Search results for: wireless network security

Authors: Nazaitul Idya Hamzah, Muhammad Syafiq Mazli, Maszatul Akmar Mustafa

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The peak demand forecast is crucial to identify the future generation plant up needed in the long-term capacity planning analysis for Peninsular Malaysia as well as for the transmission and distribution network planning activities. Currently, peak demand forecast (in Mega Watt) is derived from the generation forecast by using load factor assumption. However, a forecast using this method has underperformed due to the structural changes in the economy, emerging trends and weather uncertainty. The dynamic changes of these drivers will result in many possible outcomes of peak demand for Peninsular Malaysia. This paper will look into the independent model of peak demand forecasting. The model begins with the selection of driver variables to capture long-term growth. This selection and construction of variables, which include econometric, emerging trend and energy variables, will have an impact on the peak forecast. The actual framework begins with the development of system energy and load shape forecast by using the system’s hourly data. The shape forecast represents the system shape assuming all embedded technology and use patterns to continue in the future. This is necessary to identify the movements in the peak hour or changes in the system load factor. The next step would be developing the peak forecast, which involves an iterative process to explore model structures and variables. The final step is combining the system energy, shape, and peak forecasts into the hourly system forecast then modifying it with the forecast adjustments. Forecast adjustments are among other sales forecasts for electric vehicles, solar and other adjustments. The framework will result in an hourly forecast that captures growth, peak usage and new technologies. The advantage of this approach as compared to the current methodology is that the peaks capture new technology impacts that change the load shape.

Keywords: hourly load profile, load forecasting, long term peak demand forecasting, peak demand

Procedia PDF Downloads 161

Authors: Chuan Yang, Jing Bie, Yueh-Lung Lin, Zhong Wang

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Transportation planning is an academic integration discipline combining research and practice with the aim of mobility and accessibility improvements at both strategic-level policy-making and operational dimensions of practical planning. Transportation planning could build the linkage between traffic and social development goals, for instance, economic benefits and environmental sustainability. The transportation planning analysis and evaluation tend to apply empirical quantitative approaches with the guidance of the fundamental principles, such as efficiency, equity, safety, and sustainability. Space syntax theory has been applied in the spatial distribution of pedestrian movement or vehicle flow analysis, however rare has been written about its application in transportation planning. The correlated relationship between the variables of space syntax analysis and authentic observations have declared that the urban configurations have a significant effect on urban dynamics, for instance, land value, building density, traffic, crime. This research aims to explore the potentials of applying Space Syntax methodology to evaluate urban transportation planning through studying the effects of urban configuration on cities transportation performance. By literature review, this paper aims to discuss the effects that urban configuration with different degrees of integration and accessibility have on three elementary components of transportation planning - transportation efficiency, transportation safety, and economic agglomeration development - via intensifying and stabilising the nature movements generated by the street network. And then the potential and limits of Space Syntax theory to study the performance of urban transportation and transportation planning would be discussed in the paper. In practical terms, this research will help future research explore the effects of urban design on transportation performance, and identify which patterns of urban street networks would allow for most efficient and safe transportation performance with higher economic benefits.

Keywords: transportation planning, space syntax, economic agglomeration, transportation efficiency, transportation safety

Procedia PDF Downloads 192

Authors: V. Thomas, O. Delaune, W. Hennig, S. Hoover

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Measurement of radioactive isotopes of atmospheric xenon is used to detect, locate and identify any confined nuclear tests as part of the Comprehensive Nuclear Test-Ban Treaty (CTBT). In this context, the Alternative Energies and French Atomic Energy Commission (CEA) has developed a fixed device to continuously measure the concentration of these fission products, the SPALAX process. During its atmospheric transport, the radioactive xenon will undergo a significant dilution between the source point and the measurement station. Regarding the distance between fixed stations located all over the globe, the typical volume activities measured are near 1 mBq m⁻³. To avoid the constraints induced by atmospheric dilution, the development of a mobile detection system is in progress; this system will allow on-site measurements in order to confirm or infringe a suspicious measurement detected by a fixed station. Furthermore, this system will use beta/gamma coincidence measurement technique in order to drastically reduce environmental background (which masks such activities). The detector prototype consists of a gas cell surrounded by two large silicon wafers, coupled with two square NaI(Tl) detectors. The gas cell has a sample volume of 30 cm³ and the silicon wafers are 500 µm thick with an active surface area of 3600 mm². In order to minimize leakage current, each wafer has been segmented into four independent silicon pixels. This cell is sandwiched between two low background NaI(Tl) detectors (70x70x40 mm³ crystal). The expected Minimal Detectable Concentration (MDC) for each radio-xenon is in the order of 1-10 mBq m⁻³. Three 4-channels digital acquisition modules (Pixie-NET) are used to process all the signals. Time synchronization is ensured by a dedicated PTP-network, using the IEEE 1588 Precision Time Protocol. We would like to present this system from its simulation to the laboratory tests.

