Search results for: sensory processing patterns

Authors: Siuzan Uorner

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The era of late modernity is characterized, on the one hand, by social disintegration, values of personal freedom, tolerance, and self-expression. Boundaries between the accessible and the elitist, normal and abnormal are blurring. On the other hand, traditional social institutions, such as religion (especially Russian Orthodox Church), exist, criticizing lifestyle and worldview other than conventionally structured canons. Despite the declared values and opportunities in late modern society, people's freedom is ambivalent. Personal identity and its aspects are becoming a subject of choice. Hence, combinations of identity aspects can be incompatible. Our theoretical framework is based on P. Ricoeur's concept of narrative identity and hermeneutics, E. Goffman’s theory of social stigma, self-presentation, discrepant roles and W. James lectures about varieties of religious experience. This paper aims to reconstruct ways of coping with incompatible identities of Orthodox gays (an extreme sampling of a combination of sexual orientation and religious identity in a heteronormative society). This study focuses on the discourse of Orthodox gay parishioners and ROC gay priests in Russia (sampling ‘hard to reach’ populations because of the secrecy of gay community in ROC and sensitivity of the topic itself). We conducted a qualitative research design, using in-depth personal semi-structured online-interviews. Recruiting of informants took place in 'Nuntiare et Recreare' (Russian movement of religious LGBT) page in VKontakte through the post with an invitation to participate in the research. In this work, we analyzed interview transcripts using axial coding. We chose the Grounded Theory methodology to construct a theory from empirical data and contribute to the growing body of knowledge in ways of harmonizing incompatible identities in late modern societies. The research has found that there are two types of conflicts Orthodox gays meet with: canonic contradictions (postulates of Scripture and its interpretations) and problems in social interaction, mainly with ROC priests and Orthodox parishioners. We have revealed semantic meanings of most commonly used words that appear in the narratives (words such as ‘love’, ‘sin’, ‘religion’ etc.). Finally, we have reconstructed biographical patterns of LGBT social movements’ involvement. This paper argues that all incompatibilities are harmonizing in the narrative itself. As Ricoeur has suggested, the narrative configuration allows the speaker to gather facts and events together and to compose causal relationships between them. Sexual orientation and religious identity are getting along and harmonizing in the narrative.

Keywords: gay priests, incompatible identities, narrative identity, Orthodox gays, religious identity, ROC, sexual orientation

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Authors: Hozaifa Zaki, Ghada Soliman

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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

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Authors: Photjanat Phimnom, Haruetai Lohasiriwat

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In today’s world, the LED display has been used for presenting visual information under various circumstances. Such information is an important intermediary in the human information processing. Researchers have been investigated diverse factors that influence this process effectiveness. The letter size is undoubtedly one major factor that has been tested and recommended by many standards and guidelines. However, viewing information on the display from direct perpendicular position is a typical assumption whereas many actual events are required viewing from the angles. This current research aims to study the effect of oblique viewing angle and viewing distance on ability to recognize alphabet, number, and English word. The total of ten participants was volunteered to our 3 x 4 x 4 within subject study. Independent variables include three distance levels (2, 6, and 12 m), four oblique angle (0, 45, 60, 75 degree), and four target types (alphabet, number, short words, and long words). Following the method of constant stimuli we found that the larger oblique angle, ranging from 0 to 75 degree from the line of sight, results in significant higher legibility threshold or larger font size required (p-value < 0.05). Viewing distance factor also shows to have significant effect on the threshold (p-value < 0.05). However, the effect from distance factor is expected to be confounded by the quality of the screen we used in our experiment. Lastly, our results show that single alphabet as well as single number are recognized at significant lower threshold (smaller font size) as compared to both short and long words (p-value < 0.05). Therefore, it is recommended that when designs information to be presented on LED display, understanding of all possible ranges of oblique angle should be taken into account in order to specify the preferred letter size. Additionally, the recommendation of letter size for 100 % readability in our tested conditions is provided in the paper.

Keywords: letter size, oblique angle, viewing distance, legibility threshold

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Authors: Eva Tvrdá, Boris Botman, Marek Halenár, Tomáš Slanina, Norbert Lukáč

