Search results for: open queueing network

Authors: Mohammad R. Aghakashkooli, Milutin G. Jovanovic

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The brushless doubly-fed reluctance generator (BDFRG) is an emerging, medium-speed alternative to a conventional wound rotor slip-ring doubly-fed induction generator (DFIG) in wind energy conversion systems (WECS). It can provide competitive overall performance and similar low failure rates of a typically 30% rated back-to-back power electronics converter in 2:1 speed ranges but with the following important reliability and cost advantages over DFIG: the maintenance-free operation afforded by its brushless structure, 50% synchronous speed with the same number of rotor poles (allowing the use of a more compact, and more efficient two-stage gearbox instead of a vulnerable three-stage one), and superior grid integration properties including simpler protection for the low voltage ride through compliance of the fractional converter due to the comparatively higher leakage inductances and lower fault currents. Vector controlled pulse-width-modulated converters generally feature a much lower total harmonic distortion relative to hysteresis counterparts with variable switching rates and as such have been a predominant choice for BDFRG (and DFIG) wind turbines. Eliminating a shaft position sensor, which is often required for control implementation in this case, would be desirable to address the associated reliability issues. This fact has largely motivated the recent growing research of sensorless methods and developments of various rotor position and/or speed estimation techniques for this purpose. The main limitation of all the observer-based control approaches for grid-connected wind power applications of the BDFRG reported in the open literature is the requirement for pre-commissioning procedures and prior knowledge of the machine inductances, which are usually difficult to accurately identify by off-line testing. A model reference adaptive system (MRAS) based sensor-less vector control scheme to be presented will overcome this shortcoming. The true machine parameter independence of the proposed field-oriented algorithm, offering robust, inherently decoupled real and reactive power control of the grid-connected winding, is achieved by on-line estimation of the inductance ratio, the underlying rotor angular velocity and position MRAS observer being reliant upon. Such an observer configuration will be more practical to implement and clearly preferable to the existing machine parameter dependent solutions, and especially bearing in mind that with very little modifications it can be adapted for commercial DFIGs with immediately obvious further industrial benefits and prospects of this work. The excellent encoder-less controller performance with maximum power point tracking in the base speed region will be demonstrated by realistic simulation studies using large-scale BDFRG design data and verified by experimental results on a small laboratory prototype of the WECS emulation facility.

Keywords: brushless doubly fed reluctance generator, model reference adaptive system, sensorless vector control, wind energy conversion

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

Procedia PDF Downloads 265

Authors: Margareth S. Zanchetta, Kateryna Metersky, Valerie Tan, Charissa Cordon, Stephanie Lucchese, Yana Siganevich, Prasha Sivasundaram, Truong Binh Nguyen, Imran Qureshi

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Due to a new area of practice, Canadian nurses possess knowledge gaps regarding the use of cannabis-based therapies by clients/patients. Education related to medical cannabis (MC) and recreational cannabis (RC) is required to promote nurses’ competency and confidence in supporting clients/patients using MC/RC toward the improvement of health outcomes. A team composed of nursing researchers and undergraduate/graduate students implemented a national survey to explore this theme with the population of undergraduate, graduate (MN and NP), and Post-Diploma (RN Bridging) nursing students enrolled in Canadian Universities Nursing Programs. Upon Research Ethics Board approval, survey recruitment was supported by major nursing stakeholders. The research questions were : (a) Which are the most preferred sources of information on MC/RC for nursing students? (b) Which are the factors and preferred learning modalities that could increase interest in learning about MC/RC, and (c) What are the future career plans among nursing students, and how would they consider the prospective use of cannabis in their practice? The survey was available from Sept. 2022 to Feb. 2023, hosted by a remote platform. An original questionnaire (English-French) was composed of 18 multiple choice questions and 2 open-ended questions. Sociodemographic information and closed-ended responses were compiled as descriptive statistics, while narrative accounts will be analysed through thematic analysis. Respondents (n=153) were from 7 Canadian provinces, national (99%) and international students (1%); the majority of respondents (61%) were in the age range of 21-30 years old. Results indicated that respondents perceive a gap in the undergraduate curriculum on the topics of MC/RC (91%) and that their learning needs include regulations (90%), data on effectiveness (88%), dosing best practices (86%), contraindications (83%), and clinical and medical indications (76%). Respondents reported motivation to learn more about MC/RC through online lectures/videos (65%), e-learning modules or online interactive training (61%), workshops (51%), webinars (36%), and social media (35%). Their primary career-related motivations regarding MC/RC knowledge include enhancing nursing practice (76%), learning about this growing scope of practice (61%), keeping up-to-date responding to scientific curiosity (59%), learning about evidence-based practice (59%), and utilizing alternative forms of medical treatment (37%). Respondents indicated that the integration of topics on cannabis in any course in the undergraduate and/or graduate curriculum would increase their desire to learn about MC/RC as equally as exposure within a clinical setting (75%). The emerging trend in the set of narrative responses (n=130) suggests that respondents believe educational MC/RC content should be integrated into core nursing courses. Respondents also urged educators to be well-informed about evidence-based practice related to MC/RC and to reflect upon stigma and biases surrounding its use. Future knowledge dissemination and translation activities include scholarly products and presentations to stimulate discussion amongst nursing faculty and students, as well as nurses in clinical settings. The goal is to mobilise talents and build collaboration for the development of a socially responsive curriculum on MC/RC competency to address the education-related expectations of all these social actors.

