Search results for: nonlinear time history analysis.

Authors: Y. Harold Robinson, E. Golden Julie

Abstract:

Dynamic Routing in Wireless Sensor Networks (WSNs) has played a significant task in research for the recent years. Energy consumption and data delivery in time are the major parameters with the usage of sensor nodes that are significant criteria for these networks. The location of sensor nodes must not be prearranged. Clustering in WSN is a key methodology which is used to enlarge the life-time of a sensor network. It consists of numerous real-time applications. The features of WSNs are minimized the consumption of energy. Soft computing techniques can be included to accomplish improved performance. This paper surveys the modern trends in routing enclose fuzzy logic and Neuro-fuzzy logic based on the clustering techniques and implements a comparative study of the numerous related methodologies.

Keywords: Wireless sensor networks, clustering, fuzzy logic, neuro-fuzzy logic, energy efficiency.

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Authors: Mahnaz Mahmoudi Zarandi (Qazvin Islamic Azad University)

Abstract:

wind catchers have been served as a cooling system, used to provide acceptable ventilation by means of renewable energy of wind. In the present study, the city of Yazd in arid climate is selected as case study. From the architecture point of view, learning about wind catchers in this study is done by means of field surveys. Research method for selection of the case is based on random form, and analytical method. Wind catcher typology and knowledge of relationship governing the wind catcher's architecture were those measures that are taken for the first time. 53 wind catchers were analyzed. The typology of the wind-catchers is done by the physical analyzing, patterns and common concepts as incorporated in them. How the architecture of wind catcher can influence their operations by analyzing thermal behavior are the archetypes of selected wind catchers. Calculating fluids dynamics science, fluent software and numerical analysis are used in this study as the most accurate analytical approach. The results obtained from these analyses show the formal specifications of wind catchers with optimum operation in Yazd. The knowledge obtained from the optimum model could be used for design and construction of wind catchers with more improved operation

Keywords: Fluent Software, Iranian architecture, wind catcher

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Authors: S. Hutasavi, D. Chen

Abstract:

The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: Built-up area extraction, Google earth engine, adaptive thresholding method, rapid mapping.

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Authors: Peerapong Uthansakul, Monthippa Uthansakul

Abstract:

WLAN Positioning has been presented by many approaches in literatures using the characteristics of Received Signal Strength (RSS), Time of Arrival (TOA) or Time Difference of Arrival (TDOA), Angle of Arrival (AOA) and cell ID. Among these, RSS approach is the simplest method to implement because there is no need of modification on both access points and client devices whereas its accuracy is terrible due to physical environments. For TOA or TDOA approach, the accuracy is quite acceptable but most researches have to modify either software or hardware on existing WLAN infrastructure. The scales of modifications are made on only access card up to the changes in protocol of WLAN. Hence, it is an unattractive approach to use TOA or TDOA for positioning system. In this paper, the new concept of merging both RSS and TOA positioning techniques is proposed. In addition, the method to achieve TOA characteristic for positioning WLAN user without any extra modification necessarily appended in the existing system is presented. The measurement results confirm that the proposed technique using both RSS and TOA characteristics provides better accuracy than using only either RSS or TOA approach.

Keywords: Received signal strength, Time of arrival, Positioning system, WLAN, Measurement.

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Authors: N. Reehana, A. Parveez Ahamed, D. Mubarak Ali, A. Suresh, R. Arvind Kumar, N. Thajuddin

Abstract:

Cyanobacteria play a vital role in the production of phycobiliproteins that includes phycocyanin and phycoerythrin pigments. Phycocyanin and related phycobiliproteins have wide variety of application that is used in the food, biotechnology and cosmetic industry because of their color, fluorescent and antioxidant properties. The present study is focused to understand the pigment at molecular level in the Cyanobacteria Oscillatoria terebriformis NTRI05 and Oscillatoria foreaui NTRI06. After extraction of genomic DNA, the amplification of C-Phycocyanin gene was done with the suitable primer PCβF and PCαR and the sequencing was performed. Structural and Phylogenetic analysis was attained using the sequence to develop a molecular model.

Keywords: Cyanobacteria, C-Phycocyanin gene, Phylogenetic analysis, Structural analysis.

