Search results for: monitoring tool

Authors: Eoin Kirwan, Christopher Nulty, Declan Browne

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The professional ice hockey season consists of approximately 60 regular season games with periods of fixture congestion occurring several times in the average season. These periods of congestion provide limited time for recovery, exposing the athletes to the risk of competing whilst not fully recovered. Although a body of research is growing with respect to monitoring fatigue, particularly during periods of congested fixtures in team sports such as rugby and soccer, it has received little to no attention thus far in ice hockey athletes. Consequently, there is limited knowledge on monitoring tools that might effectively detect a fatigue response and the magnitude of fatigue that can accumulate when recovery is limited by competitive fixtures. The benefit of quantifying and establishing fatigue status is the ability to optimise training and provide pertinent information on player health, injury risk, availability and readiness. Some commonly used methods to assess fatigue and recovery status of athletes include the use of perceived fatigue and wellbeing questionnaires, tests of muscular force and ratings of perceive exertion (RPE). These measures are widely used in popular team sports such as soccer and rugby and show promise as assessments of fatigue and recovery status for ice hockey athletes. As part of a larger study, this study explored the magnitude of changes in adductor muscle strength after game play and throughout a period of fixture congestion and examined the relationship between internal game load and perceived wellbeing with adductor muscle strength. Methods 8 professional ice hockey players from a British Elite League club volunteered to participate (age = 29.3 ± 2.49 years, height = 186.15 ± 6.75 cm, body mass = 90.85 ± 8.64 kg). Prior to and after competitive games each player performed trials of the adductor squeeze test at 0˚ hip flexion with the lead investigator using hand-held dynamometry. Rate of perceived exertion was recorded for each game and from data of total ice time individual session RPE was calculated. After each game players completed a 5- point questionnaire to assess perceived wellbeing. Data was collected from six competitive games, 1 practice and 36 hours post the final game, over a 10 – day period. Results Pending final data collection in February Conclusions Pending final data collection in February.

Keywords: Conjested fixtures, fatigue monitoring, ice hockey, readiness

Procedia PDF Downloads 142

Authors: Morné Roman, Robert van Zyl, Nishanth Parus, Nishal Mahatho

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Leakage current monitoring for high voltage transmission line insulators is of interest as a performance indicator. Presently, to the best of our knowledge, there is no commercially available, clamp-on type, non-intrusive device for measuring leakage current on energised high voltage direct current (HVDC) transmission line insulators. The South African power utility, Eskom, is investigating the development of such a hand-held sensor for two important applications; first, for continuous real-time condition monitoring of HVDC line insulators and, second, for use by live line workers to determine if it is safe to work on energised insulators. In this paper, a DC leakage current sensor based on magnetic field sensing techniques is developed. The magnetic field sensor used in the prototype can also detect alternating current up to 5 MHz. The DC leakage current prototype detects the magnetic field associated with the current flowing on the surface of the insulator. Preliminary HVDC leakage current measurements are performed on glass insulators. The results show that the prototype can accurately measure leakage current in the specified current range of 1-200 mA. The influence of external fields from the HVDC line itself on the leakage current measurements is mitigated through a differential magnetometer sensing technique. Thus, the developed sensor can perform measurements on in-service HVDC insulators. The research contributes to the body of knowledge by providing a sensor to measure leakage current on energised HVDC insulators non-intrusively. This sensor can also be used by live line workers to inform them whether or not it is safe to perform maintenance on energized insulators.

Keywords: direct current, insulator, leakage current, live line, magnetic field, sensor, transmission lines

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Authors: B. Gültekin, T. Gültekin

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Peace diplomacy is the most important international tool to maintain peace all over the World. This study consists of three parts. In the first part, the leadership of Devlet Bahçeli, leader of the Nationalist Movement Party, will be introduced as a tool of peace communication and peace management. Also, in this part, peace communication will be explained by the peace leadership traits of Devlet Bahçeli, who is one of the efficient political leaders representing the concepts of compromise and agreement on different sides of politics. In the second part of study, it is aimed to analyze Devlet Bahçeli’s leadership within the frame of peace communication and the final part of this study is about creating an original public communication model for public diplomacy based on Devlet Bahçeli as an example. As a result, the main purpose of this study is to develop an original peace communication model including peace modules, peace management projects, original dialogue procedures and protocols exhibited in the policies of Devlet Bahçeli. The political leadership represented by Devlet Bahçeli inspires political leaders to provide peace communication. In this study, principles and policies of peace leadership of Devlet Bahçeli will be explained as an original model on a peace communication platform.