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In vitro storage and processing of animal semen represents a risk factor to spermatozoa vitality, potentially leading to reduced fertility. A variety of substances isolated from natural sources may exhibit protective or antioxidant properties on the spermatozoon, thus extending the lifespan of stored ejaculates. This study compared the ability of different concentrations of the Salvia officinalis extract on the motility, mitochondrial activity, viability and reactive oxygen species (ROS) production by bovine spermatozoa during different time periods (0, 2, 6 and 24 h) of in vitro culture. Spermatozoa motility was assessed using the Computer-assisted sperm analysis (CASA) system. Cell viability was examined using the metabolic activity MTT assay, the eosin-nigrosin staining technique was used to evaluate the sperm viability and ROS generation was quantified using luminometry. The CASA analysis revealed that the motility in the experimental groups supplemented with 0.5-2 µg/mL Salvia extract was significantly lower in comparison with the control (P<0.05; Time 24 h). At the same time, a long-term exposure of spermatozoa to concentrations ranging between 0.05 µg/mL and 2 µg/mL had a negative impact on the mitochondrial metabolism (P<0.05; Time 24 h). The viability staining revealed that 0.001-1 µg/mL Salvia extract had no effects on bovine male gametes, however 2 µg/mL Salvia had a persisting negative effect on spermatozoa (P<0.05). Furthermore 0.05-2 µg/mL Salvia exhibited an immediate ROS-promoting effect on the sperm culture (P>0.05; Time 0 h and 2 h), which remained significant throughout the entire in vitro culture (P<0.05; Time 24 h). Our results point out to the necessity to examine specific effects the biomolecules present in Salvia officinalis may have individually or collectively on the in vitro sperm vitality and oxidative profile.

Keywords: bulls, CASA, MTT test, reactive oxygen species, sage, Salvia officinalis, spermatozoa

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Authors: Charles Chijioke Dike, Hugh Clifford Chima Maduka, Chinwe A. Isibor

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Fish is among the products consumed at a very high rate. In most countries of the world, fish are used as part of the daily meal. The high cost of commercial fish feeds in Africa has made it necessary the development of an alternative source of fish feed processing from organic waste. The objective of this research is to investigate the efficacy of fish feeds processed from various animal wastes in order to know whether those feeds shall be alternatives to commercial feeds. This work shall be carried out at the Research Laboratory Unit of the Department of Human Biochemistry, Faculty of Basic Medical Sciences, College of Health Sciences, Nnamdi Azikiwe University (NAU), Nnewi Campus, Anambra State. The fingerlings to be used shall be gotten from the Agricultural Department of NAU, Awka, Anambra State, and allowed to acclimatize for 14 d. Animal and food wastes shall be gotten from Nnewi. The fish shall be grouped into 1-13 (Chicken manure only, cow dung only, pig manure only, chicken manure + yeast, cow dung + yeast, pig manure + yeast, chicken manure + other wastes + yeast, cow dung + other wastes + yeast, and pig manure + other wastes + yeast. Feed assessment shall be carried out by determining bulk density, feed water absorption, feed hardness, feed oil absorption, and feed water stability. The nutritional analysis shall be carried out on the feeds processed. The risk assessment shall be done on the fish by determining methylmercury (MeHg), polycyclic aromatic hydrocarbons (PAHs), and dichloro-diphenyl-trichloroethane (DDT) in the fish. The results from this study shall be analyzed statistically using SPSS statistical software, version 25. The hypothesis is that fish feeds processed from animal wastes are efficient in raising catfish. The outcome of this study shall provide the basis for the formulation of fish feeds from organic wastes.

Keywords: assessment, feeds, health risk, wastes

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Authors: Raymond Dominic Uzoh

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Starch fillers were extracted from three plant sources namely amora tuber (a wild variety of Irish potato), sweet potato and yam starch and their particle size, pH, amylose, and amylopectin percentage decomposition determined accordingly by high performance liquid chromatography (HPLC). The starch was introduced into natural rubber in liquid phase (through gelatinization) by the latex compounding method and compounded according to standard method. The prepared starch/natural rubber composites was characterized by Instron Universal testing machine (UTM) for tensile mechanical properties. The composites was further characterized by x-ray diffraction and crosslink density analysis. The particle size determination showed that amora starch granules have the highest particle size (156 × 47 μm) followed by yam starch (155× 40 μm) and then the sweet potato starch (153 × 46 μm). The pH test also revealed that amora starch has a near neutral pH of 6.9, yam 6.8, and sweet potato 5.2 respectively. Amylose and amylopectin determination showed that yam starch has a higher percentage of amylose (29.68), followed by potato (22.34) and then amora starch with the lowest value (14.86) respectively. The tensile mechanical properties testing revealed that yam starch produced the best tensile mechanical properties followed by amora starch and then sweet potato starch. The structure, crystallinity/amorphous nature of the product composite was confirmed by x-ray diffraction, while the nature of crosslinking was confirmed by swelling test in toluene solvent using the Flory-Rehner approach. This research study has rendered a workable strategy for enhancing interfacial interaction between a hydrophilic filler (starch) and hydrophobic polymeric matrix (natural rubber) yielding moderately good tensile mechanical properties for further exploitation development and application in the rubber processing industry.