Keywords: beta/gamma coincidence technique, low level measurement, radioxenon, silicon pixels

Procedia PDF Downloads 121

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 214

Authors: M. Moreno, M. Alique, D. Otero, C. Delgado, P. Lacharmoise, L. Gracia, L. Pires, A. Moya

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Marine environments are increasingly threatened by heavy metal contamination, including mercury (Hg), lead (Pb), and cadmium (Cd), posing significant risks to ecosystems and human health. Traditional monitoring techniques often fail to provide the spatial and temporal resolution needed for real-time detection of these contaminants, especially in remote or harsh environments. SEAWIZARD addresses these challenges by leveraging the flexibility, adaptability, and cost-effectiveness of printed electronics, with the integration of microfluidics to develop a compact, portable, and reusable sensor platform designed specifically for real-time monitoring of heavy metal ions in seawater. The SEAWIZARD sensor is a multiparametric Lab-on-Chip (LoC) device, a miniaturized system that integrates several laboratory functions into a single chip, drastically reducing sample volumes and improving adaptability. This platform integrates three printed graphene electrodes for the simultaneous detection of Hg, Cd and Pb via square wave voltammetry. These electrodes share the reference and the counter electrodes to improve space efficiency. Additionally, it integrates printed pH and temperature sensors to correct environmental interferences that may impact the accuracy of metal detection. The pH sensor is based on a carbon electrode with iridium oxide electrodeposited while the temperature sensor is graphene based. A protective dielectric layer is printed on top of the sensor to safeguard it in harsh marine conditions. The use of flexible polyethylene terephthalate (PET) as the substrate enables the sensor to conform to various surfaces and operate in challenging environments. One of the key innovations of SEAWIZARD is its integrated microfluidic layer, fabricated from cyclic olefin copolymer (COC). This microfluidic component allows a controlled flow of seawater over the sensing area, allowing for significant improved detection limits compared to direct water sampling. The system’s dual-channel design separates the detection of heavy metals from the measurement of pH and temperature, ensuring that each parameter is measured under optimal conditions. In addition, the temperature sensor is finely tuned with a serpentine-shaped microfluidic channel to ensure precise thermal measurements. SEAWIZARD also incorporates custom electronics that allow for wireless data transmission via Bluetooth, facilitating rapid data collection and user interface integration. Embedded artificial intelligence further enhances the platform by providing an automated alarm system, capable of detecting predefined metal concentration thresholds and issuing warnings when limits are exceeded. This predictive feature enables early warnings of potential environmental disasters, such as industrial spills or toxic levels of heavy metal pollutants, making SEAWIZARD not just a detection tool, but a comprehensive monitoring and early intervention system. In conclusion, SEAWIZARD represents a significant advancement in printed electronics applied to environmental sensing. By combining flexible, low-cost materials with advanced microfluidics, custom electronics, and AI-driven intelligence, SEAWIZARD offers a highly adaptable and scalable solution for real-time, high-resolution monitoring of heavy metals in marine environments. Its compact and portable design makes it an accessible, user-friendly tool with the potential to transform water quality monitoring practices and provide critical data to protect marine ecosystems from contamination-related risks.

Keywords: lab-on-chip, printed electronics, real-time monitoring, microfluidics, heavy metal contamination

Procedia PDF Downloads 12

Authors: M. Ntšolo, D. Kalumba, N. Lefu, G. Letlatsa

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Rock mass damage due to shear tectonic activity has been investigated largely in geoscience where fluid transport is of major interest. However, little has been studied on the effect of shear zones on rock mass behavior and its impact on stability of rock slopes. At Letšeng Diamonds open pit mine in Lesotho, the shear zone composed of sheared kimberlite material, calcite and altered basalt is forming part of the haul ramp into the main pit cut 3. The alarming rate at which the shear zone is deteriorating has triggered concerns about both local and global stability of pit the walls. This study presents the numerical modelling of the open pit slope affected by shear zone at Letšeng Diamond Mine (LDM). Analysis of the slope involved development of the slope model by using a two-dimensional finite element code RS2. Interfaces between shear zone and host rock were represented by special joint elements incorporated in the finite element code. The analysis of structural geological mapping data provided a good platform to understand the joint network. Major joints including shear zone were incorporated into the model for simulation. This approach proved successful by demonstrating that continuum modelling can be used to evaluate evolution of stresses, strain, plastic yielding and failure mechanisms that are consistent with field observations. Structural control due to geological shear zone structure proved to be important in its location, size and orientation. Furthermore, the model analyzed slope deformation and sliding possibility along shear zone interfaces. This type of approach can predict shear zone deformation and failure mechanism, hence mitigation strategies can be deployed for safety of human lives and property within mine pits.

Keywords: numerical modeling, open pit mine, shear zone, slope stability

Procedia PDF Downloads 294

Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto

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The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.

Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC

Procedia PDF Downloads 131

Authors: Piyush Hajela

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The significance of public spaces is on a rise in Indian cities as a strong interaction space across cultures and community. It is a pertinent gathering space for people across age and gender, where the face keeps changing with time. A public space is directly related to the social dimension, people, comfort, safety, and security, that, it proposes to provide, as inherent qualities. The presence of these and other dimensions of space, together with related equitable environments, impart certain quality to a public space. The higher the optimum contents of these dimensions, the better the quality of public space. Public is represented by PEOPLE through society and community, and space is created by dimensions. Society contains children, women and the elderly, community is composed of social, and religious groups. These behave differently in a different setting and call for varied quality of spaces, created and generated. Public spaces are spread across a city and have more or less established their existence and prominence in a social set up. While few of them are created others are discovered by the people themselves in their constant search for desirable interactive public spaces. These are the most sought after gathering spaces that have the quality of promoting social interaction, providing free accessibility, provide desirable scale etc. The emergence of public space dates back to the times when people started forming communities, display cultures and traditions publicly, gathered for religious observations and celebrations, and address the society. Traditional cities and societies in India were feudal and orthodox in their nature and yet had public spaces. When the gathering of people at one point in a city became more frequent the point became more accessible and occupied. Baras (large courts, Chowks (public squares) and Maidans (large grounds) became well-known gathering spaces in the towns and cities. As the population grew such points grew in number, each becoming a public space in itself and with a different and definite social character. The author aims at studying the various dimensions of public spaces with which a public space has power to hold people for a significant period of time. The human senses here are note referred to as taste, sight, hearing, touch or smell, but how human senses collectively respond to when stationed in a given public space. The collectives may reflect in dimensions like comfort, safety, environment, freedom etc. Various levels of similar other responses would be studied through interviews, observations and other scientific methods for both qualitative and quantitative analysis.

