw the conclusions.

Keywords: Z-source inverter, total harmonic distortion, direct torque control, field orientation control

Procedia PDF Downloads 567

Authors: Reyhane Hamed Kamran

Abstract:

Early stage morphogenesis requires the execution of complex systems that direct the nearby conduct of gatherings of cells. The organization of such instruments has been, for the most part, deciphered through the recognizable proof of moderated groups of flagging pathways that spatially and transiently control cell conduct. In any case, how this data is handled to control cell shape and cell elements is an open territory of examination. The structure that rises up out of differing controls, for example, cell science, material science, and formative science, focuses to bond and cortical actin arranges as controllers of cell surface mechanics. In this specific circumstance, a scope of formative marvels can be clarified by the guideline of cell surface pressure.

Keywords: cell, tissue damage, morphogenesis, cell conduct

Procedia PDF Downloads 82

Authors: Narin Salehiyan

Abstract:

Early stage morphogenesis requires the execution of complex systems that direct the nearby conduct of gatherings of cells. The organization of such instruments has been, for the most part, deciphered through the recognizable proof of moderated groups of flagging pathways that spatially and transiently control cell conduct. In any case, how this data is handled to control cell shape and cell elements is an open territory of examination. The structure that rises up out of differing controls, for example, cell science, material science and formative science, focuses to bond and cortical actin arranges as controllers of cell surface mechanics. In this specific circumstance, a scope of formative marvels can be clarified by the guideline of cell surface pressure.

Keywords: cell, tissue damage, morphogenesis, cell conduct

Procedia PDF Downloads 62

Authors: Adriana Haulica

Abstract:

Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

Procedia PDF Downloads 56

Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

Abstract:

The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic hasnot only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of the normal design, construction, and operation of cities provides a unique opportunity to improve connection between people. Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the researchcontribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create a competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: internet of things, data analytics, smart cities, competitive advantage

Procedia PDF Downloads 82

Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

Abstract:

Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

Procedia PDF Downloads 139

Authors: M.Goodarzi, M.Mohammadi, M. Rezaee

Abstract:

The technical analysis of using solar energy and electricity for water pumping in the Khuzestan province in Iran is investigated. For this purpose, the ecological conditions such as the weather data, air clearness and sunshine hours are analyzed. The nature of groundwater in the region was examined in terms of depth, static and dynamic head, water pumping rate.Three configurations for solar water pumping system were studied in this thesis; AC solar water pumping with storage battery, AC solar water pumping with storage tank and DC direct solar water pumping.

Keywords: technical feasibility, solar energy, photovoltaic systems, photovoltaic water pumping system

Procedia PDF Downloads 611

Authors: David A. Wallace, Salakjit J. Nilboworn

Abstract:

Secure and reliable transmission and distribution of electrical power is crucial in today’s ever-increasing demand for electricity. Traditional methods of protecting the electrical grid have relied on relaying systems receiving voltage and current inputs from inductive instruments transformers (IT). This method has provided robust and stable performance throughout the years. Today with the advent of new non-conventional transformers (NCIT) and sensors, the electrical landscape is changing. These new systems have to ability to provide the same electrical performance as traditional instrument transformers with the added features of data acquisition, communication, smaller footprint, lower cost and resistance to GMD/GIC events.

Keywords: non-conventional instrument transformers, digital substations, smart grids, micro-grids

Procedia PDF Downloads 66

Authors: Bidisha Chatterjee, Sonal Grover, Rekha Gurung

Abstract:

Postpartum dissection of the internal carotid artery is a relatively rare condition and is considered as an underlying aetiology in 5% to 25% of strokes under the age of 30 to 45 years. However, 86% of these cases recover completely and 14% have mild focal neurological symptoms. Prognosis is generally good with early intervention. The risk quoted for a repeat carotid artery dissection in subsequent pregnancies is less than 2%. 36-year Caucasian primipara presented on postnatal day one of forceps delivery with tachycardia. In the intrapartum period she had a history of prolonged rupture of membranes and developed intrapartum sepsis and was treated with antibiotics. Postpartum ECG showed septal inferior T wave inversion and a troponin level of 19. Subsequently Echocardiogram ruled out post-partum cardiomyopathy. Repeat ECG showed improvement of the previous changes and in the absence of symptoms no intervention was warranted. On day 4 post-delivery, she had developed symptoms of droopy right eyelid, pain around the right eye and itching in the right ear. On examination, she had developed right sided ptosis, unequal pupils (Rt miotic pupil). Cranial nerve examination, reflexes, sensory examination and muscle power was normal. Apart from migraine, there was no medical or family history of note. In view of Horner’s on the right, she had a CT Angiogram and subsequently MR/MRA and was diagnosed with dissection of the cervical portion of the right internal carotid artery. She was discharged on a course of Aspirin 75mg. By 6 week post-natal follow up patient had recovered significantly with occasional episodes of unequal pupils and tingling of right toes which resolved spontaneously. Cervical artery dissection, including VAD and carotid artery dissection, are rare complications of pregnancy with an estimated annual incidence of 2.6–3 per 100,000 pregnancy hospitalizations. Aetiology remains unclear though trauma during straining at labour, underlying arterial disease and preeclampsia have been implicated. Hypercoagulable state during pregnancy and puerperium could also be an important factor. 60-90% cases present with severe headache and neck pain and generally precede neurological symptoms like ipsilateral Horner’s syndrome, retroorbital pain, tinnitus and cranial nerve palsy. Although rare, the consequences of delayed diagnosis and management can lead to severe and permanent neurological deficits. Patients with a strong index of suspicion should undergo an MRI or MRA of head and neck. Antithrombotic and antiplatelet therapy forms the mainstay of therapy with selected cases needing endovascular stenting. Long term prognosis is favourable with either complete resolution or minimal deficit if treatment is prompt. Patients should be counselled about the recurrence risk and possibility of stroke in future pregnancy. Coronary artery dissection is rare and treatable but needs early diagnosis and treatment. Post-partum headache and neck pain with neurological symptoms should prompt urgent imaging followed by antithrombotic and /or antiplatelet therapy. Most cases resolve completely or with minimal sequelae.

Keywords: postpartum, dissection of internal carotid artery, magnetic resonance angiogram, magnetic resonance imaging, antiplatelet, antithrombotic

Procedia PDF Downloads 83