Search results for: haptic information

Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

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Authors: Maeng-Hwan Hyun, Dae-Man Do, Young-Bok Choi

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Around the world, there are frequent incidents of natural disasters, such as earthquakes, tsunamis, floods, and snowstorms, as well as man made disasters such as fires, arsons, and acts of terror. These diverse and unpredictable adversities have resulted in a number of fatalities and injuries. If disaster occurrence can be assessed quickly and information such as the exact location of the disaster and evacuation routes can be provided, victims can promptly move to safe locations, minimizing losses. This paper proposes a behavior analysis method based on a nine degrees-of-freedom (9-DOF) sensor that is effective for the emergency rescue evacuation support system (ERESS), which is being researched with an objective of providing evacuation support during disasters. Based on experiments performed using the acceleration sensor and the gyroscope sensor in the 9-DOF sensor, data are analyzed for human behavior regarding stationary position, walking, running, and during emergency situation to suggest guidelines for system judgment. Using the results of the experiments performed to determine disaster occurrence, it was confirmed that the proposed method quickly determines whether a disaster has occurred.

Keywords: behavior analysis, nine degrees of freedom sensor, emergency rescue, disaster

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Authors: Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa

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This research aims to develop a self-study system equipped with an artificial teacher who gives advice to students by detecting the learners and to evaluate language learning in a unified framework. 'Detecting the learners' means that the system understands the learners' learning conditions, such as each learner’s degree of understanding, the difference in each learner’s thinking process, the degree of concentration or boredom in learning, and problem solving for each learner, which can be interpreted from learning behavior. In this paper, we propose a system to efficiently collect brain waves from learners by focusing on only the brain waves among the biological information for 'detecting the learners'. The conventional Electroencephalograph (EEG) measurement method during learning using a simple EEG has the following disadvantages. (1) The start and end of EEG measurement must be done manually by the experiment participant or staff. (2) Even when the EEG signal is weak, it may not be noticed, and the data may not be obtained. (3) Since the acquired EEG data is stored in each PC, there is a possibility that the time of data acquisition will be different in each PC. This time, we developed a system to collect brain wave data on the server side. This system overcame the above disadvantages.

Keywords: artificial teacher, e-learning, self-study system, simple EEG

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Authors: Siri-Orn Champatong

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This research paper was aimed to examine the relationship between visitors’ attitude towards the service marketing mix and visitors’ frequency of visit to Bangpu Recreation Centre. Based on a large and uncalculated population, the number of samples was calculated according to the formula to obtain a total of 385 samples. In collecting the samples, systematic random sampling was applied and by using of a Likert five-scale questionnaire for, a total of 21 days to collect the needed information. Mean, Standard Deviation, and Pearson’s basic statistical correlations were utilized in analyzing the data. This study discovered a high level of visitors’ attitude product and service of Bangpu Recreation Centre, price, place, promotional activities, people who provided service and physical evidence of the centre. The attitude towards process of service was discovered to be at a medium level. Additionally, the finding of an examination of a relationship between visitors’ attitude towards service marketing mix and visitors’ frequency of visit to Bangpu Recreation Centre presented that product and service, people, physical evidence and process of service provision showed a relationship with the visitors’ frequency of visit to the centre per year.

Keywords: frequency of visit, visitor, service marketing mix, Bangpu Recreation Centre

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Kidus Dawit Gedamu

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Addis Ababa City Road Authority is responsible for managing and setting performance evaluation of the city’s road network using the International Roughness Index (IRI). This helps the authority to conduct pavement condition assessments of asphalt roads each year to determine the health status or Level of service (LOS) of the roadway network and plan program improvements such as maintenance, resurfacing and rehabilitation. For a lower IRI limit economical and acceptable maintenance strategy may be selected among a number of maintenance alternatives. The Highway Development and Management (HDM-4) tool can do such measures to help decide which option is the best by evaluating the economic and structural conditions. This paper specifically addresses flexible pavement, including two principal arterial streets under the administration of the Addis Ababa City Roads Authority. The roads include the road from Megenagna Interchange to Ayat Square and from Ayat Square to Tafo RA. First, it was assessed the procedures followed by the city's road authority to develop the appropriate road maintenance strategies. Questionnaire surveys and interviews are used to collect information from the city's road maintenance departments. Second, the project analysis was performed for functional and economic comparison of different maintenance alternatives using HDM-4.

