Search results for: monitoring stations

Authors: Lavdosh Lazemetaj

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The labor market in W.B. Countries presents problems and challenges, this is dictated by different risk factors. The levels of unemployment in the region are high and the rates of its reduction are a challenge. This paper presents these challenges and problems that the countries face. of the BP region. The region as a whole and the countries in their particularity are analyzed, according to the specifics, the development trends related to the labor market are looked at. Conclusions are also given that emerge from the analysis of the labor markets prior to the monitoring done by the EU and the World Bank.

Keywords: Economic Development, European Union, Economic Growth, Labor Market

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Authors: Valeria M. Bastos, Myrian A. Costa, Matheus Ambrozio, Nelson F. F. Ebecken

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In this paper a very simple and effective user administration view of computing clusters systems is implemented in order of friendly provide the configuration and monitoring of distributed application executions. The user view, the administrator view, and an internal control module create an illusionary management environment for better system usability. The architecture, properties, performance, and the comparison with others software for cluster management are briefly commented.

Keywords: big data, computing clusters, administration view, user view

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Hiba Hamdi, Thomas Corpetti, Laure Roupioz, Xavier Briottet

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Air temperatures are generally higher in cities than in their rural surroundings. The overheating of cities is a direct consequence of increasing urbanization, characterized by the artificial filling of soils, the release of anthropogenic heat, and the complexity of urban geometry. This phenomenon, referred to as urban heat island (UHI), is more prevalent during heat waves, which have increased in frequency and intensity in recent years. In the context of global warming and urban population growth, helping urban planners implement UHI mitigation and adaptation strategies is critical. In practice, the study of UHI requires air temperature information at the street canyon level, which is difficult to obtain. Many urban air temperature simulation models have been proposed (mostly based on physics or statistics), all of which require a variety of input parameters related to urban morphology, land use, material properties, or meteorological conditions. In this paper, we build and evaluate a neural network model based on Urban Weather Generator (UWG) model simulations and data from meteorological stations that simulate air temperature over Toulouse, France, on days favourable to UHI.

Keywords: air temperature, neural network model, urban heat island, urban weather generator

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Authors: Fan Ye

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Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: RWIS, visibility distance, low visibility, adverse weather

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Authors: Akunna Agunwah, Kevin Gallimore, Kathryn Kinnmond

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Entrepreneurship and project management are widely associated and seen as a vehicle for economic growth, but are studied separately. A few authors have considered the interconnectivity existing between these two fields, but relatively little empirical data currently exist in the literature. The purpose of the present empirical study is to explore whether successful entrepreneurs utilise project management approaches in enhancing enterprise growth by understanding the working practices and experiences of the entrepreneurs’ using the Theory of Planned Behaviour (TPB) as a lens. In order to understand those experiences, ten successful entrepreneurs in various business sectors in the North West of England were interviewed through a face-to-face semi-structured interview method. The collected audio tape-recorded data was transcribed and analysed using the deductive thematic technique (qualitative approach). The themes were viewed through the lens of Theory of Planned Behaviour to identify the three intentional antecedents (attitude, subjective norms, and perceived behavioural control) and to understand how they relate to the project management approaches (Planning, execution, and monitoring). The findings are twofold, the first evidence of the three intentional antecedents, which make up Theory of Planned Behaviour was present. Secondly, the analysis of project management approaches themes (planning, execution, and monitoring) using the lens of the theory of planned behaviour shows evidence of the three intentional antecedents. There were more than one intentional antecedents found in a particular project management theme, which indicates that the entrepreneur does utilise these approaches without categorising them into definite themes. However, the entrepreneur utilised these intentional antecedents as processes to enhanced business growth. In conclusion, the work presented here showed a way of understanding the interconnectivity between entrepreneurship and project management towards enhancing enterprise growth by examining the working practices and experiences of the successful entrepreneurs in the North-West England.

