Search results for: time series data mining

Authors: Shyam Sunder Gupta

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GOD is the infinite source of knowledge and from time to time, as per the need of mankind, keeps revealing a portion of HIS knowledge as” Words” through chosen messengers. In the course of time, ” Words” get converted into scripture. This process of conversion happens after a long gap of time and with the involvement of a large number of persons; and unintentionally scientific and other types of errors get into scriptures; otherwise scriptures are in reality, truly scientific. Description of Chronology of life in the womb (Fetal Development), Five types of rotations of celestial bodies, Speed of the Sun, Rotation of Universe, Multiple verses, Spherical shape of the earth, Measurement of time, Classification of species by nature of birth, Evolution process of non-living matter and living species, etc., most convincing prove that scriptures are truly scientific. In fact, there are many facts for which, till date, science has not found answers, but are available in scriptures; like source of Singularity from which the Big Bang took place and the Universe was created, the Infinite number of Universes, the most fundamental particle, Param-anu( God particle), fundamental of measurement of time and many more.

Keywords: Big Bang, God Particle, Scientific, Scriptures, Singularity, Universe

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Authors: R. Burahee, B. Chassinat, T. de Laclos, A. Dépée, A. Sastim

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The purpose of this paper is to propose a solution to detect, predict and reconstitute rain drops in real time – during the night – using an embedded material with an infrared camera. To prevent the system from needing too high hardware resources, simple models are considered in a powerful image treatment algorithm reducing considerably calculation time in OpenCV software. Using a smart model – drops will be matched thanks to a process running through two consecutive pictures for implementing a sophisticated tracking system. With this system drops computed trajectory gives information for predicting their future location. Thanks to this technique, treatment part can be reduced. The hardware system composed by a Raspberry Pi is optimized to host efficiently this code for real time execution.

Keywords: reconstitution, prediction, detection, rain drop, real time, raspberry, infrared

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Authors: Ayala Amir

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The paper presents interdisciplinary research which draws on the literary study and the cultural study of photography to explore a literary genre defined by nostalgia – the photographed book for children. This genre, which was popular in the second half of the 20th century, presents the romantic, nostalgic image of childhood created in the visual arts in the 18th century (as suggested by Ann Higonnet). At the same time, it capitalizes on the nostalgia inherent in the event of photography as formulated by Jennifer Green-Lewis: photography frames a moment in the present while transforming it into a past longed for in the future. Unlike Freudian melancholy, nostalgia is an effect that enables representation by acknowledging the loss and containing it in the very experience of the object. The representation and preservation of the lost object (nature, childhood, innocence) are in the center of the genre of children's photography books – a modern version of ancient pastoral. In it, the unique synergia of word and image results in a nostalgic image of childhood in an era already conquered by modernization. The nostalgic effect works both in the representation of space – an Edenic image of nature already shadowed by its demise, and of time – an image of childhood imbued by what Gill Bartholnyes calls the "looking backward aesthetics" – under the sign of loss. Little critical attention has been devoted to this genre with the exception of the work of Bettina Kümmerling-Meibauer, who noted the nostalgic effect of the well-known series of photography books by Astrid Lindgren and Anna Riwkin-Brick. This research aims to elaborate Kümmerling-Meibauer's approach using the theories of the study of photography, word-image studies, as well as current studies of childhood. The theoretical perspectives are implemented in the case study of photography books created in one of the most innovative social structures in our time – the Israeli Kibbutz. This communal way of life designed a society where children will experience their childhood in a parentless rural environment that will save them from the fate of the Oedipal fall. It is suggested that in documenting these children in a fictional format, photographers and writers, images and words cooperated in creating nostalgic works situated on the border between nature and culture, imagination and reality, utopia and its realization in history.

Keywords: nostalgia, photography , childhood, children's books, kibutz

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Authors: V. Reyes, P. Ferreira

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In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

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Authors: T. P. Oladele, C. A. Snyders, S. M. Bradshaw, G. Akdogan

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The effect of temperature, contact time and agitation during pre-treatment was investigated on the elution of gold from granular activated carbon at fixed caustic-cyanide concentration and elution conditions. It was shown that there are interactions between parameters during pre-treatment. At 80oC, recovery is independent of the contact time while the maximum recovery is obtained in the absence of agitation (0rpm). Increase in agitation speed from 0 rev/min to 1200 rev/min showed a decrease in recovery of approximately 20 percent at 80°C. Recovery with increased time from 15 minutes to 45 minutes is only pronounced at 25°C with approximately 4 percent increase at all agitation speeds. The results from elution recovery are aimed to give insight into the mechanisms of pre-treatment under the combinations of the chosen parameters.