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Authors: Li-Yeh Chuang, Yu-Jen Hou, Jr., Cheng-Hong Yang

Abstract:

Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, research is limited by the cost of genotyping the tremendous number of SNPs. Therefore, it is important to identify a small subset of informative SNPs, the so-called tag SNPs. This subset consists of selected SNPs of the genotypes, and accurately represents the rest of the SNPs. Furthermore, an effective evaluation method is needed to evaluate prediction accuracy of a set of tag SNPs. In this paper, a genetic algorithm (GA) is applied to tag SNP problems, and the K-nearest neighbor (K-NN) serves as a prediction method of tag SNP selection. The experimental data used was taken from the HapMap project; it consists of genotype data rather than haplotype data. The proposed method consistently identified tag SNPs with considerably better prediction accuracy than methods from the literature. At the same time, the number of tag SNPs identified was smaller than the number of tag SNPs in the other methods. The run time of the proposed method was much shorter than the run time of the SVM/STSA method when the same accuracy was reached.

Keywords: Genetic Algorithm (GA), Genotype, Single nucleotide polymorphism (SNP), tag SNPs.

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Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

Abstract:

In this paper, we consider the vehicle routing problem with mixed fleet of conventional and heterogenous electric vehicles and time dependent charging costs, denoted VRP-HFCC, in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with different insertion methods. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem.

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Authors: Paweł Żur, Alicja Żur, Andrzej Baier

Abstract:

Modal analysis is a crucial tool in the field of engineering for understanding the dynamic behavior of structures. In this study, numerical modal analysis was conducted on a multi-material 3D-printed composite bushing, which comprised a polylactic acid (PLA) outer shell and a thermoplastic polyurethane (TPU) flexible filling. The objective was to investigate the modal characteristics of the bushing and assess its potential for practical applications. The analysis involved the development of a finite element model of the bushing, which was subsequently subjected to modal analysis techniques. Natural frequencies, mode shapes, and damping ratios were determined to identify the dominant vibration modes and their corresponding responses. The numerical modal analysis provided valuable insights into the dynamic behavior of the bushing, enabling a comprehensive understanding of its structural integrity and performance. Furthermore, the study expanded its scope by investigating the entire shaft mounting of a small electric car, incorporating the 3D-printed composite bushing. The shaft mounting system was subjected to numerical modal analysis to evaluate its dynamic characteristics and potential vibrational issues. The results of the modal analysis highlighted the effectiveness of the 3D-printed composite bushing in minimizing vibrations and optimizing the performance of the shaft mounting system. The findings contribute to the broader field of composite material applications in automotive engineering and provide valuable insights for the design and optimization of similar components.

Keywords: 3D printing, composite bushing, modal analysis, multi-material.

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Authors: Andreas Theissler, Ian Dear

Abstract:

In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.

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Authors: Yoshiaki Shikata, Wataru Katagiri, Yoshitaka Takahashi

Abstract:

We propose a novel prioritized limited processor-sharing (PS) rule and a simulation algorithm for the performance evaluation of this rule. The performance measures of practical interest are evaluated using this algorithm. Suppose that there are two classes and that an arriving (class-1 or class-2) request encounters n1 class-1 and n2 class-2 requests (including the arriving one) in a single-server system. According to the proposed rule, class-1 requests individually and simultaneously receive m / (m * n1+ n2) of the service-facility capacity, whereas class-2 requests receive 1 / (m *n1 + n2) of it, if m * n1 + n2 ≤ C. Otherwise (m * n1 + n2 > C), the arriving request will be queued in the corresponding class waiting room or rejected. Here, m (
1) denotes the priority ratio, and C ( ∞), the service-facility capacity. In this rule, when a request arrives at [or departs from] the system, the extension [shortening] of the remaining sojourn time of each request receiving service can be calculated using the number of requests of each class and the priority ratio. Employing a simulation program to execute these events and calculations enables us to analyze the performance of the proposed prioritized limited PS rule, which is realistic in a time-sharing system (TSS) with a sufficiently small time slot. Moreover, this simulation algorithm is expanded for the evaluation of the prioritized limited PS system with N
3 priority classes.

Keywords: PS rule, priority ratio, service-facility capacity, simulation algorithm, sojourn time, performance measures

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Authors: Li Feng

Abstract:

In IEEE 802.11 networks, it is well known that the traditional time-domain contention often leads to low channel utilization. The first frequency-domain contention scheme, the time to frequency (T2F), has recently been proposed to improve the channel utilization and has attracted a great deal of attention. In this paper, we present the latest research progress on the weighed frequency-domain contention. We compare the basic ideas, work principles of these related schemes and point out their differences. This paper is very useful for further study on frequency-domain contention.

Keywords: 802.11, wireless LANs, frequency-domain contention, T2F.

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Authors: D. Beziakina, E. Bulgakova

Abstract:

The paper deals with cross-gender and cross-linguistic comparison of pitch characteristics for Tuvinian with two other Turkic languages - Uzbek and Azerbaijani, based on the results of statistical analysis of pitch parameter values and intonation patterns used by male and female speakers.

