Search results for: database annotation

Authors: Lim Yi Wei

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Structural equation modelling (SEM) is well-known in statistics due to its flexibility and accessibility. It plays an increasingly important role in the development of the education field. The number of research publications using SEM in education has increased in recent decades. However, there is a lack of scientific review conducted on SEM in education. The purpose of this study is to investigate research trends related to SEM in education. The researcher will use Vosviewer, Datawrapper, and SciMAT to do bibliometric analysis on 5549 papers that have been published in the Scopus database in the last five years. The result will show the publication trends of the most cited documents, the top contributing authors, countries, institutions, and journals in the research field. It will also look at how they relate to each other in terms of co-citation, collaboration, and co-occurrence of keywords. This study will benefit researchers and practitioners by identifying research trends and the current state of SEM in education.

Keywords: structural equation modeling, education, bibliometric analysis, Vosviewer

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Authors: Ahmed Emad Ahmed

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This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.

Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS

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Authors: Pappas Theodoros, Mihail Diakomihalis

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Measuring the economic impact of tourism in a benchmark economy is a global concern, with previous measurements being partial and not fully integrated. Tourism is a phenomenon that requires individual consumption of visitors and which should be observed and measured to reveal, thus, the overall contribution of tourism to an economy. The Tourism Satellite Account (TSA) is a critical tool for assessing the annual growth of tourism, providing reliable measurements. This article introduces a system of TSA information that encompasses all the works of the TSA, including input, storage, management, and analysis of data, as well as additional future functions and enhances the efficiency of tourism data management and TSA collection utility. The methodology and results presented offer insights into the development and implementation of TSA.

Keywords: tourism satellite account, information system, data-based tourist account, relation database

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Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

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In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

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Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

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Authors: C. Schneider, M. M. Seizmeir, T. Suchanek, M. Hutter-Mironovova, M. Bdiwi, M. Putz

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In this paper, a suitable measurement setup is presented to conduct force and pressure measurements for transient contact cases at the example of lathe machine tending. Empirical measurements were executed on a selected collaborative robot’s behavior regarding allowable operating speeds under consideration of sensor- and workpiece-specific factors. Comparisons between the theoretic calculations proposed in ISO/TS 15066 and the practical measurement results reveal a basis for future research. With the created database, preliminary risk assessment and economic assessment procedures of collaborative machine tending cells can be facilitated.

Keywords: biomechanical thresholds, collaborative robots, force and pressure measurements, machine tending, transient contact

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Authors: Muhammad Zia Ullah Baig, Atiq Uz Zama

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The motivation of the project is to facilitate the governance body, as well as the common man in his/her daily life consuming product rates, to easily monitor the expense, to control the budget with the help of single SMS (message), e-mail facility, and to manage governance body by task management system. The system will also be capable of finding irregularities being done by the concerned department in mitigating the complaints generated by the customer and also provide a solution to overcome problems. We are building a system that easily controls the price control system of any country, we will feeling proud to give this system free of cost to Indian Government also. The system is able to easily manage and control the price control department of government all over the country. Price control department run in different cities under City District Government, so the system easily run in different cities with different SMS Code and decentralize Database ensure the non-functional requirement of system (scalability, reliability, availability, security, safety). The customer request for the government official price list with respect to his/her city SMS code (price list of all city available on website or application), the server will forward the price list through a SMS, if the product is not available according to the price list the customer generate a complaint through an SMS or using website/smartphone application, complaint is registered in complaint database and forward to inspection department when the complaint is entertained, the inspection department will forward a message about the complaint to customer. Inspection department physically checks the seller who does not follow the price list, but the major issue of the system is corruption, may be inspection officer will take a bribe and resolve the complaint (complaint is fake) in that case the customer will not use the system. The major issue of the system is to distinguish the fake and real complain and fight for corruption in the department. To counter the corruption, our strategy is to rank the complain if the same type of complaint is generated the complaint is in high rank and the higher authority will also notify about that complain, now the higher authority of department have reviewed the complaint and its history, the officer who resolve that complaint in past and the action against the complaint, these data will help in decision-making process, if the complaint was resolved because the officer takes bribe, the higher authority will take action against that officer. When the price of any good is decided the market/former representative is also there, with the mutual understanding of both party the price is decided, the system facilitate the decision-making process. The system shows the price history of any goods, inflation rate, available supply, demand, and the gap between supply and demand, these data will help to allot for the decision-making process.

