Search results for: vaccination rates

Authors: Anouch Mkhitarian

Abstract:

The article examines an opportunity of corruption restriction exercised by international business community in Russia. Integration of Russian economy into the international business does not reduce corruption inside the country. Foreign actors investing in Russia under the condition of obtaining their required rates of returns will be reluctant to harm their investments by involving into anticorruption activities. Furthermore, many Russian firms- competitive advantage could be directly related to their corruption connections. In this case, foreign investments would only accentuate corrupt companies- success by supporting them financially

Keywords: Corrution, FDI, Russian Federation

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Authors: K. Akherfi, H. Harroud

Abstract:

Cloud computing (CC) and mobile cloud computing (MCC) have advanced rapidly the last few years. Today, MCC undergoes fast improvement and progress in terms of hardware (memory, embedded sensors, power consumption, touch screen, etc.) software (more and more sophisticated mobile applications) and transmission (higher data transmission rates achieved with different technologies such as 3Gs). This paper presents a review on the concept of CC and MCC. Then, it discusses what has been done regarding middleware in cloud and mobile cloud computing. Later, it shows the architecture of our proposed middleware along with its functionalities which will be provided to mobile clients in order to overcome the well known problems (such as low battery power, slow CPU speed and little memory…).

Keywords: Context-aware, cloud computing, middleware, mobile cloud.

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Authors: C. Ardil

Abstract:

The COVID-19 pandemic has revealed the complex and multifaceted relationship between societal structures and public health, emphasizing the need for a holistic approach to understanding pandemic responses. This study utilizes a clinical sociological perspective to analyze the social impacts of pandemics, with a particular focus on how social determinants such as income, education, race, and geographical location influence vulnerability and resilience. It explores the critical role of risk perception, communication strategies, and community dynamics in shaping public adherence to precautionary measures like mask-wearing, social distancing, and vaccination. By examining the ways in which social norms, structural inequalities, and trust in institutions affect public behavior, this study provides insights into the challenges of managing health crises in diverse communities. Comparative case studies and policy analysis are employed to highlight the variations in pandemic responses across different countries and regions, illustrating the importance of coordinated strategies and community-based interventions. The findings underscore that effective pandemic response requires addressing underlying social inequities, fostering community cohesion, and ensuring equitable access to healthcare and information. This study contributes to a deeper understanding of the broader societal implications of pandemics and offers recommendations for building more resilient, inclusive public health systems capable of mitigating the impact of future global health emergencies.

Keywords: Behavioral medicine, clinical sociology, community health, COVID-19, COVID-19 pandemic, epidemiology, infectious diseases, pandemics, precautions, psychology, public health, risks, social determinants, social dynamics, social psychiatry, social psychology, socioeconomic status, structural functionalism

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Authors: Megumi Nishida, Naoya Motegi, Takurou Kikuchi, Tomoko Tokumura

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In recent years, the power system has been changed and a flexible power pricing system such as demand response has been sought in Japan. The demand response system works simply in the household sector and the owner as the decision-maker, can benefit from power saving. On the other hand, the execution of demand response in the office building is more complex than in the household because various people such as owners, building administrators and occupants are involved in the decision-making process. While the owners benefit from demand saving, the occupants are exposed to restricted benefits of a demand-saved environment. One of the reasons is that building systems are usually under centralized management and each occupant cannot choose freely whether to participate in demand response or not. In addition, it is unclear whether incentives give occupants the motivation to participate. However, the recent development of IT and building systems enables the personalized control of the office environment where each occupant can control the lighting level or temperature individually. Therefore, it can be possible to have a system which each occupant can make a decision of whether or not to participate in demand response in the office building. This study investigates personal responses to demand response requests, under the condition where each occupant can adjust their brightness individually in their workspace. Once workers participate in the demand response, their desk-lights are automatically turned off. The participation rates in the demand response events are compared among four groups, which are divided by different motivation, the presence, or absence of incentives and the method of participation. The result shows that there are significant differences of participation rates in demand response event between four groups. The method of participation has a large effect on the participation rate. The “Opt-out” groups where the occupants are automatically enrolled in a demand response event if they do not express non-participation have the highest participation rate in the four groups. Incentives also have an effect on the participation rate. This study also reports on the impact of low illumination office environment on the occupants, such as stress or fatigue. The electrocardiogram and the questionnaire are used to investigate the autonomic nervous activity and subjective fatigue symptoms of the occupants. There is no big difference between dim workspace during demand response event and bright workspace in autonomic nervous activity and fatigue.

