Search results for: data management system

Authors: Benjamin Mauck, Kevin Winter

Abstract:

The city of Cape Town in South Africa, has shown consistent economic and population growth in the last few decades and that growth is expected to continue to increase into the future. These projected economic and population growth rates are set to place additional pressure on the city’s already strained water supply system. Thus, given Cape Town’s water scarcity, increasing water demands and stressed water supply system, coupled with global awareness around the issues of sustainable development, environmental protection and climate change, alternative water management strategies are required to ensure water is sustainably managed. Water Sensitive Urban Design (WSUD) is an approach to sustainable urban water management that attempts to assign a resource value to all forms of water in the urban context, viz. stormwater, wastewater, potable water and groundwater. WSUD employs a wide range of strategies to improve the sustainable management of urban water such as the water reuse, developing alternative available supply sources, sustainable stormwater management and enhancing the aesthetic and recreational value of urban water. Managed Aquifer Recharge (MAR) is one WSUD strategy which has proven to be a successful reuse strategy in a number of places around the world. MAR is the process where an aquifer is intentionally or artificially recharged, which provides a valuable means of water storage while enhancing the aquifers supply potential. This paper investigates the feasibility of implementing MAR in the sandy, unconfined Cape Flats Aquifer (CFA) in Cape Town. The main objective of the study is to assess if MAR is a viable strategy for stormwater management on the Cape Flats, aiding the prevention or mitigation of the seasonal flooding that occurs on the Cape Flats, while also improving the supply potential of the aquifer. This involves the infiltration of stormwater into the CFA during the wet winter months and in turn, abstracting from the CFA during the dry summer months for fit-for-purpose uses in order to optimise the recharge and storage capacity of the CFA. The fully-integrated MIKE SHE model is used in this study to simulate both surface water and groundwater hydrology. This modelling approach enables the testing of various potential recharge and abstraction scenarios required for implementation of MAR on the Cape Flats. Further MIKE SHE scenario analysis under projected future climate scenarios provides insight into the performance of MAR as a stormwater management strategy under climate change conditions. The scenario analysis using an integrated model such as MIKE SHE is a valuable tool for evaluating the feasibility of the MAR as a stormwater management strategy and its potential to contribute towards improving Cape Town’s water security into the future.

Keywords: managed aquifer recharge, stormwater management, cape flats aquifer, MIKE SHE

Procedia PDF Downloads 248

Authors: Hansraj Bookun, Angela Tan, Rachel Xuan, Linheng Zhao, Kejia Wang, Animesh Singla, David Kim, Christopher Loupos

Abstract:

Introduction: Incisional wound complications in vascular surgery patients represent a significant clinical and econometric burden of morbidity and mortality. The objective of this study was to trial the feasibility of applying the Prevena negative pressure incision management system as a routine dressing in patients who had undergone arterial surgery. Conventionally, Prevena has been applied to groin incisions, but this study features applications on multiple wound sites such as the thigh or major amputation stumps. Method: This was a cross-sectional observational, single-centre case series of 12 patients who had undergone major vascular surgery. Their wounds were managed with the Prevena system being applied either intra-operatively or on the first post-operative day. Demographic and operative details were collated as well as the length of stay and complication rates. Results: There were 9 males (75%) with mean age of 66 years and the comorbid burden was as follows: ischaemic heart disease (92%), diabetes (42%), hypertension (100%), stage 4 or greater kidney impairment (17%) and current or ex-smoking (83%). The main indications were acute ischaemia (33%), claudication (25%), and gangrene (17%). There were single instances of an occluded popliteal artery aneurysm, diabetic foot infection, and rest pain. The majority of patients (50%) had hybrid operations with iliofemoral endarterectomies, patch arterioplasties, and further peripheral endovascular treatment. There were 4 complex arterial bypass operations and 2 major amputations. The mean length of stay was 17 ± 10 days, with a range of 4 to 35 days. A single complication, in the form of a lymphocoele, was encountered in the context of an iliofemoral endarterectomy and patch arterioplasty. This was managed conservatively. There were no deaths. Discussion: The Prevena wound management system shows that in conjunction with safe vascular surgery, absolute wound complication rates remain low and that it remains a valuable adjunct in the treatment of vasculopaths.

