Search results for: continuous monitoring tool

Authors: S. M. Ishtiaque, V. K. Yadav, S. D. Joshi, J. K. Chatterjee

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The DIAMETRIC FAULTS system has been developed that captures a bi-directional image of yarn continuously in sequentially manner and provides the detailed classification of faults. A novel mathematical framework developed on the acquired bi-directional images forms the basis of fault classification in four broad categories, namely, Thick1, Thick2, Thin and Normal Yarn. A discretised version of Radon transformation has been used to convert the bi-directional images into one-dimensional signals. Images were divided into training and test sample sets. Karhunen–Loève Transformation (KLT) basis is computed for the signals from the images in training set for each fault class taking top six highest energy eigen vectors. The fault class of the test image is identified by taking the Euclidean distance of its signal from its projection on the KLT basis for each sample realization and fault class in the training set. Euclidean distance applied using various techniques is used for classifying an unknown fault class. An accuracy of about 90% is achieved in detecting the correct fault class using the various techniques. The four broad fault classes were further sub classified in four sub groups based on the user set boundary limits for fault length and fault volume. The fault cross-sectional area and the fault length defines the total volume of fault. A distinct distribution of faults is found in terms of their volume and physical dimensions which can be used for monitoring the yarn faults. It has been shown from the configurational based characterization and classification that the spun yarn faults arising out of mass variation, exhibit distinct characteristics in terms of their contours, sizes and shapes apart from their frequency of occurrences.

Keywords: Euclidean distance, fault classification, KLT, Radon Transform

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Authors: Emanuele Bonamente, Andrea Aquino

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This study presents an innovative design for geothermal heat pumps with the goal of maximizing the system efficiency (COP - Coefficient of Performance), reducing the soil use (e.g. length/depth of geothermal boreholes) and initial investment costs. Based on experimental data obtained from a two-year monitoring of a working prototype implemented for a commercial building in the city of Perugia, Italy, an upgrade of the system is proposed and the performance is evaluated via CFD simulations. The prototype was designed to include a thermal heat storage (i.e. water), positioned between the boreholes and the heat pump, acting as a flywheel. Results from the monitoring campaign show that the system is still capable of providing the required heating and cooling energy with a reduced geothermal installation (approx. 30% of the standard length). In this paper, an optimization of the system is proposed, re-designing the heat storage to include phase change materials (PCMs). Two stacks of PCMs, characterized by melting temperatures equal to those needed to maximize the system COP for heating and cooling, are disposed within the storage. During the working cycle, the latent heat of the PCMs is used to heat (cool) the water used by the heat pump while the boreholes independently cool (heat) the storage. The new storage is approximately 10 times smaller and can be easily placed close to the heat pump in the technical room. First, a validation of the CFD simulation of the storage is performed against experimental data. The simulation is then used to test possible alternatives of the original design and it is finally exploited to evaluate the PCM-storage performance for two different configurations (i.e. single- and double-loop systems).

Keywords: geothermal heat pump, phase change materials (PCM), energy storage, renewable energies

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Authors: Luciana Marrone

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Natural dyes are a great resource for today's artists and designers providing endless possibilities for design and sustainability. This research and development project focuses on the idea of making these dyeing or painting methodologies reach the widest possible range of students. The main objective is to inform and train, free of charge, teachers and students from different academic institutions, at different levels, kindergarten, primary, secondary, tertiary and university. In this research and dissemination project, in the first instance, institutions from Argentina, Chile, Uruguay, Mexico, Spain, Italy, Colombia, Paraguay, Venezuela, Brazil and Australia joined the project, reaching the grassroots of education from the very beginning. Natural dyes will become part of everyday life for more people, achieving their own colors for art, textiles or any other application. The knowledge of the techniques and resources of the student a fundamental tool, sustainable and opens endless possibilities even in places or homes with few economic resources, thus achieving that natural dyes are not only part of the world of designers but also that they are incorporated from the basics and can thus become a resource applicable in different areas even in places with few economic or development possibilities.

Keywords: art, education, natural dyes, sustainability, textile design.

