Search results for: brain machine interface (BMI)

Authors: Farina Maqbool

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Background: It is well said that children are considered the future masons of the country and a healthy brain is found in a healthy body. Therefore, a healthy generation can be produced by giving knowledge of immunization to mothers. Immunization is the most lucrative public health intrusion that has placed the greatest effect on the health of the people. The main objective of the present study was to find out the mother’s knowledge, attitude, and practices towards childhood immunization. Methods: Multistage sampling technique was used. One hundred and sixty mothers were selected conveniently who have at least one child up to two years. Data were collected through the face to face interview. The chi-square test was used to test the significance of the association between independent and dependent variables. Data were analyzed using the Statistical Package for Social Science. Results: A higher percentage of mothers (85.0%) knew vaccine-preventable diseases. Major proportion (82.5%) of the mothers had thought that immunization is important for their child’s health. A majority (66.3%) of the respondents’ children were fully immunized, whereas 26.3 percent of them were replied negatively. Remaining 7.5 percent of the respondents’ child un-immunized Chi-square value (39.14) shows a highly significant association between the education of the respondents and receiving of all recommended vaccines for children. Gamma value shows a strong positive relationship between the variables.

Keywords: attitude, childhood, immunization, knowledge, practices

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is an inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially Human Herpesvirus 6 (HHV-6), and MS is one potential cause that is not well understood. In this study, we aim to summarize the available data on HHV-6 infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis", " Human Herpesvirus 6 ", and "central nervous system" in the databases PubMed and Google Scholar between 2017 and 2022 were searched, and 12 articles were chosen, studied, and analyzed. Results: HHV 6 tends towards TCD 4+ lymphocytes and enters the CNS due to the weakening of the blood-brain barrier due to inflammatory damage. Following the observation that the HHV-6 U24 protein has a seven amino acid sequence with myelin basic protein, which is one of the main components of the myelin sheath, it could cause a molecular mimicry mechanism followed by cross-reactivity. Reactivation of HHV-6 in the CNS can cause the release of proinflammatory cytokines, including TNF-α, leading to immune-mediated demyelination in patients with MS. Conclusion: There is a high expression of endogenous retroviruses during the course of MS, which indicates the relationship between HHV-6 and MS, and that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of HHV-6 may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, human herpesvirus 6, central nervous system, autoimmunity

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: M. Shirinbayan, J. Fitoussi, N. Abbasnezhad, A. Lucas, A. Tcharkhtchi

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Sheet Molding Compounds (SMCs) with special microstructures are very attractive to use in automobile structures especially when they are accidentally subjected to collision type accidents because of their high energy absorption capacity. These are materials designated as standard SMC, Advanced Sheet Molding Compounds (A-SMC), Low-Density SMC (LD-SMC) and etc. In this study, testing methods have been performed to compare the mechanical responses and damage phenomena of SMC, LD-SMC, and A-SMC under quasi-static and high strain rate tensile tests. The paper also aims at investigating the effect of an initial pre-damage induced by fatigue on the tensile dynamic behavior of A-SMC. In the case of SMCs and A-SMCs, whatever the fibers orientation and applied strain rate are, the first observed phenomenon of damage corresponds to decohesion of the fiber-matrix interface which is followed by coalescence and multiplication of these micro-cracks and their propagations. For LD-SMCs, damage mechanisms depend on the presence of Hollow Glass Microspheres (HGM) and fibers orientation.

Keywords: SMC, Sheet Molding Compound, LD-SMC, Low-Density SMC, A-SMC, Advanced Sheet Molding Compounds, HGM, Hollow Glass Microspheres, damage