Keywords: public diplomacy, dialogue management, peace leadership, peace diplomacy

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Authors: Divya Palaniappan

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Early Childhood assessment tools must measure the quality and the appropriateness of a curriculum with respect to culture and age of the children. Preschool assessment tools lack psychometric properties and were developed to measure only few areas of development such as specific skills in music, art and adaptive behavior. Existing preschool assessment tools in India are predominantly informal and are fraught with judgmental bias of observers. The World of Discovery TM curriculum focuses on accelerating the physical, cognitive, language, social and emotional development of pre-schoolers in India through various activities. The curriculum caters to every child irrespective of their dominant intelligence as per Gardner’s Theory of Multiple Intelligence which concluded "even students as young as four years old present quite distinctive sets and configurations of intelligences". The curriculum introduces a new theme every week where, concepts are explained through various activities so that children with different dominant intelligences could understand it. For example: The ‘Insects’ theme is explained through rhymes, craft and counting corner, and hence children with one of these dominant intelligences: Musical, bodily-kinesthetic and logical-mathematical could grasp the concept. The child’s progress is evaluated using an assessment tool that measures a cluster of inter-dependent developmental areas: physical, cognitive, language, social and emotional development, which for the first time renders a multi-domain approach. The assessment tool is a 5-point rating scale that measures these Developmental aspects: Cognitive, Language, Physical, Social and Emotional. Each activity strengthens one or more of the developmental aspects. During cognitive corner, the child’s perceptual reasoning, pre-math abilities, hand-eye co-ordination and fine motor skills could be observed and evaluated. The tool differs from traditional assessment methodologies by providing a framework that allows teachers to assess a child’s continuous development with respect to specific activities in real time objectively. A pilot study of the tool was done with a sample data of 100 children in the age group 2.5 to 3.5 years. The data was collected over a period of 3 months across 10 centers in Chennai, India, scored by the class teacher once a week. The teachers were trained by psychologists on age-appropriate developmental milestones to minimize observer’s bias. The norms were calculated from the mean and standard deviation of the observed data. The results indicated high internal consistency among parameters and that cognitive development improved with physical development. A significant positive relationship between physical and cognitive development has been observed among children in a study conducted by Sibley and Etnier. In Children, the ‘Comprehension’ ability was found to be greater than ‘Reasoning’ and pre-math abilities as indicated by the preoperational stage of Piaget’s theory of cognitive development. The average scores of various parameters obtained through the tool corroborates the psychological theories on child development, offering strong face validity. The study provides a comprehensive mechanism to assess a child’s development and differentiate high performers from the rest. Based on the average scores, the difficulty level of activities could be increased or decreased to nurture the development of pre-schoolers and also appropriate teaching methodologies could be devised.

Keywords: child development, early childhood assessment, early childhood curriculum, quantitative assessment of preschool curriculum

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: John Sodeau, David O'Connor, Shane Daly, Stig Hellebust

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This study is the first to employ the online WIBS (Waveband Integrated Biosensor Sensor) technique for the monitoring of bioaerosol emissions and non-fluorescing “dust” released from a composting/green waste site. The purpose of the research was to provide a “proof of principle” for using WIBS to monitor such a location continually over days and nights in order to construct comparative “bioaerosol site profiles”. Current impaction/culturing methods take many days to achieve results available by the WIBS technique in seconds.The real-time data obtained was then used to assess variations of the bioaerosol counts as a function of size, “shape”, site location, working activity levels, time of day, relative humidity, wind speeds and wind directions. Three short campaigns were undertaken, one classified as a “light” workload period, another as a “heavy” workload period and finally a weekend when the site was closed. One main bioaerosol size regime was found to predominate: 0.5 micron to 3 micron with morphologies ranging from elongated to elipsoidal/spherical. The real-time number-concentration data were consistent with an Andersen sampling protocol that was employed at the site. The number-concentrations of fluorescent particles as a proportion of total particles counted amounted, on average, to ~1% for the “light” workday period, ~7% for the “heavy” workday period and ~18% for the weekend. The bioaerosol release profiles at the weekend were considerably different from those monitored during the working weekdays.

Keywords: bioaerosols, composting, fluorescence, particle counting in real-time

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

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

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

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Authors: Sousan Arafeh

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Educational systems and schools worldwide are increasingly reliant on information and communication technology (ICT). Unfortunately, most educational leadership development programs do not offer formal curricular and/or field experiences that prepare students for managing ICT resources, personnel, and processes. The result is a steep learning curve for the leader and his/her staff and dissipated organizational energy that compromises desired outcomes. To address this gap in education leaders’ development, Arafeh’s Integrated Technology Leadership Model (AITLM) was created. It is a conceptual model and tool that educational leadership students can use to better understand the ICT ecology that exists within their schools. The AITL Model consists of six 'infrastructure types' where ICT activity takes place: technical infrastructure, communications infrastructure, core business infrastructure, context infrastructure, resources infrastructure, and human infrastructure. These six infrastructures are further divided into 16 key areas that need management attention. The AITL Model was created by critically analyzing existing technology/ICT leadership models and working to make something more authentic and comprehensive regarding school leaders’ purview and experience. The AITL Model then served as a tool when it was distributed to over 150 educational leadership students who were asked to review it and qualitatively share their reactions. Students said the model presented crucial areas of consideration that they had not been exposed to before and that the exercise of reviewing and discussing the AITL Model as a group was useful for identifying areas of growth that they could pursue in the leadership development program and in their professional settings. While development in all infrastructures and key areas was important for students’ understanding of ICT, they noted that they were least aware of the importance of the intangible area of the resources infrastructure. The AITL Model will be presented and session participants will have an opportunity to review and reflect on its impact and utility. Ultimately, the AITL Model is one that could have significant policy and practice implications. At the very least, it might help shape ICT content in educational leadership development programs through curricular and pedagogical updates.