Keywords: society, interaction, people, accessibility, comfort, enclosure

Procedia PDF Downloads 451

Authors: Nikica Mihaljević

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Published in 2023, "Tre ciotole. Rituali per un anno di crisi" is a collection of short stories completely disconnected from one another in regard to topics and the representation of characters. However, these short stories complete and somehow continue each other in a particular way. The book happens to be Murgia's last book, as the author died a few months later after the book's publication and it appears as a kind of summary of all her previous literary works. Namely, in her previous publications, Murgia already stressed certain characters' particularities, such as solitude and alienation from others, which are at the center of attention in this literary work, too. What all the stories present in "Tre ciotole" have in common is the dealing with characters' identity and self-awareness through the challenges they confront and the way the characters live their emotions in relation to the surrounding space. Although the challenges seem similar, the spatial element around the characters is different, but it confirms each time that characters' emotions, and, consequently, their self-awareness, can be formed and built only through their connection and relation to the surrounding space. In that way, the reader creates an imaginary network of complex relations among characters in all the short stories, which gives him/her the opportunity to search for a way to break out of the usual patterns that tend to be repeated while characters focus on building self-awareness. The aim of the paper is to determine and analyze the role of spatial elements in the creation of characters' emotions and in the process of self-awareness. As the spatial element changes or gets transformed and/or substituted, in the same way, we notice the arise of the unconscious desire for self-harm in the characters, which damages their self-awareness. Namely, the characters face a crisis that they cannot control by inventing other types of crises that can be controlled. That happens to be their way of acting in order to find the way out of the identity crisis. Consequently, we expect that the results of the analysis point out the similarities in the short stories in characters' depiction as well as to show the extent to which the characters' identities depend on the surrounding space in each short story. In this way, the results will highlight the importance of spatial elements in characters' identity formation in Michela Murgia's short stories and also summarize the importance of the whole Murgia's literary opus.

Keywords: Italian literature, short stories, environment, spatial element, emotions, characters

Procedia PDF Downloads 48

Authors: Ketsada Sutthiumporn, Sittichot Thongkaw, Malee Santikunaporn

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In Thailand, biodiesel has been utilized as an attractive substitute of petroleum diesel and the government imposes a mandatory biodiesel blending requirement in transport sector to improve energy security, support agricultural sector and reduce emissions. Though biodiesel blend has many advantages over diesel fuel such as improved lubricity, low sulfur content and higher flash point, there are still some technical problems such as oxidative stability, poor cold- flow properties and impurity. Such problems were related to the fatty acid composition in feedstock. Moreover, Thailand has announced the use of low sulfur diesel as a base diesel and will be continually upgrading to EURO 5 in 2023. With ultra low sulfur content, it may affect the diesel fuel properties especially lubricity as well. Therefore, in this study, the physical and chemical properties of palm oil-based biodiesel in low sulfur diesel blends from different producers will be investigated by standard methods per ASTM and EN. Also, its economic benefits based on diesel price structure in Thailand will be highlighted. The appropriate biodiesel blend ratio can affect the physico-chemical properties and reasonable price in the country. Properties of biodiesel, including specific gravity, kinematic viscosity, FAME composition, flash point, sulfur, water, oxidation stability and lubricity were measured by standard methods of ASTM and EN. The results show that the FAME composition of biodiesel has the fatty acid of C12:0 to C20:1, mostly in C16:0, C18:0, C18:1, and C18:2, which were main characteristic compositions of palm biodiesel. The physical and chemical properties of biodiesel blended diesel was found to be increases with an increasing amount of biodiesel such as specific gravity, flash point and kinematic viscosity while sulfur value was decreased. Moreover, in this study, the various properties of each biodiesel blends were plotted to determine the appropriate proportional range of biodiesel-blended diesel with an optimum fuel price.It can be seen that the amount of B100 can be filled from 1% up to 7% in which the quality was in accordance with Notification of the department of Energy business.The understanding of relation between physico-chemical properties of palm oil-based biodiesel and pricing is beneficial to guide the better development of desired feedstock in Thailand and to implement biodiesel blends with comparative price and diesel engine performance.

Keywords: fatty acid methyl ester, biodiesel, fuel price structure, palm oil in Thailand

Procedia PDF Downloads 112

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 122

Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) wherein the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation and Control design team. This paper discusses the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), steady state, transient state

Procedia PDF Downloads 258

Authors: Md. Samim Hossain Molla, Md. Mazharul Anwar, Md. Akkas Ali, Mian Sayeed Hassan