Keywords: price control, goods, government, inspection, department, customer, employees

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this study is to evaluate the advantages and disadvantages of various machine learning techniques in forecasting ground-motion intensity measures given source characteristics, source-to-site distance, and local site condition. Intensity measures such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Estimating these variables for future earthquake events is a key step in seismic hazard assessment and potentially subsequent risk assessment of different types of structures. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as a statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The algorithms are adjusted to quantify event-to-event and site-to-site variability of the ground motions by implementing them as random effects in the proposed models to reduce the aleatory uncertainty. All the algorithms are trained using a selected database of 4,528 ground-motions, including 376 seismic events with magnitude 3 to 5.8, recorded over the hypocentral distance range of 4 to 500 km in Oklahoma, Kansas, and Texas since 2005. The main reason of the considered database stems from the recent increase in the seismicity rate of these states attributed to petroleum production and wastewater disposal activities, which necessities further investigation in the ground motion models developed for these states. Accuracy of the models in predicting intensity measures, generalization capability of the models for future data, as well as usability of the models are discussed in the evaluation process. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available.

Keywords: artificial neural network, ground-motion models, machine learning, random forest, support vector machine

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Authors: Kunal Tongaria, Abhishek Mangal, S. Mandal, Devendra Mohan

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The carbonation of concrete is a phenomenon which is a function of various interdependent parameters. Therefore, in spite of numerous literature and database, the useful generalization is not an easy task. These interdependent parameters can be grouped under the category of internal and external factors. This paper focuses on the internal parameters which govern and increase the probability of the ingress of deleterious substances into concrete. The mechanism of effects of internal parameters such as microstructure for with and without supplementary cementing materials (SCM), water/binder ratio, the age of concrete etc. has been discussed. This is followed by the comparison of various proposed mathematical models for the deterioration of concrete. Based on existing laboratory experiments as well as field results, this paper concludes the present understanding of mechanism, modeling and future research needs in this field.

Keywords: carbonation, diffusion coefficient, microstructure of concrete, reinforced concrete

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Authors: Jing (Claire) LI

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The topic of corporate social responsibility (CSR) is significant for pharmaceutical companies in China at this current stage. This is because, as a rapid growth industry in China in recent years, the pharmaceutical industry in China has been undergone continuous and terrible incidents relating to CSR. However, there is limited research and practice of CSR in Chinese pharmaceutical companies. Also, there is an urgent call for more research in an international context to understand the implications of corporate life cycle on CSR performance. To respond to the research need and research call, this study examines the relationship between corporate life cycle and CSR performance of Chinese listed companies in pharmaceutical industry. This research studies Chinese listed companies in pharmaceutical industry for the period of 2010-2017, where the data is available in database. Following the literature, this study divides CSR performance with regards to CSR dimensions, including shareholders, creditors, employees, customers, suppliers, the government, and the society. This study uses CSR scores of HEXUN database and financial measures of these CSR dimensions to measure the CSR performance. This study performed regression analysis to examine the relationship between corporate life cycle stages and CSR performance with regards to CSR dimensions for pharmaceutical listed companies in China. Using cash flow pattern as proxy of corporate life cycle to classify corporate life cycle stages, this study found that most (least) pharmaceutical companies in China are in maturity (decline) stage. This study found that CSR performance for most dimensions are highest (lowest) in maturity (decline) stage as well. Among these CSR dimensions, performing responsibilities for shareholder is the most important among all CSR responsibilities for pharmaceutical companies. This study is the first to provide important empirical evidence from Chinese pharmaceutical industry on the association between life cycle and CSR performance, supporting that corporate life cycle is a key factor in CSR performance. The study expands corporate life cycle and CSR literatures and has both empirical and theoretical contributions to the literature. From perspective of empirical contributions, the findings contribute to the argument that whether there is a relationship between CSR performance and various corporate life cycle stages in the literature. This study also provides empirical evidence that companies in different corporate life cycles have difference in CSR performance. From perspective of theoretical contributions, this study relates CSR and stakeholders to corporate life cycle stages and complements the corporate life cycle and CSR literature. This study has important implications for managers and policy makers. First, the results will be helpful for managers to have an understanding in the essence of CSR, and their company’s current and future CSR focus over corporate life cycle. This study provides a reference for their actions and may help them make more wise resources allocation decisions of CSR investment. Second, policy makers (in the government, stock exchanges, and securities commission) may consider corporate life cycle as an important factor in formulating future regulations for companies. Future research can explore the "process-based" differences in CSR performance and more industries.

