Search results for: fuzzy genetic network programming

Authors: Xiaoping Qiu, Binci You, Yue Hu

Abstract:

The executive time of the workflow network has an important effect on the efficiency of the business process. In this paper, the activity executive time is divided into the service time and the waiting time, then the lead time can be extracted from the waiting time. The executive time formulas of the three basic structures in the workflow network are deduced based on the activity lead time. Taken the process of e-commerce logistics as an example, insert appropriate lead time for key activities by using Petri net, and the executive time optimization model is built to minimize the waiting time with the time-cost constraints. Then the solution program-using VC++6.0 is compiled to get the optimal solution, which reduces the waiting time of key activities in the workflow, and verifies the role of lead time in the timeliness of e-commerce logistics.

Keywords: electronic business, execution time, lead time, optimization model, petri net, time workflow network

Procedia PDF Downloads 158

Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

Abstract:

Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

Procedia PDF Downloads 341

Authors: Arya Prakash Padhi, Anupam Chakrabarti, Rajib Chowdhury

Abstract:

Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved.

Keywords: 3D generative adversarial network, deep learning, structural topology optimization, variational auto encoder

Procedia PDF Downloads 157

Authors: Bhagwant Singh, Sikander Singh Cheema

Abstract:

This paper examines firewall mechanisms routinely implemented for network security in depth. A firewall can't protect you against all the hazards of unauthorized networks. Consequently, many kinds of infrastructure are employed to establish a secure network. Firewall strategies have already been the subject of significant analysis. This study's primary purpose is to avoid unnecessary connections by combining the capability of the firewall with the use of additional firewall mechanisms, which include packet filtering and NAT, VPNs, and backdoor solutions. There are insufficient studies on firewall potential and combined approaches, but there aren't many. The research team's goal is to build a safe network by integrating firewall strength and firewall methods. The study's findings indicate that the recommended concept can form a reliable network. This study examines the characteristics of network security and the primary danger, synthesizes existing domestic and foreign firewall technologies, and discusses the theories, benefits, and disadvantages of different firewalls. Through synthesis and comparison of various techniques, as well as an in-depth examination of the primary factors that affect firewall effectiveness, this study investigated firewall technology's current application in computer network security, then introduced a new technique named "tight coupling firewall." Eventually, the article discusses the current state of firewall technology as well as the direction in which it is developing.

Keywords: firewall strategies, firewall potential, packet filtering, NAT, VPN, proxy services, firewall techniques

Procedia PDF Downloads 87

Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

Abstract:

The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

Procedia PDF Downloads 87

Authors: Farzad Sharifi, Raziyeh Shamsi

Abstract:

In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose molti-objective DEA-R model, because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduces the efficiency score), an efficient DMU is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other case, only the ratio of stochastic data may be available (e.g; the ratio of stochastic inputs to stochastic outputs). Thus, we provide multi objective DEA model without explicit outputs and prove that in-put oriented MOP DEA-R model in the invariable return to scale case can be replacing by MOP- DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model, yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA, MOLP, STOCHASTIC, DEA-R

Procedia PDF Downloads 385

Authors: Guillaume P. Fernandez

Abstract:

Individual language use is a matter of choice in particular interactions. The paper proposes a conceptual and theoretical framework with methodological consideration to develop how language produced in dyadic relations is to be considered and situated in the larger social configuration the interaction is embedded within. An integrated and comprehensive view is taken: social interactions are expected to be ruled by a normative context, defined by the chain of interdependences that structures the personal network. In this approach, the determinants of discursive practices are not only constrained by the moment of production and isolated from broader influences. Instead, the position the individual and the dyad have in the personal network influences the discursive practices in a twofold manner: on the one hand, the network limits the access to linguistic resources available within it, and, on the other hand, the structure of the network influences the agency of the individual, by the social control inherent to particular network characteristics. Concretely, we investigate how and to what extent consistent ego is from one interaction to another in his or her use of adverbs. To do so, social network analysis (SNA) methods are mobilized. Participants (N=130) are college students recruited in the french speaking part of Switzerland. The personal network of significant ones of each individual is created using name generators and edge interpreters, with a focus on social support and conflict. For the linguistic parts, respondents were asked to record themselves with five of their close relations. From the recordings, we computed an average similarity score based on the adverb used across interactions. In terms of analyses, two are envisaged: First, OLS regressions including network-level measures, such as density and reciprocity, and individual-level measures, such as centralities, are performed to understand the tenets of linguistic similarity from one interaction to another. The second analysis considers each social tie as nested within ego networks. Multilevel models are performed to investigate how the different types of ties may influence the likelihood to use adverbs, by controlling structural properties of the personal network. Primary results suggest that the more cohesive the network, the less likely is the individual to change his or her manner of speaking, and social support increases the use of adverbs in interactions. While promising results emerge, further research should consider a longitudinal approach to able the claim of causality.

Keywords: personal network, adverbs, interactions, social influence

Procedia PDF Downloads 43

Authors: Talaat Ahmed, Amna Babssail

Abstract:

Mangroves are evergreen trees and grow along the coastal areas of Qatar. The largest and oldest area of mangroves can be found around Al-Thakhira and Al-Khor. Other mangrove areas originate from fairly recent plantings by the government, although unfortunately the picturesque mangrove lake in Al-Wakra has now been uprooted. Avicinnia marina is the predominant mangrove species found in the region. Mangroves protect and stabilize low lying coastal land, and provide protection and food sources for estuarine and coastal fishery food chains. They also serve as feeding, breeding and nursery grounds for a variety of fish, crustaceans, reptiles, birds and other wildlife. A total of 21 individuals of A. marina, representing seven diverse Natural and artificial populations, were sampled throughout its range in Qatar. Leaves from 2-3 randomly selected trees at each location were collected. The locations are as follows: Al-Rawis, Ras-Madpak, Fuwairt, Summaseima, Al-khour, AL-Mafjar and Zekreet. Total genomic DNA was extracted using commercial DNeasy Plant System (Qiagen, Inc., Valencia, CA) kit to be used for genetic diversity analysis. Total of 12 (Inter-Simple Sequence Repeat) ISSR primers were used to amplify DNA fragments using genomic DNA. The 12 ISSR primers amplified polymorphic bands among mangrove samples in different areas as well as within each area indicating the existing of variation within each area and among the different areas of mangrove in Qatar. The results could characterize Avicinnia marina populations exist in different areas of Qatar and establish DNA fingerprint documentations for mangrove population to be used in further studies. Moreover, existing of genetic variation within and among Avicinnia marina populations is a strong indication for the ability of such populations to adapt different environmental conditions in Qatar. This study could be a warning to save mangrove in Qatar and save the environment as well.

Keywords: DNA fingerprint, Avicinnia marina, genetic analysis, Qatar

Procedia PDF Downloads 378

Authors: Yuan Xu, Xun Liang, Meina Zhang

Abstract:

The rise and attenuation of the public opinion broadcast of an emergent accident, in the social network, has a close relationship with the dynamic development of its subevents cluster. In this article, we take Tianjin Port explosion's subevents as an example to research the dynamic propagation discipline of Internet public opinion in a sudden accident, and analyze the overall structure of dynamic propagation to propose four different routes for subevents clusters propagation. We also generate network diagrams for the dynamic public opinion propagation, analyze each propagation type specifically. Based on this, suggestions on the supervision and guidance of Internet public opinion broadcast can be made.

