Search results for: local stakeholders network

Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

Procedia PDF Downloads 533

Authors: Padma Chutoo, Elena Kulinskaya, Ilyas Bakbergenuly, Nicholas Steel, Dmitri Pchejetski

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Stroke is associated with a significant risk of morbidity and mortality. There is scarcity of research on the long-term survival after first-ever ischaemic stroke (IS) events in England with regards to effects of different medical therapies and comorbidities. The objective of this study was to model the all-cause mortality after an IS diagnosis in the adult population of England. Using a retrospective case-control design, we extracted the electronic medical records of patients born prior to or in year 1960 in England with a first-ever ischaemic stroke diagnosis from January 1986 to January 2017 within the Health and Improvement Network (THIN) database. Participants with a history of ischaemic stroke were matched to 3 controls by sex and age at diagnosis and general practice. The primary outcome was the all-cause mortality. The hazards of the all-cause mortality were estimated using a Weibull-Cox survival model which included both scale and shape effects and a shared random effect of general practice. The model included sex, birth cohort, socio-economic status, comorbidities and medical therapies. 20,250 patients with a history of IS (cases) and 55,519 controls were followed up to 30 years. From 2008 to 2015, the one-year all-cause mortality for the IS patients declined with an absolute change of -0.5%. Preventive treatments to cases increased considerably over time. These included prescriptions of statins and antihypertensives. However, prescriptions for antiplatelet drugs decreased in the routine general practice since 2010. The survival model revealed a survival benefit of antiplatelet treatment to stroke survivors with hazard ratio (HR) of 0.92 (0.90 – 0.94). IS diagnosis had significant interactions with gender and age at entry and hypertension diagnosis. IS diagnosis was associated with high risk of all-cause mortality with HR= 3.39 (3.05-3.72) for cases compared to controls. Hypertension was associated with poor survival with HR = 4.79 (4.49 - 5.09) for hypertensive cases relative to non-hypertensive controls, though the detrimental effect of hypertension has not reached significance for hypertensive controls, HR = 1.19(0.82-1.56). This study of English primary care data showed that between 2008 and 2015, the rates of prescriptions of stroke preventive treatments increased, and a short-term all-cause mortality after IS stroke declined. However, stroke resulted in poor long-term survival. Hypertension, a modifiable risk factor, was found to be associated with poor survival outcomes in IS patients. Antiplatelet drugs were found to be protective to survival. Better efforts are required to reduce the burden of stroke through health service development and primary prevention.

Keywords: general practice, hazard ratio, health improvement network (THIN), ischaemic stroke, multiple imputation, Weibull-Cox model.

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Authors: Jisong Zhang, Yinghua Zhao

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The present study investigated the mechanical properties and microstructure of Ultra-High Performance Concrete (UHPC) containing supplementary cementitious materials (SCMs), such as fly ash (FA) and silica fume (SF), and to verify the synergistic effect in the ternary system. On the basis of 30% fly ash replacement, the incorporation of either 10% SF or 20% SF show a better performance compared to the reference sample. The efficiency factor (k-value) was calculated as a synergistic effect to predict the compressive strength of UHPC with these SCMs. The SEM of micrographs and pore volume from BJH method indicate a high correlation with compressive strength. Further, an artificial neural networks model was constructed for prediction of the compressive strength of UHPC containing these SCMs.

Keywords: artificial neural network, fly ash, mechanical properties, ultra-high performance concrete

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Authors: Shelly-Ann Gajadhar

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Over the last twenty years, the traditional economic motivations of foreign direct investment have been amalgamated with geopolitical motivations. This is evidenced by the extensive ratification of bilateral investment treaties (BIT) globally and the emergence of state-owned multinational companies (SOMNCs) that directly compete with local domestic enterprises (LDE). This paper investigates the impact that Chinese SOMNCs have on LDEs within Trinidad and Tobago’s construction sector and, determines whether knowledge transfer occurs. The paper employed semi-structured interviews of industry experts and concluded that LDEs predominantly experience adverse spillovers, inclusive of a long-term competition effect, with no technology transfer occurring.

