Search results for: decentralized data management

Authors: Butta Singh

Abstract:

This paper presents a chaotic map based approach for secured embedding of patient’s confidential data in electrocardiogram (ECG) signal. The chaotic map generates predefined locations through the use of selective control parameters. The sample value difference method effectually hides the confidential data in ECG sample pairs at these predefined locations. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through various statistical and clinical performance measures. Statistical metrics comprise of Percentage Root Mean Square Difference (PRD) and Peak Signal to Noise Ratio (PSNR). Further, a comparative analysis between proposed method and existing approaches was also performed. The results clearly demonstrated the superiority of proposed method.

Keywords: chaotic maps, ECG steganography, data embedding, electrocardiogram

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Authors: Nikhilesh Singh, Shishir Gaur, Anitha K. Sharma

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Climate change and anthropogenic stress have severely affected ecosystems all over the globe. Indian rivers are under immense pressure, facing challenges like pollution, encroachment, extreme fluctuation in the flow regime, local ignorance and lack of coordination between stakeholders. To counter all these issues a holistic river rejuvenation plan is needed that tests, innovates and implements sustainable solutions in the river space for sustainable river management. Smart Laboratory for Clean Rivers (SLCR) an Indo-Danish collaboration project, provides a living lab setup that brings all the stakeholders (government agencies, academic and industrial partners and locals) together to engage, learn, co-creating and experiment for a clean and sustainable river that last for ages. Just like every mega project requires piloting, SLCR has opted for a small catchment of the Varuna River, located in the Middle Ganga Basin in India. Considering the integrated approach of river rejuvenation, SLCR embraces various techniques and upgrades for rejuvenation. Likely, maintaining flow in the channel in the lean period, Managed Aquifer Recharge (MAR) is a proven technology. In SLCR, Floa-TEM high-resolution lithological data is used in MAR models to have better decision-making for MAR structures nearby of the river to enhance the river aquifer exchanges. Furthermore, the concerns of quality in the river are a big issue. A city like Varanasi which is located in the last stretch of the river, generates almost 260 MLD of domestic waste in the catchment. The existing STP system is working at full efficiency. Instead of installing a new STP for the future, SLCR is upgrading those STPs with an IoT-based system that optimizes according to the nutrient load and energy consumption. SLCR also advocate nature-based solutions like a reed bed for the drains having less flow. In search of micropollutants, SLCR uses fingerprint analysis involves employing advanced techniques like chromatography and mass spectrometry to create unique chemical profiles. However, rejuvenation attempts cannot be possible without involving the entire catchment. A holistic water management plan that includes storm management, water harvesting structure to efficiently manage the flow of water in the catchment and installation of several buffer zones to restrict pollutants entering into the river. Similarly, carbon (emission and sequestration) is also an important parameter for the catchment. By adopting eco-friendly practices, a ripple effect positively influences the catchment's water dynamics and aids in the revival of river systems. SLCR has adopted 4 villages to make them carbon-neutral and water-positive. Moreover, for the 24×7 monitoring of the river and the catchment, robust IoT devices are going to be installed to observe, river and groundwater quality, groundwater level, river discharge and carbon emission in the catchment and ultimately provide fuel for the data analytics. In its completion, SLCR will provide a river restoration manual, which will strategise the detailed plan and way of implementation for stakeholders. Lastly, the entire process is planned in such a way that will be managed by local administrations and stakeholders equipped with capacity-building activity. This holistic approach makes SLCR unique in the field of river rejuvenation.

Keywords: sustainable management, holistic approach, living lab, integrated river management

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Koray Altintas, Ozalp Vayvay

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Increased global issues such as depletion of sources, environmental problems and social inequality triggered public awareness towards finding sustainable solutions in order to ensure the well-being of the current as well as future generations. Since energy plays a significant role in improved social and economic well-being and is imperative on both industrial and commercial wealth creation, it is a must to develop a standardized set of metrics which makes it possible to indicate the present condition relative to conditions in the past and to develop any perspective which is required to frame actions for the future. This is not an easy task by considering the complexity of the issue which requires integrating economic, environmental and social aspects of sustainable energy. Multi-criteria decision making (MCDM) can be considered as a form of integrated sustainability evaluation and a decision support approach that can be used to solve complex problems featuring; conflicting objectives, different forms of data and information, multi-interests and perspectives. On that matter, MCDM methods are useful for providing solutions to complex energy management problems. The aim of this study is to review MCDM approaches that can be used for examining sustainable energy management. This study presents an insight into MCDM techniques and methods that can be useful for engineers, researchers and policy makers working in the energy sector.