The main goal of our work is to obtain the ranges of pitch parameter values typical for Tuvinian speakers for the purpose of automatic language identification. We also propose a cross-gender analysis of declarative intonation in the poorly studied Tuvinian language.

The ranges of pitch parameter values were obtained by means of specially developed software that deals with the distribution of pitch values and allows us to obtain statistical language-specific pitch intervals.

Keywords: Speech analysis, Statistical analysis, Speaker recognition, Identification of person.

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Authors: Borja Bordel, Ramón Alcarria, Marina Pérez

Abstract:

In March 2020, in Spain, a sanitary and unexpected crisis caused by COVID-19 was declared. All of a sudden, all degrees, classes and evaluation tests and projects had to be transformed into online activities. However, the chaotic situation generated by a complex operation like that, executed without any well-established procedure, led to very different experiences and, finally, results. In this paper, we are describing three experiences in two different Universities in Madrid. On the one hand, the Technical University of Madrid, a public university with little experience in online education was considered. On the other hand, Alfonso X el Sabio University, a private university with more than five years of experience in online teaching was involved. All analyzed subjects were related to computer engineering. Professors and students answered a survey and personal interviews were also carried out. Besides, the professors’ workload and the students’ academic results were also compared. From the comparative analysis of all these experiences, we are extracting the most successful strategies, methodologies, and activities. The recommendations in this paper will be useful for courses during the next months when the sanitary situation is still affecting an educational organization. While, at the same time, they will be considered as input for the upcoming digitalization process of higher education.

Keywords: educational experience, online education, higher education digitalization, COVID, Spain

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Authors: Tae Jin Choi, Jong Ok Kim, Sang Min Jin, Gilwon Yoon

Abstract:

Analysis of EEG brainwave provides information on mental or emotional states. One of the particular states that can have various applications in human machine interface (HMI) is concentration. 8-channel EEG signals were measured and analyzed. The concentration index was compared during resting and concentrating periods. Among eight channels, locations the frontal lobe (F_p1 and F_p2) showed a clear increase of the concentration index during concentration regardless of subjects. The rest six channels produced conflicting observations depending on subjects. At this time, it is not clear whether individual difference or how to concentrate made these results for the rest six channels. Nevertheless, it is expected that F_p1 and F_p2 are promising locations for extracting control signal for HMI applications.

Keywords: Concentration, EEG, human machine interface.

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Authors: Salima Behdenna, Fatiha Barigou, Ghalem Belalem

Abstract:

Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic ABSA approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.

Keywords: Sentiment analysis, opinion mining, Arabic, aspect level, opinion, polarity.

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Authors: Xuanyu Bai

Abstract:

“The Communist Manifesto”, written by Karl Marx and Friedrich Engels, is one of the most significant documents throughout the whole history which covers across different fields including Economic, Politic, Sociology and Philosophy. Instead of discussing the Communist ideas presented in the Communist Manifesto, the essay focuses on exploring the reasons that contributed to the popularization of the document and its influence on political revolutions in 19^th century Europe by concentrating on the document itself along with other primary and secondary sources and temporal artwork. Combining the details from the Communist Manifesto and other documents, Marx’s writing style and word choice, his convincible notions about a new society dominated by proletariats, and the revolutionary idea of class destruction has led to the popularization of the Communist Manifesto and influenced the latter political revolutions.

Keywords: Communist Manifesto, The Wealth of Nations, 19th century Europe, word choice, capitalism, communism.

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Authors: Radek Malinský, Ivan Jelínek

Abstract:

Web 2.0 (social networking, blogging and online forums) can serve as a data source for social science research because it contains vast amount of information from many different users. The volume of that information has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. We have proposed a novel theoretical model for gathering and processing data from Web 2.0, which would reflect semantic content of web pages in better way. This article deals with the analysis part of the model and its usage for content analysis of blogs. The introductory part of the article describes methodology for the gathering and processing data from blogs. The next part of the article is focused on the evaluation and content analysis of blogs, which write about specific trend.

Keywords: Blog, Sentiment Analysis, Web 2.0, Webometrics

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Authors: S. Hellam, Y. Oulahrir, F. El Mounchid, A. Sadiq, S. Mbarki

Abstract:

In this paper, we propose a method for three-dimensional (3-D)-model indexing based on defining a new descriptor, which we call new descriptor using spherical harmonics. The purpose of the method is to minimize, the processing time on the database of objects models and the searching time of similar objects to request object. Firstly we start by defining the new descriptor using a new division of 3-D object in a sphere. Then we define a new distance which will be used in the search for similar objects in the database.