Keywords: network dynamic transmission modes, emergent subevents clusters, Tianjin Port explosion, public opinion supervision

Procedia PDF Downloads 273

Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

Abstract:

Software Defined Networking (SDN) is a paradigm designed to facilitate the way of controlling the network dynamically and with more agility. Network traffic is a set of flows, each of which contains a set of packets. In SDN, a matching process is performed on every packet coming to the network in the SDN switch. Only the headers of the new packets will be forwarded to the SDN controller. In terminology, the flow header fields are called tuples. Basically, these tuples are 5-tuple: the source and destination IP addresses, source and destination ports, and protocol number. This flow information is used to provide an overview of the network traffic. Our module is meant to extract this 5-tuple with the packets and flows numbers and show them as a list. Therefore, this list can be used as a first step in the way of detecting the DDoS attack. Thus, this module can be considered as the beginning stage of any flow-based DDoS detection method.

Keywords: matching, OpenFlow tables, POX controller, SDN, table-miss

Procedia PDF Downloads 182

Authors: Feleke Tsegaye

Abstract:

The work in this thesis mainly focuses on trajectory tracking of fixed wing unmanned aerial vehicle (FWUAV) by using fuzzy based sliding mode controller(FSMC) for surveillance applications. Unmanned Aerial Vehicles (UAVs) are general-purpose aircraft built to fly autonomously. This technology is applied in a variety of sectors, including the military, to improve defense, surveillance, and logistics. The model of FWUAV is complex due to its high non-linearity and coupling effect. In this thesis, input decoupling is done through extracting the dominant inputs during the design of the controller and considering the remaining inputs as uncertainty. The proper and steady flight maneuvering of UAVs under uncertain and unstable circumstances is the most critical problem for researchers studying UAVs. A FSMC technique was suggested to tackle the complexity of FWUAV systems. The trajectory tracking control algorithm primarily uses the sliding-mode (SM) variable structure control method to address the system’s control issue. In the SM control, a fuzzy logic control(FLC) algorithm is utilized in place of the discontinuous phase of the SM controller to reduce the chattering impact. In the reaching and sliding stages of SM control, Lyapunov theory is used to assure finite-time convergence. A comparison between the conventional SM controller and the suggested controller is done in relation to the chattering effect as well as tracking performance. It is evident that the chattering is effectively reduced, the suggested controller provides a quick response with a minimum steady-state error, and the controller is robust in the face of unknown disturbances. The designed control strategy is simulated with the nonlinear model of FWUAV using the MATLAB® / Simulink® environments. The simulation result shows the suggested controller operates effectively, maintains an aircraft’s stability, and will hold the aircraft’s targeted flight path despite the presence of uncertainty and disturbances.

Keywords: fixed-wing UAVs, sliding mode controller, fuzzy logic controller, chattering, coupling effect, surveillance, finite-time convergence, Lyapunov theory, flight path

Procedia PDF Downloads 38

Authors: Sara ElElimy, Samir Moustafa

Abstract:

Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 124

Authors: Kyoung-Jae Kim

Abstract:

Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

Procedia PDF Downloads 275

Authors: Purva Joshi, Rohit Thanki, Omar Hanif

Abstract:

Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

Procedia PDF Downloads 180

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 235

Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar

Abstract:

Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.

Keywords: data mining, defect prediction, missing requirements, software quality

Procedia PDF Downloads 450

Authors: Kenny Onayemi

Abstract:

In an era where academic institutions increasingly rely on information technology, the security of academic networks has emerged as a paramount concern. This comprehensive study delves into the effectiveness of security practices, including network mapping, vulnerability scanning, and penetration testing, within academic networks. Leveraging data from surveys administered to faculty, staff, IT professionals and IT students in the university, the study assesses their familiarity with these practices, perceived effectiveness, and frequency of implementation. The findings reveal that a significant portion of respondents exhibit a strong understanding of network mapping, vulnerability scanning, and penetration testing, highlighting the presence of knowledgeable professionals within academic institutions. Additionally, active scanning using network scanning tools and automated vulnerability scanning tools emerge as highly effective methods. However, concerns arise as the respondents show that the academic institutions conduct these practices rarely or never. Notably, many respondents have reported significant vulnerabilities or security incidents through these security measures within their institution. This study concludes with recommendations to enhance network security awareness and practices among faculty, staff, IT personnel, and students, ultimately fortifying the security posture of academic networks in the digital age.