Keywords: business growth, entrepreneurship, project management approaches, theory of planned behaviour

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Authors: Kathryn Rooney, Kaitlyn Eddy, Evan Landers, Weihui Li

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The international mortality rate for neonates and infants has been declining at a disproportionally low rate when compared to the overall decline in child mortality in recent decades. A significant portion of infant deaths could be prevented with the implementation of low-cost and easy to use physiological monitoring devices, by enabling early identification of symptoms before they progress into life-threatening illnesses. The oral diagnostic device discussed in this paper serves to continuously monitor the key vital signs of body temperature, respiratory rate, heart rate, and oxygen saturation. The device mimics an infant pacifier, designed to be easily tolerated by infants as well as orthodontically inert. The fundamental measurements are gathered via thermistors and a pulse oximeter, each encapsulated in medical-grade silicone and wired internally to a microcontroller chip. The chip then translates the raw measurements into physiological values via an internal algorithm, before outputting the data to a liquid crystal display screen and an Android application. Additionally, a biological sample collection chamber is incorporated into the internal portion of the device. The movement within the oral chamber created by sucking on the pacifier-like device pushes saliva through a small check valve in the distal end, where it is accumulated and stored. The collection chamber can be easily removed, making the sample readily available to be tested for various diseases and analytes. With the vital sign monitoring and sample collection offered by this device, abnormal fluctuations in physiological parameters can be identified and appropriate medical care can be sought. This device enables preventative diagnosis for infants who may otherwise have gone undiagnosed, due to the inaccessibility of healthcare that plagues vast numbers of underprivileged populations.

Keywords: neonate mortality, infant mortality, low-cost diagnostics, vital signs, saliva testing, preventative care

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Authors: Benslimane Marwa, Benabbas-Sahki Ilham

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Spiders play an important role in agroecosystems due to their great abundance. They are considered a valuable group of invertebrates in agricultural land. They are predators of insects harmful to crops, but their use in biological control requires in-depth research on their ecology. During our study, we counted a total of 768 spiders, which we were able to identify and classify into 14 families over a period between March 2021 and October of the same year. This study aims to compare a station subjected to agricultural practices, including the spreading of herbicides, with another station subjected to the same practices but without the use of phytosanitary products. The inventory shows a strong dominance of the Gnaphosidae family (75.8%). This result affirms that the proliferation of this family is very favorable to the knowledge of the fruits by limiting the populations of aphids infesting the plot, which can therefore be proposed for biological control. The comparative study of the populations of spiders in the stations studied shows the negative effect of agricultural practices on the species richness and abundance of these species; as for the diversity, this one is only slightly affected. Finally, we can note that the effects of herbicides did not cause a significant imbalance in this agroecosystem, unlike plowing, which showed harmful consequences on spiders.

Keywords: spiders, predator, species richness, herbicides, agricultural practices

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Authors: Kohkan Shamsi

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Background: MRI and PET are now extensively utilized in Alzheimer's disease (AD) trials for patient eligibility, efficacy assessment, and safety evaluations but including imaging in AD trials impacts site selection process, patient recruitment, and patient retention. Methods: PET/MRI are performed at baseline and at multiple follow-up timepoints. This requires prospective site imaging qualification, evaluation of phantom data, training and continuous monitoring of machines for acquisition of standardized and consistent data. This also requires prospective patient/caregiver training as patients must go to multiple facilities for imaging examinations. We will share our experience form one of the largest AD programs. Lesson learned: Many neurological diseases have a similar presentation as AD or could confound the assessment of drug therapy. The inclusion of wrong patients has ethical and legal issues, and data could be excluded from the analysis. Centralized eligibility evaluation read process will be discussed. Amyloid related imaging abnormalities (ARIA) were observed in amyloid-β trials. FDA recommended regular monitoring of ARIA. Our experience in ARIA evaluations in large phase III study at > 350 sites will be presented. Efficacy evaluation: MRI is utilized to evaluate various volumes of the brain. FDG PET or amyloid PET agents has been used in AD trials. We will share our experience about site and central independent reads. Imaging logistic issues that need to be handled in the planning phase will also be discussed as it can impact patient compliance thereby increasing missing data and affecting study results. Conclusion: imaging must be prospectively planned to include standardizing imaging methodologies, site selection process and selecting assessment criteria. Training should be transparently conducted and documented. Prospective patient/caregiver awareness of imaging requirement is essential for patient compliance and reduction in missing imaging data.