Keywords: Demand response, illumination, questionnaire, electrocardiograph.

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Authors: Carmen Navarrete, Eloy Anguiano

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In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor,in a nonconcurrent form instead of being executed concurrently ina set of processors working and communicating through a network.This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies.

Keywords: Dynamic network topology, resource and task allocation, parallel computing, heterogeneous computing, dynamic reconfiguration.

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Authors: Abtehal Y. Anaas, Mohd. Nazmi Bin Abd. Manap

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Meat Tenderness is one of the most important factors affecting consumers' assessment of meat quality. Variation in meat tenderness is genetically controlled and varies among breeds, and it is also influenced by environmental factors that can affect its creation during rigor mortis and postmortem. The final postmortem meat tenderization relies on the extent of proteolysis of myofibrillar proteins caused by the endogenous activity of the proteolytic calpain system. This calpain system includes different calcium-dependent cysteine proteases, and an inhibitor, calpastatin. It is widely accepted that in farm animals including chickens, the μ-calpain gene (CAPN1) is a physiological candidate gene for meat tenderness. This study aimed to identify the association of single nucleotide polymorphism (SNP) markers in the CAPN1 gene with the tenderness of chicken breast meat from two Malaysian native and commercial broiler breed crosses. Ten, five months old native chickens and ten, 42 days commercial broilers were collected from the local market and breast muscles were removed two hours after slaughter, packed separately in plastic bags and kept at -20ºC for 24 h. The tenderness phenotype for all chickens’ breast meats was determined by Warner-Bratzler Shear Force (WBSF). Thawing and cooking losses were also measured in the same breast samples before using in WBSF determination. Polymerase chain reaction (PCR) was used to identify the previously reported C7198A and G9950A SNPs in the CAPN1 gene and assess their associations with meat tenderness in the two breeds. The broiler breast meat showed lower shear force values and lower thawing loss rates than the native chickens (p<0.05), whereas there were similar in the rates of cooking loss. The study confirms some previous results that the markers CAPN1 C7198A and G9950A were not significantly associated with the variation in meat tenderness in chickens. Therefore, further study is needed to confirm the functional molecular mechanism of these SNPs and evaluate their associations in different chicken populations.

Keywords: CAPNl, chicken, meat tenderness, meat quality, SNPs.

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Authors: H. El Ayech, A. Trabelsi

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In this article we are going to discuss the improvement of the multi classes- classification problem using multi layer Perceptron. The considered approach consists in breaking down the n-class problem into two-classes- subproblems. The training of each two-class subproblem is made independently; as for the phase of test, we are going to confront a vector that we want to classify to all two classes- models, the elected class will be the strongest one that won-t lose any competition with the other classes. Rates of recognition gotten with the multi class-s approach by two-class-s decomposition are clearly better that those gotten by the simple multi class-s approach.

Keywords: Artificial neural network, letter-recognition, Multi class Classification, Multi Layer Perceptron.

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Authors: Masao Ohta, Yoshiyuki Higuchi

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This study analyses store layout among the many factors that underlie supermarket store design, this; in terms of what to display in a shop and where to place the items. This report examines newly-opened stores and evaluates their interior shop floor layouts, which we then attempt to categorize by various styles. We then consider the interaction between shop floor layout and customer behavior from the perspective of the supermarket as the seller. At this point, we focus on the “store magnets"–the main sections within the shop likely to attract customers into the store.

Keywords: Supermarket Store Layout, Sales magnet, Customer Circulation Rate, Section Drop-by Rates.