Keywords: gold, temperature, contact time, agitation speed, recovery

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Authors: Jesús Antonio Puente Fernández, Luis Javier Garcia Villalba

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New trends on streaming videos such as series or films require a high demand of network resources. This fact results in a huge problem within traditional IP networks due to the rigidity of its architecture. In this way, Software Defined Networks (SDN) is a new concept of network architecture that intends to be more flexible and it simplifies the management in networks with respect to the existing ones. These aspects are possible due to the separation of control plane (controller) and data plane (switches). Taking the advantage of this separated control, it is easy to deploy a monitoring tool independent of device vendors since the existing ones are dependent on the installation of specialized and expensive hardware. In this paper, we propose a framework that optimizes the traffic monitoring in SDN networks that decreases the number of monitoring queries to improve the network traffic and also reduces the overload. The performed experiments (with and without the optimization) using a video streaming delivery between two hosts demonstrate the feasibility of our monitoring proposal.

Keywords: optimization, monitoring, software defined networking, statistics, query

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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Authors: Md. Reduanul Haque

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In recent time, more and more refugees are emerging in the international arena than the times ever that has come into the notice of world scholars. The prevailing customary solutions such as voluntary repatriation, local integration, and resettlement of refugee problem have been reflected unsustainable one for the lack of regional cooperation. In the international arena, the protraction of refugee problems is seen, and refugees are suffering due to the outrageous process of customary refugee solutions. If the regional cooperation can be developed, then the suffering of the refugees can be mitigated by the contribution of neighboring country and international and regional organizations. Data collected from the various secondary sources have been used throughout the research. It has been discussing in the refugee academia for a long time to develop regional cooperation mechanisms to ensure the sustainability of this solution and to make the environment of the country of origin for suitable voluntary repatriation as well as a durable solution. It is mainly qualitative research based on primary and secondary data will be studied on library-based project. Data collected by such methodology on this study indicates to make a bridge between the gaps of the cooperation mechanism and to make a more regional approach to share the burden and to strengthen the customary refugee solution. Hence, the importance of questing for a regional mechanism is to ensure the responsible countries to be more responsible towards refugees, their human rights, and durable solution under the mandate of the UNHCR. To implement effectively all the customary durable solutions, country to country or regional organization to organization based regional cooperation can be developed where the countries and regional organizations will work together to draw a sustainable solution to this problem in international context.

Keywords: refugee, regional cooperation, sustainable implementation, customary solutions, international arena

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Authors: Ergun Sakalar, Kubra Bilgic

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In the last decades, real-time PCR has become a reliable tool preferred to use in many laboratories for pathogen detection. This technique allows for monitoring target amplification via fluorescent molecules besides admit of quantitative analysis by enabling of convert outcomes of thermal cycling to digital data. Sensitivity and traceability of real-time PCR are based on measuring of fluorescence that appears only when fluorescent reporter dye bound to specific target DNA.The fluorescent reporter systems developed for this purpose are divided into two groups. The first group consists of intercalator fluorescence dyes such as SYBR Green, EvaGreen which binds to double-stranded DNA. On the other hand, the second group includes fluorophore-labeled oligonucleotide probes that are separated into three subgroups due to differences in mechanism of action; initial primer-probes such as Cyclicons, Angler®, Amplifluor®, LUX™, Scorpions, and the second one hydrolysis probes like TaqMan, Snake assay, finally hybridization probes, for instance, Molecular Beacons, Hybprobe/FRET, HyBeacon™, MGB-Eclipse, ResonSense®, Yin-Yang, MGB-Pleiades. In addition nucleic acid analogues, an increase of probe affinity to target site is also employed with fluorescence-labeled probes. Consequently, abundant real-time PCR detection chemistries are chosen by researcher according to the field of application, mechanism of action, advantages, and proper structures of primer/probes.

