Search results for: robust diagnosis

Authors: Dr. Muhammad Idris Idris, Dr. Said Saeed Saeed

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Terrorism is the chronic issue of the hour. It is the disciplined practice of vicious activities like assassinating, slaughtering, mutilating, and frightening of the innocents to attain religious, fiscal, and political goals and to question the authority of the government. Leaders of the world promised to transform the planet by empowering community members and building community resilience (CR) against terrorism. This study concentrates to explore building community resilience against terrorism and empowering community members and implement strategies for strengthening community resilience. For data collection a mixed methods methodology will be used. Means, STD deviation, Pearson correlation, and thematic analysis will be employed to analyze the gathered data. The findings of the study will be interpreted and recommendations will be furnished accordingly. Study results will be disseminated to all concerned through conferences and seminar sessions. It is predicted that after the completion, the project team will be in a robust position to start writing the report that concentrates on strengthening community resilience, which is the crucial goal of this project. The publication will contribute effectively to all stakeholders and society, particularly to the lower rungs of social order. Moreover, it is expected that this project will contribute to future research in the domain of community resilience. This project will also reveal the remarkable potential of archival research on community resilience.

Keywords: Violent Extremism, community Role, community resilience, community empowerment, Leadership role

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Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Sittipong Jarernprasert, Enrique Bazan-Zurita, Paul C. Rizzo

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Currently, seismic probabilistic risk assessments (SPRA) for nuclear facilities use In-Structure Response Spectra (ISRS) in the calculation of fragilities for systems and components. ISRS are calculated via dynamic analyses of the host building subjected to two orthogonal components of horizontal ground motion. Each component is defined as the median motion in any horizontal direction. Structural engineers applied the components along selected X and Y Cartesian axes. The ISRS at different locations in the building are also calculated in the X and Y directions. The choice of the directions of X and Y are not specified by the ground motion model with respect to geographic coordinates, and are rather arbitrarily selected by the structural engineer. Normally, X and Y coincide with the “principal” axes of the building, in the understanding that this practice is generally conservative. For SPRA purposes, however, it is desirable to remove any conservatism in the estimates of median ISRS. This paper examines the effects of the direction of horizontal seismic motion on the ISRS on typical nuclear structure. We also evaluate the variability of ISRS calculated along different horizontal directions. Our results indicate that some central measures of the ISRS provide robust estimates that are practically independent of the selection of the directions of the horizontal Cartesian axes.

Keywords: seismic, directionality, in-structure response spectra, probabilistic risk assessment

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Authors: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

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The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

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Authors: Jonathan A. Mikhail, Arsenio Paez

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It is not uncommon for a viral infection to cause hearing loss. Many viral infections are associated with sudden-onset, often unilateral, idiopathic sensorineural hearing loss. We conducted an exploratory study with thirty patients with pre-existing hearing loss between 50 and 64 to evaluate if COVID-19 was associated with exacerbated hearing loss. We hypothesized that hearing loss would be exacerbated by COVID-19 infection in patients with pre-existing hearing loss. A statistically significant paired T-test between pure tone averages (PTAs) at the patient’s original diagnosis and a current, updated audiometric assessment indicated a regression in hearing (p-value < .001) sensitivity following the contraction of COVID-19. Speech reception thresholds (SRTs) and word recognition scores (WRSs) were also considered, as well as the participants' gender. SRTs between each ear exhibited a statistically significant change (p-value of .002 and p-value < .001). WRSs did not show statistically significant differences (p-value of .290 and p-value of .098). A non-statistically significant Two-Way ANOVA was performed to evaluate gender’s potential role in exacerbated hearing loss and proved to be statistically insignificant (p-value of .214). This study discusses practical implications for clinical and educational pursuits in understanding COVID-19's effect on the auditory system and the need to evaluate the deadly virus further.

Keywords: audiology, COVID-19, sensorineural hearing loss, otology, auditory research

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Authors: Sweta Das

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This case report is a 15-year-old male who presented with painless unilateral vision loss from left optic nerve compression due to juvenile nasopharyngeal angiofibroma. JNA is a rare, benign neoplasm that causes intracranial and intraorbital bone destruction and extends aggressively into surrounding soft tissues. It accounts for <1% of all head and neck tumors, is predominantly found in pediatric males and tends to affect indigenous population disproportionately. The most common presenting symptom for JNA is epistaxis and nasal obstruction. However, it can invade orbit, chiasm and pituitary gland, causing loss of vision and field. Visual acuity and function near normalized following surgical excision. Optometry plays an important role in the diagnosis and co-management of JNA with optic nerve compression by closely monitoring afferent optic nerve function and structure, and extraocular motility. Visual function and acuity in patients with short-term compressive neuropathy may drastically improve following surgical resection as this case demonstrates.

