Search results for: metabolic networks

Authors: Irina M. Kolesnikova, Andrey M. Gaponov, Sergey A. Roumiantsev, Tatiana V. Grigoryeva, Alexander V. Laikov, Alexander V. Shestopalov

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Background. Neuropathy is a common complication of obesity. In this regard, the content of neurotrophins in such patients is of particular interest. Neurotrophins are the proteins that regulate neuron survival and neuroplasticity and include brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF). However, the risk of complications depends on the metabolic type of obesity. Metabolically unhealthy obesity (MUHO) is associated with a high risk of complications, while this is not the case with metabolically healthy obesity (MHO). Therefore, the aim of our work was to study the effect of the obesity metabolic type on serum neurotrophins levels. Patients, materials, methods. The study included 134 healthy donors and 104 obese patients. Depending on the metabolic type of obesity, the obese patients were divided into subgroups with MHO (n=40) and MUHO (n=55). In the blood serum, the concentration of BDNF and NGF was determined. In addition, the content of adipokines (leptin, asprosin, resistin, adiponectin), myokines (irisin, myostatin, osteocrin), indicators of carbohydrate, and lipid metabolism were measured. Correlation analysis revealed the relationship between the studied parameters. Results. We found that serum BDNF concentration was not different between obese patients and healthy donors, regardless of obesity metabolic type. At the same time, in obese patients, there was a decrease in serum NGF level versus control. A similar trend was characteristic of both MHO and MUHO. However, MUHO patients had a higher NGF level than MHO patients. The literature indicates that obesity is associated with an increase in the plasma concentration of NGF. It can be assumed that in obesity, there is a violation of NGF storage in platelets, which accelerates neurotrophin degradation. We found that BDNF concentration correlated with irisin levels in MUHO patients. Healthy donors had a weak association between NGF and VEGF levels. No such association was found in obese patients, but there was an association between NGF and leptin concentrations. In MHO, the concentration of NHF correlated with the content of leptin, irisin, osteocrin, insulin, and the HOMA-IR index. But in MUHO patients, we found only the relationship between NGF and adipokines (leptin, asprosin). It can be assumed that in patients with MHO, the replenishment of serum NGF occurs under the influence of muscle and adipose tissue. In the MUHO patients only the effect of adipose tissue on NGF was observed. Conclusion. Obesity, regardless of metabolic type, is associated with a decrease in serum NGF concentration. We showed that muscle and adipose tissues make a significant contribution to the serum NGF pool in the MHO patients. In MUHO there is no effect of muscle on the NGF level, but the effect of adipose tissue remains.

Keywords: neurotrophins, nerve growth factor, NGF, brain-derived neurotrophic factor, BDNF, obesity, metabolically healthy obesity, metabolically unhealthy obesity

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Authors: Ehsan Abdolzadeh, Sanaz Nouri, Siamak Khalaj

Abstract:

Today WSNs have many applications in different fields like the environment, military operations, discoveries, monitoring operations, and so on. Coverage size and energy consumption are the important challenges that these networks need to face. This paper tries to solve the problem of coverage with a requirement of k-coverage and minimum energy consumption. In order to minimize energy consumption, visual sensor networks have been used that observe and process just those targets that are located in their view direction. As a result, sensor rotations have decreased, and subsequently, energy consumption has been minimized. To solve the problem of coverage particle swarm optimization, coverage optimization has been able to ensure coverage requirement together with minimizing sensor rotations while meeting the problem requirement of k≤14. So energy consumption has decreased, and this could extend the sensors’ lifetime subsequently.

Keywords: K coverage, particle union optimization algorithm, wireless sensor networks, visual sensor networks

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Authors: Levente Varga, Dávid Deritei, Mária Ercsey-Ravasz, Răzvan Florian, Zsolt I. Lázár, István Papp, Ferenc Járai-Szabó

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One of the major shortcomings of widely used scientometric indicators is that different disciplines cannot be compared with each other. The issue of cross-disciplinary normalization has been long discussed, but even the classification of publications into scientific domains poses problems. Structural properties of citation networks offer new possibilities, however, the large size and constant growth of these networks asks for precaution. Here we present a new tool that in order to perform cross-field normalization of scientometric indicators of individual publications relays on the structural properties of citation networks. Due to the large size of the networks, a systematic procedure for identifying scientific domains based on a local community detection algorithm is proposed. The algorithm is tested with different benchmark and real-world networks. Then, by the use of this algorithm, the mechanism of the scientometric indicator normalization process is shown for a few indicators like the citation number, P-index and a local version of the PageRank indicator. The fat-tail trend of the article indicator distribution enables us to successfully perform the indicator normalization process.