Keywords: network security, academic networks, vulnerability scanning, penetration testing, information security

Procedia PDF Downloads 33

Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

Abstract:

Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

Procedia PDF Downloads 555

Authors: David Nantes, George Gilbert

Abstract:

There are a lot of risks that might crop up as a tunneling project develops, and it's crucial to be aware of them. Due to the unexpected nature of tunneling projects and the interconnectedness of risk occurrences, the risk assessment approach presents a significant challenge. The purpose of this study is to provide a hybrid FDEMATEL-ANP model to help prioritize risks during tunnel construction projects. The ambiguity in expert judgments and the relative severity of interdependencies across risk occurrences are both taken into consideration by this model, thanks to the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The Analytic Network Process (ANP) method is used to rank priorities and assess project risks. The authors provide a case study of a subway tunneling construction project to back up the validity of their methodology. The results showed that the proposed method successfully isolated key risk factors and elucidated their interplay in the case study. The proposed method has the potential to become a helpful resource for evaluating dangers associated with tunnel construction projects.

Keywords: risk, prioritization, FDEMATEL, ANP, tunneling construction projects

Procedia PDF Downloads 73

Authors: Giulia I. Pintea

Abstract:

The Roma people are a nomadic ethnic group native to India, and they are one of the most prevalent minorities in Europe. In the past, Roma were enslaved and they were imprisoned in concentration camps during the Holocaust; today, Roma are subject to hate crimes and are denied access to healthcare, education, and proper housing. The aim of this project is to analyze how the public perception of the Roma people may be influenced by antiziganist and pro-Roma institutions in Europe. In order to carry out this project, we used social network analysis to build two large social networks: The antiziganist network, which is composed of institutions that oppress and racialize Roma, and the pro-Roma network, which is composed of institutions that advocate for and protect Roma rights. Measures of centrality, density, and modularity were obtained to determine which of the two social networks is exerting the greatest influence on the public’s perception of Roma in European societies. Furthermore, data on hate crimes on Roma were gathered from the Organization for Security and Cooperation in Europe (OSCE). We analyzed the trends in hate crimes on Roma for several European countries for 2009-2015 in order to see whether or not there have been changes in the public’s perception of Roma, thus helping us evaluate which of the two social networks has been more influential. Overall, the results suggest that there is a greater and faster exchange of information in the pro-Roma network. However, when taking the hate crimes into account, the impact of the pro-Roma institutions is ambiguous, due to differing patterns among European countries, suggesting that the impact of the pro-Roma network is inconsistent. Despite antiziganist institutions having a slower flow of information, the hate crime patterns also suggest that the antiziganist network has a higher impact on certain countries, which may be due to institutions outside the political sphere boosting the spread of antiziganist ideas and information to the European public.

Keywords: applied mathematics, oppression, Roma people, social network analysis

Procedia PDF Downloads 257

Authors: Mahsa Pishdar

Abstract:

Food traceability through the supply chain is facing increased demand. IoT and blockchain are among the tools under consideration in the Industry 4.0 era that could be integrated to help implementation of the Circular Economy (CE) principles while enhancing food traceability solutions. However, such tools need intellectual system, and infrastructureto be settled as guidance through the way, helping overcoming obstacles. That is why the critical success factors for implementing Industry 4.0 and circular economy principles in food traceability concept are analyzed in this paper by combination of interval type 2 fuzzy Worst Best Method and Measurement Alternatives and Ranking according to Compromise Solution (Interval Type 2 fuzzy WBM-MARCOS). Results indicate that “Knowledge of Industry 4.0 obligations and CE principle” is the most important factor that is the basis of success following by “Management commitment and support”. This will assist decision makers to seize success in gaining a competitive advantage while reducing costs through the supply chain.