Keywords: Canada, medical cannabis, nursing education, nursing graduate student, nursing undergraduate student, online survey, recreational cannabis

Procedia PDF Downloads 72

Authors: Eduardo Cabrera-Rode, Janet Rodriguez, Aimee Alvarez, Ragmila Echevarria, Antonio D. Reyes, Ileana Cubas-Duenas, Silvia E. Turcios, Oscar Diaz-Diaz

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Obex is a nutritional supplement to help weight loss naturally. In addition, this supplement has a satiating effect that helps control the craving to eat between meals. The purpose of this study was to evaluate the effect of Obex in the metabolic syndrome (MS). This was an open label pilot study conducted in 30 patients with MS and ages between 29 and 60 years old. Participants received Obex, at a dose of one sachet before (30 to 45 minutes) the two main meals (lunch and dinner) daily (mean two sachets per day) for 3 months. The content of the sachets was dissolved in a glass of water or fruit juice. Obex ingredients: Açai (Euterpe oleracea Mart.) berry, inulin, Phaseolus vulgaris, Caralluma fimbriata, inositol, choline, arginine, ornitine, zinc sulfate, carnitine fumarate, methionine, calcium pantothenate, pyridoxine and folic acid. In addition to anthropometric measures and blood pressure, fasting plasma glucose, total cholesterol, triglycerides and HDL-cholesterol and insulin were determined. Insulin resistance was assessed by HOMA-IR index. Three indirect indexes were used to calculate insulin sensitivity [QUICKI index (Quantitative insulin sensitivity check index), Bennett index and Raynaud index]. Metabolic syndrome was defined according to the Joint Interim Statement (JIS) criteria. The JIS criteria require at least three of the following components: (1) abdominal obesity (waist circumference major or equal major or equal 94 cm for men or 80 cm for women), (2) triglycerides major or equal 1.7 mmol/L, (3) HDL cholesterol minor 1.03 mmol/L for men or minor 1.30 mmol/L for women, (4) systolic/diastolic blood pressure major or equal 130/85mmHg or use antihypertensive drugs, and (5) fasting plasma glucose major or equal 5.6 mmol/L or known treatment for diabetes. This study was approved by the Ethical and Research Committee of the National Institute of Endocrinology, Cuba and conducted according to the Declaration of Helsinki. Obex is registered as a food supplement in the National Institute of Nutrition and Food, Havana, Cuba. Written consent was obtained from all patients before the study. The clinical trial had been registered at ClinicalTrials.gov. After three months of treatment, 43.3% (13/30) of participants decreased the frequency of MS. Compared to baseline, Obex significantly reduced body weight, BMI, waist circumference, and waist/hip ratio and improved HDL-c (p<0.0001) and in addition to lowering blood pressure (p<0.05). After Obex intake, subjects also have shown a reduction in fasting plasma glucose (p<0.0001) and insulin sensitivity was enhanced (p=0.001). No adverse effects were seen in any of the participants during the study. In this pilot study, consumption of Obex decreased the prevalence of MS due to the improved selected components of the metabolic syndrome, indicating that further studies are warranted. Obex emerges as an effective and well tolerated treatment for preventing or delaying MS and therefore potential reduction of cardiovascular risk.

Keywords: nutritional supplement, metabolic syndrome, weight loss, insulin resistance

Procedia PDF Downloads 279

Authors: B. Mohammadi, A. Riazati, P. Soltan Sanjari, S. Azimbeik

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The ever-increasing development of civic demands on one hand; and the urban constrains for newly establish of infrastructures, on the other hand, perforce the engineering committees to apply non-conflicting methods in order to optimize the results. One of these optimized procedures to establish the main sewerage networks is the pipe jacking and micro-tunneling method. The raw information and researches are based on the experiments of the slurry micro-tunneling project of the Tehran main sewerage network that it has executed by the KAYSON co. The 4985 meters route of the mentioned project that is located nearby the Azadi square and the most vital arteries of Tehran is faced to 45% physical progress nowadays. The boring machine is made by the Herrenknecht and the diameter of the using concrete-polymer pipes are 1600 and 1800 millimeters. Placing and excavating several shafts on the ground and direct Tunnel boring between the axes of issued shafts is one of the requirements of the micro-tunneling. Considering the stream of the ground located shafts should care the hydraulic circumstances, civic conditions, site geography, traffic cautions and etc. The profile length has to convert to many shortened segment lines so the generated angle between the segments will be based in the manhole centers. Each segment line between two continues drive and receive the shaft, displays the jack location, driving angle and the path straight, thus, the diversity of issued angle causes the variety of jack positioning in the shaft. The jacking frame fixing conditions and it's associated dynamic load direction produces various patterns of Stress and Strain distribution and creating fatigues in the shaft wall and the soil surrounded the shaft. This pattern diversification makes the shaft wall transformed, unbalanced subsidence and alteration in the pipe jacking Stress Contour. This research is based on experiments of the Tehran's west sewerage plan and the numerical analysis the interaction of the soil around the shaft, shaft walls and the Jacking frame direction and finally, the suitable or unsuitable location of the pipe jacking shaft will be determined.

Keywords: underground structure, micro-tunneling, fatigue analysis, dynamic-soil–structure interaction, underground water, finite element analysis

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

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Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