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Being detached about 68 years from the mainland, the previous enclaves’ (Chhitmohal) farmers were engaged only in subsistence farming with low agricultural productivity and restricted access to inputs technology. To increase crop productivity for attaining food security by addressing soil status, the experiments were undertaken in 2017 and 2018 in three previous enclaves of Northern Bangladesh i.e. Dasiarchhara of Kurigram district; Dahalakhagrabari of Panchagarh district and Banskata of Lalmonirhat district under On-Farm Research Division, Bangladesh Agricultural Research Institute, Rangpur. The Mustard (var. BARI Sarisha-14)-Boro rice (var. BRRI dhan58)-T. Aman rice (var. BRRI dhan49) cropping pattern using soil test based (STB) fertilizer with cowdung (T1) or recommended fertilizer dose (T2) were tested against existing cropping pattern Fallow-Boro rice (var. BRRI dhan28)-T. Aman rice (var. Swarna) using farmers’ practices fertilizer dose (T3) in six disperse replications at each location maintaining Randomized Complete Block design. Almost all crops yields were relatively higher in T1 followed by T2. Farmers existing pattern with local varieties and imbalance fertilizer (T3) use may be decreased the crop yield. The rice equivalent yield of T1 was 109, 103 and 95% higher than T3 and the gross margin was 164, 153 and 133% higher in T1 than T3 at Dasiarchhara, Dahalakhagrabari and Banskata, respectively. The Benefit Cost Ratio for T1, T2 and T3 were 1.99, 1.78 and 1.28 in Dasiarchhara; 1.93, 1.81 and 1.27 in Dahalakhagrabari and 1.78, 1.71 and 1.25 in Banskata, respectively. There was a remarkable decrease in mineral N, P and K in the topsoil (0–15 cm) of T3 and T2 treatments at Dasiarchhara and Dahalakhagrabari, and a generally less marked decline under the same treatments at Banskata. The same practices (T1) exhibited the greatest nutrients uptake by the test crops. The apparent balance of N, P and K was negative in most cases, where it was less negative in T1 treatment. However, from the experimentation, it is revealed that balanced fertilization (STB) and inclusion of National Agricultural Research Institutes developed improved crops varieties in cropping pattern may increase the crop productivity, farm efficiency and farmer’s income in a remarkable level.

Keywords: cropping pattern, fertilizer management, nutrient balance, previous enclaves

Procedia PDF Downloads 139

Authors: Parisa Afshin, Terje Grønning

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Norway, similar to many other countries, has set the focus of its policies in creating new strong and highly innovative sectors in recent years, as the oil and gas sector profitability is declining. Biotechnology sector in Norway has a great potential, especially in marine-biotech and cancer medicine. However, Norway being a periphery faces especial challenges in the path of creating internationally well-known biotech sector and an international knowledge hub. The aim of this article is to analyze the progress of the Norwegian biotechnology industry, its pathway to build up an innovation network and conduct collaborative innovation based on its initial conditions and its own advantage and disadvantages. The findings have important implications not only for politicians and academic in understanding the infrastructure of biotechnology sector in the country, but it has important lessons for other periphery countries or regions aiming in creating strong biotechnology sector and catching up with the strong internationally-recognized regions. Data and methodology: To achieve the main goal of this study, information has been collected via secondary resources such as web pages and annual reports published by the officials and mass media along with interviews were used. The data were collected with the goal to shed light on a brief history and current status of Norway biotechnology sector, as well as geographic distribution of biotech industry, followed by the role of academic and industry collaboration and public policies in Norway biotech. As knowledge is the key input in innovation, knowledge perspective of the system such as knowledge flow in the sector regarding the national and regional innovation system has been studied. Primary results: The internationalization has been an important element in development of periphery regions' innovativeness enabling them to overcome their weakness while putting more weight on the importance of regional policies. Following such findings, suggestions on policy decision and international collaboration, regarding national and regional system of innovation, has been offered as means of promoting strong innovative sector.

Keywords: biotechnology sector, knowledge-based industry, national innovation system, regional innovation system

Procedia PDF Downloads 219

Authors: Sameer Masood, Lucas Chartier

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Head injuries are a commonly encountered presentation in emergency departments (ED) and the Choosing Wisely Canada (CWC) campaign was released in June 2015 in an attempt to decrease imaging utilization for patients with minor head injuries. The impact of the CWC campaign on imaging utilization for head injuries has not been explored in the ED setting. In our study, we describe the characteristics of patients with head injuries presenting to a tertiary care academic ED and the impact of the CWC campaign on CT head utilization. This retrospective cohort study used linked databases from the province of Ontario, Canada to assess emergency department visits with a primary diagnosis of head injury made between June 1, 2014 and Aug 31, 2016 at the University Health Network in Toronto, Canada. We examined the number of visits during the study period, the proportion of patients that had a CT head performed before and after the release of the CWC campaign, as well as mode of arrival, and disposition. There were 4,322 qualifying visits at our site during the study period. The median presenting age was 44.12 years (IQR 27.83,67.45), the median GCS was 15 (IQR 15,15) and the majority of patients presenting had intermediate acuity (CTAS 3). Overall, 43.17% of patients arrived via ambulance, 49.24 % of patients received a CT head and 10.46% of patients were admitted. Compared to patients presenting before the CWC campaign release, there was no significant difference in the rate of CT heads after the CWC (50.41% vs 47.68%, P = 0.07). There were also no significant differences between the two groups in mode of arrival (ambulance vs ambulatory) (42.94% vs 43.48%, P = 0.72) or admission rates (9.85% vs 11.26%, P = 0.15). However, more patients belonged to the high acuity groups (CTAS 1 or 2) in the post CWC campaign release group (12.98% vs 8.11% P <0.001). Visits for head injuries make up a significant proportion of total ED visits and approximately half of these patients receive CT imaging in the ED. The CWC campaign did not seem to impact imaging utilization for head injuries in the 14 months following its launch. Further efforts, including local quality improvement initiatives, are likely needed to increase adherence to its recommendation and reduce imaging utilization for head injuries.