Keywords: foreign direct investment, bilateral investment treaties, knowledge transfer, international business, Caribbean

Procedia PDF Downloads 247

Authors: Sohni Siddiqui, Anja Schultze-Krumbholz

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Our lives now revolve more around online-related tasks, as the internet has become a necessity. One of the disturbance concerns with high internet usage is the multiplication of cyber-associated risky behaviors such as cyber aggression and/or cyberbullying. Cyber Bullying is an emerging issue that needs immediate attention from many stakeholders such as parents, doctors, school administrators, policymakers, researchers, and others, especially in the COVID-19 pandemic when online learning has been adopted as an instructional strategy, and there is a continuous rise in cyberbullying cases. The aim of the article is to review existing successful and emerging interventions designed to control bullying and cyberbullying by engaging individuals through teachers’ professional development and adopting a whole-school approach. The study identified the strengths and limitations of the programs and suggested improvements to existing interventions. Preparing interventions with a strong theoretical framework, integrating applications of emerging theories in interventions, promoting proactive and reactive strategies in combination, beginning with the baseline needs assessment surveys, reducing digital time and digital divide among parents and children, promoting the concept of lead trainer, peer trainer, and hot spots, focusing on physical activities, use of landmarks are some of the recommendations proposed by authors. In addition to face-to-face intervention, the researchers recommend updating and improving previous intervention programs with games and apps. Especially in the time of pandemic crises, when face-to-face interactions are limited and cyberbullying is triggered, the use of apps, web-based interventions, and games can be an effective way to control electronic perpetration and victimization.

Keywords: anti bullying programs, cyber bullying, individualized trainings, teachers’ professional development, whole school interventions

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Authors: Chris Nelson

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Quality and excellence are qualitative topics that are usually addressed based on knowledge and past experience from leadership and those in charge of the organization. The significance of this study is to highlight the differences and similarities between these two mindsets and how an operational staff can most appropriately use them in the workplace. Quality and excellence are two words that are talked about a lot in the manufacturing world. Buzzwords such as operational excellence, quality controls, and efficiencies are discussed in the boardroom as well on the shop floor. These terms are used quite frequently and with good reasons. When a person visits their favorite local restaurant, They go because 1) they like the food and 2) the people are some of the greatest individuals to be around. With that in mind, they know they always put out quality food. They do not always go because the quality of the food is far superior than other restaurants. But the quality of ingredients always meets their expectations. When they compare them to the term excellence, they are disappointed. The food never looks like the pictures on the menu. But when have you ever been to a restaurant where the food looks the same as on the menu? For them, when evaluating which buzzword to use as a guiding star, its simple: excellence. The corporation can accomplish these goals by operating at a standard that far exceeds customer’s wants and needs.

Keywords: industrial engineering, innovation, management and technology, logistics and scheduling, six sigma

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Authors: Mohammed Islam

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Graduate employability is a well debated topic by governments, employers, and higher education institutes (HEI) across the world. Much of the focus of these debates have centred around the skills that graduates bring or should bring to the job market, a point echoed by United Arab Emirates (UAE) policy makers and employers. While some research has been carried out on graduates' employability skills, little or no attention has been paid to the forces at play in developing employability policy and its subsequent implementation. The focus of debate has been on a perceived skills gap rather than policy. Recognising a gap in the literature, this paper details a study of UAE employability policy development. Taking a social constructionist approach, this case study views policy as discursive and socially constructed through interactions with key stakeholders. It is within the myriad of interdependent socio-political factors and social practices, particularly power relationships, that this paper explores UAE policy on graduate employability. In doing so, this adds to the debate on graduate employability from the perspective of policy and explores its roots in the interaction between human activity and the ‘system’. Data was collected from two main sources: documentary review and semi-structured interviews. Policies and publicly stated rhetoric on graduate employability were analysed using Critical Discourse Analysis. Semi-structured interviews with representatives from policy makers, HEIs, and employers were reviewed through Thematic Analysis. The theoretical framework for the discussion of findings draws from social practice theories and highlights the factors at play in access to employment for UAE graduates. This case study presents a methodological approach to policy studies that can be applied beyond the context under investigation. Education policy researchers are provided with an opportunity to compare similarities and differences with their own specific contexts.

