Search results for: password based key derivation

Authors: M. Caruffo, P. Navarrete, C. G. Feijoo, L. Sáenz

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Disease prevention through the use of vaccines has been crucial to achieve the current level of production in the salmon industry. However, vaccines have been developed based largely on inactivated bacterial formulations, using the whole pathogen. These formulations have demonstrated excellent efficacy against extracellular bacterial pathogens. However diseases with the greatest economic impacts correspond to intracellular bacterial and viral pathogens, vaccines based on these types of agents have shown a discrete effectiveness. It is for these reasons that the development of subunit vaccines based on defined antigens offers a promising solution. The main problem is that subunit vaccines offer a low immunogenicity, since they lack immunostimulatory elements, so that the development of new adjuvants platforms becomes an important challenge for this type of formulations. We evaluate the effect of a formulation based on proteoliposomes of Vibrio anguillarum administered by immersion as a new adjuvant strategy, allowing efficient stimulation of the innate immune system. Proteoliposomes physicochemical properties were evaluated in its ability to produce an inflammatory process. Using zebrafish (Danio rerio) larvae as a model species and the transgenic line (Tg(mpx: GFP)i114) allowed us to track the neutrophil migration in real time. Additionally we evaluated the gene expression of some molecular markers involved in the development of the innate immune response characterizing the adjuvant capacity of the formulation.

Keywords: adjuvants, vaccine development, zebrafish, innate immunity

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Authors: Helen Dilman, Eyal Oz, Shmuel Hayun, Nahum Frage

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The conventional approach for manufacturing silicon carbide and boron carbide reaction bonded composites is based on infiltrating a ceramic porous preform with molten silicon. The relatively high melting temperature of the silicon infiltrating medium is a drawback of the process. The present contribution is concerned with an approach that allows obtaining reaction bonded composites by pressure-less infiltration at a significantly lower (850-1000oC) temperature range. This approach was applied for the fabrication of fully dense SiC/(Si-Al) and (SiC+B4C)/(Si-Al) composites. The key feature of the approach is based on using Si alloys with low melting temperature and the Mg-vapor atmosphere, under which an adequate wetting between ceramics and liquid alloys for the infiltration process is achieved. In the first set of the experiments ceramic performs compacted from multimodal SiC powders (with the green density of about 27 vol. %) without free carbon addition were infiltrated by Si-20%Al alloy at 950oC. In the second set, 19 vol. % of a fine boron carbide powder was added to SiC powders as a source of carbon. The green density of the SiC-B4C preforms was about 23-25 vol. %. In both cases, successful infiltration was achieved and the composites were fully dense. The density of the composites was about 3g/cm3. For the SiC based composites the hardness value was 750±150HV, Young modulus-280GPa and bending strength-240±30MPa. These values for (SiC-B4C)/(Si-Al) composites (1460±200HV, 317GPa and 360±20MPa) were significantly higher due to the formation of novel ceramics phases. Microstructural characteristics of the composites and their phase composition will be discussed.

Keywords: boron carbide, composites, infiltration, low temperatures, silicon carbide

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Authors: Mohamed Haffar, Muhammad Abdul Aziz, Ahmad Ghoneim

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The importance of having a good organizational culture that supports employee job satisfaction has fascinated both the business and academic world because of a tantalizing promise: culture can be fundamental to the enhancement of financial performance. This promise has led to growing interest for both researchers and practitioners in attempting to understand the influence of organizational culture on employees’ satisfaction and organizational performance. Even though the relationship between organizational culture and employee job satisfaction have gained attention in the literature, the majority of studies have been conducted within manufacturing organizations and tend to oversee the impact of culture on employee job satisfaction in a service-based environment. Thus, the main driving force of this study was to explore the role of organizational culture types in facilitating employee job satisfaction at Emerald Publishing Group. Interviews qualitative data analysis indicated that Emerald’s culture dominated by adhocracy and clan culture values. In addition, the findings provided evidence, which demonstrated that group and adhocracy organizational culture types play key roles in facilitating employee job satisfaction in a service-based environment.

Keywords: employee satisfaction, organizational culture, performance, service based environment

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Authors: Riki H. Patel, Arpan Desia, Trushit Upadhayay

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The demand of compact antenna is ever increasing since the inception of wireless communication devices. In the age of wireless communication, requirement of miniaturized antennas is quite high. It is quite often that antenna dimensions are decided based on application based requirement compared to practical antenna constraints. The tradeoff in efficiency and other antenna parameters against to antenna size is always a debatable issue. The article presents detailed review of fundamentals of electrically small antennas and its potential applications. In addition, constraints and challenges of electrically small antennas are also presented in the article.