Keywords: fluorescent dye, food safety, molecular probes, nucleic acid analogues

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Authors: A. Bolaji Adesoye, Alimi Olorunfemi

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This paper examines the impact of small and medium-scale enterprises (SMEs) credit financing and financial market development and their shocks on the output growth of Nigeria. The study estimated a VAR model for Nigeria using 1970-2013 annual data series. Unit root tests and cointegration are carried out. The study also explores IRFs and FEVDs in a system that includes output, commercial bank loan to SMEs, domestic credit to private sector by banks, money supply, lending rate and investment. Findings suggest that shocks in commercial bank credit to SMEs has a major impact on the output changes of Nigeria. Money supply shocks also have a sizeable impact on output growth variations amidst other financial instruments. Lastly, neutrality of investment does not hold in Nigeria as it also has impact on output fluctuations.

Keywords: SMEs financing, financial development, investment, output, Nigeria

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Authors: M. Cizmesija, N. Erjavec, V. Bahovec

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While the European Union (EU) harmonized methodology is a benchmark of worldwide used business survey (BS) methodology, the choice of variables that are components of the confidence indicators, as the leading indicators, is not strictly determined and unique. Therefore, the aim of this paper is to investigate and to quantify the relationship between all business survey variables in manufacturing industry and industrial production as a reference macroeconomic series in Croatia. The assumption is that there are variables in the business survey, that are not components of Industrial Confidence Indicator (ICI) and which can accurately (and sometimes better then ICI) predict changes in Croatian industrial production. Empirical analyses are conducted using quarterly data of BS variables in manufacturing industry and Croatian industrial production over the period from the first quarter 2005 to the first quarter 2013. Research results confirmed the assumption: three BS variables which is not components of ICI (competitive position, demand and liquidity) are the best leading indicator then ICI, in forecasting changes in Croatian industrial production instantaneously, with one, two or three quarter ahead.

Keywords: balance, business survey, confidence indicators, industrial production, forecasting

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Authors: Rafia Hassan, Ali Rizwan, Sadaf Farhan, Bushra Sabir

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The purpose of this study is to compare the conventional crop monitoring system with the satellite based crop monitoring system in Pakistan. This study is conducted for SUPARCO (Space and Upper Atmosphere Research Commission). The study focused on the wheat crop, as it is the main cash crop of Pakistan and province of Punjab. This study will answer the following: Which system is better in terms of cost, time and man power? The man power calculated for Punjab CRS is: 1,418 personnel and for SUPARCO: 26 personnel. The total cost calculated for SUPARCO is almost 13.35 million and CRS is 47.705 million. The man hours calculated for CRS (Crop Reporting Service) are 1,543,200 hrs (136 days) and man hours for SUPARCO are 8, 320hrs (40 days). It means that SUPARCO workers finish their work 96 days earlier than CRS workers. The results show that the satellite based crop monitoring system is efficient in terms of manpower, cost and time as compared to the conventional system, and also generates early crop forecasts and estimations. The research instruments used included: Interviews, physical visits, group discussions, questionnaires, study of reports and work flows. A total of 93 employees were selected using Yamane’s formula for data collection, which is done with the help questionnaires and interviews. Comparative graphing is used for the analysis of data to formulate the results of the research. The research findings also demonstrate that although conventional methods have a strong impact still in Pakistan (for crop monitoring) but it is the time to bring a change through technology, so that our agriculture will also be developed along modern lines.

Keywords: area frame, crop reporting service, CRS, sample frame, SRS/GIS, satellite remote sensing/ geographic information system

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Authors: Xuemei Jiang, Kunfu Zhu, Shouyang Wang

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In this paper, we selected China as a case and employ a time-series of unique input-output tables distinguishing firm ownership and processing exports, to evaluate the role of foreign-invested enterprises (FIEs) in China’s rapid carbon dioxide emission growth. The results suggested that FIEs contributed to 11.55% of the economic outputs’ growth in China between 1992-2010, but accounted for only 9.65% of the growth of carbon dioxide emissions. In relative term, until 2010 FIEs still emitted much less than Chinese-owned enterprises (COEs) when producing the same amount of outputs, although COEs experienced much faster technology upgrades. In an ideal scenario where we assume the final demands remain unchanged and COEs completely mirror the advanced technologies of FIEs, more than 2000 Mt of carbon dioxide emissions would be reduced for China in 2010. From a policy perspective, the widespread FIEs are very effective and efficient channel to encourage technology transfer from developed to developing countries.