Keywords: citation networks, cross-field normalization, local cluster detection, scientometric indicators

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Authors: Kashish Sareen, Jatinder Singh Bal

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The use of wireless sensor networks (WSNs) has grown vastly in the last era, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. Wireless Sensor Networks have now recently emerged as a most important computing platform and continue to grow in diverse areas to provide new opportunities for networking and services. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. The sensors collect data about their surrounding and forward it to a command centre through a base station. The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) as they are very useful in target detecting and other applications. However, hierarchical clustering protocols have maximum been used in to overall system lifetime, scalability and energy efficiency. In this paper, the state of the art in corresponding hierarchical clustering approaches for large-scale WSN environments is shown.

Keywords: clustering, DLCC, MLCC, wireless sensor networks

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Authors: Danilo López, Nelson Vera, Luis Pedraza

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This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.

Keywords: neural networks, multilayer perceptron, long short-term memory, recurrent neuronal network, mathematical analysis

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Authors: Zahra Bahadoran, Parvin Mirmiran, Hanieh-Sadat Ejtahed, Maryam Tohidi, Fereidoun Azizi

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Background and Aim: Broccoli sprouts, rich source of bioactive compounds specially sulforaphane (SFN), have unique functional properties. This study was conducted to investigate the possible treatment effects of high-SFN broccoli sprouts powder on metabolic and liver disorders in rats fed with high-fructose corn syrup. Methods: Thirty-two male wistar rats, pretreated with an eight-week high-fructose diet (water containing 30% fructose), were randomly allocated into three groups: Baseline control (BC), control (C) (normal diet), and BSP-diet (normal diet+5% BSP). The duration of the study was 6 weeks. Biochemical measurements, liver weight and triglyceride content were evaluated and histopathological examination of liver was performed. Results: After 6-weeks, the liver weight was significantly lower in BSP group compared to controls (13.4 g vs. 11.4 g, P<0.05). After 6 weeks, a significant decrease was observed in fasting serum glucose, total cholesterol and triglyceride levels in both experimental groups (P<0.05). Compared to controls, serum levels of HDL-C were significantly higher in BSP group. The liver TG content in BSP compared to control group was lower (14.6 vs. 16.4 mg/mg tissue). The hepatic levels of alanine aminotransferase, aspartate aminotransferase and γ-glutamyl transferase had not considerable changes in the groups after the intervention period but the level of alkaline phosphatase significantly decreased in BSP group (P<0.05). The histopathological examination of liver confirmed a decrease lobular and portal inflammation and ballooning in BSP group compared to control. Conclusion: High-SFN broccoli sprouts powder has beneficials effect on metabolic and liver changes-induced by high fructose corn syrup.

Keywords: broccoli sprouts, metabolic disorders, fatty liver, food science

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Authors: R. Oleko, A. Saraceni

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The aim of this research is to provide a rigorous evaluation of the existing academic productivity in relation to value proposition and creation in networked environments. Bibliometrics is a vigorous approach used to structure existing literature in an objective and reliable manner. To that aim, a thorough bibliometric analysis was performed in order to assess the large volume of the information encountered in a structured and reliable manner. A clear distinction between networks and service networks was considered indispensable in order to capture the effects of each network’s type properties on value creation processes. Via the use of bibliometric parameters, this review was able to capture the state-of-the-art in both value proposition and value creation consecutively. The results provide a rigorous assessment of the annual scientific production, the most influential journals, and the leading corresponding author countries. By means of citation analysis, the most frequently cited manuscripts and countries for each network type were identified. Moreover, by means of co-citation analysis, existing collaborative patterns were detected through the creation of reference co-citation networks and country collaboration networks. Co-word analysis was also performed in order to provide an overview of the conceptual structure in both networks and service networks. The acquired results provide a rigorous and systematic assessment of the existing scientific output in networked settings. As such, they positively contribute to a better understanding of the distinct impact of service networks on value proposition and value creation when compared to regular networks. The implications derived can serve as a guide for informed decision-making by practitioners during network formation and provide a structured evaluation that can stand as a basis for future research in the field.