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Authors: Subodh Kumar, Sanjeev Kumar Sharma, Gaurav Kaushik, Pramod Avti, Phulen Sarma, Bikash Medhi, Krishan Lal Khanduja

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Background: It is well known that cigarette smoke is one of the causative factors in various lung diseases especially cancer. Carcinogens and oxidant molecules present in cigarette smoke not only damage the cellular constituents (lipids, proteins, DNA) but may also regulate the molecular pathways involved in inflammation and cancer. Continuous oxidative stress caused by the constituents of cigarette smoke leads to higher PhospholipaseA₂ (PLA₂) activity, resulting in elevated levels of secondary metabolites whose role is well defined in cancer. To reduce the burden of chronic inflammation as well as oxidative stress, and higher levels of secondary metabolites, we checked the curative potential of PLA₂ inhibitor Bromoenol Lactone (BEL) during continuous exposure of cigarette smoke condensate (CSC). Aim: To check the therapeutic potential of Bromoenol Lactone (BEL), an inhibitor of PhospholipaseA₂s, in pathways of CSC-induced changes in type I and type II alveolar epithelial cells. Methods: Effect of BEL on CSC-induced PLA2 activity were checked using colorimetric assay, cellular toxicity using cell viability assay, membrane integrity using fluorescein di-acetate (FDA) uptake assay, reactive oxygen species (ROS) levels and apoptosis markers through flow cytometry, and cellular regulation using MAPKinases levels, in lung epithelium. Results: BEL significantly mimicked CSC-induced PLA₂ activity, ROS levels, apoptosis, and kinases level whereas improved cellular viability and membrane integrity. Conclusions: Current observations revealed that BEL may be a potential therapeutic agent during Cigarette smoke-induced anomalies in lung epithelium.

Keywords: cigarette smoke condensate, phospholipase A₂, oxidative stress, alveolar epithelium, bromoenol lactone

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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

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Authors: Weic-Ting Chen, Jo-Ming Tseng

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Ammonium nitrate (AN) has caused many accidents in the world, which have caused a large number of people’s life and serious economic losses. In this study, the safety of the AN production process was discussed deeply, and the influence of incompatible substances was estimated according to the change of their heat value by mixing them with incompatible substances by thermal analysis techniques, and their safety parameters were calculated according to their kinetic parameters. In this study, differential scanning calorimeters (DSC) were applied for the temperature rise test and adiabatic thermal analysis in combination with the Advanced Reactive System Screening Tool (ARSST). The research results could contribute to the safety of the ammonium nitrate production process. Manufacturers can better understand the possibility of chemical heat release and the operating conditions that will cause a chemical reaction to be out of control when storing or adding new substances, so safety parameters were researched for these complex reactions. The results of this study will benefit the process of AN and the relevant staff, which also have safety protection in the working environment.

Keywords: ammonium nitrate, incompatible substances, differential scanning calorimeters, advanced reactive system screening tool, safety parameters

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Authors: Thummalapalli CSM Gupta, Banti Sidhiwala

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Mineral oils of naphthenic and paraffinic type have been traditionally been used as insulating liquids in the transformer applications to protect the solid insulation from moisture and ensures effective heat transfer/cooling. The performance of these type of oils have been proven in the field over many decades and the condition monitoring and diagnosis of transformer performance have been successfully monitored through oil properties and dissolved gas analysis methods successfully. Different type of gases representing various types of faults due to components or operating conditions effectively. While large amount of data base has been generated in the industry on dissolved gas analysis for mineral oil based transformer oils and various models for predicting the fault and analysis, oil specifications and standards have also been modified to include stray gassing limits which cover the low temperature faults and becomes an effective preventative maintenance tool that can benefit greatly to know the reasons for the breakdown of electrical insulating materials and related components. Natural esters have seen a rise in popularity in recent years due to their "green" credentials. Some of its benefits include biodegradability, a higher fire point, improvement in load capability of transformer and improved solid insulation life than mineral oils. However, the Stray gases evolution like hydrogen and hydrocarbons like methane (CH4) and ethane (C2H6) show very high values which are much higher than the limits of mineral oil standards. Though the standards for these type esters are yet to be evolved, the higher values of hydrocarbon gases that are available in the market is of concern which might be interpreted as a fault in transformer operation. The current paper focuses on developing a natural ester based transformer oil which shows very levels of stray gassing by standard test methods show much lower values compared to the products available currently and experimental results on various test conditions and the underlying mechanism explained.