Keywords: appropriate maintenance strategy, cost stream, road deterioration, maintenance alternative

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Authors: Ryan Tehini

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The purpose of this paper is to explore the value of practical experience with Autism Spectrum Disorder (ASD) as a microcosm of mental disorders, in psychology students’ attempt to fully understand it in all of its intricacies. The study follows a one-year program where students of psychology volunteer at a school for Autistic children of ages 3-18. The individual levels of experience with, and theoretical understanding of, ASD varies measurably amongst the volunteers; these volunteers are then intermittently interviewed, observed and surveyed throughout the program in order to determine any decline or growth in their understanding of Autism Spectrum Disorder. A panel of professionals all of whom are active in the world of ASD (headmasters of Autistic schools, psychologists, child development specialists, special needs teachers, parents of autistic children and Occupational Therapists) were used specifically for this study, in order to develop the guideline for understanding ASD that will be used comparatively against the information gained from the volunteers in order to establish the individual results. The paper concludes by illustrating how psychology has a responsibility to the community to understand disorders past what is academic and theoretical, and how increasing student experience with a disorder can aid in a more holistic psychological approach to mental disorders in the future.

Keywords: autism, mental disorders, practical experience, psychology

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Authors: Hakan Bozdoğan

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A wide variety of traditional methodologies has been enhanced for characterising smooth habitats in order to find out different environmental objectives. The habitats were characterised based on size and shape by using Geo-Gebra Software. In this study, an innovative approach to researching habitat characterisation in the lacewing species, GeoGebra software is utilised. This approach is demonstrated using the example of ‘surface area’ as an analytical concept, wherein the goal was to increase clearness for researchers, and to improve the quality of researching in survey area. In conclusion, habitat characterisation using the mathematical programme provides a unique potential to collect more comprehensible and analytical information about in shapeless areas beyond the range of direct observations methods. This research contributes a new perspective for assessing the structure of habitat, providing a novel mathematical tool for the research and management of such habitats and environments. Further surveys should be undertaken at additional sites within the Amanos Mountains for a comprehensive assessment of lacewings habitat characterisation in an analytical plane. This paper is supported by Ahi Evran University Scientific Research Projects Coordination Unit, Projects No:TBY.E2.17.001 and TBY.A4.16.001.

Keywords: uneven habitat shape, habitat assessment, lacewings, Geo-Gebra Software

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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Authors: Bezhan Ghvaberidze

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A fuzzy multi-objective facility location-selection problem (FLSP) under uncertain and extreme environments based on possibility theory is developed. The model’s uncertain parameters in the q-rung orthopair fuzzy values are presented and transformed in the Dempster-Shaper’s belief structure environment. An objective function – distribution centers’ selection ranking index as an extension of Dempster’s extremal expectations under discrimination q-rung orthopair fuzzy information is constructed. Experts evaluate each humanitarian aid from distribution centers (HADC) against each of the uncertain factors. HADCs location problem is reduced to the bicriteria problem of partitioning the set of customers by the set of centers: (1) – Minimization of transportation costs; (2) – Maximization of centers’ selection ranking indexes. Partitioning type constraints are also constructed. For an illustration of the obtained results, a numerical example is created from the facility location-selection problem.

Keywords: FLSP, multi-objective combinatorial optimization problem, evidence theory, HADC, q-rung orthopair fuzzy set, possibility theory

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Authors: Issa M. Hweidi, Saba W. Al-Ibraheem

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This study aimed to assess the increased hospital length of stay and healthcare costs associated with SSIs among ventriculoperitoneal shunting surgery patients in Jordan. This study adopted a retrospective and nested 1:1 matched case-control design. A non-probability convenient sample of 48 VP shunt patients was recruited for the purpose of the study. The targeted groups of the study basically used to cross-match the variables investigated to minimize the risk of confounding. Information was extracted from the text of patients' electronic health records. As compared to the non-SSI group, the SSI group had an extra mean healthcare cost of $13,696.53 (p=0.001) and longer hospital length of stay (22.64 mean additional days). Furthermore, Acinetobacter baumannii and Klebsiella pneumonia were identified as being the most predominant causative agents of SSIs. The results of this study may provide baseline data for national and regional benchmarking to evaluate the quality of care provided to likewise patients. Adherence to infection control strategies and protocols considering new surveillance methods of SSIs is encouraged.