Keywords: natural rubber, fillers, starch, amylose, amylopectin, crosslink density

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Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

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This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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Authors: Mirco Tarozzi, Giacomo Pignagnoli, Andrea Benedetti

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The design of planning maintenance of civil structures often requires the evaluation of their level of safety in order to be able to choose which structure, and in which measure, it needs a structural retrofit. This work deals with the evaluation of the stiffness reduction of a scaled steel deck due to the presence of localized damages. The dynamic tests performed on it have shown the variability of its main frequencies linked to the gradual reduction of its rigidity. This deck consists in a steel grillage of four secondary beams and three main beams linked to a concrete slab. This steel deck is 6 m long and 3 m wide and it rests on two abutments made of concrete. By processing the signals of the accelerations due to a random excitation of the deck, the main natural frequencies of this bridge have been extracted. In order to assign more reliable parameters to the numerical model of the deck, some load tests have been performed and the mechanical property of the materials and the supports have been obtained. The two external beams have been cut at one third of their length and the structural strength has been restored by the design of a bolted plate. The gradual loss of the bolts and the plates removal have made the simulation of localized damage possible. In order to define the relationship between frequency variation and loss in stiffness, the identification of its natural frequencies has been performed, before and after the occurrence of the damage, corresponding to each step. The study of the relationship between stiffness losses and frequency shifts has been reported in this paper: the square of the frequency variation due to the presence of the damage is proportional to the ratio between the rigidities. This relationship can be used to quantify the loss in stiffness of a real scale bridge in an efficient way.

Keywords: damage detection, dynamic test, frequency shifts, operational modal analysis, steel bridge

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Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

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Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Ali Aydin, Mert Sudagidan, Aysen Coban, Alparslan Kadir Devrim

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Pseudomonas spp. (specifically, P. fluorescens and P. fragi) are considered the principal spoilage microorganisms of refrigerated poultry meats. The higher the level psychrophilic spoilage Pseudomonas spp. on carcasses at the end of processing lead to decrease the shelf life of the refrigerated product. The aim of the study was the identification of psychrophilic Pseudomonas spp. having proteolytic and lipolytic activities from poultry meats by 16S rRNA and rpoB gene sequencing, investigation of protease and lipase related genes and determination of proteolytic activity of Pseudomonas spp. In the of isolation procedure, collected chicken meat samples from local markets and slaughterhouses were homogenized and the lysates were incubated on Standard method agar and Skim Milk agar for selection of proteolytic bacteria and tributyrin agar for selection of lipolytic bacteria at +4 °C for 7 days. After detection of proteolytic and lipolytic colonies, the isolates were firstly analyzed by biochemical tests such as Gram staining, catalase and oxidase tests. DNA gene sequencing analysis and comparison with GenBank revealed that 126 strong enzyme Pseudomonas spp. were identified as predominantly P. fluorescens (n=55), P. fragi (n=42), Pseudomonas spp. (n=24), P. cedrina (n=2), P. poae (n=1), P. koreensis (n=1), and P. gessardi (n=1). Additionally, protease related aprX gene was screened in the strains and it was detected in 69/126 strains, whereas, lipase related lipA gene was found in 9 Pseudomonas strains. Protease activity was determined using commercially available protease assay kit and 5 strains showed high protease activity. The results showed that psychrophilic Pseudomonas strains were present in chicken meat samples and they can produce important levels of proteases and lipases for food spoilage to decrease food quality and safety.

Keywords: Pseudomonas, chicken meat, protease, lipase

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Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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Authors: S. Koul, Joshua Adedamola

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Currently, the global concerning fact about electromagnetic pollution (EMP) is that it not only adversely affects human health but rather projects the malfunctioning of sensitive equipment both locally and at a global level. The market offers many incumbent technologies to solve the issues, but still, a processable sustainable material solution with acceptable limits for GHG emission is still at an exploratory stage. The present work offers a sustainable material solution with a wide range of processability in terms of a polymeric resin matrix and shielding operational efficiency across the electromagnetic spectrum, covering both ionizing and non-ionizing electromagnetic radiations. The present work offers an in-situ synthesized conducting polyaniline (PANI) in the presence of the hybrid dual dopant system with tuned conductivity and high shielding efficiency between 89 to 92 decibels, depending upon the EMI frequency range. The conductive polymer synthesized in the presence of a hybrid dual dopant system via the in-situ emulsion polymerization method offers a higher surface resistance of 1.0 ohms/cm with thermal stability up to 2450C in their powder form. This conductive polymer with a hybrid dual dopant system was used as a filler material with different polymeric thermoplastic resin systems for the preparation of conductive composites. Intrinsically Conductive polymeric (ICP) composites based on hybrid dual dopant systems were prepared using melt blending, extrusion, and finally by, compression molding processing techniques. ICP composites with hybrid dual dopant systems offered good mechanical, thermal, structural, weathering, and stable surface resistivity properties over a period of time. The preliminary shielding behavior for ICP composites between frequency levels of 10 GHz to 24GHZ offered a shielding efficiency of more than 90 dB.