Keywords: China, corporate life cycle, corporate social responsibility, pharmaceutical industry

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Authors: Mamatha M. N.

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Traffic problems, congested traffic, and flow management were recognized as major problems mostly in all the areas, which have caused a problem for the ambulance which carries the emergency patient. The proposed paper aims in the development of ambulance which reaches the nearby hospital faster even in heavy traffic scenario. This process is activated by implementing hardware in an ambulance as well as in traffic post thus allowing a smooth flow to the ambulance to reach the hospital in time. 1) The design of the vehicle to have a communication between ambulance and traffic post. 2)Electronic Health Record with Data-acquisition system 3)Telemetry of acquired biological parameters to the nearest hospital. Thus interfacing all these three different modules and integrating them on the ambulance could reach the hospital earlier than the present ambulance. The system is accurate and efficient of 99.8%.

Keywords: bio-telemetry, data acquisition, patient database, automatic traffic control

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Authors: Milad Abolfazli, Milad Bazli

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In this critical review, the topic of how composites maintain their tensile strength when exposed to elevated temperatures will be studied. A comprehensive database of 761 tests have been analyzed and closely examined to study the various factors that affect the strength retention. Conclusions are drawn from the collective research efforts of numerous scholars who have investigated this subject. Through the analysis of these tests, the relationships between the tensile strength retention and various effective factors are investigated. This review is meant to be a practical resource for researchers and engineers. It provides valuable information that can guide the development of composites tailored for high-temperature applications. By offering a deeper understanding of how composites behave in extreme heat, the paper contributes to the advancement of materials science and engineering.

Keywords: tesnile tests, high temperatures, FRP composites, mechanical perfomance

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Authors: J. Zhang, K. Agyapong-Kodua

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Digital factory based on visual design and simulation has emerged as a mainstream to reduce digital development life cycle. Some basic industrial systems are being integrated via semantic modelling, and products (P) matching process (P)-resource (R) requirements are designed to fulfill current customer demands. Nevertheless, product design is still limited to fixed product models and known knowledge of product engineers. Therefore, this paper presents a rapid reconfiguration method based on semantic technologies with PPR ontologies to reuse known and unknown knowledge. In order to avoid the influence of big data, our system uses a cloud manufactory and distributed database to improve the efficiency of querying meeting PPR requirements.

Keywords: semantic technologies, factory system, digital factory, cloud manufactory

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Authors: Parthiban Srinivasan

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PubMed provides online access to the National Library of Medicine database (MEDLINE) and other publications, which contain close to 25 million scientific citations from 1865 to the present. There are close to 80 million author name instances in those close to 25 million citations. For any work of literature, a fundamental issue is to identify the individual(s) who wrote it, and conversely, to identify all of the works that belong to a given individual. Due to the lack of universal standards for name information, there are two aspects of name ambiguity: name synonymy (a single author with multiple name representations), and name homonymy (multiple authors sharing the same name representation). In this talk, we present some results from our extensive work in author name disambiguation for PubMed citations. Information will be presented on the effectiveness and shortcomings of different aspects of successful name disambiguation such as parsing, validation, standardization and normalization.

