Search results for: mode choice models

Authors: Hao Wang, Shuguo Pan

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The Global Navigation Satellite System (GNSS) signal received by the dynamic vehicle in the harsh environment will be frequently interfered with and blocked, which generates gross error affecting the positioning accuracy of the GNSS/Inertial Navigation System (INS) integrated navigation. Therefore, this paper put forward an improved robust Cubature Kalman filter (CKF) algorithm for single-frequency GNSS/INS tightly coupled system ambiguity resolution. Firstly, the dynamic model and measurement model of a single-frequency GNSS/INS tightly coupled system was established, and the method for GNSS integer ambiguity resolution with INS aided is studied. Then, we analyzed the influence of pseudo-range observation with gross error on GNSS/INS integrated positioning accuracy. To reduce the influence of outliers, this paper improved the CKF algorithm and realized an intelligent selection of robust strategies by judging the ill-conditioned matrix. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm based on the double-differenced solution mode. The experiment has proved the improved robust algorithm can greatly weaken the influence of separate, continuous, and hybrid observation anomalies for enhancing the reliability and accuracy of GNSS/INS tightly coupled navigation solutions.

Keywords: GNSS/INS integrated navigation, ambiguity resolution, Cubature Kalman filter, Robust algorithm

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Authors: Jia-Jia He, Lin Jiang, Jin-Hua Sun

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Rigid polyurethane foam (RPU) has been extensively applied in building insulation system, yet with high flammability for being easily ignited by high temperature spark or radiative heat flux from other flaming materials or surrounding building facade. Using a cone calorimeter by Fire Testing Technology and thermal couple tree, this study systematically investigated the effect of radiative heat flux on the ignition time and characteristic temperature distribution during RPU combustion under different heat fluxes gradient (12, 15, 20, 25, 30, 35, 40, 45, and 50 kW/m²) with spark ignition/ignition by radiation. The ignition time decreases proportionally with increase of external heat flux, meanwhile increasing the external heat flux raises the peak heat release rate and impresses on the vertical temperature distribution greatly. The critical ignition heat flux is found to be 15 and 25 kW/m² for spark ignition and radiative ignition, respectively. Based on previous experienced ignition formula, a methodology to predict ignition times in both modes has been developed theoretically. By analyzing the heat transfer mechanism around the sample surroundings, both radiation from cone calorimeter and convection flow are considered and calculated theoretically. The experimental ignition times agree well with the theoretical ones in both radiative and convective conditions; however, the observed critical ignition heat flux is higher than the calculated one under piloted-ignition mode because the heat loss process, especially in lower heat flux radiation, is not considered in this developed methodology.

Keywords: rigid polyurethane foam, cone calorimeter, ignition time, external heat flux

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Opeyemi Atiba-Oyewo, Maurice S. Onya, Christian Wolkersdorfer

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Nanostructure formation and characterization of eco-friendly banana peels nanosorbent are thoroughly described in this paper. The transformation of material during mechanical milling to enhance certain properties such as changes in microstructure and surface area to solve the current problems involving water pollution and water quality were studied. The mechanical milling was employed using planetary continuous milling machine and ethanol as process control agent, the sample were taken at time interval between 10 h to 30 h to examine the structural changes. The samples were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infra-red (FTIR), Transmission electron microscopy (TEM) and Brunauer Emmett and teller (BET). Results revealed that the three typical structures with different grain-size, lattice strain and shapes were observed, and the deformation mechanisms in these structures were found to be different, further particles fracturing results to surface area increment which was confirmed by Brunauer Emmett and teller (BET) analysis. X-ray diffraction (XRD) shows high densities of dislocations in large crystallites, implying that dislocation slip is the dominant deformation mechanism. Scanning electron microscopy revealed the morphological properties of the materials at different milling time, nanostructure of the particles and fibres were confirmed by Transmission electron microscopy and FT-IR identified the functional groups responsible for its capacity to coordinate and remove metal ions, such as the carboxylic and amine groups at absorption bands of 1730 and 889 cm-1, respectively. However, the choice of this sorbent material for the sorption of any contaminants will depend on the composition of the effluent to be treated.