Keywords: wound care, negative pressure, vascular surgery, closed incision

Procedia PDF Downloads 137

Authors: Yas Barzegaar, Atrin Barzegar

Abstract:

The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

Procedia PDF Downloads 102

Authors: T. Theodosiou, P. Polychronidou, A. G. Karasavvoglou

Abstract:

The latest years the number of immigrants at Greece has increased dramatically. Their impact on the National Health System (NHS) has not been yet thoroughly investigated. This paper analyses the cost of immigrants to the NHS hospitals of the region of Eastern Macedonia and Thrace. The data are collected from 2005 to 2011 from five different hospitals and are analysed using linear mixed effects models in order to investigate the effects of nationality and year on the cost of hospitalization and treatment. The results show that generally the Greek nationality patients have a higher mean cost of hospitalization compared to the immigrants and that there is an increasing trend for the cost except for the year 2010.

Keywords: cost, Eastern Macedonia and Thrace, immigrants, national health system

Procedia PDF Downloads 245

Authors: Mehrnoosh Askarizadeh

Abstract:

Globalization of the economy, e-business, and introduction of new technologies pose new challenges to all organizations. In recent decades, globalization, outsourcing, and information technology have enabled many organizations to successfully operate collaborative supply networks in which each specialized business partner focuses on only a few key strategic activities For this industries supply network can be acknowledged as a new form of organization. We will study about critical success factors (CSFs) for implementation of SCM in companies. It is shown that in different circumstances e- supply chain management has a higher impact on performance.

Keywords: supply chain management, logistics management, critical success factors, information technology, top management support, human resource

Procedia PDF Downloads 409

Authors: Trisiladi Supriyanto

Abstract:

This study aims to establish a concept of rate of profit on Islamic banking that can create economic justice and stability in the Islamic Financial Market (Banking and Capital Markets). A rate of profit that creates economic justice and stability can be achieved through its role in maintaining the stability of the financial system in which there is an equitable distribution of income and wealth. To determine the role of the rate of profit as the basis of the profit sharing system implemented in the Islamic financial system, we can see the connection of rate of profit in creating financial stability, especially in the asset-liability management of financial institutions that generate a stable net margin or the rate of profit that is not affected by the ups and downs of the market risk factors, including indirect effect on interest rates. Furthermore, Islamic financial stability can be seen from the role of the rate of profit on the stability of the Islamic financial assets value that are measured from the Islamic financial asset price volatility in the Islamic Bond Market in the Capital Market.

Keywords: economic justice, equitable distribution of income, equitable distribution of wealth, rate of profit, stability in the financial system

Procedia PDF Downloads 314

Authors: Hamza Saeed, Khurram Iqbal Ahmad Khan

Abstract:

Effective information management is crucial for any construction project and its success. Primary areas of information generation are either the construction site or the design office. There are different types of information required at different stages of construction involving various stakeholders creating complexity. There is a need for effective management of information flows to reduce uncertainty creating complexity. Nature provides a unique perspective in terms of dealing with complexity, in particular, information complexity. System dynamics methodology provides tools and techniques to address complexity. It involves modeling and simulation techniques that help address complexity. Nature has been dealing with complex systems since its creation 4.5 billion years ago. It has perfected its system by evolution, resilience towards sudden changes, and extinction of unadaptable and outdated species that are no longer fit for the environment. Nature has been accommodating the changing factors and handling complexity forever. Humans have started to look at their natural counterparts for inspiration and solutions for their problems. This brings forth the possibility of using a biomimetics approach to improve the management practices used in the construction sector. Ants inhabit different habitats. Cataglyphis and Pogonomyrmex live in deserts, Leafcutter ants reside in rainforests, and Pharaoh ants are native to urban developments of tropical areas. Detailed studies have been done on fifty species out of fourteen thousand discovered. They provide the opportunity to study the interactions in diverse environments to generate collective behavior. Animals evolve to better adapt to their environment. The collective behavior of ants emerges from feedback through interactions among individuals, based on a combination of three basic factors: The patchiness of resources in time and space, operating cost, environmental stability, and the threat of rupture. If resources appear in patches through time and space, the response is accelerating and non-linear, and if resources are scattered, the response follows a linear pattern. If the acquisition of energy through food is faster than energy spent to get it, the default is to continue with an activity unless it is halted for some reason. If the energy spent is rather higher than getting it, the default changes to stay put unless activated. Finally, if the environment is stable and the threat of rupture is low, the activation and amplification rate is slow but steady. Otherwise, it is fast and sporadic. To further study the effects and to eliminate the environmental bias, the behavior of four different ant species were studied, namely Red Harvester ants (Pogonomyrmex Barbatus), Argentine ants (Linepithema Humile), Turtle ants (Cephalotes Goniodontus), Leafcutter ants (Genus: Atta). This study aims to improve the information system in the construction sector by providing a guideline inspired by nature with a systems-thinking approach, using system dynamics as a tool. Identified factors and their interdependencies were analyzed in the form of a causal loop diagram (CLD), and construction industry professionals were interviewed based on the developed CLD, which was validated with significance response. These factors and interdependencies in the natural system corresponds with the man-made systems, providing a guideline for effective use and flow of information.

Keywords: biomimetics, complex systems, construction management, information management, system dynamics

Procedia PDF Downloads 137

Authors: Murtala Aminu, Salisu Adamu Aliero, Adamu Muhammed

Abstract:

Records are a vital asset in ensuring that the institution is governed effectively and efficiently, and is accountable to its staff, students and the community that it serves. The major purpose of this study was to assess record management of the registry department of Kebbi state University of science and technology Aliero. To be able to achieve this objective, research questions were formulated and answers obtained, which centered on records creation, record management policy, challenges facing records management. The review of related literature revealed that there is need for records to be properly managed and in doing so there is need for good records management policy that clearly spells out the various programs required for effective records management. Survey research method was used involving questionnaire, and observation. The findings revealed that the registry department of the University still has a long way to go with respect to day-today records management. The study recommended provision for adequate, modern, safe and functional storage facilities, sufficient and regular funding, recruitment of trained personnel, on the job training for existing staff, computerization of all units records, and uninterrupted power supply to all parts of the unit as a means of ensuring proper records management.

Keywords: records, management, records management policy, registry

Procedia PDF Downloads 316

Authors: Hashim Zameer

Abstract:

Effective tourism management plays a vital role in promoting sustainability and supporting ecosystems. A common principle that has been in practice over the years is “first pollute and then clean,” indicating countries need financial resources to promote sustainability. Financial development and the tourism management both seems very important to promoting sustainable development. However, without institutional support, it is very difficult to succeed. In this context, it seems prominently significant to explore how institutional quality, tourism development, and financial development could promote sustainable development. In the past, no research explored the role of tourism development in sustainable development. Moreover, the role of financial development, natural resources, and institutional quality in sustainable development is also ignored. In this regard, this paper aims to investigate the role of tourism development, natural resources, financial development, and institutional quality in sustainable development in China. The study used time-series data from 2000–2021 and employed the Bayesian linear regression model because it is suitable for small data sets. The robustness of the findings was checked using a quantile regression approach. The results reveal that an increase in tourism expenditures stimulates the economy, creates jobs, encourages cultural exchange, and supports sustainability initiatives. Moreover, financial development and institution quality have a positive effect on sustainable development. However, reliance on natural resources can result in negative economic, social, and environmental outcomes, highlighting the need for resource diversification and management to reinforce sustainable development. These results highlight the significance of financial development, strong institutions, sustainable tourism, and careful utilization of natural resources for long-term sustainability. The study holds vital insights for policy formulation to promote sustainable tourism.