Keywords: ventriculoperitoneal shunt, health care cost, length of stay, neurosurgery, surgical site infections

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Authors: George D. Ranis, Valasia Iakovoglou, George N. Zaimes

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Fires are one of the main types of disturbances that shape ecosystems in the Mediterranean region. However nowadays, climate alterations towards higher temperature regimes results on the increased levels of the intensity, frequency and the spread of fires inducing obstacles for the natural regeneration. Thasos Island is one of the Greek islands that have experienced those problems. Since 1984, a series of wildfires led to the reduction of forest cover from 61.6% to almost 20%. The negative impacts were devastating in many different aspects for the island. The absence of plant cover, post-wildfire precipitation and steep slopes were the major factors that induced severe soil erosion and intense flooding events. That also resulted to serious economic problems to the local communities and the ability of the burnt areas to regenerate naturally. Despite the substantial amount of published work regarding Thasos wildfires, there is no information related to post-wildfire effects on the hydrology and soil erosion. More research related to post-fire effects should help to an overall assessment of the negative impacts of wildfires on land degradation through processes such as soil erosion and flooding.

Keywords: erosion, land degradation, Mediterranean islands, regeneration, Thasos, wildfires

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Authors: Shayan Rezvanigilkolaei, Shayesteh Vefaghnematollahi

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Electrical impedance tomography is a non-invasive medical imaging technique suitable for medical applications. This paper describes an electrical impedance tomography device with the ability to navigate a robotic arm to manipulate a target object. The design of the device includes various hardware and software sections to perform medical imaging and control the robotic arm. In its hardware section an image is formed by 16 electrodes which are located around a container. This image is used to navigate a 3DOF robotic arm to reach the exact location of the target object. The data set to form the impedance imaging is obtained by having repeated current injections and voltage measurements between all electrode pairs. After performing the necessary calculations to obtain the impedance, information is transmitted to the computer. This data is fed and then executed in MATLAB which is interfaced with EIDORS (Electrical Impedance Tomography Reconstruction Software) to reconstruct the image based on the acquired data. In the next step, the coordinates of the center of the target object are calculated by image processing toolbox of MATLAB (IPT). Finally, these coordinates are used to calculate the angles of each joint of the robotic arm. The robotic arm moves to the desired tissue with the user command.

Keywords: electrical impedance tomography, EIT, surgeon robot, image processing of electrical impedance tomography

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Authors: Ahmed Amin Mousa, M. Abd El-Salam

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This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.

Keywords: kindergarten, child, learning resources, QR code, smart phone, mobile

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Authors: Alhulw H. Alshammari, Ahmed Iraqi, S. A. Saad, T. A. Taha

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In this work, we present for the first time the study of Raman spectra and dielectric relaxation of polyester polymer-CoFe₂O₄ (5.0, 10.0, 15.0, and 20.0 wt%) nanocomposites. Raman spectroscopy was applied as a sensitive structural identification technique to characterize the polyester-CoFe₂O₄ nanocomposites. The images of AFM confirmed the uniform distribution of CoFe₂O₄ inside the polymer matrix. Dielectric relaxation was employed as an important analytical technique to obtain information about the ability of the polymer nanocomposites to store and filter electrical signals. The dielectric relaxation analyses were carried out on the polyester-CoFe₂O₄ nanocomposites at different temperatures. An increase in dielectric constant ε₁ was observed for all samples with increasing temperatures due to the alignment of the electric dipoles with the applied electric field. In contrast, ε₁ decreased with increasing frequency. This is attributed to the difficulty for the electric dipoles to follow the electric field. The α relaxation peak that appeared at a high frequency shifted to higher frequencies when increasing the temperature. The activation energies for Maxwell-Wagner Sillar (MWS) changed from 0.84 to 1.01 eV, while the activation energies for α relaxations were 0.54 – 0.94 eV. The conduction mechanism for the polyester- CoFe₂O₄ nanocomposites followed the correlated barrier hopping (CBH) model.