Keywords: banana peels, eco-friendly, mechanical milling, nanosorbent, nanostructure water quality

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Meenu Kaushik, Ayon K. Bandhoyadhayay, Lalit M. Joshi

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Inductive output tubes (IOTs) are widely used as microwave power amplifiers for broadcast and scientific applications. It is capable of amplifying radio frequency (RF) power with very good efficiency. Its compactness, reliability, high efficiency, high linearity and low operating cost make this device suitable for various applications. The device consists of an integrated structure of electron gun and RF cavity, collector and focusing structure. The working principle of IOT is a combination of triode and klystron. The cathode lies in the electron gun produces a stream of electrons. A control grid is placed in close proximity to the cathode. Basically, the input part of IOT is the integrated structure of gridded electron gun which acts as an input cavity thereby providing the interaction gap where the input RF signal is applied to make it interact with the produced electron beam for supporting the amplification phenomena. The paper presents the design, fabrication and testing of a radial re-entrant cavity for implementing in the input structure of IOT at 350 MHz operating frequency. The model’s suitability has been discussed and a generalized mathematical relation has been introduced for getting the proper transverse magnetic (TM) resonating mode in the radial narrow gap RF cavities. The structural modeling has been carried out in CST and SUPERFISH codes. The cavity is fabricated with the Aluminum material and the RF characterization is done using vector network analyzer (VNA) and the results are presented for the resonant frequency peaks obtained in VNA.

Keywords: inductive output tubes, IOT, radial cavity, coaxial cavity, particle accelerators

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Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

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Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

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Authors: Zhao Liu, Kang Cao

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Strategic spatial planning, which is taken as an effective and competitive way for the governors of the city to improve the development and management level of a city, has been blooming in recent years all over the world. In the context of globalization and informatization, strategic spatial planning must transfer its focus on three different levels: global, regional and urban. Internal and external changes in environmental conditions lead to new advances in strategic planning both theoretically and practically. However, such advances or changes respond differently to cities on account of different dynamic mechanisms. This article aims at two cities of Tianjin in China and Melbourne in Australia, through a comparative study on strategic planning, to explore the differentiation of mechanisms in urban planning. By comparison and exploration, the purpose of this article is to exhibit two different planning worlds, western and Chinese, in a new way. The article can be divided into four parts. The first part outlines strategic planning transformations in the new era on three levels, generally analysing the internal and external environmental factors of today. The second part indicates the concepts of strategic planning theoretically, demonstrating briefly its development background and process in western and China, respectively. The third part takes Tianjin and Melbourne urban strategic spatial planning as examples to mainly carry on the contrast research from the aspects of strategic planning mode, competitive mechanism, contents, strategy implementation and management. It is expected to summarize the differences and similarities of the two plans, meanwhile, to explore the inherent factors or mechanisms probably spatial, material, political and etc., which affect cities in the course of urban planning. The final part is a summary of general mechanisms of planning from the perspective of strategic spatial planning.

Keywords: differentiation, strategic planning, Melbourne, Australia, Tianjin, China

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Authors: Adrian Reynaldo Sudirman, Siti Farida, Aisyah Aminy Maulidina, Caren Andika Surbakti

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Sedentary lifestyle and imbalance consumption pattern has made metabolic syndrome as the global time bomb phenomenon in the world. The increasing tendency of people in consuming high amount of fructose and cholesterol food has worsened this issue in the society. Pancreas steatosis become one of the most comorbid when early diagnosis and prompt treatment has not been applied on hyperglycemic and hyperlipidemic condition in metabolic syndrome patient. Gemfibrozil become the drug of choice to prevent this issue, yet the efficacy of this regiment was still questionable. Acalypha indica Linn. is the herb that has protective effect on hyperlipidemic and hyperglycemic condition. This study was aimed to compare therapeutic effect of gemfibrozil (G) and Acalypha indica Linn. (AI) on high fructose and cholesterol diet-induced pancreas steatosis in Sprague-Dawley mice. The post induction mice were divided into four groups: control, gemfibrozil, AI extract, and G+AI combination regiment. Each group received four weeks intervention. The result of statistical analysis using the One-Way ANOVA test and Tukey Post Hoc test showed significant decrease in pancreatic steatosis between the control group and administered Acalypha indica group (p = 0.004, 95% CI: 0.170-0.959) and the group administered with a combination of Gemfibrozil-Acalypha indica (p = 0.023, 95% CI: 0.537-0.813). The protective effect of Acalypha indica Linn. shows that this plant has the potential as therapeutic option in overcoming the condition of pancreas steatosis in metabolic syndrome.