Keywords: biodegadability, fire point, dissolved gassing analysis, stray gassing

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Authors: Marta Fonseca, Pedro Marvão, Beatriz Oliveira, Bruno Heleno, Pedro Carreiro-Martins, Nuno Neuparth, António Rendas

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Background: Concept maps (CMs) visually represent hierarchical connections among related ideas. They foster logical organization and clarify idea relationships, potentially aiding medical students in critical thinking (to think clearly and rationally about what to do or what to believe). However, there are inconsistent claims about the use of CMs in undergraduate medical education. Our three research questions are: 1) What studies have been published on concept mapping in undergraduate medical education? 2) What was the impact of CMs on students’ critical thinking? 3) How and why have these interventions had an educational impact? Methods: Eight databases were systematically searched (plus a manual and an additional search were conducted). After eliminating duplicate entries, titles, and abstracts, and full-texts were independently screened by two authors. Data extraction and quality assessment of the studies were independently performed by two authors. Qualitative and quantitative data were integrated using mixed-methods. The results were reported using the structured approach to the reporting in healthcare education of evidence synthesis statement and BEME guidance. Results: Thirty-nine studies were included from 26 journals (19 quantitative, 8 qualitative and 12 mixed-methods studies). CMs were considered as a tool to promote critical thinking, both in the perception of students and tutors, as well as in assessing students’ knowledge and/or skills. In addition to their role as facilitators of knowledge integration and critical thinking, CMs were considered both teaching and learning methods. Conclusions: CMs are teaching and learning tools which seem to help medical students develop critical thinking. This is due to the flexibility of the tool as a facilitator of knowledge integration, as a learning and teaching method. The wide range of contexts, purposes, and variations in how CMs and instruments to assess critical thinking are used increase our confidence that the positive effects are consistent.

Keywords: concept map, medical education, undergraduate, critical thinking, meaningful learning

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Authors: Ahmad B. Habieb, Gabriele Milani, Tavio Tavio, Federico Milani

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Housings in developing countries have often inadequate seismic protection, particularly for masonry. People choose this type of structure since the cost and application are relatively cheap. Seismic protection of masonry remains an interesting issue among researchers. In this study, we develop a low-cost seismic isolation system for masonry using fiber reinforced elastomeric isolators. The elastomer proposed consists of few layers of rubber pads and fiber lamina, making it lower in cost comparing to the conventional isolators. We present a finite element (FE) analysis to predict the behavior of the low cost rubber isolators undergoing moderate deformations. The FE model of the elastomer involves a hyperelastic material property for the rubber pad. We adopt a Yeoh hyperelasticity model and estimate its coefficients through the available experimental data. Having the shear behavior of the elastomers, we apply that isolation system onto small masonry housing. To attach the isolators on the building, we model the shear behavior of the isolation system by means of a damped nonlinear spring model. By this attempt, the FE analysis becomes computationally inexpensive. Several ground motion data are applied to observe its sensitivity. Roof acceleration and tensile damage of walls become the parameters to evaluate the performance of the isolators. In this study, a concrete damage plasticity model is used to model masonry in the nonlinear range. This tool is available in the standard package of Abaqus FE software. Finally, the results show that the low-cost isolators proposed are capable of reducing roof acceleration and damage level of masonry housing. Through this study, we are also capable of monitoring the shear deformation of isolators during seismic motion. It is useful to determine whether the isolator is applicable. According to the results, the deformations of isolators on the benchmark one story building are relatively small.

Keywords: masonry, low cost elastomeric isolator, finite element analysis, hyperelasticity, damped non-linear spring, concrete damage plasticity

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Authors: Gherbi Khadidja

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In the Mediterranean region, water resources are limited and very unevenly distributed in space and time. The main objective of this project is the development of a wireless network for the management of water resources in northern Algeria, the Mitidja plain, which helps farmers to irrigate in the most optimized way and solve the problem of water shortage in the region. Therefore, we will develop an aid tool that can modernize and replace some traditional techniques, according to the real needs of the crops and according to the soil conditions as well as the climatic conditions (soil moisture, precipitation, characteristics of the unsaturated zone), These data are collected in real-time by sensors and analyzed by an algorithm and displayed on a mobile application and the website. The results are essential information and alerts with recommendations for action to farmers to ensure the sustainability of the agricultural sector under water shortage conditions. In the first part: We want to set up a wireless sensor network, for precise management of water resources, by presenting another type of equipment that allows us to measure the water content of the soil, such as the Watermark probe connected to the sensor via the acquisition card and an Arduino Uno, which allows collecting the captured data and then program them transmitted via a GSM module that will send these data to a web site and store them in a database for a later study. In a second part: We want to display the results on a website or a mobile application using the database to remotely manage our smart irrigation system, which allows the farmer to use this technology and offers the possibility to the growers to access remotely via wireless communication to see the field conditions and the irrigation operation, at home or at the office. The tool to be developed will be based on satellite imagery as regards land use and soil moisture. These tools will make it possible to follow the evolution of the needs of the cultures in time, but also to time, and also to predict the impact on water resources. According to the references consulted, if such a tool is used, it can reduce irrigation volumes by up to up to 40%, which represents more than 100 million m3 of savings per year for the Mitidja. This volume is equivalent to a medium-size dam.