Keywords: AC conductivity, activation energy, dielectric permittivity, polyester nanocomposites

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Authors: Jana Heimel, Franziska Drescher, Lauren Ugur, Graciela Kuchle

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Sharing platforms are a widely investigated field. However, there is a research gap with a lack of focus on ‘real’ (non-profit-orientated) sharing platforms. The research project addresses this gap by conducting an empirical study on a private peer-to-peer (P2P) network to investigate cooperative behavior from a socio-psychological perspective. In recent years the conversion from possession to accessing is increasingly influencing different sectors, particularly the traveling industry. The number of people participating in hospitality exchange platforms like Airbnb, Couchsurfing, and Warmshowers (WS) is rapidly growing. WS is an increasingly popular online community that is linking cycling tourists and locals. It builds on the idea of the “sharing economy” as a not-for-profit hospitality network for bicycle tourists. Hosts not only provide a sleeping berth and warm shower free of charge but also offer additional services to their guests, such as cooking and washing clothes for them. According to previous studies, they are motivated by the idea of promoting cultural experience and forming new friendships. Trust and reciprocity are supposed to play major roles in the success of such platforms. The objective of this research project is to analyze the reciprocity behavior within the WS community. Reciprocity is the act of giving and taking among each other. Individuals feel obligated to return a favor and often expect to increase their own chances of receiving future benefits for themselves. Consequently, the drivers that incite giving and taking, as well as the motivation for hosts and guests, are examined. Thus, the project investigates a particular tourism offer that contributes to sustainable tourism by analyzing P2P resp. cyclist-to-cyclist, C2C) tourism. C2C tourism is characterized by special hospitality and generosity. To find out what motivations drive the hosts and which determinants drive the sharing cycling economy, an empirical study has been conducted globally through an online survey. The data was gathered through the WS community and comprised responses from more than 10,000 cyclists around the globe. Next to general information mostly comprising quantitative data on bicycle tourism (year/tour distance, duration and budget), qualitative information on traveling with WS as well as hosting was collected. The most important motivations for a traveler is to explore the local culture, to save money, and to make friends. The main reasons to host a guest are to promote the use of bicycles and to make friends, but also to give back and pay forward. WS members prefer to stay with/host cyclists. The results indicate that C2C tourists share homogenous characteristics and a similar philosophy, which is crucial for building mutual trust. Members of WS are generally extremely trustful. The study promotes an ecological form of tourism by combining sustainability, regionality, health, experience and the local communities' cultures. The empirical evidence found and analyzed, despite evident limitations, enabled us to shed light, especially on the issue of motivations and social capital, and on the functioning of ‘sharing’ platforms. Final research results are intended to promote C2C tourism around the globe to further replace conventional by sustainable tourism.

Keywords: bicycle tourism, homogeneity, reciprocity, sharing economy, trust

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Authors: Muhammad R. Ahmed, Mohammed Aseeri

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Wireless Sensor Network (WSN) consists of low-cost and multi functional resources constrain nodes that communicate at short distances through wireless links. It is open media and underpinned by an application driven technology for information gathering and processing. It can be used for many different applications range from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. With its nature and application scenario, security of WSN had drawn a great attention. It is known to be valuable to variety of attacks for the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or internal attacker has gained prominence and poses the most challenging attacks to WSN. Many works have been done to secure WSN from internal attacks but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure a WSN needs to find the internal attacks is a challenge. In this paper we present an internal attack detection method based on maximum entropy model. The final experimental works showed that the proposed algorithm does work well at the designed level.

Keywords: internal attack, wireless sensor network, network security, entropy

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: A. Alvaredo , R. Guzman De Villoria, P. Castell, Juan P. Fernandez-Blazquez

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Since graphene was discovered in 2004, has been considered as superb material, due to its outstanding mechanical, electrical and thermal properties. Graphene has been incorporated as reinforcement in several high performance polymers in order to obtain a good balance of properties and to get new properties as thermal or electric conductivity. As well known, the properties of semicrystalline polymer and its composites depends heavily on degree of crystallinity. In this context, our research group has studied the crystallization behavior from amorphous state of PEEK/GNP composites. The monitoring of cold crystallization processes studied by time-resolved simultaneous wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS). These techniques allowed to get an extremely relevant information about the evolution of the morphology of the PEEK/GNP composites. In addition, the thermal evolution of cold crystallization was followed by differential scanning calorimetry (DSC) as well. The experimental results showed changes in crystallization kinetics and c parameter unit cell when adding graphene. The main aim of this work is to produce PEEK/GNP composites and characterize their morphology, unit cell parameters and crystallization kinetic.