Keywords: education leadership, information and communications technology, ICT, leadership capacity building, leadership development

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Authors: Harish Bisht, Bahadur Singh Kotlia, Kireet Kumar

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In order to reconstruct past retreating rates, total area loss, volume change and shift in snout position were measured through multi-temporal satellite data from 1989 to 2016 and kinematic GPS survey from 2015 to 2016. The results obtained from satellite data indicate that in the last 27 years, Chaturangi glacier snout has retreated 1172.57 ± 38.3 m (average 45.07 ± 4.31 m/year) with a total area and volume loss of 0.626 ± 0.001 sq. Km and 0.139 Km³, respectively. The field measurements through differential global positioning system survey revealed that the annual retreating rate was 22.84 ± 0.05 m/year. The large variations in results derived from both the methods are probably because of higher difference in their accuracy. Snout monitoring of the Gangotri glacier during the ablation season (May to September) in the years 2005 and 2015 reveals that the retreating rate has been comparatively more declined than that shown by the earlier studies. The GPS dataset shows that the average recession rate is 10.26 ± 0.05 m/year. In order to determine the possible causes of decreased retreating rate, a relationship between debris thickness and melt rate was also established by using ablation stakes. The present study concludes that remote sensing method is suitable for large area and long term study, while kinematic GPS is more appropriate for the annual monitoring of retreating rate of glacier snout. The present study also emphasizes on mapping of all the tributary glaciers in order to assess the overall changes in the main glacier system and its health.

Keywords: Chaturangi glacier, Gangotri glacier, glacier snout, kinematic global positioning system, retreat rate

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Authors: Nahlah Abbas, Saleh A. Wasimi, Nadhir Al-Ansari

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The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future.

Keywords: Tigris River, climate change, water resources, SWAT

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Authors: Chayanika Hazarika Bordoloi

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This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

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Authors: Jugal Bhandari, K. Hari Priya

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The ECG signal provides important clinical information which could be used to pretend the diseases related to heart. Accordingly, delineation of ECG signal is an important task. Whereas delineation of P and T waves is a complex task. This paper deals with the Study of ECG signal and analysis of signal by means of Verilog Design of efficient filters and MATLAB tool effectively. It includes generation and simulation of ECG signal, by means of real time ECG data, ECG signal filtering and processing by analysis of different algorithms and techniques. In this paper, we design a basic particle filter which generates a dynamic model depending on the present and past input samples and then produces the desired output. Afterwards, the output will be processed by MATLAB to get the actual shape and accurate values of the ranges of P-wave and T-wave of ECG signal. In this paper, Questasim is a tool of mentor graphics which is being used for simulation and functional verification. The same design is again verified using Xilinx ISE which will be also used for synthesis, mapping and bit file generation. Xilinx FPGA board will be used for implementation of system. The final results of FPGA shall be verified with ChipScope Pro where the output data can be observed.

Keywords: ECG, MATLAB, Bayesian filtering, particle filter, Verilog hardware descriptive language

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Authors: Roy. H. A. Lindelauf

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Cyberattacks are complex processes consisting of multiple interwoven tasks conducted by a set of agents. Interdictions and defenses against such attacks often rely on cyber kill chain (CKC) models. A CKC is a framework that tries to capture the actions taken by a cyber attacker. There exists a growing body of literature on CKCs. Most of this work either a) describes the CKC with respect to one or more specific cyberattacks or b) discusses the tools and technologies used by the attacker at each stage of the CKC. Defenders, facing scarce resources, have to decide where to allocate their resources given the CKC and partial knowledge on the tools and techniques attackers use. In this presentation CKCs are analyzed through the lens of covert projects, i.e., interrelated tasks that have to be conducted by agents (human and/or computer) with the aim of going undetected. Various aspects of covert project models have been studied abundantly in the operations research and game theory domain, think of resource-limited interdiction actions that maximally delay completion times of a weapons project for instance. This presentation has investigated both cooperative and non-cooperative game theoretic covert project models and elucidated their relation to CKC modelling. To view a CKC as a covert project each step in the CKC is broken down into tasks and there are players of which each one is capable of executing a subset of the tasks. Additionally, task inter-dependencies are represented by a schedule. Using multi-glove cooperative games it is shown how a defender can optimize the allocation of his scarce resources (what, where and how to monitor) against an attacker scheduling a CKC. This study presents and compares several cooperative game theoretic solution concepts as metrics for assigning resources to the monitoring of agents.

Keywords: cyber defense, cyber kill chain, game theory, information warfare techniques

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Authors: Marinella Majorano, Rachele Ferrari, Tamara Bastianello