Keywords: food traceability, industry 4.0, internet of things, block chain, best worst method, marcos

Procedia PDF Downloads 183

Authors: I. Boroňová, J. Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, S. Mačeková, J. Poráčová, M. M. Blaščáková

Abstract:

Osteoporosis is a common multifactorial disease with a strong genetic component characterized by reduced bone mass and increased risk of fractures. Genetic factors play an important role in the pathogenesis of osteoporosis. The aim of our study was to identify the genotype and allele distribution of T245G polymorphism in OPG gene in Slovak postmenopausal women. A total of 200 unrelated Slovak postmenopausal women with diagnosed osteoporosis and 200 normal controls were genotyped for T245G (rs3134069) polymorphism of OPG gene. Genotyping was performed using the Custom Taqman®SNP Genotyping assays. Genotypes and alleles frequencies showed no significant differences (p=0.5551; p=0.6022). The results of the present study confirm the importance of T245G polymorphism in OPG gene in the pathogenesis of osteoporosis.

Keywords: OPG gene, T245G polymorphism, osteoporosis, T245G polymorphism, real-time PCR

Procedia PDF Downloads 395

Authors: Afshin Moazami, Andrea Schiffauerova

Abstract:

The objective of this work is to investigate the development and the role of collaboration networks in the creation of knowledge and innovations in the US and Canada, with a special focus on Quebec. In order to create scientific networks, the data on journal articles were extracted from SCOPUS, and the networks were built based on the co-authorship of the journal papers. For innovation networks, the USPTO database was used, and the networks were built on the patent co-inventorship. Various indicators characterizing the evolution of the network structure and the positions of the researchers and inventors in the networks were calculated. The comparison between the United States, Canada, and Quebec was then carried out. The preliminary results show that the nature of scientific collaboration networks differs from the one seen in innovation networks. Scientists work in bigger teams and are mostly interconnected within one giant network component, whereas the innovation network is much more clustered and fragmented, the inventors work more repetitively with the same partners, often in smaller isolated groups. In both Canada and the US, an increasing tendency towards collaboration was observed, and it was found that networks are getting bigger and more centralized with time. Moreover, a declining share of knowledge transfers per scientist was detected, suggesting an increasing specialization of science. The US collaboration networks tend to be more centralized than the Canadian ones. Quebec shares a lot of features with the Canadian network, but some differences were observed, for example, Quebec inventors rely more on the knowledge transmission through intermediaries.

Keywords: Canada, collaboration, innovation network, scientific network, Quebec, United States

Procedia PDF Downloads 183

Authors: G. Baraneedaran, Deepak Singh, Kollipara Tejesh

Abstract:

The wireless sensors network has been an active research area over the y-ear passed. Due to the limited energy and communication ability of sensor nodes, it seems especially important to design a routing protocol for WSNs so that sensing data can be transmitted to the receiver effectively, an energy-balanced routing method based on forward-aware factor (FAF-EBRM) is proposed in this paper. In FAF-EBRM, the next-hop node is selected according to the awareness of link weight and forward energy density. A spontaneous reconstruction mechanism for Local topology is designed additionally. In this experiment, FAF-EBRM is compared with LEACH and EECU, experimental results show that FAF-EBRM outperforms LEACH and EECU, which balances the energy consumption, prolongs the function lifetime and guarantees high Qos of WSN.

Keywords: energy balance, forward-aware factor (FAF), forward energy density, link weight, network performance

Procedia PDF Downloads 525

Authors: Sabitha Rani A., Nagamani V.

