Search results for: calibration data requirements

Authors: Mohammed Islam, Jungyong Wang, Dong Cheol Seo

Abstract:

The Smoothed Particle Hydrodynamics (SPH) method is a novel, meshless, and Lagrangian technique based numerical method that has shown promises to accurately predict the hydrodynamics of water and structure interactions in violent flow conditions. The main goal of this study is to build confidence on the versatility of the Smoothed Particle Hydrodynamics (SPH) based tool, to use it as a complementary tool to the physical model testing capabilities and support research need for the performance evaluation of ships and offshore platforms exposed to an extreme and harsh environment. In the current endeavor, an open-sourced SPH-based tool was used and validated for modeling and predictions of the hydrodynamic interactions of a 6-DOF ship and bergy bits. The study involved the modeling of a modern generic drillship and simplified bergy bits in floating and towing scenarios and in regular and irregular wave conditions. The predictions were validated using the model-scale measurements on a moored ship towed at multiple oblique angles approaching a floating bergy bit in waves. Overall, this study results in a thorough comparison between the model scale measurements and the prediction outcomes from the SPH tool for performance and accuracy. The SPH predicted ship motions and forces were primarily within ±5% of the measurements. The velocity and pressure distribution and wave characteristics over the free surface depicts realistic interactions of the wave, ship, and the bergy bit. This work identifies and presents several challenges in preparing the input file, particularly while defining the mass properties of complex geometry, the computational requirements, and the post-processing of the outcomes.

Keywords: SPH, ship and bergy bit, hydrodynamic interactions, model validation, physical model testing

Procedia PDF Downloads 121

Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

Abstract:

Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: block caving, ground penetrating radar, reflectivity, RQD

Procedia PDF Downloads 123

Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

Abstract:

Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then, the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler.

Keywords: intuitionistic fuzzy set, rough set, relational database, IF rough relational database

Procedia PDF Downloads 422

Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

Abstract:

Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

Procedia PDF Downloads 255

Authors: Andre Bechuke

Abstract:

The quality of every learning programme in Higher Education (HE) is dependent on the planning, design, and development of the curriculum decisions. These curriculum development decisions are highly influenced by the knowledge of the end-user, who are not always just the students. When curriculum experts plan, design and develop learning programmes, they always have the end-users in mind throughout the process. Without proper knowledge of the end-user(s), the design and development of a learning programme might be flawed. Curriculum experts often struggle to determine who the real end-user is. As such, it is even more challenging to establish what needs to be known about the end user that should inform the plan, design, and development of a learning programme. This research sought suggest approaches to guide curriculum experts to identify the end-user(s), taking into consideration the pressure and influence other agencies and structures or stakeholders (industry, students, government, universities context, lecturers, international communities, professional regulatory bodies) have on the design of a learning programme and the graduates of the programmes. Considering the influence of these stakeholders, which is also very important, the task of deciding who the real end-user of the learning programme becomes very challenging. This study makes use of criteria 1 and 18 of the Council on Higher Education criteria for programme accreditation to guide the process of identifying the end-users when developing a learning programme. Criterion 1 suggests that designers must ensure that the programme is consonant with the institution’s mission, forms part of institutional planning and resource allocation, meets national requirements and the needs of students and other stakeholders, and is intellectually credible. According to criterion 18, in designing a learning programme, steps must be taken to enhance the employability of students and alleviate shortages of expertise in relevant fields. In conclusion, there is hardly ever one group of end-users to be considered for developing a learning programme, and the notion that students are the end-users is not true, especially when the graduates are unable to use the qualification for employment.

Keywords: council on higher education, curriculum design and development, higher education, learning programme

Procedia PDF Downloads 66

Authors: Bahram Fathi, Mahdi Khodaparast Mashhadi, Masuod Homayounifar

Abstract:

Global awareness on energy security and climate change has created much interest in assessing energy efficiency performance. A number of previous studies have contributed to evaluate energy efficiency performance using different analytical techniques among which data envelopment analysis (DEA) has recently received increasing attention. Most of DEA-related energy efficiency studies do not consider undesirable outputs such as CO2 emissions in their modeling framework, which may lead to biased energy efficiency values. Within a joint production frame work of desirable and undesirable outputs, in this paper we construct energy efficiency performance index for measuring energy efficiency performance by using environmental DEA model with CO2 emissions. We finally apply the index proposed to assess the energy efficiency performance in OPEC over time.