Keywords: ICP, dopant, EMI, shielding

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Authors: Neslihan Sahin Celik, Ali Eraslan

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Mathematical model and modeling are one of the topics that have been intensively discussed in recent years. In line with the results of the PISA studies, researchers in many countries have begun to question how much students in school-education system are prepared to solve the real-world problems they encounter in their future professional lives. As a result, many mathematics educators have begun to emphasize the importance of new skills and understanding such as constructing, Hypothesizing, Describing, manipulating, predicting, working together for complex and multifaceted problems for success in beyond the school. When students increasingly face this kind of situations in their daily life, it is important to make sure that students have enough experience to work together and interpret mathematical situations that enable them to think in different ways and share their ideas with their peers. Thus, model eliciting activities are one of main tools that help students to gain experiences and the new skills required. This research study was carried on the town center of a big city located in the Black Sea region in Turkey. The participants were eighth-grade students in a middle school. After a six-week preliminary study, three students in an eighth-grade classroom were selected using criterion sampling technique and placed in a focus group. The focus group of three students was videotaped as they worked on a model eliciting activity, the Summer Job Problem. The conversation of the group was transcribed, examined with students’ written work and then qualitatively analyzed through the lens of Blum’s (1996) modeling processing cycle. The study results showed that eighth grade students can successfully work with the model eliciting, develop a model based on the two parameters and review the whole process. On the other hand, they had difficulties to relate parameters to each other and take all parameters into account to establish the model.

Keywords: middle school, modeling, mathematical modeling, summer job problem

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Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

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Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman

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Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.

Keywords: mechanistic-empirical pavement design guide (MEPDG), traffic characteristics, materials properties, climate, Riyadh

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Authors: L. Piñeiro, N. Cobas, L. Gómez-Limia, S. Martínez, I. Franco

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The swordfish (Xiphias gladius) is a large oceanic fish of high commercial value, which is widely distributed in waters of the world’s oceans. They are considered to be an important source of high quality proteins, vitamins and essential fatty acids, although only half of the population follows the recommendation of nutritionists to consume fish at least twice a week. Swordfish is consumed worldwide because of its low fat content and high protein content. It is generally sold as fresh, frozen, and as pieces or slices. The aim of this study was to evaluate the effect of salting and frying on the composition of the water-soluble vitamins (B₂, B₃, B₉ and B₁₂) and fat-soluble vitamins (A, D, and E) of swordfish. Three loins of swordfish from Pacific Ocean were analyzed. All the fishes had a weight between 50 and 70 kg and were transported to the laboratory frozen (-18 ºC). Before the processing, they were defrosted at 4 ºC. Each loin was sliced and salted in brine. After cleaning the slices, they were divided into portions (10×2 cm) and fried in olive oil. The identification and quantification of vitamins were carried out by high-performance liquid chromatography (HPLC), using methanol and 0.010% trifluoroacetic acid as mobile phases at a flow-rate of 0.7 mL min^-1. The UV-Vis detector was used for the detection of the water- and fat-soluble vitamins (A and D), as well as the fluorescence detector for the detection of the vitamin E. During salting, water and fat-soluble vitamin contents remained constant, observing an evident decrease in the values of vitamin B₂. The diffusion of salt into the interior of the pieces and the loss of constitution water that occur during this stage would be related to this significant decrease. In general, after frying water-soluble and fat-soluble vitamins showed a great thermolability with high percentages of retention with values among 50–100%. Vitamin B₃ is the one that exhibited higher percentages of retention with values close to 100%. However, vitamin B₉ presented the highest losses with a percentage of retention of less than 20%.

Keywords: frying, HPLC, salting, swordfish, vitamins

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Authors: Pothula Madhusudhan Reddy

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Introduction: Yoga is a way of life. of uniting the mind, body and soul. It is also an art of living the right way. The techniques of Yoga are very practical, so they can always be applied. This is the reason why Yoga has been practiced for thousands of years and is still valid today. Importance of Yoga: Yoga that helps to inculcate healthy habits and adopt a healthy lifestyle to achieve good health Research Aim: The aim of this study is to explore the potential benefits of yoga for holistic health and wellbeing, both at an individual and societal level The ultimate goal of human being is to attain the state of perfect freedom from the shackles of ignorance, which is the generator of all the pangs and miseries of life. Methodology: This research follows a thematic and practical experience approach. Yoga includes body postures and movements (stretching), breathing practices, imagery, meditation, and progressive relaxation techniques. Data Collection: The data for this research is collected through a combination of literature review, expert interviews, and practical yoga sessions. The literature review provides a comprehensive understanding of the principles and practices of yoga, while expert interviews offer insights from experienced practitioners. Practical yoga sessions allow for first hand experiences and observations, facilitating a deeper understanding of the subject matter. Analysis Procedures: The collected data is analyzed thematically, where key themes and patterns related to the benefits and effects of yoga on holistic health and wellbeing are identified. The findings are then interpreted and synthesized to draw meaningful conclusions. Questions Addressed: This research addresses the following questions: What are the potential benefits of yoga for holistic health and wellbeing? How does yoga promote rejuvenate the body, mind, and senses? What are the implications of a society embracing yoga for overall societal wellbeing and happiness? Findings: The research highlights that practicing yoga can lead to increased awareness of the body, mind, and senses. It promotes overall physical and mental health, helping individuals achieve a state of happiness and contentment. Moreover, the study emphasizes that a society embracing yoga can contribute to the development of a healthy and happy community. Theoretical Importance: The study of yoga for holistic health and wellbeing holds theoretical importance as it provides insights into the science of yoga and its impact on individuals and society. It contributes to the existing body of knowledge on the subject and further establishes yoga as a potential tool for enhancing overall wellness. Conclusion: The study concludes that yoga is a powerful practice for achieving holistic health and wellbeing. This research provides valuable insights into the science of yoga and its potential as a tool for promoting overall wellness.