Keywords: bandwidth, communication, electrically small antenna, communication engineering

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Authors: Aminreza Koohestani

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This paper intends to explore the existing safeguards available within the Iranian law in protecting refugees affected by Sexual and Gender-Based Violence (SGBV). The Iranian law afforded protection for women and girls against SGBV is scattered across various bodies of law. Moreover, the degree of protection provided by the law varies greatly from one type of SGBV to another. The paper discusses the scope of applicability of Iranian laws to refugees affected by SGBV as well as substantive and procedural laws afforded protection for survivors of SGBV.

Keywords: Iran, law, violence, women

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Authors: Hemant Kumar, Nilendu Das

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A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesion class, earthquakes, IMD

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Authors: Mingook Lee, Sungjoo Lee

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As technology-based service industries grow drastically worldwide; companies are recognizing the importance of market preoccupancy and have made an effort to capture a large market to gain the upper hand. To this end, a focus on patents can be used to determine the properties of a technology, as well as to capture advantages in technical skills, in comparison with the firm’s competitors. However, technology-based services largely depend not only on their technological value but also their economic value, due to the recognized worth that is passed to a plurality of users. Thus, it is important to determine whether there are any competitors in the target areas and what services they provide in any field. Despite this importance, little effort has been made to systematically benchmark competitors in order to identify business opportunities. Thus, this study aims to not only identify each position of technology-centered service companies in complex market dynamics, but also to discover new business opportunities. For this, we try to consider both technology and market environments simultaneously by utilizing patent data as a representative proxy for technology and trademark dates as an index for a firm’s target goods and services. Theoretically, this is one of the earliest attempts to combine patent data and trademark data to analyze corporate strategies. In practice, the research results are expected to be used as a decision criterion to diagnose the economic value that companies can obtain by entering the market, as well as the technological value to be passed onto their customers. Thus, the proposed approach can be useful to support effective technology and business strategies in a firm.

Keywords: business opportunity, patent, Portfolio analysis, trademark

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: Nizaha Juhaida Mohamad, David Gray, Bettina Wolf

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Chocolate is a material composite with a high fraction of solid particles dispersed in a fat phase largely composed of cocoa butter. Viscosity properties of chocolate can be manipulated by the amount of fat - increased levels of fat lead to lower viscosity. However, a high content of cocoa butter can increase the cost of the chocolate and instead surfactants are used to manipulate viscosity behaviour. Most commonly, lecithin and polyglycerol polyricinoleate (PGPR) are used. Lecithin is a natural lipid emulsifier which is based on phospholipids while PGPR is a chemically produced emulsifier which based on the long continuous chain of ricinoleic acid. Lecithin and PGPR act to lower the viscosity and yield stress, respectively. Recently, natural lipid emulsifiers based on galactolipid as the functional ingredient have become of interest. Spinach lipid is found to have a high amount of galactolipid, specifically MGDG and DGDG. The aim of this research is to explore the influence of spinach lipid in comparison with PGPR and lecithin on the rheological properties of sugar/oil suspensions which serve as chocolate model system. For that purpose, icing sugar was dispersed from 40%, 45% and 50% (w/w) in oil which has spinach lipid at concentrations from 0.1 – 0.7% (w/w). Based on viscosity at 40 s-1 and yield value reported as shear stress measured at 5 s-1, it was found that spinach lipid shows viscosity reducing and yield stress lowering effects comparable to lecithin and PGPR, respectively. This characteristic of spinach lipid demonstrates great potential for it to act as single natural lipid emulsifier in chocolate.

Keywords: chocolate viscosity, lecithin, polyglycerol polyricinoleate (PGPR), spinach lipid