Keywords: sustainable energy, sustainability criteria, multi-criteria decision making, sustainability dimensions

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Authors: Juan-Gabriel Cegarra-Navarro, Alexeis Garcia-Perez, Denise Bedford

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This paper provides guidelines for what constitutes a knowledge worker. Many graduates from non-managerial domains adopt, at some point in their professional careers, management roles at different levels, ranging from team leaders through to executive leadership. This is particularly relevant for professionals from an engineering background. Moving from a technical to an executive-level requires an understanding of those behaviour management techniques that can motivate and support individuals and their performance. Further, the transition to management also demands a shift of contextual enablers from tangible to intangible resources, which allows individuals to create new capacities, competencies, and capabilities. In this dynamic process, the knowledge worker becomes that key individual who can help members of the management board to transform information into relevant knowledge. However, despite its relevance in shaping the future of the organization in its transition to the knowledge economy, the role of a knowledge worker has not yet been studied to an appropriate level in the current literature. In this study, the authors review both the contextual enablers and behaviour outputs related to the role of the knowledge worker and relate these to their ability to deal with everyday management issues such as knowledge heterogeneity, varying motivations, information overload, or outdated information. This study highlights that the aggregate of capacities, competences and capabilities (CCCs) can be defined as knowledge structures, the study proposes several contextual enablers and behaviour outputs that knowledge workers can use to work cooperatively, acquire, distribute and knowledge. Therefore, this study contributes to a better comprehension of how CCCs can be managed at different levels through their contextual enablers and behaviour outputs.

Keywords: knowledge workers, capabilities, capacities, competences, knowledge structures

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Authors: Yendo Hu, Xu-Yu Wu, Dylan Oh

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GPS-Denied drones open the possibility of indoor applications, including dynamic arial surveillance, inspection, safety enforcement, and discovery. Indoor swarming further enhances these applications in accuracy, robustness, operational time, and coverage. For micro-drones, power management becomes a critical issue, given the battery payload restriction. This paper proposes an application enabling battery replacement solution that extends the micro-drone active phase without human intervention. First, a framework to quantify the effectiveness of a power management solution for a drone fleet is proposed. The operation-to-non-operation ratio, ONR, gives one a quantitative benchmark to measure the effectiveness of a power management solution. Second, a survey was carried out to evaluate the ONR performance for the various solutions. Third, through analysis, this paper proposes a solution tailored to the indoor micro-drone, suitable for swarming applications. The proposed automated battery replacement solution, along with a modified micro-drone architecture, was implemented along with the associated micro-drone. Fourth, the system was tested and compared with the various solutions within the industry. Results show that the proposed solution achieves an ONR value of 31, which is a 1-fold improvement of the best alternative option. The cost analysis shows a manufacturing cost of $25, which makes this approach viable for cost-sensitive markets (e.g., consumer). Further challenges remain in the area of drone design for automated battery replacement, landing pad/drone production, high-precision landing control, and ONR improvements.

Keywords: micro-drone, battery swap, battery replacement, battery recharge, landing pad, power management

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Authors: Joshua Ikpimi, Dimeji Abe, Nonso Okoye, Gideon Ikpimi, Prince Idemudia

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Training programmes are integral parts of development for employees to develop themselves and also to develop the organisation. Lack of training and inadequate training adversely affect the productivity in any organisation. Lack of training in the water sector can impair development and improper management of water. Training programs are given to water professionals, especially in a developing country like South Africa, to perform well in their day to day activities. The aim of this study was to evaluate the current training program in place for water professionals at KwaZulu Natal province of South Africa. The objectives were to determine the training programs that are suitable for their job descriptions and to determine the gaps with the training programs and to make recommendations on ways to improve the training programs. This study is a quantitative study which enabled an evaluation of training programs for KwaZulu Natal water professionals. The sample population was 120 professionals across all the cities and towns in KwaZulu Natal province. The water professionals were evaluated using structured questionnaire distributed to the respondents from September to December 2017. The data was analysed using R software. The study found that province has training programs that are valuable for their water professionals. However, involvement of some professionals in administrative activities was hindered by some inappropriate training. Many areas of improvement are suggested to the province in training its water professionals. Training was found to improve performance, commitment, motivation and staff retention of water professionals in the province.