Keywords: yoga, asana, pranayama, meditation

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Authors: Abdallah Al-ZoubI, Mamoun Dmour

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The spectrum of IoT devices is becoming widely diversified, entering almost all possible fields and finding applications in industry, health, finance, logistics, education, to name a few. The IoT active endpoint sensors and devices exceeded the 12 billion mark in 2021 and are expected to reach 27 billion in 2025, with over $34 billion in total market value. This sheer rise in numbers and use of IoT devices bring with it considerable concerns regarding data storage, analysis, manipulation and protection. IoT Blockchain-based systems have recently been proposed as a decentralized solution for large-scale data storage and protection. COVID-19 has actually accelerated the desire to utilize IoT devices as it impacted both demand and supply and significantly affected several regions due to logistic reasons such as supply chain interruptions, shortage of shipping containers and port congestion. An IoT-blockchain system is proposed to handle big data generated by a distributed network of sensors and controllers in an interactive manner. The system is designed using the Ethereum platform, which utilizes smart contracts, programmed in solidity to execute and manage data generated by IoT sensors and devices. such as Raspberry Pi 4, Rasbpian, and add-on hardware security modules. The proposed system will run a number of applications hosted by a local machine used to validate transactions. It then sends data to the rest of the network through InterPlanetary File System (IPFS) and Ethereum Swarm, forming a closed IoT ecosystem run by blockchain where a number of distributed IoT devices can communicate and interact, thus forming a closed, controlled environment. A prototype has been deployed with three IoT handling units distributed over a wide geographical space in order to examine its feasibility, performance and costs. Initial results indicated that big IoT data retrieval and storage is feasible and interactivity is possible, provided that certain conditions of cost, speed and thorough put are met.

Keywords: IoT devices, blockchain, Ethereum, big data

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Authors: Abdul-Rahman Al-Ali

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As the number of mobile devices is growing exponentially, it is estimated to connect about 50 million devices to the Internet by the year 2020. At the end of this decade, it is expected that an average of eight connected devices per person worldwide. The 50 billion devices are not mobile phones and data browsing gadgets only, but machine-to-machine and man-to-machine devices. With such growing numbers of devices the Internet of Things (I.o.T) concept is one of the emerging technologies as of recently. Within the smart grid technologies, smart home appliances, Intelligent Electronic Devices (IED) and Distributed Energy Resources (DER) are major I.o.T objects that can be addressable using the IPV6. These objects are called the smart grid internet of things (SG-I.o.T). The SG-I.o.T generates big data that requires high-speed computing infrastructure, widespread computer networks, big data storage, software, and platforms services. A company’s utility control and data centers cannot handle such a large number of devices, high-speed processing, and massive data storage. Building large data center’s infrastructure takes a long time, it also requires widespread communication networks and huge capital investment. To maintain and upgrade control and data centers’ infrastructure and communication networks as well as updating and renewing software licenses which collectively, requires additional cost. This can be overcome by utilizing the emerging computing paradigms such as cloud computing. This can be used as a smart grid enabler to replace the legacy of utilities data centers. The talk will highlight the role of I.o.T, cloud computing services and their development models within the smart grid technologies.

Keywords: intelligent electronic devices (IED), distributed energy resources (DER), internet, smart home appliances

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Authors: Edison A. Bonifaz

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In this work, a numerical procedure is proposed to design dense multi-material structures using the Directed Energy Deposition (DED) process. A thermo-mechanical finite element model to predict thermal cycles and residual stresses is presented. A numerical layer build-up procedure coupled with a moving heat flux was constructed to minimize strains and residual stresses that result in the multi-layer deposition of an AISI 316 austenitic steel on an AISI 304 austenitic steel substrate. To simulate the DED process, the automated interface of the ABAQUS AM module was used to define element activation and heat input event data as a function of time and position. Of this manner, the construction of ABAQUS user-defined subroutines was not necessary. Thermal cycles and thermally induced stresses created during the multi-layer deposition metal AM pool crystallization were predicted and validated. Results were analyzed in three independent metal layers of three different experiments. The one-way heat and material deposition toolpath used in the analysis was created with a MatLab path script. An optimal combination of feedstock and heat input printing parameters suitable for fabricating multi-material dense structures in the directed energy deposition metal AM process was established. At constant power, it can be concluded that the lower the heat input, the lower the peak temperatures and residual stresses. It means that from a design point of view, the one-way heat and material deposition processing toolpath with the higher welding speed should be selected.