Keywords: bibliometrics, co-citation analysis, networks, service networks, value creation, value proposition

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Authors: Yu-Ling Tsai, Chih-Jung Chang, Chia-Chen Lu, Eric Wu, Chuan-Sheng Lin, Tzu-Lung Lin, Hsin-Chih Lai

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It is urgent that novel anti-obesity measures that are safe, effective and widely available are developed for counteracting the rapidly growing obesity epidemics. In the present study, we show that a probiotic bacterium Parabacteroides goldsteinii screened through culture under the high molecular weight polysaccharides prepared from two iconic medicinal fungi, the Ganoderma lucidum and the Hirsutella sinensis, reduced body weight by ca. 20% in high-fat diet (HFD)-fed mice. The bacterium also decreased intestinal permeability, metabolic endotoxemia, inflammation and insulin resistance. Notably, oral administration of live, but not high temperature-killed, P. goldsteinii to HFD fed mice considerably reduces weight gain and obesity-associated metabolic disorders. A three months feeding of the mice with P. goldsteinii did not show any aberrant side effects, indicating the safety of this bacterium. Transcriptome analysis indicated that P. goldsteinii enhances immunity in resting dendritic cells, but reduces inflammation in lipopolysaccharide (LPS)-induced dendritic cells. On top, Naïve T-cells were skewed towards regulatory T-cells after encountering with dendritic cells (DCs) pretreated with P. goldsteinii. These results indicated P. goldsteinii showed anti-inflammatory effects and can work as a potential probiotic ameliorating obesogenicity and related metabolic syndromes.

Keywords: Parabacteroides goldsteinii, gut microbiome, obesity, immune modulation

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Authors: S. Sudhharani

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Energy distribution networks are the main link between the energy industry and consumers and are subject to the most scrutiny and testing of any category. As a result, it is important to monitor energy levels during the distribution phase. Power distribution networks, on the other hand, remain subject to common problems, including voltage breakdown, power outages, harmonics, and capacitor switching, all of which disrupt sinusoidal waveforms and reduce the quality and power of the network. Using power appliances in the form of custom power appliances is one way to deal with energy quality issues. Dynamic Voltage Restorer (DVR), integrated with network and distribution networks, is one of these devices. At the same time, by injecting voltage into the system, it can adjust the voltage amplitude and phase in the network. In the form of injections and three-phase syncing, it is used to compensate for the difficulty of energy quality. This article examines the recent use of DVR for power compensation and provides data on the control of each DVR in distribution networks.

Keywords: dynamic voltage restorer (DVR), power quality, distribution networks, control systems(PWM)

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Authors: Juan José Mesas, Luis Sainz

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The motivation for the development of this paper lies in the need for energy networks to reduce losses, improve performance, optimize their operation and try to benefit from the interconnection capacity with other networks enabled for other energy carriers. These interconnections generate interdependencies between some energy networks and others, which requires suitable models and methods for their analysis. Traditionally, the modeling and study of energy networks have been carried out independently for each energy carrier. Thus, there are well-established models and methods for the steady-state analysis of electrical networks, gas networks, and thermal networks separately. What is intended is to extend and combine them adequately to be able to face in an integrated way the steady-state analysis of networks with multiple energy carriers. Firstly, the added value of multi-energy networks, their operation, and the basic principles that characterize them are explained. In addition, two current aspects of great relevance are exposed: the storage technologies and the coupling elements used to interconnect one energy network with another. Secondly, the characteristic equations of the different energy networks necessary to carry out the steady-state analysis are detailed. The electrical network, the natural gas network, and the thermal network of heat and cold are considered in this paper. After the presentation of the equations, a particular case of the steady-state analysis of a specific multi-energy network is studied. This network is represented graphically, the interconnections between the different energy carriers are described, their technical data are exposed and the equations that have previously been presented theoretically are formulated and developed. Finally, the two iterative numerical resolution methods considered in this paper are presented, as well as the resolution procedure and the results obtained. The pros and cons of the application of both methods are explained. It is verified that the results obtained for the electrical network (voltages in modulus and angle), the natural gas network (pressures), and the thermal network (mass flows and temperatures) are correct since they comply with the distribution, operation, consumption and technical characteristics of the multi-energy network under study.