Keywords: orbital mass, painless monocular vision loss, compressive optic neuropathy, pediatric tumor

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Authors: Huma Naqeeb

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Epidemiological studies have shown the robust link between breast cancer and dietary pattern. There has been no previous study conducted in Pakistan, which specifically focuses on dietary patterns among breast cancer women. This study aims to examine the association of breast cancer with dietary patterns among Pakistani women. This case-control research was carried in multiple tertiary care facilities. Newly diagnosed primary breast cancer patients were recruited as cases (n = 408); age matched controls (n = 408) were randomly selected from the general population. Data on required parameters were systematically collected using subjective and objective tools. Factor and Principal Component Analysis (PCA) techniques were used to extract women’s dietary patterns. Four dietary patterns were identified based on eigenvalue >1; (i) veg-ovo-fish, (ii) meat-fat-sweet, (iii) mix (milk and its products, and gourds vegetables) and (iv) lentils - spices. Results of the multiple regressions were displayed as adjusted odds ratio (Adj. OR) and their respective confidence intervals (95% CI). After adjusted for potential confounders, veg-ovo-fish dietary pattern was found to be robustly associated with a lower risk of breast cancer among women (Adj. OR: 0.68, 95%CI: (0.46-0.99, p<0.01). The study findings concluded that attachment to the diets majorly composed of fresh vegetables, and high quality protein sources may contribute in lowering the risk of breast cancer among women.

Keywords: breast cancer, dietary pattern, women, principal component analysis

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Authors: Harry Aginta

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Using Phillips curve framework, this paper seeks for new empirical evidence on the relationship between inflation and output in a major emerging economy. By exploiting sub-national data, the contribution of this paper is threefold. First, it resolves the issue of using on-target national inflation rates that potentially causes weakening inflation-output nexus. This is very relevant for Indonesia as its central bank has been adopting inflation targeting framework based on national consumer price index (CPI) inflation. Second, the study tests the relevance of mining sector in output gap estimation. The test for mining sector is important to control for the effects of mining regulation and nominal effects of coal prices on real economic activities. Third, the paper applies panel econometric method by incorporating regional variation that help to improve model estimation. The results from this paper confirm the strong presence of Phillips curve in Indonesia. Positive output gap that reflects excess demand condition gives rise to the inflation rates. In addition, the elasticity of output gap is higher if the mining sector is excluded from output gap estimation. In addition to inflation adaptation, the dynamics of exchange rate and international commodity price are also found to affect inflation significantly. The results are robust to the alternative measurement of output gap

Keywords: Phillips curve, inflation, Indonesia, panel data

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Authors: Carlos David Carrillo Trujillo, Rebelín Echeverría Echeverría, Nancy Evia Alamilla, Rocío Quintal López

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Gender as a social construct is a term now widely studied. Within the social sciences it has become very important. In this sense, psychology tries to make some contributions from your area. The intention is to promote equal opportunities for men and women. Social, employment and educational inequities perpetuate sexism, violence and other important social problems in Mexico. The gender perspective is conceptualized as a tool to promote laws, policies, plans, programs and procedures where women are made ​​visible and empowered. The aim of this is the pursuit of equality. Thus, gender mainstreaming is one of the main challenges of education in Mexico. Only a few universities have programs, research or subjects related to the topic. Human resources, and time allocated to teachers are identified as obstacles to the institutionalization of gender. The objective was to make a diagnosis on course offerings and policies on gender. A documentary study and interviews with managers of at least 20 higher education institutions (IES's) were performed. The results indicate the need for greater gender courses, research projects and intervention. The need to promote policies that seek equal opportunities between men and women is also noted.

