Search results for: network formation

Authors: Jin Xu

Abstract:

5G network developers need to satisfy the necessary requirements of additional capacity from massive users and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in network is motivating operators to combine long-term evolution (LTE) with intelligent spectrum management technology. This new LTE intelligent spectrum management in unlicensed band (LTE-U) has the physical layer topology to access spectrum, specifically the 5-GHz band. We proposed a new intelligent cloud RAN for 5G.

Keywords: cloud radio access network, wireless network, cloud computing, multi-agent

Procedia PDF Downloads 394

Authors: V. Andal Priyadharshini, Anumalasetty Yashwanth Nath

Abstract:

Network automation has evolved into a solution that ensures efficiency in all areas. The age-old technique to configure common software-defined networking protocols is inefficient as it requires a box-by-box approach that needs to be repeated often and is prone to manual errors. Network automation assists network administrators in automating and verifying the protocol configuration to ensure consistent configurations. This paper implemented network automation using Python and Ansible to configure different protocols and configurations in the container lab virtual environment. Ansible can help network administrators minimize human mistakes, reduce time consumption, and enable device visibility across the network environment.

Keywords: Python network automation, Ansible configuration, container lab deployment, software-defined networking, networking lab

Procedia PDF Downloads 133

Authors: Zeta Dooly, Aidan Duane

Abstract:

The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

Procedia PDF Downloads 103

Authors: Chenhao Zhu

Abstract:

Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

Procedia PDF Downloads 111

Authors: Elmira Ghanbari, Jan Van Esch, Stephen J. Picken, Sahil Aggarwal

Abstract:

Organogels are formed by the assembly of low molecular weight gelators (LMWG) into fibrous structures. The assembly of these molecules into crystalline fibrous structures occurs as a result of reversible interactions such as π-stacking, hydrogen-bonding, and van der Waals interactions. Bisamide organogelators with two amide groups have been used as one of LMWGs which show efficient assembly behavior via hydrogen bonding for network formation, the formation of a crystalline network for solvent entrapment. In this study, different bisamide gelators with different lengths of alkyl chains have been added to the bisamide parent gels. The effect of the addition of bisamide additives on the gelation of bisamide gels is described. Investigation of the thermal properties of the gels by differential scanning calorimetry and dropping ball techniques indicated that the bisamide gels can be formed by the addition of a high concentration of the second bisamide components. The microstructure of the gels with different gelator components has been visualized with scanning electron microscopy (SEM) which has shown systematic woven, platelet-like, and a combination of those morphologies for different gels. Examining the addition of a range of bisamide additives with different structural characteristics than the parent bisamide gels has confirmed the effect of the molecular structure on the morphology of the bisamide gels and their final properties.

Keywords: bisamide organogelator additives, gel morphology, gel properties, self-assembly

Procedia PDF Downloads 171

Authors: F. S. Kadhim, A. Samsuri, H. Alwan

Abstract:

Well logging records can help to answer many questions from a wide range of special interested information and basic petrophysical properties to formation evaluation of oil and gas reservoirs. The accurate calculations of porosity in carbonate reservoirs are the most challenging aspects of well log analysis. Many equations have been developed over the years based on known physical principles or on empirically derived relationships, which are used to calculate porosity, estimate lithology and water saturation; however these parameters are calculated from well logs by using modern technique in a current study. Nasiriya (NS) oilfield is one of giant oilfields in the Middle East, and the formation under study is the Mishrif carbonate formation which is the shallowest hydrocarbon bearing zone in the NS oilfield. Neurolog software (V5, 2008) was used to digitize the scanned copies of the available logs. Environmental corrections had been made as per Schlumberger charts 2005, which supplied in the Interactive Petrophysics software (IP, V3.5, 2008). Three saturation models have been used to calculate water saturation of carbonate formations, which are simple Archie equation, Dual water model, and Indonesia model. Results indicate that the Mishrif formation consists mainly of limestone, some dolomite and shale. The porosity interpretation shows that the logging tools have a good quality after making the environmental corrections. The average formation water saturation for Mishrif formation is around 0.4-0.6.This study is provided accurate behavior of petrophysical properties with depth for this formation by using modern software.