Keywords: coupling elements, energy carriers, multi-energy networks, steady-state analysis

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Authors: Lameck Zetu Khonje, Mulala Danny Simatele

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The tourism industry in Malawi has grown tremendously during the past twenty-five years. This growth is attributed to the change in the political system which opened doors to international tourist and investment opportunities in the country which previously was under a strict repressive one-party political system. This research paper focuses on the developments that took place in the accommodation sector during the same period and the impact that it has partly caused on an environmental metabolic rift in the country which is now vulnerable to climate change-related catastrophes. Respondents from the government departments and the hotel sector were recruited for in-depth interviews. These interviews were conducted between July and November 2015 and follow up interviews were conducted between September and December 2017. Both results indicated there were minimal efforts pursued from the public sector to cartel capitalistic development tendencies in the accommodation sector. The results from the hotel revealed there were considerable efforts pursued driven by operating cost-cutting motive. Applying systems thinking the paper recommends that the policing machinery needs improvement to ensure that the industry also focuses on environmental wellbeing instead of profit maximization. This paper contributes to the body of knowledge on tourism development and climate change.

Keywords: accommodation sector, climate change, metabolic rift, Malawi, tourism industry

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Authors: Mohammad Reza Taherkhani‎

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make a connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: underwater sensor networks, clustering, learning automata, energy consumption

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Authors: Jesús Antonio Puente Fernández, Luis Javier Garcia Villalba

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New trends on streaming videos such as series or films require a high demand of network resources. This fact results in a huge problem within traditional IP networks due to the rigidity of its architecture. In this way, Software Defined Networks (SDN) is a new concept of network architecture that intends to be more flexible and it simplifies the management in networks with respect to the existing ones. These aspects are possible due to the separation of control plane (controller) and data plane (switches). Taking the advantage of this separated control, it is easy to deploy a monitoring tool independent of device vendors since the existing ones are dependent on the installation of specialized and expensive hardware. In this paper, we propose a framework that optimizes the traffic monitoring in SDN networks that decreases the number of monitoring queries to improve the network traffic and also reduces the overload. The performed experiments (with and without the optimization) using a video streaming delivery between two hosts demonstrate the feasibility of our monitoring proposal.

Keywords: optimization, monitoring, software defined networking, statistics, query

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Authors: Xupin Zhang, Maria Caterina Bramati, Enrest Fokoue

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Understanding the career placement of graduates from the university is crucial for both the qualities of education and ultimate satisfaction of students. In this research, we adapt the capabilities of dynamic Bayesian networks to characterize and predict students’ job placement using data from various universities. We also provide elements of the estimation of the indicator (score) of the strength of the network. The research focuses on overall findings as well as specific student groups including international and STEM students and their insight on the career path and what changes need to be made. The derived Bayesian network has the potential to be used as a tool for simulating the career path for students and ultimately helps universities in both academic advising and career counseling.

Keywords: dynamic bayesian networks, indicator estimation, job placement, social networks

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Authors: Belbahi Ahlam

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With the phenomenal growth in the Internet, network security has become an integral part of computer and information security. In order to come up with measures that make networks more secure, it is important to learn about the vulnerabilities that could exist in a computer network and then have an understanding of the typical attacks that have been carried out in such networks. The first half of this paper will expose the readers to the classical network attacks that have exploited the typical vulnerabilities of computer networks in the past and solutions that have been adopted since then to prevent or reduce the chances of some of these attacks. The second half of the paper will expose the readers to the different network security controls including the network architecture, protocols, standards and software/ hardware tools that have been adopted in modern day computer networks.

Keywords: network security, attacks and controls, computer and information, solutions

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Authors: Ali Mustafa Elshawesh, Mohamed Abdulali

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The paper presents an approach to dimension circuit switched networks and find the relationship between the parameters of the circuit switched networks on the condition of specific probability of call blocking. Our work is creating a Simulation code based on Erlang (B) formula to draw graphs which show two curves for each graph; one of simulation and the other of calculated. These curves represent the relationships between average number of calls and average call duration with the probability of call blocking. This simulation code facilitates to select the appropriate parameters for circuit switched networks.

