Search results for: health information exchanges

Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: Road accident, machine learning, support vector machines.

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Authors: S.Solaymani, T.Ghodselahi, N.B.Nezafat, H.Zahrabi, A.Gelali

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The morphological parameter of a thin film surface can be characterized by power spectral density (PSD) functions which provides a better description to the topography than the RMS roughness and imparts several useful information of the surface including fractal and superstructure contributions. Through the present study Nanoparticle copper/carbon composite films were prepared by co-deposition of RF-Sputtering and RF-PECVD method from acetylene gas and copper target. Surface morphology of thin films is characterized by using atomic force microscopy (AFM). The Carbon content of our films was obtained by Rutherford Back Scattering (RBS) and it varied from .4% to 78%. The power values of power spectral density (PSD) for the AFM data were determined by the fast Fourier transform (FFT) algorithms. We investigate the effect of carbon on the roughness of thin films surface. Using such information, roughness contributions of the surface have been successfully extracted.

Keywords: Atomic force microscopy, Fast Fourier transform, Power spectral density, RBS.

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Authors: Fatanah M. Suhaimi, J. Geoffrey Chase, Christopher G. Pretty, Rodney Elliott, Geoffrey M. Shaw

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Microcirculatory dysfunction is very common in sepsis and may results in organ failure and increased risk of death. Analyzing oxygen utilization can potentially assess microcirculation function of an individual. In this study, a modified pulse oximeter is used to extract information signals due to absorption of red (R) and infrared (IR) light. IR and R signal are related to the overall blood volume and reduced hemoglobin, respectively. Differences between these two signals thus represent the amount of oxygenated hemoglobin. Avascular occlusion test has been conducted on healthy individuals to validate the pulse oximeter concept. In this test, both R and IR signals rapidly changed according to the occlusion process. The pulse oximeter concept presented is capable of extracting valuable information to assess microcirculation condition. Implementing this concept on ICU patients has the potential to aid sepsis diagnosis and provide more accurate tracking of patient state and sepsis status.

Keywords: Microcirculation, sepsis, sepsis diagnosis, oxygen extraction.

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Authors: Osuagwu Justine Ugochukwu, Sazali Abd Wahab, Sunday Sunday Akpan

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Investigating the effects of transformational and transactional leadership styles on the performance of healthcare employees at the University Teaching Hospital (UNTH) in Enugu, Nigeria, was the goal of the research. The respondents were asked to fill out a structured questionnaire. The respondents were chosen using a straightforward random sampling technique and consisted of 370 health workers at the hospital. The result of the analysis revealed that transactional and transformational leadership style has a positive while ambidextrous leadership has a negative effect on healthcare workers' performance in UNTH, Enugu. Therefore, the management of public hospitals that have the capacity to change their top management approach to leadership styles will gain substantial support from their employees’ thereby increasing organizational commitment and performance among health workers. This will have remarkable social implications, one of which is a change in the work culture and attitude of medical personnel from the seemingly anti-community of patients to friendly engagement and treatment of patients leading to a harmonious coexistence among these individuals in society. Investigating ambidextrous leadership and the use of nonparametric analysis is unique and has brought knowledge to leadership literature.

Keywords: Workers’ performance, transformational leadership, transactional leadership, governance quality, ambidextrous leadership.

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: Public emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining.

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Authors: Urva Maryam

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Private data are more often breached by clever social engineering rather than exploiting technical vulnerabilities in the systems. Complete information security requires good data safety practices to go along with technical solutions. Hackers often begin their operation by simply sending spoofed emails or fraudulent URLs to their targets and trick them into providing sensitive information such as passwords or bank account details. This technique is called phishing. Phishing attacks can be launched on email addresses, open ports and unsecured web browsers. This study uses quantitative method of research to execute phishing experiments on the participants to test their response to the phishing emails. These experiments were run on Kali Linux distribution which came bundled with multiple open-source intelligence (OSINT) tools that were used in the study. The aim of this research is to see how successful phishing attacks can be launched using OSINT and to test the response of people to spoofed emails.