Keywords: carbon dioxide emissions, foreign-invested enterprises, technology transfer, input–output analysis, China

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Authors: Michael Scott, Phil Jarrell

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Digitalization seems to be everywhere these days. So if one was to digitalize Functional Safety, what would that require: • Ability to directly use data from intelligent P&IDs / process design in a PHA / LOPA • Ability to directly use data from intelligent P&IDs in the SIS Design to support SIL Verification Calculations, SRS, C&Es, Functional Test Plans • Ability to create Unit Operation / SIF Libraries to radically reduce engineering manhours while ensuring consistency and improving quality of SIS designs • Ability to link data directly from a PHA / LOPA to SIS Designs • Ability to leverage reliability models and SRS details from SIS Designs to automatically program the Safety PLC • Ability to leverage SIS Test Plans to automatically create Safety PLC application logic Test Plans for a virtual FAT • Ability to tie real-time data from Process Historians / CMMS to assumptions in the PHA / LOPA and SIS Designs to generate leading indicators on protection layer health • Ability to flag SIS bad actors for proactive corrective actions prior to a near miss or loss of containment event What if I told you all of this was available today? This paper will highlight how the digital revolution has revolutionized the way Safety Instrumented Systems are designed, configured, operated and maintained.

Keywords: IEC 61511, safety instrumented systems, functional safety, digitalization, IIoT

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

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Authors: Cheryl Forchuk, Sandra Fisman, Steve Cordes, Dan Catunto, Katherine Krakowski, Melissa Jeffrey, John D’Oria

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The discharge of youth aged 16-25 from hospital into homelessness is a prevalent issue despite research indicating social, safety, health and economic detriments on both the individual and community. Lack of stable housing for youth discharged into homelessness results in long-term consequences, including exacerbation of health problems and costly health care service use and hospital readmission. People experiencing homelessness are four times more likely to be readmitted within one month of discharge and hospitals must spend $2,559 more per client. Finding safe housing for these individuals is imperative to their recovery and transition back to the community. People discharged from hospital to homelessness experience challenges, including poor health outcomes and increased hospital readmissions. Youth are the fastest-growing subgroup of people experiencing homelessness in Canada. The needs of youth are unique and include supports related to education, employment opportunities, and age-related service barriers. This study aims to identify the needs of youth at risk of homelessness by evaluating the efficacy of the “Preventing Discharge to No Fixed Address – Youth” (NFA-Y) program, which aims to prevent youth from being discharged from hospital into homelessness. The program connects youth aged 16-25 who are inpatients at London Health Sciences Centre and St. Joseph’s Health Care London to housing and financial support. Supports are offered through collaboration with community partners: Youth Opportunities Unlimited, Canadian Mental Health Association Elgin Middlesex, City of London Coordinated Access, Ontario Works, and Salvation Army’s Housing Stability Bank. This study was reviewed and approved by Western University’s Research Ethics Board. A series of interviews are being conducted with approximately ninety-three youth participants at three time points: baseline (pre-discharge), six, and twelve months post-discharge. Focus groups with participants, health care providers, and community partners are being conducted at three-time points. In addition, administrative data from service providers will be collected and analyzed. Since homelessness has a detrimental effect on recovery, client and community safety, and healthcare expenditure, locating safe housing for psychiatric patients has had a positive impact on treatment, rehabilitation, and the system as a whole. If successful, the findings of this project will offer safe policy alternatives for the prevention of homelessness for at-risk youth, help set them up for success in their future years, and mitigate the rise of the homeless youth population in Canada.