Keywords: Acalypha Indica Linn., Cholesterol, Fructose, Gemfibrozil, Pancreas Steatosis

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Authors: R. Mkahl, A. Nait-Sidi-Moh, M. Wack

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Batteries of electric vehicles (BEV) are becoming more attractive with the advancement of new battery technologies and promotion of electric vehicles. BEV batteries are recharged on board vehicles using either the grid (G2V for Grid to Vehicle) or renewable energies in a stand-alone application (H2V for Home to Vehicle). This paper deals with the modeling, sizing and control of a photo voltaic stand-alone application that can charge the BEV at home. The modeling approach and developed mathematical models describing the system components are detailed. Simulation and experimental results are presented and commented.

Keywords: electric vehicles, photovoltaic energy, lead-acid batteries, charging process, modeling, simulation, experimental tests

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Authors: Ashenafi Beyene Fanta, Daniel Makina

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Economic theory predicts that finance promotes economic growth. Although the finance-growth link is among the most researched areas in financial economics, our understanding of the link between the two is still incomplete. This is caused by, among others, wrong econometric specifications, using weak proxies of financial development, and inability to address the endogeneity problem. Studies on the finance growth link in South Africa consistently report economic growth driving financial development. Early studies found that economic growth drives financial development in South Africa, and recent studies have confirmed this using different econometric models. However, the monetary aggregate (i.e. M2) utilized used in these studies is considered a weak proxy for financial development. Furthermore, the fact that the models employed do not address the endogeneity problem in the finance-growth link casts doubt on the validity of the conclusions. For this reason, the current study examines the finance growth link in South Africa using data for the period 1990 to 2011 by employing a generalized method of moments (GMM) technique that is capable of addressing endogeneity, simultaneity and omitted variable bias problems. Unlike previous cross country and country case studies that have also used the same technique, our contribution is that we account for the development of bond markets and non-bank financial institutions rather than being limited to stock market and banking sector development. We find that bond market development affects economic growth in South Africa, and no similar effect is observed for the bank and non-bank financial intermediaries and the stock market. Our findings show that examination of individual elements of the financial system is important in understanding the unique effect of each on growth. The observation that bond markets rather than private credit and stock market development promotes economic growth in South Africa induces an intriguing question as to what unique roles bond markets play that the intermediaries and equity markets are unable to play. Crucially, our results support observations in the literature that using appropriate measures of financial development is critical for policy advice. They also support the suggestion that individual elements of the financial system need to be studied separately to consider their unique roles in advancing economic growth. We believe that our understanding of the channels through which bond market contribute to growth would be a fertile ground for future research.

Keywords: bond market, finance, financial sector, growth

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Hakimeh Sharififard, Mansooreh Soleimani

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In this work, the magnetic activated carbon nanocomposite (Fe-CAC) has been synthesized by anchorage iron hydr(oxide) nanoparticles onto commercial activated carbon (CAC) surface and characterized using BET, XRF, SEM techniques. The influence of various removal parameters such as pH, contact time and initial concentration of vanadium on vanadium removal was evaluated using CAC and Fe-CAC in batch method. The sorption isotherms were studied using Langmuir, Freundlich and Dubinin–Radushkevich (D–R) isotherm models. These equilibrium data were well described by the Freundlich model. Results showed that CAC had the vanadium adsorption capacity of 37.87 mg/g, while the Fe-AC was able to adsorb 119.01 mg/g of vanadium. Kinetic data was found to confirm pseudo-second-order kinetic model for both adsorbents.

Keywords: magnetic activated carbon, remove, vanadium, nanocomposite, freundlich

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Authors: Masayuki Higashino, Toshiya Kawato, Takao Kawamura

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A monolithic service is based on the N-tier architecture in many cases. In order to divide a monolithic service into microservices, it is necessary to redefine a model as a new microservice by extracting and merging existing models across layers. Refactoring a monolithic service into microservices requires advanced technical capabilities, and it is a difficult way. This paper proposes a design and concept to ease the migration of a monolithic service to microservices using the mobile agent technology. Our proposed approach, mobile agents-based design and concept, enables to ease dividing and merging services.