Keywords: choosing wisely, emergency department, head injury, quality improvement

Procedia PDF Downloads 220

Authors: Oyatayo Kehinde Taofik, Ndabula Christopher

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Drainage basins are a central theme in the green economy. The rising challenges in flooding, erosion or sediment transport and sedimentation threaten the green economy. This has led to increasing emphasis on quantitative analysis of drainage basin parameters for better understanding, estimation and prediction of fluvial responses and, thus associated hazards or disasters. This can be achieved through direct measurement, characterization, parameterization, or modeling. This study applied the Remote Sensing and Geographic Information System approach of parameterization and characterization of the morphometric variables of Katsina – Ala basin using a 30 m resolution Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM). This was complemented with topographic and hydrological maps of Katsina-Ala on a scale of 1:50,000. Linear, areal and relief parameters were characterized. The result of the study shows that Ala and Udene sub-watersheds are 4th and 5th order basins, respectively. The stream network shows a dendritic pattern, indicating homogeneity in texture and a lack of structural control in the study area. Ala and Udene sub-watersheds have the following values for elongation ratio, circularity ratio, form factor and relief ratio: 0.48 / 0.39 / 0.35/ 9.97 and 0.40 / 0.35 / 0.32 / 6.0. They also have the following values for drainage texture and ruggedness index of 0.86 / 0.011 and 1.57 / 0.016. The study concludes that the two sub-watersheds are elongated, suggesting that they are susceptible to erosion and, thus higher sediment load in the river channels, which will dispose the watersheds to higher flood peaks. The study also concludes that the sub-watersheds have a very coarse texture, with good permeability of subsurface materials and infiltration capacity, which significantly recharge the groundwater. The study recommends that efforts should be put in place by the Local and State Governments to reduce the size of paved surfaces in these sub-watersheds by implementing a robust agroforestry program at the grass root level.

Keywords: erosion, flood, mitigation, morphometry, watershed

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Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

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Authors: Chang Liu, Nuria Fiol, Isabel Villaescusa, Jordi Poch

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Over the last decades, biosorption has been an alternative to costly wastewaters treatment for metal removal. Most of the literature on metal biosorption was devoted to studying of single metal ions but nowadays studies on multi-components biosorption are booming. Hexavalent chromium is usually found in mixtures with divalent metal ions in industries wastewaters. However, studies on the simultaneous removal of Cr(VI) and divalent metals are hardly found and the cooperative or competitive mechanism governing each metal ions sorption is still unclear. In this work, simultaneous sorption of Cr(VI) and Cu(II) from their binary mixtures by using sweet potato vine (SPV) was investigated. Sweet potato is one of the four major grain crops in China. Each year about 2000 tons of SPV are generated as by-products. SPV could be a low-cost biosorbent for metal ions due to its rich in cellulose and lignin. In this work, the sorption of Cr(VI) and Cu(II) from their binary mixtures solutions was studied by using SPV sorbent. Equilibrium studies were carried out in binary mixtures in which Cr(VI) and Cu(II) concentration was both varied between 0.1 mM and 0.3 mM, Cr(VI) and Cu(II) single solutions were also prepared as comparison. All the experiments were performed at pH 3±0.05 under 30±2°C for 7 days to make sure sorption achieved equilibrium. Results showed that (i) chromium was partially (10.93%-42.04%) eliminated under studied conditions through reduction and sorption of hexavalent and trivalent forms. The presence of Cu(II) exerts a synergistic effect on the overall sorption process in all the cases of the 0.1-0.3 mM binary mixtures concentration range. (ii) Cr(VI) removal by SPV is favoured by the presence of Cu(II) in solution, because more protons needed for Cr(VI) reduction are available due to Cu(II)-proton competition; however sorption of the formed Cr(III) is unfavoured as a result of the competition between Cr(III) and Cu(II) for protons and sorbent active sites. (iii) Copper was partially (9.26%-13.91%) sorbed onto SPV under studied conditions. The presence of Cr(VI) in binary mixtures also exerts a synergistic effect on the Cu(II) removal in all the cases of the 0.1-0.3 mM binary mixtures concentration range. The results of the present work indicate that sweet potato vine can be successfully employed for the simultaneously removal of Cr(VI) and Cu(II) in binary mixtures, taking advantage of the synergistic effect provoked by one of the metal ion to each other, even though the acquisition of higher removal yields has to be further investigated. Acknowledgements—This work has been financially supported by Ministry of Human Resources and Social Security of PRC (Anhui15), Education Department of Anhui Province (KJ2016A270) and Anhui Normal University (2015rcpy33, 2014bsqdjj53).

Keywords: sweet potato vine, chromium reduction, divalent metal, synergistic sorption

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Authors: Muhammad Abid

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The ultimate goal of this research was to produce a cold galvanizing compound (CGC) at reduced pigment volume concentration (PVC) to protect metallic structures from corrosion. The influence of the partial replacement of Zn dust by nano-layered graphene (NGr) and Zn metal nanoparticles on the electrochemical, morphological, rheological, and mechanical properties of CGC was investigated. EIS was used to explore the electrochemical nature of coatings. The EIS results revealed that the partial replacement of Zn by NGr and Zn nanoparticles enhanced the cathodic protection at reduced PVC (4:1) by improving the electrical contact between the Zn particles and the metal substrate. The Tafel scan was conducted to support the cathodic behaviour of the coatings. The sample formulated solely with Zn at PVC 4:1 was found to be dominated in physical barrier characteristics over cathodic protection. By increasing the concentration of NGr in the formulation, the corrosion potential shifted towards a more negative side. The coating with 1.5% NGr showed the highest galvanic action at reduced PVC. FE-SEM confirmed the interconnected network of conducting particles. The coating without NGr and Zn nanoparticles at PVC 4:1 showed significant gaps between the Zn dust particles. The novelty was evidenced when micrographs showed the consistent distribution of NGr and Zn nanoparticles all over the surface, which acted as a bridge between spherical Zn particles and provided cathodic protection at a reduced PVC. The layered structure of graphene also improved the physical shielding effect of the coatings, which limited the diffusion of electrolytes and corrosion products (oxides/hydroxides) into the coatings, which was reflected by the salt spray test. The rheological properties of coatings showed good liquid/fluid properties. All the coatings showed excellent adhesion but had different strength values. A real-time scratch resistance assessment showed all the coatings had good scratch resistance.