Keywords: youth homelessness, no-fixed address, mental health, homelessness prevention, hospital discharge

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Authors: Ami Fadhillah Amir Abdul Nasir, Amanda C. Niehaus, Skye F. Cameron, Frank A. Von Hippel, John Postlethwait​, Robbie S. Wilson

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For suicidal breeders, the physiological stresses and energetic costs of breeding are fatal. Environmental stressors such as pollution should compound these costs, yet suicidal breeding is so rare among mammals that this is unknown. Here, we explored the consequences of metal contamination to the health, aging and performance of endangered, suicidally-breeding northern quolls (Dasyurus hallucatus) living near an active manganese mine on Groote Eylandt, Northern Territory, Australia. We found respirable manganese dust at levels exceeding international recommendations even 20km from mining sites and substantial accumulation of manganese within quolls’ hair, testes, and in two brain regions—the neocortex and cerebellum, responsible for sensory perception and motor function, respectively. Though quolls did not differ in sprint speeds, motor skill, or manoeuvrability, those with higher accumulation of manganese crashed at lower speeds during manoeuvrability tests, indicating a potential effect on sight or cognition. Immune function and telomere length declined over the breeding season, as expected with ageing, but manganese contamination exacerbated immune declines and suppressed cortisol. Unexpectedly, male quolls with higher levels of manganese had longer telomeres, supporting evidence of unusual telomere dynamics among Dasyurids—though whether this affects their lifespan is unknown. We posit that sublethal contamination via pollution, mining, or urbanisation imposes physiological costs on wildlife that may diminish reproductive success or survival.

Keywords: ecotoxicology, heavy metal, manganese, telomere length, cortisol, locomotor

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Authors: Nuray Uçar, Mervin Ölmez, Özge Alptoğa, Nilgün K. Yavuz, Ayşen Önen

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In recent years, research on continuous graphene oxide fibers has been intensified. Therefore, many factors of production stages are being studied. In this study, the effect of exfoliation time and presence of activated carbon particle (ACP) on graphene oxide fiber’s properties has been analyzed. It has been seen that cross-sectional appearance of sample with ACP is harsh and porous because of ACP. The addition of ACP did not change the electrical conductivity. However, ACP results in an enormous decrease of mechanical properties. Longer exfoliation time results to higher crystallinity degree, C/O ratio and less d space between layers. The breaking strength and electrical conductivity of sample with less exfoliation time is some higher than sample with high exfoliation time.

Keywords: activated carbon, coagulation by wet spinning, exfoliation, graphene oxide fiber

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Authors: H. Arzani, Z. Arzani

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Every piece of rangeland has a different set of physical and biological characteristics. This requires the manager to synthesis various information for regular monitoring to define changes trend to get wright decision for sustainable management. So range managers need to use computerized technologies to monitor rangeland, and select. The best management practices. There are four examples of computerized technologies that can benefit sustainable management: (1) Photographic method for cover measurement: The method was tested in different vegetation communities in semi humid and arid regions. Interpretation of pictures of quadrats was done using Arc View software. Data analysis was done by SPSS software using paired t test. Based on the results, generally, photographic method can be used to measure ground cover in most vegetation communities. (2) GPS application for corresponding ground samples and satellite pixels: In two provinces of Tehran and Markazi, six reference points were selected and in each point, eight GPS models were tested. Significant relation among GPS model, time and location with accuracy of estimated coordinates was found. After selection of suitable method, in Markazi province coordinates of plots along four transects in each 6 sites of rangelands was recorded. The best time of GPS application was in the morning hours, Etrex Vista had less error than other models, and a significant relation among GPS model, time and location with accuracy of estimated coordinates was found. (3) Application of satellite data for rangeland monitoring: Focusing on the long term variation of vegetation parameters such as vegetation cover and production is essential. Our study in grass and shrub lands showed that there were significant correlations between quantitative vegetation characteristics and satellite data. So it is possible to monitor rangeland vegetation using digital data for sustainable utilization. (4) Rangeland suitability classification with GIS: Range suitability assessment can facilitate sustainable management planning. Three sub-models of sensitivity to erosion, water suitability and forage production out puts were entered to final range suitability classification model. GIS was facilitate classification of range suitability and produced suitability maps for sheep grazing. Generally digital computers assist range managers to interpret, modify, calibrate or integrating information for correct management.