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Authors: Zakeia Benmoussa

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Pressure on freshwater systems comes from removing too much water to grow crops; contamination from economic activities, land use practices, and human waste. The paper will be focusing on how water management can influence the design, implementation, and impacts of the ecological principles of biomimicry as sustainable methods in recycling wastewater. At Texas State, United States of America, in particular the lower area of the Trinity River refuge, there is a true example of the diversity to be found in that area, whether when exploring the lands or the waterways. However, as the Trinity River supplies water to the state’s residents, the lower part of the river at Liberty County presents several problem of wastewater discharge in the river. Therefore, conservation efforts are particularly important in the Trinity River basin. Clearly, alternative ways must be considered in order to conserve water to meet future demands. As a result, there should be another system provided rather than the conventional water treatment. Mimicking ecosystem's technologies out of context is not enough, but if we incorporate plants into building architecture, in addition to their beauty, they can filter waste, absorb excess water, and purify air. By providing an architectural proposal center, a living system can be explored through several methods that influence natural resources on the micro-scale in order to impact sustainability on the macro-scale. The center consists of an ecological program of Plant and Water Biomimicry study which becomes a living organism that purifies the river water in a natural way through architecture. Consequently, a rich beautiful nature could be used as an educational destination, observation and adventure, as well as providing unpolluted fresh water to the major cities of Texas. As a result, these facts raise a couple of questions: Why is conservation so rarely practiced by those who must extract a living from the land? Are we sufficiently enlightened to realize that we must now challenge that dogma? Do architects respond to the environment and reflect on it in the correct way through their public projects? The method adopted in this paper consists of general research into careful study of the system of the living machine, in how to integrate it at architectural level, and finally, the consolidation of the all the conclusions formed into design proposal. To summarise, this paper attempts to provide a sustainable alternative perspective in bridging physical and mental interaction with biodiversity to enhance nature by using architecture.

Keywords: Biodiversity, Design with Nature, Sustainable architecture, Waste water treatment.

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Authors: Aitor Bilbao, Dragos Axinte, John Billingham

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The inverse problem in Energy Beam (EB) Processes consists of defining the control parameters, in particular the 2D beam path (position and orientation of the beam as a function of time), to arrive at a prescribed solution (freeform surface). This inverse problem is well understood for conventional machining, because the cutting tool geometry is well defined and the material removal is a time independent process. In contrast, EB machining is achieved through the local interaction of a beam of particular characteristics (e.g. energy distribution), which leads to a surface-dependent removal rate. Furthermore, EB machining is a time-dependent process in which not only the beam varies with the dwell time, but any acceleration/deceleration of the machine/beam delivery system, when performing raster paths will influence the actual geometry of the surface to be generated. Two different EB processes, Abrasive Water Machining (AWJM) and Pulsed Laser Ablation (PLA), are studied. Even though they are considered as independent different technologies, both can be described as time-dependent processes. AWJM can be considered as a continuous process and the etched material depends on the feed speed of the jet at each instant during the process. On the other hand, PLA processes are usually defined as discrete systems and the total removed material is calculated by the summation of the different pulses shot during the process. The overlapping of these shots depends on the feed speed and the frequency between two consecutive shots. However, if the feed speed is sufficiently slow compared with the frequency, then consecutive shots are close enough and the behaviour can be similar to a continuous process. Using this approximation a generic continuous model can be described for both processes. The inverse problem is usually solved for this kind of process by simply controlling dwell time in proportion to the required depth of milling at each single pixel on the surface using a linear model of the process. However, this approach does not always lead to the good solution since linear models are only valid when shallow surfaces are etched. The solution of the inverse problem is improved by using a discrete adjoint optimization algorithm. Moreover, the calculation of the Jacobian matrix consumes less computation time than finite difference approaches. The influence of the dynamics of the machine on the actual movement of the jet is also important and should be taken into account. When the parameters of the controller are not known or cannot be changed, a simple approximation is used for the choice of the slope of a step profile. Several experimental tests are performed for both technologies to show the usefulness of this approach.

Keywords: abrasive waterjet machining, energy beam processes, inverse problem, pulsed laser ablation

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Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

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The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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Authors: Rupan Das Chakraborty, Surendra K. Martha

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Hard carbons (HCs) are extensively used as anode materials for sodium-ion batteries due to their availability, low cost, and ease of synthesis. It possesses the ability to store Na ion between stacked sp2 carbon layers and micropores. In this work, hard carbons are synthesized from different concentrations (0.5M to 5M) of dextrose solutions by hydrothermal synthesis followed by high-temperature calcination at 1100 ⁰C in an inert atmosphere. Dextrose has been chosen as a precursor material as it is a eco-friendly and renewable source. Among all hard carbon derived from different concentrations of dextrose solutions, hard carbon derived from 3M dextrose solution delivers superior electrochemical performance compared to other hard carbons. Hard carbon derived from 3M dextrose solution (Dextrose derived Hard Carbon-3M) provides an initial reversible capacity of 257 mAh g-1 with a capacity retention of 83 % at the end of 100 cycles at 30 mA g-1). The carbons obtained from different dextrose concentration show very similar Cyclic Voltammetry and chargedischarging behavior at a scan rate of 0.05 mV s-1 the Cyclic Voltammetry curve indicate that solvent reduction and the solid electrolyte interface (SEI) formation start at E < 1.2 V (vs Na/Na+). Among all 3M dextrose derived electrode indicate as a promising anode material for Sodium-ion batteries (SIBs).