Keywords: energy efficiency, environmental, OPEC, data envelopment analysis

Procedia PDF Downloads 372

Authors: Somayeh Sobati Moghadam

Abstract:

Business processes are crucial for organizations and help businesses to evaluate and optimize their performance and processes against current and future-state business goals. Outsourcing business processes to the cloud becomes popular due to a wide varsity of benefits and cost-saving. However, cloud outsourcing raises enterprise data security concerns, which must be incorporated in Business Process Model and Notation (BPMN). This paper, presents SeCloudBPMN, a lightweight extension for BPMN which extends the BPMN to explicitly support the security threats in the cloud as an outsourcing environment. SeCloudBPMN helps business’s security experts to outsource business processes to the cloud considering different threats from inside and outside the cloud. In this way, appropriate security countermeasures could be considered to preserve data security in business processes outsourcing to the cloud.

Keywords: BPMN, security threats, cloud computing, business processes outsourcing, privacy

Procedia PDF Downloads 253

Authors: Paula Lopez-Arce, Hector Altamirano, Dimitrios Rovas, James Berry, Bryan Hindle, Steven Hodgson

Abstract:

Efficient mould remediation and accurate moisture diagnostics leading to condensation and mould growth in dwellings are largely untapped. Number of factors are contributing to the rising trend of excessive moisture in homes mainly linked with modern living, increased levels of occupation and rising fuel costs, as well as making homes more energy efficient. Environmental monitoring by means of data collection though loggers sensors and survey forms has been performed in a range of buildings from different UK regions. Air and surface temperature and relative humidity values of residential areas affected by condensation and/or mould issues were recorded. Additional measurements were taken through different trials changing type, location, and position of loggers. In some instances, IR thermal images and ventilation rates have also been acquired. Results have been interpreted together with environmental key parameters by processing and connecting data from loggers and survey questionnaires, both in buildings with and without moisture issues. Monitoring exercises carried out during Winter and Spring time show the importance of developing and following accurate protocols for guidance to obtain consistent, repeatable and comparable results and to improve the performance of environmental monitoring. A model and a protocol are being developed to build a diagnostic tool with the goal of performing a simple but precise residential atmospheric moisture diagnostics to distinguish the cause entailing condensation and mould generation, i.e., ventilation, insulation or heating systems issue. This research shows the relevance of monitoring and processing environmental data to assign moisture risk levels and determine the origin of condensation or mould when dealing with a building atmospheric moisture excess.

Keywords: environmental monitoring, atmospheric moisture, protocols, mould

Procedia PDF Downloads 126

Authors: Eugen Rusu

Abstract:

The objective of the work proposed is to perform an analysis of the wave conditions in the Black Sea basin. This is especially focused on the spatial and temporal occurrences and on the dynamics of the most extreme storms in the context of the climate changes. A numerical modelling system, based on the spectral phase averaged wave model SWAN, has been implemented and validated against both in situ measurements and remotely sensed data, all along the sea. Moreover, a successive correction method for the assimilation of the satellite data has been associated with the wave modelling system. This is based on the optimal interpolation of the satellite data. Previous studies show that the process of data assimilation improves considerably the reliability of the results provided by the modelling system. This especially concerns the most sensitive cases from the point of view of the accuracy of the wave predictions, as the extreme storm situations are. Following this numerical approach, it has to be highlighted that the results provided by the wave modelling system above described are in general in line with those provided by some similar wave prediction systems implemented in enclosed or semi-enclosed sea basins. Simulations of this wave modelling system with data assimilation have been performed for the 30-year period 1987-2016. Considering this database, the next step was to analyze the intensity and the dynamics of the higher storms encountered in this period. According to the data resulted from the model simulations, the western side of the sea is considerably more energetic than the rest of the basin. In this western region, regular strong storms provide usually significant wave heights greater than 8m. This may lead to maximum wave heights even greater than 15m. Such regular strong storms may occur several times in one year, usually in the wintertime, or in late autumn, and it can be noticed that their frequency becomes higher in the last decade. As regards the case of the most extreme storms, significant wave heights greater than 10m and maximum wave heights close to 20m (and even greater) may occur. Such extreme storms, which in the past were noticed only once in four or five years, are more recent to be faced almost every year in the Black Sea, and this seems to be a consequence of the climate changes. The analysis performed included also the dynamics of the monthly and annual significant wave height maxima as well as the identification of the most probable spatial and temporal occurrences of the extreme storm events. Finally, it can be concluded that the present work provides valuable information related to the characteristics of the storm conditions and on their dynamics in the Black Sea. This environment is currently subjected to high navigation traffic and intense offshore and nearshore activities and the strong storms that systematically occur may produce accidents with very serious consequences.

