Search results for: Infectious disease spread

Authors: Haowei Chen, Kaiqi Xiong

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We have developed a better model for understanding the dynamics of malware spread in WMNs in this paper. The suggested model provides an insight into how viral propagation with energy exhaustion and various dispersed node densities might function. Based on a theoretical examination of the suggested model, we conclude that the threshold parameter could be used to identify the dynamics of viral spread globally. When the threshold is less than 1, the virus may be contained, but if it is greater than 1, a pandemic may result. Lastly, we discuss the various viral propagation strategies in relation to the distributed node densities and communication radii in WMNs. The aforementioned numerical simulation findings could serve as a guarantee of the theoretical analyses’ correctness.

Keywords: Bluetooth Security, Malware Propagation, Wireless Mesh Networks, Stability Analysis.

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Authors: Kasra Afsahi, Maryam Soheilifar

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Cerebrovascular accident (CVA) is a neurological side effect of COVID-19 disease wit high rate in pandemics. Effect of COVID-19 disease on disorder is unclear. In this cohort, patients with COVID-19 disease were assessed. 60 CVA cases were assessed in a referral hospital in 2020. The major factor was mortality and the cases were those with and without death. The groups were compared for all features about mortality in the patients with COVID-19 and CVA. Totally 23 out of 60 cases (38.3%) were expired. In univariate analysis there was significant association for death by ischemic heart disease (P = 0.015), high-severity stroke (P = 0.012), high C-reactive protein (CRP) (P = 0.001), high ESR (P = 0.009), pleural effusion (P = 0.005), pericardial effusion (P = 0.027), cardiomegaly (P = 0.005), ground glass opacity (P = 0.001), and consolidation (P = 0.001). Among these factors, there was significant association only for CRP (P = 0.001) and consolidation (P = 0.003) in multivariate analysis. Mortality in the cases with COVID-19-related CVA is one-third and it has relationship to elevated CRP and finding the consolidation in the computerized tomography scan of the lungs.

Keywords: COVID-19, stroke, prognosis, C-reactive protein, CRP.

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Authors: H. N. Agiza, M. A. Sohaly, M. A. Elfouly

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Parkinson's disease (PD) is a heterogeneous disorder with common age of onset, symptoms, and progression levels. In this paper we will solve analytically the PD model as a non-linear delay differential equation using the steps method. The step method transforms a system of delay differential equations (DDEs) into systems of ordinary differential equations (ODEs). On some numerical examples, the analytical solution will be difficult. So we will approximate the analytical solution using Picard method and Taylor method to ODEs.

Keywords: Parkinson's disease, Step method, delay differential equation, simulation.

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Authors: Jiří Barta

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The paper deals with simulation programs of spread of harmful substances. Air pollution has a direct impact on the quality of human life and environmental protection is currently a very hot topic. Therefore, the paper focuses on the simulation of release of harmful substances. The first part of article deals with perspectives and possibilities of implementation outputs of simulations programs into the system which is education and of practical training of the management staff during emergency events in the frame of critical infrastructure. The last part shows the practical testing and evaluation of simulation programs. Of the tested simulations software been selected Symos97. The tool offers advanced features for setting leakage. Gradually allows the user to model the terrain, location, and method of escape of harmful substances.

Keywords: Computer Simulation, Symos97, spread, simulation software, harmful substances.

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Authors: Jong-won Lee

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Since Cloud environment has appeared as the most powerful keyword in the computing industry, the growth in VDI (Virtual Desktop Infrastructure) became remarkable in domestic market. In recent years, with the trend that mobile devices such as smartphones and pads spread so rapidly, the strengths of VDI that allows people to access and perform business on the move along with companies' office needs expedite more rapid spread of VDI. In this paper, mobile OTP (One-Time Password) authentication method is proposed to secure mobile device portability through rapid and secure authentication using mobile devices such as mobile phones or pads, which does not require additional purchase or possession of OTP tokens of users. To facilitate diverse and wide use of Services in the future, service should be continuous and stable, and above all, security should be considered the most important to meet advanced portability and user accessibility, the strengths of VDI.