Keywords: gender mainstreaming, institutionalization, universities, intervention

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Authors: Ana M. Korol, Bibiana Riquelme, Osvaldo A. Rosso

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Since erythrocyte deformability analysis is mostly qualitative, the development of quantitative nonlinear methods is crucial for restricting subjectivity in the study of cell behaviour. An electro-optic mechanic system called erythrodeformeter has been developed and constructed in our laboratory in order to evaluate the erythrocytes' viscoelasticity. A numerical method formulated on the basis of fractal approximation for ordinary (OBM) and fractionary Brownian motion (FBM), as well as wavelet transform analysis, are proposed to distinguish chaos from noise based on the assumption that diffractometric data involves both deterministic and stochastic components, so it could be modelled as a system of bounded correlated random walk. Here we report studies on 25 donors: 4 alpha thalassaemic patients, 11 beta thalassaemic patients, and 10 healthy controls non-alcoholic and non-smoker individuals. The Correlation Coefficient, a nonlinear parameter, showed evidence of the changes in the erythrocyte deformability; the Wavelet Entropy could quantify those differences which are detected by the light diffraction patterns. Such quantifiers allow a good deal of promise and the possibility of a better understanding of the rheological erythrocytes aspects and also could help in clinical diagnosis.

Keywords: red blood cells, deformability, nonlinear dynamics, chaos theory, wavelet trannsform

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Authors: Sarah A. Goodchild, Rachel Gao, Philip N. Bartlett

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A novel detection approach using immobilized DNA probes labeled with Anthraquinone (AQ) as an electrochemically active reporter moiety has been successfully developed as a new, simple, reliable method for the detection of DNA. This method represents a step forward in DNA detection as it can discriminate between multiple nucleotide polymorphisms within target DNA strands without the need for any additional reagents, reporters or processes such as melting of DNA strands. The detection approach utilizes single-stranded DNA probes immobilized on gold surfaces labeled at the distal terminus with AQ. The effective immobilization has been monitored using techniques such as AC impedance and Raman spectroscopy. Simple voltammetry techniques (Differential Pulse Voltammetry, Cyclic Voltammetry) are then used to monitor the reduction potential of the AQ before and after the addition of complementary strand of target DNA. A reliable relationship between the shift in reduction potential and the number of base pair mismatch has been established and can be used to discriminate between DNA from highly related pathogenic organisms of clinical importance. This indicates that this approach may have great potential to be exploited within biosensor kits for detection and diagnosis of pathogenic organisms in Point of Care devices.

Keywords: Anthraquinone, discrimination, DNA detection, electrochemical biosensor

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Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

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Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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Authors: Seyedmilad Kazemisangdehi, Seyedmehdi Kazemisangdehi

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Flux switching permanent magnet machines are considered for wide range of applications because of their outstanding merits including high torque/power densities, high efficiency, simple and robust rotor structure. Therefore, several topologies have been proposed like the PM exited flux switching machine, hybrid excited flux switching type, and so on. Recently, a novel laminated segmented rotor flux switching permanent magnet machine was introduced. It features flux barriers on rotor structure to enhance the performances of machine including torque ripple reduction and also torque and efficiency improvements at the same time. This is while, the design of barriers was not optimized by the authors. Therefore, in this paper three coefficients regarding the position of the barriers are considered for optimization. The effect of each coefficient on the performance of this machine is investigated by finite element method and finally an optimized design of flux barriers based on these three coefficients is proposed from different points of view including electromagnetic torque maximization and cogging torque/torque ripple minimization. At optimum design from maximum developed torque aspect, this machine generates 0.65 Nm torque higher than that of the not-optimized design with an almost 0.4 % improvement in efficiency.

Keywords: finite element analysis, FSPM, laminated segmented rotor flux switching permanent magnet machine, optimization

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Authors: Tasir Khan, Yejuan Wan, Kalim Ullah

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Hydrological frequency analysis has been conducted to estimate the minimum flow elevation of the Indus River in Pakistan to protect the ecosystem. The Maximum likelihood estimation (MLE) technique is used to estimate the best-fitted distribution for Minimum Ecological Flows at nine stations of the Indus River in Pakistan. The four selected distributions, Generalized Extreme Value (GEV) distribution, Generalized Logistics (GLO) distribution, Generalized Pareto (GPA) distribution, and Pearson type 3 (PE3) are fitted in all sites, usually used in hydro frequency analysis. Compare the performance of these distributions by using the goodness of fit tests, such as the Kolmogorov Smirnov test, Anderson darling test, and chi-square test. The study concludes that the Maximum Likelihood Estimation (MLE) method recommended that GEV and GPA are the most suitable distributions which can be effectively applied to all the proposed sites. The quantiles are estimated for the return periods from 5 to 1000 years by using MLE, estimations methods. The MLE is the robust method for larger sample sizes. The results of these analyses can be used for water resources research, including water quality management, designing irrigation systems, determining downstream flow requirements for hydropower, and the impact of long-term drought on the country's aquatic system.

