Search results for: intrinsic information

Authors: George Mariano Soriano

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In this study, a Rapid Earthquake Risk Ranking Criteria was formulated by integrating various existing maps and databases by the Department of Public Works and Highways (DPWH) and Philippine Institute of Volcanology and Seismology (PHIVOLCS). Utilizing Geographic Information System (GIS) software, the above-mentioned maps and databases were used in extracting seismic hazard parameters and bridge vulnerability characteristics in order to rank the seismic damage risk rating of bridges in the National Capital Region.

Keywords: bridge, earthquake, GIS, hazard, risk, vulnerability

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Authors: Weiqi Xia

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We assess the perceptions of China’s hotel m-bookers using the E-SERVQUAL model and technology affordance assessment metrics. The data analysis provides insight into Chinese hotel m-bookers’ perceptions of information quality items, system quality items, and functional quality items. Respondents’ perceived value of such items is greatly enhanced via mini-program support and self-service innovation, which are predicted to be of increasing importance in the future. The findings of this study help close the gap between hotel operators’ understanding and customers’ perceptions. Our findings may also provide valuable insights into the functioning of China’s hotel industry.

Keywords: mobile hotel booking, hotel m-bookers, user perception, China’s WeChat mini program, hotel booking apps.

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Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

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This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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Authors: Lukas Reznak, Maria Reznakova

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Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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Authors: Karim Akkouche, Amine Nekmouche, Leyla Bouzid

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This study focuses on the development of a multifunctional Expert System (ES) called post-seismic damage inspection tool (PSDIT), a powerful tool which allows the evaluation, the processing, and the archiving of the collected data stock after earthquakes. PSDIT can be operated by two user types; an ordinary user (ingineer, expert, or architect) for the damage visual inspection and an administrative user for updating the knowledge and / or for adding or removing the ordinary user. The knowledge acquisition is driven by a hierarchical knowledge model, the Information from investigation reports and those acquired through feedback from expert / engineer questionnaires are part.

Keywords: .disaster, damaged structures, damage assessment, expert system

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Authors: Pin Yu Chen, Puay Chuan Lee, Yu Jen Loo, Ju Xia Zhang, Deborah Teo, Jack Wei Chieh Tan, Biauw Chi Ong

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Background: Synchronous communication, such as telephone calls, remains the standard communication method between nurses and other healthcare professionals in Singapore public hospitals despite advances in asynchronous technological platforms, such as instant messaging. Although miscommunication is one of the most common causes of lapses in patient care, there is a scarcity of research characterizing baseline inter-professional healthcare communications in a hospital setting due to logistic difficulties. Objective: This study aims to characterize the frequency and patterns of communication behaviours among healthcare professionals. Methods: The one-week observational study was conducted on Monday through Sunday at the nursing station of a cardiovascular medicine and cardiothoracic surgery inpatient ward at the National Heart Centre Singapore. Subjects were shadowed by two physicians for sixteen hours or consecutive morning and afternoon nursing shifts. Communications were logged and characterized by type, duration, caller, and recipient. Results: A total of 1,023 communication events involving the attempted use of the common telephones at the nursing station were logged over a period of one week, corresponding to a frequency of one event every 5.45 minutes (SD 6.98, range 0-56 minutes). Nurses initiated the highest proportion of outbound calls (38.7%) via the nursing station common phone. A total of 179 face-to-face communications (17.5%), 362 inbound calls (35.39%), 481 outbound calls (47.02%), and 1 emergency alert (0.10%) were captured. Average response time for task-oriented communications was 159 minutes (SD 387.6, range 86-231). Approximately 1 in 3 communications captured aimed to clarify patient-related information. The total duration of time spent on synchronous communication events over one week, calculated from total inbound and outbound calls, was estimated to be a total of 7 hours. Conclusion: The results of our study showed that there is a significant amount of time spent on inter-professional healthcare communications via synchronous channels. Integration of patient-related information and use of asynchronous communication channels may help to reduce the redundancy of communications and clarifications. Future studies should explore the use of asynchronous mobile platforms to address the inefficiencies observed in healthcare communications.