Keywords: Erlang B formula, call blocking, telephone system dimension, Markov model, link capacity

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Authors: Tolga Yazıcı

Abstract:

As a matter of the fact that online social networks like Twitter, Facebook and MySpace have experienced an extensive growth in recent years. Social media offers individuals with a tool for communicating and interacting with one another. These social networks enable people to stay in touch with other people and express themselves. This process makes the users of online social networks active creators of content rather than being only consumers of traditional media. That’s why millions of people show strong desire to learn the methods and tools of digital content production and necessary communication skills. However, the booming interest in communication and interaction through online social networks and high level of eagerness to invent and implement the ways to participate in content production raise some privacy and security concerns. This presentation aims to open the assumed revolutionary, democratic and liberating nature of the online social media up for discussion by reviewing some recent political developments in Turkey. Firstly, the role of Internet and online social networks in mobilizing collective movements through social interactions and communications will be questioned. Secondly, some cases from Gezi and Okmeydanı Protests and also December 17-25 period will be presented in order to illustrate misinformation and manipulation in social media and violation of individual privacy through online social networks in order to damage social unity and stability contradictory to democratic nature of online social networking.

Keywords: online social media networks, democratic participation, social movements, social polarization, privacy of individuals, Turkey

Procedia PDF Downloads 343

Authors: Yogesh Rai, Saurabh Singh, Sanjay Pandey, Dhananjay K. Sah, B. G. Roy, B. S. Dwarakanath, Anant N. Bhatt

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One of the most common signatures of highly malignant gliomas is their capacity to metabolize more glucose to lactic acid than normal brain tissues, even under normoxic conditions (Warburg effect), indicating that aerobic glycolysis is constitutively upregulated through stable genetic or epigenetic changes. However, oxidative phosphorylation (OxPhos) is also required to maintain the mitochondrial membrane potential for tumor cell survival. In the process of tumorigenesis, tumor cells during fastest growth rate exhibit both high glycolytic and high OxPhos. Therefore, metabolically reprogrammed cancer cells with combination of both aerobic glycolysis and altered OxPhos develop a robust metabolic phenotype, which confers a selective growth advantage. In our study, we grew the high glycolytic BMG-1 (glioma) cells with continuous exposure of mitochondrial uncoupler 2, 4, dinitro phenol (DNP) for 10 passages to obtain a phenotype of high glycolysis with enhanced altered OxPhos. We found that OxPhos modified BMG (OPMBMG) cells has similar growth rate and cell cycle distribution but high mitochondrial mass and functional enzymatic activity than parental cells. In in-vitro studies, OPMBMG cells showed enhanced invasion, proliferation and migration properties. Moreover, it also showed enhanced angiogenesis in matrigel plug assay. Xenografted tumors from OPMBMG cells showed reduced latent period, faster growth rate and nearly five folds reduction in the tumor take in nude mice compared to BMG-1 cells, suggesting that robust metabolic phenotype facilitates tumor formation and growth. OPMBMG cells which were found radio-resistant, showed enhanced radio-sensitization by 2-DG as compared to the parental BMG-1 cells. This study suggests that metabolic reprogramming in cancer cells enhances the potential of migration, invasion and proliferation. It also strengthens the cancer cells to escape the death processes, conferring resistance to therapeutic modalities. Our data also suggest that combining metabolic inhibitors like 2-DG with conventional therapeutic modalities can sensitize such metabolically aggressive cancer cells more than the therapies alone.

Keywords: 2-DG, BMG, DNP, OPM-BMG

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Authors: Danilo López, Johana Hernández, Edwin Rivas

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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: cognitive radio, neural network, prediction, primary user

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Authors: Jan Masak, Eva Kvasnickova, Vladimir Scholtz, Olga Matatkova, Marketa Valkova, Alena Cejkova