Keywords: disambiguation, normalization, parsing, PubMed

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Authors: Tabrej Khan

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Examination Scheduling System (ESS) is a scheduling system that targets as an exam committee in any academic institute to help them in managing the exams automatically. We present an algorithm for Examination Scheduling System. Nowadays, many universities have challenges with creating examination schedule fast with less confliction compared to hand works. Our aims are to develop a computerized system that can be used in examination scheduling in an academic institute versus available resources (Time, Hall, Invigilator and instructor) with no contradiction and achieve fairness among students. ESS was developed using HTML, C# language, Crystal Report and ASP.NET through Microsoft Visual Studio 2010 as developing tools with integrated SQL server database. This application can produce some benefits such as reducing the time spent in creating an exam schedule and achieving fairness among students

Keywords: examination scheduling system (ESS), algorithm, ASP.NET, crystal report

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Authors: M. Prasanth, V. Nithin, R. Keerthana, S.Kalyani

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In the current scenario, the steering system in automobiles is such that the motion from the steering wheel is transferred to driving wheel by mechanical linkages. In this paper, we propose a method to design a steering mechanism using servomotors to turn the wheels instead of linkages. In this method, a steering angle sensor senses the turn angle of the steering wheel and its output is processed by an electronical control module. Then the ECM compares the angle value to that of a standard value from a look-up database. Then it gives the appropriate input power and the turning duration to the motors. Correspondingly, the motors turn the wheels by means of bevel gears welded to both the motor output shafts and the wheel hubs. Thus, the wheels are turned without the complicated framework of linkages, reducing the driver’s effort and fatigue considerably.

Keywords: electronic control unit, linkage-less steering, servomotors, E-Mo Steer

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Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

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Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

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Authors: Isaura Bonneux

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District heating and cooling (DHC) is increasingly recognized as a viable path towards sustainable heating and cooling. While some countries like Sweden and Denmark have a longstanding tradition of DHC, Belgium is lacking behind. The Northern part of Belgium, Flanders, had only a total of 95 heating networks in July 2023. Nevertheless, it is increasingly exploring its possibilities to enhance the scope of DHC. DHC is a complex energy system, requiring a lot of collaboration between various stakeholders on various levels. Therefore, it is of interest to look closer at policy-related documents at the Flemish (regional) level, as these policies set the scene for DHC development in the Flemish region. This kind of analysis has not been undertaken so far. This paper has the following research question: “Who talks about DHC, and in which way and context is DHC discussed in Flemish policy-related documents?” To answer this question, the Overton policy database was used to search and retrieve relevant policy-related documents. Overton retrieves data from governments, think thanks, NGOs, and IGOs. In total, out of the 244 original results, 117 documents between 2009 and 2023 were analyzed. Every selected document included theme keywords, policymaking department(s), date, and document type. These elements were used for quantitative data description and visualization. Further, qualitative content analysis revealed patterns and main themes regarding DHC in Flanders. Four main conclusions can be drawn: First, it is obvious from the timeframe that DHC is a new topic in Flanders with still limited attention; 2014, 2016 and 2017 were the years with the most documents, yet this number is still only 12 documents. In addition, many documents talked about DHC but not much in depth and painted it as a future scenario with a lot of uncertainty around it. The largest part of the issuing government departments had a link to either energy or climate (e.g. Flemish Environmental Agency) or policy (e.g. Socio-Economic Council of Flanders) Second, DHC is mentioned most within an ‘Environment and Sustainability’ context, followed by ‘General Policy and Regulation’. This is intuitive, as DHC is perceived as a sustainable heating and cooling technique and this analysis compromises policy-related documents. Third, Flanders seems mostly interested in using waste or residual heat as a heating source for DHC. The harbors and waste incineration plants are identified as potential and promising supply sources. This approach tries to conciliate environmental and economic incentives. Last, local councils get assigned a central role and the initiative is mostly taken by them. The policy documents and policy advices demonstrate that Flanders opts for a bottom-up organization. As DHC is very dependent on local conditions, this seems a logic step. Nevertheless, this can impede smaller councils to create DHC networks and slow down systematic and fast implementation of DHC throughout Flanders.

Keywords: district heating and cooling, flanders, overton database, policy analysis

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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Authors: Adriana Radan Ungureanu

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The industrial landscape is changing due to the financial crises, poor availability of raw materials, new discoveries and interdisciplinary collaborations. New ideas shape the change through technologies and bring responses for a better life. The process of change is leaded by big players like states and companies, but they cannot keep their places on the market without the help of the small ones. The main tool of change is technology and the entire developed world dedicated efforts for decades in this direction. Even the expectations are not yet met, the research for finding adequate solutions is far from to be stopped. A relevant example is nanotechnology where most of discoveries still remain into laboratory and could not succeed to find the right way to the market. In front of this situation the right question could be: ”Is it worth investing in nanotechnology in the name of an uncertain future but with very little impact on present?” This paper tries to find a positive answer from a three-dimensional approach using a descriptive analyse based on available database supplied by the European case studies, reports, and literature.