Keywords: minimum ecological flow, frequency distribution, indus river, maximum likelihood estimation

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Authors: Kathy Mwende Kiema, Remember Samu, Murat Fahrioglu

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The potential of power generation from solar resources has been established as being robust in sub Saharan Africa. Consequently many governments in the region have encouraged the exploitation of this resource through, inter alia direct funding, subsidies and legislation (such as feed in tariffs). Through a case study of Kenya and Zimbabwe it is illustrated that a good deal of proposed grid connected solar power projects and related feed in tariffs have failed to take into account key economic and technical considerations in the selection of solar technologies to be implemented. This paper therefore presents a comparison between concentrated solar power (CSP) and solar photovoltaic (PV) to assess which technology is better suited to meet the energy demand for a given set of prevailing conditions. The evaluation criteria employed is levelized cost of electricity (LCOE), net present value (NPV) and plant capacity factor. The outcome is therefore a guide to aid policy makers and project developers in choosing between CSP and PV given certain solar irradiance values, planned nominal plant capacity, availability of water resource and a consideration of whether or not the power plant is intended to compete with existing technologies, primarily fossil fuel powered, in meeting the peak load.load.

Keywords: capacity factor, peak load, solar PV, solar CSP

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Authors: Ezechi Onyerionwu

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If there is a modern world literary culture that has so tremendously patronized the tragic mode, it has to be that of Africa, and this has been largely true to the extent that the African socio-historical process has been given strong projection by its literature and other art forms. From the three-century-long transatlantic slave trade which brutally translocated millions of Africans to the ‘outermost parts of the earth’, to the vicious partitioning of Africa among European powers and the subsequent imposition of colonial authority on a pulverized people, Africa has really been at the receiving end of the big negatives of global transactions. The African tale has largely been one long tragic narrative. However, the postcolonial African tragic saga has presented an interesting variety of forms and approaches, which have seen to the production of some of the most thought-provoking and acclaimed African novels of the late 20th and early 21st century. Some of the defining characteristics of the African tragic prose has been: the exploration of the many neocolonial implications of the African contemporary existence; the significance of the robust interplay between the essentially foreign, and the originally indigenous elements of the modern African society; and the implosive aftermaths of the individual modern African’s attempt to rationalize his position at the centre of a very complex society. Obioma’s incredible novel, The Fishermen, is in many ways, a classic of the African postcolonial narrative tragedy. The reasons for this bold categorization would occupy the present paper.

Keywords: African narrative tragedy, neocolonialism, postcolonial literature, twenty first century African literature

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Authors: Bruce G. Wilson

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The collection of municipal solid waste at the curbside is a complex operation that is repeated daily under varying circumstances around the world. There have been several attempts to develop Monte Carlo simulation models of the waste collection process dating back almost 50 years. Despite this long history, the use of simulation modeling as a planning or optimization tool for waste collection is still extremely limited in practice. Historically, simulation modeling of waste collection systems has been hampered by the limitations of computer hardware and software and by the availability of representative input data. This paper outlines the development of a Monte Carlo simulation model that overcomes many of the limitations contained in previous models. The model uses a general purpose simulation software program that is easily capable of modeling an entire waste collection network. The model treats the stops on a waste collection route as a queue of work to be processed by a collection vehicle (or server). Input data can be collected from a variety of sources including municipal geographic information systems, global positioning system recorders on collection vehicles, and weigh scales at transfer stations or treatment facilities. The result is a flexible model that is sufficiently robust that it can model the collection activities in a large municipality, while providing the flexibility to adapt to changing conditions on the collection route.

Keywords: modeling, queues, residential waste collection, Monte Carlo simulation

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Authors: ELdessouky Sheta, Sayed Elzomor, Haithem Farghali, Kawkab A. Ahmed, Naglaa A. Abd Elkader

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The present investigation has been dealt with Spirocerca (S.) lupi infested mongrel dogs. This parasitic disease is highly infective to human beings and carnivores. The diagnosis march has been comprised the lateral contrast thoracic radiographs, fecal examination, blood profile, endoscopic examination and histopathological sections of deep seated pinch biopsies. These infested dogs have been put under an adopted treatment with Ivermectin injection combined with oral prednisolone. The obtained results reveal an absence of the pessimistic recognitions particularly after 3 weeks from the onset of treatment. Endoscopically the presented esophageal nodules are marked out in the distal third of infested dogs' esophagus as masses assigned into the esophageal lumen and fundus of stomach. The endoscopic outlook of Spirocerca lupi lesions has been considered an integral procedure of the diagnostic march and for evaluation of treatment follow up. The diagnostic procedures and the recommended treatment are the vet's guidance to care for Spirocerca lupi in dogs, hoping in future to prevent this disease from being spread among human beings and other carnivores.