Keywords: optimal irrigation, soil moisture, smart irrigation, water management

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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: Sinisa J. Vukicevic

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Edmonton is currently one of the youngest North American cities and has achieved significant growth over the past 40 years. Strong urban shift requires a new approach to how the city is envisioned, planned, and built. This approach is evidence-based scenario development, and an urban growth model was a key support tool in framing Edmonton development strategies, developing urban policies, and assessing policy implications. The urban growth model has been developed using the Metronamica software platform. The Metronamica land use model evaluated the dynamic of land use change under the influence of key development drivers (population and employment), zoning, land suitability, and land and activity accessibility. The model was designed following the Big City Moves ideas: become greener as we grow, develop a rebuildable city, ignite a community of communities, foster a healing city, and create a city of convergence. The Big City Moves were converted to three development scenarios: ‘Strong Central City’, ‘Node City’, and ‘Corridor City’. Each scenario has a narrative story that expressed scenario’s high level goal, scenario’s approach to residential and commercial activities, to transportation vision, and employment and environmental principles. Land use demand was calculated for each scenario according to specific density targets. Spatial policies were analyzed according to their level of importance within the policy set definition for the specific scenario, but also through the policy measures. The model was calibrated on the way to reproduce known historical land use pattern. For the calibration, we used 2006 and 2011 land use data. The validation is done independently, which means we used the data we did not use for the calibration. The model was validated with 2016 data. In general, the modeling process contain three main phases: ‘from qualitative storyline to quantitative modelling’, ‘model development and model run’, and ‘from quantitative modelling to qualitative storyline’. The model also incorporates five spatial indicators: distance from residential to work, distance from residential to recreation, distance to river valley, urban expansion and habitat fragmentation. The major finding of this research could be looked at from two perspectives: the planning perspective and technology perspective. The planning perspective evaluates the model as a tool for scenario development. Using the model, we explored the land use dynamic that is influenced by a different set of policies. The model enables a direct comparison between the three scenarios. We explored the similarities and differences of scenarios and their quantitative indicators: land use change, population change (and spatial allocation), job allocation, density (population, employment, and dwelling unit), habitat connectivity, proximity to objects of interest, etc. From the technology perspective, the model showed one very important characteristic: the model flexibility. The direction for policy testing changed many times during the consultation process and model flexibility in applying all these changes was highly appreciated. The model satisfied our needs as scenario development and evaluation tool, but also as a communication tool during the consultation process.

Keywords: urban growth model, scenario development, spatial indicators, Metronamica

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Authors: Xie Xiaobin, Zhang Yan, Shi Yipeng, Sun Wenying, Chen Shuang, Cai Zhipeng, Zhang Hong, Zhang Lixia, Xie Like

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Objective: The objective of this research is to compare the efficacy of the late in-situ surgical revision augmented with continuous infusion and needle revision on failed trabeculectomy blebs. Methods From December 2018 to December 2021, a prospective randomized controlled trial was performed on 44 glaucoma patients with failed bleb ≥ 6months with medically uncontrolled in Eye Hospital, China Academy of Chinese Medical Sciences. They were randomly divided into two groups. 22 eyes of 22 patients underwent the late in-situ surgical revision with continuous anterior chamber infusion in the study group, and 22 of 22 patients were treated with needle revision in the control group. Main outcome measures include preoperative and postoperative intraocular pressure (IOP), the number of anti-glaucoma medicines, the operation success rate, and the postoperative complications. Results The postoperative IOP values decreased significantly from the baseline in both groups (both P<0.05). IOP was significantly lower in the study group than in the control group at one week, 1, and 3 months postoperatively (all P<0.05). IOP reductions in the study group were substantially more prominent than in the control group at all postoperative time points (all P<0.05). The complete success rate in the study group was significantly higher than in the control group (71.4% vs. 33.3%, P<0.05), while the complete failure rate was significantly lower in the study group (0% vs. 28.5%, P<0.05). According to Cox’s proportional hazards regression analysis, high IOP at baseline was independently associated with increased risks of complete failure (adjusted hazard ratio=1.141, 95% confidence interval=1.021-1.276, P<0.05). There was no significant difference in the incidence of postoperative complications between the two groups (P>0.05). Conclusion: Both in-situ surgical and needle revision have acceptable success rates and safety for the late failed trabeculectomy blebs, while the former is likely to have a higher level of efficacy over the latter. Needle revision may be insufficient for eyes with low target IOP.