Keywords: computer, GPS, GIS, remote sensing, photographic method, monitoring, rangeland ecosystem, management, suitability, sheep grazing

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Authors: Faisal G. Khamis, Ghaleb A. El-Refae

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Many researchers have studied socioeconomic, health, and security variables in the developed countries; however, very few studies used multivariate analysis in developing countries. The current study contributes to the scarce literature about the determinants of the variance in socioeconomic, health, and security factors. Questions raised were whether the independent variables (IVs) of governorate and year impact the socioeconomic, health, and security dependent variables (DVs) in Jordan, whether the marginal mean of each DV in each governorate and in each year is significant, which governorates are similar in difference means of each DV, and whether these DVs vary. The main objectives were to determine the source of variances in DVs, collectively and separately, testing which governorates are similar and which diverge for each DV. The research design was time series and cross-sectional analysis. The main hypotheses are that IVs affect DVs collectively and separately. Multivariate and univariate analyses of variance were carried out to test these hypotheses. The population of 12 governorates in Jordan and the available data of 15 years (2000–2015) accrued from several Jordanian statistical yearbooks. We investigated the effect of two factors of governorate and year on the four DVs of divorce rate, mortality rate, unemployment percentage, and crime rate. All DVs were transformed to multivariate normal distribution. We calculated descriptive statistics for each DV. Based on the multivariate analysis of variance, we found a significant effect in IVs on DVs with p < .001. Based on the univariate analysis, we found a significant effect of IVs on each DV with p < .001, except the effect of the year factor on unemployment was not significant with p = .642. The grand and marginal means of each DV in each governorate and each year were significant based on a 95% confidence interval. Most governorates are not similar in DVs with p < .001. We concluded that the two factors produce significant effects on DVs, collectively and separately. Based on these findings, the government can distribute its financial and physical resources to governorates more efficiently. By identifying the sources of variance that contribute to the variation in DVs, insights can help inform focused variation prevention efforts.

Keywords: ANOVA, crime, divorce, governorate, hypothesis test, Jordan, MANOVA, means, mortality, unemployment, year

Procedia PDF Downloads 260

Authors: Agung A. Ginanjar, Lilitasari, Indra Prasetya, Rizal R. Hanif, Yusrina Rismandini, Atina Hussaana, Nurita P. Sari

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Hyperlipidemia is an increase of lipids and cholesterol in the blood that causes the formation of atherosklerosis. The recent pharmacological therapy nowadays is statin. Many Indonesian people use of medicinal plants. There are several medical plants that people always use to cure hyperlipidemia such as bulbs onion sabrang, areca nuts, and seed of fenugreek. Most people often use a combination therapy of conventional medicine and herbs to achieve the desired therapeutic effect of combination therapy. The use of combination therapy might cause the interaction of pharmacodynamic from those medicines so that it influences the pharmacological effect of one of medicine. The aim of this study is to know the interaction of simvastatin and a cholesterol-lowering herb seen in rats pharmacodynamic simvastatin phase. This research used post-test only controlled group design. Analysis of statistical data normality and homogenity were tested by Kolmogorov Smirnov. The ANOVA test is used when the data is obtained homogeneous but if it is found that the data are not homogeneous then kruskal-wallis test is used. Normal (63.196 mg/dl), negative (70.604 mg/dl), positive (62.512 mg/dl), areca nuts (56.564 mg/dl), fenugreek seed (47.538 ,g/dl), onion sabrang (62.312 mg/dl). The results prove that the combination of herbs and simvastatin did not have a significant difference (P>0,05). The conclusion of this study is that the combination of simvastatin and a cholesterol-lowering herb can cause some pharmacodynamic interactions such as a synergistic effect, antagonist, and a powerful additive, so that combination therapy is not more effective than single simvastatin therapy. The use of the combination therapy is not given in the same time. It would be better if there are some period of time when the combination therapy is applied.

Keywords: onion bulb sabrang, areca nuts, seed of fenugreek, interaction medicine, hyperlipidemia

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Authors: Khurram Shahzad, Muhammad Usman

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The main aim of this study is to examine the direct and interactive effects of job insecurity and Islamic work ethics on employee’s attitude towards change and organizational citizenship behavior. Design/methodology/approach: The data was collected from 171 male and female university teachers of Pakistan. Self administered, close ended questionnaires were used to collect the data. Data was analyzed through correlation and regression analysis. Findings: Through the analysis of data, it was found that job insecurity has a strong negative effect on the attitude towards change of university teachers. On the contrary, job insecurity has no significant effect on organizational citizenship behavior of university teachers. Our results also show that Islamic work ethics does not moderate the relationship of job insecurity and attitude towards change, while a strong moderation effect of Islamic wok ethics is found on the relationship of job insecurity and organizational citizenship behavior. Originality/value: This study for the first time examines the relationship of job insecurity with employee’s attitude towards change and organizational citizenship behavior with the moderating effect of Islamic work ethics.