Keywords: sustainability, tourism development, financial development, institutional quality

Procedia PDF Downloads 83

Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

Abstract:

The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

Procedia PDF Downloads 127

Authors: Karolína Vozková, Matěj Kuc

Abstract:

Net fee and commission income is one of the key elements of a bank’s core income. In the current low-interest rate environment, this type of income is gaining importance relative to net interest income. This paper analyses the effects of bank and country specific determinants of net fee and commission income on a set of cooperative banks from European countries in the 2007-2014 period. In order to do that, dynamic panel data methods (system Generalized Methods of Moments) were employed. Subsequently, alternative panel data methods were run as robustness checks of the analysis. Strong positive impact of bank concentration on the share of net fee and commission income was found, which proves that cooperative banks tend to display a higher share of fee income in less competitive markets. This is probably connected with the fact that they stick with their traditional deposit-taking and loan-providing model and fees on these services are driven down by the competitors. Moreover, compared to commercial banks, cooperatives do not expand heavily into non-traditional fee bearing services under competition and their overall fee income share is therefore decreasing with the increased competitiveness of the sector.

Keywords: cooperative banking, dynamic panel data models, net fee and commission income, system GMM

Procedia PDF Downloads 330

Authors: Bhupeshwaran Mani, S. Radha, A. Jawahar, A. Sivasubramanian

Abstract:

Here, we study the characteristic feature of conventional (ON-OFF keying) and soliton based transmission system. We consider 20 Gbps transmission system implemented with Conventional Single Mode Fiber (C-SMF) to examine the role of Gaussian pulse which is the characteristic of conventional propagation and hyperbolic-secant pulse which is the characteristic of soliton propagation in it. We note the influence of these pulses with respect to different dispersion lengths and soliton period in conventional and soliton system, respectively, and evaluate the system performance in terms of quality factor. From the analysis, we could prove that the soliton pulse has more consistent performance even for long distance without dispersion compensation than the conventional system as it is robust to dispersion. For the length of transmission of 200 Km, soliton system yielded Q of 33.958 while the conventional system totally exhausted with Q=0.

Keywords: dispersion length, retrun-to-zero (rz), soliton, soliton period, q-factor

Procedia PDF Downloads 346

Authors: Ayodele Adekunle Faiyetole, Olumide Olawale Jegede

Abstract:

This paper presents the experimental design and needs justifications for a localized intelligent parking system (L-IPS), ideal for quasi-close communities with increasing vehicular volume that depends on limited or constant parking facilities. For a constant supply in parking facilities, the demand for an increasing vehicular volume could lead to poor time conservation or extended travel time, traffic congestion or impeded mobility, and safety issues. Increased negative environmental and economic externalities are other associated and consequent downsides of disparities in demand and supply. This L-IPS is designed using a microcontroller, ultrasonic sensors, LED indicators, such that the current status, in terms of parking spots availability, can be known from the main entrance to the community or a parking zone on a LCD screen. As an advanced traffic management system (ATMS), the L-IPS is designed to resolve aspects of infrastructure-to-driver (I2D) communication and parking detection issues. Thus, this L-IPS can act as a timesaver for users by helping them know the availability of parking spots. Providing on-time, informed routing, to a next preference or seamless moving to berth on the available spot on a proximate facility as the case may be. Its use could also increase safety and increase mobility, and fuel savings and costs, therefore, reducing negative environmental and economic externalities due to transportation systems.

Keywords: intelligent parking systems, localized intelligent parking system, intelligent transport systems, advanced traffic management systems, infrastructure-to-drivers communication

Procedia PDF Downloads 171

Authors: Muhammad Ajmal, Ahmad Shahrul Nizam Bin Isha, Shahrina Md. Nordin, Paras Behrani, Al-Baraa Abdulrahman Al-Mekhlafi

Abstract:

This study aims to investigate the impact of safety management practices via safety compliance on occupational injuries in the context of downstream the oil and gas industry of Malaysia. However, it is still challenging for researchers and academicians to control occupational injuries in high-safety-sensitive organizations. In this study response rate was 62%, and 280 valid responses were used for analysis through SmartPLS. The study results revealed that safety management practices (management commitment, safety training, safety promotion policies, workers’ involvement) play a significant role in lowering the rate of accidents in downstream the oil and gas industry via safety compliance. Furthermore, the study results also revealed that safety management practices also reduce safety management costs of organizations, e.g., lost work days and employee absenteeism. Moreover, this study is helpful for safety leaders and managers to understand the importance of safety management practices to lower the ratio of occupational injuries.