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Authors: Mahadehe Hassan

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In most countries manufacturing, trading and distribution of gasoline and diesel fuels belongs to the most important sectors of national economy. For Bangladesh, a robust, well-functioning, secure and smartly managed national fuel distribution chain is an essential precondition for achieving Government top priorities in development and modernization of transportation infrastructure, protection of national environment and population health as well as, very importantly, securing due tax revenue for the State Budget. Bangladesh is a developing country with complex fuel supply network, high fuel taxes incidence and – till now - limited possibilities in application of modern, automated technologies for Government national fuel market control. Such environment allows dishonest physical and legal persons and organized criminals to build and profit from illegal fuel distribution schemes and fuel illicit trade. As a result, the market transparency and the country attractiveness for foreign investments, law-abiding economic operators, national consumers, State Budget and the Government ability to finance development projects, and the country at large suffer significantly. Research shows that over 50% of retail petrol stations in major agglomerations of Bangladesh sell adulterated fuels and/or cheat customers on the real volume of the fuel pumped into their vehicles. Other forms of detected fuel illicit trade practices include misdeclaration of fuel quantitative and qualitative parameters during internal transit and selling of non-declared and smuggled fuels. The aim of the study is to recommend the implementation of a National Fuel Distribution Integrity Program (FDIP) in Bangladesh to address and resolve fuel adulteration and illicit trade problems. The program should be customized according to the specific needs of the country and implemented in partnership with providers of advanced technologies. FDIP should enable and further enhance capacity of respective Bangladesh Government authorities in identification and elimination of all forms of fuel illicit trade swiftly and resolutely. FDIP high-technology, IT and automation systems and secure infrastructures should be aimed at the following areas (1) fuel adulteration, misdeclaration and non-declaration; (2) fuel quality and; (3) fuel volume manipulation at retail level. Furthermore, overall concept of FDIP delivery and its interaction with the reporting and management systems used by the Government shall be aligned with and support objectives of the Vision 2041 and Smart Bangladesh Government programs.

Keywords: fuel adulteration, octane, kerosene, diesel, petrol, pollution, carbon emissions

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

Procedia PDF Downloads 179

Authors: B. F. Espiritu

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This paper examines the resistance of the Lumad people, the indigenous peoples in Mindanao, Southern Philippines, and of environmental and human rights activists to the Philippine government's neoliberal policies and their call for justice and a new economic paradigm that will uphold peoples' rights and environmental protection in two alternative media online sites. The study contributes to the body of knowledge on indigenous resistance to neoliberal globalization and the quest for a new economic paradigm that upholds social justice for the marginalized in society, empathy and compassion for those who depend on the land for their survival, and environmental sustainability. The study analyzes the discourses in selected news articles from Davao Today and Kalikasan (translated to English as 'Nature') People's Network for the Environment’s statements and advocacy articles for the Lumad and the environment from 2018 to February 2020. The study reveals that the alternative media news articles and the advocacy articles contain statements that expose the oppression and violation of human rights of the Lumad people, farmers, government environmental workers, and environmental activists as shown in their killings, illegal arrest and detention, displacement of the indigenous peoples, destruction of their schools by the military and paramilitary groups, and environmental plunder and destruction with the government's permit for the entry and operation of extractive and agribusiness industries in the Lumad ancestral lands. Anchored on Christian Fuch's theory of alternative media as critical media and Bert Cammaerts' theorization of alternative media as counterhegemonic media that are part of civil society and form a third voice between state media and commercial media, the study reveals the counterhegemonic discourses of the news and advocacy articles that oppose the dominant economic system of neoliberalism which oppresses the people who depend on the land for their survival. Furthermore, the news and advocacy articles seek to advance social struggles that transform society towards the realization of cooperative potentials or a new economic paradigm that upholds economic democracy, where the local people, including the indigenous people, are economically empowered their environment and protected towards the realization of self-sustaining communities. The study highlights the call for justice, empathy, and compassion for both the people and the environment and the need for a new economic paradigm wherein indigenous peoples and local communities are empowered towards becoming self-sustaining communities in a sustainable environment.

Keywords: alternative media, environmental sustainability, human rights, indigenous resistance

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Authors: Alejandra Martin-Dominguez, Javier Canto-Rios, Velitchko Tzatchkov

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Electrocoagulation is a water treatment technology that consists of generating coagulant species in situ by electrolytic oxidation of sacrificial anode materials triggered by electric current. It removes suspended solids, heavy metals, emulsified oils, bacteria, colloidal solids and particles, soluble inorganic pollutants and other contaminants from water, offering an alternative to the use of metal salts or polymers and polyelectrolyte addition for breaking stable emulsions and suspensions. The method essentially consists of passing the water being treated through pairs of consumable conductive metal plates in parallel, which act as monopolar electrodes, commonly known as ‘sacrificial electrodes’. Physicochemical, electrochemical and hydraulic processes are involved in the efficiency of this type of treatment. While the physicochemical and electrochemical aspects of the technology have been extensively studied, little is known about the influence of the hydraulics. However, the hydraulic process is fundamental for the reactions that take place at the electrode boundary layers and for the coagulant mixing. Electrocoagulation reactors can be open (with free water surface) and closed (pressurized). Independently of the type of rector, hydraulic head loss is an important factor for its design. The present work focuses on the study of the total hydraulic head loss and flow velocity and pressure distribution in electrocoagulation reactors with single or multiple concentric annular cross sections. An analysis of the head loss produced by hydraulic wall shear friction and accessories (minor head losses) is presented, and compared to the head loss measured on a semi-pilot scale laboratory model for different flow rates through the reactor. The tests included laminar, transitional and turbulent flow. The observed head loss was compared also to the head loss predicted by several known conceptual theoretical and empirical equations, specific for flow in concentric annular pipes. Four single concentric annular cross section and one multiple concentric annular cross section reactor configuration were studied. The theoretical head loss resulted higher than the observed in the laboratory model in some of the tests, and lower in others of them, depending also on the assumed value for the wall roughness. Most of the theoretical models assume that the fluid elements in all annular sections have the same velocity, and that flow is steady, uniform and one-dimensional, with the same pressure and velocity profiles in all reactor sections. To check the validity of such assumptions, a computational fluid dynamics (CFD) model of the concentric annular pipe reactor was implemented using the ANSYS Fluent software, demonstrating that pressure and flow velocity distribution inside the reactor actually is not uniform. Based on the analysis, the equations that predict better the head loss in single and multiple annular sections were obtained. Other factors that may impact the head loss, such as the generation of coagulants and gases during the electrochemical reaction, the accumulation of hydroxides inside the reactor, and the change of the electrode material with time, are also discussed. The results can be used as tools for design and scale-up of electrocoagulation reactors, to be integrated into new or existing water treatment plants.

