Search results for: modular function deployment

Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

Abstract:

Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

Procedia PDF Downloads 128

Authors: Iman Farasat, Howard M. Salis

Abstract:

Engineered genetic circuits reprogram cellular behavior to act as living computers with applications in detecting cancer, creating self-controlling artificial tissues, and dynamically regulating metabolic pathways. Phenemenological models are often used to simulate and design genetic circuit behavior towards a desired behavior. While such models assume that each circuit component’s function is modular and independent, even small changes in a circuit (e.g. a new promoter, a change in transcription factor expression level, or even a new media) can have significant effects on the circuit’s function. Here, we use statistical thermodynamics to account for the several factors that control transcriptional regulation in bacteria, and experimentally demonstrate the model’s accuracy across 825 measurements in several genetic contexts and hosts. We then employ our first principles model to design, experimentally construct, and characterize a family of signal amplifying genetic circuits (genetic OpAmps) that expand the dynamic range of cell sensors. To develop these models, we needed a new approach to measuring the in vivo binding free energies of transcription factors (TFs), a key ingredient of statistical thermodynamic models of gene regulation. We developed a new high-throughput assay to measure RNA polymerase and TF binding free energies, requiring the construction and characterization of only a few constructs and data analysis (Figure 1A). We experimentally verified the assay on 6 TetR-homolog repressors and a CRISPR/dCas9 guide RNA. We found that our binding free energy measurements quantitatively explains why changing TF expression levels alters circuit function. Altogether, by combining these measurements with our biophysical model of translation (the RBS Calculator) as well as other measurements (Figure 1B), our model can account for changes in TF binding sites, TF expression levels, circuit copy number, host genome size, and host growth rate (Figure 1C). Model predictions correctly accounted for how these 8 factors control a promoter’s transcription rate (Figure 1D). Using the model, we developed a design framework for engineering multi-promoter genetic circuits that greatly reduces the number of degrees of freedom (8 factors per promoter) to a single dimensionless unit. We propose the Ptashne (Pt) number to encapsulate the 8 co-dependent factors that control transcriptional regulation into a single number. Therefore, a single number controls a promoter’s output rather than these 8 co-dependent factors, and designing a genetic circuit with N promoters requires specification of only N Pt numbers. We demonstrate how to design genetic circuits in Pt number space by constructing and characterizing 15 2-repressor OpAmp circuits that act as signal amplifiers when within an optimal Pt region. We experimentally show that OpAmp circuits using different TFs and TF expression levels will only amplify the dynamic range of input signals when their corresponding Pt numbers are within the optimal region. Thus, the use of the Pt number greatly simplifies the genetic circuit design, particularly important as circuits employ more TFs to perform increasingly complex functions.

Keywords: transcription factor, synthetic biology, genetic circuit, biophysical model, binding energy measurement

Procedia PDF Downloads 472

Authors: Genute Gedviliene, Vidmantas Tutlys

Abstract:

The aim of this paper is to reveal the deployment and development of the social competence in the higher education programmes of adult education and in the continuing training and competence development of the andragogues. There will be compared how the issues of cooperation and communication in the learning and teaching processes are treated in the study programmes and in the courses of continuing training of andragogues. Theoretical and empirical research methods were combined for research analysis. For the analysis the following methods were applied: 1) Literature and document analysis helped to highlight the communication and cooperation as fundamental phenomena of the social competence, it’s important for the adult education in the context of digitalization and globalization. There were also analyzed the research studies on the development of social competence in the field of andragogy, as well as on the place and weight of the social competence in the overall competence profile of the andragogue. 2) The empirical study is based on questionnaire survey method. The population of survey consists of 240 students of bachelor and master degree studies of andragogy in Lithuania and of 320 representatives of the different bodies and institutions involved in the continuing training and professional development of the adult educators in Lithuania. The themes of survey questionnaire were defined on the basis of findings of the literature review and included the following: 1) opinions of the respondents on the role and place of a social competence in the work of andragogue; 2) opinions of the respondents on the role and place of the development of social competence in the curricula of higher education studies and continuing training courses; 3) judgements on the implications of the higher education studies and courses of continuing training for the development of social competence and it’s deployment in the work of andragogue. Data analysis disclosed a wide range of ways and modalities of the deployment and development of social competence in the preparation and continuing training of the adult educators. Social competence is important for the students and adult education providers not only as the auxiliary capability for the communication and transfer of information, but also as the outcome of collective learning leading to the development of new capabilities applied by the learners in the learning process, their professional field of adult education and their social life. Equally so, social competence is necessary for the effective adult education activities not only as an auxiliary capacity applied in the teaching process, but also as a potential for improvement, development and sustainability of the didactic competence and know-how in this field. The students of the higher education programmes in the field of adult education treat social competence as important generic capacity important for the work of adult educator, whereas adult education providers discern the concrete issues of application of social competence in the different processes of adult education, starting from curriculum design and ending with assessment of learning outcomes.