Keywords: event series, thermal cycles, residual stresses, multi-pass welding, abaqus am modeler

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Authors: Antonio Pratelli, Lorenzo Brocchini, Reginald Roy Souleyrette

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A rotary is a traffic circle intersection where vehicles entering from branches give priority to circulating flow. Vehicles entering the intersection from converging roads move around the central island and weave out of the circle into their desired exiting branch. This creates merging and diverging conflicts among any entry and its successive exit, i.e., a section. Therefore, rotary capacity models are usually based on the weaving of the different movements in any section of the circle, and the maximum rate of flow value is then related to each weaving section of the rotary. Nevertheless, the single-section capacity value does not lead to the typical performance characteristics of the intersection, such as the entry average delay which is directly linked to its level of service. From another point of view, modern roundabout capacity models are based on the limitation of the flow entering from the single entrance due to the amount of flow circulating in front of the entrance itself. Modern roundabouts capacity models generally lead also to a performance evaluation. This paper aims to incorporate a modern roundabout capacity model into an old rotary capacity method to obtain from the latter the single input capacity and ultimately achieve the related performance indicators. Put simply; the main objective is to calculate the average delay of each single roundabout entrance to apply the most common Highway Capacity Manual, or HCM, criteria. The paper is organized as follows: firstly, the rotary and roundabout capacity models are sketched, and it has made a brief introduction to the model combination technique with some practical instances. The successive section is deserved to summarize the TRRL old rotary capacity model and the most recent HCM-7th modern roundabout capacity model. Then, the two models are combined through an iteration-based algorithm, especially set-up and linked to the concept of roundabout total capacity, i.e., the value reached due to a traffic flow pattern leading to the simultaneous congestion of all roundabout entrances. The solution is the average delay for each entrance of the rotary, by which is estimated its respective level of service. In view of further experimental applications, at this research stage, a collection of existing rotary intersections operating with the priority-to-circle rule has already started, both in the US and in Italy. The rotaries have been selected by direct inspection of aerial photos through a map viewer, namely Google Earth. Each instance has been recorded by location, general urban or rural, and its main geometrical patterns. Finally, conclusion remarks are drawn, and a discussion on some further research developments has opened.

Keywords: mixed methods, old rotary and modern roundabout capacity models, total capacity algorithm, level of service estimation

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Authors: Grazia Disciglio, Francesco Lops, Annalisa Tarantino, Emanuele Tarantino

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The parasitic weed specie Phelipanche ramosa (L) Pomel is one of the major constraints in tomato crop in Apulia region (southern Italy). The experimental was considered to investigate the effect of six organic compounds (Olive miller wastewater, Allil isothiocyanate®, Alfa plus K®, Radicon®, Rizosum Max®, Kendal Nem®) on the naturally infested field of tomato growing season in 2016. The randomized block design with 3 replicates was adopted. Tomato seedling were transplant on 19 May 2016. During the growing cycle of the tomato at 74, 81, 93 and 103 days after transplantation (DAT), the number of parasitic shoots (branched plants) that had emerged in each plot was determined. At harvesting on 13 September 2016 the major quanti-qualitative yield parameters were determined, including marketable yield, mean weight, dry matter, soluble solids, fruit colour, pH and titratable acidity. The treatments provided the results show that none of treatments provided complete control against P. ramosa. However, among the products tested Olive miller wastewater, Alfa plus K®, Rizosum Max® and Kendal Nem® products applied to the soil show the number of emerged shoots significantly lower than Radicon® and especially than the Allil isothiocyanate® treatment and the untreated control. Regarding the effect of different treatments on the tomato productive parameters, the marketable yield resulted significantly higher in the same mentioned treatments which gave the lower P. ramosa infestation. No significative differences for the other fruit characteristics were observed.

Keywords: processing tomato crop, Phelipanche ramosa, olive-mill wastewater, organic fertilizers

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Authors: Safieh Javadinejad

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In order to make well-informed decisions respecting long-term system planning, resource managers and policy creators necessitate to comprehend the interconnections among energy and water utilization and manufacture—and also the energy-water nexus. Planning and assessment issues contain the enhancement of strategies for declining the water and energy system’s vulnerabilities to climate alteration with also emissions of decreasing greenhouse gas. In order to deliver beneficial decision support for climate adjustment policy and planning, understanding the regionally-specific features of the energy-water nexus, and the history-future of the water and energy source systems serving is essential. It will be helpful for decision makers understand the nature of current water-energy system conditions and capacity for adaptation plans for future. This research shows an integrated hydrology/energy modeling platform which is able to extend water-energy examines based on a detailed illustration of local circumstances. The modeling links the Water Evaluation and Planning (WEAP) and the Long Range Energy Alternatives Planning (LEAP) system to create full picture of water-energy processes. This will allow water managers and policy-decision makers to simply understand links between energy system improvements and hydrological processing and realize how future climate change will effect on water-energy systems. The Zayandeh Rud river basin in Iran is selected as a case study to show the results and application of the analysis. This region is known as an area with large integration of both the electric power and water sectors. The linkages between water, energy and climate change and possible adaptation strategies are described along with early insights from applications of the integration modeling system.