Keywords: Cloud, VDI, OTP, Mobility

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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Authors: Somorjeet Sharma Shamurailatpam, Rabindra Das, A. Suchitra Devi

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Computer and video display users might complain about Asthenopia, burning, dry eyes etc. The management of dry eyes is often not in the lines of severity. Following systematic evaluation and grading, dry eye disease is one condition that can be practiced at all levels of ophthalmic care. In the present study, different spectrum causing dry eye and prevalence of dry eye disease in computer users of Manipur, India are determined with 600 individuals (300 cases and 300 control). Individuals between 15 and 50 years who used computers for more than 3 hrs a day for 1 year or more were included. Tear break up time (TBUT) and Schirmer’s test were conducted. It shows that 33 (20.4%) out of 164 males and 47 (30.3%) out of 136 females have dry eye. Possible explanation for the observed result is discussed.

Keywords: Asthenopia, computer vision syndrome, dry eyes, Schirmer’s test, tear breakup time.

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Authors: Sri Ratna Rahayu, Oktia Woro Kasmini Handayani, Lourensiana Y. S. Ngaga, Imade Sudana, Irwan Budiono

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Malaria is an infectious disease that still cannot be solved in Kori village, West Nusa Tenggara, Indonesia, where the most of people live in rumah panggung (Stilts House). The purpose of this study was to know whether there were the effects of rumah panggung environment, social culture, and behavior on malaria incidence in the Kori village. A cross-sectional study was performed to explore the effects of rumah panggung environment, social culture and behavior on malaria incidence. This study recruited 280 respondents, who live in the rumah panggung, permanent residents in Kori village, were age above 17 years old, and suffered from malaria in the past year. The collected data were analyzed with path analysis. The results of this study showed that the environment of rumah panggung and behavior have a direct effect on the incidence of malaria (p < 0.05). It could be concluded that improvement of environmental conditions of rumah panggung, sociocultural, and behavioral changes to maintain a healthy environment are needed to reduce the malaria incidence.

Keywords: Rumah panggung, socio cultural, behavior, malaria.

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Authors: Nebi Gedik

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Regardless of age or gender, cardiovascular illnesses are a serious health concern because of things like poor eating habits, stress, a sedentary lifestyle, hard work schedules, alcohol use, and weight. It tends to happen suddenly and has a high rate of recurrence. Machine learning models can be implemented to assist healthcare systems in the accurate detection and diagnosis of cardiovascular disease (CVD) in patients. Improved heart failure prediction is one of the primary goals of researchers using the heart disease dataset. The purpose of this study is to identify the feature or features that offer the best classification prediction for CVD detection. The support vector machine classifier is used to compare each feature's performance. It has been determined which feature produces the best results.

Keywords: Cardiovascular disease, feature extraction, supervised learning, support vector machine.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: Tahsin Toma Sabbagh, Ihsan Al-Abboodi, Ali Al-Jazaairry

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Allowable-bearing capacity is the competency of soil to safely carries the pressure from the superstructure without experiencing a shear failure with accompanying excessive settlements. Ensuring a safe bearing pressure with respect to failure does not tolerate settlement of the foundation will be within acceptable limits. Therefore, settlement analysis should always be performed since most structures are settlement sensitive. When visualising the movement of a soil wedge in the bearing capacity criterion, both vertically and horizontally, it becomes clear that by confining the soil surrounding the foundation, both the bearing capacity and settlement values improve. In this study, two sizes of spread foundation were considered; (2×4) m and (3×5) m. These represent two real problem case studies of an existing building. The foundations were analysed in terms of dimension as well as position with respect to a confining wall (i.e., sheet piles on both sides). Assuming B is the least foundation dimension, the study comprised the analyses of three distances; (0.1 B), (0.5 B), and (0.75 B) between the sheet piles and foundations alongside three depths of confinement (0.5 B), (1 B), and (1.5 B). Nonlinear three-dimensional finite element analysis (ANSYS) was adopted to perform an analytical investigation on the behaviour of the two foundations contained by the case study. Results showed that confinement of foundations reduced the overall stresses near the foundation by 65% and reduced the vertical displacement by 90%. Moreover, the most effective distance between the confinement wall and the foundation was found to be 0.5 B.

Keywords: Bearing capacity, cohesionless soils, spread footings, soil confinement, soil modelling.