Keywords: critical discourse analysis, employability, methodology, policy, social constructionism

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Authors: Umang Varshney, Amit Karamchandani, Rohit Kapoor

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Practitioners and researchers have realized that Blockchain is not limited to currency. Blockchain as a distributed ledger can ensure a transparent and traceable supply chain. Due to Blockchain-enabled IoTs, a firm’s information management system can now take inputs from other supply chain partners in real-time. This study aims to provide empirical evidence of dimensions responsible for blockchain implemented firm’s growth and highlight how sector (manufacturing or service), state's regulatory environment, and choice of blockchain network affect the blockchain's usefulness. This post-adoption study seeks to validate the findings of pre-adoption studies done on the blockchain. Data will be collected through a survey of managers working in blockchain implemented firms and analyzed through PLS-SEM.

Keywords: blockchain, information management system, PLS-SEM, firm's growth

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Authors: Amir Abbas Kamanbedast, Masood Mohammad Shafipor, Amir Ghotboddin

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Fish way is a structure that in generally using to migrate to the place where they are spawned and is made near the spillway. Preventing fish spawning or migrating to their original place by fishway structures can affect their lives in the river or even erase one access to intended environment. The main objective of these structures is establishing a safe path for fish migration. In the present study first the hydraulic specifications of Hamidieh diversion dam were assessed and then it is problems were evaluated. In this study the dimensions of the fish way, including velocity of pools, were evaluated by CCHE2D software. Then by change slope in this structure streamlines like velocity in the pools were measured. For calibration can be use measuring local velocities in some pools. The information can be seen the fishway width of 0.3 m has minimum rate of descent in the total number of structures (pools and overflow).

Keywords: fishway, velocity, Hamidieh-Diversion Dam, CCHE2D model

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Authors: Ozoemelam Ikechukwu Lazarus, Nizamuddin B. Zainuddi, Abdul Kafi

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Numerous studies have been carried out on Green Logistics Management Practices (GLMPs) across the globe. The study on the practices and performance of green chain practices in Africa in particular has not gained enough scholarly attention. Again, the majority of supply chain sustainability research being conducted focus on environmental sustainability. Logistics has been a major cause of supply chain resource waste and environmental damage. Many sectors of the economy that engage in logistical operations significantly rely on vehicles, which emit pollutants into the environment. Due to urbanization and industrialization, the logistical operations of manufacturing companies represent a serious hazard to the society and human life, making the sector one of the fastest expanding in the world today. Logistics companies are faced with numerous difficulties when attempting to implement logistics practices along their supply chains. In Nigeria, manufacturing companies aspire to implement reverse logistics in response to stakeholders’ requirements to reduce negative environmental consequences. However, implementing this is impeded by a criteria framework, and necessitates the careful analysis of how such criteria interact with each other in the presence of uncertainty. This study integrates most of the green logistics management practices (GLMPs) into the Nigerian firms to improve generalizability, and credibility. It examines the effect of Green Logistics Management Practices on environmental performance, social performance, market performance, and financial performance in the logistics industries. It seeks to identify the critical success factors in order to develop a model that incorporates different factors from the perspectives of the technology, organization, human and environment to inform the adoption and use of technologies for logistics supply chain social sustainability in Nigeria. It uses exploratory research approach to collect and analyse the data.

Keywords: logistics, management, sustainability, environment, operations

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Authors: S. Bennoud, S. Hocine, H. Slme

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Developments in turbine cooling technology play an important role in increasing the thermal efficiency and the power output of recent gas turbines, in particular the turbojets. Advanced turbojets operate at high temperatures to improve thermal efficiency and power output. These temperatures are far above the permissible metal temperatures. Therefore, there is a critical need to cool the blades in order to give theirs a maximum life period for safe operation. The focused objective of this work is to calculate the turbojet performances, as well as the calculation of turbine blades cooling. The developed application able the calculation of turbojet performances to different altitudes in order to find a point of optimal use making possible to maintain the turbine blades at an acceptable maximum temperature and to limit the local variations in temperatures in order to guarantee their integrity during all the lifespan of the engine.