Keywords: endoscopy, esophagus, stomach spirocercosis, dogs

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Authors: Fadwa Alhalaiqa, Othman Alfuqaha, Anas H. Khalifeh, Mahmoud Alsaraireh, Rami Masa’Deh, Natija S Manaa

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Background: Post-traumatic stress disorders (PTSD) usually occur after traumatic occurrences that exceed the range of common human experience. This study aimed to test the psychometric properties of PCL-5 checklist for the 20 PTSD symptoms from DSM-5 among Lebanese population and to identify the prevalence of PTSD. Methods: A cross sectional survey of PCL5 among 950 Lebanese using the online survey platform by Google form was conducted. Snowball recruitment was used to identify participants for the survey. STROBE guideline was used in reporting the current study. Results: Face content, construct, discriminant, and convergent validity had been accomplished of PCL-5. The reliability by Cronbach alpha, composite, and average variance extracted were set superior. We found also that more than half of the participants (55.6%) scored 33 or above, which is the cutoff score for a likely diagnosis of PTSD. Conclusion: The current study provides further support for the Arabic version PCL-5 validity and reliability among non-Western populations. This support using this tool in the screening of PTSD.

Keywords: post traumatic stress disorder, psychometric properties, stress, adult population

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Martin A. Curry

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Madeline Island is a small island community in Wisconsin, USA. Located in Lake Superior, it has been home to the Anishinaabe/Ojibway people for 1000s of years and is known as Moningwankuaning Minis-"The Island of the Golden Breasted Woodpecker". The community relies on summer tourism as its source of income, with a small population of 400 year-round residents. Supervisor Martin A. Curry (Ojibway/German descent) has been working on a fiscally responsible, environmentally principled and culturally centered approach to waste diversion and recycling. The tenets of this program encompass plastics, paper, food waste, local farming, energy production and art education. Through creative writing for the local newspaper and creative interactions, Martin has worked to engage the community in a more robust interest in waste diversion, including setting up a free-will donation store that incorporates elder volunteering opportunities, a compost program that works with the local community garden, biodiesel production and an art program that works with children from the local island school to make paper, grow local food and paint murals. The entirety of this program is based on the Ojibway concept of Mino-Bimadiiziwiin- "The Good Life" and benefits the community and its guests and represents a microcosm of the global dilemmas of waste and recycling.

Keywords: recycling, waste diversion, island, Native American, art

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Authors: Shubhangi Salokhe

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Agriculture encompasses crop and livestock production, forestry, and fisheries for food and non-food products. Farmers combine land, water, commercial inputs, labor, and their management skills into practices and systems that produce food and fibre. Harvesting of agricultural produce is either followed by the processing of fresh produce or storage for later consumption. All these activities result in a vast generation of waste in terms of crop residue or food waste. So, a large amount of agricultural waste is produced every year. Waste arising from food and agricultural sectors has the potential for vast applications. So, agricultural waste management is an essential component of sustainable agriculture. The major portion of the waste comes from the residues of crops on farms, food processing, livestock, aquaculture, and agro-industry waste. Therefore, management of these agricultural wastes is an important task, and it requires robust strategic planning. It can contribute to three pillars of sustainable agriculture development. It protects the environment (environmental pillar), enhances the livelihoods of farmers (economic pillar), and can contribute to increasing the sustainability of the agricultural sector (social pillar). This paper addresses the essential technological aspects, possible solutions, and sound policy concerns to accomplish long-term way out of agriculture waste management and to minimize the negative impact of waste on the environment. The author has developed a sustainable agriculture waste management model for improving the sustainability of agriculture.

Keywords: agriculture, development, management, waste

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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Authors: Fakhr Eddin Alnaal, Angela Dahdal, Duaa Aladib, Sabeen Ibrahim, Ibrahim Ghoraibi, Bissan Ahmed

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Dementia is one of the diseases which had several stages and Alzheimer’s term was selected in respect for the first doctor Alzheimer who defined the first symptoms of this diseases in a woman whom was well treated by him. The fact that this is a type of a silent disease on which you have a long-term process of neurological degradation and suddenly gives symptoms which are most often irreversible, on clinical level likely we can consider it as a malignancy, one in terms of that it is sudden shocking irreversible and on the level of behavior and some mortality beside the lack of early detection tools for diagnosis. Therefore, the goal of our project is to test the concept of the ability of Statin in prevention of such disease and we investigated that both on experimental level and most importantly on clinical one, the clinical part was performed in a recognized house of aged people who had accidently a high cholesterol and were for years given Statin to treat that elevation, however after the symptoms of Alzheimer’s appeared and when diagnosed, they were well treated and rapidly recovered compared to Alzheimer’s patients in the same house who did not receive Statin had a mild improvement in their symptoms after the therapy, on the other hand we confirmed such observation by a well-organized experimental work.