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The recent technological advance allows for applying innovative and multimedia screen-based assessment tools to test children's language and early literacy skills, monitor their growth over the preschool years, and test their readiness for primary school. Several are the advantages that a computer-based assessment tool offers with respect to paper-based tools. Firstly, computer-based tools which provide the use of games, videos, and audio may be more motivating and engaging for children, especially for those with language difficulties. Secondly, computer-based assessments are generally less time-consuming than traditional paper-based assessments: this makes them less demanding for children and provides clinicians and researchers, but also teachers, with the opportunity to test children multiple times over the same school year and, thus, to monitor their language growth more systematically. Finally, while paper-based tools require offline coding, computer-based tools sometimes allow obtaining automatically calculated scores, thus producing less subjective evaluations of the assessed skills and provide immediate feedback. Nonetheless, using computer-based assessment tools to test meta-phonological and language skills in children is not yet common practice in Italy. The present contribution aims to estimate the internal consistency of a computer-based assessment (i.e., the Simo-syl assessment). Sixty-three Italian pre-schoolers aged between 4;10 and 5;9 years were tested at the beginning of the last year of the preschool through paper-based standardised tools in their lexical (Peabody Picture Vocabulary Test), morpho-syntactical (Grammar Repetition Test for Children), meta-phonological (Meta-Phonological skills Evaluation test), and phono-articulatory skills (non-word repetition). The same children were tested through Simo-syl assessment on their phonological and meta-phonological skills (e.g., recognise syllables and vowels and read syllables and words). The internal consistency of the computer-based tool was acceptable (Cronbach's alpha = .799). Children's scores obtained in the paper-based assessment and scores obtained in each task of the computer-based assessment were correlated. Significant and positive correlations emerged between all the tasks of the computer-based assessment and the scores obtained in the CMF (r = .287 - .311, p < .05) and in the correct sentences in the RCGB (r = .360 - .481, p < .01); non-word repetition standardised test significantly correlates with the reading tasks only (r = .329 - .350, p < .05). Further tasks should be included in the current version of Simo-syl to have a comprehensive and multi-dimensional approach when assessing children. However, such a tool represents a good chance for the teachers to early identifying language-related problems even in the school environment.

Keywords: assessment, computer-based, early identification, language-related skills

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Authors: Sinan Serkan Çağlı

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This study explores the effectiveness of incorporating storytelling tasks into language acquisition programs for young learners. The research investigates how storytelling, as a pedagogical tool, can contribute to the enhancement of language acquisition skills in children. Drawing upon relevant literature and empirical data, this article examines the impact of storytelling on vocabulary development, comprehension, and overall language proficiency in early childhood education in Turkey. The study adopts a qualitative approach, including classroom observations and interviews with teachers and students. Findings suggest that storytelling tasks not only foster linguistic competence but also stimulate cognitive and socio-emotional development in young learners. Additionally, the article explores various storytelling techniques and strategies suitable for different age groups. It is evident that integrating storytelling tasks into language learning environments can create engaging and effective opportunities for young learners to acquire language skills in a natural and enjoyable way. This research contributes valuable insights into the pedagogical practices that promote language acquisition in early childhood, emphasizing the significance of storytelling as a powerful educational tool, especially in Turkey for EFL students.

Keywords: storytelling, language acquisition, young learners, early childhood education, pedagogy, language proficiency

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Authors: Warda Ajaz

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This study uses the ‘Community Capitals Framework’ (CCF) to develop a community resilience index that can serve as a useful tool for measuring resilience of communities in diverse contexts and backgrounds. CCF is an important analytical tool to assess holistic community change. This framework identifies seven major types of community capitals: natural, cultural, human, social, political, financial and built, and claims that the communities that have been successful in supporting healthy sustainable community and economic development have paid attention to all these capitals. The framework, therefore, proposes to study the community development through identification of assets in these major capitals (stock), investment in these capitals (flow), and the interaction between these capitals. Capital based approaches have been extensively used to assess community resilience, especially in the context of natural disasters and extreme events. Therefore, this study identifies key indicators for estimating each of the seven capitals through an extensive literature review and then develops an index to calculate a community resilience score. The CCF-based community resilience index presents an innovative way of operationalizing the concept of community resilience and will contribute toward decision-relevant research regarding adaptation and mitigation of community vulnerabilities to climate change-induced, as well as other adverse events.

Keywords: adverse events, community capitals, community resilience, climate change, economic development, sustainability

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Authors: Lou J. Pino, Mark Campbell, Matthew J. Kennedy, Ashleigh C. Kennedy

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A concussion is complex and nuanced, with cognitive rest being a key component of recovery. Cognitive overexertion during rehabilitation from a concussion is associated with delayed recovery. However, daily living imposes cognitive demands that may be unavoidable and difficult to quantify. Therefore, a portable tool capable of alerting patients before cognitive overexertion occurs could allow patients to maintain their quality of life while preventing symptoms and recovery setbacks. EEG allows for a sensitive measure of cognitive exertion. Clinical 32-lead EEG headsets are not practical for day-to-day concussion rehabilitation management. However, there are now commercially available and affordable portable EEG headsets. Thus, these headsets can potentially be used to continuously monitor cognitive exertion during mental tasks to alert the wearer of overexertion, with the aim of preventing the occurrence of symptoms to speed recovery times. The objective of this study was to test an algorithm for predicting cognitive exertion from EEG data collected from a portable headset. EEG data were acquired from 10 participants (5 males, 5 females). Each participant wore a portable 4 channel EEG headband while completing 10 tasks: rest (eyes closed), rest (eyes open), three levels of the increasing difficulty of logic puzzles, three levels of increasing difficulty in multiplication questions, rest (eyes open), and rest (eyes closed). After each task, the participant was asked to report their perceived level of cognitive exertion using the NASA Task Load Index (TLX). Each participant then completed a second session on a different day. A customized machine learning model was created using data from the first session. The performance of each model was then tested using data from the second session. The mean correlation coefficient between TLX scores and predicted cognitive exertion was 0.75 ± 0.16. The results support the efficacy of the algorithm for predicting cognitive exertion. This demonstrates that the algorithms developed in this study used with portable EEG devices have the potential to aid in the concussion recovery process by monitoring and warning patients of cognitive overexertion. Preventing cognitive overexertion during recovery may reduce the number of symptoms a patient experiences and may help speed the recovery process.