Keywords: climate impacts, hydrology, water systems, adaptation planning, electricity, integrated modeling

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Authors: Clara Voyvodic

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Transitions from conflict to peace are by no means smooth nor linear, particularly from the perspective of those living through them. Over the last few decades, the changing focus in peacebuilding studies has come to appreciate the everyday experience of communities and how that provides a lens through which the relative success or efficacy of these transitions can be understood. In particular, the demobilization of a significant conflict actor is not without consequences, not just for the macro-view of state stabilization and peace, but for the communities who find themselves without a clear authority of territorial control. In Colombia, the demobilization and disarmament of the FARC guerilla group provided a brief respite to the conflict and a major political win for President Manuel Santos. However, this victory has proven short-lived. Drawing from extensive field research in Colombia within the last year, including interviews with local communities and actors operating in these regions, field observations, and other primary resources, this paper examines the post-accord transitions in Colombia and the everyday security experiences of local communities in regions formerly controlled by the FARC. In order to do so, the research focused on a semi-ethnographic approach in the northern region of the department of Antioquia and the coastal area of the border department of Nariño that documented how individuals within these marginalized communities have come to understand and negotiate their security in the years following the accord and the demobilization of the FARC. This presentation will argue that the removal of the FARC as an informal governance actor opened a space for multiple actors to attempt to control the same territory, including the state. This shift has had a clear impact on the everyday security experiences of the local communities. With an exploration of the dynamics of local governance and its impact on lived security experiences, this research seeks to demonstrate how distinct patterns of armed group behavior are emerging not only from a vacuum of control left by the FARC but from an increase in state presence that nonetheless remains inconsistent and unpersuasive as a monopoly of force in the region. The increased multiplicity of actors, particularly the state, has meant that the normal (informal) rules for communities to navigate these territories are no longer in play as the identities, actions, and intentions of different competing groups have become frustratingly opaque. This research provides a prescient analysis on how the shifting dynamics of territorial control in a post-peace accord landscape produce uncertain realities that affect the daily lives of the local communities and endanger the long-term prospect of human-centered security.

Keywords: armed actors, conflict transitions, informal governance, post-accord, security experiences

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Authors: Quoc Hung Le Pham

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In the field of language study, classifier is an interesting research feature. In the world’s languages, some languages have classifier system, some do not. Mandarin Chinese and Vietnamese languages are a rich classifier system, however, because of the language system, the cognitive, cultural differences, so that the syntactic structure of classifier of them also dissimilar. When using Mandarin Chinese classifiers must collocate with nouns or verbs, in the lexical category it is not like nouns or verbs, belong to the open class. But some scholars believe that Mandarin Chinese measure words are similar to English and other Indo European languages. The word hanging on the structure and word formation (suffix), is a closed class. Compared to other languages, such as Chinese, Vietnamese, Thai and other Asian languages are still belonging to the classifier language’s second type, this type of language is classifier, it is in the majority of quantity must exist, and following deictic, anaphoric or quantity appearing together, not separation between its modified noun, also known as numeral classifier language. Main syntactic structure of Chinese classifiers are as follows: ‘quantity+measure+noun’, ‘pronoun+measure+noun’, ‘pronoun+quantity+measure+noun’, ‘prefix+quantity+measure +noun’, ‘quantity +adjective + measure +noun’, ‘ quantity (above 10 whole number), + duo (多)measure +noun’, ‘ quantity (around 10) + measure + duo (多) +noun’. Main syntactic structure of Vietnamese classifiers are: ‘quantity+measure+noun’, ‘ measure+noun+pronoun’, ‘quantity+measure+noun+pronoun’, ‘measure+noun+prefix+ quantity’, ‘quantity+measure+noun+adjective', ‘duo (多) +quanlity+measure+noun’, ‘quantity+measure+adjective+pronoun (quantity word could not be 1)’, ‘measure+adjective+pronoun’, ‘measure+pronoun’. In daily life, classifiers are commonly used, if Chinese learners failed to standardize this using catergory, because the negative impact might occur on their verbal communication. The richness of the Chinese classifier system contributes to the complexity in the study of the system by foreign learners, especially in the inter language of Vietnamese learners. As above mentioned, Vietnamese language also has a rich system of classifiers, however, the basic structure order of two languages are similar but both still have differences. These similarities and dissimilarities between Chinese and Vietnamese classifier systems contribute significantly to the common errors made by Vietnamese students while they acquire Chinese, which are distinct from the errors made by students from the other language background. This article from a comparative perspective of language, has an orientation towards Chinese and Vietnamese languages commonly used in classifiers semantics and structural form two aspects. This comparative study aims to identity Vietnamese students while learning Chinese classifiers may face some negative transference of mother language, beside that through the analysis of the classifiers questionnaire, find out the causes and patterns of the errors they made. As the preliminary analysis shows, Vietnamese students while learning Chinese classifiers made some errors such as: overuse classifier ‘ge’(个); misuse the other classifiers ‘*yi zhang ri ji’(yi pian ri ji), ‘*yi zuo fang zi’(yi jian fang zi), ‘*si zhang jin pai’(si mei jin pai); homonym words ‘dui, shuang, fu, tao’ (对、双、副、套), ‘ke, li’ (颗、粒).