Abstract:

Embelia ribes Burm.f (Family-Myrsinaceae) commonly known as Vidanga or Baibirang, is one of the important medicinal plants of India. The seed extract is reported to be antidiabetic, antitumour, analgesic, anti-inflammatory, antispermatogenic, free radical scavenging activities and widely used in more than 75 Ayurvedic commercial formulations. Among the 100 different species of Embelia, E. ribes is considered as a major source of Embelin, a bioactive compound. Because of high demand and low availability, the seeds of E. ribes are substituted with many cheaper alternatives. Therefore, the present study of RAPD-PCR analysis was undertaken to develop molecular markers for identification of E. ribes. A total of 13 different seed samples of Embelia were collected from different agro-climatic regions of India. The seeds of E.ribes were collected from Kalpetta, Kerala and three different seed samples were collected from traders of Odisha, Madhya Pradesh, Maharastra. The other nine seed samples were collected from local traders which they have collected from different regions of India. Genomic DNA was isolated from different seed samples E. ribes and RAPD-PCR was performed on 13 different seed samples using 47 random primers. Out of all the primers, only 22 primers produced clear and highly-reproducible banding patterns. The 22 selected RAPD primers generated a total of 280 alleles with an average of 12 alleles per primer pair. In the present study, we have identified three RAPD-PCR markers i.e. OPF5_480 bp, OPH11_520 bp and OPH4_530 bp which can be used for genetic fingerprinting of E. ribes. This methodology can be employed for identification of original E. ribes and also distinguishing it from other substitutes and adulterants.

Keywords: Embelia ribes, RAPD-PCR, primers, genetic analysis

Procedia PDF Downloads 284

Authors: A. Kardi, R. Zagrouba, M. Alqahtani

Abstract:

The Internet of Everything (IoE) presents today a very attractive and motivating field of research. It is basically based on Wireless Sensor Networks (WSNs) in which the routing task is the major analysis topic. In fact, it directly affects the effectiveness and the lifetime of the network. This paper, developed from recent works and based on extensive researches, proposes a taxonomy of routing protocols in WSNs. Our main contribution is that we propose a classification model based on nine classes namely application type, delivery mode, initiator of communication, network architecture, path establishment (route discovery), network topology (structure), protocol operation, next hop selection and latency-awareness and energy-efficient routing protocols. In order to provide a total classification pattern to serve as reference for network designers, each class is subdivided into possible subclasses, presented, and discussed using different parameters such as purposes and characteristics.

Keywords: routing, sensor, survey, wireless sensor networks, WSNs

Procedia PDF Downloads 166

Authors: Begna Tulu, Gobena Ameni

Abstract:

Understanding the types of Mycobacterium bovis (M. bovis) strains circulating in a country and exploring its zoonotic potential has significant contribution in the effort to design control strategies. The main aim of this study was to review and compile the results of studies conducted on M. bovis genotyping and its zoonotic potential of M. bovis in Ethiopia. A systematic search and review of articles published on M. bovis strains in Ethiopia were made. PubMed and Google Scholar databases were considered for the search while the keywords used were 'Mycobacteria,' 'Mycobacterium bovis,' 'Bovine Tuberculosis' and 'Ethiopia.' Fourteen studies were considered in this review and a total of 31 distinct strains of M. bovis (N=211) were obtained; the most dominant strains were SB0133 (N=62, 29.4%), SB1176 (N=61, 28.9%), and followed by SB0134 and SB1476 each (N=18, 8.5%). The clustering rate of M. bovis strains was found to be 42.0%. On the other hand, 6 strains of M. bovis were reported from human namely; SB0665 (N=4), SB0303 (N=2), SB0982 (N=2), SB0133 (N=1), SB1176 (N=1), and 1 new strain. Similarly, a total of 8 strains (N=13) of M. tuberculosis bacteria were also identified from animal subjects; namely SIT149 (N=3), SIT1 (N=2), SIT1688 (n=2), SIT262 (N=2), SIT53 (N=1), SIT59 (N=1), and one new-Ethiopian strain. The result showed that the genetic diversity of M. bovis strains reported from Ethiopia are less diversified and highly clustered. And also the result underlines that there is an ongoing active transmission of M. bovis and M. tuberculosis between human and animals in Ethiopia because a significant number strains of both type of bacteria were reported from human and animals.