Keywords: Europe, KET’s, nanotechnology, technology

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Authors: Jose R. Garcia, Lexi Frankel, Amalia Ardeljan, Sergio Medina, Ali Yasback, Omar Rashid

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Background: Helicobacter pylori (H. pylori) is a gram-negative, spiral-shaped bacterium that affects nearly half of the population worldwide and humans serve as the principal reservoir. Infection rates usually follow an inverse relationship with hygiene practices and are higher in developing countries than developed countries. Incidence varies significantly by geographic area, race, ethnicity, age, and socioeconomic status. H. pylori is primarily associated with conditions of the gastrointestinal tract such as atrophic gastritis and duodenal peptic ulcers. Infection is also associated with an increased risk of carcinogenesis as there is evidence to show that H. pylori infection may lead to gastric adenocarcinoma and mucosa-associated lymphoid tissue (MALT) lymphoma. It is suggested that H. pylori infection may be considered as a systemic condition, leading to various novel associations with several different neoplasms such as colorectal cancer, pancreatic cancer, and lung cancer, although further research is needed. Emerging evidence suggests that H. pylori infection may offer protective effects against Mycobacterium tuberculosis as a result of non-specific induction of interferon- γ (IFN- γ). Similar methods of enhanced immunity may affect the development of bronchogenic carcinoma due to the antiproliferative, pro-apoptotic and cytostatic functions of IFN- γ. The purpose of this study was to evaluate the correlation between Helicobacter pylori infection and the incidence of bronchogenic carcinoma. Methods: The data was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database to evaluate the patients infected versus patients not infected with H. pylori using ICD-10 and ICD-9 codes. Access to the database was granted by the Holy Cross Health, Fort Lauderdale for the purpose of academic research. Standard statistical methods were used. Results:-Between January 2010 and December 2019, the query was analyzed and resulted in 163,224 in both the infected and control group, respectively. The two groups were matched by age range and CCI score. The incidence of bronchogenic carcinoma was 1.853% with 3,024 patients in the H. pylori group compared to 4.785% with 7,810 patients in the control group. The difference was statistically significant (p < 2.22x10-16) with an odds ratio of 0.367 (0.353 - 0.383) with a confidence interval of 95%. The two groups were matched by treatment and incidence of cancer, which resulted in a total of 101,739 patients analyzed after this match. The incidence of bronchogenic carcinoma was 1.929% with 1,962 patients in the H. pylori and treatment group compared to 4.618% with 4,698 patients in the control group with treatment. The difference was statistically significant (p < 2.22x10-16) with an odds ratio of 0.403 (0.383 - 0.425) with a confidence interval of 95%.

Keywords: bronchogenic carcinoma, helicobacter pylori, lung cancer, pathogen-associated molecular patterns

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Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

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Authors: Francisco Toledo-Castillo, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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Motorcycles constitute about 9% of all motorized vehicles in Spain and are generally overrepresented in traffic accidents, accounting for 21% of total accidents. Six years of motorcycle accident data were obtained through the national accident database of Spain (Dirección General de Tráfico). Some of the studied factors are age, gender, helmet wearing, alcohol consumption, speeding, subject’s driving license and for how long it has been held, the trip purpose, and the presence of a passenger on the vehicle. Key findings show helmet use, unsafe speed, the trip purpose, weather, distraction, collision type and other variables play significant roles in crash-injury outcomes. Finally, we examine evolution of mortality and severity from 2006 to 2011.