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Authors: Xin Li

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The uncertainty and the complexity of the urban environment combining with the threat of climate change are contributing factors to the vulnerability in multiple-dimensions in Chinese megacities, especially in Shanghai. The urban area occupied high valuable technological infrastructure and density buildings is under the threats of climate change and can provide insufficient ecological service to remain the trade-off on urban sustainable development. Urban ecological-based adaptation (UEbA) combines practices and theoretical work and integrates ecological services into multiple-layers of urban environment planning in order to reduce the impact of the complexity and uncertainty. To understand and to respond to the challenges in the urban level, this paper considers Shanghai as the research objective. It is necessary that its urban adaptation strategies should be reflected and contain the concept and knowledge of EbA. In this paper, we firstly use software to illustrates the visualizing patterns and trends of UEBA research in the current 10 years. Specifically, Citespace software was used for interpreting the significant hubs, landmarks points of peer-reviewed literature on the context of ecological service research in recent 10 years. Secondly, 135 evidence-based EbA literature were reviewed for categorizing the methodologies and framework of evidence-based EbA by the systematic map protocol. Finally, a conceptual framework combined with culture, economic and social components was developed in order to assess the current adaptation strategies in Shanghai. This research founds that the key to reducing urban vulnerability does not only focus on co-benefit arguments but also should pay more attention to the concept of trade-off. This research concludes that the designed framework can provide key knowledge and indicates the essential gap as a valuable tool against climate variability in the process of urban adaptation in Shanghai.

Keywords: urban ecological-based adaptation, climate change, sustainable development, climate variability

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Authors: Xinyue Jiao, Yu-Ren Lin

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Argumentation is an essential aspect of scientific thinking which has been widely concerned in recent reform of science education. The purpose of the present studies was to explore the influences of two variables termed ‘the argumentation strategy’ and ‘the kind of science concept’ on student’s web-based argumentation. The first variable was divided into either monological (which refers to individual’s internal discourse and inner chain reasoning) or dialectical (which refers to dialogue interaction between/among people). The other one was also divided into either descriptive (i.e., macro-level concept, such as phenomenon can be observed and tested directly) or theoretical (i.e., micro-level concept which is abstract, and cannot be tested directly in nature). The present study applied the quasi-experimental design in which 138 7th grade students were invited and then assigned to either monological group (N=70) or dialectical group (N=68) randomly. An argumentation learning program called ‘the PWAL’ was developed to improve their scientific argumentation abilities, such as arguing from multiple perspectives and based on scientific evidence. There were two versions of PWAL created. For the individual version, students can propose argument only through knowledge recall and self-reflecting process. On the other hand, the students were allowed to construct arguments through peers’ communication in the collaborative version. The PWAL involved three descriptive science concept-based topics (unit 1, 3 and 5) and three theoretical concept-based topics (unit 2, 4 and 6). Three kinds of scaffoldings were embedded into the PWAL: a) argument template, which was used for constructing evidence-based argument; b) the model of the Toulmin’s TAP, which shows the structure and elements of a sound argument; c) the discussion block, which enabled the students to review what had been proposed during the argumentation. Both quantitative and qualitative data were collected and analyzed. An analytical framework for coding students’ arguments proposed in the PWAL was constructed. The results showed that the argumentation approach has a significant effect on argumentation only in theoretical topics (f(1, 136)=48.2, p < .001, η2=2.62). The post-hoc analysis showed the students in the collaborative group perform significantly better than the students in the individual group (mean difference=2.27). However, there is no significant difference between the two groups regarding their argumentation in descriptive topics. Secondly, the students made significant progress in the PWAL from the earlier descriptive or theoretical topic to the later one. The results enabled us to conclude that the PWAL was effective for students’ argumentation. And the students’ peers’ interaction was essential for students to argue scientifically especially for the theoretical topic. The follow-up qualitative analysis showed student tended to generate arguments through critical dialogue interactions in the theoretical topic which promoted them to use more critiques and to evaluate and co-construct each other’s arguments. More explanations regarding the students’ web-based argumentation and the suggestions for the development of web-based science learning were proposed in our discussions.

Keywords: argumentation, collaborative learning, scientific concepts, web-based learning

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Authors: K. Paradkar, S. N. Mudliar, A. Sharma, A. B. Pandit, R. A. Pandey