Keywords: dextrose derived hard carbon, anode, sodium-ion battery, electrochemical performance

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Authors: Giacomo Rossi, Bernardo Favini, Eugenio Giacomazzi, Franca Rita Picchia, Nunzio Maria Salvatore Arcidiacono

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A numerical technique for mesh refinement in the HeaRT (Heat Release and Transfer) numerical code is presented. In the CFD framework, Large Eddy Simulation (LES) approach is gaining in importance as a tool for simulating turbulent combustion processes, also if this approach has an high computational cost due to the complexity of the turbulent modeling and the high number of grid points necessary to obtain a good numerical solution. In particular, when a numerical simulation of a big domain is performed with a structured grid, the number of grid points can increase so much that the simulation becomes impossible: this problem can be overcame with a mesh refinement technique. Mesh refinement technique developed for HeaRT numerical code (a staggered finite difference code) is based on an high order reconstruction of the variables at the grid interfaces by means of a least square quasi-ENO interpolation: numerical code is written in modern Fortran (2003 standard of newer) and is parallelized using domain decomposition and message passing interface (MPI) standard.

Keywords: LES, multi-resolution, ENO, fortran

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Authors: Laura Dembovska, Diana Bajare, Vitalijs Lusis, Genadijs Sahmenko, Aleksandrs Korjakins

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This study focused on the mechanical properties of the fibre reinforced High Performance Concrete. The most important benefits of addition of fibres to the concrete mix are the hindrance of the development of microcracks, the delay of the propagation of microcracks to macroscopic cracks and the better ductility after microcracks have been occurred. This work presents an extensive comparative experimental study on six different types of fibres (alkali resistant glass, polyvinyl alcohol fibres, polypropylene fibres and carbon fibres) with the same binding High Performance Concrete matrix. The purpose was to assess the influence of the type of fibre on the mechanical properties of Fibre Reinforced High Performance Concrete. Therefore, in this study three main objectives have been chosen: 1) analyze the structure of the bulk cementitious matrix, 2) determine the influence of fibres and distribution in the matrix on the mechanical properties of fibre reinforced High Performance Concrete and 3) characterize the microstructure of the fibre-matrix interface. Acknowledgement: This study was partially funded by European Regional Development Fund project Nr.1.1.1.1/16/A/007 “A New Concept for Sustainable and Nearly Zero-Energy Buildings” and COST Action TU1404 Conference grants project.

Keywords: high performance concrete, fibres, mechanical properties, microstructure

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Authors: Niranjan Mukherjee, Burga Braun, Ulrich Szewzyk

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Recalcitrant pharmaceuticals are increasingly found in urban water systems forced by demographic changes. The groundwater-surface water interface, or the hyporheic zone, is known for its impressive self-purification capacity of water bodies. Redox gradients present in this zone provide a wide range of electron acceptors and harbour diverse microbial communities. Biotic transformations of pharmaceuticals in this zone have been demonstrated, but not much information is available on the kind of communities bringing about these transformations. Therefore, bioreactors using sediment from the hyporheic zone of a river in Berlin were set up and fed with iopromide, a recalcitrant iodinated X-ray contrast medium. Iopromide, who’s many oxic and anoxic transformation products have been characterized, was shown to be transformed in such a bioreactor as it passes along the gradient. Many deiodinated transformation products of iopromide could be identified at the outlet of the reactor. In our experiments, it was seen that at the same depths of the column, the transformation of iopromide increased over time. This could be an indication of the microbial communities in the sediment adapting to iopromide. The hyporheic zone, with its varying redox conditions, mainly due to the upwelling and downwelling of surface and groundwater levels, could potentially provide microorganisms with conditions for the complete transformation of recalcitrant pharmaceuticals.