Keywords: Black Sea, extreme storms, SWAN simulations, waves

Procedia PDF Downloads 229

Authors: Ram Moorat Singh, Arun Kumar Sharma, Ravi Chaurey

Abstract:

Assessment of characteristics of Himalayan glaciers with or without glacier lakes was carried out for 1937glaciers of Kosi sub-basin, Ganga basin by using remote sensing and GIS techniques. Analysis of IRS-P6 AWiFS Data of 2004-07 periods, SRTM DEM and MODIS Land Surface Temperature (LST) data (15year mean) using image processing and GIS tools has provided significant information on various glacier parameters. The glacier area, length, width, ice exposed area, debris cover area, glacier slope, orientation, elevation and temperature data was analysed. The 119 supra glacier lakes and 62 moraine dam/peri-glacier lakes (area > 0.02 km2) in the study were studied to discern the suitable glacier conditions for glacier lake formation. On analysis it is observed that the glacial lakes are preferably formed in association with large dimension glaciers (area, length and width), glaciers with higher percent ice exposed area, lower percent debris cover area and in general mean elevation value greater than 5300 m amsl. On analysis of lake type shows that the moraine dam lakes are formed associated with glaciers located at relatively higher altitude as compared to altitude of glaciers with supra glacier lakes. Analysis of frequency of occurrence of lakes vis a vis glacier orientation shows that more number of glacier lakes are formed associated with glaciers having orientation south, south east, south west, east and west directions. The supra glacial lakes are formed in association with glaciers having higher mean temperature as compared to moraine dam lakes as verified using LST data of 15 years (2000-2014).

Keywords: remote sensing, supra glacial lake, Himalaya, Kosi sub-basin, glaciers, moraine-dammed lake

Procedia PDF Downloads 357

Authors: Àidan Higgins

Abstract:

Higher education will be crucial in the coming decades in helping to make Ireland a nation is known for innovation, competitive enterprise, and ongoing academic success, as well as a desirable location to live and work with a high quality of life, vibrant culture, and inclusive social structures. Higher education institutions will actively connect with each student community, society, and business; they will help students develop a sense of place and identity in Ireland and provide the tools they need to contribute significantly to the global community. It will also serve as a catalyst for novel ideas through research, many of which will become the foundation for long-lasting inventive businesses in the future as part of the 2030 National Strategy on Education focuses on change and developing our education system with a focus on how we carry out Research. The emphasis is central to knowledge transfer and a consistent research framework with exploiting opportunities and having the necessary expertise. The newly formed Technological Universities (TU) in Ireland are based on a government initiative to create a new type of higher education institution that focuses on applied and industry-focused research and education. The basis of the TU is to bring together two or more existing institutes of technology to create a larger and more comprehensive institution that offers a wider range of programs and services to students and industry partners. The TU model aims to promote collaboration between academia, industry, and community organizations to foster innovation, research, and economic development. The TU model also aims to enhance the student experience by providing a more seamless pathway from undergraduate to postgraduate studies, as well as greater opportunities for work placements and engagement with industry partners. Additionally, the TUs are designed to provide a greater emphasis on applied research, technology transfer, and entrepreneurship, with the goal of fostering innovation and contributing to economic growth. A project is a collection of organised tasks carried out precisely to produce a singular output (product or service) within a given time frame. Project management is a set of activities that facilitates the successful implementation of a project. The significant differences between research and development projects are the (lack of) precise requirements and (the inability to) plan an outcome from the beginning of the project. The evaluation criteria for a research project must consider these and other "particularities" in works; for instance, proving something cannot be done may be a successful outcome. This study intends to explore how a newly established multi-campus technological university manages research projects effectively. The study will identify the potential and difficulties of managing research projects, the tools, resources and processes available in a multi-campus Technological University context and the methods and approaches employed to deal with these difficulties. Key stakeholders like project managers, academics, and administrators will be surveyed as part of the study, which will also involve an explorative investigation of current literature and data. The findings of this study will contribute significantly to creating best practices for project management in this setting and offer insightful information about the efficient management of research projects within a multi-campus technological university.