Keywords: adult education, andragogues, social competence, curriculum

Procedia PDF Downloads 141

Authors: Mahesh Koti

Abstract:

In this paper, we present a quantum transport study of a quantum dot in steady state in the presence of static gate potential. We consider a quantum dot coupled to the two metallic leads. The quantum dot under study is modeled through Anderson Impurity Model (AIM) with hopping parameter modulated through voltage drop between leads and the central dot region. Based on the Landauer's formula derived from Nonequilibrium Green's Function and Single Electron Theory, the essential ingredients of transport properties are revealed. We show that the results out of two approaches closely agree with each other. We demonstrate that Landauer current response derived from single electron approach converges with non-zero interaction through gate potential whereas Landauer current response derived from Nonequilibrium Green's Function (NEGF) hits a pole.

Keywords: Anderson impurity model (AIM), nonequilibrium Green's function (NEGF), Landauer's formula, single electron analysis

Procedia PDF Downloads 470

Authors: Wedad Azhar

Abstract:

Vitamin D is an essential fat-soluble vitamin that is required for the maintenance of good health. It is obtained either through exposure to sunlight (ultraviolet B radiation) or through dietary sources. The role of vitamin D is beyond bone health. Indeed, it plays a critical role in the immune system and a broad range of organ functions such as the cardiovascular system. Moreover, vitamin D plays a critical role in the endothelial function, which is one of the main indicators of atherosclerosis. This study is investigating the correlation between vitamin D status and endothelial function in preventing and treating atherosclerosis especially in country that has ample of sunshine but yet, Saudis from suffering from this issue vitamin D deficiency and insufficiency. Ninety participants from both genders and aged 40 to 60will be involved. The participants will be categorised into three groups: the control group will be healthy persons, patients at risk of developing atherosclerosis, patients formally diagnosed atherosclerosis. Half of the participants in each group should already have been taking vitamin D supplementations. Fasting blood samples will be taken from the participants for biochemical assays. Endothelial function will be assist by flow-mediated dilation of the brachial artery. Participants will be asked to complete a questionnaire on their social and economic status, education level, daily exposure to sunlight, smoking status, consumption of supplements and medication, and a food frequency of vitamin D intake. The data will be analysed using SPSS.

Keywords: atherosclerosis, endothelial function, nutrition, vitamin D

Procedia PDF Downloads 294

Authors: Hong-Ming Chen

Abstract:

This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

Procedia PDF Downloads 161

Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi

Abstract:

Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.

Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory

Procedia PDF Downloads 401

Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad

Abstract:

This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.

Keywords: MANET, AODV, malicious node, OPNET

Procedia PDF Downloads 293

Authors: Jasna Prester, Ivana Rašić Bakarić, Božidar Matijević

Abstract:

Various prominent scholars and substantial practitioner-oriented literature on innovation orientation have shown positive effects on firm performance. There is a myriad of factors that influence and enhance innovation but it has been found in the literature that new product innovations accounted for an average of 14 percent of sales revenues for all firms. If there is one thing that has changed in innovation management during the last decade, it is the growing reliance on external partners. As a consequence, a new task for purchasing arises, as firms need to understand which suppliers actually do have high potential contributing to the innovativeness of the firm and which do not. Purchasing function in an organization is extremely important as it deals on an average of 50% or more of a firm's expenditures. In the nineties the purchasing department was largely seen as a transaction-oriented, clerical function but today purchasing integration provides a formal interface mechanism between purchasing and other firm functions that services other functions within the company. Purchasing function has to be organized differently to enable firm innovation potential. However, innovations are inherently risky. There are behavioral risk (that some partner will take advantage of the other party), technological risk in terms of complexity of products and processes of manufacturing and incoming materials and finally market risks, which in fact judge the value of the innovation. These risks are investigated in this work since it has been found in the literature that the higher the technological risk, higher will be the centralization of the purchasing function as an interface with other supply chain members. Most researches on organization of purchasing function were done by case study analysis of innovative firms. This work actually tends to prove or discard results found in the literature based on case study method. A large data set of 1493 companies, from 25 countries collected in the GMRG 4 survey served as a basis for analysis.