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Authors: Hani M. Aburas

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“Dengue" is an African word meaning “bone breaking" because it causes severe joint and muscle pain that feels like bones are breaking. It is an infectious disease mainly transmitted by female mosquito, Aedes aegypti, and causes four serotypes of dengue viruses. In recent years, a dramatic increase in the dengue fever confirmed cases around the equator-s belt has been reported. Several conventional indices have been designed so far to monitor the transmitting vector populations known as House Index (HI), Container Index (CI), Breteau Index (BI). However, none of them describes the adult mosquito population size which is important to direct and guide comprehensive control strategy operations since number of infected people has a direct relationship with the vector density. Therefore, it is crucial to know the population size of the transmitting vector in order to design a suitable and effective control program. In this context, a study is carried out to report a new statistical index, ABURAS Index, using Poisson distribution based on the collection of vector population in Jeddah Governorate, Saudi Arabia.

Keywords: Poisson distribution, statistical index, prediction, Aedes aegypti.

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Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

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The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: Asymptotic stability, incubation period, Routh-Hurwitz criterion, Runge Kutta method.

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Authors: Jae-Yeon Song, Seung-Yerl Lee, Kyu-Yeul Wang, Byung-Soo Kim, Sang-Seol Lee, Seong-Seob Shin, Jae-Young Choi, Chong Ho Lee, Jeahyun Park, Duck-Jin Chung

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In this paper, we propose disease diagnosis hardware architecture by using Hypernetworks technique. It can be used to diagnose 3 different diseases (SPECT Heart, Leukemia, Prostate cancer). Generally, the disparate diseases require specified diagnosis hardware model for each disease. Using similarities of three diseases diagnosis processor, we design diagnosis processor that can diagnose three different diseases. Our proposed architecture that is combining three processors to one processor can reduce hardware size without decrease of the accuracy.

Keywords: Diagnosis processor, Hypernetworks, Leukemia, Mask, Prostate cancer, SPECT Heart data

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Authors: Ali Payan, Bijan Rahmani Parchicolaie

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Universities have different offices such as educational, research, student, administrative, and financial offices. This paper considers universities as groups of decision making units (DMUs) in which DMUs are their offices. This approach gives us with a more just evaluation of universities instead of separate evaluation of the offices of universities. The proposed approach to evaluate group performance of universities is based on common set of weights method in DEA. The suggested method not only can compare groups and measure their efficiencies, but also can calculate the efficiency of units within group and efficiency spread of groups. At last, the suggested method is applied for the analysis of the performance of universities in 14^th district of Islamic Azad University as groups under evaluation.

Keywords: Common set of weights, group efficiency, performance analysis, spread efficiency.

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Authors: Kristýna Pokorná, Petr Teplý

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This paper focuses on sovereign credit risk meaning a hot topic related to the current Eurozone crisis. In the light of the recent financial crisis, market perception of the creditworthiness of individual sovereigns has changed significantly. Before the outbreak of the financial crisis, market participants did not differentiate between credit risk born by individual states despite different levels of public indebtedness. In the proceeding of the financial crisis, the market participants became aware of the worsening fiscal situation in the European countries and started to discriminate among government issuers. Concerns about the increasing sovereign risk were reflected in surging sovereign risk premium. The main of this paper is to shed light on the characteristics of the sovereign risk with the special attention paid to the mutual relation between credit spread and the CDS premium as the main measures of the sovereign risk premium.

Keywords: cointegration, credit default swap, credit risk, credit spread, sovereign risk

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Authors: M. A. Sohaly, M. A. Elfouly

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Parkinson's disease (PD) is a heterogeneous movement disorder that often appears in the elderly. PD is induced by a loss of dopamine secretion. Some drugs increase the secretion of dopamine. In this paper, we will simply study the stability of PD models as a nonlinear delay differential equation. After a period of taking drugs, these act as positive feedback and increase the tremors of patients, and then, the differential equation has positive coefficients and the system is unstable under these conditions. We will present a set of suggested modifications to make the system more compatible with the biodynamic system. When giving a set of numerical examples, this research paper is concerned with the mathematical analysis, and no clinical data have been used.

Keywords: Parkinson's disease, stability, simulation, two delay differential equation.