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The study explores the hybrid combination of Hydrodynamic Cavitation (HC) and Subcritical Wet Air Oxidation-based pretreatment of complex industrial effluent to enhance the biodegradability selectively (without major COD destruction) to facilitate subsequent enhanced downstream processing via anaerobic or aerobic biological treatment. Advanced oxidation based techniques can be less efficient as standalone options and a hybrid approach by combining Hydrodynamic Cavitation (HC), and Wet Air Oxidation (WAO) can lead to a synergistic effect since both the options are based on common free radical mechanism. The HC can be used for initial turbulence and generation of hotspots which can begin the free radical attack and this agitating mixture then can be subjected to less intense WAO since initial heat (to raise the activation energy) can be taken care by HC alone. Lab-scale venturi-based hydrodynamic cavitation and wet air oxidation reactor with biomethanated distillery wastewater (BMDWW) as a model effluent was examined for establishing the proof-of-concept. The results indicated that for a desirable biodegradability index (BOD: COD - BI) enhancement (up to 0.4), the Cavitation (standalone) pretreatment condition was: 5 bar and 88 min reaction time with a COD reduction of 36 % and BI enhancement of up to 0.27 (initial BI - 0.17). The optimum WAO condition (standalone) was: 150oC, 6 bar and 30 minutes with 31% COD reduction and 0.33 BI. The hybrid pretreatment (combined Cavitation + WAO) worked out to be 23.18 min HC (at 5 bar) followed by 30 min WAO at 150oC, 6 bar, at which around 50% COD was retained yielding a BI of 0.55. FTIR & NMR analysis of pretreated effluent indicated dissociation and/or reorientation of complex organic compounds in untreated effluent to simpler organic compounds post-pretreatment.

Keywords: hybrid, hydrodynamic cavitation, wet air oxidation, biodegradability index

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Authors: Sa-Kil Kim, Jang-Soo Lee

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On March 31, 1993, a severe fire accident took place in a nuclear power plant located in Narora in North India. The event involved a major fire in the turbine building of NAPS unit-1 and resulted in a total loss of power to the unit for 17 hours. In addition, there was a heavy ingress of smoke in the control room, mainly through the intake of the ventilation system, forcing the operators to vacate the control room. The Narora fire accident provides us lessons indicating that operators could lose their mind and predictable behaviors during a fire. After the Fukushima accident, which resulted from a natural disaster, unanticipated external events are also required to be prepared and controlled for the ultimate safety of nuclear power plants. From last year, our research team has developed a test and evaluation facility that can simulate external events such as an earthquake and fire based on the operators’ real-sense. As one of the results of the project, we proposed a unit real-sense-based facility that can simulate fire events in a control room for utilizing a test-bed of human factor validation. The test-bed has the operator’s workstation shape and functions to simulate fire conditions such as smoke, heat, and auditory alarms in accordance with the prepared fire scenarios. Furthermore, the test-bed can be used for the operators’ training and experience.

Keywords: human behavior in fire, human factors validation, nuclear power plants, real-sense-based fire simulation

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Authors: A. Baviskar, C. Sandeep, K. Shankar

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Solving Multi-objective Optimization Problems requires faster convergence and better spread. Though existing Evolutionary Algorithms (EA's) are able to achieve this, the computation effort can further be reduced by hybridizing them with innovative strategies. This study is focuses on converging to the pareto front faster while adapting the advantages of Strength Pareto Evolutionary Algorithm-II (SPEA-II) for a better spread. Two different approaches based on optimizing the objective functions independently are implemented. In the first method, the decision variables corresponding to the optima of individual objective functions are strategically used to guide the search towards the pareto front. In the second method, boundary points of the pareto front are calculated and their decision variables are seeded to the initial population. Both the methods are applied to different constrained and unconstrained multi-objective test functions. It is observed that proposed guided search based algorithm gives better convergence and diversity than several well-known existing algorithms (such as NSGA-II and SPEA-II) in considerably less number of iterations.

Keywords: boundary points, evolutionary algorithms (EA's), guided search, strength pareto evolutionary algorithm-II (SPEA-II)

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Authors: V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

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This paper presents different methodology for an acoustic source sensing and localization in an unknown environment. The developed methodology includes an acoustic based sensing and localization system, a converging target localization based on the recursive direction of arrival (DOA) error minimization, and a regressive obstacle avoidance function. Our method is able to augment the existing proven localization techniques and improve results incrementally by utilizing robot locomotion and is capable of converging to a position estimate with greater accuracy using fewer measurements. The results also evinced the DOA error minimization at each iteration, improvement in time for reaching the destination and the efficiency of this target localization method as gradually converging to the real target position. Initially, the system is tested using Kinect mounted on turntable with DOA markings which serve as a ground truth and then our approach is validated using a FireBird VI (FBVI) mobile robot on which Kinect is used to obtain bearing information.