Keywords: brayton cycle, turbine blades cooling, turbojet cycle, turbojet performances

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: O. Arbouche, Y. Benallou, K. Amara

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We report a first-principles study of structural, electronic and magnetic properties of ternary plumbides (rare earth-transition metal-Plumb) Dy2Ni2Pb crystallizes with the orthorhombic structure of the Mn2AlB2 type (space group Cmmm), were studied by means of the full-relativistic version of the full-potential augmented plane wave plus local orbital method within the frame work of spin-polarized density functional theory (SP-DFT). The electronic exchange-correlation energy is described by generalized gradient approximation (GGA). We have calculated the lattice parameters, bulk modulii and the first pressure derivatives of the bulk modulii, total densities of states and magnetic properties. The calculated total magnetic moment is found to be equal to 9.52 μB.

Keywords: spin-polarized, magnetic properties, Dy2Ni2Pb, Density functional theory

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Authors: Kuladeep Kumar Sadevi

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The shift towards raising global urban population has intense implications on the sustainability of the urban livelihoods. Rapid urbanization has made governments, companies and civil societies recognize that they are barely equipped to deal with growing urban demands, especially water, waste and energy management. Effective management of land, water, energy and waste at a community level should be addressed well to attain greener cities. In pursuit of Green livelihoods; various norms, codes, and green rating programmes have been followed by stakeholders at various levels. While the sustainability is being adapted at smaller scale developments, greening the urban environment at community/city level is still finding its path to reality. This is due to lack of the sense of ownership in the citizens for their immediate neighborhoods and city as a whole. This phenomenon can be well connected to the theory of 'tragedy of commons' with respect to the community engagement to manage the common pool resources. The common pool resource management has been well addressed by Elinor Ostrom, who shared the Nobel Prize in Economics in 2009 for her lifetime of scholarly work investigating how communities succeed or fail at managing common pool (finite) resources. This paper examines the applicability of Elinor Ostrom's 8 Principles for Managing a Commons, to meet urban sustainability. The key objective of this paper is to come up with a model for effective urban common pool resource management, which ultimately leads to sustainability as a whole. The paper brings out a methodology to understand various parameters involved in urban sustainability, examine the synergies of all such parameters, and application of Ostrom’s principles to correlate these parameters in order to attain effective urban resource management.

Keywords: common pool resources, green cities, green communities, participatory management, sustainable development, urban resource management, urban sustainability

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Authors: Fabricia G. F. S. Rossato, Ieda G. Hidalgo, Andres Susseta, Felipe Casale, Leticia H. Nakamiti

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This research was conducted to show the useful source of biomass energy provided from forest waste and the black liquor from the pulping process. This energy source could be able to assist and improve its area environment in a sustainable way. The research will demonstrate the challenges from producing the biomass energy and the implantation of the pulp industry in the city of Três Lagoas, MS. – Brazil. Planted forest’s potential, energy production in the pulp industries and its consequence of impacts on the local region environmental was also studied and examined. The present study is classified as descriptive purposes as it exposes the characteristics of a given population and the means such as bibliographical and documentary. All the data and information collected and demonstrate in this study was carefully analyzed and provided from reliable sources such as official government agencies.

Keywords: Brazil, pulp industry, renewable energy, Três Lagoas

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Authors: Muhammad Yusuf Abduh, Robert Manurung, Hero Jan Heeres

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Biodiesel can be produced in small scale mobile units which are designed with local input and demand. Unlike the typical biodiesel production plants, mobile biodiesel unit consiss of a biodiesel production facility placed inside a standard cargo container and mounted on a truck so that it can be transported to a region near the location of raw materials. In this paper, we review the existing concept and unit for the development of community-scale and mobile production of biodiesel. This includes the main reactor technology to produce biodiesel as well as the pre-treatment prior to the reaction unit. The pre-treatment includes the oil-expeller unit to obtain oil from the oilseeds as well as the quality control of the oil before it enters the reaction unit. This paper also discusses the post-treatment after the production of biodiesel. It includes the refining and purification of biodiesel to meet the product specification set by the biodiesel industry.