Keywords: PEEK, graphene, synchrotron, cold crystallization

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Authors: Juan Sebastián Hernández

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The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

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Authors: Elham Abbas Aljaaly, Nahlaa Abdulwahab Khalifa

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The active method of disease prevention is seen as the most affordable and sustainable action to deal with risks of non-communicable diseases such as obesity. This eight-week project aimed to pilot the feasibility and acceptability of a school-based programme, which is proposed to prevent and modify overweight status and possible related risk factors among student girls 'at the intermediate level' in Jeddah city. The programme was conducted through comprehensible approach targeting physical environment and school policies (nutritional/exercise/behavioural approach). The programme was designed to cultivate the personal and environmental awareness in schools for girls. This was applied by promoting healthy eating and physical activity through policies, physical education, healthier options for school canteens, and the creation of school health teams. The prevention programme was applied on 68 students (who agreed to participate) from grades 7th, 8th and 9th. A pre and post assessment questionnaire was employed on 66 students. The questionnaires were designed to obtain information on students' knowledge about health, nutrition and physical activity. Survey questions included information about nutrients, food consumption patterns, food intake and lifestyle. Physical education included training sessions for new opportunities for physical activities to be performed during school or after school hours. A running competition 'to enhance students’ performance for physical activities' was also conducted during the school visit. A visit to the school canteen was conducted to check, observe, record and assess all available food/beverage items and meals. The assessment method was a subjective method for the type of food/beverages if high in saturated fat, salt and sugar (HFSS) or non-HFSS. The school canteen administrators were encouraged to provide healthy food/beverage items and a sample healthy canteen was provided for implementation. Two healthy options were introduced to the school canteen. A follow up for students’ preferences for the introduced options and the purchasing power were assessed. Thirty-eight percent of young girls (n=26) were not participating in any form of physical activities inside or outside school. Skipping breakfast was stated by 42% (n=28) of students with no daily consumption (19%, n=13) for fruit/vegetables. Significant changes were noticed in students’ (n=66) overall responses to the pre and post questions (P value=.001). All students had participated in the conducted running competition sessions and reported satisfaction and enjoyment about the sessions. No absence was reported by the research team for attending physical education and activity sessions throughout the delivered programme. The purchasing power of the introduced healthy options of 'Salad and oatmeal' was increased to 18% in 8 weeks at the school canteen, and slightly affected the purchase for other less healthy options. The piloted programme indorsed better health and nutrition knowledge, healthy eating and lifestyle attitude, which could help young girls to obtain sustainable changes. It is expected that the outcomes of the programme will be a cornerstone for the futuristic national study that will assist policy makers and participants to build a knowledgeable health promotion scenario and make sure that school students have access to healthy foods, physical exercise and healthy lifestyle.

Keywords: adolescents, diet, exercise, behaviours, overweight/obesity, prevention-intervention programme, Saudi Arabia, schoolgirls

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Authors: Chutikarn Sriwiboon

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The purposes of this paper were to study the production problems of basketry in the central region and to study the development of potential in skilled labourers in producing basketry in three provinces: Suphanburi, Ayuthaya, and Aungthong. A quota sampling was utilized to get 486 respondents from 243 basketry communities that were registered with OTOP project. A focus group was also used with a connoisseurship model to study knowledge and factors that related to the development of potential in skilled labourers in producing basketry. The findings revealed that the process getting service is the major problem for customers to get service. Also, there should be more of a variety of knowledge for customers. In terms of technology, the variety of information was rated as the most important problem. In terms staff's ability, the knowledge of staff was the most important problem. For the development of potential in high skilled labours for basketry, the findings revealed that having proper tools was considered the most important factor. In terms of economy, the findings revealed that the basketry job must provide sufficient income was considered the most important factor. In terms of using natural resources, efficiency is the most important factor. In terms of mentality, integrity is the most important factor. Finally, in terms of society and culture, help in the local activities is the most important factor.

Keywords: basketry, development, potential, skilled labours

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Authors: Hatem A. El-Mezayen, Ahmed Abdelmajeed, Fatehya Metwally, Usama Elsaly, Salwa Atef