Keywords: healthcare communication, healthcare management, nursing, qualitative observational study

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Authors: Michael Heuer, Ayoub Al-Hamadi, Alexander Rain, Marc-Michael Meinecke

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Vulnerable road users, e.g. pedestrians, have a high impact on fatal accident numbers. To reduce these statistics, car manufactures are intensively developing suitable safety systems. Hereby, fast and reliable environment recognition is a major challenge. In this paper we describe a tracking approach that is only based on a 24 GHz radar sensor. While common radar signal processing loses much information, we make use of a track-before-detect filter to incorporate raw measurements. It is explained how the Range-Doppler spectrum can help to indicated pedestrians and stabilize tracking even in occultation scenarios compared to sensors in series.

Keywords: radar, pedestrian detection, active safety, sensor

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Authors: Ezgi Şendil

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Information extracted from social media has received great attention since it has become an effective alternative for collecting people’s opinions and emotions based on specific experiences in a faster and easier way. The paper aims to put data in a meaningful way to analyze users’ posts and get a result in terms of the experiences and opinions of the users during and after natural disasters. The posts collected from Reddit are classified into nine different categories, including injured/dead people, infrastructure and utility damage, missing/found people, donation needs/offers, caution/advice, and emotional support, identified by using labelled Twitter data and four different machine learning (ML) classifiers.

Keywords: disaster, NLP, postdisaster management, sentiment analysis

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Authors: L. Agneni, F. Carta, C. Micheletta, V. Tersigni

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The development of a qualitative method to profile jobseekers is needed to improve the quality of the Public Employment Services (PES) in Italy. This is why the National Agency for Active Labour Market Policies (ANPAL) decided to introduce a Qualitative Profiling Service in the context of the activities carried out by local employment offices’ operators. The qualitative profiling service provides information and data regarding the jobseeker’s personal transition status, through a semi-structured questionnaire administered to PES clients during the guidance interview. The questionnaire responses allow PES staff to identify, for each client, proper activities and policy measures to support jobseekers in their reintegration into the labour market. Data and information gathered by the qualitative profiling tool are the following: frequency, modalities and motivations for clients to apply to local employment offices; clients’ expectations and skills; difficulties that they have faced during the previous working experiences; strategies, actions undertaken and activated channels for job search. These data are used to assess jobseekers’ personal and career characteristics and to measure their employability level (qualitative profiling index), in order to develop and deliver tailor-made action programmes for each client. This paper illustrates the use of the above-mentioned qualitative profiling service on the national territory and provides an overview of the main findings of the survey: concerning the difficulties that unemployed people face in finding a job and their perception of different aspects related to the transition in the labour market. The survey involved over 10.000 jobseekers registered with the PES. Most of them are beneficiaries of the “citizens' income”, a specific active labour policy and social inclusion measure. Furthermore, data analysis allows classifying jobseekers into a specific group of clients with similar features and behaviours, on the basis of socio-demographic variables, customers' expectations, needs and required skills for the profession for which they seek employment. Finally, the survey collects PES staff opinions and comments concerning clients’ difficulties in finding a new job and also their strengths. This is a starting point for PESs’ operators to define adequate strategies to facilitate jobseekers’ access or reintegration into the labour market.

Keywords: labour market transition, public employment services, qualitative profiling, vocational guidance

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Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

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Authors: Tulasi Rayasa, Phani Kumar Pullela

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

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

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Authors: Temidayo James Aransiola, Vania Ceccato, Marcelo Justus

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

Keywords: deprivation, inequality, interaction, unemployment, violence

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Authors: Radul Shishkov, Orlin Davchev

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The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

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Authors: Mustafa Metin Donma