Keywords: Alzheimer's disease, ARIA, MRI, PET, patient recruitment, retention

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Authors: Artiya Sopharak, Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong

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This paper presents an energy-saving study of Mass Rapid Transit (MRT) using an optimal train coasting operation. For the dynamic train movement with four modes of operation, including accelerating mode, constant speed or cruising mode, coasting mode, and braking mode are considered in this study. The acceleration rate, the deceleration rate, and the starting coasting point are taken into account the optimal train speed profile during coasting mode with considering the energy saving and acceptable travel time comparison to the based case with no coasting operation. In this study, the mathematical method as a Quadratic Search Method (QDS) is conducted to carry out the optimization problem. A single train of MRT services between two stations with a distance of 2 km and a maximum speed of 80 km/h is taken to be the case study. Regarding the coasting mode operation, the results show that the longer distance of costing mode, the less energy consumption in cruising mode and the less braking energy. On the other hand, the shorter distance of coasting mode, the more energy consumption in cruising mode and the more braking energy.

Keywords: energy saving, coasting mode, mass rapid transit, quadratic search method

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Authors: Launcelot McGrath, Xiaoxiao Liu, Colin Flanagan

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It is widely recognised that a comprehensive understanding of physiological data is a vital aid to the anaesthesiologist in monitoring and maintaining the well-being of a patient undergoing surgery. Bio signal analysis is one of the most important topics that researchers have tried to develop over the last century to understand numerous human diseases. There are tremendous biological signals during anaesthesia, and not all of them are important, which to choose to observe is a significant decision. It is important that the anaesthesiologist understand both the signals themselves, and the limitations introduced by the processes of acquisition. In this article, we provide an all-sided overview of different types of biological signals as well as the mechanisms applied to acquire them.

Keywords: general biosignals, anaesthesia, biological, electroencephalogram

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Authors: Visar Baxhuku, Halil Demolli, Alishukri Shkodra

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This paper presents the monitoring of vehicle movement, namely the developing of speed of vehicles during movement in a certain twist. The basic geometry data of twist are measured with the purpose of calculating the slide in border speed. During the research, measuring developed speed of passenger vehicles for the real conditions of the road surface, dry road with average damage, was realised. After setting values, the analysis was done in function security of movement in twist.

Keywords: critical sliding velocity, moving velocity, curve, passenger vehicles

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Authors: Innocent Uzougbo Onwuegbuzie

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Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.

Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security

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Authors: Jan Bohata, Stanislav Zvanovec, Matej Komanec, Jakub Jaros, David Hruby

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Even though there is a rapid development in new optical networks, still optical communication infrastructures remain composed of thousands of kilometers of aging optical cables. Many of them are located in a harsh environment which contributes to an increased attenuation or induced birefringence of the fibers leading to the increase of polarization mode dispersion (PMD). In this paper, we report experimental results from environmental optical cable tests and characterization in the climate chamber. We focused on the evaluation of optical network reliability in a harsh environment. For this purpose, a special thermal chamber was adopted, targeting to the large temperature changes between -60 °C and 160 C° with defined humidity. Single mode optical cable 230 meters long, having six tubes and a total number of 72 single mode optical fibers was spliced together forming one fiber link, which was afterward tested in the climate chamber. The main emphasis was put to the polarization mode dispersion (PMD) changes, which were evaluated by three different PMD measuring methods (general interferometry technique, scrambled state-of-polarization analysis and polarization optical time domain reflectometer) in order to fully validate obtained results. Moreover, attenuation and chromatic dispersion (CD), as well as the PMD, were monitored using 17 km long single mode optical cable. Results imply a strong PMD dependence on thermal changes, imposing the exceeding 200 % of its value during the exposure to extreme temperatures and experienced more than 20 dB insertion losses in the optical system. The derived statistic is provided in the paper together with an evaluation of such as optical system reliability, which could be a crucial tool for the optical network designers. The environmental tests are further taken in context to our previously published results from long-term monitoring of fundamental parameters within an optical cable placed in a harsh environment in a special outdoor testbed. Finally, we provide a correlation between short-term and long-term monitoring campaigns and statistics, which are necessary for optical network safety and reliability.