Keywords: lithology, porosity, water saturation, carbonate formation, mishrif formation

Procedia PDF Downloads 347

Authors: Asit K. Sikary, O. P. Murty

Abstract:

Adipocere formation is a modification of the process of putrefaction. It consists mainly of saturated fatty acids, formed by the post-mortem hydrolysis and hydrogenation of body fats with the help of bacterial enzymes in the presence of warmth, moisture and anaerobic bacteria. In temperate climate, it takes weeks to develop while in India it starts to begin within 4-5 days. In this study, we have collected cases with adipocere formation, which were from the South Delhi region (average room temperature 27-390C) and autopsied at our centre. Details of the circumstances of the death, cause and time of death, surrounding environment and demographic profile of the deceased were taken into account. Total 16 cases were included in this study. Adipocere formation was predominantly present over cheeks, shoulder, breast, flanks, buttocks, and thighs. Out of 16, 11 cases were found in a dry atmosphere, 5 cases were brought from the water. There were 5 cases in which adipocere formation was seen in less than 2 days, and among them, in 1 case, as early as one day. This study showed that adipocere formation can be seen as early as 1 day in a hot and humid environment.

Keywords: adipocere, drowning, hanging, humid environment, strangulation, subtropical climate

Procedia PDF Downloads 394

Authors: Voronina Ekaterina Borisovna

Abstract:

The problem of expressivity of advertising lexicon is studied in the article. The comparison of English and Russian advertising lexicons is done. The objects of the analysis were English and Russian advertising texts, both printed advertising texts and texts extracted from the commercials. Some conclusions concerning the expressivity of advertising lexicon were made. Expressivity can be included in the semantic structure of words or created by word-formation means. Expressivity caused by morphological derivatives includes such facilities as derivational affixes, models and types of word formation.

Keywords: advertising lexicon, expressivity, word-formation means, linguistics

Procedia PDF Downloads 323

Authors: Nashrawan Naser Taha, Andrew M. Cox

Abstract:

In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.

Keywords: mixed methods, social network analysis, multi-cultural learning, social network dynamics

Procedia PDF Downloads 487

Authors: Mohsen Dourandish

Abstract:

Iran has a huge pipeline network in every state of country which is the longest and vastest pipeline network after Russia and USA (360,000 Km high pressure pipelines and 250,000 Km distribution networks). Furthermore in recent years National Iranian Gas Company is planning to develop natural gas network to cover all cities and villages above 20 families, in a way that 97 percent of Iran population will be gas consumer by 2020. In this condition, network resiliency will be the first priority of NIGC and due to that several planning for increasing resiliency of gas network is under construction. The most important strategy of NIGC is converting tree form pattern network to loop gas networks and developing underground gas storage near main gas consuming centers. In this regard NIGC is planning for construction of over 3500 km high-pressure pipeline and also 10 TCM gas storage capacities in UGSs.

Keywords: Iranian gas network, peak shaving, resiliency, underground gas storage

Procedia PDF Downloads 296

Authors: Motonobu Hattori

Abstract:

In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

Procedia PDF Downloads 239

Authors: Razieh Niazmand, Dina Sadat Mousavian, Parvin Sharayei

Abstract:

This study investigated the effect of carboxymethyl cellulose (CMC), tragacanth, and saalab hydrocolloids in two concentrations (0.3%, 0.7%) and different frying media, refined canola oil (RCO), RCO + 1% bene kernel oil (BKO), and RCO + 1 mg/l unsaponifiable matter (USM) of BKO on acrylamide formation in fried potato slices. The hydrocolloid coatings significantly reduced acrylamide formation in potatoes fried in all oils. Increasing the hydrocolloid concentration from 0.3% to 0.7% produced no effective inhibition of acrylamide. The 0.7 % CMC solution was identified as the most promising inhibitor of acrylamide formation in RCO oil, with a 62.9% reduction in acrylamide content. The addition of BKO or USM to RCO led to a noticeable reduction in the acrylamide level in fried potato slices. The findings suggest that a 0.7% CMC solution and RCO+USM are promising inhibitors of acrylamide formation in fried potato products.

Keywords: CMC, frying, potato, saalab, tracaganth

Procedia PDF Downloads 263

Authors: Kritsada Moonpa, Kannipa Motanated, Weerapan Srichan

Abstract:

Hong Hoi Formation is a Middle Triassic deep marine succession presented in outcrops throughout the Lampang Basin of northern Thailand. The primary goal of this research is to diagnose the paleoenvironment, petrographic compositions, and sedimentary sources of the Hong Hoi Formation in Ban Huat, Ngao District. The Triassic Hong Hoi Formation is chosen because the outcrops are continuous and fossils are greatly exposed and abundant. Depositional environment is reconstructed through sedimentological studies along with facies analysis. The Hong Hoi Formation is petrographically divided into two major facies, they are: sandstones with mudstone interbeds, and mudstones or shale with sandstone interbeds. Sandstone beds are lithic arenite and lithic greywacke, volcanic lithic fragments are dominated. Sedimentary structures, paleocurrent data and lithofacies arrangement indicate that the formation deposited in a part of deep marine abyssal plain environment. The sedimentological and petrographic features suggest that during the deposition the Hong Hoi Formation received sediment supply from nearby volcanic arc. This suggested that the intensive volcanic activity within the Sukhothai Arc during the Middle Triassic is the main sediment source.