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Circumference measurements are important because they are easily obtained values for the identification of the weight gain without determining body fat. They may give meaningful information about the varying stages of obesity. Besides, some formulas may be derived from a number of body circumference measurements to estimate body fat. Waist (WC), hip (HC) and neck (NC) circumferences are currently the most frequently used measurements. The aim of this study was to develop a formula derived from these three anthropometric measurements, each giving a valuable information independently, to question whether their combined power within a formula was capable of being helpful for the differential diagnosis of morbid obesity without metabolic syndrome (MetS) from MetS. One hundred and eighty seven children were recruited from the pediatrics outpatient clinic of Tekirdag Namik Kemal University Faculty of Medicine. The parents of the participants were informed about asked to fill and sign the consent forms. The study was carried out according to the Helsinki Declaration. The study protocol was approved by the institutional non-interventional ethics committee. The study population was divided into four groups as normal-body mass index (N-BMI), obese (OB), morbid obese (MO) and MetS, which were composed of 35, 44, 75 and 33 children, respectively. Age- and gender-adjusted BMI percentile values were used for the classification of groups. The children in MetS group were selected based upon the nature of the MetS components described as MetS criteria. Anthropometric measurements, laboratory analysis and statistical evaluation confined to study population were performed. Body mass index values were calculated. A circumference index, advanced Donma circumference index (ADCI) was introduced as WC*HC/NC. The statistical significance degree was chosen as p value smaller than 0.05. Body mass index values were 17.7±2.8, 24.5±3.3, 28.8±5.7, 31.4±8.0 kg/m2, for N-BMI, OB, MO, MetS groups, respectively. The corresponding values for ADCI were 165±35, 240±42, 270±55, and 298±62. Significant differences were obtained between BMI values of N-BMI and OB, MO, MetS groups (p=0.001). Obese group BMI values also differed from MO group BMI values (p=0.001). However, the increase in MetS group compared to MO group was not significant (p=0.091). For the new index, significant differences were obtained between N-BMI and OB, MO, MetS groups (p=0.001). Obese group ADCI values also differed from MO group ADCI values (p=0.015). A significant difference between MO and MetS groups was detected (p=0.043). The correlation coefficient value and the significance check of the correlation was found between BMI and ADCI as r=0.0883 and p=0.001 upon consideration of all participants. In conclusion, in spite of the strong correlation between BMI and ADCI values obtained when all groups were considered, ADCI, but not BMI, was the index, which was capable of differentiating cases with morbid obesity from cases with morbid obesity and MetS.

Keywords: anthropometry, body mass index, child, circumference, metabolic syndrome, obesity

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Authors: Boris M. Fedorov, Liudmila P. Goncharenko, Sergey A. Sybachin, Natalia A. Mamedova, Ekaterina V. Makarenkova, Saule Rakhimova

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In modern economic conditions, the question of the possibility of correct recognition of a signature on digital documents in order to verify the expression of will or confirm a certain operation is relevant. The additional complexity of processing lies in the dynamic variability of the signature for each individual, as well as in the way information is processed because the signature refers to biometric data. The article discusses the issues of using artificial intelligence models in order to improve the quality of signature confirmation in document recognition. The analysis of several possible options for using the model is carried out. The results of the study are given, in which it is possible to correctly determine the authenticity of the signature on small samples.

Keywords: signature recognition, biometric data, artificial intelligence, neural networks

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Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

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Authors: Tony Ikponmwosa Obaseki

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The paper studied Colleges of education environments with specific insight at available technologies in college libraries with the objective of ascertaining the services rendered and the impact of information services on teacher trainings in the overall development and benefit of the educational ecosystem. Problems were situated and assumptions formulated made to guide the study proper. Twelve (12) Colleges of education environment from the six geopolitical zones in Nigeria were comparatively studied, using twelve (12) librarians and six hundred (600) randomly selected training teachers. Analysis and presentation of findings will be done using well stated scientific procedures.

Keywords: library, technologies, digital library, colleges of education, teacher training, education ecosystem

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Authors: M. Abdullah, Al-Wadud

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Sensor-based activity recognition systems usually accounts which sensors have been activated to perform an activity. The system then combines the conditional probabilities of those sensors to represent different activities and takes the decision based on that. However, the information about the sensors which are not activated may also be of great help in deciding which activity has been performed. This paper proposes an approach where the sensory data related to both usage and non-usage of objects are utilized to make the classification of activities. Experimental results also show the promising performance of the proposed method.

Keywords: Naïve Bayesian, based classification, activity recognition, sensor data, object-usage model

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Authors: Ivana Scidà, Francesco Alotto, Anna Osello