Keywords: safety management, safety compliance, occupational injuries, oil and gas, Malaysia

Procedia PDF Downloads 155

Authors: Maha Mourad

Abstract:

Higher education in any competitive European economy should serve the new information society by increasing the supply of good quality education services and by creating good international brands in the international higher education market. Hence, continuous risk management techniques through higher educational reforms programs became one of the top priorities within the European Union to control the quality of higher education. Risk is higher education is studies by several researchers who agreed that the risk in higher education has a direct influence on continuity of quality education and research contribution. The focus of this research is to highlights the Internal Quality Assurance (IQA) activities in the Polish higher education system as a risk management tool used to control the quality of education. This paper presents a qualitative empirical analysis in 5 different universities in Poland. In addition, it aims to help in finding global practical and create benchmark for policy makers concerning the risk management techniques based on the Polish experience.

Keywords: education development, quality assurance, sustainability, european higher education

Procedia PDF Downloads 468

Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad

Abstract:

As energetic and environmental issues are getting more and more attention all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascends with an unprecedented rate. This matter causes more uncertainties to appear in the power system context; ergo, the uncertainty analysis of the system performance is an obligation. The uncertainties of any system can be represented probabilistically or possibilistically. Since sufficient historical data about all the system variables is not available, therefore, they do not have a probability density function (PDF) and must be represented possibilistiacally. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution is appealed. The first of this two-paper series formulates a new possibilistic-probabilistic tool for the load flow uncertainty assessment. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. This possibilistic- probabilistic formulation is solved in the second companion paper in an uncertain load flow (ULF) study problem.

Keywords: probabilistic uncertainty modeling, possibilistic uncertainty modeling, uncertain load flow, wind turbine generator

Procedia PDF Downloads 562

Authors: A. Kourou, M. Panoutsopoulou

Abstract:

Nowadays, disaster risk reduction requires innovative ways of working collaboratively, monitoring tools, management methods, risk communication, and knowledge, as key factors for decision-making actors. Experience has shown that the assessment of seismic risk and its effective management is still an important challenge. In Greece, Ionian Islands region is characterized as the most seismic area of the country and one of the most active worldwide. It is well known that in case of a disastrous earthquake the local authorities need to assess the situation in the affected area and coordinate the disaster response. In particular, the main outcomes of 'Telemachus' project are the development of an innovative operational system that hosts the needed data of seismic risk management in the Ionian Islands and the implementation of educational actions for the involved target groups. This project is funded in the Priority Axis 'Environmental Protection and Sustainable Development' of Operational Plan 'Ionian Islands 2014-2020'. EPPO is one of the partners of the project and it is responsible, among others, for the development of proper training material. This paper presents the training material of 'Telemachus' and its usage as a helpful, managerial tool in case of earthquake emergency. This material is addressed to different target groups, such as civil protection staff, people that involved with the tourism industry, educators of disabled people, etc. Very positive aspect of the project is the involvement of end-users that should evaluate the training products; test standards; clarify the personnel’s roles and responsibilities; improve interagency coordination; identify gaps in resources; improve individual performance; and identify opportunities for improvement. It is worth mentioning that even though the abovementioned material developed is useful for the training of specific target groups on emergency management issues within Ionian Islands Region, it could be used throughout Greece and other countries too.