Keywords: project management, research and research-related projects, multi-campus technology university, processes

Procedia PDF Downloads 46

Authors: A. Farhad Sadri, B. Ali Farhadi, C. Nasim Shalamzari

Abstract:

Waste management is a principle of urban and environmental governance. Waste management in Tehran metropolitan requires good strategies for better governance. Using of good urban governance principles together with eight main indexes can be an appropriate base for this aim. One of the reasonable tools in this field is usage of SWOT methods which provides possibility of comparing the opportunities, threats, weaknesses, and strengths by using IFE and EFE matrixes. The results of the above matrixes, respectively 2.533 and 2.403, show that management system of Tehran metropolitan wastes has performed weak regarding to internal factors and has not have good performance regarding using the opportunities and dealing with threats. In this research, prioritizing and describing the real value of each 24 strategies in waste management in Tehran metropolitan have been surveyed considering good governance derived from Quantitative Strategic Planning Management (QSPM) by using Kolomogrof-Smirnoff by 1.549 and significance level of 0.073 in order to define normalization of final values and all of the strategies utilities and Variance Analysis of ANOVA has been calculated for all SWOT strategies. Duncan’s test results regarding four WT, ST, WO, and SO strategies show no significant difference. In addition to mean comparison by Duncan method in this research, LSD (Lowest Significant Difference test) has been used by probability of 5% and finally, 7 strategies and final model of Tehran metropolitan waste management strategy have been defined. Increasing the confidence of people with transparency of budget, developing and improving the legal structure (rule-oriented and law governance, more responsibility about requirements of private sectors, increasing recycling rates and real effective participation of people and NGOs to improve waste management (contribution) and etc, are main available strategies which have been achieved based on good urban governance management principles.

Keywords: waste, strategy, environmental management, urban good governance, SWOT

Procedia PDF Downloads 302

Authors: Bahram Fathi, Karim Alizadeh, Azam Mohammadbagheri

Abstract:

The aim of this paper is to investigate the role of oil price shocks in explaining business cycles in Iran using a dynamic stochastic general equilibrium approach. This model incorporates both productivity and oil revenue shocks. The results indicate that productivity shocks are relatively more important to business cycles than oil shocks. The model with two shocks produces different values for volatility, but these values have the same ranking as that of the actual data for most variables. In addition, the actual data are close to the ratio of standard deviations to the output obtained from the model with two shocks. The results indicate that productivity shocks are relatively more important to business cycles than the oil shocks. The model with only a productivity shock produces the most similar figures in term of volatility magnitude to that of the actual data. Next, we use the Impulse Response Functions (IRF) to evaluate the capability of the model. The IRF shows no effect of an oil shock on the capital stocks and on labor hours, which is a feature of the model. When the log-linearized system of equations is solved numerically, investment and labor hours were not found to be functions of the oil shock. This research recommends using different techniques to compare the model’s robustness. One method by which to do this is to have all decision variables as a function of the oil shock by inducing the stationary to the model differently. Another method is to impose a bond adjustment cost. This study intends to fill that gap. To achieve this objective, we derive a DSGE model that allows for the world oil price and productivity shocks. Second, we calibrate the model to the Iran economy. Next, we compare the moments from the theoretical model with both single and multiple shocks with that obtained from the actual data to see the extent to which business cycles in Iran can be explained by total oil revenue shock. Then, we use an impulse response function to evaluate the role of world oil price shocks. Finally, I present implications of the findings and interpretations in accordance with economic theory.

Keywords: oil price, shocks, dynamic stochastic general equilibrium, Iran

Procedia PDF Downloads 417

Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

Abstract:

It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

Procedia PDF Downloads 124

Authors: Ezgiamn Abraha Hagos

Abstract:

The primary objective of this study was to assess the existential concerns and related manifestations of higher learning students by investigating their perception of meaningful life and evaluating their purpose in life. In addition, this study was aimed at assessing the manifestations of existential pain among the students. Data was procured using Purpose in Life test (PIL), Well-being Manifestation Measure Scale (WBMMS), and focus group discussion. The total numbers of participants was 478, of which 299 were males and the remaining 179 females. They were selected using a simple random sampling technique. Data was analyzed using two ways. SPSS-version 20 was used to analyze the quantitative part, and narrative modes were utilized to analyze the qualitative data. The research finding revealed that students are involved in risk taking behaviors like alcohol ingestion, drug use, Khat (chat) chewing, and unsafe sex. In line with this it is found out that life in campus was perceived as temporary and as a result the sense of hedonism was prevalent at any cost. Of course, the most important thing for the majority of the students was to know about the purpose of life. Regarding WBMMS, there was no statistically significant difference among males and females and with the exception of the sub-scale of happiness; in all the sub-scales the mean is low. At last, assisting adolescents to develop holistically in terms of body, mind, and spirit is recommended.