Keywords: optical fiber, polarization mode dispersion, harsh environment, aging

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Authors: Snehal D. Ganjave, Hardik Dodia, Avinash V. Sunder, Swati Madhu, Pramod P. Wangikar

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Batch cultivation of recombinant bacteria in shake flasks results in low cell density due to nutrient depletion. Previous protocols on high cell density cultivation in shake flasks have relied mainly on controlled release mechanisms and extended cultivation protocols. In the present work, we report an optimized fed-batch process for high cell density cultivation of recombinant E. coli BL21(DE3) for protein production. A cybernetic model-based, multi-objective optimization strategy was implemented to obtain the optimum operating variables to achieve maximum biomass and minimized substrate feed rate. A syringe pump was used to feed a mixture of glycerol and yeast extract into the shake flask. Preliminary experiments were conducted with online monitoring of dissolved oxygen (DO) and offline measurements of biomass and glycerol to estimate the model parameters. Multi-objective optimization was performed to obtain the pareto front surface. The selected optimized recipe was tested for a range of proteins that show different extent soluble expression in E. coli. These included eYFP and LkADH, which are largely expressed in soluble fractions, CbFDH and GcanADH , which are partially soluble, and human PDGF, which forms inclusion bodies. The biomass concentrations achieved in 24 h were in the range 19.9-21.5 g/L, while the model predicted value was 19.44 g/L. The process was successfully reproduced in a standard laboratory shake flask without online monitoring of DO and pH. The optimized fed-batch process showed significant improvement in both the biomass and protein production of the tested recombinant proteins compared to batch cultivation. The proposed process will have significant implications in the routine cultivation of E. coli for various applications.

Keywords: cybernetic model, E. coli, high cell density cultivation, multi-objective optimization

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Authors: Tiberiu Boros, Angela Ionita, Maria Visan

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Wildfires are one of the frequent and uncontrollable phenomena that currently affect large areas of the world where the climate, geographic and social conditions make it impossible to prevent and control such events. In this paper we introduce the ground concepts that lie behind the SIAFIM (Satellite Image Analysis for Fire Monitoring) project in order to create a context and we introduce a set of newly created tools that are external to the project but inherently in interventions and complex decision making based on geospatial information and spatial data infrastructures.

Keywords: wildfire, forest fire, natural language processing, mobile applications, communication, GPS

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Authors: R. Meier, M. Pander

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In accordance with the industry 4.0 concept, manufacturing process steps as well as the materials themselves are going to be more and more digitalized within the next years. The “digital twin” representing the simulated and measured dataset of the (semi-finished) product can be used to control and optimize the individual processing steps and help to reduce costs and expenditure of time in product development, manufacturing, and recycling. In the present work, two material characterization methods based on Lamb waves were evaluated and compared. For demonstration purpose, both methods were shown at a standard industrial product - copper ribbons, often used in photovoltaic modules as well as in high-current microelectronic devices. By numerical approximation of the Rayleigh-Lamb dispersion model on measured phase velocities second order elastic constants (Young’s modulus, Poisson’s ratio) were determined. Furthermore, the effective third order elastic constants were evaluated by applying elastic, “non-destructive”, mechanical stress on the samples. In this way, small microstructural variations due to mechanical preconditioning could be detected for the first time. Both methods were compared with respect to precision and inline application capabilities. Microstructure of the samples was systematically varied by mechanical loading and annealing. Changes in the elastic ultrasound transport properties were correlated with results from microstructural analysis and mechanical testing. In summary, monitoring the elastic material properties of plate-like structures using Lamb waves is valuable for inline and non-destructive material characterization and manufacturing process control. Second order elastic constants analysis is robust over wide environmental and sample conditions, whereas the effective third order elastic constants highly increase the sensitivity with respect to small microstructural changes. Both Lamb wave based characterization methods are fitting perfectly into the industry 4.0 concept.

Keywords: lamb waves, industry 4.0, process control, elasticity, acoustoelasticity, microstructure

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Authors: E. Fathallahi Aghdam, V. Hosseini

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Environmental pollution is not limited to a specific region or country; that is why sustainable development, as a necessary process for improvement, pays attention to issues such as destruction of natural resources, degradation of biological system, global pollution, and climate change in the world, especially in the developing countries. According to the World Health Organization, as a developing city, Tehran (capital of Iran) is one of the most polluted cities in the world in terms of air pollution. In this study, three pollutants including particulate matter less than 10 microns, nitrogen oxides, and sulfur dioxide were evaluated in Tehran using data mining techniques and through Crisp approach. The data from 21 air pollution measuring stations in different areas of Tehran were collected from 1999 to 2013. Commercial softwares Clementine was selected for this study. Tehran was divided into distinct clusters in terms of the mentioned pollutants using the software. As a data mining technique, clustering is usually used as a prologue for other analyses, therefore, the similarity of clusters was evaluated in this study through analyzing local conditions, traffic behavior, and industrial activities. In fact, the results of this research can support decision-making system, help managers improve the performance and decision making, and assist in urban studies.