Keywords: mobile agent, microservice, web service, distributed system

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Authors: Valentin Nickolai, Florian Pfeffel, Christian Louis Kühner

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In many industrialized nations, the demand for skilled workers rises, causing the current market for employees to be more candidate-driven than employer-driven. Therefore, losing highly skilled and experienced employees due to early or partial retirement negatively impacts firms. Therefore, finding new ways to incentivize older employees (Silver Workers) to stay longer with the company and in their job can be crucial for the success of a firm. This study analyzes how working remotely can be a valid incentive for experienced Silver Workers to stay in their job and instead work from home with more flexible working hours. An online survey with n = 684 respondents, who are employed in the service sector, has been conducted based on 13 constructs that influence job satisfaction. These have been further categorized into three groups “classic influencing factors,” “influencing factors changed by remote working,” and new remote working influencing factors,” and were analyzed using structural equation modeling (SEM). Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). It was shown in the SEM-analysis that the influencing factor on job satisfaction, “identification with the work,” is the most significant with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis also shows that the identification with the work is the most significant factor in all three work models mentioned above and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees between the ages of 56 and 65 years have the highest job satisfaction when working entirely from home or remotely. Furthermore, their job satisfaction score of 5.4 on a scale from 1 (very dissatisfied) to 7 (very satisfied) is the highest amongst all age groups in any of the three work models. Due to the significantly higher job satisfaction, it can be argued that giving Silver Workers the offer to work from home or remotely can incentivize them not to opt for early retirement or partial retirement but to stay in their job full-time Furthermore, these findings can indicate that employees in the Silver Worker age are much more inclined to leave their job for early retirement if they have to entirely work in the office.

Keywords: home office, remote work instead of early or partial retirement, silver worker, structural equation modeling

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Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

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Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

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Authors: Yutae Lee

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In this paper, we consider the performance and availability of a redundancy model. The redundancy model is a form of resilience that ensures service availability in the event of component failure. This paper considers a 2N redundancy model. In the model there are at most one active service unit and at most one standby service unit. The active one is providing the service while the standby is prepared to take over the active role when the active fails. We design our analysis model using Stochastic Reward Nets, and then evaluate the performance and availability of 2N redundancy model using Stochastic Petri Net Package (SPNP).

Keywords: availability, performance, stochastic reward net, 2N redundancy

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Authors: Mikhail V. Khachaturyan, Inga A. Koryagina, Maria Nikishova

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The study investigates the impact of the ongoing financial crisis, started in the 2^nd half of 2014, on marketing budgets spent by Fast-moving consumer goods companies. In these conditions, special importance is given to efficient possessory risk management systems. The main objective for establishing and developing possessory risk management systems for FMCG companies in a crisis is to analyze the data relating to the external environment and consumer behavior in a crisis. Another important objective for possessory risk management systems of FMCG companies is to develop measures and mechanisms to maintain and stimulate sales. In this regard, analysis of risks and threats which consumers define as the main reasons affecting their level of consumption become important. It is obvious that in crisis conditions the effective risk management systems responsible for development and implementation of strategies for consumer demand stimulation, as well as the identification, analysis, assessment and management of other types of risks of economic security will be the key to sustainability of a company. In terms of financial and economic crisis, the problem of forming and developing possessory risk management systems becomes critical not only in the context of management models of FMCG companies, but for all the companies operating in other sectors of the Russian economy. This study attempts to analyze the specifics of formation and development of company possessory risk management systems. In the modern economy, special importance among all the types of owner’s risks has the risk of reduction in consumer activity. This type of risk is common not only for the consumer goods trade. Study of consumer activity decline is especially important for Russia due to domestic market of consumer goods being still in the development stage, despite its significant growth. In this regard, it is especially important to form and develop possessory risk management systems for FMCG companies. The authors offer their own interpretation of the process of forming and developing possessory risk management systems within owner’s management models of FMCG companies as well as in Russian economy in general. Proposed methods and mechanisms of problem analysis of formation and development of possessory risk management systems in FMCG companies and the results received can be helpful for researchers interested in problems of consumer goods market development in Russia and overseas.