Keywords: protective coatings, anti-corrosion, galvanization, graphene, nanomaterials, polymers

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Authors: M. S. Aparna, Pushparaj Shetty D.

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Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

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Authors: Siti Napsiyah, Ismet Firdaus, Lisma Dyawati Fuaida, Ellies Sukmawati

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This paper examines the existence, role, and challenge of Family Service Agency, in Bahasa Indonesia known as Lembaga Konsultasi Kesejahteraan Keluarga (LK3) of Syarif Hidayatullah State Islamic University (UIN) Jakarta. It has been established since 2012. It is an official agency under the Ministry of Social Affairs of Indonesia. The establishment of LK3 aims to provide psychosocial services for families of students who has psychosocial problem in their life. The study also aims to explore the trend of psychosocial problems of its client (student) for the past three years (2014-2016). The research method of the study is using a qualitative social work research method. A review of selected data of the client of LK3 UIN Syarif Hidayatullah Jakarta around five main issues: Family background, psychosocial mapping, potential resources, student coping mechanism strategy, client strength and network. The study also uses a review of academic performance report as well as an interview and observation. The findings show that the trend of psychosocial problems of the client of LK3 UIN Syarif Hidayatullah Jakarta vary as follow: bad academic performance, low income family, broken home, domestic violence, disability, mental disorder, sexual abuse, and the like. LK3 UIN Syarif Hidayatullah Jakarta has significant roles to provide psychosocial support and services for the survival of the students to deal with their psychosocial problems. Social worker of LK3 performs indigenous social work practice: individual counseling, family counseling, group therapy, home visit, case conference, Islamic Spiritual Approach, and Spiritual Emotional Freedom Technique (SEPT).

Keywords: psychosocial, indigenizing social work, resiliency, coping mechanism

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Authors: Maria Campos, Alain Massart, Hugo Sarmento

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The Meter Matters Erasmus Sport European Project (ID: 101050372) explores the field of social inclusion in and through sports with the aim of a) proposing appropriate criteria for co-funding sports programs involving people with intellectual and developmental disabilities and other more vulnerable people, primarily in mainstream sports organizations and b) proposing a model for co-funding social inclusion in and through sports at the national level. This European project (2022-2024) involves 6 partners from 3 countries: Univerza V Ljubljani – coordinator and Drustvo Specialna Olimpiada Slovenije (Slovenia); Magyar Specialis Olimpia Szovetseg and Magyar Testnevelesi Es Sporttudomanyi Egyetem (Hungary) and APPDA Coimbra - Associação Portuguesa para as Perturbações do Desenvolvimento e Autismo and Universidade De Coimbra, Faculty of Sport Sciences and Physical Education (Portugal). Equal involvement of all people in sports activities is, in terms of national and international guidelines, enshrined in some conventions and strategies in the field of sports, as well as human rights, social security, physical and mental health, architecture, environment and public administration. However, there is a gap between the practice and EU guidelines in terms of sustainable support for socially inclusive sports programs in the form of co-funding by state and local (municipal) resources. We observe considerable opacity in the regulation of the field. Given that there are both relevant programs and inclusive legislation and policies, we believe that the reason for the missing article is reflected in the undeveloped criteria for measuring social inclusion in sports. Major sports programs are usually co-funded based on crowds (number of involved athletes) and performance (sports score). In the field of social inclusion in sports, the criteria cannot be the same, as it is a smaller population. Therefore, the goals of inclusion in sports should not be the focused on competitive results but on opening equal opportunities for all, regardless of their psychophysical abilities. In the Meter Matters program, we are searching for criteria for co-funding social inclusion in sports through focus groups with coaches, social workers, psychologists and others professionals involved in inclusive sports programs in regular sports clubs and with athletes and their parents or guardians. Moreover, experts in the field of social inclusion in sports were also interviewed. Based on the proposals for measuring social inclusion in sports, we developed a model for co-funding socially inclusive sports programs.

Keywords: European project, meter matters, inclusion, sport

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Authors: Mahera Abdulrahman, Satish Chandrasekhar Nair

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Growing demand for human health research in the United Arab Emirates (UAE) has prompted the need to develop a robust research ethics oversight, particularly given the large unskilled-worker immigrant population and the elderly citizens utilizing health services. Examination of the structure, function, practices and outcomes of the human research ethics committees (HREC) was conducted using two survey instruments, reliable and validated. Results indicate that in the absence of a national ethics regulatory body, the individual emirate’s governed 21 HRECs covering health facilities and academic institutions in the UAE. Among the HRECs, 86% followed International Council for Harmonization-Good Clinical Practice guidelines, 57% have been in operation for more than five years, 81% reviewed proposals within eight weeks, 48% reviewed for clinical and scientific merit apart from ethics, and 43% handled more than 50 research proposals per year. However, researcher recognition, funding transparency, adverse event reporting systems were widespread in less than one-third of all HRECs. Surprisingly, intellectual property right was not included as a research output. Research was incorporated into the vision and mission statements of many (62%) organizations and, mechanisms such as research publications, collaborations, and recognitions were employed as key performance indicators to measure research output. In spite, resources to generate research output such as dedicated budget (19%), support staff (19%) and continuous training and mentoring program for medical residents and HREC members were somehow lacking. HREC structure and operations in the UAE are similar to other regions of the world, resources allocation for efficient, quality monitoring, continuous training, and the creation of a clinical research network are needed to strengthen the clinical research enterprise to scale up for the future. It is anticipated that the results of this study will benefit investigators, regulators, pharmaceutical sponsors and the policy makers in the region.