Keywords: acquisition, classifiers, negative transfer, Vietnamse learners

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Authors: Yebeen Ji, Jimin Yun, Kwonhoo Kim

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Magnesium alloys were limited for industrial applications due to having a limited slip system and high plastic anisotropy. It has been known that specific textures were formed during processing (rolling, etc.), and These textures cause poor formability. To solve these problems, many researchers have studied controlling texture by adding rare-earth elements. However, the high cost limits their use; therefore, alternatives are needed to replace them. Although Pb addition doesn’t directly improve magnesium properties, it has been known to suppress the diffusion of other alloying elements and reduce grain boundary energy. These characteristics are similar to the additions of rare-earth elements, and a similar texture behavior is expected as well. However, there is insufficient research on this. Therefore, this study investigates the behavior of texture and microstructure development after adding Pb to magnesium. This study compared and analyzed AZ61 alloy and Mg-15wt%Pb alloy to determine the effect of adding solute elements. The alloy was hot rolled and annealed to form a single phase and initial texture. Afterward, the specimen was set to contraction and elongate parallel to the rolling surface and the rolling direction and then subjected to high-temperature plane strain compression under the conditions of 723K and 0.05/s. Microstructural analysis and texture measurements were performed by SEM-EBSD. The peak stress in the true strain-stress curve after compression was higher in AZ61, but the shape of the flow curve was similar for both alloys. For both alloys, continuous dynamic recrystallization was confirmed to occur during the compression process. The basal texture developed parallel to the compressed surface, and the pole density was lower in the Mg-15wt%Pb alloy. It is confirmed that this change in behavior is because the orientation distribution of recrystallized grains has a more random orientation compared to the parent grains when Pb is added.

Keywords: Mg, texture, Pb, DRX

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Authors: Jamuna Loganath

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Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.

Keywords: big data, cloud, CCTV, education process

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Authors: Mária Ildikó Farkas

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Kokugaku of the Edo period can be seen as a key factor of defining cultural (and national) identity in the 18th and early 19th century based on Japanese cultural heritage. Kokugaku focused on Japanese classics, on exploring, studying and reviving (or even inventing) ancient Japanese language, literature, myths, history and also political ideology. ‘Japanese culture’ as such was distinguished from Chinese (and all other) cultures, ‘Japanese identity’ was thus defined. Meiji scholars used kokugaku conceptions of Japan to construct a modern national identity based on the premodern and culturalist conceptions of community. The Japanese cultural movement of the 18-19th centuries (kokugaku) of defining cultural and national identity before modernization can be compared not to the development of Western Europe (where national identity strongly attached to modern nation states) or other parts of Asia (where these emerged after the Western colonization), but rather with the ‘national awakening’ movements of the peoples of East Central Europe, a comparison which have not been dealt with in the secondary literature yet. The role of a common language, culture, history and myths in the process of defining cultural identity – following mainly Miroslav Hroch’s comparative and interdisciplinary theory of national development – can be examined compared to the movements of defining identity of the peoples of East Central Europe (18th-19th c). In the shadow of a cultural and/or political ‘monolith’ (China for Japan and Germany for Central Europe), before modernity, ethnic groups or communities started to evolve their own identities with cultural movements focusing on their own language and culture, thus creating their cultural identity, and in the end, a new sense of community, the nation. Comparing actual texts (‘narratives’) of the kokugaku scholars and Central European writers of the nation building period (18th and early 19th centuries) can reveal the similarities of the discourses of deliberate searches for identity. Similar motives of argument can be identified in these narratives: ‘language’ as the primary bearer of collective identity, the role of language in culture, ‘culture’ as the main common attribute of the community; and similar aspirations to explore, search and develop native language, ‘genuine’ culture, ‘original’ traditions. This comparative research offering ‘development patterns’ for interpretation can help us understand processes that may be ambiguously considered ‘backward’ or even ‘deleterious’ (e.g. cultural nationalism) or just ‘unique’. ‘Cultural identity’ played a very important role in the formation of national identity during modernization especially in the case of non-Western communities, who had to face the danger of losing their identities in the course of ‘Westernization’ accompanying modernization.

Keywords: cultural identity, Japanese modernization, kokugaku, national awakening

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