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Due to the importance given today to innovation, the education sector is evolving thanks digital technologies. Virtual Reality (VR) can be a potential teaching tool offering many advantages in the field of training and education, as it allows to acquire theoretical knowledge and practical skills using an immersive experience in less time than the traditional educational process. These assumptions allow to lay the foundations for a new educational environment, involving and stimulating for students. Starting from the objective of strengthening the innovative teaching offer and the learning processes, the case study of the research concerns the digitalization of MastrLAB, High Quality Laboratory (HQL) belonging to the Department of Structural, Building and Geotechnical Engineering (DISEG) of the Polytechnic of Turin, a center specialized in experimental mechanical tests on traditional and innovative building materials and on the structures made with them. The MastrLAB-VR has been developed, a revolutionary innovative training tool designed with the aim of educating the class in total safety on the techniques of use of machinery, thus reducing the dangers arising from the performance of potentially dangerous activities. The virtual laboratory, dedicated to the students of the Building and Civil Engineering Courses of the Polytechnic of Turin, has been projected to simulate in an absolutely realistic way the experimental approach to the structural tests foreseen in their courses of study: from the tensile tests to the relaxation tests, from the steel qualification tests to the resilience tests on elements at environmental conditions or at characterizing temperatures. The research work proposes a methodology for the virtualization of technical laboratories through the application of Building Information Modelling (BIM), starting from the creation of a digital model. The process includes the creation of an independent application, which with Oculus Rift technology will allow the user to explore the environment and interact with objects through the use of joypads. The application has been tested in prototype way on volunteers, obtaining results related to the acquisition of the educational notions exposed in the experience through a virtual quiz with multiple answers, achieving an overall evaluation report. The results have shown that MastrLAB-VR is suitable for both beginners and experts and will be adopted experimentally for other laboratories of the University departments.

Keywords: building information modelling, digital learning, education, virtual laboratory, virtual reality

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Authors: Alireza Akbari, Gelareh Babaee Khou

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Ground Penetrating Radar (GPR) is an important nondestructive remote sensing tool that has been used in both military and civilian fields. Recently, GPR imaging has attracted lots of attention in detection of subsurface shallow small targets such as landmines and unexploded ordnance and also imaging behind the wall for security applications. For the monostatic arrangement in the space-time GPR image, a single point target appears as a hyperbolic curve because of the different trip times of the EM wave when the radar moves along a synthetic aperture and collects reflectivity of the subsurface targets. With this hyperbolic curve, the resolution along the synthetic aperture direction shows undesired low resolution features owing to the tails of hyperbola. However, highly accurate information about the size, electromagnetic (EM) reflectivity, and depth of the buried objects is essential in most GPR applications. Therefore hyperbolic curve behavior in the space-time GPR image is often willing to be transformed to a focused pattern showing the object's true location and size together with its EM scattering. The common goal in a typical GPR image is to display the information of the spatial location and the reflectivity of an underground object. Therefore, the main challenge of GPR imaging technique is to devise an image reconstruction algorithm that provides high resolution and good suppression of strong artifacts and noise. In this paper, at first, the standard back-projection (BP) algorithm that was adapted to GPR imaging applications used for the image reconstruction. The standard BP algorithm was limited with against strong noise and a lot of artifacts, which have adverse effects on the following work like detection targets. Thus, an improved BP is based on cross-correlation between the receiving signals proposed for decreasing noises and suppression artifacts. To improve the quality of the results of proposed BP imaging algorithm, a weight factor was designed for each point in region imaging. Compared to a standard BP algorithm scheme, the improved algorithm produces images of higher quality and resolution. This proposed improved BP algorithm was applied on the simulation and the real GPR data and the results showed that the proposed improved BP imaging algorithm has a superior suppression artifacts and produces images with high quality and resolution. In order to quantitatively describe the imaging results on the effect of artifact suppression, focusing parameter was evaluated.

Keywords: algorithm, back-projection, GPR, remote sensing

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Authors: Siriporn Meenanan

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The objective of this study is to study about the uses and gratification of the sample who use the website that named secret-thai.com which provides moral contents, inspires, and builds up the spirit. The study found that the samples mainly use this website to follow up on the dharma activities. They also use the space as the web board to discuss about dharma issues. Moreover, the contents help readers to relax and also provides the guidelines to deal with stress and uncomfortable situations properly. The samples found to be most satisfied. In other words, the samples found the contents of the website are complete, and can cover their needs. Moreover, they found that contents useful in their ways of living. In addition, they are satisfied with the beautiful and interesting design of the website and well classification of the contents that readers can easily find the information that they want.

Keywords: uses and gratification, website, Secret-Thai.com, moral contents

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Authors: Raif Parlakkaya, Huseyin Cetin, Halil Akmese, Mesut Murat Adabali

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As the economies of other countries in the Mediterranean Basin, the tourism sector in our country has a high denominator in economics. Tourism businesses, which are building blocks of tourism, sector faces with a variety of problems during their activities. These problems faced make business efficiency and competition conditions of the businesses difficult. Most of the problems faced by the tourism businesses and the information of consumers about consumers’ rights were used in this study, which is conducted to determine the problems of tourism businesses in the Central Anatolia Region. It is aimed to contribute the awareness of staff and executives working at tourism sector and to attract attention of businesses active concurrently with tourism sector and legislators.