Keywords: FMCG companies, marketing budget, risk management, owner, Russian economy, organization, formation, development, system

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Authors: Ahmad Qabaha

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This paper teases out the ways in which the constructs of placelessness and mobility are articulated in modern exilic Palestinian literature and American expatriate writing. The mode of placelessness embodied by the characters of each of my two authors (expatriation in Paris Montparnasse for Hemingway's characters and involuntary exile in Europe for Jabra's) will be elicited from the orientations of their mobility. This paper argues that the proclivity of Hemingway's characters for centrifugal motion (moving away from the centre) is a strategy to increase their sense of freedom that space (expatriation), rather than place, secures. By contrast, the movement of Jabra's characters is centripetal (moving or tending to move towards the centre). It echoes his Palestinian characters' recurrent futile attempts to return to Palestine, and it expresses their resistance to the lures of exile. This paper asserts that the involuntarily exiled character (the Palestinian in this case) is a figure obsessed with and ache for a place, roots and 'a dwelling' from which he was uprooted - a place that defines his authentic existence and frames his understanding of the world in Martin Heidegger's, Simone Weil's and Gaston Bachelard's senses. In parallel, this paper explains that the expatriate character (the American in this case) views place as confining, restrictive and disagreeable, while mobility as a figure of freedom, resistance, wealth, self-fashioning and understanding/inhabiting the world. Place in this sense is associated with past, tradition, ideology, existence and being. Mobility is equivalent with modernity, progression, innovation, self-fashioning and freedom.

Keywords: American expatriate literature, exilic Palestinian literature, mobility, place, placelessness

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Authors: Jorge Prada, Christina Cordes, Carsten Harms, Walter Lang

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The development of microfluidic-based biosensors over the last years has shown an increasing employ of thermoplastic polymers as constitutive material. Their low-cost production, high replication fidelity, biocompatibility and optical-mechanical properties are sought after for the implementation of disposable albeit functional lab-on-chip solutions. Among the range of thermoplastic materials on use, the Cyclo-Olefin Copolymer (COC) stands out due to its optical transparency, which makes it a frequent choice as manufacturing material for fluorescence-based biosensors. Moreover, several processing techniques to complete a closed COC microfluidic biosensor have been discussed in the literature. The reported techniques differ however in their implementation, and therefore potentially add more or less complexity when using it in a mass production process. This work introduces and reports results on the application of a purely thermal bonding process between COC substrates, which were produced by the hot-embossing process, and COC foils containing screen-printed circuits. The proposed procedure takes advantage of the transition temperature difference between two COC grades foils to accomplish the sealing of the microfluidic channels. Patterned heat injection to the COC foil through the COC substrate is applied, resulting in consistent channel geometry uniformity. Measurements on bond strength and bursting pressure are shown, suggesting that this purely thermal bonding process potentially renders a technique which can be easily adapted into the thermoplastic microfluidic chip production workflow, while enables a low-cost as well as high-quality COC biosensor manufacturing process.

Keywords: biosensor, cyclo-olefin copolymer, hot embossing, thermal bonding, thermoplastics

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Authors: V. A. Dubovsky, V. V. Savchenko, A. A. Baryskevich

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The current trend in the automotive industry towards automatic vehicles is creating new challenges related to human factors. This occurs due to the fact that the driver is increasingly relieved of the need to be constantly involved in driving the vehicle, which can negatively impact his/her situation awareness when manual control is required, and decrease driving skills and abilities. These new problems need to be studied in order to provide road safety during the transition towards self-driving vehicles. For this purpose, it is important to develop an appropriate conceptual model of the interaction between the driver and the automated vehicle, which could serve as a theoretical basis for the development of mathematical and simulation models to explore different aspects of driver behaviour in different road situations. Well-known driver behaviour models describe the impact of different stages of the driver's cognitive process on driving performance but do not describe how the driver controls and adjusts his actions. A more complete description of the driver's cognitive process, including the evaluation of the results of his/her actions, will make it possible to more accurately model various aspects of the human factor in different road situations. This paper presents a conceptual model of the 'driver – highly automated vehicle' system based on the P.K. Anokhin's theory of functional systems, which is a theoretical framework for describing internal processes in purposeful living systems based on such notions as goal, desired and actual results of the purposeful activity. A central feature of the proposed model is a dynamic coupling mechanism between the decision-making of a driver to perform a particular action and changes of road conditions due to driver’s actions. This mechanism is based on the stage by stage evaluation of the deviations of the actual values of the driver’s action results parameters from the expected values. The overall functional structure of the highly automated vehicle in the proposed model includes a driver/vehicle/environment state analyzer to coordinate the interaction between driver and vehicle. The proposed conceptual model can be used as a framework to investigate different aspects of human factors in transitions between automated and manual driving for future improvements in driving safety, and for understanding how driver-vehicle interface must be designed for comfort and safety. A major finding of this study is the demonstration that the theory of functional systems is promising and has the potential to describe the interaction of the driver with the vehicle and the environment.