Keywords: mycobacterium bovis, Mycobacterium tuberculosis, zoonotic potential, genetic diversity, Ethiopia

Procedia PDF Downloads 121

Authors: Andre Slonopas, Zona Kostic, Warren Thompson

Abstract:

Obfuscation is one of the most useful tools to prevent network compromise. Previous research focused on the obfuscation of the network communications between external-facing edge devices. This work proposes the use of two edge devices, external and internal facing, which communicate via private IPv4 addresses in a software-defined pseudo-random IP hopping. This methodology does not require additional IP addresses and/or resources to implement. Statistical analyses demonstrate that the hopping surface must be at least 1e3 IP addresses in size with a broad standard deviation to minimize the possibility of coincidence of monitored and communication IPs. The probability of breaking the hopping algorithm requires a collection of at least 1e6 samples, which for large hopping surfaces will take years to collect. The probability of dropped packets is controlled via memory buffers and the frequency of hops and can be reduced to levels acceptable for video streaming. This methodology provides an impenetrable layer of security ideal for information and supervisory control and data acquisition systems.

Keywords: moving target defense, cybersecurity, network security, hopping randomization, software defined network, network security theory

Procedia PDF Downloads 170

Authors: Muntadher Sallal, Gareth Owenson, Mo Adda, Safa Shubbar

Abstract:

Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation, which makes the system vulnerable to double-spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, that are based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In MNBC protocol, physical internet connectivity increases, as well as the number of hops between nodes, decreases through assigning nodes to be responsible for maintaining clusters based on physical internet proximity. We show, through simulations, that the proposed protocol defines better clustering structures that optimize the performance of the transaction propagation over the Bitcoin protocol. The evaluation of partition attacks in the MNBC protocol, as well as the Bitcoin network, was done in this paper. Evaluation results prove that even though the Bitcoin network is more resistant against the partitioning attack than the MNBC protocol, more resources are needed to be spent to split the network in the MNBC protocol, especially with a higher number of nodes.

Keywords: Bitcoin network, propagation delay, clustering, scalability

Procedia PDF Downloads 105

Authors: Madia Safdar, G. Amjad Hussain, Mashhood Ahmad

Abstract:

One of the major challenges of today’s era is peak demand which causes stress on the transmission lines and also raises the cost of energy generation and ultimately higher electricity bills to the end users, and it was used to be managed by the supply side management. However, nowadays this has been withdrawn because of existence of potential in the demand side management (DSM) having its economic and- environmental advantages. DSM in domestic load can play a vital role in reducing the peak load demand on the network provides a significant cost saving. In this paper the potential of demand response (DR) in reducing the peak load demands and electricity bills to the electric users is elaborated. For this purpose the domestic appliances are modeled in MATLAB Simulink and controlled by a module called energy management controller. The devices are categorized into controllable and uncontrollable loads and are operated according to real-time tariff pricing pattern instead of fixed time pricing or variable pricing. Energy management controller decides the switching instants of the controllable appliances based on the results from optimization algorithms. In GAMS software, the MILP (mixed integer linear programming) algorithm is used for optimization. In different cases, different constraints are used for optimization, considering the comforts, needs and priorities of the end users. Results are compared and the savings in electricity bills are discussed in this paper considering real time pricing and fixed tariff pricing, which exhibits the existence of potential to reduce electricity bills and peak loads in demand side management. It is seen that using real time pricing tariff instead of fixed tariff pricing helps to save in the electricity bills. Moreover the simulation results of the proposed energy management system show that the gained power savings lie in high range. It is anticipated that the result of this research will prove to be highly effective to the utility companies as well as in the improvement of domestic DR.

Keywords: controllable and uncontrollable domestic loads, demand response, demand side management, optimization, MILP (mixed integer linear programming)

Procedia PDF Downloads 288