Keywords: KwaZulu Natal, performance, training, water

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Authors: Hyun-Woo Cho

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The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

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Authors: Sandrine Andriantsimietry, Hantanirina Ravaosendrasoa

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Madagascar, in 2018, set up the first best available technology, autoclave, to treat the health care waste in public hospitals according the best environmental practices in health care waste management. Incineration of health care waste, frequently through open burning is the most common practice of treatment and elimination of health care waste across the country. Autoclave is a best available technology for non-incineration of health care waste that permits recycling of treated waste and prevents harm in environment through the reduction of unintended persistent organic pollutants from the health sector. A Global Environment Fund project supported the introduction of the non-incineration treatment of health care waste to help countries in Africa to move towards Stockholm Convention objectives in the health sector. Two teaching hospitals in Antananarivo and one district hospital in Manjakandriana were equipped respectively with 1300L, 250L and 80L autoclaves. The capacity of these model hospitals was strengthened by the donation of equipment and materials and the training of the health workers in best environmental practices in health care waste management. Proper segregation of waste in the wards to collect the infectious waste that was treated in the autoclave was the main step guaranteeing a cost-efficient non-incineration of health care waste. Therefore, the start-up of the switch of incineration into non-incineration treatment was carried out progressively in each ward with close supervision of hygienist. Emissions avoided of unintended persistent organic pollutants during these four months of autoclaves use is 9.4 g Toxic Equivalent per year. Public hospitals in low income countries can be model in best environmental practices in health care waste management but efforts must be made internally for sustainment.

Keywords: autoclave, health care waste management, model hospitals, non-incineration

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Authors: Ivana Tadic, Snjezana Pivac

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Although human resources are recognized as the crucial companies’ resources and their positive influence on companies’ performances has been confirmed through different researches, scientists are still debating it. In order to contribute this debate, this paper firstly discusses the most important human resource management elements and practices and its influence on companies’ success. Afterwards it defines human resource “bundles” – interrelated and internally consistent human resource practices, complementary to each other, or the most important human resource practices and elements regarding Croatian companies and its human resource management activities. Finally, the paper provides empirical results; more precisely it reveals the relation of the level of development of human resource management function (“bundles”) and companies’ financial performances (using profitability ratios, liquidity ratios, solvency ratios and a group of additional ratios related to employees’ indicators).

Keywords: companies’ performances, human resource bundles, multivariate statistical analysis, marketing

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Authors: Seonaid Hume, Gordon Dobie, Graeme West

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Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

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Authors: Muhammad Shoaib Iqbal, Shih Ping Ho

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Megaprojects are large-scale, complex ventures with significant financial investments, numerous stakeholders, and extended timelines, requiring meticulous management for successful completion. This study explores the interplay between project governance, project complexity, and servant leadership and their combined effects on project success, specifically within the context of Pakistani megaprojects. The primary objectives are to examine the direct impact of project governance on project success, understand the negative influence of project complexity, assess the positive role of servant leadership, explore the moderating effect of servant leadership on the relationship between governance and success, and investigate how servant leadership mitigates the adverse effects of complexity. Using a quantitative approach, survey data were collected from project managers and team members involved in Pakistani megaprojects. Using a Comprehensive empirical model, 257 Valid responses were analyzed. Multiple regression analysis tested the hypothesized relationships and interaction effects using PLS-SEM. Findings reveal that project governance significantly enhances project success, emphasizing the need for robust governance structures. Conversely, project complexity negatively impacts success, highlighting the challenges of managing complex projects. Servant leadership significantly boosts project success by prioritizing team support and empowerment. Although the interaction between governance and servant leadership is not significant, suggesting no significant change in project success, servant leadership significantly mitigates the negative effects of project complexity, enhancing team resilience and adaptability. These results underscore the necessity for a balanced approach integrating strong governance with flexible, supportive leadership. The study offers valuable insights for practitioners, recommending adaptive governance frameworks and promoting servant leadership to improve the management and success rates of megaprojects. This research contributes to the broader understanding of effective project management practices in complex environments.