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Authors: Minh-Khai Nguyen, Young-Gook Jung, Young-Cheol Lim

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It is known that if harmonic spectra are decreased, then acoustic noise also decreased. Hence, this paper deals with a new random switching strategy using DSP TMS320F2812 to decrease the harmonics spectra of single phase switched reluctance motor. The proposed method which combines random turn-on, turn-off angle technique and random pulse width modulation technique is shown. A harmonic spread factor (HSF) is used to evaluate the random modulation scheme. In order to confirm the effectiveness of the new method, the experimental results show that the harmonic intensity of output voltage for the proposed method is better than that for conventional methods.

Keywords: Single phase switched reluctance motor (SRM), harmonic spread factor (HSF), random switching technique.

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Authors: Sadek Makhlouf, Hassan M. Nouh

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Bone hydatidosis is an infection in worldwide distribution. Although there is no evidence in literature on Bone Hydatid disease in Libya, we tried to present the first Epidemiological study of this disease in Eastern Libya through retrospective study from 1995 to 2013. Our data were collected from 3 hospitals in Eastern Libya particularly the sheep-raising areas with total number of musculoskeletal infection cases of two thousand one hundred ninety four (2,194). There were five (5) five cases of bone infection, four (4) of it have been diagnosed after more than three (3) months.  Our study is comparable to other international study but this type of bone infection need further studies for effective control strategies for all dogs to avoid serious complications that might happened from the delay in diagnosing this type of disease.

Keywords: Bone infection, Hydatidosis, Eastern Libya, Sheep-raising areas.

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Authors: Negar Khezri, Golnaz Yaghoubnezhadzanganeh, Amirreza Attarzadeh

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Type 2 Diabetes (T2DM) and Alzheimer's disease (AD) are two main health problems influencing millions of people in the world. Neuron loss and synaptic impairment that interfere with cognition and memory cause for the behavioral indications of AD. While it is now accepted that insulin has central neuromodulatory purpose, it was contemplated for many years that brain is insusceptible to insulin, involving its function in memory and learning, which are impaired in AD. The common characteristics of both AD and T2D are impaired insulin signaling, oxidative stress, the excitation of inflammatory pathways and unqualified glucose metabolism. This review summarizes how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches. Here we summarize how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches.

Keywords: Alzheimer’s disease, diabetes, insulin resistance, neurodegenerative.

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Authors: Sarah Motiee, Azadeh Nematzadeh, Mehrnoush Shamsfard

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Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques to extract phrases from documents and the query and doing stemming on words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done flexible and in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Mehrnoush Shamsfard, Azadeh Nematzadeh, Sarah Motiee

Abstract:

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: S. Chadsuthi, W. Triampo, C. Modchang, P. Kanthang, D. Triampo, N. Nuttavut

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We present analysis of spatial patterns of generic disease spread simulated by a stochastic long-range correlation SIR model, where individuals can be infected at long distance in a power law distribution. We integrated various tools, namely perimeter, circularity, fractal dimension, and aggregation index to characterize and investigate spatial pattern formations. Our primary goal was to understand for a given model of interest which tool has an advantage over the other and to what extent. We found that perimeter and circularity give information only for a case of strong correlation– while the fractal dimension and aggregation index exhibit the growth rule of pattern formation, depending on the degree of the correlation exponent (β). The aggregation index method used as an alternative method to describe the degree of pathogenic ratio (α). This study may provide a useful approach to characterize and analyze the pattern formation of epidemic spreading

Keywords: spatial pattern epidemics, aggregation index, fractaldimension, stochastic, long-rang epidemics

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Authors: F. May Liou, Y. C. Edwin Tang

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This paper aims to provide a conceptual framework to examine competitive disadvantage of banks that suffer from poor performance. Banks generate revenues mainly from the interest rate spread on taking deposits and making loans while collecting fees in the process. To maximize firm value, banks seek loan growth and expense control while managing risk associated with loans with respect to non-performing borrowers or narrowing interest spread between assets and liabilities. Competitive disadvantage refers to the failure to access imitable resources and to build managing capabilities to gain sustainable return given appropriate risk management. This paper proposes a four-quadrant framework of organizational typology is subsequently proposed to examine the features of competitive disadvantage in the banking sector. A resource configuration model, which is extracted from CAMEL indicators to examine the underlying features of bank failures.

Keywords: Bank failure, CAMEL, competitive disadvantage, resource configuration.