Keywords: automated vehicle, driver behavior, human factors, human-machine system

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Authors: Xiaoqing Li

Abstract:

Social entrepreneurship drives the global movement as social enterprises create best ways to satisfy social needs through connecting international resources. However, what determines social enterprises to internationalize is underexplored. This study aims to answer this question by conducting a systematic review of studies of past 20 years on social enterprises' internationalization. Findings reveal that factors at the individual (entrepreneur), firm, and environment (home and host country) levels determine the degree of social enterprises' internationalization. Future research is challenged by: a. adopting an integrated approach examining the three levels to explain social enterprises' internationalization; b. the different nature of social enterprises from commercial businesses demands scholars to refine and develop appropriate theoretical models to capture the dynamism of social enterprises' internationalization behavior.

Keywords: determinants, entrepreneurship, internationalization, social enterprises

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Authors: A. Brahma

Abstract:

Analysis of deferred deformations of concrete under sustained load shows that the creep has a leading role on deferred deformations of concrete structures. Knowledge of the creep characteristics of concrete is a Necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable deformation in pre-stressed concrete or reinforced and the appropriate steps can be taken in design to accommodate this movement. In this study, we propose a prediction model that involves the acting principal parameters on the deferred behaviour of concrete structures. For the estimation of the model parameters Levenberg-Marquardt method has proven very satisfactory. A confrontation between the experimental results and the predictions of models designed shows that it is well suited to describe the evolution of the creep of concrete structures.

Keywords: concrete structure, creep, modelling, prediction

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Authors: Tulasi Rayasa, Phani Kumar Pullela

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A systematic review is a research method that involves collecting and evaluating the information on a specific topic in order to provide a comprehensive and unbiased review. This type of review aims to improve the software development process by ensuring that the research is thorough and accurate. To ensure objectivity, it is important to follow systematic guidelines and consider multiple sources, such as literature reviews, interviews, and surveys. The evaluation process should also be streamlined by incorporating research from journals and other sources, such as grey literature. The main goal of a systematic review is to identify the consistency of current models in the field of computer application and software engineering.

Keywords: computer application, software engineering, process research, data science

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Authors: Temidayo James Aransiola, Vania Ceccato, Marcelo Justus

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This paper investigates the effect of absolute deprivation (proxy unemployment) and relative deprivation (proxy income inequality) on homicide levels in Brazil. A database from the Brazilian Information System about Mortality and Census of the year 2000 and 2010 was used to estimate negative binomial models of homicide levels controlling for socioeconomic, demographic and geographic factors. Findings show that unemployment and income inequality affect homicides levels and that the effect of the former is more pronounced compared to the latter. Moreover, the combination of income inequality and unemployment exacerbates the overall effect of deprivation on homicide levels.

Keywords: deprivation, inequality, interaction, unemployment, violence

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Authors: Simon Espigolé, Igor Shalyminov, Helen Hastie

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Deep machine learning techniques including deep neural networks (DNN) have been used to model language and dialogue for conversational agents to perform tasks, such as giving technical support and also for general chit-chat. They have been shown to be capable of generating long, diverse and coherent sentences in end-to-end dialogue systems and natural language generation. However, these systems tend to imitate the training data and will only generate the concepts and language within the scope of what they have been trained on. This work explores how deep neural networks can be used in a task that would normally require human creativity, whereby the human would read the movie description and/or watch the movie and come up with a compelling, interesting movie title. This task differs from simple summarization in that the movie title may not necessarily be derivable from the content or semantics of the movie description. Here, we train a type of DNN called a sequence-to-sequence model (seq2seq) that takes as input a short textual movie description and some information on e.g. genre of the movie. It then learns to output a movie title. The idea is that the DNN will learn certain techniques and approaches that the human movie titler may deploy that may not be immediately obvious to the human-eye. To give an example of a generated movie title, for the movie synopsis: ‘A hitman concludes his legacy with one more job, only to discover he may be the one getting hit.’; the original, true title is ‘The Driver’ and the one generated by the model is ‘The Masquerade’. A human evaluation was conducted where the DNN output was compared to the true human-generated title, as well as a number of baselines, on three 5-point Likert scales: ‘creativity’, ‘naturalness’ and ‘suitability’. Subjects were also asked which of the two systems they preferred. The scores of the DNN model were comparable to the scores of the human-generated movie title, with means m=3.11, m=3.12, respectively. There is room for improvement in these models as they were rated significantly less ‘natural’ and ‘suitable’ when compared to the human title. In addition, the human-generated title was preferred overall 58% of the time when pitted against the DNN model. These results, however, are encouraging given the comparison with a highly-considered, well-crafted human-generated movie title. Movie titles go through a rigorous process of assessment by experts and focus groups, who have watched the movie. This process is in place due to the large amount of money at stake and the importance of creating an effective title that captures the audiences’ attention. Our work shows progress towards automating this process, which in turn may lead to a better understanding of creativity itself.