Keywords: electrocoagulation reactors, hydraulic head loss, concentric annular pipes, computational fluid dynamics model

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Authors: Carolyn Hatch, Laurent Simon

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Urban mobility and the transportation industry are undergoing a transformation, shifting from an auto production-consumption model that has dominated since the early 20th century towards new forms of personal and shared multi-modality [1]. This is shaped by key forces such as climate change, which has induced a shift in production and consumption patterns and efforts to decarbonize and improve transport services through, for instance, the integration of vehicle automation, electrification and mobility sharing [2]. Advanced innovation practices and platforms for experimentation and validation of new mobility products and services that are increasingly complex and multi-stakeholder-oriented are shaping this new world of mobility. Transportation hubs – such as airports - are emblematic of these disruptive forces playing out in the mobility industry. Airports are emerging as the core of innovation ecosystems on and around contemporary mobility issues, and increasingly recognized as complex public/private nodes operating in many societal dimensions [3,4]. These include urban development, sustainability transitions, digital experimentation, customer experience, infrastructure development and data exploitation (for instance, airports generate massive and often untapped data flows, with significant potential for use, commercialization and social benefit). Yet airport innovation practices have not been well documented in the innovation literature. This paper addresses this gap by proposing a model of airport innovation that aims to equip airport stakeholders to respond to these new and complex innovation needs in practice. The methodology involves: 1 – a literature review bringing together key research and theory on airport innovation management, open innovation and innovation ecosystems in order to evaluate airport practices through an innovation lens; 2 – an international benchmarking of leading airports and their innovation practices, including such examples as Aéroports de Paris, Schipol in Amsterdam, Changi in Singapore, and others; and 3 – semi-structured interviews with airport managers on key aspects of organizational practice, facilitated through a close partnership with the Airport Council International (ACI), a major stakeholder in this research project. Preliminary results find that the most successful airports are those that have shifted to a multi-stakeholder, platform ecosystem model of innovation. The recent entrance of new actors in airports (Google, Amazon, Accor, Vinci, Airbnb and others) have forced the opening of organizational boundaries to share and exchange knowledge with a broader set of ecosystem players. This has also led to new forms of governance and intermediation by airport actors to connect complex, highly distributed knowledge, along with new kinds of inter-organizational collaboration, co-creation and collective ideation processes. Leading airports in the case study have demonstrated a unique capacity to force traditionally siloed activities to “think together”, “explore together” and “act together”, to share data, contribute expertise and pioneer new governance approaches and collaborative practices. In so doing, they have successfully integrated these many disruptive change pathways and forced their implementation and coordination towards innovative mobility outcomes, with positive societal, environmental and economic impacts. This research has implications for: 1 - innovation theory, 2 - urban and transport policy, and 3 - organizational practice - within the mobility industry and across the economy.

Keywords: airport management, ecosystem, innovation, mobility, platform, transport hubs

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Authors: Mariyan Tomov

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Bulgarian working class immigrants are increasingly concerned with UK’s recent immigration policies in the context of Brexit. The new ID system would exclude many people currently working in Britain and would break the usual immigrant travel patterns. Post-Brexit Britain would aim to repeal seasonal immigrants. Measures for keeping long-term and life-long immigrants have been implemented and migrants that aim to remain in Britain and establish a household there would be more privileged than temporary or seasonal workers. The results of such regulating mechanisms come at the expense of migrants’ longings for a ‘normal’ existence, especially for those coming from Central and Eastern Europe. Based on in-depth interviews with Bulgarian working class immigrants, the study found out that their major concerns following the decision of the UK to leave the EU are related with the freedom to travel, reside and work in the UK. Furthermore, many of the interviewed women are concerned that they could lose some of the EU's fundamental rights, such as maternity and protection of pregnant women from unlawful dismissal. The soar of commodity prices and university fees and the limited access to public services, healthcare and social benefits in the UK, are also subject to discussion in the paper. The most serious problem, according to the interview, is that the attitude towards Bulgarians and other immigrants in the UK is deteriorating. Both traditional and social media in the UK often portray the migrants negatively by claiming that they take British job positions while simultaneously abuse the welfare system. As a result, the Bulgarian migrants often face social exclusion, which might have negative influence on their health and welfare. In this sense, some of the interviewed stress on the fact that the most important changes after Brexit must take place in British society itself. The aim of the proposed study is to provide a better understanding of the Bulgarian migrants’ economic, health and sociocultural experience in the context of Brexit. Methodologically, the proposed paper leans on: 1. Analysing ethnographic materials dedicated to the pre- and post-migratory experiences of Bulgarian working class migrants, using SPSS. 2. Semi-structured interviews are conducted with more than 50 Bulgarian working class migrants [N > 50] in the UK, between 18 and 65 years. The communication with the interviewees was possible via Viber/Skype or face-to-face interaction. 3. The analysis is guided by theoretical frameworks. The paper has been developed within the framework of the research projects of the National Scientific Fund of Bulgaria: DCOST 01/25-20.02.2017 supporting COST Action CA16111 ‘International Ethnic and Immigrant Minorities Survey Data Network’.

Keywords: Bulgarian migrants in UK, economic experiences, sociocultural experiences, Brexit

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Authors: Jun Won Kim

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Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.

Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Sebastian Kehne, Alexander Epple, Werner Herfs

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A new method for optimal selection of components for multi-axes forward-feed drive systems is proposed in which the choice of motors, gear boxes and ball screw drives is optimized. Essential is here the synchronization of electrical and mechanical frequency behavior of all axes because even advanced controls (like H∞-controls) can only control a small part of the mechanical modes – namely only those of observable and controllable states whose value can be derived from the positions of extern linear length measurement systems and/or rotary encoders on the motor or gear box shafts. Further problems are the unknown processing forces like cutting forces in machine tools during normal operation which make the estimation and control via an observer even more difficult. To start with, the open source Modelica Feed Drive Library which was developed at the Laboratory for Machine Tools, and Production Engineering (WZL) is extended from one axis design to the multi axes design. It is capable to simulate the mechanical, electrical and thermal behavior of permanent magnet synchronous machines with inverters, different gear boxes and ball screw drives in a mechanical system. To keep the calculation time down analytical equations are used for field and torque producing equivalent circuit, heat dissipation and mechanical torque at the shaft. As a first step, a small machine tool with a working area of 635 x 315 x 420 mm is taken apart, and the mechanical transfer behavior is measured with an impulse hammer and acceleration sensors. With the frequency transfer functions, a mechanical finite element model is built up which is reduced with substructure coupling to a mass-damper system which models the most important modes of the axes. The model is modelled with Modelica Feed Drive Library and validated by further relative measurements between machine table and spindle holder with a piezo actor and acceleration sensors. In a next step, the choice of possible components in motor catalogues is limited by derived analytical formulas which are based on well-known metrics to gain effective power and torque of the components. The simulation in Modelica is run with different permanent magnet synchronous motors, gear boxes and ball screw drives from different suppliers. To speed up the optimization different black-box optimization methods (Surrogate-based, gradient-based and evolutionary) are tested on the case. The objective that was chosen is to minimize the integral of the deviations if a step is given on the position controls of the different axes. Small values are good measures for a high dynamic axes. In each iteration (evaluation of one set of components) the control variables are adjusted automatically to have an overshoot less than 1%. It is obtained that the order of the components in optimization problem has a deep impact on the speed of the black-box optimization. An approach to do efficient black-box optimization for multi-axes design is presented in the last part. The authors would like to thank the German Research Foundation DFG for financial support of the project “Optimierung des mechatronischen Entwurfs von mehrachsigen Antriebssystemen (HE 5386/14-1 | 6954/4-1)” (English: Optimization of the Mechatronic Design of Multi-Axes Drive Systems).

Keywords: ball screw drive design, discrete optimization, forward feed drives, gear box design, linear drives, machine tools, motor design, multi-axes design

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Authors: Abeeb Abiodun Bakare

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The advent of blockchain technology has birthed a revolutionary innovation: smart contracts. These self-executing contracts, encoded within the immutable ledger of a blockchain, hold the potential to transform the landscape of traditional contractual agreements. This research paper embarks on a comprehensive exploration of the legal implications surrounding smart contracts, delving into their enforceability and their profound impact on traditional contract law. The first section of this paper delves into the foundational principles of smart contracts, elucidating their underlying mechanisms and technological intricacies. By harnessing the power of blockchain technology, smart contracts automate the execution of contractual terms, eliminating the need for intermediaries and enhancing efficiency in commercial transactions. However, this technological marvel raises fundamental questions regarding legal enforceability and compliance with traditional legal frameworks. Moving beyond the realm of technology, the paper proceeds to analyze the legal validity of smart contracts within the context of traditional contract law. Drawing upon established legal principles, such as offer, acceptance, and consideration, we examine the extent to which smart contracts satisfy the requirements for forming a legally binding agreement. Furthermore, we explore the challenges posed by jurisdictional issues as smart contracts transcend physical boundaries and operate within a decentralized network. Central to this analysis is the examination of the role of arbitration and dispute resolution mechanisms in the context of smart contracts. While smart contracts offer unparalleled efficiency and transparency in executing contractual terms, disputes inevitably arise, necessitating mechanisms for resolution. We investigate the feasibility of integrating arbitration clauses within smart contracts, exploring the potential for decentralized arbitration platforms to streamline dispute resolution processes. Moreover, this paper explores the implications of smart contracts for traditional legal intermediaries, such as lawyers and judges. As smart contracts automate the execution of contractual terms, the role of legal professionals in contract drafting and interpretation may undergo significant transformation. We assess the implications of this paradigm shift for legal practice and the broader legal profession. In conclusion, this research paper provides a comprehensive analysis of the legal implications surrounding smart contracts, illuminating the intricate interplay between code and law. While smart contracts offer unprecedented efficiency and transparency in commercial transactions, their legal validity remains subject to scrutiny within traditional legal frameworks. By navigating the complex landscape of smart contract law, we aim to provide insights into the transformative potential of this groundbreaking technology.