Keywords: glaucoma, trabeculectomy blebs, in-situ surgical revision, needle revision

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Authors: Anubha Kaushik, Raman Preet

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Distillery wastewater in the form of spent wash is a complex and strong industrial effluent, with high load of organic pollutants that may deplete dissolved oxygen on being discharged into aquatic systems and contaminate groundwater by leaching of pollutants, while untreated spent wash disposed on land acidifies the soil. Stringent legislative measures have therefore been framed in different countries for discharge standards of distillery effluent. Utilising the organic pollutants present in various types of wastes as food by mixed microbial populations is emerging as an eco-friendly approach in the recent years, in which complex organic matter is converted into simpler forms, and simultaneously useful gases are produced as renewable and clean energy sources. In the present study, wastewater from a rice bran based distillery has been used as the substrate in a dark fermenter, and native microbial consortium from the digester sludge has been used as the inoculum to treat the wastewater and produce hydrogen. After optimising the operational conditions in batch reactors, sequential batch mode and continuous flow stirred tank reactors were used to study the best operational conditions for enhanced and sustained hydrogen production and removal of pollutants. Since the rate of hydrogen production by the microbial consortium during dark fermentation is influenced by concentration of organic matter, pH and temperature, these operational conditions were optimised in batch mode studies. Maximum hydrogen production rate (347.87ml/L/d) was attained in 32h dark fermentation while a good proportion of COD also got removed from the wastewater. Slightly acidic initial pH seemed to favor biohydrogen production. In continuous stirred tank reactor, high H₂ production from distillery wastewater was obtained from a relatively shorter substrate retention time (SRT) of 48h and a moderate organic loading rate (OLR) of 172 g/l/d COD.

Keywords: distillery wastewater, hydrogen, microbial consortium, organic pollution, sludge

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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: 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: 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: J. Fox, J. Randhawa, M. Chan, L. Campbell, A. Weakely, D. J. Harvey, S. Tomaszewski Farias

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Early identification of individuals at risk for conversion to dementia provides an opportunity for preventative treatment. Many older adults (30-60%) report specific subjective cognitive decline (SCD); however, previous research is inconsistent in terms of what types of complaints predict future cognitive decline. The purpose of this study is to identify which specific complaints from the Everyday Cognition Scales (ECog) scales, a measure of self-reported concerns for everyday abilities across six cognitive domains, are associated with: 1) conversion from a clinical diagnosis of normal to either MCI or dementia (categorical variable) and 2) progressive cognitive decline in memory and executive function (continuous variables). 415 cognitively normal older adults were monitored annually for an average of 5 years. Cox proportional hazards models were used to assess associations between self-reported ECog items and progression to impairment (MCI or dementia). A total of 114 individuals progressed to impairment; the mean time to progression was 4.9 years (SD=3.4 years, range=0.8-13.8). Follow-up models were run controlling for depression. A subset of individuals (n=352) underwent repeat cognitive assessments for an average of 5.3 years. For those individuals, mixed effects models with random intercepts and slopes were used to assess associations between ECog items and change in neuropsychological measures of episodic memory or executive function. Prior to controlling for depression, subjective concerns on five of the eight Everyday Memory items, three of the nine Everyday Language items, one of the seven Everyday Visuospatial items, two of the five Everyday Planning items, and one of the six Everyday Organization items were associated with subsequent diagnostic conversion (HR=1.25 to 1.59, p=0.003 to 0.03). However, after controlling for depression, only two specific complaints of remembering appointments, meetings, and engagements and understanding spoken directions and instructions were associated with subsequent diagnostic conversion. Episodic memory in individuals reporting no concern on ECog items did not significantly change over time (p>0.4). More complaints on seven of the eight Everyday Memory items, three of the nine Everyday Language items, and three of the seven Everyday Visuospatial items were associated with a decline in episodic memory (Interaction estimate=-0.055 to 0.001, p=0.003 to 0.04). Executive function in those reporting no concern on ECog items declined slightly (p <0.001 to 0.06). More complaints on three of the eight Everyday Memory items and three of the nine Everyday Language items were associated with a decline in executive function (Interaction estimate=-0.021 to -0.012, p=0.002 to 0.04). These findings suggest that specific complaints across several cognitive domains are associated with diagnostic conversion. Specific complaints in the domains of Everyday Memory and Language are associated with a decline in both episodic memory and executive function. Increased monitoring and treatment of individuals with these specific SCD may be warranted.