Keywords: project governance, project complexity, servant leadership, project success, megaprojects, Pakistan

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Authors: Ishaq Kashif, Muhammad Younas, Muhammad Riaz, Mubarak Ali

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Poor feeding management during pre-weaning period is one of the factors resulting in compromised growth of Beetal kids fattened for meat purpose. The main reason for this anomaly may be less milk offered to kids and non-serious efforts for its management. This study was planned to find the most appropriate protein level suiting the age of the weaning while shifting animals to high input feeding system. Total of 42 Beetal male kids having 30 (±10), 60 (±10) and 90 (±10) days of age were selected with 16 in each age group. They were designated as G30, G60 and G90, respectively. The weights of animals were; 8±2 kg (G30), 12±2 kg (G60) and 16±2 kg (G90), respectively. All animals were weaned by introducing the total mix feed gradually and withdrawing the milk during the adjustment period of two weeks. The pelleted starter ration (total mix feed) with three various dietary protein levels designated as R1 (16% CP), R2 (20% CP) and R3 (26% CP) were introduced. The control group was reared on the fodder (Maize). The starter rations were iso-caloric and were offered for six-week duration. All animals were exposed to treatment using two-factor factorial (3×3) plus control treatment arrangement under completely randomized design. The data were collected on average daily feed intake (ADFI), average daily gain (ADG), gain to intake ratio, Klieber ratio (KR), body measurements and blood metabolites of kids. The data was analyzed using aov function of R-software. The statistical analysis showed that starter feed protein levels and age of weaning had significant interaction for ADG (P < 0.001), KR (P < 0.001), ADFI (P < 0.05) and blood urea nitrogen (P < 0.05) while serum creatinine and feed conversion had non-significant interaction. The trend analysis revealed that ADG had significant quadratic interaction (P < 0.05) within protein levels and age of weaning. It was found that animals weaned at 30 or 60 days, on R2 diet had better ADG (46.8 gm/day and 87.06 gm/day, respectively) weaned at 60 days of age. The animals weaned at 90 days had best ADG (127 gm/day) with R1. It is concluded that animal weaned at 30 or 40 days required 20% CP for better growth performance while animal at 90 days showed better performance with 16% CP.

Keywords: average daily gain, starter protein levels, weaning age, gain to intake ratio

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Authors: Hermann Luecken, Young Won Park, Judith M. Puetter

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Quality is known to be the accordance of product characteristics and customer requirements. Both the customer requirements and the assessment of the characteristics of the product with regard to the fulfillment of customer requirements are subject to cultural influences. Of course, the processes itself which lead to product manufacturing is also subject to cultural influences. In the first point, the cultural background of the customer influences the quality, in the second point, it is the cultural background of the employees and the company that influences the process itself. In times of globalization products are manufactured at different locations around the world, but typically the quality management system of the country in which the mother company is based is used. This leads to significantly different results in terms of productivity, product quality and process efficiency at the different locations, although the same quality management system is in use. The aim of an efficient and effective quality management system is therefore not doing the same at all locations, but to have the same result at all locations. In the past, standardization was used to achieve the same results. Recent investigations show that this is not the best way to achieve the same characteristics of product quality and production performance. In the present work, it is shown that the consideration of cultural aspects in the design of processes, production systems, and quality management systems results in a significantly higher efficiency and a quality improvement. Both Japanese and German companies were investigated with comparative interviews. The background of this selection is that in most cases the cultural difference regarding industrial processes between Germany and Japan is high. At the same time, however, the customer expectations regarding the product quality are very similar. Interviews were conducted with experts from German and Japanese companies; in particular, companies were selected that operate production facilities both in Germany and in Japan. The comparison shows that the cultural influence on the respective production performance is significant. Companies that adapt the design of their quality management and production systems to the country where the production site is located have a significantly higher productivity and a significantly higher quality of the product than companies that work with a centralized system.