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Authors: Noda L. M., Salvador I. C, C. M. L. G. Parada, Fonseca C. R. B.

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In Brazil, neonatal mortality rate is considered incompatible with the country development conditions, and has been a Public Health concern. Reduction in infant mortality rates has also been part of the Millennium Development Goals, a commitment made by countries, members of the Organization of United Nations (OUN), including Brazil. Fetal mortality rate is considered a highly sensitive indicator of health care quality. Suitable actions, such as good quality and access to health services may contribute positively towards reduction in these fetal and neonatal rates. With appropriate antenatal follow-up and health care during gestation and delivery, some death causes could be reduced or even prevented by means of early diagnosis and intervention, as well as changes in risk factors and interventions. Objectives: To study the quality of maternal and infant health care based on fetal and neonatal mortality, as well as the possible actions to prevent those deaths in Botucatu (Brazil). Methods: Classification of prevention according to the International Classification of Diseases and the modified Wigglesworth´s classification. In order to evaluate adequacy, indicators of quality of antenatal and delivery care were established by the authors. Results: Considering fetal deaths, 56.7% of them occurred before delivery, which reveals possible shortcomings in antenatal care, and 38.2% of them were a result of intra- labor changes, which could be prevented or reduced by adequate obstetric management. These findings were different from those in the group of early neonatal deaths which were also studied. Adequacy of health services showed that antenatal and childbirth care was appropriate for 24% and 33.3% of pregnant women, respectively, which corroborates the results of prevention. These results revealed that shortcomings in obstetric and antenatal care could be the causes of deaths in the study. Early and late neonatal deaths have similar characteristics: 76% could be prevented or reduced mainly by adequate newborn care (52.9%) and adequate health care for gestational women (11.7%). When adequacy of care was evaluated, childbirth and newborn care was adequate in 25.8% and antenatal care was adequate in 16.1%. In conclusion, direct relationship was found between adequacy and quality of care rendered to pregnant women and newborns, and fetal and infant mortality. Moreover, our findings highlight that deaths could be prevented by an adequate obstetric and neonatal management.

Keywords: Fetal Mortality, Infant Mortality, Maternal-Child Health Services, Program Evaluation.

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Authors: Wojciech Rejchel

Abstract:

The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.

Keywords: Convex loss function, empirical risk minimization, empirical process, U-process, boosting, euclidean family.

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Authors: El Miloud Ar Reyouchi, Kamal Ghoumid, Koutaiba Ameziane, Otman El Mrabet, Slimane Mekaoui

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In this paper we focus on the Round Trip Delay (RTD) time measurement technique which is an easy way to obtain the operating condition information in wireless network (WN). RTD measurement is affected by various parameters of wireless network. We illustrate how these RTD parameters vary (in a telemanagement application) versus distance, baud rates, number of hops, between nodes, using radio modem & router unit as a means of transmission and wireless routing.

Keywords: Wireless Network, Round Trip Delay, Radio modem, Router.

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Authors: R. Bourziza, A. Hammani, M. Kuper, A. Bouaziz

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In oases, the surface water resources are becoming increasingly scarce and groundwater resources, which generally have a poor quality due to the high levels of salinity, are often overexploited. Water saving have therefore become imperative for better oases sustainability. If drip irrigation is currently recommended in Morocco for saving water and valuing, its use in the sub-desert areas does not keep water safe from high evaporation rates. An alternative to this system would be the use of subsurface drip irrigation. This technique is defined as an application of water under the soil surface through drippers, which deliver water at rates generally similar to surface drip irrigation. As subsurface drip irrigation is a recently introduced in Morocco, a better understanding of the infiltration process around a buried source, in local conditions, and its impact on plant growth is necessarily required. This study aims to contribute to improving the water use efficiency by testing the performance of subsurface irrigation system, especially in areas where water is a limited source. The objectives of this research are performance evaluation in arid conditions of the subsurface drip irrigation system for young date palms compared to the surface drip. In this context, an experimental test is installed at a farmer’s field in the area of Erfoud (Errachidia Province, southeastern Morocco), using the subsurface drip irrigation system in comparison with the classic drip system for young date palms. Flow measurement to calculate the uniformity of the application of water was done through two methods: a flow measurement of drippers above the surface and another one underground. The latter method has also helped us to estimate losses through evaporation for both irrigation techniques. In order to compare the effect of two irrigation modes, plants were identified for each type of irrigation to monitor certain agronomic parameters (cumulative numbers of palms and roots development). Experimentation referred to a distribution uniformity of about 88%; considered acceptable for subsurface drip irrigation while it is around 80% for the surface drip irrigation. The results also show an increase in root development and in the number of palm, as well as a substantial water savings due to lower evaporation losses compared to the classic drip irrigation. The results of this study showed that subsurface drip irrigation is an efficient technique, which allows sustainable irrigation in arid areas.