Keywords: Sukhothai zone, petrography, Hong Hoi formation, Lampang, Triassic

Procedia PDF Downloads 186

Authors: Min Jindong, Wang Mingxia

Abstract:

With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

Procedia PDF Downloads 248

Authors: Gunasekaran Raja, Ramkumar Jayaraman, Rajakumar Arul, Kottilingam Kottursamy

Abstract:

Broadband Wireless Network (BWN) is the promising technology nowadays due to the increased number of smartphones. Buffering scheme using network coding considers the reliability and proper degree distribution in Worldwide interoperability for Microwave Access (WiMAX) multi-hop network. Using network coding, a secure way of transmission is performed which helps in improving throughput and reduces the packet loss in the multicast network. At the outset, improved network coding is proposed in multicast wireless mesh network. Considering the problem of performance overhead, degree distribution makes a decision while performing buffer in the encoding / decoding process. Consequently, BuS (Buffer Scheme) based on network coding is proposed in the multi-hop network. Here the encoding process introduces buffer for temporary storage to transmit packets with proper degree distribution. The simulation results depend on the number of packets received in the encoding/decoding with proper degree distribution using buffering scheme.

Keywords: encoding and decoding, buffer, network coding, degree distribution, broadband wireless networks, multicast

Procedia PDF Downloads 371

Authors: Iliya Musa Adamu

Abstract:

This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.

Keywords: expert system, forward chaining rule based system, network, troubleshooting

Procedia PDF Downloads 611

Authors: Zhaojunfeng

Abstract:

Driven by the national policy of "East Data and Western Calculation", the computing first network will attract a new wave of development. As the foundation of the development of the computing first network, the computing force bearer network has become the key direction of technology research and development in the industry. This article will analyze typical computing force application scenarios and bearing requirements and sort out the SLA indicators of computing force applications. On this basis, this article carries out research and discussion on the key technologies of computing force bearer network in a slice packet network, and finally, gives evolution policy for SPN computing force bearer network to support the development of SPN computing force bearer network technology and network deployment.

Keywords: component-computing force bearing, bearing requirements of computing force application, dual-SLA indicators for computing force applications, SRv6, evolution strategies

Procedia PDF Downloads 100

Authors: Abdelhadi Lotfi, Abdelkader Benyettou

Abstract:

In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.

Keywords: classification, probabilistic neural networks, network optimization, pattern recognition

Procedia PDF Downloads 226

Authors: Anca Radulescu, Danae Evans

Abstract:

The relationship between a network’s hardwiring and its emergent dynamics are central to neuroscience. We study the principles of this correspondence in a canonical setup (in which network nodes exhibit well-studied complex quadratic dynamics), then test their universality in biological networks. By extending methods from discrete dynamics, we study the effects of network connectivity on temporal patterns, encapsulating long-term behavior into the rich topology of network Mandelbrot sets. Then elements of fractal geometry can be used to predict and classify network behavior.

Keywords: canonical model, complex dynamics, dynamic networks, fractals, Mandelbrot set, network connectivity

Procedia PDF Downloads 278

Authors: Gulcan Sahal, Nermin Hande Avcioglu, Isil Seyis Bilkay

Abstract:

Klebsiella species which are natural colonizers of human upper respiratory and human gastrointestinal tracts are also responsible for every reoccurring nosocomial infections by means of having ability to form slimy layers known as biofilm on many surfaces. Therefore, in this study, investigation of biofilm formation in K. pneumoniae and K. rhinoscleromatis and examination of each Klebsiella strains’ clinical information in the light of their biofilm formation results were aimed. In this respect, biofilm formation of Klebsiella strains was analyzed via crystal violet binding assay. According to our results, biofilm formation levels of K. pneumoniae and K. rhinoscleromatis strains were different from each other. Additionally, in comparison to K. rhinoscleromatis strains, K. pneumoniae was observed to include higher amounts of strong biofilm forming strains. Besides, it was also seen that clinical information of patients from which strong biofilm forming Klebsiella strains were isolated were similar to each other. Our results indicate that there should be more precautions against K. pneumoniae which includes higher amount of strong biofilm forming strains.