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Microbial colonization of medical instruments, catheters, implants, etc. is a serious problem in the spread of nosocomial infections. Biofilms exhibit enormous resistance to environment. The resistance of biofilm populations to antibiotic or biocides often increases by two to three orders of magnitude in comparison with suspension populations. Subjects of interests are substances or physical processes that primarily cause the destruction of biofilm, while the released cells can be killed by existing antibiotics. In addition, agents that do not have a strong lethal effect do not cause such a significant selection pressure to further enhance resistance. Non-thermal plasma (NTP) is defined as neutral, ionized gas composed of particles (photons, electrons, positive and negative ions, free radicals and excited or non-excited molecules) which are in permanent interaction. In this work, the effect of NTP generated by the cometary corona with a metallic grid on the formation and stability of biofilm and metabolic activity of cells in biofilm was studied. NTP was applied on biofilm populations of Staphylococcus epidermidis DBM 3179, Pseudomonas aeruginosa DBM 3081, DBM 3777, ATCC 15442 and ATCC 10145, Escherichia coli DBM 3125 and Candida albicans DBM 2164 grown on solid media on Petri dishes and on the titanium alloy (Ti6Al4V) surface used for the production joint replacements. Erythromycin (for S. epidermidis), polymyxin B (for E. coli and P. aeruginosa), amphotericin B (for C. albicans) and ceftazidime (for P. aeruginosa) were used to study the combined effect of NTP and antibiotics. Biofilms were quantified by crystal violet assay. Metabolic activity of the cells in biofilm was measured using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) colorimetric test based on the reduction of MTT into formazan by the dehydrogenase system of living cells. Fluorescence microscopy was applied to visualize the biofilm on the surface of the titanium alloy; SYTO 13 was used as a fluorescence probe to stain cells in the biofilm. It has been shown that biofilm populations of all studied microorganisms are very sensitive to the type of used NTP. The inhibition zone of biofilm recorded after 60 minutes exposure to NTP exceeded 20 cm², except P. aeruginosa DBM 3777 and ATCC 10145, where it was about 9 cm². Also metabolic activity of cells in biofilm differed for individual microbial strains. High sensitivity to NTP was observed in S. epidermidis, in which the metabolic activity of biofilm decreased after 30 minutes of NTP exposure to 15% and after 60 minutes to 1%. Conversely, the metabolic activity of cells of C. albicans decreased to 53% after 30 minutes of NTP exposure. Nevertheless, this result can be considered very good. Suitable combinations of exposure time of NTP and the concentration of antibiotic achieved in most cases a remarkable synergic effect on the reduction of the metabolic activity of the cells of the biofilm. For example, in the case of P. aeruginosa DBM 3777, a combination of 30 minutes of NTP with 1 mg/l of ceftazidime resulted in a decrease metabolic activity below 4%.

Keywords: anti-biofilm activity, antibiotic, non-thermal plasma, opportunistic pathogens

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Authors: Manuel Meranza-Castillon, Rolando Diaz-Castillo, Adrian Arellano-Delgado, Cesar Cruz-Hernandez, Rosa Martha Lopez-Gutierrez

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In this work, we deal with experimental network synchronization of chaotic nodes with different topologies. Our approach is based on complex system theory, and we use a master-slave configuration to couple the nodes in the networks. In particular, we design and implement electronically complex dynamical networks composed by nine coupled chaotic Chua’s circuits with topologies: in nearest-neighbor, small-world, open ring, star, and global. Also, network synchronization is evaluated according to a particular coupling strength for each topology. This study is important by the possible applications to private transmission of information in a chaotic communication network of multiple users.

Keywords: complex networks, Chua's circuit, experimental synchronization, multiple users

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Authors: Elaheh Vaezpour

Abstract:

Data sensing in wireless sensor networks is done by query deceleration the network by the users. In many applications of the wireless sensor networks, many users send queries to the network simultaneously. If the queries are processed separately, the network’s energy consumption will increase significantly. Therefore, it is very important to aggregate the queries before sending them to the network. In this paper, we propose a multiple query optimization framework based on sensors physical and temporal correlation. In the proposed method, queries are merged and sent to network by considering correlation among the sensors in order to reduce the communication cost between the sensors and the base station.

Keywords: wireless sensor networks, multiple query optimization, data correlation, reducing energy consumption

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Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

Procedia PDF Downloads 694

Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

Procedia PDF Downloads 158

Authors: Motahareh Fadaei

Abstract:

Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: clustering, energy consumption‎, learning automata, underwater sensor networks

Procedia PDF Downloads 317

Authors: Sara Alshehri, Bayan Alenzi, Atheer Alshehri, Samia Chelloug, Zainab Almry, Hussah Albugmai

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This paper concerns body area networks sensor that collect signals around a human body. The black hole attacks are the main security challenging problem because the data traffic can be dropped at any node. The focus of our proposed solution is to efficiently route data packets while detecting black hole nodes.