Keywords: data mining, clustering, air pollution, crisp approach

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Authors: Mousa Keshavarz, Abdul-Reza Dabbagh, Maryam Soyuf Jahromi

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The diversity of mangrove macrobenthos assemblages at mudflat and mangrove ecosystems of Port Khamir, Iran were investigated for one year. During this period, we measured physicochemical properties of water temperature, salinity, pH, DO and the density and distribution of the macrobenthos. We sampled a total of 9 transects, at three different topographic levels along the intertidal zone at three stations. Assemblages at class level were compared. The five most diverse and abundant classes were Foraminifers (54%), Gastropods (23%), Polychaetes (10%), Bivalves (8%) & Crustaceans (5%), respectively. Overall densities were 1869 ± 424 ind/m2 (26%) in spring, 2544 ± 383 ind/m2(36%) in summer, 1482 ± 323 ind/m2 (21%) in autumn and 1207 ± 80 ind/m2 (17%) in winter. Along the intertidal zone, the overall relative density of individuals at high, intermediate, and low topographic levels was 40, 30, and 30% respectively. Biodiversity indices were used to compare different classes: Gastropoda (Shannon index: 0.33) and Foraminifera (Simpson index: 0.28) calculated the highest scores. It was also calculated other bio-indices. With the exception of bivalves, filter feeders were associated with coarser sediments at higher intertidal levels, while deposit feeders were associated with finer sediments at lower levels. Salinity was the most important factor acting on community structure, while DO and pH had little influence.

Keywords: macrobenthos, biodiversity, mangrove forest, Khamir Port

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Authors: Thanh Van Hoang, Tien Yin Chou, Yao Min Fang, Yi Min Huang, Xuan Linh Nguyen

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Reliable information on the spatial distribution of annual rainfall and temperature is essential in research projects relating to urban and regional planning. This research presents results of a classification of temperature and rainfall in the Red River Delta of northern Vietnam based on measurements from seven meteorological stations (Ha Nam, Hung Yen, Lang, Nam Dinh, Ninh Binh, Phu Lien, Thai Binh) in the river basin over a thirty-years period from 1982-2011. The average accumulated rainfall trends in the delta are analysed and form the basis of research essential to weather and climate forecasting. This study employs interpolation based on the Kriging Method for daily rainfall (min and max) and daily temperature (min and max) in order to improve the understanding of sources of variation and uncertainly in these important meteorological parameters. To the Kriging method, the results will show the different models and the different parameters based on the various precipitation series. The results provide a useful reference to assist decision makers in developing smart agriculture strategies for the Red River Delta in Vietnam.

Keywords: spatial interpolation method, ArcGIS, temperature variability, rainfall variability, Red River Delta, Vietnam

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Authors: Cristobal García

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The visual inspection of bolted joints in wind turbines is dangerous, expensive, and impractical due to the non-possibility to access the platform by workboat in certain sea state conditions, as well as the high costs derived from the transportation of maintenance technicians to offshore platforms located far away from the coast, especially if helicopters are involved. Consequently, the wind turbine operators have the need for simpler and less demanding techniques for the analysis of the bolts tightening. Vibration-based structural health monitoring is one of the oldest and most widely-used means for monitoring the health of onshore and offshore wind turbines. The core of this work is to find out if the modal parameters can be efficiently used as a key performance indicator (KPIs) for the assessment of joint bolts in a 1:50 scale tower of a floating offshore wind turbine (12 MW). A non-destructive vibration test is used to extract the vibration signals of the towers with different damage statuses. The procedure can be summarized in three consecutive steps. First, an artificial excitation is introduced by means of a commercial shaker mounted on the top of the tower. Second, the vibration signals of the towers are recorded for 8 s at a sampling rate of 20 kHz using an array of commercial accelerometers (Endevco, 44A16-1032). Third, the natural frequencies, damping, and overall vibration mode shapes are calculated using the software Siemens LMS 16A. Experiments show that the natural frequencies, damping, and mode shapes of the tower are directly dependent on the fixing conditions of the towers, and therefore, the variations of both parameters are a good indicator for the estimation of the static axial force acting in the bolt. Thus, this vibration-based structural method proposed can be potentially used as a diagnostic tool to evaluate the tightening torques of the bolted joints with the advantages of being an economical, straightforward, and multidisciplinary approach that can be applied for different typologies of connections by operation and maintenance technicians. In conclusion, TSI, in collaboration with the consortium of the FIBREGY project, is conducting innovative research where vibrations are utilized for the estimation of the tightening torque of a 1:50 scale steel-based tower prototype. The findings of this research carried out in the context of FIBREGY possess multiple implications for the assessment of the bolted joint integrity in multiple types of connections such as tower-to-nacelle, modular, tower-to-column, tube-to-tube, etc. This research is contextualized in the framework of the FIBREGY project. The EU-funded FIBREGY project (H2020, grant number 952966) will evaluate the feasibility of the design and construction of a new generation of marine renewable energy platforms using lightweight FRP materials in certain structural elements (e.g., tower, floating platform). The FIBREGY consortium is composed of 11 partners specialized in the offshore renewable energy sector and funded partially by the H2020 program of the European Commission with an overall budget of 8 million Euros.