Keywords: biodiesel, community scale, mobile biodiesel unit, reactor technology

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Bibi Somayeh Aliakbari, Niknaz Kachooei, Fatemeh Amiri Najafabadi

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According to the results of contemporary urbanism, social living moved into buildings and the quality of urban space has been declining. But still, there are life in open public space and it is one of reason attendance and activities of people in open public spaces.The purpose of this research is finding reason creation friendly public space in urban spaces and also use these in new urban spaces.The research methodology consisted of a qualitative model based on observation and graphical analysis. In this paper case study is public space historical, moderns in urban scales and local scales in Iran.This paper shows that Existence of friendly public space in cities cause is attendance and activities of people in open public spaces that it is reason the revitalization of public open spaces in cities.

Keywords: public space, public open space, friendly public space, Iran

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in various domains has created a pressing need for effective methods to transform this data into meaningful knowledge. In this era of big data, mathematical and statistical innovations play a crucial role in unlocking insights and facilitating informed decision-making in data analytics. This abstract aims to explore the transformative potential of these innovations and their impact on converting raw data into actionable knowledge. Drawing upon a comprehensive review of existing literature, this research investigates the cutting-edge mathematical and statistical techniques that enable the conversion of data into knowledge. By evaluating their underlying principles, strengths, and limitations, we aim to identify the most promising innovations in data analytics. To demonstrate the practical applications of these innovations, real-world datasets will be utilized through case studies or simulations. This empirical approach will showcase how mathematical and statistical innovations can extract patterns, trends, and insights from complex data, enabling evidence-based decision-making across diverse domains. Furthermore, a comparative analysis will be conducted to assess the performance, scalability, interpretability, and adaptability of different innovations. By benchmarking against established techniques, we aim to validate the effectiveness and superiority of the proposed mathematical and statistical innovations in data analytics. Ethical considerations surrounding data analytics, such as privacy, security, bias, and fairness, will be addressed throughout the research. Guidelines and best practices will be developed to ensure the responsible and ethical use of mathematical and statistical innovations in data analytics. The expected contributions of this research include advancements in mathematical and statistical sciences, improved data analysis techniques, enhanced decision-making processes, and practical implications for industries and policymakers. The outcomes will guide the adoption and implementation of mathematical and statistical innovations, empowering stakeholders to transform data into actionable knowledge and drive meaningful outcomes.

Keywords: data analytics, mathematical innovations, knowledge extraction, decision-making

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Authors: Supattra Kanchanopast

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The purpose of this research is to develop and design a management information system for 7 eleven shop in Bangkok. The system was designed and developed to meet users’ requirements via the internet network by use of application software such as My SQL for database management, Apache HTTP Server for Web Server and PHP Hypertext Preprocessor for an interface between web server, database and users. The system was designed into two subsystems as the main system, or system for head office, and the branch system for branch shops. These consisted of three parts which are classified by user management as shop management, inventory management and Point of Sale (POS) management. The implementation of the MIS for the mini-mart shop, can lessen the amount of paperwork and reduce repeating tasks so it may decrease the capital of the business and support an extension of branches in the future as well.

Keywords: convenience store, the management information system, inventory management, 7 eleven shop

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Elmira Fotoohi

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Representation of women in commercials and the place of sex in advertising is a part of communication studies and all of them are subset of advertising sociology. In this context, a lot of national and international studies have been done from different aspects. But in the meantime, and in connection with women issues, researchers in Communication Science and Sociology are interested in two topics “use of pornographic images of women” and “repeated representations of women in traditional roles and gender stereotypes by emphasizing the differences between men and women”, more than any other topics. Considering a number of changes that have occurred in social institutions and at different levels, the main research question currently are, what is the role of women in our TV ads and how are they represented in them? Do the local television ads represent women in the same issues as the researchers on this topic has proposed or new changes have occurred? Many scholars and thinkers in the field of media outlet that, today, media not just focus on women as gender issues or sex objects, but also seeks to strengthen the gender division of labor in the family and emphasize on the traditional muliebrity and masculinity stereotype.