Keywords: body sensor networks, security, black hole, routing, broadcasting, OMNeT++

Procedia PDF Downloads 647

Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

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Authors: Mustafa M. Donma, Orkide Donma

Abstract:

Metabolic syndrome (MetS) is a severe health problem which is common among obese individuals. The components of MetS are rather stable in adults compared to the components discussed for children. Due to the ambiguity in this group of the population, how to diagnose MetS in morbid obese (MO) children still constitutes a matter of discussion. For this purpose, a formula, which facilitates the diagnosis of MetS in MO children, was investigated. The aim of this study was to develop a formula which was capable of discriminating MO children with and without MetS findings. Study population comprised MO children. Age and sex-dependent body mass index (BMI) percentiles of the children were above 99. Metabolic syndrome components were also determined. Elevated systolic and diastolic blood pressures (SBP and DBP), elevated fasting blood glucose (FBG), elevated triglycerides (TRG), and/or depressed high density lipoprotein cholesterol (HDL-C) in addition to central obesity were listed as MetS components for each child. Presence of at least two of these components confirmed that the case was MetS. Two groups were constituted. In the first group, there were forty-two MO children without MetS components. Second group was composed of forty-four MO children with at least two MetS components. Anthropometric measurements, including weight, height, waist, and hip circumferences, were performed following physical examination. Body mass index and homeostatic model assessment of insulin resistance values were calculated. Informed consent forms were obtained from the parents of the children. Institutional Non-Interventional Ethics Committee approved the study design. Blood pressure values were recorded. Routine biochemical analysis, including FBG, insulin (INS), TRG, HDL-C were performed. The performance and the clinical utility of the Diagnostic Obesity Notation Model Assessment Metabolic Syndrome Index (DONMA MetS index) [(INS/FBG)/(HDL-C/TRG)*100] was tested. Appropriate statistical tests were applied to the study data. p value smaller than 0.05 was defined as significant. Metabolic syndrome index values were 41.6±5.1 in MO group and 104.4±12.8 in MetS group. Corresponding values for HDL-C values were 54.5±13.2 mg/dl and 44.2±11.5 mg/dl. There were statistically significant differences between the groups (p<0.001). Upon evaluation of the correlations between MetS index and HDL-C values, a much stronger negative correlation was found in MetS group (r=-0.515; p=0.001) in comparison with the correlation detected in MO group (r=-0.371; p=0.016). From these findings, it was concluded that the statistical significance degree of the difference between MO and MetS groups was highly acceptable for this recently introduced MetS index as expected. This was due to the involvement of all of the biochemically defined MetS components into the index. This is particularly important because each of these four parameters used in the formula is cardiac risk factor. Aside from discriminating MO children with and without MetS findings, MetS index introduced in this study is important from the cardiovascular risk point of view in MetS group of children.

Keywords: children, fasting blood glucose, high density lipoprotein cholesterol, index, insulin, metabolic syndrome, morbid obesity, triglycerides.

Procedia PDF Downloads 92

Authors: Myriam Ferreira

Abstract:

Websites and social networks allow museums to divulge their works by new and attractive means. Besides, these technologies provide tools to generate a new history of art’s contents and promote visits to their installations. At the same time, museums are proposing more and more activities to families, children and young people. However, these activities usually take place in the museum’s physical installations, while websites and social networks seem to be mainly targeted to adults. The problem is that being children and young people digital natives, they feel apart from museums, so they need a presence of museums in digital means to feel attracted to them. Some institutions are making efforts to fill this vacuum. In this paper, resources designed specifically for children and teenagers have been selected from websites and social networks of five Spanish Museums: Prado Museum, Thyssen Museum, Guggenheim Museum, America Museum and Cerralbo Museum. After that, we have carried out an investigation in a school with children and teenagers between 11 and 15 years old. Those young people have been asked about their valuation of those web pages and social networks, with quantitative-qualitative questions. The results show that the least rated resources were videos and social networks because they were considered ‘too serious’, while the most rated were games and augmented reality. These ratings confirm theoretical papers that affirm that the future of technologies applied to museums is edutainment and interaction.

Keywords: children, museums, social networks, teenagers, websites

Procedia PDF Downloads 153

Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

Abstract:

Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

Procedia PDF Downloads 229