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Tumor metastasis involves the dissemination of malignant cells into the basement membrane and vascular system contributes to the circulating pool of these markers. In this context our aim has been focused on development of a non-invasive. Circulating tumor cells (CTCs) represent a unique liquid biopsy carrying comprehensive biological information of the primary tumor. Herein, we sought to develop a novel score based on the combination of the most significant CTCs biomarkers with and routine laboratory tests for accurate detection of metastatic breast cancer. Methods: Cytokeratin 18 (CK18), Cytokeratin 19 (CK19), and CA15.3 were assayed in metastatic breast cancer (MBC) patients (75), non-MBC patients (50) and healthy control (20). Results: Areas under receiving operating curve (AUCs) were calculated and used for construction on novel score. A novel score named MBC-CTCs = CA15.3 (U/L) × 0.08 + CK 18 % × 2.9 + CK19 × 3.1– 510. That function correctly classified 87% of metastatic breast cancer at cut-off value = 0.55. (i.e great than 0.55 indicates patients with metastatic breast cancer and less than 0.55 indicates patients with non-metastatic breast cancer). Conclusion: MBC-CTCs is a novel, non-invasive and simple can applied to discriminate patients with metastatic breast cancer.

Keywords: metastatic breast cancer, circulating tumor cells, cytokeratin, EpiCam

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: Imoh Philip

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Basà language is classified as belonging to Kainji family, under the sub-phylum Western-Kainji known as Rubasa (Basa Benue) (Croizier & Blench, 1992:32). Basà is an under-described language spoken in the North-Central Nigeria. The language is characterized by subject-verb-object (henceforth SVO) as its canonical word order. Data for this work is sourced from the researcher’s native intuition of the language corroborated with a careful observation of native speakers. This paper investigates the syntactic derivational strategy of information-structure encoding in Basà language. It emphasizes on a negative operator, as a strategy for focusing a constituent or clause that follows it and negativizes a whole proposition. For items that are not nouns, they have to undergo an obligatory nominalization process, either by affixation, modification or conversion before they are moved to the pre verbal position for these operations. The study discovers and provides evidence of the fact showing that deferent constituents in the sentence such as the subject, direct, indirect object, genitive, verb phrase, prepositional phrase, clause and idiophone, etc. can be focused with the same negativizing operator. The process is characterized by focusing the pre verbal NP constituent alone, whereas the whole proposition is negated. The study can stimulate similar study or be replicated in other languages.

Keywords: negation, focus, Basà, nominalization

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Authors: Pham Duc Hieu, Do Thi Huong Lan

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The aim of this paper is to investigate the factors affecting the extent of voluntary disclosure by examining the annual reports of 205 industrial and manufacturing companies listing on Ho Chi Minh Stock Exchange (HSX) and Hanoi Stock Exchange (HNX) for the year end of 2012. Those factors include company size, profitability, leverage, state ownership, managerial ownership, and foreign ownership, board independence, role duality and type of external auditors. Evidence from this study suggests two main findings. (1) Companies with high foreign ownership have a high level of voluntary disclosure. (2) The company size is an important factor related to the increased level of voluntary disclosure in annual reports made by Vietnamese listed companies. The larger the company, the higher the information is disclosed. However, no significant associations are found between profitability, leverage, state ownership, managerial ownership, board independence, role duality and type of external auditors as hypothesized in this study.

Keywords: voluntary disclosure, Vietnamese listed companies, voluntary, duality

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Authors: Silvia Baralla, Raffaella Zucaro, Romina Lorenzetti

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Water management needs to cope with economic, societal, and environmental changes. This could be guaranteed through 'shifting from government to governance'. In the last decades, it was applied in Europe through and within important legislative pillars (Water Framework Directive and Common Agricultural Policy) and their measures focused on resilience and adaptation to climate change, with particular attention to the creation of synergies among policies and all the actors involved at different levels. Within the climate change context, the agricultural sector can play, through sustainable water management, a leading role for climate-resilient growth and environmental integrity. A recent analysis on the water management governance of different countries identified some common gaps dealing with administrative, policy, information, capacity building, funding, objective, and accountability. The ability of a country to fill these gaps is an essential requirement to make some of the changes requested by Europe, in particular the improvement of the agro-ecosystem resilience to the effect of climatic change, supporting green and digital transitions, and sustainable water use. This research aims to contribute in sharing examples of water governances and related advantages useful to fill the highlighted gaps. Italy has developed a strong and exhaustive model of water governance in order to react with strategic and synergic actions since it is one of the European countries most threatened by climate change and its extreme events (drought, floods). In particular, the Italian water governance model was able to overcome several gaps, specifically as concerns the water use in agriculture, adopting strategies as a systemic/integrated approach, the stakeholder engagement, capacity building, the improvement of planning and monitoring ability, and an adaptive/resilient strategy for funding activities. They were carried out, putting in place regulatory, structural, and management actions. Regulatory actions include both the institution of technical committees grouping together water decision-makers and the elaboration of operative manuals and guidelines by means of a participative and cross-cutting approach. Structural actions deal with the funding of interventions within European and national funds according to the principles of coherence and complementarity. Finally, management actions regard the introduction of operational tools to support decision-makers in order to improve planning and monitoring ability. In particular, two cross-functional and interoperable web databases were introduced: SIGRIAN (National Information System for Water Resources Management in Agriculture) and DANIA (National Database of Investments for Irrigation and the Environment). Their interconnection allows to support sustainable investments, taking into account the compliance about irrigation volumes quantified in SIGRIAN, ensuring a high level of attention on water saving, and monitoring the efficiency of funding. Main positive results from the Italian water governance model deal with a synergic and coordinated work at the national, regional, and local level among institutions, the transparency on water use in agriculture, a deeper understanding from the stakeholder side of the importance of their roles and of their own potential benefits and the capacity to guarantee continuity to this model, through a sensitization process and the combined use of management operational tools.