Keywords: smart-contracts, law, blockchain, legal, technology

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Tristance Kee

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With the unprecedented increase in elderly population globally, it is critical to search for new sustainable housing and urban development alternatives to traditional housing options. This research examines concepts of elderly migration pattern in the context of a high density city in Hong Kong to Mainland China. The research objectives are to: 1) explore the relationships between soon-to-be-old elderly and their intentions to move to Mainland upon retirement and their demographic characteristics; and 2) What are the desired amenities, locational factors and activities that are expected in the soon-to-be-old generation’s retirement housing environment? Primary data was collected through questionnaire survey conducted using random sampling method with respondents aged between 45-64 years old. The face-to-face survey was completed by 500 respondents. The survey was divided into four sections. The first section focused on respondent’s demographic information such as gender, age, education attainment, monthly income, housing tenure type and their visits to Mainland China. The second section focused on their retirement plans in terms of intended retirement age, prospective retirement funding and retirement housing options. The third section focused on the respondent’s attitudes toward retiring in Mainland for housing. It asked about their intentions to migrate retire into Mainland and incentives to retire in Hong Kong. The fourth section focused on respondent’s ideal housing environment including preferred housing amenities, desired living environment and retirement activities. The dependent variable in this study was ‘respondent’s consideration to move to Mainland China upon retirement’. Eight primary independent variables were integrated into the study to identify the correlations between them and retirement migration plan. The independent variables include: gender, age, marital status, monthly income, present housing tenure type, property ownership in Hong Kong, relationship with Mainland and the frequency of visiting Mainland China. In addition to the above independent variables, respondents were asked to indicate their retirement plans (retirement age, funding sources and retirement housing options), incentives to migrate to retire (choices included: property ownership, family relations, cost of living, living environment, medical facilities, government welfare benefits, etc.), perceived ideal retirement life qualities including desired amenities (sports, medical and leisure facilities etc.), desired locational qualities (green open space, convenient transport options and accessibility to urban settings etc.) and desired retirement activities (home-based leisure, elderly friendly sports, cultural activities, child care, social activities, etc.). The finding shows correlations between the used independent variables and consideration to migrate for housing options. The two independent variables indicated a possible correlation were gender and the frequency of visiting Mainland at present. When considering the increasing property prices across the border and strong social relationships, potential retirement migration is a very subjective decision that could vary from person to person. This research adds knowledge to housing research and migration study. Although the research is based in Mainland, most of the characteristics identified including better medical services, government welfare and sound urban amenities are shared qualities for all sustainable urban development and housing strategies.

Keywords: elderly migration, housing alternative, soon-to-be-old, sustainable environment

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Vanita Singh

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In developing countries, there are conflicting political agendas; policy makers have to prioritize issues from a list of issues competing for the limited resources. Thus, it is imperative to understand how some issues gain attention, and others lose in the policy circles. Multiple-Streams Theory of Kingdon (1984) is among the influential theories that help to understand the public policy process and is utilitarian for health policy makers to understand how certain health issues emerge on the policy agendas. The issue of maternal mortality was long standing in India and was linked with high birth rate thus the focus of maternal health policy was on family planning since India’s independence. However, a paradigm shift was noted in the maternal health policy in the year 1992 with the launch of Safe Motherhood Programme and then in the year 2005, when the agenda of maternal health policy became universalizing institutional deliveries and phasing-out of Traditional Birth Attendants (TBAs) from the health system. There were many solutions proposed by policy communities other than universalizing of institutional deliveries, including training of TBAs and improving socio-economic conditions of pregnant women. However, Government of India favored medical community, which was advocating for the policy of universalizing institutional delivery, and neglected the solutions proposed by other policy communities. It took almost 15 years for the advocates of institutional delivery to transform their proposed solution into a program - the Janani Suraksha Yojana (JSY), a safe-motherhood program promoting institutional delivery through cash incentives to pregnant women. Thus, the case of safe motherhood policy in India is worth studying to understand how certain issues/problems gain political attention and how advocacy work in policy circles. This paper attempts to understand the factors that favored the agenda of safe-motherhood in the policy circle in India, using John Kingdon’s Multiple-Stream model of agenda-setting. Through document analysis and literature review, the paper traces the evolution of safe motherhood program and maternal health policy. The study has used open source documents available on the website of Ministry of Health and Family Welfare, media reports (Times of India Archive) and related research papers. The documents analyzed include National health policy-1983, National Health Policy-2002, written reports of Ministry of Health and Family Welfare Department, National Rural Health Mission (NRHM) document, documents related to Janani Suraksha Yojana and research articles related to maternal health programme in India. The study finds that focusing events and credible indicators coupled with media attention has the potential to recognize a problem. The political elites favor clearly defined and well-accepted solutions. The trans-national organizations affect the agenda-setting process in a country through conditional resource provision. The closely-knit policy communities and political entrepreneurship are required for advocating solutions high on agendas. The study has implications for health policy makers in identifying factors that have the potential to affect the agenda-setting process for a desired policy agenda and identify the challenges in generating political priorities.

Keywords: agenda-setting, focusing events, Kingdon’s model, safe motherhood program India

Procedia PDF Downloads 121

Authors: Shilpa Sahoo, Michel Louge, Anthony Reeves, Olivier Desjardins, Susan Daniel, Sadik Omowunmi

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The microgravity on the International Space Station (ISS) was exploited to study the imbibition of water into a network of hydrophilic cylindrical capillaries on time and length scales long enough to observe details hitherto inaccessible under Earth gravity. When a drop touches a porous medium, it spreads as if laid on a composite surface. The surface first behaves as a hydrophobic material, as liquid must penetrate pores filled with air. When contact is established, some of the liquid is drawn into pores by a capillarity that is resisted by viscous forces growing with length of the imbibed region. This process always begins with an inertial regime that is complicated by possible contact pinning. To study imbibition on Earth, time and distance must be shrunk to mitigate gravity-induced distortion. These small scales make it impossible to observe the inertial and pinning processes in detail. Instead, in the International Space Station (ISS), astronaut Luca Parmitano slowly extruded water spheres until they touched any of nine capillary plates. The 12mm diameter droplets were large enough for high-speed GX1050C video cameras on top and side to visualize details near individual capillaries, and long enough to observe dynamics of the entire imbibition process. To investigate the role of contact pinning, a text matrix was produced which consisted nine kinds of porous capillary plates made of gold-coated brass treated with Self-Assembled Monolayers (SAM) that fixed advancing and receding contact angles to known values. In the ISS, long-term microgravity allowed unambiguous observations of the role of contact line pinning during the inertial phase of imbibition. The high-speed videos of spreading and imbibition on the porous plates were analyzed using computer vision software to calculate the radius of the droplet contact patch with the plate and height of the droplet vs time. These observations are compared with numerical simulations and with data that we obtained at the ESA ZARM free-fall tower in Bremen with a unique mechanism producing relatively large water spheres and similarity in the results were observed. The data obtained from the ISS can be used as a benchmark for further numerical simulations in the field.