Keywords: iopromide, hyporheic zone, recalcitrant pharmaceutical, redox gradients

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Authors: Omar Sorour, Michael Leahy, Thomas Irvine, Vladimir Koren

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Introduction: Covid encephalitis is a rare yet dangerous complication, particularly affecting the older and immunocompromised. Symptoms range from confusion to delirium, coma, and seizures. Although neurological manifestations have become more well-characterized in COVID patients, little is known about whether priorneurological abnormalities may predispose patients to COVID encephalopathy. Case Description: A 73 y.o. male with a CT and MRI-confirmed stable, prior 9 mm cavernoma in the right frontal lobe and no past history of seizures was hospitalized with generalized weakness, abdominal pain, nausea, and shortness of breath with subsequent COVID pneumonia. Three days after the initial presentation, the patient developed a spontaneous generalized tonic-clonic seizure consistent with presumed COVID encephalitis, along with somnolence and confusion. A day later, the patient had two other seizure episodes. Follow-up EEG suggested an inter-ictal epileptic focus with sharp waves corresponding to roughly the same location as the patient’s pre-existing cavernoma. The patient’s seizures stopped shortly thereafter, while his encephalopathy continued for days. Conclusion: We illustrate that a pre-existing anatomic cortical abnormality may act as a potential nidus for new-onset seizure activity in the context of suggested COVID encephalopathy. Future studies may further demonstrate that manifestations of COVIDencephalopathy in certain patients may be more predictable than initially assumed.

Keywords: cavernoma, covid, encephalopathy, seizures

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Authors: Yin-Yann Chen, Tzu-Ling Chen

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This study presents the case of an actual Taiwanese semiconductor assembly and testing manufacturer. Three major bottleneck manufacturing processes, namely, die bond, wire bond, and molding, are analyzed to determine how to use finite resources to achieve the optimal capacity allocation. A medium-term capacity allocation planning model is developed by considering the optimal total profit to satisfy the promised volume demanded by customers and to obtain the best migration decision among production lines for machines and tools. Finally, sensitivity analysis based on the actual case is provided to explore the effect of various parameter levels.

Keywords: capacity planning, capacity allocation, machine migration, resource configuration

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Authors: Fateme Nokhodchi Bonab

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Studies related to magnetic resonance imaging (MRI) and drug delivery are reviewed in this study to demonstrate the role of transport theory in porous media in facilitating advances in biomedical applications. Diffusion processes are believed to be important in many therapeutic modalities such as: B. Delivery of drugs to the brain. We analyse the progress in the development of diffusion equations using the local volume average method and the evaluation of applications related to diffusion equations. Torsion and porosity have significant effects on diffusive transport. In this study, various relevant models of torsion are presented and mathematical modeling of drug release from biodegradable delivery systems is analysed. In this study, a new model of drug release kinetics from porous biodegradable polymeric microspheres under bulk and surface erosion of the polymer matrix is presented. Solute drug diffusion, drug dissolution from the solid phase, and polymer matrix erosion have been found to play a central role in controlling the overall drug release process. This work paves the way for MRI and drug delivery researchers to develop comprehensive models based on porous media theory that use fewer assumptions compared to other approaches.

Keywords: MRI, porous media, drug delivery, biomedical applications

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Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Nafisa Komilova, Plamena Angelova, Andrey Abramov, Ulugbek Mirkhodjaev

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Parkinson’s disease (PD) is a progressive neurodegenerative disorder which is induced by the loss of dopaminergic neurons in the midbrain. The mechanism of neurodegeneration is associated with the aggregation of misfolded proteins, oxidative stress, and mitochondrial disfunction. Considering this, the process of removal of unwanted organelles or proteins by autophagy is vitally important in neurons, and activation of these processes could be protective in PD. Short-time acidification of cytosol can activate mitophagy and autophagy, and here we used sodium pyruvate and sodium lactate in human fibroblasts with PD mutations (Pink1, Pink1/Park2, α-syn triplication, A53T) to induce changes in intracellular pH. We have found that both lactate and pyruvate in millimolar concentrations can induce short-time acidification of cytosol in these cells. It induced activation of mitophagy and autophagy in control and PD fibroblasts and protected against cell death. Importantly, the application of lactate to acute brain slices of control and Pink1 knockout mice also induced a reduction of pH in neurons and astrocytes that increase the level of mitophagy. Thus, acidification of cytosol by compounds which play important role in cell metabolism also can activate mitophagy and autophagy and protect cells in the familial form of PD.