Keywords: SHM, vibrations, connections, floating offshore platform

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Authors: E. K. Naseela, B. M. Dodamani, Chaithra Chandran

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The GIS and remote sensing techniques facilitate accurate estimation of surface runoff from watershed. In the present study an attempt has been made to evaluate the applicability of Natural Resources Service Curve Number method using GIS and Remote sensing technique in the upper Krishna basin (69,425 Sq.km). Landsat 7 (with resolution 30 m) satellite data for the year 2012 has been used for the preparation of land use land cover (LU/LC) map. The hydrologic soil group is mapped using GIS platform. The weighted curve numbers (CN) for all the 5 subcatchments calculated on the basis of LU/LC type and hydrologic soil class in the area by considering antecedent moisture condition. Monthly rainfall data was available for 58 raingauge stations. Overlay technique is adopted for generating weighted curve number. Results of the study show that land use changes determined from satellite images are useful in studying the runoff response of the basin. The results showed that there is no significant difference between observed and estimated runoff depths. For each subcatchment, statistically positive correlations were detected between observed and estimated runoff depth (0.6Keywords: curve number, GIS, remote sensing, runoff

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Authors: David X. Dong, Qingming Zhang, Meng Lu

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Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

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Authors: Chien Chin-Wen

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Collaborative teaching has different teaching models and station teaching is one type of collaborative teaching. Station teaching is not commonly practiced in elementary school English education and introduced in language teacher education programs in Taiwan. In station teaching, each teacher takes a small part of instructional content, working with a small number of students. Students rotate between stations where they receive the assignments and instruction from different teachers. The teachers provide the same content to each group, but the instructional method can vary based upon the needs of each group of students. This study explores thirty-four Taiwanese pre-service elementary school English teachers’ knowledge about station teaching and their competence demonstrated in designing activities for and delivering of station teaching in an English remedial education to six sixth graders in a local elementary school in northern Taiwan. The participants simultaneously enrolled in this Elementary School English Teaching Materials and Methods class, a part of an elementary school teacher education program in a northern Taiwan city. The instructor (Jennifer, pseudonym) in this Elementary School English Teaching Materials and Methods class collaborated with an English teacher (Olivia, pseudonym) in Maureen Elementary School (pseudonym), an urban elementary school in a northwestern Taiwan city. Of Olivia’s students, four male and two female sixth graders needed to have remedial English education. Olivia chose these six elementary school students because they were in the lowest 5 % of their class in terms of their English proficiency. The thirty-four pre-service English teachers signed up for and took turns in teaching these six sixth graders every Thursday afternoon from four to five o’clock for twelve weeks. While three participants signed up as a team and taught these six sixth graders, the last team consisted of only two pre-service teachers. Each team designed a 40-minute lesson plan on the given language focus (words, sentence patterns, dialogue, phonics) of the assigned unit. Data in this study included the KWLA chart, activity designs, and semi-structured interviews. Data collection lasted for four months, from September to December 2014. Data were analyzed as follows. First, all the notes were read and marked with appropriate codes (e.g., I don’t know, co-teaching etc.). Second, tentative categories were labeled (e.g., before, after, process, future implication, etc.). Finally, the data were sorted into topics that reflected the research questions on the basis of their relevance. This study has the following major findings. First of all, the majority of participants knew nothing about station teaching at the beginning of the study. After taking the course Elementary School English Teaching Materials and Methods and after designing and delivering the station teaching in an English remedial education program to six sixth graders, they learned that station teaching is co-teaching, and that it includes activity designs for different stations and students’ rotating from station to station. They demonstrated knowledge and skills in activity designs for vocabulary, sentence patterns, dialogue, and phonics. Moreover, they learned to interact with individual learners and guided them step by step in learning vocabulary, sentence patterns, dialogue, and phonics. However, they were still incompetent in classroom management, time management, English, and designing diverse and meaningful activities for elementary school students at different English proficiency levels. Hence, language teacher education programs are recommended to integrate station teaching to help pre-service teachers be equipped with eight knowledge and competences, including linguistic knowledge, content knowledge, general pedagogical knowledge, curriculum knowledge, knowledge of learners and their characteristics, pedagogical content knowledge, knowledge of education content, and knowledge of education’s ends and purposes.