Keywords: job security, islamic work ethics, attitude towards change, organizational citizenship behavior

Procedia PDF Downloads 457

Authors: Tzong-Ying Hao, Mohammad T. Rahmani

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The Torre Central building is a 9-story shear wall structure located in Santiago, Chile, and has been instrumented since 2009. Events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded, and thus the building can serve as a full-scale benchmark to evaluate the structural health monitoring method developed. The first part of this article presents an analysis of inter-story drifts, and of changes in the first system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) as baseline indicators of the occurrence of damage. During 2010 Chile earthquake the system frequencies were detected decreasing approximately 24% in the EW and 27% in NS motions. Near the end of shaking, an increase of about 17% in the EW motion was detected. The structural health monitoring (SHM) method based on changes in wave traveling time (wave method) within a layered shear beam model of structure is presented in the second part of this article. If structural damage occurs the velocity of wave propagated through the structure changes. The wave method measures the velocities of shear wave propagation from the impulse responses generated by recorded data at various locations inside the building. Our analysis and results show that the detected changes in wave velocities are consistent with the observed damages. On this basis, the wave method is proven for actual implementation in structural health monitoring systems.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response, layered shear beam, structural health monitoring, Torre Central building, wave method, wave travel time

Procedia PDF Downloads 352

Authors: Abdul-Rahman Al-Ali

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As the number of mobile devices is growing exponentially, it is estimated to connect about 50 million devices to the Internet by the year 2020. At the end of this decade, it is expected that an average of eight connected devices per person worldwide. The 50 billion devices are not mobile phones and data browsing gadgets only, but machine-to-machine and man-to-machine devices. With such growing numbers of devices the Internet of Things (I.o.T) concept is one of the emerging technologies as of recently. Within the smart grid technologies, smart home appliances, Intelligent Electronic Devices (IED) and Distributed Energy Resources (DER) are major I.o.T objects that can be addressable using the IPV6. These objects are called the smart grid internet of things (SG-I.o.T). The SG-I.o.T generates big data that requires high-speed computing infrastructure, widespread computer networks, big data storage, software, and platforms services. A company’s utility control and data centers cannot handle such a large number of devices, high-speed processing, and massive data storage. Building large data center’s infrastructure takes a long time, it also requires widespread communication networks and huge capital investment. To maintain and upgrade control and data centers’ infrastructure and communication networks as well as updating and renewing software licenses which collectively, requires additional cost. This can be overcome by utilizing the emerging computing paradigms such as cloud computing. This can be used as a smart grid enabler to replace the legacy of utilities data centers. The talk will highlight the role of I.o.T, cloud computing services and their development models within the smart grid technologies.

Keywords: intelligent electronic devices (IED), distributed energy resources (DER), internet, smart home appliances

Procedia PDF Downloads 307

Authors: Shaidatul Azdawiyah Abdul Talib, Wan Mohd Razi Idris, Liew Ju Neng, Tukimat Lihan, Muhammad Zamir Abdul Rasid