Keywords: agricultural sustainability, governance model, water management, water policies

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Authors: Mohammad Soliman, Mohamed A. Abou-Shouk

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Knowledge management focuses on the development, storage, retrieval, and dissemination of information and expertise. It has become an important tool to improve performance in tourism enterprises. This includes improving decision-making, developing customer services, and increasing sales and profits. Knowledge management adoption depends on human, organizational and technological factors. This study aims to explore the concept of knowledge management in travel agents in Egypt. It explores the requirements of adoption and its impact on performance in these agencies. The study targets Category A travel agents in Egypt. The population of the study encompasses Category A travel agents having online presence. An online questionnaire is used to collect data from managers of travel agents. This study is useful for travel agents who are in urgent need to restructure their intermediary role and support their survival in the global travel market. The study sheds light on the requirements of adoption and the expected impact on performance. This could help travel agents identify their situation and the determine the extent to which they are ready to adopt knowledge management. This study is contributing to knowledge by providing insights from the tourism sector in a developing country where the concept of knowledge management is still in its infancy stages.

Keywords: knowledge management, knowledge management adoption, performance, travel agents

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Authors: Monika Kulikowska-Pawlak, Katarzyna Bratnicka-Myśliwiec, Tomasz Ingram

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This study seeks to contribute to the literature on firm competitiveness by advancing the perspective of organizational politics that views this process as a driver which creates identifiable differences in firm performance. The hypothesized relationships were tested on the basis of data from 355 Polish medium and large-sized enterprises. Data were analyzed using correlation analysis, EFA and robustness tests. The main result of the conducted analyses proved the coexistence, previously examined in the literature, of corporate entrepreneurship and firm performance. The obtained research findings made it possible to add organizational politics to a wide range of elements determining corporate entrepreneurship, followed by competitive advantage, in addition to antecedents such as strategic leadership, corporate culture, opportunity-oriented resource-based management, etc. Also, the empirical results suggest that four dimensions of organizational politics (dominant coalition, influence exertion, making organizational changes, and information openness) are positively related to firm competitiveness. In addition, these findings seem to underline a supposition that corporate entrepreneurship is an important mediator which strengthens the competitive effects of organizational politics.

Keywords: corporate entrepreneurship, firm competitiveness, organizational politics, sensemaking

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Authors: Leanne Sanders, Leonie Hallo, Tiep Nguyen, Nicholas Chileshe.

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Purpose – Small and Medium-Sized Enterprises (SMEs) play an important role globally, yet the investigation of sustainability in this context is limited. The leader’s relationships with employees are a critical aspect of creating a positive and supportive organizational culture. Therefore, to bridge the knowledge gap, the aim of this paper is to extend the notion that the creation of trust is central to the sustainability of SMEs. Design: The study employs a case study observational research (CSOR) approach, and data were collected using first-hand observations and interviews. Findings: A model of leadership behaviour and a series of steps that leaders can take to leverage trust are presented. Leaders can have a positive impact even if the team is operating in a challenging context. Creating a positive environment brings sustainability to the team and perhaps the wider organization as well. Originality: This paper provides detailed information about the context in which developing trust can produce positive outcomes despite the prevailing overall toxic culture of an organization. The paper provides concrete advice for leaders to assist them in this highly important task.

Keywords: leadership, organizational culture, organizational sustainability, trust, positive culture

Procedia PDF Downloads 15