Keywords: institutional review board, ethics committee, human research ethics, United Arab Emirates (UAE)

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Authors: Nicholas S. Norbert Jr., John E. Bischoff, Christopher J. Willy

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Knowledge Management (KM) is globally recognized as a crucial element in securing competitive advantage through building and maintaining organizational memory, codifying and protecting intellectual capital and business intelligence, and providing mechanisms for collaboration and innovation. KM frameworks and approaches have been developed and defined identifying critical success factors for conducting KM within numerous industries ranging from scientific to business, and for ranges of organization scales from small groups to large enterprises. However, engineering and technical teams operating within restricted environments are subject to unique barriers and KM challenges which cannot be directly treated using the approaches and tools prescribed for other industries. This research identifies barriers in conducting KM within Hardware Development Engineering (HDE) teams and statistically compares significance to barriers upholding the four KM pillars of organization, technology, leadership, and learning for HDE teams. HDE teams suffer from restrictions in knowledge sharing (KS) due to classification of information (national security risks), customer proprietary restrictions (non-disclosure agreement execution for designs), types of knowledge, complexity of knowledge to be shared, and knowledge seeker expertise. As KM evolved leveraging information technology (IT) and web-based tools and approaches from Web 1.0 to Enterprise 2.0, KM may also seek to leverage emergent tools and analytics including expert locators and hybrid recommender systems to enable KS across barriers of the technical teams. The research will test hypothesis statistically evaluating if KM barriers for HDE teams affect the general set of expected benefits of a KM System identified through previous research. If correlations may be identified, then generalizations of success factors and approaches may also be garnered for HDE teams. Expert elicitation will be conducted using a questionnaire hosted on the internet and delivered to a panel of experts including engineering managers, principal and lead engineers, senior systems engineers, and knowledge management experts. The feedback to the questionnaire will be processed using analysis of variance (ANOVA) to identify and rank statistically significant barriers of HDE teams within the four KM pillars. Subsequently, KM approaches will be recommended for upholding the KM pillars within restricted environments of HDE teams.

Keywords: engineering management, knowledge barriers, knowledge management, knowledge sharing

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Authors: Maja Ruzic-Baf, Vedrana Keteles, Andrea Debeljuh

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Younger and younger children are now using a smartphone, a device which has become ‘a must have’ and the life of children would be almost ‘unthinkable’ without one. Devices are becoming lighter and lighter but offering an array of options and applications as well as the unavoidable access to the Internet, without which it would be almost unusable. Numerous features such as taking of photographs, listening to music, information search on the Internet, access to social networks, usage of some of the chatting and messaging services, are only some of the numerous features offered by ‘smart’ devices. They have replaced the alarm clock, home phone, camera, tablet and other devices. Their use and possession have become a part of the everyday image of young people. Apart from the positive aspects, the use of smartphones has also some downsides. For instance, free time was usually spent in nature, playing, doing sports or other activities enabling children an adequate psychophysiological growth and development. The greater usage of smartphones during classes to check statuses on social networks, message your friends, play online games, are just some of the possible negative aspects of their application. Considering that the age of the population using smartphones is decreasing and that smartphones are no longer ‘foreign’ to children of pre-school age (smartphones are used at home or in coffee shops or shopping centers while waiting for their parents, playing video games often inappropriate to their age), particular attention must be paid to a very sensitive group, the teenagers who almost never separate from their ‘pets’. This paper is divided into two sections, theoretical and empirical ones. The theoretical section gives an overview of the pros and cons of the usage of smartphones, while the empirical section presents the results of a research conducted in three elementary schools regarding the usage of smartphones and, specifically, their usage during classes, during breaks and to search information on the Internet, check status updates and 'likes’ on the Facebook social network.

Keywords: education, smartphone, social networks, teenagers

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Authors: Luís Miguel Cabeça Marques, Alberto Manuel Martinho Vale, José Pedro Miragaia Trancoso Vaz, Ana Sofia Baptista Fernandes, Rui Alexandre de Barros Coito, Tiago Miguel Prates da Costa

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The detection and localization of hidden radioactive sources are of significant importance in countering the illicit traffic of Special Nuclear Materials and other radioactive sources and materials. Radiation portal monitors are commonly used at airports, seaports, and international land borders for inspecting cargo and vehicles. However, these equipment can be expensive and are not available at all checkpoints. Consequently, the localization of SNM and other radioactive sources often relies on handheld equipment, which can be time-consuming. The current study presents the advantages of real-time analysis of gamma-ray count rate data from a mobile radiation detection system based on simulated data and field tests. The incorporation of profit functions and decision criteria to optimize the detection system's path significantly enhances the radiation field information and reduces survey time during cargo inspection. For source position estimation, a maximum likelihood estimation algorithm is employed, and confidence intervals are derived using the Fisher information. The study also explores the impact of uncertainties, baselines, and thresholds on the performance of the profit function. The proposed detection system, utilizing a plastic scintillator with silicon photomultiplier sensors, boasts several benefits, including cost-effectiveness, high geometric efficiency, compactness, and lightweight design. This versatility allows for seamless integration into any mobile platform, be it air, land, maritime, or hybrid, and it can also serve as a handheld device. Furthermore, integration of the detection system into drones, particularly multirotors, and its affordability enable the automation of source search and substantial reduction in survey time, particularly when deploying a fleet of drones. While the primary focus is on inspecting maritime container cargo, the methodologies explored in this research can be applied to the inspection of other infrastructures, such as nuclear facilities or vehicles.