Keywords: motorcycle accidents, risk factors, statistics, Spain

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Authors: Tianqi Wu, Min Wang

Abstract:

Research investigating language acquisition from a constructionist perspective has demonstrated that language is learned as constructions at various linguistic levels, which is related to factors of frequency, semantic prototypicality, and form-meaning contingency. However, previous research on construction learning tended to focus on clause-level constructions such as verb argument constructions but few attempts were made to study morpheme-level constructions such as the progressive construction, which is regarded as a source of acquisition problems for English learners from diverse L1 backgrounds, especially for those whose L1 do not have an equivalent construction such as German and Chinese. To trace the developmental trajectory of Chinese EFL learners’ use of the progressive with respect to verb frequency, verb-progressive contingency, and verbal prototypicality and generality, a learner corpus consisting of three sub-corpora representing three different English proficiency levels was extracted from the Chinese Learners of English Corpora (CLEC). As the reference point, a native speakers’ corpus extracted from the Louvain Corpus of Native English Essays was also established. All the texts were annotated with C7 tagset by part-of-speech tagging software. After annotation all valid progressive hits were retrieved with AntConc 3.4.3 followed by a manual check. Frequency-related data showed that from the lowest to the highest proficiency level, (1) the type token ratio increased steadily from 23.5% to 35.6%, getting closer to 36.4% in the native speakers’ corpus, indicating a wider use of verbs in the progressive; (2) the normalized entropy value rose from 0.776 to 0.876, working towards the target score of 0.886 in native speakers’ corpus, revealing that upper-intermediate learners exhibited a more even distribution and more productive use of verbs in the progressive; (3) activity verbs (i.e., verbs with prototypical progressive meanings like running and singing) dropped from 59% to 34% but non-prototypical verbs such as state verbs (e.g., being and living) and achievement verbs (e.g., dying and finishing) were increasingly used in the progressive. Apart from raw frequency analyses, collostructional analyses were conducted to quantify verb-progressive contingency and to determine what verbs were distinctively associated with the progressive construction. Results were in line with raw frequency findings, which showed that contingency between the progressive and non-prototypical verbs represented by light verbs (e.g., going, doing, making, and coming) increased as English proficiency proceeded. These findings altogether suggested that beginning Chinese EFL learners were less productive in using the progressive construction: they were constrained by a small set of verbs which had concrete and typical progressive meanings (e.g., the activity verbs). But with English proficiency increasing, their use of the progressive began to spread to marginal members such as the light verbs.

Keywords: Construction learning, Corpus-based, Progressives, Prototype

Procedia PDF Downloads 128

Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

Abstract:

Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.

Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate

Procedia PDF Downloads 500

Authors: Onder Yakut, Serdar Solak, Emine Dogru Bolat

Abstract:

Measuring the Electrocardiogram (ECG) signal is an essential process for the diagnosis of the heart diseases. The ECG signal has the information of the degree of how much the heart performs its functions. In medical diagnosis and treatment systems, Decision Support Systems processing the ECG signal are being developed for the use of clinicians while medical examination. In this study, a modular wireless ECG (WECG) measuring and recording system using a single board computer and e-Health sensor platform is developed. In this designed modular system, after the ECG signal is taken from the body surface by the electrodes first, it is filtered and converted to digital form. Then, it is recorded to the health database using Wi-Fi communication technology. The real time access of the ECG data is provided through the internet utilizing the developed web interface.

Keywords: ECG, e-health sensor shield, Raspberry Pi, wiFi technology

Procedia PDF Downloads 401

Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

Abstract:

Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: arrhythmic beat detection, ECG, HRV, kNN classifier

Procedia PDF Downloads 352

Authors: Komlan Sedzro

Abstract:

We apply the non-parametric, unconditional, hyperbolic order-α quantile estimator to appraise the relative efficiency of Microfinance Institutions in Africa in terms of outreach. Our purpose is to verify if these institutions, which must constantly try to strike a compromise between their social role and financial sustainability are operationally efficient. Using data on African MFIs extracted from the Microfinance Information eXchange (MIX) database and covering the 2004 to 2006 periods, we find that more efficient MFIs are also the most profitable. This result is in line with the view that social performance is not in contradiction with the pursuit of excellent financial performance. Our results also show that large MFIs in terms of asset and those charging the highest fees are not necessarily the most efficient.

Keywords: data envelopment analysis, microfinance institutions, quantile estimation of efficiency, social and financial performance

Procedia PDF Downloads 310