Keywords: existential concerns, higher learning institutions, Ethiopia, Aksum University

Procedia PDF Downloads 407

Authors: Grant Bifolchi

Abstract:

As global environmental problems continue to have highly adverse effects, finding long-term, sustainable solutions to combat ecological distress are of growing paramount concern. Ghost Gear—also known as abandoned, lost or otherwise discarded fishing gear (ALDFG) and derelict fishing gear (DFG)—represents one of the greatest threats to the world’s oceans, posing a significant hazard to human health, livelihoods, and global food security. In fact, according to the UN Food and Agriculture Organization (FAO), abandoned, lost and discarded fishing gear represents approximately 10% of marine debris by volume. Around the world, many governments, governmental and non-profit organizations are doing their best to manage the reporting and retrieval of nets, lines, ropes, traps, floats and more from their respective bodies of water. However, these organizations’ ability to effectively manage files and documents about the environmental problem further complicates matters. In Ghost Gear monitoring and management, organizations face additional complexities. Whether it’s data ingest, industry regulations and standards, garnering actionable insights into the location, security, and management of data, or the application of enforcement due to disparate data—all of these factors are placing massive strains on organizations struggling to save the planet from the dangers of Ghost Gear. In this 90-minute educational session, globally recognized Ghost Gear technology expert Grant Bifolchi CET, BBA, Bcom, will provide real-world insight into how governments currently manage Ghost Gear and the technology that can accelerate success in combatting ALDFG and DFG. In this session, attendees will learn how to: • Identify specific technologies to solve the ingest and management of Ghost Gear data categories, including type, geo-location, size, ownership, regional assignment, collection and disposal. • Provide enhanced access to authorities, fisheries, independent fishing vessels, individuals, etc., while securely controlling confidential and privileged data to globally recognized standards. • Create and maintain processing accuracy to effectively track ALDFG/DFG reporting progress—including acknowledging receipt of the report and sharing it with all pertinent stakeholders to ensure approvals are secured. • Enable and utilize Business Intelligence (BI) and Analytics to store and analyze data to optimize organizational performance, maintain anytime-visibility of report status, user accountability, scheduling, management, and foster governmental transparency. • Maintain Compliance Reporting through highly defined, detailed and automated reports—enabling all stakeholders to share critical insights with internal colleagues, regulatory agencies, and national and international partners.

Keywords: ghost gear, ALDFG, DFG, abandoned, lost or otherwise discarded fishing gear, data, technology

Procedia PDF Downloads 81

Authors: Ahmed Saheel

Abstract:

Enhanced oil recovery using carbon dioxide (CO₂-EOR) is a method that can increase oil production beyond what is typically achievable using conventional recovery methods by injecting, and hence storing, carbon dioxide (CO₂) in the oil reservoir. In Libya, plans are under way to source a proportion of this CO₂ from subsurface geology that is known from previous drilling to contain high volumes of CO₂. But first these subsurface volumes need to be more clearly defined and understood. Focusing on the Al-Harouj region of central Libya, ground gravity and airborne magnetic data from the LPI database and the African Magnetic Mapping Project respectively have been prepared and processed by Libyan Petroleum Institute (LPI) and Reid Geophysics Limited (RGL) to produce a range of grids and related products suitable for interpreting geological structure and to make recommendations for subsequent work that will assist CO₂ exploration for purposes of enhanced oil recovery (EOR).

Keywords: gravity, magnetic, deduced lineaments, upward continuation

Procedia PDF Downloads 103

Authors: C. Copilusi, C. Ploscaru

Abstract:

This paper addresses attention to a research regarding the design of a knee orthosis in a modular form used on children walking rehabilitation. This research is focused on the human lower limb kinematic analysis which will be used as input data on virtual simulations and prototype validation. From this analysis, important data will be obtained and used as input for virtual simulations of the knee modular orthosis. Thus, a knee orthosis concept was obtained and validated through virtual simulations by using MSC Adams software. Based on the obtained results, the modular orthosis prototype will be manufactured and presented in this article.