Keywords: 3D indexation, spherical harmonic, similarity of 3D objects.

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Authors: R. Sabre, W. Horrigue, J. C. Simon

Abstract:

This paper is interested in two difficulties encountered in practice when observing a continuous time process. The first is that we cannot observe a process over a time interval; we only take discrete observations. The second is the process frequently observed with a constant additive error. It is important to give an estimator of the spectral density of such a process taking into account the additive observation error and the choice of the discrete observation times. In this work, we propose an estimator based on the spectral smoothing of the periodogram by the polynomial Jackson kernel reducing the additive error. In order to solve the aliasing phenomenon, this estimator is constructed from observations taken at well-chosen times so as to reduce the estimator to the field where the spectral density is not zero. We show that the proposed estimator is asymptotically unbiased and consistent. Thus we obtain an estimate solving the two difficulties concerning the choice of the instants of observations of a continuous time process and the observations affected by a constant error.

Keywords: Spectral density, stable processes, aliasing, periodogram.

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Authors: Trisha Malhotra

Abstract:

Sentiment analysis is a recent field of study that computationally assesses the emotional nature of a body of text. To assess its test-validity, sentiment analysis was carried out on the emotional corpus of text from a personal 15-day mood diary. Self-reported mood scores varied more or less accurately with daily mood evaluation score given by the software. On further assessment, it was found that while sentiment analysis was good at assessing ‘global’ mood, it was not able to ‘locally’ identify and differentially score synonyms of various emotional words. It is further critiqued for treating the intensity of an emotion as universal across cultures. Finally, the software is shown not to account for emotional complexity in sentences by treating emotions as strictly positive or negative. Hence, it is posited that a better output could be two (positive and negative) affect scores for the same body of text.

Keywords: Analysis, data, diary, emotions, mood, sentiment.

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Authors: E.Sasikumar, T.Viruthagiri

Abstract:

Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.

Keywords: Sugarcane bagasse, ethanol, optimization, Pachysolen tannophilus.

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Authors: W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sathasivam

Abstract:

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, Modeling, Neural Networks, Preconditioned Conjugate Gradient.

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Authors: S. Montenegro, W. Hu

Abstract:

The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.

Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.

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Authors: Erika K. Méndez, Carlos E. Orrego, Diana L. Manrique, Juan D. Gonzalez, Doménica Vallejo

Abstract:

High moisture content in fruits generates post-harvest problems such as mechanical, biochemical, microbial and physical losses. Dehydration, which is based on the reduction of water activity of the fruit, is a common option for overcoming such losses. However, regular hot air drying could affect negatively the quality properties of the fruit due to the long residence time at high temperature. Power ultrasound (US) application during the convective drying has been used as a novel method able to enhance drying rate and, consequently, to decrease drying time. In the present study, a new approach was tested to evaluate the effect of US on the drying time, the final antioxidant activity (AA) and the total polyphenol content (TPC) of banana slices (BS), mango slices (MS) and guava slices (GS). There were also studied the drying kinetics with nine different models from which water effective diffusivities (Deff) (with or without shrinkage corrections) were calculated. Compared with the corresponding control tests, US assisted drying for fruit slices showed reductions in drying time between 16.23 and 30.19%, 11.34 and 32.73%, and 19.25 and 47.51% for the MS, BS and GS respectively. Considering shrinkage effects, Deff calculated values ranged from 1.67*10-10 to 3.18*10-10 m2/s, 3.96*10-10 and 5.57*10-10 m2/s and 4.61*10-10 to 8.16*10-10 m2/s for the BS, MS and GS samples respectively. Reductions of TPC and AA (as DPPH) were observed compared with the original content in fresh fruit data in all kinds of drying assays.

Keywords: Banana, drying, effective diffusivity, guava, mango, ultrasound.