Keywords: comparison of German and Japanese production systems, cultural influence on quality management, expert interviews, process efficiency

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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Authors: Abdullah Arafat, Ali Al-Farhan, Amir Omair

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Objectives: To review and assess the effectiveness of the implemented modified five-levels triage and acuity scale triage system in AL-Yarmook Urgent Care Center (UCC), King Abdulaziz Residential city, Riyadh, Saudi Arabia. Method: The applied study design was an observational cross sectional design. A data collection sheet was designed and distributed to triage nurses; the data collection was done during triage process and was directly observed by the co-investigator. Triage system was reviewed by measuring three time intervals as quality indicators: time before triage (TBT), time before being seen by physician (TBP) and total length of stay (TLS) taking in consideration timing of presentation and level of triage. Results: During the study period, a total of 187 patients were included in our study. 118 visits were at weekdays and 68 visits at weekends. Overall, 173 patients (92.5%) were seen by the physician in timely manner according to triage guidelines while 14 patients (7.5%) were not seen at appropriate time.Overall, The mean time before seen the triage nurse (TBT) was 5.36 minutes, the mean time to be seen by physician (TBP) was 22.6 minutes and the mean length of stay (TLS) was 59 minutes. The data didn’t showed significant increase in TBT, TBP, and number of patients not seen at the proper time, referral rate and admission rate during weekend. Conclusion: The CTAS is adaptable to countries beyond Canada and worked properly. The applied CTAS triage system in Al-Yarmook UCC is considered to be effective and well applied. Overall, urgent cases have been seen by physician in timely manner according to triage system and there was no delay in the management of urgent cases.

Keywords: CTAS, emergency, Saudi Arabia, triage, urgent care

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Suglo Tohari Luri

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Data analysis is an important aspect of business performance. With the application of artificial intelligence within databases, selecting a suitable database engine for an application design is also very crucial for business data analysis. The application of business intelligence (BI) software into some relational databases such as Neo4j has proved highly effective in terms of customer data analysis. Yet what remains of great concern is the fact that not all business organizations have the neo4j business intelligence software applications to implement for customer data analysis. Further, those with the BI software lack personnel with the requisite expertise to use it effectively with the neo4j database. The purpose of this research is to demonstrate how the Neo4j program code alone can be applied for the analysis of e-commerce website customer visits. As the neo4j database engine is optimized for handling and managing data relationships with the capability of building high performance and scalable systems to handle connected data nodes, it will ensure that business owners who advertise their products at websites using neo4j as a database are able to determine the number of visitors so as to know which products are visited at routine intervals for the necessary decision making. It will also help in knowing the best customer segments in relation to specific goods so as to place more emphasis on their advertisement on the said websites.

Keywords: data, engine, intelligence, customer, neo4j, database

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Authors: Kanwal Javid, Shazia Pervaiz, Maria Mumtaz, Muhammad Ameer Nawaz Akram

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Forests and grasslands ecosystems play an important role in the global carbon cycle. Land management activities influence both ecosystems and enable them to absorb and sequester carbon dioxide (CO2). Similarly, in Pakistan, these terrestrial ecosystems are well known to mitigate carbon emissions and have a great source to supply a variety of services such as clean air and water, biodiversity, wood products, wildlife habitat, food, recreation and carbon sequestration. Carbon sequestration is the main agenda of developed and developing nations to reduce the impacts of global warming. But the amount of carbon storage within these ecosystems can be affected by many factors related to air quality such as land management, land-use change, deforestation, over grazing and natural calamities. Moreover, the long-term capacity of forests and grasslands to absorb and sequester CO2 depends on their health, productivity, resilience and ability to adapt to changing conditions. Thus, the main rationale of this study is to monitor the difference in carbon amount of forests and grasslands of Northern Pakistan using MODIS data sets and map results using Geographic Information System. Results of the study conclude that forests ecosystems are more effective in reducing the CO2 level and play a key role in improving the quality of air.

Keywords: carbon sequestration, grasslands, global warming, climate change.

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Authors: R. Gupta, P. Jain, S. Das

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One way to approach construction scheduling optimization problem is to focus on the individual aspects of planning, which can be broadly classified as time scheduling, crew and resource management, and cost control. During the last four decades, construction planning has seen a lot of research, but to date, no paper had attempted to summarize the literature available under important heads. This paper addresses each of aspects separately, and presents the findings of an in-depth literature of the various planning techniques. For techniques dealing with time scheduling, the authors have adopted a rough chronological documentation. For crew and resource management, classification has been done on the basis of the different steps involved in the resource planning process. For cost control, techniques dealing with both estimation of costs and the subsequent optimization of costs have been dealt with separately.