Keywords: human lower limb, children orthoses, kinematic analysis, knee orthosis

Procedia PDF Downloads 274

Authors: Olusegun Adeleke Adenuga

Abstract:

The study examined effect of fishbone creative thinking strategy on problem-solving skills of public teachers in Ogun state, Nigeria. A 2x2x2 factorial design was employed for the study which consisted of 80 participants made up of 40 male and 40 female public teachers randomly selected among public teaching personnel from the two local government area headquarters (Ijebu-ode and Ijebu-Igbo) within Ogun East Senatorial District. Each treatment group received 45minutes instructions and training per week for 8weeks. Data was collected from participants with the use of standardized instrument tagged ‘Problem Solving Inventory’ (PSI) developed by the researchers prior to the training to form a pre-test and immediately after eight weeks of training to form a post-test. One hypothesis was tested; the data obtained was analyzed using Analysis of Covariance (ANCOVA) tested at significance level of 0.05. The result of the data analysis shows that there was a significant effect of the fishbone creative thinking technique on the participants (F (2,99) = 12.410; p <.05). Based on the findings, it is therefore recommended that the report of this study be used to effect organizational change and development of teaching service in Nigeria through teachers’ retraining and capacity building.

Keywords: fishbone, creative thinking strategy, and problem-solving skills, public teachers

Procedia PDF Downloads 337

Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

Abstract:

Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

Procedia PDF Downloads 137

Authors: Shunyi Yang, Jingjing Yan, Siyu Dong, Xiangguo Cui

Abstract:

Current architectural façade design practices incorporate various daylighting and solar radiation analysis methods. These emphasize the impact of geometry on façade design. There is scope to extend this knowledge into methods that address material translucency, porosity, and form. Such approaches can also achieve these conditions through adaptive robotic manufacturing approaches that exploit material dynamics within the design, and alleviate fabrication waste from molds, ultimately accelerating the autonomous manufacturing system. Besides analyzing the environmental solar radiant in building facade design, there is also a vacancy research area of how lighting effects can be precisely controlled by engaging the instant real-time data-driven robot control and manipulating the material properties. Ceramics carries a wide range of transmittance and deformation potentials for robotics control with the research of its material property. This paper presents one semi-autonomous system that engages with real-time data-driven robotics control, hardware kit design, environmental building studies, human interaction, and exploratory research and experiments. Our objectives are to investigate the relationship between different clay bodies or ceramics’ physio-material properties and their transmittance; to explore the feedback system of instant lighting data in robotic fabrication to achieve precise lighting effect; to design the sufficient end effector and robot behaviors for different stages of deformation. We experiment with architectural clay, as the material of the façade that is potentially translucent at a certain stage can respond to light. Studying the relationship between form, material properties, and porosity can help create different interior and exterior light effects and provide façade solutions for specific architectural functions. The key idea is to maximize the utilization of in-progress robotics fabrication and ceramics materiality to create a highly integrated autonomous system for lighting facade design and manufacture.

Keywords: light transmittance, data-driven fabrication, computational design, computer vision, gamification for manufacturing

Procedia PDF Downloads 101

Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

Abstract:

Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

Procedia PDF Downloads 299

Authors: Nnadi Ezekiel Ejiofor

Abstract:

In Enugu, Nigeria, this study investigates the connection between strategic leadership and project management sustainability, with an emphasis on building projects in the State. The study set out to accomplish two specific goals: first, it sought to establish a link between creative project management and resource efficiency in construction projects in Enugu State, Nigeria; and second, it sought to establish a link between innovative thinking and waste minimization in those same projects. A structured questionnaire was used to collect primary data from 45 registered construction enterprises in the study area as part of the study's descriptive research approach. Due to the nonparametric nature of the data, Spearman Rank Order Correlation was used to evaluate the acquired data. The findings demonstrate that creative project management had a significant positive impact on resource efficiency in construction projects carried out by architecture firms in Enugu State, Nigeria (r =.849; p.001), and that innovative thinking had a significant impact on waste reduction in those same projects (r =.849; p.001). It was determined that strategic leadership had a significant impact on the sustainability of project management, and it was thus advised that project managers should foresee, prepare for, and effectively communicate present and future developments to project staff in order to ensure that the objective of sustainable initiatives, such as recycling and reuse, is implemented in construction projects.

Keywords: construction, project management, strategic leadership, sustainability, waste reduction

Procedia PDF Downloads 35

Authors: Saahith M. S., Sivakami R.