Keywords: biofilm formation, Klebsiella pneumoniae, Klebsiella rhinoscleromatis, biosystems engineering

Procedia PDF Downloads 365

Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

Abstract:

In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

Procedia PDF Downloads 141

Authors: Radha Tomar, Satish K. Jain, Manish Panchal, P. S. Rathore

Abstract:

In the presented work, inset fed microstrip patch antenna (IFMPA) based two port MIMO Antenna system has been proposed, which is suitable for wireless local area network (WLAN) applications. IFMPA has been designed, optimized for 2.4 GHz and applied for MIMO formation. The optimized parameters of the proposed IFMPA have been used for fabrication of antenna and two port MIMO in a laboratory. Fabrication of the designed MIMO antenna has been done and tested experimentally for performance parameters like Envelope Correlation Coefficient (ECC), Mean Effective Gain (MEG), Directive Gain (DG), Channel Capacity Loss (CCL), Multiplexing Efficiency (ME) etc and results are compared with simulated parameters extracted with simulated S parameters to validate the results. The simulated and experimentally measured plots and numerical values of these MIMO performance parameters resembles very much with each other. This shows the success of MIMO antenna design methodology.

Keywords: multiple-input and multiple-output, wireless local area network, vector network analyzer, envelope correlation coefficient

Procedia PDF Downloads 27

Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

Abstract:

In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

Procedia PDF Downloads 532

Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

Abstract:

Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

Procedia PDF Downloads 348

Authors: M. Kollar, A. Zieba

Abstract:

In this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The two eNBs are cooperating in so-called inter eNB CA (Carrier Aggregation) case and connected via asymmetrical IP network. We solve the problem by using broadcasting signals generated in E-UTRAN as synchronization signals. The results show that the time synchronization with the proposed method is possible with the error significantly less than 1 ms which is sufficient considering the time transmission interval is 1 ms in E-UTRAN. This makes this method (with low complexity) more suitable than Network Time Protocol (NTP) in the mobile applications with generated broadcasting signals where time synchronization in asymmetrical network is required.

Keywords: IP scheduled throughput, E-UTRAN, Evolved Universal Terrestrial Radio Access Network, NTP, Network Time Protocol, assymetric network, delay

Procedia PDF Downloads 336

Authors: Gulcan Sahal, Behzad Nasseri, Ali Akbar Ebrahimi, Isil Seyis Bilkay

Abstract:

Proteus mirabilis strains which are natural colonizers of healthy individuals’ gastrointestinal tract are also known as common causes of catheter-associated urinary tract infections. Nowadays, as a result of an increased resistance to various antimicrobial drugs, there has been a growing interest in natural products. Therefore, the aim of this study is to investigate biofilm formation of P. mirabilis strains on lemongrass oil containing polycaprolactone nanofibers. Polycaprolactone nanofibers with different lemongrass oil concentrations were successfully prepared by electrospinning and biofilm formation of P. mirabilis on these nanofibers were determined by ‘Crystal Violet Staining Assay’. According to our results, polycaprolactone nanofibers with some lemongrass oil concentrations, decreased biofilm formation of P. mirabilis and this effect increased in parallel with the increase in lemongrass oil concentration. Our results indicate that, polycaprolactone nanofibers with some concentrations of lemongrass oil may provide a treatment against catheter-associated urinary tract infections by means of causing an inhibition on biofilm formation of P. mirabilis.

Keywords: anti-biofilm, biofilm formation, essential oils, nanofibers, proteus mirabilis

Procedia PDF Downloads 387

Authors: Kolesnik Nadezda A.

Abstract:

The research aims to elaborate inter-organizational network relationships management model to maximize value co-creation. We propose a network management framework that requires evaluation of network partners with respect to their position and role in network; and elaboration of appropriate relationship development strategy with partners in network. Empirical research and approval is based on the case study method, including structured in-depth interviews with the companies from b2b market.

Keywords: inter-organizational networks, value co-creation, model, B2B market

Procedia PDF Downloads 424

Authors: Reza Alikhani

Abstract:

This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

Procedia PDF Downloads 42

Authors: Sourour Ramzi, Claudia Sarrico

Abstract:

Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

Procedia PDF Downloads 344

Authors: Sandeep Singh Waraich

Abstract:

Wireless sensor network (WSN ) consists of a large number of sensor nodes. The disparity in their energy consumption usually lead to the loss of equilibrium in wireless sensor network which may further results in an energy hole problem in wireless network. In this paper, we have considered the inclusion of orphan nodes which usually remain unutilized as intermediate nodes in multi-hop routing. The Orphan Node Inclusion (ONI) Protocol lets the cluster member to bring the orphan nodes into their clusters, thereby saving important resources and increasing network lifetime in critical applications of WSN.

Keywords: wireless sensor network, orphan node, clustering, ONI protocol

Procedia PDF Downloads 388