Keywords: Parkinson's disease, mutations, mitophagy, autophagy

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Authors: John Segars

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Built out of a real-world need to have better, more detailed, asset and infrastructure documentation, this project will lay out the case for using the database functionality of ArcGIS as a tool to track and maintain infrastructure location, status, maintenance and serviceability. Workflows and processes will be presented and detailed which may be applied to an organizations’ infrastructure needs that might allow them to make use of the robust tools which surround the ArcGIS platform. The end result is a value-added information system framework with a geographic component e.g., the spatial location of various I.T. assets, a detailed set of records which not only documents location but also captures the maintenance history for assets along with photographs and documentation of these various assets as attachments to the numerous feature class items. In addition to the asset location and documentation benefits, the staff will be able to log into the devices and pull SNMP (Simple Network Management Protocol) based query information from within the user interface. The entire collection of information may be displayed in ArcGIS, via a JavaScript based web application or via queries to the back-end database. The project is applicable to all organizations which maintain an IT infrastructure but specifically targets post-secondary educational institutions where access to ESRI resources is generally already available in house.

Keywords: ESRI, GIS, infrastructure, network documentation, PostgreSQL

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Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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Authors: Fatemeh Noughani, Seyd Mehdi Sadat

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Medical tourism or travel therapy is travelling from one country to another to be under medical treatment, utilizing the health factors of natural sector like mineral water springs and so on. From 1990s medical tourism around the world developed and grew because of different factors like globalization and free trade in the fields of health services, changes in exchange rates in the world economy (which caused the desirability of Asian countries as a medical tourist attraction) in a way that currently there is a close competition in this field among famous countries in medical services to make them find a desirable place in medical tourism market of the world as a complicated and growing industry in a short time. Perhaps tourism is an attractive industry and a good support for the economy of Iran, if we try to merge oil earnings and tourism industry it would be better and more constructive than putting them in front of each other. Moving from oil toward tourism economy especially medical tourism, must be one of the prospects of Iran's government for the oil industry to provide a few percent of the yearly earnings of the country. Among the achievements in medical tourism we can name the prevention of brain drain to other countries and an increase in employment rate for healthcare staff, increase in foreign exchange earnings of the country because of the tourists' staying and followed by increasing the quality of life and cultural transmission as well as empowering the medical human resources.

Keywords: developing countries, health tourism, quality of life, cultural transmission

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Authors: Anu Paul, Varghese Paul

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The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.

Keywords: enterprise architecture, service-oriented e-Government enterprise, service interface layer, service model

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Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

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Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

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Authors: Zahira Anane, Abdelhafid Bayadi

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Corona in the HV overhead transmission lines is an important source of attenuation and distortion of overvoltage surges. This phenomenon of distortion, which is superimposed on the distortion by skin effect, is due to the dissipation of energy by injection of space charges around the conductor, this process with place as soon as the instantaneous voltage exceeds the threshold voltage of the corona effect conductors. This paper presents a mathematical model to determine the corona inception voltage, the critical electric field and the corona radius, to predict the capacitive changes at conductor of transmission line due to corona. This model has been incorporated into the Alternative Transients Program version of the Electromagnetic Transients Program (ATP/EMTP) as a user defined component, using the MODELS interface with NORTON TYPE94 of this program and using the foreign subroutine. For obtained the displacement of corona charge hell, dichotomy mathematical method is used for this computation. The present corona model can be used for computing of distortion and attenuation of transient overvoltage waves being propagated in a transmission line of the very high voltage electric power.

Keywords: high voltage, corona, Type94 NORTON, dichotomy, ATP/EMTP, MODELS, distortion, foreign model

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Authors: M. Hijazi, A. Zeki, A. Ismail

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An enormous amount of valuable human knowledge is preserved in documents. The rapid growth in the number of machine-readable documents for public or private access requires the use of automatic text classification. Text classification can be defined as assigning or structuring documents into a defined set of classes known in advance. Arabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information written in the Arabic language on the web. This paper presents a review on the published researches of Arabic Text Classification using classical data representation, Bag of words (BoW), and using conceptual data representation based on semantic resources such as Arabic WordNet and Wikipedia.