Keywords: co-teaching, competence, knowledge, pre-service teachers, station teaching

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Authors: Haffaf Hafid

Abstract:

Hypergraphs, after being used to model the structural organization of System of Sytems (SoS) at macroscopic level, has recent trends towards generalizing this powerful representation at different stages of complex system modelling. In this paper, we first describe different applications of hypergraph theory, and step by step, introduce multilevel modeling of SoS by means of integrating Constraint Programming Langages (CSP) dealing with engineering system reconfiguration strategy. As an application, we give an A.C.T Terminal controlled by a set of Intelligent Automated Vehicle.

Keywords: hypergraph model, structural analysis, bipartite graph, monitoring, system of systems, reconfiguration analysis, hypernetwork

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Authors: Ashraf Aly

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The aim of this study is to examine the impact of 5G communication technology radiation on human health and airport safety. The term 5G refers to the fifth generation of wireless mobile technology. The 5G wireless technology will increase the number of high-frequency-powered base stations and other devices and browsing and download speeds, as well as improve the network connectivity and play a big part in improving the performance of integrated applications, such as self-driving cars, medical devices, and robotics. 4G was the latest embedded version of mobile networking technology called 4G, and 5G is the new version of wireless technology. 5G networks have more features than 4G networks, such as lower latency, higher capacity, and increased bandwidth compared to 4G. 5G network improvements over 4G will have big impacts on how people live, business, and work all over the world. But neither 4G nor 5G have been tested for safety and show harmful effects from this wireless radiation. This paper presents biological factors on the effects of 5G radiation on human health. 5G services use C-band radio frequencies; these frequencies are close to those used by radio altimeters, which represent important equipment for airport and aircraft safety. The aviation industry, telecommunications companies, and their regulators have been discussing and weighing these interference concerns for years.

Keywords: wireless communication, radiofrequency, Electromagnetic field, environmental issues

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Authors: Amit Kumar Jain, Surbhi Jain

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The urban freight in a city constitutes 10 to 18 per cent of all city road traffic, and 40 per cent of air pollution and noise emissions, are directly related to commercial transport. The policy measures implemented by urban planners have sought to restrict rather than assist goods-vehicle operations. This approach has temporarily controlled the urban transport demand during peak hours of traffic but has not effectively solved transport congestion. The solution discussed in the paper envisages the development of a comprehensive network of Urban Freight Stations (UFS) connected through underground conveyor belts in the city in line with baggage segregation and distribution in any of the major airports. The transportation of freight shall be done in standard size containers/cars through rail borne carts. The freight can be despatched or received from any of the UFS. Once freight is booked for a destination from any of the UFS, it would be stuffed in the container and digitally tagged for the destination. The container would reach the destination UFS through a network of rail borne carts. The container would be de-stuffed at the destination UFS and sent for further delivery, or the consignee may be asked to collect the consignment from urban freight station. The obvious benefits would be decongestion of roads, reduction in air and noise pollution, saving in manpower used for freight transportation.