Keywords: education of civil protection staff, Ionian Islands Region of Greece, seismic risk, training material

Procedia PDF Downloads 123

Authors: Dongho Kim, Sung Choi, Kyowoong Pee, Youngsik Cho, Seungwoo Jeong, Soo-Ho Kim

Abstract:

This study is about the orbital TIG welding robot system which travels on the guide rail installed on the pipe, and welds and tracks the pipe seam using the LVS (Laser Vision Sensor) joint profile data. The orbital welding robot system consists of the robot, welder, controller, and LVS. Moreover we can define the relationship between welding travel speed and wire feed speed, and we can make the linear equation using the maximum and minimum amount of weld metal. Using the linear equation we can determine the welding travel speed and the wire feed speed accurately corresponding to the area of weld captured by LVS. We applied this orbital TIG welding robot system to the stainless steel or duplex pipe on DSME (Daewoo Shipbuilding and Marine Engineering Co. Ltd.,) shipyard and the result of radiographic test is almost perfect. (Defect rate: 0.033%).

Keywords: adaptive welding, automatic welding, pipe welding, orbital welding, laser vision sensor, LVS, welding D/B

Procedia PDF Downloads 689

Authors: Pongsiri Kingkan

Abstract:

This research aims to study the Readiness of Thai Restaurant in Bangkok in Applying for Certification of Halal Food Services Standard for Tourism. This research was conduct by using mix methodology; both quantitative and qualitative data were used. 420 questionnaires were used as tools to collected data from the samples, the restaurant employees. The results were divided into two parts, the demographic data and the Readiness of Thai Restaurant in Bangkok in Applying for Certification of Halal Food Services Standard for Tourism. The majority of samples are single female age between 18–30 years old, who earn about 282.40 US dollars a month. The result of Thai restaurant readiness study demonstrated that readiness in foods and restaurant operating processes were scored at the lowest level. Readiness in social responsibility, food contact persons and food materials were rated at the low level. The readiness of utensils and kitchen tools, waste management, environmental management, and the availability of space to implement the establishment of halal food were scored at the average level. Location readiness, foods service safety and the relationship with the local community were rated at high level. But interestingly there is none of them rated at the highest level.

Keywords: availability, Bangkok, halal, Thai restaurant, readiness

Procedia PDF Downloads 316

Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

Procedia PDF Downloads 150

Authors: Muhammad Tahir Hassan, Stas Burek, Muhammad Asif, Mohamed Emad

Abstract:

Industrial sector in Pakistan accounts for 25% of total energy consumption in the country. The performance of this sector has been severely affected due to the adverse effect of current energy crises in the country. Energy conservation potentials of Pakistan’s industrial sectors through energy management can save wasted energy which would ultimately leads to economic and environmental benefits. However due to lack of financial incentives of energy efficiency and absence of energy benchmarking within same industrial sectors are some of the main challenges in the implementation of energy management. In Pakistan, this area has not been adequately explored, and there is a lack of focus on the need for industrial energy efficiency and proper management. The main objective of this research is to evaluate the current energy management performance of Pakistani industrial sector and empirical investigation of the existence of various barriers to industrial energy efficiency. Data was collected from the respondents of 192 small and medium-sized enterprises (SME’s) of Pakistan i.e. foundries, textile, plastic industries, light engineering, auto and spare parts and ceramic manufacturers and analysed using Statistical Package for the Social Sciences (SPSS) software. Current energy management performance of manufacturing SME’s in Pakistan has been evaluated by employing two significant indicators, ‘Energy Management Matrix’ and ‘pay-off criteria’, with modified approach. Using the energy management matrix, energy management profiles of overall industry and the individual sectors have been drawn to assess the energy management performance and identify the weak and strong areas as well. Results reveal that, energy management practices in overall surveyed industries are at very low level. Energy management profiles drawn against each sector suggest that performance of textile sector is better among all the surveyed manufacturing SME’s. The empirical barriers to industrial energy efficiency have also been ranked according to the overall responses. The results further reveal that there is a significant relationship exists among the industrial size, sector type and nature of barriers to industrial energy efficiency for the manufacturing SME’s in Pakistan. The findings of this study may help the industries and policy makers in Pakistan to formulate a sustainable energy policy to support industrial energy efficiency keeping in view the actual existing energy efficiency scenario in the industrial sector.