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Climate change has received great attention worldwide due to the impact of weather causing extreme events. Rainfall and temperature are crucial weather components associated with climate change. In Malaysia, increasing temperatures and changes in rainfall distribution patterns lead to drought and flood events involving agricultural areas, especially rice fields. Muda Agricultural Development Authority (MADA) is the largest rice growing area among the 10 granary areas in Malaysia and has faced floods and droughts in the past due to changing climate. Changes in rainfall and temperature patter affect rice yield. Therefore, trend analysis is important to identify changes in temperature and rainfall patterns as it gives an initial overview for further analysis. Six locations across the MADA area were selected based on the availability of meteorological station (MetMalaysia) data. Historical data (1991 to 2020) collected from MetMalaysia and future climate projection by multi-model ensemble of climate model from CMIP5 (CNRM-CM5, GFDL-CM3, MRI-CGCM3, NorESM1-M and IPSL-CM5A-LR) have been analyzed using Mann-Kendall test to detect the time series trend, together with standardized precipitation anomaly, rainfall anomaly index, precipitation concentration index and temperature anomaly. Future projection data were analyzed based on 3 different periods; early century (2020 – 2046), middle century (2047 – 2073) and late-century (2074 – 2099). Results indicate that the MADA area does encounter extremely wet and dry conditions, leading to drought and flood events in the past. The Mann-Kendall (MK) trend analysis test discovered a significant increasing trend (p < 0.05) in annual rainfall (z = 0.40; s = 15.12) and temperature (z = 0.61; s = 0.04) during the historical period. Similarly, for both RCP 4.5 and RCP 8.5 scenarios, a significant increasing trend (p < 0.05) was found for rainfall (RCP 4.5: z = 0.15; s = 2.55; RCP 8.5: z = 0.41; s = 8.05;) and temperature (RCP 4.5: z = 0.84; s = 0.02; RCP 8.5: z = 0.94; s = 0.05). Under the RCP 4.5 scenario, the average temperature is projected to increase up to 1.6 °C in early century, 2.0 °C in the middle century and 2.4 °C in the late century. In contrast, under RCP 8.5 scenario, the average temperature is projected to increase up to 1.8 °C in the early century, 3.1 °C in the middle century and 4.3 °C in late century. Drought is projected to occur in 2038 and 2043 (early century); 2052 and 2069 (middle century); and 2095, 2097 to 2099 (late century) under RCP 4.5 scenario. As for RCP 8.5 scenario, drought is projected to occur in 2021, 2031 and 2034 (early century); and 2069 (middle century). No drought is projected to occur in the late century under the RCP 8.5 scenario. Thus, this information can be used for the analysis of the impact of climate change scenarios on rice growth and yield besides other crops found in MADA area. Additionally, this study, it would be helpful for researchers and decision-makers in developing applicable adaptation and mitigation strategies to reduce the impact of climate change.

Keywords: climate projection, drought, flood, rainfall, RCP 4.5, RCP 8.5, temperature

Procedia PDF Downloads 60

Authors: G.–A. Constantin, G. Voicu, E.–M. Stefan, P. Tudor, G. Paraschiv, M.–G. Munteanu

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In the activity of handling and transport of food products, the products may be subjected to mechanical stresses that may lead to their deterioration by deformation, breaking, or crushing. This is the case for biscuits, regardless of their type (gluten-free or sugary), the addition of ingredients or flour from which they are made. However, gluten-free biscuits have a higher mechanical resistance to breakage or crushing compared to easily shattered sugar biscuits (especially those for children). The paper presents the results of the experimental evaluation of the texture for four varieties of commercial biscuits, using the penetrometer equipped with needle cone at five different additional weights on the cone-rod. The assortments of biscuits tested in the laboratory were Petit Beurre, Picnic, and Maia (all three manufactured by RoStar, Romania) and Sultani diet biscuits, manufactured by Eti Burcak Sultani (Turkey, in packs of 138 g). For the four varieties of biscuits and the five additional weights (50, 77, 100, 150 and 177 g), the experimental data obtained were subjected to regression analysis in the MS Office Excel program, using Velon's relationship (h = a∙ln(t) + b). The regression curves were analysed comparatively in order to identify possible differences and to highlight the variation of the penetration depth h, in relation to the time t. Based on the penetration depth between two-time intervals (every 5 seconds), the curves of variation of the penetration speed in relation to time were then drawn. It was found that Velon's law verifies the experimental data for all assortments of biscuits and for all five additional weights. The correlation coefficient R2 had in most of the analysed cases values over 0.850. The values recorded for the penetration depth were framed, in general, within 45-55 p.u. (penetrometric units) at an additional mass of 50 g, respectively between 155-168 p.u., at an additional mass of 177 g, at Petit Beurre biscuits. For Sultani diet biscuits, the values of the penetration depth were within the limits of 32-35 p.u., at an additional weight of 50 g and between 80-114 p.u., at an additional weight of 177g. The data presented in the paper can be used by both operators on the manufacturing technology flow, as well as by the traders of these food products, in order to establish the most efficient parametric of the working regimes (when packaging and handling).

Keywords: biscuits resistance/texture, penetration depth, penetration velocity, sharp pin penetrometer

Procedia PDF Downloads 117

Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

Procedia PDF Downloads 124