Keywords: purchasing function organization, innovation, technological risk, GMRG 4 survey

Procedia PDF Downloads 481

Authors: Ching-Yuan Huang, Rhay-Hung Weng, Yi-Ting Chen

Abstract:

Mentoring functions will improve new nurses' job performance, provide support with new nurses, and then reduce the turnover rate of them. This study explored the impact of transformational leadership and interpersonal interaction on mentoring functions. We employed a questionnaire survey to collect data and selected a sample of new nurses from three hospitals in Taiwan. A total of 306 valid surveys were obtained. Multiple regression model analysis was conducted to test the study hypothesis. Inspirational motivation, idealized influence, and individualized consideration had a positive influence on overall mentoring function, but intellectual stimulation had a positive influence on career development function only. Perceived similarity and interaction frequency also had positive influences on mentoring functions. When the shift overlap rate exceeded 80%, mentoring function experienced a negative result. The transformational leadership of mentors actually would improve the mentoring functions among new staff nurses. Perceived similarity and interaction frequency between mentees and mentors also had a positive influence on mentoring functions. Managers should enhance the transformational leadership of mentors by designing leadership training and motivation programs. Furthermore, nursing managers should promote the interaction between new staff nurses and their mentors, but the shift overlap rate should not exceed 80%.

Keywords: interpersonal interaction, mentoring function, mentor, new nurse, transformational leadership

Procedia PDF Downloads 331

Authors: Armel Asongu Nkembi, Ahmad Fawad

Abstract:

The aim of this paper is to determine in a concise way the transfer function that characterizes a DC electrical motor with a helix. In practice it can be obtained by applying a particular input to the system and then, based on the observation of its output, determine an approximation to the transfer function of the system. In our case, we use a step input and find the transfer function parameters that give the simulated first-order time response. The simulation of the system is done using MATLAB/Simulink. In order to determine the parameters, we assume a first order system and use the Broida approximation to determine the parameters and then its Mean Square Error (MSE). Furthermore, we design a PID controller for the control process first in the continuous time domain and tune it using the Ziegler-Nichols open loop process. We then digitize the controller to obtain a digital controller since most systems are implemented using computers, which are digital in nature.

Keywords: transfer function, step input, MATLAB, Simulink, DC electrical motor, PID controller, open-loop process, mean square process, digital controller, Ziegler-Nichols

Procedia PDF Downloads 54

Authors: Ari S. Prabowo, Nia Febriyanti, Haryono B. Santosa

Abstract:

Security function that is called as Physical Protection Systems (PPS) has functions to detect, delay and response. Physical Protection Systems (PPS) in Detection and Radiation Measurement Laboratory needs to be improved continually by using internal resources. The nuclear security culture provides some potentials to support this research. The study starts by identifying the security function’s weaknesses and its strengths of security culture as a purpose. Secondly, the strengths of security culture are implemented in the laboratory management. Finally, a simulation was done to measure its effectiveness. Some changes were happened in laboratory personnel behaviors and procedures. All became more prudent. The results showed a good influence of nuclear security culture in laboratory security functions.

Keywords: laboratory, physical protection system, security culture, security function

Procedia PDF Downloads 184

Authors: Takashi Mitsuishi

Abstract:

Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure).

Keywords: defuzzification, fuzzy membership function, periodic function, polar coordinates transformation

Procedia PDF Downloads 362

Authors: S. Doyle, G. A. Aggidis

Abstract:

Wave energy converter technologies continue to show good progress in worldwide research. One of the most researched technologies, the Oscillating Water Column (OWC), is arguably one of the most popular categories within the converter technologies due to its robustness, simplicity and versatility. However, the versatility of the OWC is still largely untapped with most deployments following similar trends with respect to applications and operating systems. As the competitiveness of the energy market continues to increase, the demand for wave energy technologies to be innovative also increases. For existing wave energy technologies, this requires identifying areas to diversify for lower costs of energy with respect to applications and synergies or integrated systems. This paper provides a review of all OWCs systems integrated into alternative applications in the past and present. The aspects and variation in their design, deployment and system operation are discussed. Particular focus is given to the Multi-OWCs (M-OWCs) and their great potential to increase capture on a larger scale, especially in synergy applications. It is made clear that these steps need to be taken in order to make wave energy a competitive and viable option in the renewable energy mix as progression to date shows that stand alone single function devices are not economical. Findings reveal that the trend of development is moving toward these integrated applications in order to reduce the Levelised Cost of Energy (LCOE) and will ultimately continue in this direction in efforts to make wave energy a competitive option in the renewable energy mix.