Keywords: women, representation, tv commercials, advertising sociology, gender stereotypes

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Authors: Andreas Kohlhepp, Gerrit Schatte, Wieland Christoph, Spliethoff Hartmut

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In recent years the research of heat transfer phenomena of water and other working fluids near the critical point experiences a growing interest for power engineering applications. To match the highly volatile characteristics of renewable energies, conventional power plants need to shift towards flexible operation. This requires speeding up the load change dynamics of steam generators and their heating surfaces near the critical point. In dynamic load transients, both a high heat flux with an unfavorable ratio to the mass flux and a high difference in fluid and wall temperatures, may cause problems. It may lead to deteriorated heat transfer (at supercritical pressures), dry-out or departure from nucleate boiling (at subcritical pressures), all cases leading to an extensive rise of temperatures. For relevant technical applications, the heat transfer coefficients need to be predicted correctly in case of transient scenarios to prevent damage to the heated surfaces (membrane walls, tube bundles or fuel rods). In transient processes, the state of the art method of calculating the heat transfer coefficients is using a multitude of different steady-state correlations for the momentarily existing local parameters for each time step. This approach does not necessarily reflect the different cases that may lead to a significant variation of the heat transfer coefficients and shows gaps in the individual ranges of validity. An algorithm was implemented to calculate the transient behavior of steam generators during load changes. It is used to assess existing correlations for transient heat transfer calculations. It is also desirable to validate the calculation using experimental data. By the use of a new full-scale supercritical thermo-hydraulic test rig, experimental data is obtained to describe the transient phenomena under dynamic boundary conditions as mentioned above and to serve for validation of transient steam generator calculations. Aiming to improve correlations for the prediction of the onset of deteriorated heat transfer in both, stationary and transient cases the test rig was specially designed for this task. It is a closed loop design with a directly electrically heated evaporation tube, the total heating power of the evaporator tube and the preheater is 1MW. To allow a big range of parameters, including supercritical pressures, the maximum pressure rating is 380 bar. The measurements contain the most important extrinsic thermo-hydraulic parameters. Moreover, a high geometric resolution allows to accurately predict the local heat transfer coefficients and fluid enthalpies.

Keywords: departure from nucleate boiling, deteriorated heat transfer, dryout, supercritical working fluid, transient operation of steam generators

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Authors: Raif Parlakkaya, Mustafa Nihat Demirci, Mehmet Nuri Salur

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Environmental pollution has detrimental effects on the quality of our life and its scope has reached such an extent that measures are being taken both at the national and international levels to reduce, prevent and mitigate its impact on social, economic and political spheres. Therefore, awareness of environmental problems has been increasing among stakeholders and accordingly among companies. It is seen that corporate reporting is expanding beyond environmental performance. Primary purpose of publishing an environmental report is to provide specific audiences with useful, meaningful information. This paper is intended to analyze the extent and qualification of environmental disclosures of Turkish publicly quoted firms and see how it varies from one sector to another. The data for the study were collected from annual activity reports of companies, listed on the corporate governance index (BIST-XKURY) of Istanbul Stock Exchange. Content analysis was the research methodology used to measure the extent of environmental disclosure. Accordingly, 2015 annual activity reports of companies that carry out business in some particular fields were acquired from Capital Market Board, websites of Public Disclosure Platform and companies’ own websites. These reports were categorized into five main aspects: Environmental policies, environmental management systems, environmental protection and conservation activities, environmental awareness and information on environmental lawsuits. Subsequently, each component was divided into several variables related to what each firm is supposed to disclose about environmental information. In this context, the nature and scope of the information disclosed on each item were assessed according to five different ways (N.I: No Information; G.E.: General Explanations; Q.E.: Qualitative Detailed Explanations; N.E.: Quantitative (numerical) Detailed Explanations; Q.&N.E.: Both Qualitative and Quantitative Explanations).