Keywords: OSINT, phishing, spear phishing, email spoofing, theHarvester, Maltego.

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Authors: Kanda Runapongsa Saikaew, Patcharaporn Jiranuwattanawong, Patinya Taearak

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Currently, there is excessively growing information about places on Facebook, which is the largest social network but such information is not explicitly organized and ranked. Therefore users cannot exploit such data to recommend places conveniently and quickly. This paper proposes a Facebook application and an Android application that recommend places based on the number of check-ins of those places, the distance of those places from the current location, the number of people who like Facebook page of those places, and the number of talking about of those places. Related Facebook data is gathered via Facebook API requests. The experimental results of the developed applications show that the applications can recommend places and rank interesting places from the most to the least. We have found that the average satisfied score of the proposed Facebook application is 4.8 out of 5. The users’ satisfaction can increase by adding the app features that support personalization in terms of interests and preferences.

Keywords: Mobile computing, location-based services, recommendation system, social network analysis.

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Authors: Deniz Deryakulu, Sener Buyukozturk, Sirin Karadeniz, Sinan Olkun

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The purpose of this study was to determine the most satisfying and frustrating aspects of ICT (Information and Communications Technologies) teaching in Turkish schools. Another aim was to compare these aspects based-on ICT teachers- selfefficacy. Participants were 119 ICT teachers from different geographical areas of Turkey. Participants were asked to list salient satisfying and frustrating aspects of ICT teaching, and to fill out the Self-Efficacy Scale for ICT Teachers. Results showed that the high self-efficacy teachers listed more positive and negative aspects of ICT teaching then did the low self-efficacy teachers. The satisfying aspects of ICT teaching were the dynamic nature of ICT subject, higher student interest, having opportunity to help other subject teachers, and lecturing in well-equipped labs, whereas the most frequently cited frustrating aspects of ICT teaching were ICT-related extra works of schools and colleagues, shortages of hardware and technical problems, indifferent students, insufficient teaching time, and the status of ICT subject in school curriculum. This information could be useful in redesigning ICT teachers- roles and responsibilities as well as job environment in schools.

Keywords: ICT teachers, frustrating aspects of ICT teaching, satisfying aspects of ICT teaching, teacher self-efficacy.

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Authors: Kumara Jayapathma J. H. M. S. S., Dampegama S. D. P. J.

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Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.

Keywords: Android, Firebase, GeoJSON, GIS, JAVA, JSON, LIS, mobile GIS, real-time, REST API.

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: Genetic data, Pinzgau cattle, supervised learning.

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Authors: Jonghoon Kim, Gilwon Yoon

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A wrist-band type biosignal measurement system and its data transfer through human body communication (HBC) were investigated. An HBC method based on pulses of ultra-wide band instead of using frequency or amplitude modulations was studied and implemented since the system became very compact and it was more suited for personal or mobile health monitoring. Our system measured photo-plethysmogram (PPG) and measured PPG signals were transmitted through a finger to a monitoring PC system. The device was compact and low-power consuming. HBC communication has very strongsecurity measures since it does not use wireless network.Furthermore, biosignal monitoring system becomes handy because it does not need to have wire connections.

Keywords: Biosignal, human body communication, mobile health, PPG, ultrawide band.

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Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: Resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan.

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Authors: Napisporn Memongkol, Runchana Sinthavalai, Nattapong Seneeratanaprayune Weerawat Ounsaneha, Chanisada Choosuk

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The objective of this research is to develop the performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency Medical Institute of Thailand (EMIT) was considered using strategic analysis to developed Strategy Map (SM) and identified the Success Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited only with the first dimension of National Strategic Plan (infrastructure and information technology development). Besides, the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators were developed from the analysis results of SM and SFs.