Keywords: Subsurface drip irrigation, Water conservation, Arid areas, Young date palms.

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Authors: Ahtesham Javaid, Costin S. Bildea

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The design and plantwide control of an integrated plant where the endothermic 1,4-butanediol dehydrogenation and the exothermic furfural hydrogenation is simultaneously performed in a single reactor is studied. The reactions can be carried out in an adiabatic reactor using small hydrogen excess and with reduced parameter sensitivity. The plant is robust and flexible enough to allow different production rates of γ-butyrolactone and 2-methyl furan, keeping high product purities. Rigorous steady state and dynamic simulations performed in AspenPlus and AspenDynamics to support the conclusions.

Keywords: Dehydrogenation and hydrogenation, Reaction coupling, Design and control, Process integration.

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Authors: Irena Markovska, Nikolai Zaicev, Bogdan Bogdanov, Dimitar Georgiev, Yancho Hristov

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The present paper deals with problems related to the possibilities to use fractal systems to solve some important scientific and practical problems connected with filtering and separation of aqueous phases from organic ones. For this purpose a special separator have been designed. The reactor was filled with a porous material with fractal dimension, which is an integral part of the set for filtration and separation of emulsions. As a model emulsion hexadecan mixture with water in equal quantities (1:1) was used. We examined the hydrodynamics of the separation of the emulsion at different rates of submission of the entrance of the reactor.

Keywords: pilot reactor, fractal systems, separation, emulsions

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Authors: Z. Neffah, H. Kahalerras

Abstract:

A numerical study is made in a parallel-plate porous channel subjected to an oscillating flow and an exothermic chemical reaction on its walls. The flow field in the porous region is modeled by the Darcy–Brinkman–Forchheimer model and the finite volume method is used to solve the governing equations. The effects of the modified Frank-Kamenetskii (FKm) and Damköhler (Dm) numbers, the amplitude of oscillation (A), and the Strouhal number (St) are examined. The main results show an increase of heat and mass transfer rates with A and St, and their decrease with FKm and Dm.

Keywords: Chemical reaction, heat transfer, mass transfer, oscillating flow, porous channel.

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Authors: Anelise Leal Vieira Cubas, Marina de Medeiros Machado, Marília de Medeiros Machado

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The volatile organic compounds - BTEX (Benzene, Toluene, Ethylbenzene, and Xylene) petroleum derivatives, have high rates of toxicity, which may carry consequences for human health, biota and environment. In this directon, this paper proposes a method of treatment of these compounds by using corona discharge plasma technology. The efficiency of the method was tested by analyzing samples of BTEX after going through a plasma reactor by gas chromatography method. The results show that the optimal residence time of the sample in the reactor was 8 minutes.

Keywords: BTEX, Degradation, Cold plasma.

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Authors: Apurv Kulkarni, Shreyas Badave, B. Rajiv

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Non-parametric reliability technique is useful for assessment of reliability of systems for which failure rates are not available. This is useful when detection of malfunctioning of any component is the key purpose during ongoing operation of the system. The main purpose of the Heat Exchanger Cycle discussed in this paper is to provide hot water at a constant temperature for longer periods of time. In such a cycle, certain components play a crucial role and this paper presents an effective way to predict the malfunctioning of the components by determination of system reliability. The method discussed in the paper is feasible and this is clarified with the help of various test cases.