Keywords: wave energy converter, oscillating water column, ocean energy, renewable energy

Procedia PDF Downloads 132

Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

Abstract:

In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions.

Keywords: NFV, resource allocation, virtual routing function, minimum power consumption

Procedia PDF Downloads 340

Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

Abstract:

A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

Procedia PDF Downloads 150

Authors: Yasser Rammah, Wolf-Christian Mueller

Abstract:

Nonlinear triad interactions in incompressible three-dimensional magnetohydrodynamic (3D-MHD) turbulence are studied by analyzing data from high-resolution direct numerical simulations of decaying isotropic (5123 grid points) and forced anisotropic (10242 x256 grid points) turbulence. An accurate numerical approach toward analyzing nonlinear turbulent energy transfer function and triad interactions is presented. It involves the direct numerical examination of every wavenumber triad that is associated with the nonlinear terms in the differential equations of MHD in the inertial range of turbulence. The technique allows us to compute the spectral energy transfer and energy fluxes, as well as the spectral locality property of energy transfer function. To this end, the geometrical shape of each underlying wavenumber triad that contributes to the statistical transfer density function is examined to infer the locality of the energy transfer. Results show that the total energy transfer is local via nonlocal triad interactions in decaying macroscopically isotropic MHD turbulence. In anisotropic MHD, turbulence subject to a strong mean magnetic field the nonlinear transfer is generally weaker and exhibits a moderate increase of nonlocality in both perpendicular and parallel directions compared to the isotropic case. These results support the recent mathematical findings, which also claim the locality of nonlinear energy transfer in MHD turbulence.

Keywords: magnetohydrodynamic (MHD) turbulence, transfer density function, locality function, direct numerical simulation (DNS)

Procedia PDF Downloads 384

Authors: Pablo Chico De Guzman, Cesar Sanchez

Abstract:

Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

Procedia PDF Downloads 178

Authors: Michael Luc Andre, Célia Maintenant

Abstract:

Theory of mind is a milestone in child development which allows children to understand that others could have different mental states than theirs. Understanding the developmental stages of theory of mind in children leaded researchers on two Connected research problems. In one hand, the link between executive function and theory of mind, and on the other hand, the relationship of theory of mind and syntax processing. These two lines of research involved a great literature, full of important results, despite certain level of disagreement between researchers. For a long time, these two research perspectives continue to grow up separately despite research conclusion suggesting that the three variables should implicate same developmental period. Indeed, our goal was to study the relation between theory of mind, executive function, and language via a unique research question. It supposed that between executive function and language, one of the two variables could play a critical role in the relationship between theory of mind and the other variable. Thus, 112 children aged between three and six years old were recruited for completing a receptive and an expressive vocabulary task, a syntax understanding task, a theory of mind task, and three executive function tasks (inhibition, cognitive flexibility and working memory). The results showed significant correlations between performance on theory of mind task and performance on executive function domain tasks, except for cognitive flexibility task. We also found significant correlations between success on theory of mind task and performance in all language tasks. Multiple regression analysis justified only syntax and general abilities of language as possible predictors of theory of mind performance in our preschool age children sample. The results were discussed in the perspective of a great role of language abilities in theory of mind development. We also discussed possible reasons that could explain the non-significance of executive domains in predicting theory of mind performance, and the meaning of our results for the literature.

Keywords: child development, executive function, general language, syntax, theory of mind

Procedia PDF Downloads 62

Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

Abstract:

Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 155

Authors: Yamin Sayyari

Abstract:

In this paper, we generalized the Jensen's inequality for m-convex functions and also we present a correction of Jensen's inequality which is a better than the generalization of this inequality for m-convex functions. Finally, we have found new lower and new upper bounds for Jensen's discrete inequality.

Keywords: Jensen's inequality, m-convex function, Convex function, Inequality

Procedia PDF Downloads 144

Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

Abstract:

This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

Procedia PDF Downloads 394

Authors: Ahmed Noor Al-Qayyim

Abstract:

During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

Procedia PDF Downloads 346

Authors: Umar D. M., Aminu A. M., Izaddeen K. Y.