Keywords: Emergency Medical Service, Performance Indicator, Success Factor, Thailand

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Authors: Marwa Ben Abdessalem, Amin Zribi, Ammar Bouallègue

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In this paper, a Joint Source Channel coding scheme based on LDPC codes is investigated. We consider two concatenated LDPC codes, one allows to compress a correlated source and the second to protect it against channel degradations. The original information can be reconstructed at the receiver by a joint decoder, where the source decoder and the channel decoder run in parallel by transferring extrinsic information. We investigate the performance of the JSC LDPC code in terms of Bit-Error Rate (BER) in the case of transmission over an Additive White Gaussian Noise (AWGN) channel, and for different source and channel rate parameters. We emphasize how JSC LDPC presents a performance tradeoff depending on the channel state and on the source correlation. We show that, the JSC LDPC is an efficient solution for a relatively low Signal-to-Noise Ratio (SNR) channel, especially with highly correlated sources. Finally, a source-channel rate optimization has to be applied to guarantee the best JSC LDPC system performance for a given channel.

Keywords: AWGN channel, belief propagation, joint source channel coding, LDPC codes.

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.

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Authors: V. Viduĉić, J. Žanić Mikuliĉić, M. Raĉić, K. Sladojević

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The research presented in this paper has been focused on analysing the impact of traffic on the sustainable development of tourism in Croatia's Dubrovacko-Neretvanska County by the year 2020, based on the figures and trends reported in 2014 and using the relevant variables that characterise the synergy of traffic and tourism in, speaking from the geographic viewpoint, the most problematic county in the Republic of Croatia. The basic hypothesis has been confirmed through scientifically obtained research results, through the quantification of the model's variables and the direct growth rates of the designed model. On the basis of scientific insights into the sustainable development of traffic and tourism in Dubrovacko- Neretvanska County, it is possible to propose a new information model for traffic at the service of the sustainable development of tourism in the County for the period 2014-2020.

Keywords: Environment protection, hotel industry, private sector, quantification.

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: Decision tree, classification, data mining, scholarship.

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Authors: O. Z. Jasim

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An accuracy digital map must satisfy the users for two main requirements, first, map must be visually readable and second, all the map elements must be in a good representation. These two requirements hold especially true for map generalization which aims at simplifying the representation of cartographic data. Different scales of maps are very important for any decision in any maps with different scales such as master plan and all the infrastructures maps in civil engineering. Cartographer cannot project the data onto a piece of paper, but he has to worry about its readability. The map layout of any geodatabase is very important, this layout is help to read, analyze or extract information from the map. There are many principles and guidelines of generalization that can be find in the cartographic literature. A manual reduction method for generalization depends on experience of map maker and therefore produces incompatible results. Digital generalization, rooted from conventional cartography, has become an increasing concern in both Geographic Information System (GIS) and mapping fields. This project is intended to review the state of the art of the new technology and help to understand the needs and plans for the implementation of digital generalization capability as well as increase the knowledge of production topographic maps.

Keywords: Cartography, digital generalization, mapping, GIS.

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Authors: Ion-Cosmin Dita, Vasile Gui, Franz Quint, Marius Otesteanu

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In automatic manufacturing and assembling of mechanical, electrical and electronic parts one needs to reliably identify the position of components and to extract the information of these components. Data Matrix Codes (DMC) are established by these days in many areas of industrial manufacturing thanks to their concentration of information on small spaces. In today’s usually order-related industry, where increased tracing requirements prevail, they offer further advantages over other identification systems. This underlines in an impressive way the necessity of a robust code reading system for detecting DMC on the components in factories. This paper compares two methods for estimating the angle of orientation of Data Matrix Codes: one method based on the Hough Transform and the other based on the Mean Shift Algorithm. We concentrate on Data Matrix Codes in industrial environment, punched, milled, lasered or etched on different materials in arbitrary orientation.

Keywords: Industrial data matrix code, Hough transform, mean shift.

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Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng

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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.

Keywords: Biological molecular networks, essential genes, graph theory, network subgraphs.