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Authors: Eirini Petratou, Pezirkianidis Christos, Anastassios Stalikas

Abstract:

Nostalgia is characterized as a mental state of human’s emotional longing for the past that activates both positive and negative emotions. The bittersweet emotions that are activated by nostalgia aid psychological functions to humans and are depended on the type of stimuli that evoke nostalgia but also on the nostalgia activation context. In general, despite that nostalgia can be activated and experienced by all people; however, it differs both in terms of nostalgia experience but also nostalgia frequency. As a matter of fact, nostalgia experience along with nostalgia frequency differs according to the level of the nostalgia proneness. People with high nostalgia proneness tend to experience nostalgia more intensely and frequently than people with low nostalgia proneness. Nostalgia proneness is considered as a basic individual difference that affects the experience of nostalgia, and it can be measured by the Southampton Nostalgia Scale (SNS); a psychometric instrument that measures human’s nostalgia proneness consisting of seven questions that assess a person’s attitude towards nostalgia, the degree of experience or tendency to nostalgic feelings and the nostalgia frequency. In the current study, we translated, validated and calibrated the SNS in Greek population (N = 267). For the calibration process, we used several scales relevant to positive dimensions, such as life satisfaction, positive and negative emotions, time perspective and wellbeing. A confirmatory factor analysis revealed the factors that provide a good Southampton Nostalgia Proneness model fit for young adult Greek population.

Keywords: Nostalgia proneness, nostalgia, psychometric instruments, positive emotions.

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Authors: Hamid Abdi, Abolfazl Salami, Abolfazl Ahmadi

Abstract:

Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.

Keywords: Programmable Logic Controller, PLC Programming, Neural Networks, Perception Network, Intelligent Control.

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Authors: Chien-Chun Kung, Feng-Lung Chiang, Kuei-Yi Chen, Hsien-Wen Wei, Ming-Yi Huang, Cai-Ming Huang, Sheng-Kai Wang

Abstract:

The aim of this paper is to present a new three-dimensional proportional-pursuit coupled (PP) guidance law to track highly maneuverable aircraft. Utilizing a 3-D polar coordinate frame, the PP guidance law is formed by collecting proportional navigation guidance in Z-R plane and pursuit guidance in X-Y plane. Feedback linearization control method to solve the guidance accelerations is used to implement PP guidance. In order to compensate the actuator time delay, the time delay compensated version of PP guidance law (CPP) was derived and proved the effectiveness of modifying the problem of high acceleration in the final phase of pursuit guidance and improving the weak robustness of proportional navigation. The simulation results for intercepting Max G turn situation show that the proposed proportional-pursuit coupled guidance law guidance law with actuator delay compensation (CPP) possesses satisfactory robustness and performance.

Keywords: Feedback linearization control, time delay, guidance law, robustness, proportional navigation guidance, pursuit guidance.

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Authors: A. Al-Rifaie, Z. W. Guan, S. W. Jones

Abstract:

This paper presents a method for modelling and analysing end plate beam-to-column connections to obtain the quasi-static behaviour using non-linear dynamic explicit integration. In addition to its importance to study the static behaviour of a structural member, quasi-static behaviour is largely needed to be compared with the dynamic behaviour of such members in order to investigate the dynamic effect by proposing dynamic increase factors (DIFs). The beam-to-column bolted connections contain various contact surfaces at which the implicit procedure may have difficulties converging, resulting in a large number of iterations. Contrary, explicit procedure could deal effectively with complex contacts without converging problems. Hence, finite element modelling using ABAQUS/explicit is used in this study to address the dynamic effect may be produced using explicit procedure. Also, the effect of loading rate and mass scaling are discussed to investigate their effect on the time of analysis. The results show that the explicit procedure is valuable to model the end plate beam-to-column connections in terms of failure mode, load-displacement relationships. Also, it is concluded that loading rate and mass scaling should be carefully selected to avoid the dynamic effect in the solution.

Keywords: Quasi-static, end plate, finite element, connections.

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Authors: A. V. Dolzhikova

Abstract:

The article deals with the problems of labour migration in the Russian Federation in the context of Russia's national security, provides the typology of migrants residing in the territory of the Russian Federation and analyzes the risk factors. The author considers the structure of migration flows and the terms of legal, economic and socio-cultural adaptation of migrants in the Russian Federation. In this connection, the status of the Russian migration legislation, the concept of the comprehensive exam in Russian as a foreign language, history of Russia and the basics of the Russian Federation legislation for foreign citizens which was introduced in Russia on January 1, 2015, are analyzed. The article discloses its role as the adaptation strategy and the factor of Russia's migration security.

Keywords: Comprehensive exam, migration policy, migration legislation, Russia's national security.

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Authors: Emmanuel U. Ohaegbulem, Felix N. Nwobi

Abstract:

Alternative and simple computational arrangements in carrying out multivariate profile analysis when more than two groups (populations) are involved are presented. These arrangements have been demonstrated to not only yield equivalent results for the test statistics (the Wilks lambdas), but they have less computational efforts relative to other arrangements so far presented in the literature; in addition to being quite simple and easy to apply.

Keywords: Coincident profiles, g-group profile analysis, level profiles, parallel profiles, repeated measures MANOVA.

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