Keywords: barriers, energy conservation, energy management profile, environment, manufacturing SME's of Pakistan

Procedia PDF Downloads 290

Authors: Danlei Yang, Luofeng Huang

Abstract:

The integration of digital twin technology with renewable energy systems offers an innovative approach to predicting and optimising performance throughout the entire lifecycle. A digital twin is a continuously updated virtual replica of a real-world entity, synchronised with data from its physical counterpart and environment. Many digital twin companies today claim to have mature digital twin products, but their focus is primarily on equipment visualisation. However, the core of a digital twin should be its model, which can mirror, shadow, and thread with the real-world entity, which is still underdeveloped. For a floating solar energy system, a digital twin model can be defined in three aspects: (a) the physical floating solar energy system along with environmental factors such as solar irradiance and wave dynamics, (b) a digital model powered by artificial intelligence (AI) algorithms, and (c) the integration of real system data with the AI-driven model and a user interface. The experimental setup for the floating solar energy system, is designed to replicate real-ocean conditions of floating solar installations within a controlled laboratory environment. The system consists of a water tank that simulates an aquatic surface, where a floating catamaran structure supports a solar panel. The solar simulator is set up in three positions: one directly above and two inclined at a 45° angle in front and behind the solar panel. This arrangement allows the simulation of different sun angles, such as sunrise, midday, and sunset. The solar simulator is positioned 400 mm away from the solar panel to maintain consistent solar irradiance on its surface. Stability for the floating structure is achieved through ropes attached to anchors at the bottom of the tank, which simulates the mooring systems used in real-world floating solar applications. The floating solar energy system's sensor setup includes various devices to monitor environmental and operational parameters. An irradiance sensor measures solar irradiance on the photovoltaic (PV) panel. Temperature sensors monitor ambient air and water temperatures, as well as the PV panel temperature. Wave gauges measure wave height, while load cells capture mooring force. Inclinometers and ultrasonic sensors record heave and pitch amplitudes of the floating system’s motions. An electric load measures the voltage and current output from the solar panel. All sensors collect data simultaneously. Artificial neural network (ANN) algorithms are central to developing the digital model, which processes historical and real-time data, identifies patterns, and predicts the system’s performance in real time. The data collected from various sensors are partly used to train the digital model, with the remaining data reserved for validation and testing. The digital twin model combines the experimental setup with the ANN model, enabling monitoring, analysis, and prediction of the floating solar energy system's operation. The digital model mirrors the functionality of the physical setup, running in sync with the experiment to provide real-time insights and predictions. It provides useful industrial benefits, such as informing maintenance plans as well as design and control strategies for optimal energy efficiency. In long term, this digital twin will help improve overall solar energy yield whilst minimising the operational costs and risks.

Keywords: digital twin, floating solar energy system, experiment setup, artificial intelligence

Procedia PDF Downloads 9

Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

Abstract:

Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

Procedia PDF Downloads 881

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

Procedia PDF Downloads 378

Authors: Majed Sanan, Mohammad Rammal, Wassim Rammal

Abstract:

Today, security is a major concern. Intrusion Detection, Prevention Systems and Honeypot can be used to moderate attacks. Many researchers have proposed to use many IDSs ((Intrusion Detection System) time to time. Some of these IDS’s combine their features of two or more IDSs which are called Hybrid Intrusion Detection Systems. Most of the researchers combine the features of Signature based detection methodology and Anomaly based detection methodology. For a signature based IDS, if an attacker attacks slowly and in organized way, the attack may go undetected through the IDS, as signatures include factors based on duration of the events but the actions of attacker do not match. Sometimes, for an unknown attack there is no signature updated or an attacker attack in the mean time when the database is updating. Thus, signature-based IDS fail to detect unknown attacks. Anomaly based IDS suffer from many false-positive readings. So there is a need to hybridize those IDS which can overcome the shortcomings of each other. In this paper we propose a new approach to IDS (Intrusion Detection System) which is more efficient than the traditional IDS (Intrusion Detection System). The IDS is based on Honeypot Technology and Anomaly based Detection Methodology. We have designed Architecture for the IDS in a packet tracer and then implemented it in real time. We have discussed experimental results performed: both the Honeypot and Anomaly based IDS have some shortcomings but if we hybridized these two technologies, the newly proposed Hybrid Intrusion Detection System (HIDS) is capable enough to overcome these shortcomings with much enhanced performance. In this paper, we present a modified Hybrid Intrusion Detection System (HIDS) that combines the positive features of two different detection methodologies - Honeypot methodology and anomaly based intrusion detection methodology. In the experiment, we ran both the Intrusion Detection System individually first and then together and recorded the data from time to time. From the data we can conclude that the resulting IDS are much better in detecting intrusions from the existing IDSs.