Keywords: congestion, urban freight, intelligent transport system, pollution

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Authors: Milagros S. Salibad, Levita B. Grana

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The presence and role of Indigenous Peoples residing in key biodiversity, protected, and watershed areas within the ancestral domain in the Caraga Region hold immense significance. This study aimed to determine the level of biodiversity conservation practices among the Mamanwas, Manobos, and Higaonons, and identify facilitating or hindering factors. Employing a mixed-method research design, 421 respondents participated through a researcher-made questionnaire. Focus group discussions, key informant interviews, researcher field notes, community immersions, and secondary sources were done. The three groups have demonstrated a high level of biodiversity conservation practices manifesting their commitment to conserving their natural resources and ecosystems. Evidently, selecting and cutting only mature trees for shelter and tribal usage, and preservation of large trees that harbor ancestors’ spirits and worship through rituals (Mambabaja). Each group exhibited unique environmental practices shaped by their distinct cultures, traditions, customary knowledge, and access to information. The Mamanwa practiced traditional hunting and gathering by using traps while Manobo practiced shifting cultivation to maintain soil fertility and biodiversity, and Higaonon managed forest resources through traditional forest management (establishment of sacred forests and conservation areas). Various facilitating and hindering factors influenced their conservation efforts. Their traditional knowledge and practices, partnership and collaboration, legal recognition and support, access to information, and biodiversity monitoring system facilitate practices. Insufficient government assistance, political and social issues, scarce financial support, inadequate policy enforcement, lack of livelihood opportunities, and land use conflicts hinder them. Monitoring the sustainability of IPs' local biodiversity conservation practices is essential as they contribute to conservation endeavors.

Keywords: biodiversity, conservation, indigenous peoples, traditional knowledge

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Authors: Thais Cardoso Franco, Caio Nahuel Sousa Fagonde, Willer Gomes dos Santos

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Aurora Borealis is an optical phenomenon composed of luminous events observed in the night skies in the polar regions resulting from disturbances in the magnetosphere due to the impact of solar wind particles with the Earth's upper atmosphere, channeled by the Earth's magnetic field, which causes atmospheric molecules to become excited and emit electromagnetic spectrum, leading to the display of lights in the sky. However, there are still different implications of this phenomenon under study: high intensity auroras are often accompanied by geomagnetic storms that cause blackouts on Earth and impair the transmission of signals from the Global Navigation Satellite Systems (GNSS). Auroras are also known to occur on other planets and exoplanets, so the activity is an indication of active space weather conditions that can aid in learning about the planetary environment. In order to improve understanding of the phenomenon, this research aims to design a satellite formation flying solution for collecting and transmitting data for monitoring aurora borealis in northern hemisphere, an approach that allows studying the event with multipoint data collection in a reduced time interval, in order to allow analysis from the beginning of the phenomenon until its decline. To this end, the ideal number of satellites, the spacing between them, as well as the ideal topology to be used will be analyzed. From an orbital study, approaches from different altitudes, eccentricities and inclinations will also be considered. Given that at large relative distances between satellites in formation, controllers tend to fail, a study on the efficiency of nonlinear adaptive control methods from the point of view of position maintenance and propellant consumption will be carried out. The main orbital perturbations considered in the simulation: non-homogeneity terrestrial, atmospheric drag, gravitational action of the Sun and the Moon, accelerations due to solar radiation pressure and relativistic effects.

Keywords: formation flying, nonlinear adaptive control method, aurora borealis, adaptive SDRE method

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

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Achieving precise radiotherapy through carbon therapy necessitates the accurate monitoring of radiation dose distribution within the patient's body. This process is pivotal for targeted tumor treatment, minimizing harm to healthy tissues, and enhancing overall treatment effectiveness while reducing the risk of side effects. In our investigation, we adopted a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo (MC) simulations. Initially, Geant4 simulations were employed to extract the initial positions of secondary particles generated during interactions between carbon ions and water, including protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we explored the relationship between the carbon ion beam and these secondary particles. Interaction vertex imaging (IVI) proves valuable for monitoring dose distribution during carbon therapy, providing information about secondary particle locations and abundances, particularly protons. The IVI method relies on charged particles produced during ion fragmentation to gather range information by reconstructing particle trajectories back to their point of origin, known as the vertex. In the context of carbon ion therapy, our simulation results indicated a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the unique elongated geometry of the target, hindering the straightforward transmission of forward-generated protons. Consequently, the limited protons that did emerge predominantly originated from points close to the target entrance. Fragment (protons) trajectories were approximated as straight lines, and a beam back-projection algorithm, utilizing interaction positions recorded in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitor secondary proton doses, interaction vertex imaging

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