Keywords: cognitive activity, EEG, machine learning, personalized recovery

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Authors: A. Degale Desta, Tamirat Kebamo

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Background: Recent advances in computer vision and pattern recognition have significantly improved activity recognition through video analysis, particularly with the application of Deep Convolutional Neural Networks (CNNs). One-stage detectors now enable efficient video-based recognition by simultaneously predicting object categories and locations. Such advancements are highly relevant in educational settings where CCTV surveillance could automatically monitor academic activities, enhancing security and classroom management. However, current datasets and recognition systems lack the specific focus on campus environments necessary for practical application in these settings.Objective: This study aims to address this gap by developing a dataset and testing an automated activity recognition system specifically tailored for educational campuses. The EthioCAD dataset was created to capture various classroom activities and teacher-student interactions, facilitating reliable recognition of academic activities using deep learning models. Method: EthioCAD, a novel video-based dataset, was created with a design science research approach to encompass teacher-student interactions across three domains and 18 distinct classroom activities. Using the Roboflow AI framework, the data was processed, with 4.224 KB of frames and 33.485 MB of images managed for frame extraction, labeling, and organization. The Ultralytics YOLOv8 model was then implemented within Google Colab to evaluate the dataset’s effectiveness, achieving high mean Average Precision (mAP) scores. Results: The YOLOv8 model demonstrated robust activity recognition within campus-like settings, achieving an mAP50 of 90.2% and an mAP50-95 of 78.6%. These results highlight the potential of EthioCAD, combined with YOLOv8, to provide reliable detection and classification of classroom activities, supporting automated surveillance needs on educational campuses. Discussion: The high performance of YOLOv8 on the EthioCAD dataset suggests that automated activity recognition for surveillance is feasible within educational environments. This system addresses current limitations in campus-specific data and tools, offering a tailored solution for academic monitoring that could enhance the effectiveness of CCTV systems in these settings. Conclusion: The EthioCAD dataset, alongside the YOLOv8 model, provides a promising framework for automated campus activity recognition. This approach lays the groundwork for future advancements in CCTV-based educational surveillance systems, enabling more refined and reliable monitoring of classroom activities.

Keywords: deep CNN, EthioCAD, deep learning, YOLOv8, activity recognition

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Authors: Ajda Osifo, Fatma Elshafie

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Mobile-assisted language learning favors social-constructivist and connectivist theories to learning and adaptive approaches to teaching. It offers many opportunities to differentiated instruction in meaningful ways as it enables learners to become more collaborative, engaged and independent through additional dimensions such as web-based media, virtual learning environments, online publishing to an imagined audience and digitally mediated communication. MALL applications can be a tool for the teacher to personalize and adjust instruction according to the learners’ needs and give continuous feedback to improve learning and performance in the process, which support differentiated instruction practices. This paper explores the utilization of Mobile Assisted Language Learning applications as a supporting tool for effective differentiation in the language classroom. It reports overall experience in terms of implementing MALL to shape and apply differentiated instruction and expand learning options. This session is structured in three main parts: first, a review of literature and effective practice of academically responsive instruction will be discussed. Second, samples of differentiated tasks, activities, projects and learner work will be demonstrated with relevant learning outcomes and learners’ survey results. Finally, project findings and conclusions will be given.

Keywords: academically responsive instruction, differentiation, mobile learning, mobile-assisted language learning

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Authors: Subhajit Das, Nirjhar Dhang

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Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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Authors: Louise Reyntjens

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In response to Islamic-inspired terrorism and the growing trend of foreign fighters, European governments are increasingly relying on the deprivation of citizenship as a security tool. This development fits within a broader securitization of immigration, where the terrorist threat is perceived as emanating from abroad. As a result, immigration law became more and more ‘securitized’. The European migration crisis has reinforced this trend. This research evaluates the deprivation of citizenship from a human rights perspective. For this, the author selected four European countries for a comparative study: Belgium, France, the United Kingdom and Sweden. All these countries face similar social and security issues, vitalizing (the debate on) deprivation of citizenship as a counterterrorism tool. Yet, they adopt a very different approach on this: The United Kingdom positions itself on the repressive side of the spectrum. Sweden on the other hand, also ‘securitized’ its immigration policy after the recent terrorist hit in Stockholm but remains on the tolerant side of the spectrum. Belgium and France are situated in between. This contribution evaluates the deprivation of citizenship in Belgium. Belgian law has provided the possibility to strip someone of their Belgian citizenship since 1919. However, the provision long remained a dead letter. The 2015 Charlie Hebdo attacks in Paris sparked a series of legislative changes, elevating the deprivation measure to a key security tool in Belgian law. Yet, the measure raises profound human rights issues. Firstly, it infringes the right to private and family life. As provided by Article 8 (2) European Court of Human Right (ECHR), this right can be limited if necessary for national security and public safety. Serious questions can however be raised about the necessity for the national security of depriving an individual of its citizenship. Behavior giving rise to this measure will generally be governed by criminal law. From a security perspective, criminal detention will thus already provide in removing the individual from society. Moreover, simply stripping an individual of its citizenship and deporting them constitutes a failure of criminal law’s responsibility to prosecute criminal behavior. Deprivation of citizenship is also discriminatory, because it differentiates, without a legitimate reason, between those liable to deprivation and those who are not. It thereby installs a secondary class of citizens, violating the European Court of Human Right’s principle that no distinction can be tolerated between children on the basis of the status of their parents. If followed by expulsion, deprivation also seriously jeopardizes the right to life and prohibition of torture. This contribution explores the human rights consequences of citizenship deprivation as a security tool in Belgium. It also offers a critical view on its efficacy for protecting national security.