Abstract:

Deployments of mini macrocell base stations also referred to as femtocells, improve the quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with an in-depth focus on the most important aspect of mobility management -handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function, and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time, as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength-based handover decision algorithm.

Keywords: user-equipment, radio signal service, long term evolution, mobility management, handoff

Procedia PDF Downloads 123

Authors: Adrian Millea

Abstract:

In hierarchical reinforcement learning, one of the main issues encountered is the discovery of subgoal states or options (which are policies reaching subgoal states) by partitioning the environment in a meaningful way. This partitioning usually requires an expensive global clustering operation or eigendecomposition of the Laplacian of the states graph. We propose a local solution to this issue, much more efficient than algorithms using global information, which successfully discovers subgoal states by computing a simple function, which we call heterogeneity for each state as a function of its neighbors. Moreover, we construct a value function using the difference in heterogeneity from one step to the next, as reward, such that we are able to explore the state space much more efficiently than say epsilon-greedy. The same principle can then be applied to higher level of the hierarchy, where now states are subgoals discovered at the level below.

Keywords: exploration, hierarchical reinforcement learning, locality, options, value functions

Procedia PDF Downloads 171

Authors: Aman Sharma, Sonali Sengupta

Abstract:

The study explores the utility of Bayesian optimization in tuning the physical and chemical parameters of reactions in an offline experimental setup. A comparative analysis of the influence of the acquisition function on the optimization performance is also studied. For proxy first and second-order reactions, the results are indifferent to the acquisition function used, whereas, while studying the parameters for oxidative desulphurization of thiophene in an offline setup, upper confidence bound (UCB) provides faster convergence along with a marginal trade-off in the maximum conversion achieved. The work also demarcates the critical number of independent parameters and input observations required for both sequential and offline reaction setups to yield tangible results.

Keywords: acquisition function, Bayesian optimization, desulfurization, kinetics, thiophene

Procedia PDF Downloads 182

Authors: Abhimanyu Pati, Prabir K. Bandyopadhyay

Abstract:

The paper intends to highlight the significance of Digital Manufacturing (DM) strategy in support and achievement of business strategy and goals of any manufacturing organization. Towards this end, DM initiatives have been given a process perspective, while not undermining its technological significance, with a view to link its benefits directly with fulfilment of customer needs and expectations in a responsive and cost-effective manner. A digital process model has been proposed to categorize digitally enabled organizational processes with a view to create synergistic groups, which adopt and use digital tools having similar characteristics and functionalities. This will throw future opportunities for researchers and developers to create a unified technology environment for integration and orchestration of processes. Secondly, an effort has been made to apply “what” and “how” features of Quality Function Deployment (QFD) framework to establish the relationship between customers’ needs – both for external and internal customers, and the features of various digital processes, which support for the achievement of these customer expectations. The paper finally concludes that in the present highly competitive environment, business organizations cannot thrive to sustain unless they understand the significance of digital strategy and integrate it with their business strategy with a clearly defined implementation roadmap. A process-oriented approach to DM strategy will help business executives and leaders to appreciate its value propositions and its direct link to organization’s competitiveness.

Keywords: knowledge management, cloud computing, knowledge management approaches, cloud-based knowledge management

Procedia PDF Downloads 307

Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

Abstract:

The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

Procedia PDF Downloads 84

Authors: Truong Nguyen Luan Vu, Le Hieu Giang, Le Linh

Abstract:

The FOPI controller is proposed based on the main properties of the decoupling control scheme, as well as the fractional calculus. By using the simplified decoupling technique, the transfer function of decoupled apparent process is firstly separated into a set of n equivalent independent processes in terms of a ratio of the diagonal elements of original open-loop transfer function to those of dynamic relative gain array and the fraction – order PI controller is then developed for each control loops due to the Bode’s ideal transfer function that gives the desired fractional closed-loop response in the frequency domain. The simulation studies were carried out to evaluate the proposed design approach in a fair compared with the other existing methods in accordance with the structured singular value (SSV) theory that used to measure the robust stability of control systems under multiplicative output uncertainty. The simulation results indicate that the proposed method consistently performs well with fast and well-balanced closed-loop time responses.

Keywords: ideal transfer function of bode, fractional calculus, fractional order proportional integral (FOPI) controller, decoupling control system

Procedia PDF Downloads 330

Authors: Boukari Nassim

Abstract:

This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

Procedia PDF Downloads 344