Keywords: financial problems, the problems of tourism businesses, tourism businesses, tourism sector in Turkey

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Authors: Ahmed M. Jamel

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Electronic government initiatives and public participation to them are among the indicators of today's development criteria of the countries. After consequent two wars, Iraq's current position in, for example, UN's e-government ranking is quite concerning and did not improve in recent years, either. In the preparation of this work, we are motivated with the fact that handling geographic data of the public facilities and resources are needed in most of the e-government projects. Geographical information systems (GIS) provide most common tools not only to manage spatial data but also to integrate such type of data with nonspatial attributes of the features. With this background, this paper proposes that establishing a working GIS in the health sector of Iraq would improve e-government applications. As the case study, investigating hospital locations in Erbil is chosen.

Keywords: e-government, GIS, Iraq, Erbil

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Authors: Ebtesam Shadadi, Rasha Ibrahim, Essam Ghadafi

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Phishing poses a significant threat as a cybercrime by tricking end users into revealing their confidential and sensitive information. Attackers often manipulate victims to achieve their malicious goals. The increasing prevalence of Phishing has led to extensive research on this issue, including studies focusing on phishing attempts in healthcare institutions in the Kingdom of Saudi Arabia. This paper explores the importance of analyzing phishing attacks, specifically focusing on those targeting the healthcare industry. The study delves into the tactics, obstacles, and remedies associated with these attacks, all while considering the implications for Saudi Vision 2030.

Keywords: phishing, cybersecurity, cyber threat, social engineering, vision 2030

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Authors: Roger M. Wall, David G. Proverbs, Yamina Silva, Danny Scipion

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This paper critically reviews the outcomes of a 4 day workshop focused on building resilience to El Niño related Flood Events in northern Perú. The workshop was run jointly by Birmingham City University (BCU) in partnership with Instituto Geofísico del Perú (IGP) and was hosted by the Universidad de Piura (UDEP). The event took place in August 2018 and was funded by the Newton-Paulet fund administered by the British Council. The workshop was a response to the severe flooding experienced in Piura during the El Niño event of March 2017 which damaged over 100,000 homes and destroyed much local infrastructure including around 100 bridges. El Niño is a recurrent event and there is concern that its frequency and intensity may change in the future as a consequence of climate change. A group of 40 early career researchers and practitioners from the UK and Perú were challenged with working together across disciplines to identify key cross-cutting themes and make recommendations for building resilience to similar future events. Key themes identified on day 1 of the workshop were governance; communities; risk information; river management; urban planning; health; and infrastructure. A field study visit took place on day 2 so that attendees could gain first-hand experience of affected and displaced communities. Each of the themes was then investigated in depth on day 3 by small interdisciplinary teams drawing on their own expertise, local knowledge and the experiences of the previous day’s field trip. Teams were responsible for developing frameworks for analysis of their chosen theme and presenting their findings to the whole group. At this point, teams worked together to develop links between the different themes so that an integrated approach could be developed and presented on day 4. This paper describes the approaches taken by each team and the way in which these were integrated to form an holistic picture of the whole system. The findings highlighted the importance of risk-related information and the need for strong governance structures to enforce planning regulations and development. The structured facilitation approach proved to be very effective and it is recommended that the process be repeated with a broader group of stakeholders from across the region.

Keywords: El Niño, integrated flood risk management, Perú, structured facilitation, systems approach, resilience

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Authors: S. Yesmin, N. F.Rahman, R. Akther, T. Begum, T. Tahmid, T. Chowdury, S. Afrin, J. D. Hamadani