Keywords: droplet imbibition, hydrophilic surface, inertial phase, porous medium

Procedia PDF Downloads 114

Authors: Charles Mazhazhate

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This study interrogates and analyses the intricate kin- and- kith network patterns of corruption and mismanagement of resources prevalent in public sector supply chains bedeviling the developing economies of Sub-Saharan Africa with particular reference to Zimbabwe. This is forcing governments to resort to harsh fiscal policies that see their citizens paying high taxes against a backdrop of incomes below the poverty datum line, and this negatively affects their quality of life. The corporate world is also affected by the various tax-regime instituted. Mismanagement of resources and corrupt practices are rampant in state-owned enterprises to the extent that institutional policies, procedures, and practices are often flouted for the benefit of a clique of individuals. This interwoven in kith and kin blood human relations in organizations where appointments to critical positions are based on ascribed status. People no longer place value in their systems to make them work thereby violating corporate governance principles. Greediness and ‘unholy friendship connections’ are instrumental in fueling the employment of people who know each other from their discrete backgrounds. Such employments or socio-metric unions are meant to protect those at the top by giving them intelligent information through spying on what other subordinates are doing inside and outside the organization. This practice has led to the underperforming of organizations as those employees with connections and their upper echelons favorites connive to abuse resources for their own benefit. Even if culprits are known, no draconian measures are employed as a deterrence measure. Public value along public sector supply chains is lost. The study used a descriptive case study research design on fifty organizations in Zimbabwe mainly state-owned enterprises. Both qualitative and quantitative instrumentations were used. Both Snowball and random sampling techniques were used. The study found out that in all the fifty SOEs, there were employees in key positions related to top management, with tentacles feeding into the law enforcement agents, judiciary, security systems, and the executive. Such employees in public seem not to know each other with but would be involved in dirty scams and then share the proceeds with top people behind the scenes. The study also established that the same employees do not have the necessary competencies, qualifications, abilities, and capabilities to be in those positions. This culture is now strong that it is difficult to bust. The study recommends recruitment of all employees through an independent employment bureau to ensure strategic fit.

Keywords: corruption, state owned enterprises, strategic fit, public sector supply chains, efficiency

Procedia PDF Downloads 141

Authors: Henry Okechukwu Onyeiwu, Arfah Ab. Majid

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To fully understand the critical role of marriage in society, it is important to view it as a social institution that provides some basic social needs for society. A ‘social institution’ is the network of shared meanings, norms, definitions, expectations, and understandings held by the members of society. It is what guides and governs how the members of the society are expected to act and interact, what is socially desirable and legitimate, what they should be striving for, and so on. One of the major social institutions is marriage. Marriage is and has often focused on children and what is best for them because the rising generation literally is the future of every society. However, according to the aforementioned definition, which notes that marriage may also be a union between two persons of the same sex with legal support, this study stands with the definitions that are based on marriage being a union between a man and woman that is the most appropriate in Igbo land and not the other way round. The issue to be evaluated concerns marriage as it associates with Igbo Catholic Christians in Nigeria. Pasts of Igbo culture should be better organized into the Christian faith. Igbo Christians actually convey a significant number of their customary thoughts, customs, and social qualities, particularly regarding marriage, in the aftermath of switching to Christianity. The analyst agrees that marriage among Igbo Christians warrants adequate evolution. This study, therefore, concentrates on the Igbo community’s interpretation of the concept of culture and religion and the religious implications of traditional marriage and Christian marriage ceremonies in Igbo. The research design of this study is a qualitative design that provides in-depth information on the dual religious identity of the Igbo people on the rite of marriage in Imo state. The study population was composed of both male and female members from each selected local government area in Imo State. Thematic analysis was used to elaborate on the result from the respondents. This survey found that reputation is a major concern for Ibo people. Parental discomfort can lead to the use of coping strategies such as displacement, in which parents pass on their own vulnerable sentiments to their children. Those who participate in marriage negotiations feel the pain of their parents because they are unable to communicate their own feelings. As a result, participants experience increased stress and a range of negative emotions related to their marriage, including worry, dissatisfaction, and ambivalence. It was concluded that when it comes to Igbo culture, marriage is seen as a need for the continuation of the family’s lineage of descent, according to the outcome. The Task at hand was to discover how the locals preparing to get married define the impending transition. Imo State is home to the practice of Igba-nkwu, where the woman is either inherited or taken in the place of another.