Keywords: Belgium, counterterrorism strategies, deprivation of citizenship, human rights, immigration law

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Authors: Alejandro Rodríguez-Molinero, Carlos Pérez-López, Jorge Hernández-Vara, Àngels Bayes-Rusiñol, Juan Carlos Martínez-Castrillo, David A. Pérez-Martínez

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Background: Monitoring motor symptoms in Parkinson's patients is often a complex and time-consuming task for clinicians, as Hauser's diaries are often poorly completed by patients. Recently, new automatic devices (Parkinson's holter: STAT-ON®) have been developed capable of monitoring patients' motor fluctuations. The MoMoPa-EC clinical trial (NCT04176302) investigates which of the two methods produces better clinical results. In this sub-analysis, the concordance between both methods is analyzed. Methods: In the MoMoPa-EC clinical trial, 164 patients with moderate-severe Parkinson's disease and at least two hours a day of Off will be included. At the time of patient recruitment, all of them completed a seven-day motor fluctuation diary at home (Hauser’s diary) while wearing the Parkinson's holter. In this sub-analysis, 71 patients with complete data for the purpose of this comparison were included. The intraclass correlation coefficient was calculated between the patient diary entries and the Parkinson's holter data in terms of time On, Off, and time with dyskinesias. Results: The intra-class correlation coefficient of both methods was 0.57 (95% CI: 0.3-0.74) for daily time in Off (%), 0.48 (95% CI: 0.14-0.68) for daily time in On (%), and 0.37 (95% CI %: -0.04-0.62) for daily time with dyskinesias (%). Conclusions: Both methods have a moderate agreement with each other. We will have to wait for the results of the MoMoPa-EC project to estimate which of them has the greatest clinical benefits. Acknowledgment: This work is supported by AbbVie S.L.U, the Instituto de Salud Carlos III [DTS17/00195], and the European Fund for Regional Development, 'A way to make Europe'.

Keywords: Parkinson, sensor, motor fluctuations, dyskinesia

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Authors: Pei-Chih Wu, Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Hsien-Chang Wang

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The impact of climate change to health has always been well documented. Amongst them, water-borne infectious diseases, chronic adverse effects or cancer risks due to chemical contamination in flooding or drought events are especially important in river basin. This study therefore utilizes GIS and different models to integrate demographic, land use, disaster prevention, social-economic factors, and human health assessment in the Erren River basin. Therefore, through the collecting of climatic, demographic, health surveillance, water quality and other water monitoring data, potential risks associated with the Erren River Basin are established and to understand human exposure and vulnerability in response to climate extremes. This study assesses the temporal and spatial patterns of melioidosis (2000-2015) and various cancer incidents in Tainan and Kaohsiung cities. The next step is to analyze the spatial association between diseases incidences, climatic factors, land uses, and other demographic factors by using ArcMap and GeoDa. The study results show that amongst all melioidosis cases in Taiwan, 24% cases (115) residence occurred in the Erren River basin. The relationship between the cases and in Tainan and Kaohsiung cities are associated with population density, aging indicator, and residence in Erren River basin. Risks from flooding due to heavy rainfall and fish farms in spatial lag regression are also related. Through liver cancer, the preliminary analysis in temporal and spatial pattern shows an increases pattern in annual incidence without clusters in Erren River basin. Further analysis of potential cancers connected to heavy metal contamination from water pollution in Erren River is established. The final step is to develop an assessment tool for human exposure from water contamination and vulnerability in response to climate extremes for the second year.

Keywords: climate change, health impact, health adaptation, Erren River Basin

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Authors: Kazi Md. Shifun Newaz, S. Miaji, Shahnewaz Hazanat-E-Rabbi

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In this study, the kernel density estimation tool has been used to identify most crash prone locations in a national highway of Bangladesh. Like other developing countries, in Bangladesh road traffic crashes (RTC) have now become a great social alarm and the situation is deteriorating day by day. Today’s black spot identification process is not based on modern technical tools and most of the cases provide wrong output. In this situation, characteristic analysis and black spot identification by spatial analysis would be an effective and low cost approach in ensuring road safety. The methodology of this study incorporates a framework on the basis of spatial-temporal study to identify most RTC occurrence locations. In this study, a very important and economic corridor like Dhaka to Sylhet highway has been chosen to apply the method. This research proposes that KDE method for identification of Hazardous Road Location (HRL) could be used for all other National highways in Bangladesh and also for other developing countries. Some recommendations have been suggested for policy maker to reduce RTC in Dhaka-Sylhet especially in black spots.