Keywords: construction planning techniques, time scheduling, resource planning, cost control

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Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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Authors: Chen Xi, LIU Xuebin, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Lao Xuerui

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature have led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using Yolov5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network, machine vision

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Authors: Babanyara Y. Y., Ibrahim D. B., Garba T., Bogoro A. G., Abubakar, M. Y.

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Medical care is vital for our life, health, and well-being. However, the waste generated from medical activities can be hazardous, toxic, and even lethal because of their high potential for diseases transmission. The hazardous and toxic parts of waste from healthcare establishments comprising infectious, medical, and radioactive material as well as sharps constitute a grave risks to mankind and the environment, if these are not properly treated/disposed or are allowed to be mixed with other municipal waste. In Nigeria, practical information on this aspect is inadequate and research on the public health implications of poor management of medical wastes is few and limited in scope. Findings drawn from Literature particularly in the third world countries highlights financial problems, lack of awareness of risks involved in MWM, lack of appropriate legislation and lack of specialized MWM staff. The paper recommends how MWM practices can be improved in medical facilities.

Keywords: environmental pollution, infectious, management, medical waste, public health

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Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

Abstract:

The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

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Authors: H. N. S. Silva, S. N. Silva

Abstract:

Introduction: The latest WHO data published in 2014 states that Sri Lanka has reached 2,773 of total deaths and over 14000 individuals’ sustained injuries due to RTAs each year. It was noticed in previous studies that policemen, three wheel drivers and also pedestrians were the first to respond to RTAs but the victim’s condition was aggravated due to unskilled attempts made by the responders while management of the victim’s wounds, moving and positioning of the victims and also mainly while transportation of the victims. Objective: To observe the practices of the urban public in Sri Lanka who are encountered with RTAs. Methods: A qualitative study was done to analyze public behavior seen on video recordings of scenes of accidents purposefully selected from social media, news websites, YouTube and Google. Results: The results showed that all individuals who tried to help during the RTA were middle aged men, who were mainly pedestrians, motorcyclists and policemen during that moment. Vast majority were very keen to actively help the victims to get to hospital as soon as possible and actively participated in providing 'aid'. But main problem was the first aid attempts were disorganized and uncoordinated. Even though all individuals knew how to control external bleeding, none of them was aware of spinal prevention techniques or management of limb injuries. Most of the transportation methods and transfer techniques used were inappropriate and more injury prone. Conclusions: The public actively engages in providing aid despite their inappropriate practices in giving first aid.

Keywords: encountered, pedestrians, road traffic accidents, urban public

Procedia PDF Downloads 282

Authors: Fan Ye

Abstract:

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

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

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Authors: Rahul Malhotra

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 550

Authors: Amany A. Ragheb, Ghada Ragheb, Abd ElRahman A.

Abstract:

Egypt has a countless heritage of mansions, castles, cities, towns, villages, industrial and manufacturing sites. This richness of heritage provides endless and matchless prospects for culture. Despite being famous worldwide, Egypt’s heritage still is in constant need of protection. Political conflicts and religious revolutions form a direct threat to buildings in various areas, historic, archaeological sites, and religious monuments. Egypt has witnessed two revolutions in less than 60 years; both had an impact on its architectural heritage. In this paper, the authors aim to review legal and policy framework to protect the cultural heritage and present the risk management strategy for cultural heritage in conflict. Through a review of selected international models of devastated architectural heritage in conflict zones and highlighting some of their changes, we can learn from the experiences of other countries to assist towards the development of a methodology to halt the plundering of architectural heritage. Finally, the paper makes an effort to enhance the formulation of a risk management strategy for protection and conservation of cultural heritage, through which to end the plundering of Egypt’s architectural legacy in the Egyptian community (revolutions, 1952 and 2011); and by presenting to its surrounding community the benefits derived from maintaining it.

Keywords: cultural heritage, legal regulation, risk management, preservation

Procedia PDF Downloads 392

Authors: Vahid Bayrami Rad

Abstract:

In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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Authors: Roberta Mugellesi Dow

Abstract:

As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

Procedia PDF Downloads 126