Abstract:

In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

Procedia PDF Downloads 25

Authors: Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin Leeuwen, Steven Riley

Abstract:

Traditional syndromic surveillance for influenza has substantial public health value in characterizing epidemics. Because the relationship between syndromic incidence and the true infection events can vary from one population to another and from one year to another, recent studies rely on combining serological test results with syndromic data from traditional surveillance into epidemic models to make inference on epidemiological processes of influenza. However, despite the widespread availability of serological data, epidemic models have thus far not explicitly represented antibody titre levels and their correspondence with immunity. Most studies use dichotomized data with a threshold (Typically, a titre of 1:40 was used) to define individuals as likely recently infected and likely immune and further estimate the cumulative incidence. Underestimation of Influenza attack rate could be resulted from the dichotomized data. In order to improve the use of serosurveillance data, here, a refinement of the concept of the stratified immunity within an epidemic model for influenza transmission was proposed, such that all individual antibody titre levels were enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Haemagglutination inhibition titres from 523 individuals and 465 individuals during pre- and post-pandemic phase of the 2009 pandemic in Hong Kong were collected. The model was fitted to serological data in age-structured population using Bayesian framework and was able to reproduce key features of the epidemics. The effects of age-specific antibody boosting and protection were explored in greater detail. RB was defined to be the effective reproductive number in the presence of stratified immunity and its temporal dynamics was compared to the traditional epidemic model using use dichotomized seropositivity data. Deviance Information Criterion (DIC) was used to measure the fitness of the model to serological data with different mechanisms of the serological response. The results demonstrated that the differential antibody response with age was present (ΔDIC = -7.0). The age-specific mixing patterns with children specific transmissibility, rather than pre-existing immunity, was most likely to explain the high serological attack rates in children and low serological attack rates in elderly (ΔDIC = -38.5). Our results suggested that the disease dynamics and herd immunity of a population could be described more accurately for influenza when the distribution of immunity was explicitly represented, rather than relying only on the dichotomous states 'susceptible' and 'immune' defined by the threshold titre (1:40) (ΔDIC = -11.5). During the outbreak, RB declined slowly from 1.22[1.16-1.28] in the first four months after 1st May. RB dropped rapidly below to 1 during September and October, which was consistent to the observed epidemic peak time in the late September. One of the most important challenges for infectious disease control is to monitor disease transmissibility in real time with statistics such as the effective reproduction number. Once early estimates of antibody boosting and protection are obtained, disease dynamics can be reconstructed, which are valuable for infectious disease prevention and control.

Keywords: effective reproductive number, epidemic model, influenza epidemic dynamics, stratified immunity

Procedia PDF Downloads 247

Authors: Sadeq Al Yaari, Fayza Alhammadi, Ayman Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Saleh Al Yami

Abstract:

Background: A rapidly increasing number of studies that focus on the relationship between language and cortical (CD) and subcortical dementias (SCD) have recently shown that such correlation is existent. Mounting evidence suggests that cognitive impairments should be investigated against language disorders. Aims: This study aims at investigating how language is associated with dementia diseases namely CD &SCD in light of psychoneurolinguistic approach. Method: Data from multiple sources (e.g., theses, dissertations, articles, research, medical records, direct testing, staff reports, and client observations) have been integrated to provide a detailed analysis of the relationship between language and CD&SCD. The researchers identified over 20 most of dementia types, and described them. Having collected and described data, the researchers then analyzed these data independently to see to what extent CD&SCD are involved in matters concerning language. Results: Results of the present study demonstrate that language and CD&SCD are undoubtedly correlated with each other. The loss of the ability of some organs to perform certain functions (due to any of the dementia diseases) results in no way to the loss of some language aspects and /or speech skills. In clearer terms, it is rare to find a patient with dementia who is not suffering from partial or complete linguistic difficulties. Many deficits run through the current interpretation of linguistic disorders: language disorders, speech disorders, articulation disorders, or voice disorders.