Keywords: hazardous road location (HRL), crash, GIS, kernel density

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Authors: Doaa Alhaboby

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Behavior change is a complex process that often requires ongoing support and guidance. Telecoaching programs have emerged as effective tools in facilitating behavior change by providing personalized support remotely. This abstract explores the lessons learned from a randomized controlled trial (RCT) evaluation of a telecoaching program focused on behavior change for Diabetics and discusses strategies for implementing these lessons to overcome the challenge of making physical activity a habit. The telecoaching program involved participants engaging in regular coaching sessions delivered via phone calls. These sessions aimed to address various aspects of behavior change, including goal setting, self-monitoring, problem-solving, and social support. Over the course of the program, participants received personalized guidance tailored to their unique needs and preferences. One of the key lessons learned from the RCT was the importance of engagement, readiness to change and the use of technology. Participants who set specific, measurable, attainable, relevant, and time-bound (SMART) goals were more likely to make sustained progress toward behavior change. Additionally, regular self-monitoring of behavior and progress was found to be instrumental in promoting accountability and motivation. Moving forward, implementing the lessons learned from the RCT can help individuals overcome the hardest part of behavior change: making physical activity a habit. One strategy is to prioritize consistency and establish a regular routine for physical activity. This may involve scheduling workouts at the same time each day or week and treating them as non-negotiable appointments. Additionally, integrating physical activity into daily life routines and taking into consideration the main challenges that can stop the process of integrating physical activity routines into the daily schedule can help make it more habitual. Furthermore, leveraging technology and digital tools can enhance adherence to physical activity goals. Mobile apps, wearable activity trackers, and online fitness communities can provide ongoing support, motivation, and accountability. These tools can also facilitate self-monitoring of behavior and progress, allowing individuals to track their activity levels and adjust their goals as needed. In conclusion, telecoaching programs offer valuable insights into behavior change and provide strategies for overcoming challenges, such as making physical activity a habit. By applying the lessons learned from these programs and incorporating them into daily life, individuals can cultivate sustainable habits that support their long-term health and well-being.

Keywords: lifestyle, behavior change, physical activity, chronic conditions

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Authors: Pankaj Kumar

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Rapid global changes resulted in unfavorable hydrological, ecological, and environmental changes and cumulatively affected natural resources. As a result, the local communities become vulnerable to water stress, poor hygiene, the spread of diseases, food security, etc.. However, the central point for this vulnerability revolves around water resources and the way people interrelate with the hydrological system. Also, most of the efforts to minimize the adverse effect of global changes are centered on the mitigation side. Hence, countries with poor adaptive capacities and poor governance suffer most in case of disasters. However, several transdisciplinary numerical tools are well designed and are capable of answering “what-if questions” through scenario analysis using a system approach. This study has predicted the future water environment in Marikina River in the National Capital Region, Metro Manila of Philippines, using Water Evaluation and Planning (WEAP), an integrated water resource management tool. Obtained results can answer possible adaptation measures along with their associated uncertainties. It also highlighted various challenges for the policy planners to design adaptation countermeasures as well as to track the progress of achieving SDG 6.0.

Keywords: water quality, Philippines, climate change adaptation, hydrological simulation, wastewater management, weap

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Authors: Fadwa Al Bawardi

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In March 2021, the Saudi Arabian Council of Ministers issued a decision to form a committee called the "Higher Committee for Research, Development and Innovation," a committee linked to the Council of Economic and Development Affairs, chaired by the Chairman of the Council of Economic and Development Affairs, and concerned with the development of the research, development and innovation sector in the Kingdom. In order to talk about the dimensions of this wonderful step, let us first try to answer the following questions. Is there a difference between creativity and innovation..? What are the factors of creativity in the individual. Are they mental genetic factors or are they factors that an individual acquires through learning..? The methodology included surveys that have been conducted on more than 500 individuals, males and females, between the ages of 18 till 60. And the answer is. "Creativity" is the creation of a new idea, while "Innovation" is the development of an already existing idea in a new, successful way. They are two sides of the same coin, as the "creative idea" needs to be developed and transformed into an "innovation" in order to achieve either strategic achievements at the level of countries and institutions to enhance organizational intelligence, or achievements at the level of individuals. For example, the beginning of smart phones was just a creative idea from IBM in 1994, but the actual successful innovation for the manufacture, development and marketing of these phones was through Apple later. Nor does creativity have to be hereditary. There are three basic factors for creativity: The first factor is "the presence of a challenge or an obstacle" that the individual faces and seeks thinking to find solutions to overcome, even if thinking requires a long time. The second factor is the "environment surrounding" of the individual, which includes science, training, experience gained, the ability to use techniques, as well as the ability to assess whether the idea is feasible or otherwise. To achieve this factor, the individual must be aware of own skills, strengths, hobbies, and aspects in which one can be creative, and the individual must also be self-confident and courageous enough to suggest those new ideas. The third factor is "Experience and the Ability to Accept Risk and Lack of Initial Success," and then learn from mistakes and try again tirelessly. There are some tools and techniques that help the individual to reach creative and innovative ideas, such as: Mind Maps tool, through which the available information is drawn by writing a short word for each piece of information and arranging all other relevant information through clear lines, which helps in logical thinking and correct vision. There is also a tool called "Flow Charts", which are graphics that show the sequence of data and expected results according to an ordered scenario of events and workflow steps, giving clarity to the ideas, their sequence, and what is expected of them. There are also other great tools such as the Six Hats tool, a useful tool to be applied by a group of people for effective planning and detailed logical thinking, and the Snowball tool. And all of them are tools that greatly help in organizing and arranging mental thoughts, and making the right decisions. It is also easy to learn, apply and use all those tools and techniques to reach creative and innovative solutions. The detailed figures and results of the conducted surveys are available upon request, with charts showing the %s based on gender, age groups, and job categories.