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Authors: Jeerapa Sappakitkamjorn, Sa-aat Niwitpong

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In many practical applications in various areas, such as engineering, science and social science, it is known that there exist bounds on the values of unknown parameters. For example, values of some measurements for controlling machines in an industrial process, weight or height of subjects, blood pressures of patients and retirement ages of public servants. When interval estimation is considered in a situation where the parameter to be estimated is bounded, it has been argued that the classical Neyman procedure for setting confidence intervals is unsatisfactory. This is due to the fact that the information regarding the restriction is simply ignored. It is, therefore, of significant interest to construct confidence intervals for the parameters that include the additional information on parameter values being bounded to enhance the accuracy of the interval estimation. Therefore in this paper, we propose a new confidence interval for the coefficient of variance where the population mean and standard deviation are bounded. The proposed interval is evaluated in terms of coverage probability and expected length via Monte Carlo simulation.  

Keywords: Bounded parameters, coefficient of variation, confidence interval, Monte Carlo simulation.

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Yu-Te Wu, Sui-Hing Yan

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This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions, and the network analysis based on graph theory to investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI.

Keywords: Cognitive decline, functional connectivity, MCI, MMSE.

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Authors: S. Abed, S. O’Neill

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This research explored ward nurses’ views about the characteristics of effective nurse leaders in the context of Iraq as a developing country, where the delivery of health care continues to face disruption and change. It is well established that the provision of modern health care requires effective nurse leaders, but in countries such as Iraq the lack of effective nurse leaders is noted as a major challenge. In a descriptive quantitative study, a survey questionnaire was administered to 210 ward nurses working in two public hospitals in a major city in the north of Iraq. The participating nurses were of the opinion that the effectiveness of their nurse leaders was evident in their ability to demonstrate: good clinical knowledge, effective communication and managerial skills. They also viewed their leaders as needing to hold high-level nursing qualifications, though this was not necessarily the case in practice. Additionally, they viewed nurse leaders’ personal qualities as important, which included politeness, ethical behaviour, and trustworthiness. When considered against the issues raised in interviews with a smaller group (20) of senior nurse leaders, representative of the various occupational levels, implications identify the need for professional development that focuses on how the underpinning competencies relate to leadership and how transformational leadership is evidenced in practice.

Keywords: Health care, nurse education, nurse leadership, nursing in Iraq, transformational leadership.

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: Feature generation, feature learning, genetic algorithm, music information retrieval.

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Authors: Chi-Lun Liu

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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.

Keywords: Knowledge representation, reasoning, ontology, class diagram, software engineering.

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Authors: Jaehoon Ha, Byungmo Kang, Kilho Hong, Jungsoo Park

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Electro-optical (EO) stabilized platforms have been widely used for surveillance and reconnaissance on various types of vehicles, from surface ships to unmanned air vehicles (UAVs). EO stabilized platforms usually consist of an assembly of structure, bearings, and motors called gimbals in which a gyroscope is installed. EO elements such as a CCD camera and IR camera, are mounted to a gimbal, which has a range of motion in elevation and azimuth and can designate and track a target. In addition, a laser range finder (LRF) can be added to the gimbal in order to acquire the precise slant range from the platform to the target. Recently, a versatile functionality of target localization is needed in order to cooperate with the weapon systems that are mounted on the same platform. The target information, such as its location or velocity, needed to be more accurate. The accuracy of the target information depends on diverse component errors and alignment errors of each component. Specially, the type of moving platform can affect the accuracy of the target information. In the case of flying platforms, or UAVs, the target location error can be increased with altitude so it is important to measure altitude as precisely as possible. In the case of surface ships, target location error can be increased with obliqueness of the elevation angle of the gimbal since the altitude of the EO stabilized platform is supposed to be relatively low. The farther the slant ranges from the surface ship to the target, the more extreme the obliqueness of the elevation angle. This can hamper the precise acquisition of the target information. So far, there have been many studies on EO stabilized platforms of flying vehicles. However, few researchers have focused on ship-borne EO stabilized platforms of the surface ship. In this paper, we deal with a target localization method when an EO stabilized platform is located on the mast of a surface ship. Especially, we need to overcome the limitation caused by the obliqueness of the elevation angle of the gimbal. We introduce a well-known approach for target localization using Unscented Kalman Filter (UKF) and present the problem definition showing the above-mentioned limitation. Finally, we want to show the effectiveness of the approach that will be demonstrated through computer simulations.