Keywords: plastic scintillators, profit functions, path planning, gamma-ray detection, source localization, mobile radiation detection system, security scenario

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Authors: Rahma Saleh Hussein Al Balushi

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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS department. This paper will describe in detail the current GIS data submission process and the journey for developing it. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, and updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) for excavation permits and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting and data alterations has also contributed to reducing the missing attributes and enhance data quality index of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the years 2017 and year 2022. Overall, concluding that by governance, asset information & GIS department can control the GIS data process; collect, properly record, and manage asset data and information within the OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

Keywords: asset management ISO55001, standard procedures process, governance, CMMS

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Authors: P. Caimmi, E. Bele, A. Abolfathi

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Lattice materials are cellular structures composed of a periodic network of beams. They offer high weight-specific mechanical properties and lend themselves to numerous weight-sensitive applications. The periodic internal structure responds to external vibrations through characteristic frequency bandgaps, making these materials suitable for the reduction of noise and vibration. However, the deviation from architectural homogeneity, due to, e.g., manufacturing imperfections, has a strong influence on the mechanical properties and vibration response of these materials. In this work, we present results on the influence of geometric imperfections on the vibration response of hexagonal lattices. Three classes of geometrical variables are used: the characteristics of the architecture (relative density, ligament length/cell size ratio), imperfection type (degree of non-periodicity, cracks, hard inclusions) and defect morphology (size, distribution). Test specimens with controlled size and distribution of imperfections are manufactured through selective laser sintering. The Frequency Response Functions (FRFs) in the form of accelerance are measured, and the modal shapes are captured through a high-speed camera. The finite element method is used to provide insights on the extension of these results to semi-infinite lattices. An updating procedure is conducted to increase the reliability of numerical simulation results compared to experimental measurements. This is achieved by updating the boundary conditions and material stiffness. Variations in FRFs of periodic structures due to changes in the relative density of the constituent unit cell are analysed. The effects of geometric imperfections on the dynamic response of periodic structures are investigated. The findings can be used to open up the opportunity for tailoring these lattice materials to achieve optimal amplitude attenuations at specific frequency ranges.

Keywords: lattice architectures, geometric imperfections, vibration attenuation, experimental modal analysis

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Authors: Adel Francis

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Most of scheduling methods and software apply the critical path logic. This logic schedule activities, apply constraints between these activities and try to optimize and level the allocated resources. The extensive use of this logic produces a complex an erroneous network hard to present, follow and update. Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic, and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. The objective of the space planning is to link the spatial and temporal aspects, promote efficient use of the site, define optimal site occupancy rates, and ensures suitable rotation of the workforce in the different spaces. The Chronographic scheduling modelling belongs to this category and models construction operations as well as their processes, logical constraints, association and organizational models, which help to better illustrate the schedule information using multiple flexible approaches. The model defined three categories of areas (punctual, surface and linear) and four different layers (space creation, systems, closing off space, finishing, and reduction of space). The Chronographical modelling is a more complete communication method, having the ability to alternate from one visual approach to another by manipulation of graphics via a set of parameters and their associated values. Each individual approach can help to schedule a certain project type or specialty. Visual communication can also be improved through layering, sheeting, juxtaposition, alterations, and permutations, allowing for groupings, hierarchies, and classification of project information. In this way, graphic representation becomes a living, transformable image, showing valuable information in a clear and comprehensible manner, simplifying the site management while simultaneously utilizing the visual space as efficiently as possible.

Keywords: building projects, chronographic modelling, CPM, critical path, precedence diagram, scheduling

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Authors: Dalma Varga, Nora Hubayne H.

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Nowadays, among the measures taken to offset the consequences of climate change, water resources management is one of the key tools, which can include excess water management. As a result of climate change’s effects and as a result of the frequent inappropriate landuse, more and more areas are affected by the excess water inundation. Hungary is located in the deepest part of the Pannonian Basin, which is exposed to water damage – especially lowland areas that are endangered by floods or excess waters. The periodical presence of excess water creates specific habitats in a given area, which have ecological, functional, and aesthetic values. Excess water inundation affects approximately 74% of Hungary’s lowland areas, of which about 46% is also under nature protection (such as national parks, protected landscape areas, nature conservation areas, Natura 2000 sites, etc.). These data prove that areas exposed to excess water inundation – which are predominantly characterized by agricultural land uses – have an important ecological role. Other research works have confirmed the presence of numerous rare and endangered plant species in drainage canals, on grasslands exposed to excess water, and on special agricultural fields with mud vegetation. The goal of this research is to define and analyze ecosystem services of areas exposed to excess water inundation. In addition to this, it is also important to determine the quantified indicators of these areas’ natural and landscape values besides the presence of protected species and the naturalness of habitats, so all in all, to analyze the various nature protections related to excess water. As a result, a practice-orientated assessment method has been developed that provides the ecological water demand, assimilates to ecological and habitat aspects, contributes to adaptive excess water management, and last but not least, increases or maintains the share of the green infrastructure network. In this way, it also contributes to reduce and mitigate the negative effects of climate change.

Keywords: ecosystem services, landscape architecture, excess water management, green infrastructure planning

Procedia PDF Downloads 307