Keywords: acoustic source localization, acoustic sensing, recursive direction of arrival, robot locomotion

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Authors: Alpesh Adeshara, Rajendrasinh Jadeja, Praghnesh Bhatt

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Implementation of advanced technologies requires sophisticated instruments that deal with the operation, control, restoration and protection of rapidly growing power system network under normal and abnormal conditions. Presently, the applications of Phasor Measurement Unit (PMU) are widely found in real time operation, monitoring, controlling and analysis of power system network as it eliminates the various limitations of Supervisory Control and Data Acquisition System (SCADA) conventionally used in power system. The use of PMU data is very rapidly increasing its importance for online and offline analysis. Wide Area Measurement System (WAMS) is developed as new technology by use of multiple PMUs in power system. The present paper proposes a model of MATLAB based PMU using Discrete Fourier Transform (DFT) algorithm and evaluation of its operation under different contingencies. In this paper, PMU based two bus system having WAMS network is presented as a case study.

Keywords: GPS global positioning system, PMU phasor measurement system, WAMS wide area monitoring system, DFT, PDC

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Authors: Indraj Singh, Xuan Lee, Yu-Chieh Cheng

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Scientists are very keen on biomimetic research that mimics biological species to micro-robotic devices with the novel functionalities and accessibility. The source of inspiration is the complexity, sophistication, and intelligence of the biological systems. In this work, we design a light-driven star-shaped microgripper, an autonomous soft device which can change the shape under the external stimulus such as light. The design is based on light-responsive Liquid Crystal Elastomers which fabricated onto the polymer coated aligned substrate. The change in shape, controlled by the anisotropicity and the molecular orientation of the Liquid Crystal Elastomer, based on the external stimulus. This artificial star-shaped microgripper is capable of autonomous closure and capable to grab the objects in response to an external stimulus. This external stimulus-responsive materials design, based on soft active smart materials, provides a new approach to autonomous, self-regulating optical systems.

Keywords: liquid crystal elastomers, microgripper, smart materials, robotics

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Authors: Wiem Zaabi, Yemna Bensalem, Hafedh Trabelsi

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The paper presents a finite element (FE) based efficient analysis procedure for induction machine (IM). The FE formulation approaches are proposed to achieve this goal: the magnetostatic and the non-linear transient time stepped formulations. The study based on finite element models offers much more information on the phenomena characterizing the operation of electrical machines than the classical analytical models. This explains the increase of the interest for the finite element investigations in electrical machines. Based on finite element models, this paper studies the influence of the stator and the rotor faults on the behavior of the IM. In this work, a simple dynamic model for an IM with inter-turn winding fault and a broken bar fault is presented. This fault model is used to study the IM under various fault conditions and severity. The simulation results are conducted to validate the fault model for different levels of fault severity. The comparison of the results obtained by simulation tests allowed verifying the precision of the proposed FEM model. This paper presents a technical method based on Fast Fourier Transform (FFT) analysis of stator current and electromagnetic torque to detect the faults of broken rotor bar. The technique used and the obtained results show clearly the possibility of extracting signatures to detect and locate faults.

Keywords: Finite element Method (FEM), Induction motor (IM), short-circuit fault, broken rotor bar, Fast Fourier Transform (FFT) analysis

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Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo

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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.

Keywords: the bluff body wakes, low-order modeling, neural network, system identification

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Authors: Juliet F. Poujol, Jeff John Tanner, Christophe Fournier

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Employers desire a favorable brand as an employer. This research considers whether motivation theory is applied to identify universally desirable employer brand elements. Based on data from a website where employees give their opinion about their employer (N=200), this research examines what salespeople found positive and negative about their job. Results show that traditional motivators like opportunities of advancement, and 'hygiene' factors such as benefits and work conditions are a source of satisfaction for salespeople. We also found differences by sectors. Implications are related to sales force recruitment and management.

Keywords: employer brand, motivation, qualitative study, salespeople

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Aaron Zhang, Alimire Kahaer, Gerald Weber, Nalin Arachchilage

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Access control is an essential safeguard for the security of enterprise data, which controls users’ access to information resources and ensures the confidentiality and integrity of information resources [1]. Research shows that the more common types of access control now have shortcomings [2]. In this direction, to improve the existing access control, we have studied the current technologies in the field of data security, deeply investigated the previous data access control policies and their problems, identified the existing deficiencies, and proposed a new extension structure of SPBAC. SPBAC extension proposed in this paper aims to combine Policy-Based Access Control (PBAC) with semantics to provide logically connected, real-time data access functionality by establishing associations between enterprise data through semantics. Our design combines policies with linked data through semantics to create a "Semantic link" so that access control is no longer per-database and determines that users in each role should be granted access based on the instance policy, and improves the SPBAC implementation by constructing policies and defined attributes through the XACML specification, which is designed to extend on the original XACML model. While providing relevant design solutions, this paper hopes to continue to study the feasibility and subsequent implementation of related work at a later stage.