Keywords: environmental accounting, disclosure, corporate governance, content analysis

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Authors: Daniel Barkley, Jianyi Zhu

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This study investigates base salary differentials and gender equity among university presidents across 427 U.S. colleges and universities. While endowments typically do not directly determine university presidents' base salaries, our analysis reveals a noteworthy pattern: endowments explain more than half of the variance in female university presidents' base salaries, compared to a mere 0.69 percent for males. Moreover, female presidents' base salaries tend to rise much faster than male base salaries with increasing university endowments. This disparate impact of endowments on base salaries implies an endowment threshold for achieving gender pay equity. We develop an analytical model predicting an endowment threshold for achieving gender equality and empirically estimate this equity threshold using data from over 427 institutions. Surprisingly, the fields of science and athletics have emerged as sources of gender-neutral base pay. Both male and female university presidents with STEM backgrounds command higher base salaries than those without such qualifications. Additionally, presidents of universities affiliated with Power 5 conferences consistently receive higher base salaries regardless of gender. Consistent with the theory of human capital accumulation, the duration of the university presidency incrementally raises base salaries for both genders but at a diminishing rate. Curiously, prior administrative leadership experience as a vice president, provost, dean, or department chair does not significantly influence base salaries for either gender. By providing empirical evidence and analytical models predicting an endowment threshold for achieving gender equality in base salaries, the study offers valuable insights for policymakers, university administrators, and other stakeholders. These findings hold crucial policy implications, informing strategies to promote gender equality in executive compensation within higher education institutions.

Keywords: higher education, endowments, base salaries, university presidents

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Dariush Jafari, Seyed Ali Jafari

Abstract:

The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water

Procedia PDF Downloads 422

Authors: J. Dutton, L. Knight

Abstract:

Achieving quality and respectful maternal health care is part of the global agenda to improve reproductive health and achieve universal reproductive rights. Barriers to quality of care in South African maternal health facilities exist at both systemic and individual levels. Addition to this, the normalization of gender violence within South Africa has a large impact on people seeking health care as well as those who provide care within health facilities. The hierarchical environment of South Africa’s public health system penalizes both patients and providers who battle to assume any assessable power. This paper explores how systemic and individual level barriers to quality of care affect the midwifery profession within South African maternal health services and create, at times, an environment of enmity rather than care. This paper analyzes and discusses the data collected from in-depth, semi-structured interviews with nurses and midwives at three maternal health facilities in South Africa. This study has taken a holistic approach to understand the realities of nurses and midwives in order to explore the ways in which experience informs their practice and treatment of pregnant women. Through collecting and analyzing narratives, linkages between nurses and midwives day-to-day and historical experiences and disrespectful care have been made. Findings from this study show that barriers to quality of care take form in complex and interrelated ways. The physical structure of the health facility, human resource shortages, and the current model of maternal health care, which often lacks a person-centered approach, is entangled within personal beliefs and attitudes of what it means to be a midwife to create an environment that is often not conducive to a positive birthing experience. This entanglement sits within a society of high rates of violence, inequality, and poverty. Having teased out the nuances of each of these barriers and the multiple ways they reinforce each other, the findings of this paper demonstrate that birth, and the work of a midwife, are situated in a mode of discipline and punishment within this context. For analytical purposes, this paper has broken down the individual barriers to quality care and discusses the current and historical significance before returning to the interrelated forms in which barriers to quality maternal health care manifest. In conclusion this paper questions the role of agency in the ability to subvert systemic barriers to quality care and ideas around shifting attitudes and beliefs of and about midwives. International and local policies and guidelines have a role to play in realizing such shifts, however, as this paper suggests, when policy does not speak to the local context there is the risk of it contributing to frustrations and impeding the path to quality and respectful maternal health care.

Keywords: disrespect and abuse in childbirth, midwifery, South African maternal health care, quality of care

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Authors: M. Caramihai, Irina Severin

Abstract:

This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques

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Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

Abstract:

In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

Procedia PDF Downloads 303