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Authors: Farbod Behnaminia, Saeed Samet

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The COVID-19 pandemic has paralyzed many lives until a vaccine has been available, which caused the so-called "new normal". COVID-19 is an infectious disease. It can cause significant illness or death in anyone. Governments and health officials tried to impose rules and regulations to avoid and slow down transmission. Therefore, software engineers worldwide developed applications to trace and track patients’ movements and notify others, mainly using Bluetooth. In this way, everyone could be informed whether they came in close contact with someone who has COVID-19 and take proper safety precautions. Because most of the applications use technologies that can potentially reveal the user’s identity and location, researchers have debated privacy preservation and how to improve user privacy during such pandemics. We conducted a comprehensive evaluation of the literature by looking for papers in the relevant field and dividing them into pre- and post-pandemic systems. Additionally, we discussed the many uses of blockchain technology in pandemic control. We found that two major obstacles facing blockchain implementation across many healthcare systems are scalability and privacy. The Polkadot platform is presented, along with a review of its efficacy in tackling current concerns. A more scalable healthcare system is achievable in near future using Polkadot as well as a much more privacy-preserving environment.

Keywords: Blockchain, Electronic Record Management, EHR, Privacy-Preserving, patient tracking, COVID-19, trust and confidence, Polkadot.

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Authors: Piyush Samant, Ravinder Agarwal

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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: Complementary and alternative medicine, Iridology, iris, feature extraction, classification, disease prediction.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

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An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: Ashish Dhamaniya, Satish Chandra

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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: Normal distribution, percentile speed, speed spread ratio, traffic volume.

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Authors: Franco Frattolillo

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The advances in multimedia and networking technologies have created opportunities for Internet pirates, who can easily copy multimedia contents and illegally distribute them on the Internet, thus violating the legal rights of content owners. This paper describes how a simple and well-known watermarking procedure based on a spread spectrum method and a watermark recovery by correlation can be improved to effectively and adaptively protect MPEG-2 videos distributed on the Internet. In fact, the procedure, in its simplest form, is vulnerable to a variety of attacks. However, its security and robustness have been increased, and its behavior has been made adaptive with respect to the video terminals used to open the videos and the network transactions carried out to deliver them to buyers. In fact, such an adaptive behavior enables the proposed procedure to efficiently embed watermarks, and this characteristic makes the procedure well suited to be exploited in web contexts, where watermarks usually generated from fingerprinting codes have to be inserted into the distributed videos “on the fly", i.e. during the purchase web transactions.

Keywords: Copyright protection, digital watermarking, intellectualproperty protection.

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Authors: Chanhoe Kang, Changhyun Lee, Seock-Hee Jun, Yeong-Tae Oh

Abstract:

Offshore floating structure under the various environmental conditions maintains a fixed position by mooring system. Environmental conditions, vessel motions and mooring loads are applied to mooring lines as the dynamic tension. Because global responses of mooring system in deep water are specified as wave frequency and low frequency response, they should be calculated from the time-domain analysis due to non-linear dynamic characteristics. To take into account all mooring loads, environmental conditions, added mass and damping terms at each time step, a lot of computation time and capacities are required. Thus, under the premise that reliable fatigue damage could be derived through reasonable analysis method, it is necessary to reduce the analysis cases through the sensitivity studies and appropriate assumptions. In this paper, effects in fatigue are studied for spread mooring system connected with oil FPSO which is positioned in deep water of West Africa offshore. The target FPSO with two Mbbls storage has 16 spread mooring lines (4 bundles x 4 lines). The various sensitivity studies are performed for environmental loads, type of responses, vessel offsets, mooring position, loading conditions and riser behavior. Each parameter applied to the sensitivity studies is investigated from the effects of fatigue damage through fatigue analysis. Based on the sensitivity studies, the following results are presented: Wave loads are more dominant in terms of fatigue than other environment conditions. Wave frequency response causes the higher fatigue damage than low frequency response. The larger vessel offset increases the mean tension and so it results in the increased fatigue damage. The external line of each bundle shows the highest fatigue damage by the governed vessel pitch motion due to swell wave conditions. Among three kinds of loading conditions, ballast condition has the highest fatigue damage due to higher tension. The riser damping occurred by riser behavior tends to reduce the fatigue damage. The various analysis results obtained from these sensitivity studies can be used for a simplified fatigue analysis of spread mooring line as the reference.

Keywords: Mooring system, fatigue analysis, time domain, non-linear dynamic characteristics.

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