Keywords: creativity, deep machine learning, natural language generation, movies

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Authors: Radovan Cobanovic, Milica Rankov-Sicar

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The fresh cake is in the group of perishable food which cannot be kept a long period of time. The study of sustainability has been done in order to extend the shelf-life of the product which was 10 days. According to the plan of sustainability, it was defined that 5 samples had to be stored for 20 days at max +8°C and analyzed every 5th day from the day of reception until the 20th day. The shelf life of cake has expired during the study of sustainability in the period between 10th and 20th day of analyses. Cake samples were subjected to sensory analysis (appearance, odor, taste, color, aroma) and bacteriological analysis (Listeria monocytogenes, Salmonella spp. and Enterobacteriaceae) according to Serbian state regulation. All analysis were tested according to ISO methodology: sensory analysis ISO 6658, Listeria monocytogenes ISO 11290-1, Salmonella spp ISO 6579, and Enterobacteriaceae ISO 21258-2. Analyses showed that after ten days of storage at a temperature defined by the manufacturers and within the product's shelf life, the cake did not have any noticeable changes in sensory characteristics. Smell and taste are unaffected there was no presence of strange smell or taste. As far as microbiological analyses are concerned, neither one pathogen was detected and number of Enterobacteriaceae was at level less than 102 cfu/g. After expiry of shelf life in a period of 15th and 20th day of storage, the sensory analysis showed the presence of strange sour-milky smell and rancid taste. Concerning microbiological analyses, there still were not positive results for pathogen microorganisms but the number of Enterobacteriaceae was at level more than 103cfu/g. Reviewing the results of sensory analysis indicates that it is not recommended to extend the shelf-life of the product comparing to the already defined shelf-life because occurred changes may adversely affect the consumer desire for the choice of this product.

Keywords: confectionary product, extension of shelf life, sensory and microbiological analyses, sustainability

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Authors: J. Satya Eswari, J. Sekhar Babub, Meena Murmu, Govardhan Bhat

Abstract:

Electrical Discharge Machining (EDM) is an unconventional manufacturing process based on removal of material from a part by means of a series of repeated electrical sparks created by electric pulse generators at short intervals between a electrode tool and the part to be machined emmersed in dielectric fluid. In this paper, a study will be performed on the influence of the factors of peak current, pulse on time, interval time and power supply voltage. The output responses measured were material removal rate (MRR) and surface roughness. Finally, the parameters were optimized for maximum MRR with the desired surface roughness. RSM involves establishing mathematical relations between the design variables and the resulting responses and optimizing the process conditions. RSM is not free from problems when it is applied to multi-factor and multi-response situations. Design of experiments (DOE) technique to select the optimum machining conditions for machining AISI 4140 using EDM. The purpose of this paper is to determine the optimal factors of the electro-discharge machining (EDM) process investigate feasibility of design of experiment techniques. The work pieces used were rectangular plates of AISI 4140 grade steel alloy. The study of optimized settings of key machining factors like pulse on time, gap voltage, flushing pressure, input current and duty cycle on the material removal, surface roughness is been carried out using central composite design. The objective is to maximize the Material removal rate (MRR). Central composite design data is used to develop second order polynomial models with interaction terms. The insignificant coefficients’ are eliminated with these models by using student t test and F test for the goodness of fit. CCD is first used to establish the determine the optimal factors of the electro-discharge machining (EDM) for maximizing the MRR. The responses are further treated through a objective function to establish the same set of key machining factors to satisfy the optimization problem of the electro-discharge machining (EDM) process. The results demonstrate the better performance of CCD data based RSM for optimizing the electro-discharge machining (EDM) process.

Keywords: electric discharge machining (EDM), modeling, optimization, CCRD

Procedia PDF Downloads 333