Keywords: cortical dementia, subcortical dementia, diseases, psychoneurolinguistics, language, impairments, relationship

Procedia PDF Downloads 25

Authors: Medhat Gad

Abstract:

Wastewater treatment became a big issue in this decade due to shortage of water resources, growth of population and modern live requirements. Reuse of treated wastewater in industrial and agriculture sectors has a big demand to substitute the shortage of clean water supply as well as to save the eco system from dangerous pollutants in insufficient treated wastewater In last decades, most of wastewater treatment plants are built using primary or secondary biological treatment technology which almost does not provide enough treatment and removal of phosphorus and nitrogen. those plants which built ten to 15 years ago also now suffering from overflow which decrease the treatment efficiency of the plant. Discharging treated wastewater which contains phosphorus and nitrogen to water reservoirs and irrigation canals destroy ecosystem and aquatic life. Using chemical material to enhance treatment efficiency for domestic wastewater but it leads to huge amount of sludge which cost a lot of money. To enhance wastewater treatment, we used INNPT nano material which consists of calcium, aluminum and iron oxides and compounds plus silica, sodium and magnesium. INNPT nano material used with a dose of 100 mg/l to upgrade SBR treatment plant in Cairo Egypt -which has three treatment tanks each with a capacity of 2500 cubic meters per day - to tertiary treatment level by removing Phosphorus, Nitrogen and increase dissolved oxygen in final effluent. The results showed that the treatment retention time decreased from 9 hours in SBR system to one hour using INNPT nano material with improvement in effluent quality while increasing plant capacity to 20 k cubic meters per day. Nitrogen removal efficiency achieved 77%, while phosphorus removal efficiency achieved 90% and COD removal efficiency was 93% which all comply with tertiary treatment limits according to Egyptian law.

Keywords: INNPT technology, nanomaterial, tertiary wastewater treatment, capacity extending

Procedia PDF Downloads 149

Authors: Pooja Kumbhare

Abstract:

Water is an important resource for the survival of life. The inadequate availability of surface water makes people depend on ground water for fulfilling their needs. However, ground water is generally too hard to satisfy the requirements for domestic as well as industrial applications. Removal of hardness involves various techniques such as lime soda process, ion exchange, reverse osmosis, nano-filtration, distillation, and, evaporation, etc. These techniques have individual problems such as high annual operating cost, sediment formation on membrane, sludge disposal problem, etc. Electrocoagulation (EC) is being explored as modern and cost-effective technology to cope up with the growing demand of high water quality at the consumer end. In general, earlier studies on electrocoagulation for hardness removal are found to deploy batch processes. As batch processes are always inappropriate to deal with large volume of water to be treated, it is essential to develop continuous flow EC process. So, in the present study, an attempt is made to investigate continuous flow EC process for decreasing excessive hardness of bore-well water. The experimental study has been conducted using 12 aluminum electrodes (25cm*10cm, 1cm thick) provided in EC reactor with volume of 8 L. Bore well water sample, collected from a local bore-well (i.e. at – Vishrambag, Sangli; Maharashtra) having average initial hardness of 680 mg/l (Range: 650 – 700 mg/l), was used for the study. Continuous flow electrocoagulation experiments were carried out by varying operating parameters specifically reaction time (Range: 10 – 60 min), voltage (Range: 5 – 20 V), current (Range: 1 – 5A). Based on the experimental study, it is found that hardness removal to the desired extent could be achieved even for continuous flow EC reactor, so the use of it is found promising.

Keywords: hardness, continuous flow EC process, aluminum electrode, optimal operating parameters

Procedia PDF Downloads 168

Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

Abstract:

Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

Procedia PDF Downloads 85

Authors: Ahmed M. AlHasem

Abstract:

The Kuwaiti society has long been aware of climatic changes and their annual dates and trying to link them to astronomy in an attempt to forecast the future weather conditions. The reason for this concern is that many of the economic, social and living activities of the society depend deeply on the nature of the weather conditions directly and indirectly. In other words, Kuwaiti society, like the case of many human societies, has in the past tried to predict climatic conditions by linking them to astronomy or popular statements to indicate the timing of climate changes. Accordingly, this study was devoted to scientific investigation based on the statistical analysis of climatic data to show the accuracy and compatibility of some of the most important elements of the cultural heritage in relation to climate change and to relate it scientifically to precise climatic measurements for decades. The research has been divided into 10 topics, each topic has been focused on one legacy, whether by linking climate changes to the appearance/disappearance of star or a popular statement inherited through generations, through explain the nature and timing and thereby statistical analysis to indicate the proportion of accuracy based on official climatic data since 1962. The study's conclusion is that the relationship is weak and, in some cases, non-existent between the popular heritage and the actual climatic data. Therefore, it does not have a dependable relationship and a reliable scientific prediction between both the popular heritage and the forecast of weather conditions.

Keywords: astronomy, cultural heritage, statistical analysis, weather prediction

Procedia PDF Downloads 109