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Abstract: Maternal depression is one of the risk factors of developmental delay in young children in low-income countries. Maternal depressions during pregnancy are rarely reported in Bangladesh. Objectives: The purpose of the present study was to examine the efficacy of a community based psychosocial intervention on women with mild to moderate depressive illness during the perinatal period and on their children from birth to 12 months on mothers’ mental status and their infants’ growth and development. Methodology: The study followed a prospective longitudinal approach with a randomized controlled design. Total 250 pregnant women aged between 15 and 40 years were enrolled in their third trimester of pregnancy of which 125 women were in the intervention group and 125 in the control group. Women in the intervention group received the “Thinking Healthy (CBT based) program” at their home setting, from their last month of pregnancy till 10 months after delivery. Their children received psychosocial stimulation from birth till 12 months. The following instruments were applied to get the outcome information- Bangla version of Edinburgh Postnatal Depression Scale (BEPDS), Prenatal Attachment Inventory (PAI), Maternal Attachment Inventory (MAI), Bayley Scale of Infant Development-Third version (Bayley–III) and Family Care Indicator (FCI). In addition, sever morbidity; breastfeeding, immunization, socio-economic and demographic information were collected. Data were collected at three time points viz. baseline, midline (6 months after delivery) and endline (12 months after delivery). Results: There was no significant difference between any of the socioeconomic and demographic variables at baseline. A very preliminary analysis of the data shows an intervention effect on Socioemotional behaviour of children at endline (p<0.001), motor development at midline (p=0.016) and at endline (p=0.065), language development at midline (p=0.004) and at endline (p=0.023), cognitive development at midline (p=0.008) and at endline (p=0.002), and quality of psychosocial stimulation at midline (p=0.023) and at endline (p=0.010). EPDS at baseline was not different between the groups (p=0.419), but there was a significant improvement at midline (p=0.027) and at endline (p=0.024) between the groups following the intervention. Conclusion: Psychosocial intervention is found effective in reducing women’s low and moderate depressive illness to cope with mental health problem and improving development of young children in Bangladesh.

Keywords: mental health, maternal depression, infant development, CBT, EPDS

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Authors: Amjad F. Alharbi, Bashayer A. Alotaibi, Fahd S. Alotaibi

Abstract:

The emergence of Internet of Things (IoT) technology provides capabilities for a huge number of smart devices, services and people to be communicate with each other for exchanging data and information over existing network. While as IoT is progressing, it provides many opportunities for new ways of communications as well it introduces many security and privacy threats and challenges which need to be considered for the future of IoT development. In this survey paper, an IoT security issues as threats and current challenges are summarized. The security architecture for IoT are presented from four main layers. Based on these layers, the IoT security requirements are presented to insure security in the whole system. Furthermore, some researches initiatives related to IoT security are discussed as well as the future direction for IoT security are highlighted.

Keywords: Internet of Things (IoT), IoT security challenges, IoT security requirements, IoT security architecture

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Authors: Tabrej Khan

Abstract:

Neuromarketing can refer to the commercial application of neuroscience technologies and insights to drive business further. On the other side, consumer neuroscience can be seen as the academic use of neuroscience to better understand marketing effects on consumer behavior. Consumer Neuroscience and Neuromarketing is a multidisciplinary effort between economics, psychology, and neuroscience and information technology. Traditional methods are using survey, interviews, focus group people are overtly and consciously reporting on their experience and thoughts. The unconscious side of customer behavior is largely unmeasured in the traditional methods. Neuroscience has a potential to understand the unconscious part. Through this paper, we are going to present specific results of selected tools and methods that are used to understand consumer behaviors.

Keywords: neuromarketing, neuroscience, consumer behaviors, tools

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Authors: Ananya G., B. Varshitha, Shwetha S., Kavitha S. N., Praveen Kumar Gupta

Abstract:

Teleportation is the ability to travel by just reappearing at some other spot. Though teleportation has never been achieved, quantum teleportation is possible. Quantum teleportation is a process of transferring the quantum state of a particle onto another particle, under the circumstance that one does not get to know any information about the state in the process of transformation. This paper presents a brief overview of quantum teleportation, discussing the topics like Entanglement, EPR Paradox, Bell's Theorem, Qubits, elements for a successful teleport, some examples of advanced teleportation systems (also covers few ongoing experiments), applications (that includes quantum cryptography), and the current hurdles for future scientists interested in this field. Finally, major advantages and limitations to the existing teleportation theory are discussed.

Keywords: teleportation, quantum teleportation, quantum entanglement, qubits, EPR paradox, bell states, quantum particles, spooky action at a distance

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Authors: Yolanda Ramírez, Ángel Tejada, Agustín Baidez

Abstract:

The purpose of this paper is to examine the quality of voluntary intellectual capital disclosure by public Spanish universities on their websites. To this end, a content analysis was used to analyze the websites of 50 public Spanish universities i 2016. The results of this study show that human capital was the most disclosed category with relational capital being the least frequently disclosed in Spain. However, the quality of structural capital disclosures was higher than relational and human capital. Finally, most IC disclosures were narrative in nature.

Keywords: intellectual capital, quality disclosure, websites, universities, Spain

Procedia PDF Downloads 208