Keywords: Alzheimer's, dementia, silent disease, statin

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Authors: Dian Ariyawati, Romi Sukoco, Sinung Agung Joko

Abstract:

Background: Postural Orthostatic Tachycardia Syndrome (POTS) is a form of orthostatic intolerance caused by autonomic dysfunction. POTS predominantly occurs in young women. Regular exercise has proven to improve the organ system functions, including autonomous systems. The aim of this research was to determine the correlation between exercise frequency and POTS in young women. Method: 510 young women (16-23 years of age) were screened. They were obtained by interview and physical examination. The diagnosis of POTS was performed with Active Stand Test (AST) and heart rate measurement using a pulsemeter. There were 29 young women who suffered from POTS. The exercise frequency was obtained by interview. Data was statistically analyzed using Spearman Correlation test. Result: The subjects’, who tested positive for POTS didn’t perform regular exercise. The Spearman correlation test showed there was a moderate negative correlation between exercise frequency and POTS in young women (r = -0.487, p < 0.00). Conclusion: There is a moderate reverse correlation between exercise frequency and POTS in young women. Further studies are suggested to develop an exercise program for young who suffered from POTS.

Keywords: POTS, autonomic dysfunction, exercise frequency, young woman

Procedia PDF Downloads 556

Authors: Dennis L. Owuor, Okuthe P. Kogeda, Johnson I. Agbinya

Abstract:

Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.

Keywords: indoor localization, digital forensics, fingerprinting, tracking and cloud

Procedia PDF Downloads 337

Authors: Mabrouka Immhemd Al-Werfalli

Abstract:

How are political alienation and corruption related? What is the nature of relationship linking corruption and political alienation? When citizens withdraw their loyalty from their political regime and leaders, they highlight their alienation from them. The link between corruption and political alienation is that the individual would intentionally involve in corruption particularly when a state of lawlessness prevails. This paper represents a challenge- how to gauge a link between political alienation culture of corruption and corruption. It aims to highlight the political alienation related factors that determine the levels of corruption in Libya. One of the most prominent reasons for the Libyan uprising in February 2011 was the pervasiveness of corruption. Corruption in Libya remained a significant problem despite a robust anti-corruption discourse and harsh legislation undertaken by the previous regime. The long-standing political corruption in Libya has offered ample opportunity for the evolution of a structure of negative values and morals. This has formed what is termed as a ‘culture of corruption’, which has induced people to accept and justify corrupt behavior. The paper is a part of a study concerns the phenomenon of political alienation in Libya which was based on a survey conducted in 2001 in the city of Benghazi. The finding shows that abuse of power, embezzlement and misuse of public funds for personal enrichment was thought to be rife within public bodies, institutions, companies, factories, banks and enterprises owned entirely or partially by the state.

Keywords: Libya, abuse of power, anti-corruption, corruption, culture of corruption, embezzlement, participation in corruption, political alienation

Procedia PDF Downloads 313

Authors: Maryam Hashemi, Nematollah Razmi, Rasool Madani

Abstract:

M. paratuberculosis is a slow growing mycobactin dependent mycobacterial species known to be the causative agent of Johne’s disease in all species of domestic ruminants worldwide. JD is characterized by gradual weight loss; decreased milk production. Excretion of the organism may occur for prolonged periods (1 to 2.5 years) before the onset of clinical disease. In recent years, researchers focus on identification a specific antigen of MAP to use in diagnosis test and preparation of effective vaccine. In this paper, for production of polyclonal antibody against proteins of Mycobacterium avium paratuberculosis cell wall a rabbit immunization at a certain time period with antigen. After immunization of the animal, blood samples were collected from the rabbit for producing enriched serum. Antibodies were purified with ion exchange chromatography. For exact measurement of interaction, western blotting test was used and as it is demonstrated in the study, sharp bands appear in nitrocellulose paper and specific bands were 50 and 150 KD molecular weight. These were indicating immunodominant proteins.

Keywords: immunodominant, paratuberculosis, Western blotting, cell wall proteins, protein purification

Procedia PDF Downloads 254