Keywords: security, intrusion detection, intrusion prevention, honeypot, anomaly-based detection, signature-based detection, cloud computing, kfsensor

Procedia PDF Downloads 383

Authors: Sung Ho Oh

Abstract:

The advanced traffic lights, the system of traffic information collection and provision, the CCTVs for traffic control, and the traffic information center were installed in Asuncion, capital of Paraguay. After pre-post comparison of the installation, significant changes were found. Even though the traffic volumes were increased, travel speed was higher, so that travel time from origin to destination was decreased. the saving values for travel time, gas cost, and environmental cost are about 47 million US dollars per year. Satisfaction survey results for the installation were presented with statistical significance analysis.

Keywords: advanced transport management systems, effectiveness, Paraguay, traffic lights

Procedia PDF Downloads 352

Authors: Mounir Kehal, Adel Al Araifi

Abstract:

The post-globalisation epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper we present likewise an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

Procedia PDF Downloads 417

Authors: Peris Wanjiku

Abstract:

The objective of this paper is to describe the development and implications of a national nursing workforce analytical system in Kenya. Findings: Creating a national electronic nursing workforce analytical system provides more reliable information on nurses ‘national demographics, migration patterns, and workforce capacity and efficiency. Data analysis is most useful for human resources for health (HRH) planning when workforce capacity data can be linked to worksite staffing requirements. As a result of establishing this database, the Kenya Ministry of Health has improved its capability to assess its nursing workforce and document important workforce trends, such as out-migration. Current data identify the United States as the leading recipient country of Kenyan nurses. The overwhelming majority of Kenyan nurses who decide to out-migrate are amongst Kenya’s most qualified. Conclusions: The Kenya nursing database is a first step toward facilitating evidence-based decision-making in HRH. This database is unique to developing countries in sub-Saharan Africa. Establishing an electronic workforce database requires long-term investment and sustained support by national and global stakeholders.

Keywords: analytical, information, health, migration

Procedia PDF Downloads 96

Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

Abstract:

The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

Procedia PDF Downloads 182

Authors: Lingerew Nebere Kassie, Ping-Yu Chang, Hsin-Hua Huang, , Chaw-Son Chen

Abstract:

Transient electromagnetic (TEM) data plays a crucial role in hydrogeological and environmental applications, providing valuable insights into geological structures and resistivity variations. However, the presence of noise often hinders the interpretation and reliability of these data. Our study addresses this issue by utilizing a FASTSNAP system for the TEM survey, which operates at different modes (low, medium, and high) with continuous adjustments to discretization, gain, and current. We employ a denoising approach that processes the raw data obtained from each acquisition mode to improve signal quality and enhance data reliability. We use a signal-averaging technique for each mode, increasing the signal-to-noise ratio. Additionally, we utilize wavelet transform to suppress noise further while preserving the integrity of the underlying signals. This approach significantly improves the data quality, notably suppressing severe noise at late times. The resulting denoised data exhibits a substantially improved signal-to-noise ratio, leading to increased accuracy in parameter estimation. By effectively denoising TEM data, our study contributes to a more reliable interpretation and analysis of underground structures. Moreover, the proposed denoising approach can be seamlessly integrated into existing ground-based TEM data processing workflows, facilitating the extraction of meaningful information from noisy measurements and enhancing the overall quality and reliability of the acquired data.

Keywords: data quality, signal averaging, transient electromagnetic, wavelet transform

Procedia PDF Downloads 85