Keywords: Heat exchanger cycle, K-statistics, PID controller, system reliability.

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Authors: Boncho G. Bonev, Kliment N. Angelov, Emil S. Altimirski

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In this paper, the link quality in SHF and EHF ranges are studied. In order to achieve high data rate higher frequencies must be used – centimeter waves (SHF), millimeter waves (EHF) or optical range. However, there are significant problem when a radio link work in that diapason – rain attenuation and attenuation in earth-s atmosphere. Based on statistical rain rates data for Bulgaria, the link availability can be determined, depending on the working frequency, the path length and the Power Budget of the link. For the calculations of rain attenuation and atmosphere-s attenuation the ITU recommendations are used.

Keywords: rain attenuation, atmospheric gaseous attenuation, link availability, link breaking probability

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Authors: Mojca Ciglaric, Andrej Krevl, Matjaž Pancur, Tone Vidmar

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P2P Networks are highly dynamic structures since their nodes – peer users keep joining and leaving continuously. In the paper, we study the effects of network change rates on query routing efficiency. First we describe some background and an abstract system model. The chosen routing technique makes use of cached metadata from previous answer messages and also employs a mechanism for broken path detection and metadata maintenance. Several metrics are used to show that the protocol behaves quite well even with high rate of node departures, but above a certain threshold it literally breaks down and exhibits considerable efficiency degradation.

Keywords: Network dynamics, overlay network, P2P system, routing efficiency.

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Authors: Shamsuddin Ahmed, M. G. M. Khan, Biman Prasad, Avlin Prasad

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The focus of this paper is to construct daily time series exchange rate forecast models of Samoan Tala/USD and Tala/AUD during the year 2008 to 2012 with neural network The performance of the models was measured by using varies error functions such as Root Square mean error (RSME), Mean absolute error (MAE), and Mean absolute percentage error (MAPE). Our empirical findings suggest that AR (1) model is an effective tool to forecast the Tala/USD and Tala/AUD.

Keywords: Neural Network Forecasting Model, Autoregressive time series, Exchange rate, Tala/AUD, winters model.

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Authors: Mohamed A. Ismail, Samar M. M. Abdelmageed

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The main objective of this paper is to estimate the cost of road traffic accidents in Egypt. The Human Capital (HC) approach, specifically the Gross-Loss-of-Output methodology, is adopted for estimation. Moreover, cost values obtained by previous national literature are updated using the inflation rates. The results indicate an estimated cost of road traffic accidents in Egypt of approximately 10 billion Egyptian Pounds (about $US 1.8 billion) for the year 2008. In addition, it is expected that this cost will rise in 2009 to 11.8 billion Egyptian Pounds (about $US 2.1 billion).

Keywords: Cost, Gross-Loss-of-Output, Human CapitalApproach, Road Traffic Accidents.

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Authors: Raid R. O. Al-Nima, S. S. Dlay, W. L. Woo

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A relationship between face and signature biometrics is established in this paper. A new approach is developed to predict faces from signatures by using artificial intelligence. A multilayer perceptron (MLP) neural network is used to generate face details from features extracted from signatures, here face is the physical biometric and signatures is the behavioural biometric. The new method establishes a relationship between the two biometrics and regenerates a visible face image from the signature features. Furthermore, the performance efficiencies of our new technique are demonstrated in terms of minimum error rates compared to published work.

Keywords: Behavioural biometric, Face biometric, Neural network, Physical biometric, Signature biometric.

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Authors: Ahmad M. Sarhan, Omar I. Al Helalat

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In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.

Keywords: ANN, Backpropagation, Gaussian, LMS, MSE, Neuron, standard deviation, Widrow-Hoff rule.