Keywords: access control, semantic policy-based access control, semantic link, access control model, instance policy, XACML

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Authors: Hao Chen, Bo Guo, Ping Jiang

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Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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Authors: Nasar Aldian Ambark Shashoa

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Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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Authors: Tamás Matuszka, Attila Kiss

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Due the proliferation of smartphones in everyday use, several different outdoor navigation systems have become available. Since these smartphones are able to connect to the Internet, the users can obtain location-based information during the navigation as well. The users could interactively get to know the specifics of a particular area (for instance, ancient cultural area, Statue Park, cemetery) with the help of thus obtained information. In this paper, we present an Augmented Reality system which uses Semantic Web technologies and is based on the interaction between the user and the smartphone. The system allows navigating through a specific area and provides information and details about the sight an interactive manner.

Keywords: augmented reality, semantic web, human computer interaction, mobile application

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Authors: Marwa Ahmed Abd El Hamied

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In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

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Authors: Liang Qin, Hanan M. D. Habbi

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A robust sensorless speed for permanent magnet synchronous motor (PMSM) has been presented for estimation of stator flux components and rotor speed based on The Extended Kalman Filter (EKF). The model of PMSM and its EKF models are modeled in Matlab /Sirnulink environment. The proposed EKF speed estimation method is also proved insensitive to the PMSM parameter variations. Simulation results demonstrate a good performance and robustness.

Keywords: DTC, Extended Kalman Filter (EKF), PMSM, sensorless control, anti-windup PI

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Authors: Olga Mironiuk, Małgorzata Kossowska

Abstract:

The aim of the present study was to investigate the influence of Situational Attribution Training on reducing automatic in-group stereotyping in females. The experiment was conducted with the control of age and level of prejudice. 90 female participants were randomly assigned to two conditions: experimental and control group (each group was also divided into younger- and older-aged condition). Participants from the experimental condition were subjected to more extensive training. In the first part of the experiment, the experimental group took part in the first session of Situational Attribution Training while the control group participated in the Grammatical Training Control. In the second part of the research both groups took part in the Situational Attribution Training (which was considered as the second training session for the experimental group and the first one for the control condition). The training procedure was based on the descriptions of ambiguous situations which could be explained using situational or dispositional attributions. The participant’s task was to choose the situational explanation from two alternatives, out of which the second one presented the explanation based on neutral or stereotypically associated with women traits. Moreover, the experimental group took part in the third training session after two- day time delay, in order to check the persistence of the training effect. The main hypothesis stated that among participants taking part in the more extensive training, the automatic in-group stereotyping would be less frequent after having finished training sessions. The effectiveness of the training was tested by measuring the response time and the correctness of answers: the longer response time for the examples where one of two possible answers was based on the stereotype trait and higher correctness of answers was considered to be a proof of the training effectiveness. As the participants’ level of prejudice was controlled (using the Ambivalent Sexism Inventory), it was also assumed that the training effect would be weaker for participants revealing a higher level of prejudice. The obtained results did not confirm the hypothesis based on the response time: participants from the experimental group responded faster in case of situations where one of the possible explanations was based on stereotype trait. However, an interesting observation was made during the analysis of the answers’ correctness: regardless the condition and age group affiliation, participants made more mistakes while choosing the situational explanations when the alternative was based on stereotypical trait associated with the dimension of warmth. What is more, the correctness of answers was higher in the third training session for the experimental group in case when the alternative of situational explanation was based on the stereotype trait associated with the dimension of competence. The obtained results partially confirm the effectiveness of the training.

Keywords: female, in-group stereotyping, prejudice, situational attribution training

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Authors: Kathryn Watson

Abstract:

In 2020 North Carolina passed legislation mandating all educators be trained in identifying, referring, and supporting students showing signs of mental health issues, drug use, suicidal ideation, and sex trafficking. This study collected survey responses from 226 educators in North Carolina to better understand their perspectives on the legislation and their self-efficacy in supporting student mental health needs. Key findings of the study reveal that the mandated trainings increased educator awareness of student mental health, and higher awareness was linked to higher self-efficacy in supporting student mental health needs. Additionally, the results showed that educators who identify as Black had lower levels of self-efficacy in supporting student mental health. Additionally, rural educators were least likely to support the legislation in comparison to their urban and suburban counterparts. These findings can help inform policymakers in evaluating the policy and district decision-makers in selecting and implementing school-based mental health training.

Keywords: school-based mental health, education policy, student health, North Carolina, K-12 education

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