Keywords: innovation, creativity, factors, tools

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Authors: Orhan Akınoğlu, Arif Çömek, Ersin Elmacı, Tuğba Gündoğdu

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The concept map is known to be a powerful tool to organize the ideas and concepts of an individuals’ mind. This tool is a kind of visual map that illustrates the relationships between the concepts of a certain subject. The effect of concept mapping on cognitive and affective qualities is one of the research topics among educational researchers for last decades. We educators want to utilize it both as an instructional tool or an assessment tool in classes. For that reason, this study aimed to determine the effect of concept mapping as a learning strategy in science classes on students’ academic achievement and attitude. The research employed a randomized pre-test post-test control group design. Data collected from 60 sixth grade students participated in the study from a randomly selected primary school in Turkey. Sixth-grade classes of the school were analyzed according to students’ academic achievement, science attitude, gender, mathematics, science courses grades, and their GPAs before the implementation. Two of the classes found to be equivalent (t=0,983, p>0,05) and one of them was defined as experimental and the other one control group randomly. During a 5-weeks period, the experimental group students (N=30) used the paper-based concept mapping method while the control group students (N=30) were taught with the traditional approach according to the science and technology education curriculum for light and sound subject. Both groups were taught by the same teacher who is experienced using concept mapping in science classes. Before the implementation, the teacher explained the theory of the concept maps and showed how to create paper-based concept mapping individually to the experimental group students for two hours. Then for two following hours she asked them to create some concept maps related to their former science subjects and gave them feedback by reviewing their concept maps to be sure that they can create during the implementation. The data were collected by science achievement test, science attitude scale and personal information form. Science achievement test and science attitude scale were implemented as pre-test and post-test while personal information form was implemented just as once. The reliability coefficient of the achievement test was KR20=0,76 and Cronbach’s Alpha of the attitude scale was 0,89. SPSS statistical software was used to analyze the data. According to the results, there was a statistically significant difference between the experimental and control group for academic achievement but not for attitude. The experimental group had significantly greater gains from academic achievement test than the control group (t=0,02, p<0,05). The findings showed that the paper-and-pencil concept mapping can be used as an effective method for students’ academic achievement in science classes. The results have implications for further researches.

Keywords: concept mapping, science education, constructivism, academic achievement, science attitude

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Authors: Sidra Rizwan

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The article focuses on the training needs of secondary school teachers related to the knowledge component of instructional planning and strategies as stated in the National professional standards for teachers in Pakistan. The study aimed to determine the training needs of secondary school teachers on different aspects of knowledge & understanding component of instructional planning and strategies. The target population of the study was the secondary school teachers across Pakistan. For this purpose, a sample of 400 secondary school teachers was selected through multistage sampling from all the four provinces and Federal capital area. Survey method was adopted to assess the training needs by using a self reporting tool. The tool helped to gauge the training needs through indirect inventory questions as well as a ranking list in which the respondents themselves prioritized their training areas. The results showed variation between the direct and indirect reporting of the teachers on the basis of which it was concluded that the secondary school teachers needed awareness about the knowledge component of instructional planning and strategies in order to redefine their actual training needs. The researcher further identified the training needs of secondary school teachers within each province and Islamabad capital territory; including an analysis of variations between strata. As teachers are considered agents of change, their training according to the professional standards should provide a solid base for “rethinking education”.

Keywords: training needs, secondary school teachers, instructional planning & strategies, knowledge & understanding

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Authors: H. Malachova, A. Oulehlova, D. Rezac

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Crisis preparedness training is the best possible strategy for identifying weak points, understanding vulnerability, and finding possible strategies for mitigation of blackout consequences. Training represents an effective tool for developing abilities and skills to cope with crisis situations. This article builds on the results of the research carried out in the field of preparation, realization, process, and impacts of training on subjects of energy sector critical infrastructure as a part of crisis preparedness. The research has revealed that the subjects of energy sector critical infrastructure have not realized training and therefore are not prepared for the restoration of the energy supply and black start after blackout regardless of the fact that most subjects state blackout and subsequent black start as key dangers. Training, together with mutual communication and processed crisis documentation, represent a basis for successful solutions for dealing with emergency situations. This text presents the suggested model of SIMEX simulator as a tool which supports managing crisis situations, containing training environment. Training models, possibilities of constructive simulation making use of non-aggregated as well as aggregated entities and tools of communication channels of individual simulator nodes have been introduced by the article.

Keywords: communication, energetic critical infrastructure, training, simulation

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