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Authors: Yue-Der Lin, Wei-Ting Liu, Ching-Che Tsai, Wen-Hsiu Chen

Abstract:

PPG is a potential tool in clinical applications. Among such, the relationship between respiration and PPG signal has attracted attention in past decades. In this research, a bivariate AR spectral estimation method was utilized for the coherence analysis between these two signals. Ten healthy subjects participated in this research with signals measured at different respiratory rates. The results demonstrate that high coherence exists between respiration and PPG signal, whereas the coherence disappears in breath-holding experiments. These results imply that PPG signal reveals the respiratory information. The utilized method may provide an attractive alternative approach for the related researches.

Keywords: Coherence analysis, photoplethysmography (PPG), bivariate AR spectral estimation.

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Authors: P. Soda, G.Iannello

Abstract:

In this paper we address the issue of classifying the fluorescent intensity of a sample in Indirect Immuno-Fluorescence (IIF). Since IIF is a subjective, semi-quantitative test in its very nature, we discuss a strategy to reliably label the image data set by using the diagnoses performed by different physicians. Then, we discuss image pre-processing, feature extraction and selection. Finally, we propose two ANN-based classifiers that can separate intrinsically dubious samples and whose error tolerance can be flexibly set. Measured performance shows error rates less than 1%, which candidates the method to be used in daily medical practice either to perform pre-selection of cases to be examined, or to act as a second reader.

Keywords: Artificial neural networks, computer aided diagnosis, image classification, indirect immuno-fluorescence, pattern recognition.

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Authors: Ε. Giovanis

Abstract:

In this paper we present, propose and examine additional membership functions for the Smoothing Transition Autoregressive (STAR) models. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. Because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach, more fuzzy membership functions should be tested. Furthermore, fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation or genetic algorithm instead to nonlinear squares. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecast , Fuzzy membership functions, Smoothingtransition, Time-series

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Authors: Ilze Stokmane

Abstract:

Baltic competitiveness is quite controversial. In a situation with the rapid structural changes, economy develops in balance very rarely - in different fields will always be more rapid changes in another more stagnation. Analyzing different economic indices developed by international organizations the situation in three Baltic countries are described from a different competitiveness positions highlighting strengths and weaknesses of each country. Exploring the openness of the economy, it is possible to observe certain risks included in the reports describing situation of competitiveness where government policies competing in the tax system, the rates of labour market policies, investment environment, etc. This is a very important factor resulting in competitive advantage. Baltic countries are still at a weak position from a technological perspective, and need to borrow the knowledge and technology from more developed countries.

Keywords: Baltic countries, Baltic region, competitiveness, indices of competitiveness.

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Authors: Kexin Jia, Youxin Lu

Abstract:

To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a novel method of designing combined classifier based on fuzzy neural network (FNN) is presented in this paper. The method employs fuzzy neural network classifiers and interclass distance (ICD) to improve recognition reliability. Experimental results show that the proposed combined classifier has high recognition rate with large variation range of SNR (success rates are over 99.9% when SNR is not lower than 5dB).

Keywords: Modulation classification, combined classifier, fuzzy neural network, interclass distance.

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Authors: Ε. Giovanis

Abstract:

In this paper we propose and examine an Adaptive Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition Autoregressive (STAR) modeling. Because STAR models follow fuzzy logic approach, in the non-linear part fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation algorithm instead to nonlinear squares. Furthermore, additional fuzzy membership functions can be examined, beside the logistic and exponential, like the triangle, Gaussian and Generalized Bell functions among others. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecasting, Neuro-Fuzzy, Smoothing transition, Time-series

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Authors: Ilya Popov, Steven Hulshoff

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A numerical investigation of the effects of nanosecond barrier discharge on the stability of a two-dimensional free shear layer is performed. The computations are carried out using a compressible Navier-Stokes algorithm coupled with a thermodynamic model of the discharge. The results show that significant increases in the shear layer-s momentum thickness and Reynolds stresses occur due to actuation. Dependence on both frequency and amplitude of actuation are considered, and a comparison is made of the computed growth rates with those predicted by linear stability theory. Amplitude and frequency ranges for the efficient promotion of shear-layer instabilities are identified.

Keywords: NS-DBD, plasma, actuator, flow control, instability, shear layer

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