Keywords: Target localization, ship-borne electro-optical stabilized platform, unscented Kalman filter.

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Authors: Yang Luo, Beibei Wang

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In this paper, we present a design methodology of lightweight register transfer level (RTL) hardware threat implemented based on a MAX II FPGA platform. The dynamic power consumed by the toggling of the various bit of registers as well as the dynamic power consumed per unit of logic circuits were analyzed. The hardware threat was designed taking advantage of the differences in dynamic power consumed per unit of logic circuits to hide the transfer information. The experiment result shows that the register hardware threat was successfully implemented by using different dynamic power consumed per unit of logic circuits to hide the key information of DES encryption module. It needs more than 100000 sample curves to reduce the background noise by comparing the sample space when it completely meets the time alignment requirement. In additional, an external trigger signal is playing a very important role to detect the hardware threat in this experiment.

Keywords: Side-channel analysis, hardware threat, register transfer level, dynamic power.

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Authors: C. Cruz, A. Breda

Abstract:

Emotions are manifestations of everything that happens around us, influencing, consequently, our actions. People experience emotions continuously when socialize with friends, when facing complex situations, and when at school, among many other situations. Although the influence of emotions in the teaching and learning process is nothing new, its study in the academic field has been more popular in recent years, distinguishing between positive (e.g., enjoyment and curiosity) and negative emotions (e.g., boredom and frustration). There is no doubt that emotions play an important role in the students’ learning process since the development of knowledge involves thoughts, actions, and emotions. Nowadays, one of the most significant changes in acquiring knowledge, accessing information, and communicating is the way we do it through technological and digital resources. Faced with an increasingly frequent use of technological or digital means with different purposes, whether in the acquisition of knowledge or in communicating with others, the emotions involved in these processes change naturally. The speed with which the Internet provides information reduces the excitement for searching for the answer, the gratification of discovering something through our own effort, the patience, the capacity for effort, and resilience. Thus, technological and digital devices are bringing changes to the emotional domain. For this reason and others, it is essential to educate children from an early age to understand that it is not possible to have everything with just one click and to deal with negative emotions. Currently, many curriculum guidelines highlight the importance of the development of so-called soft skills, in which the emotional domain is present, in academic contexts. Within the scope of the Portuguese reality, the “Students’ profile by the end of compulsory schooling” and the “Health education reference” also emphasize the importance of emotions in education. There are several resources to stimulate good emotions in articulation with cognitive development. One of the most predictable and not very used resources in the most diverse areas of knowledge after pre-school education is the literature. Due to its characteristics, in the narrative or in the illustrations, literature provides the reader with a journey full of emotions. On the other hand, literature makes it possible to establish bridges between narrative and different areas of knowledge, reconciling the cognitive and emotional domains. This study results from the presentation session of a children's book, entitled “From the Outside to Inside and from the Inside to Outside”, to children attending the 2nd, 3rd, and 4th years of basic education in the Portuguese education system. In this book, rationale and emotion are in constant dialogue, so in this session, based on excerpts from the book dramatized by the authors, some questions were asked to the children in a large group, with an aim to explore their perception regarding certain emotions or events that trigger them. According to the aim of this study, qualitative, descriptive, and interpretative research was carried out based on participant observation and audio records.

Keywords: Emotions, children’s literature, basic education, soft skills.

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Authors: Ahd Aljarf, Saad Amin

Abstract:

Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.

Keywords: Image Filtering, Image Reconstruction, Image Processing, Forensic Images.

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

Abstract:

The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8.

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