Keywords: Arabic text classification, Arabic WordNet, bag of words, conceptual representation, semantic relations

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Authors: Billy Zou

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Statement of the Problem: The burden of mental illness and problem behaviors in adolescence has risen worldwide. While less than 50% of teens have access to traditional mental health care, more than 73% have smartphones. Internet-based interventions offer advantages such as cost-effectiveness, availability, and flexibility. Methodology & Theoretical Orientation: A literature review was done using a PubMed search with the words mental health app yielding 2113 results. 103 articles that met inclusion criteria were reviewed, and findings were then described and synthesized. Findings: 1. Computer-based CBT was found to be effective for OCD, depression, social phobia, and panic disorder. 2. Web-based psychoeducation reduced problem behavior and improved parental well-being. 3. There is limited evidence for mobile-phone-based apps, but preliminary results suggest computer-based interventions are transferrable to mobile apps. 4. Adherence to app-based treatment was correlated with impressions about the user interface Conclusion & Significance: There is evidence for the effectiveness of computer-based programs in filling the significant gaps that currently exist in mental health delivery in the United States and internationally. There is also potential and theoretical validity for mobile-based apps to do the same, though more data is needed.

Keywords: children's mental health, mental health app, child and adolecent psychiatry, digital therapy

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, Bayesian, echocardiographic image, feature vector

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Authors: Nawab Yousuf Ali, S. Golam, A. Ameer, Ashok Toru Roy

Abstract:

This paper develops new morphological rules suitable for Bangla repetition words to be incorporated into an inter lingua representation called Universal Networking Language (UNL). The proposed rules are to be used to combine verb roots and their inflexions to produce words which are then combined with other similar types of words to generate repetition words. This paper outlines the format of morphological rules for different types of repetition words that come from verb roots based on the framework of UNL provided by the UNL centre of the Universal Networking Digital Language (UNDL) foundation.

Keywords: Universal Networking Language (UNL), universal word (UW), head word (HW), Bangla-UNL Dictionary, morphological rule, enconverter (EnCo)

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Authors: Manuela Nayantara Jeyaraj

Abstract:

PostgreSQL is an Object-Relational Database Management System (ORDBMS) with an architecture that ensures optimal quality data management. But due to the shading growth of similar ORDBMS, PostgreSQL has not been renowned among the database user community. Despite having its features and in-built functionalities shadowed, PostgreSQL renders a vast range of utilities for data manipulation and hence calling for it to be upheld more among users. But introducing PostgreSQL in order to stimulate its advantageous features among users, mandates endorsing learn-ability as an add-on as the target groups considered consist of both amateur as well as professional PostgreSQL users. The scope of this paper deliberates providing easy contemplation of query formulations and flows through a visual editor designed according to user interface principles that standby to support every aspect of making PostgreSQL learn-able by self-operation and creation of queries within the visual editor. This paper tends to scrutinize the importance of choosing PostgreSQL as the working database environment, the visual perspectives that influence human behaviour and ultimately learning, the modes in which learn-ability can be provided via visualization and the advantages reaped by the implementation of the proposed system features.

Keywords: database, learn-ability, PostgreSQL, query, visual-editor

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Authors: Dmitry Fedoseyev

Abstract:

The ultimate success of unmanned aerial vehicles (UAVs) depends largely on the effective control of their flight, especially in variable wind conditions. This paper investigates different approaches to selecting the optimal flight level to maximize the range of UAVs. We propose to consider methods based on mathematical models of atmospheric conditions, as well as the use of sensor data and machine learning algorithms to automatically optimize the flight level in real-time. The proposed approaches promise to improve the efficiency and range of UAVs in various wind conditions, which may have significant implications for the application of these systems in various fields, including geodesy, environmental surveillance, and search and rescue operations.

Keywords: drone, UAV, flight trajectory, wind-searching, efficiency

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Authors: Roland Tolulope Loto, Cleophas Akintoye Loto, Abimbola Patricia Popoola

Abstract:

The inhibiting action of 2-dimethylamine on the electrochemical behaviour of austenitic stainless steel (type 304) in dilute hydrochloric was evaluated through weight-loss method, open circuit potential measurement and potentiodynamic polarization tests at specific concentrations of the organic compound. Results obtained reveal that the compound performed effectively giving a maximum inhibition efficiency of 79% at 12.5% concentration from weight loss analysis and 80.9% at 12.5% concentration from polarization tests. The average corrosion potential of -321 mV was obtained the same concentration from other tests which is well within passivation potentials on the steel thus, providing good protection against corrosion in the acid solutions. 2-dimethylamine acted through physiochemical interaction at the steel/solution interface from thermodynamic calculations and obeyed the Langmuir adsorption isotherm. The values of the inhibition efficiency determined from the three methods are in reasonably good agreement. Polarization studies showed that the compounds behaved as cathodic type inhibitor.

Keywords: corrosion, 2-dimethylamine, inhibition, adsorption, hydrochloric acid, steel

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