Keywords: alzheimer’s disease, dementia, memory complaints, mild cognitive impairment, risk factors, subjective cognitive decline

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Authors: Yudo Prasetyo, Hana Sugiastu Firdaus, Diyanah Diyanah

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The phenomenon of the lack of clean water supply in several big cities in Indonesia is a major problem in the development of urban areas. Moreover, in the city of Semarang, the population density and growth of physical development is very high. Continuous and large amounts of underground water (aquifer) exposure can result in a drastically aquifer supply declining in year by year. Especially, the intensity of aquifer use in the fulfilment of household needs and industrial activities. This is worsening by the land subsidence phenomenon in some areas in the Semarang city. Therefore, special research is needed to know the spatial correlation of the impact of decreasing aquifer capacity on the land subsidence phenomenon. This is necessary to give approve that the occurrence of land subsidence can be caused by loss of balance of pressure on below the land surface. One method to observe the correlation pattern between the two phenomena is the application of remote sensing technology based on radar and optical satellites. Implementation of Differential Interferometric Synthetic Aperture Radar (DINSAR) or Small Baseline Area Subset (SBAS) method in SENTINEL-1A satellite image acquisition in 2014-2017 period will give a proper pattern of land subsidence. These results will be spatially correlated with the aquifer-declining pattern in the same time period. Utilization of survey results to 8 monitoring wells with depth in above 100 m to observe the multi-temporal pattern of aquifer change capacity. In addition, the pattern of aquifer capacity will be validated with 2 underground water cavity maps from observation of ministries of energy and natural resources (ESDM) in Semarang city. Spatial correlation studies will be conducted on the pattern of land subsidence and aquifer capacity using overlapping and statistical methods. The results of this correlation will show how big the correlation of decrease in underground water capacity in influencing the distribution and intensity of land subsidence in Semarang city. In addition, the results of this study will also be analyzed based on geological aspects related to hydrogeological parameters, soil types, aquifer species and geological structures. The results of this study will be a correlation map of the aquifer capacity on the decrease in the face of the land in the city of Semarang within the period 2014-2017. So hopefully the results can help the authorities in spatial planning and the city of Semarang in the future.

Keywords: aquifer, differential interferometric synthetic aperture radar (DINSAR), land subsidence, small baseline area subset (SBAS)

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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: 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: 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: Lun Lou, Jintu Fan

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While personal protective equipment (PPE) prevents the healthcare personnel from exposing to harmful surroundings, it creates a barrier to the dissipation of body heat and perspiration, leading to severe heat stress during prolonged exposure, especially in hot environments. It has been found that most of the existed personal cooling strategies have limitations in achieving effective cooling performance with long duration and lightweight. This work aimed to develop a lightweight (<1.0 kg) and less expensive wearable air cooling and dehumidifying system (WCDS) that can be applied underneath the protective clothing and provide 50W mean cooling power for more than 5 hours at 35°C environmental temperature without compromising the protection of PPE. For the WCDS, blowers will be used to activate an internal air circulation inside the clothing microclimate, which doesn't interfere with the protection of PPE. An air cooling and dehumidifying chamber (ACMR) with a specific design will be developed to reduce the air temperature and humidity inside the protective clothing. Then the cooled and dried air will be supplied to upper chest and back areas through a branching tubing system for personal cooling. A detachable ice cooling unit will be applied from the outside of the PPE to extract heat from the clothing microclimate. This combination allows for convenient replacement of the cooling unit to refresh the cooling effect, which can realize a continuous cooling function without taking off the PPE or adding too much weight. A preliminary thermal manikin test showed that the WCDS was able to reduce the microclimate temperature inside the PPE averagely by about 8°C for 60 minutes when the environmental temperature was 28.0 °C and 33.5 °C, respectively. Replacing the ice cooling unit every hour can maintain this cooling effect, while the longest operation duration is determined by the battery of the blowers, which can last for about 6 hours. This unique design is especially helpful for the PPE users, such as health care workers in infectious and hot environments when continuous cooling and dehumidifying are needed, but the change of protective clothing may increase the risk of infection. The new WCDS will not only improve the thermal comfort of PPE users but can also extend their safe working duration.

Keywords: personal thermal management, heat stress, ppe, health care workers, wearable device

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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: 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: 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: 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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