Keywords: Igbo, culture, Christianity, traditional marriage, Christian wedding

Procedia PDF Downloads 133

Authors: Nadja Ylvestedt

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Uppsala University Library is a geographically dispersed research library consisting of nine subject libraries located in different campus areas throughout the city of Uppsala. Despite the geographical dispersion, it is the library's ambition to be perceived as a cohesive library with consistently high service and quality. A key factor to being one cohesive library is the library's online services, especially the virtual reference service. E-mail, chat and phone are answered by a team of specially trained staff under the supervision of a team leader. When covid-19 hit, well-established routines and processes to provide an infrastructure for students and researchers at the university changed radically. The strong connection between services provided at the library locations as well as at the VRS has been one of the key components of the library’s success in providing patrons with the help they need. With radically minimized availability at the physical locations, the infrastructure was at risk of collapsing. Objectives:- The objective of this project has been to evaluate the consequences of the sudden change in the organization of the library. The focus of this evaluation is the library’s VRS as an important space for learning, interaction and communication between the library and the community when other traditional spaces were not available. The goal of this evaluation is to capture the lessons learned from providing infrastructure for learning and research in times of crisis both on a practical, user-centered level but also to stress the importance of leadership in ever-changing environments that supports and creates agile, flexible services and teams instead of rigid processes adhering to obsolete goals. Results:- Reduced availability at the physical library locations was one of the strategies to prevent the spread of the covid-19 virus. The library staff was encouraged to work from home, so student workers staffed the library’s physical locations during that time, leaving the VRS to be the only place where patrons could get expert help. The VRS had an increase of 65% of questions asked between spring term 2019 and spring term 2020. The VRS team had to navigate often complicated and fast-changing new routines depending on national guidelines. The VRS team has a strong emphasis on agility in their approach to the challenges and opportunities, with methods to evaluate decisions regularly with user experience in mind. Fast decision-making, collecting feedback, an open-minded approach to reviewing rules and processes with both a short-term and a long-term focus and providing a healthy work environment have been key factors in managing this crisis and learn from it. This was resting on a strong sense of ownership regarding the VRS, well-working communication tools and agile and active communication between team members, as well as between the team and the rest of the organization who served as a second-line support system to aid the VRS team. Moving forward, the VRS has become an important space for communication, interaction and provider of infrastructure, implementing new routines and more extensive availability due to the lessons learned during crisis. The evaluation shows that the virtual environment has become an important addition to the physical spaces, existing in its own right but always in connection with and in relationship with the library structure as a whole. Thereby showing that the basis of human interaction stays the same while its form morphs and adapts to changes, thus leaving the virtual environment as a space of communication and infrastructure with unique opportunities for outreach and the potential to become a staple in patron’s education and learning.

Keywords: virtual reference service, leadership, digital infrastructure, research library

Procedia PDF Downloads 149

Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

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Authors: Stefan Papastefanou

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Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

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Authors: Raveena Naz

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The concept of ‘Corporate Social Responsibility’ (CSR) has often relied on firms thinking beyond their economic interest despite the larger debate of shareholder versus stakeholder interest. India gave legal recognition to CSR in the Companies Act, 2013 which promises better corporate governance. CSR in India is believed to be different for two reasons: the dominance of family business and the history of practice of social responsibility as a form of philanthropy (mainly among the family business). This paper problematises the actual structure of business houses in India and the role of CSR in India. When the law identifies each company as a separate business entity, the economics of institutions emphasizes the ‘business group’ consisting of a plethora of firms as the institutional organization of business. The capital owned or controlled by the family group is spread across the firms through the interholding (interlocked holding) structures. This creates peculiar implications for CSR legislation in India. The legislation sets criteria for individual firms to undertake liability of mandatory CSR if they are above a certain threshold. Within this framework, the largest family firms which are all part of family owned business groups top the CSR expenditure list. The interholding structures, common managers, auditors and series of related party transactions among these firms help the family to run the business as a ‘family business’ even when the shares are issued to the public. This kind of governance structure allows family owned business group to show mandatory compliance of CSR even when they actually spend much less than what is prescribed by law. This aspect of the family firms is not addressed by the CSR legislation in particular or corporate governance legislation in general in India. The paper illustrates this with an empirical study of one of the largest family owned business group in India which is well acclaimed for its CSR activities. The individual companies under the business group are identified, shareholding patterns explored, related party transactions investigated, common managing authorities are identified; and assets, liabilities and profit/loss accounting practices are analysed. The data has been mainly collected from mandatory disclosures in the annual reports and financial statements of the companies within the business group accessed from the official website of the ultimate controlling authority. The paper demonstrates how the business group through these series of shareholding network reduces its legally mandated CSR liability. The paper thus indicates the inadequacy of CSR legislation in India because the unit of compliance is an individual firm and it assumes that each firm is independent and only connected to each other through market dealings. The law does not recognize the inter-connections of firms in corporate governance structures of family owned business group and hence is inadequate in its design to effect the threshold level of CSR expenditure. This is the central argument of the paper.

Keywords: business group, corporate governance, corporate social responsibility, family firm

Procedia PDF Downloads 259

Authors: Szymon Kuczynski, Krystian Liszka, Mariusz Laciak, Andrii Oliinyk, Adam Szurlej

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The history of gaseous fuel use in the motive power of vehicles dates back to the second half of the nineteenth century, and thus the beginnings of the automotive industry. The engines were powered by coal gas and became the prototype for internal combustion engines built so far. It can thus be considered that this construction gave rise to the automotive industry. As the socio-economic development advances, so does the number of motor vehicles. Although, due to technological progress in recent decades, the emissions generated by internal combustion engines of cars have been reduced, a sharp increase in the number of cars and the rapidly growing traffic are an important source of air pollution and a major cause of acoustic threat, in particular in large urban agglomerations. One of the solutions, in terms of reducing exhaust emissions and improving air quality, is a more extensive use of alternative fuels: CNG, LNG, electricity and hydrogen. In the case of electricity use for transport, it should be noted that the environmental outcome depends on the structure of electricity generation. The paper shows selected regulations affecting the use of alternative fuels for transport (including Directive 2014/94/EU) and its dynamics between 2000 and 2015 in Poland and selected EU countries. The paper also gives a focus on the impact of alternative fuels on the environment by comparing the volume of individual emissions (compared to the emissions from conventional fuels: petrol and diesel oil). Bearing in mind that the extent of various alternative fuel use is determined in first place by economic conditions, the article describes the price relationships between alternative and conventional fuels in Poland and selected EU countries. It is pointed out that although Poland has a wealth of experience in using methane alternative fuels for transport, one of the main barriers to their development in Poland is the extensive use of LPG. In addition, a poorly developed network of CNG stations in Poland, which does not allow easy transport, especially in the northern part of the country, is a serious problem to a further development of CNG use as fuel for transport. An interesting solution to this problem seems to be the use of home CNG filling stations: Home Refuelling Appliance (HRA, refuelling time 8-10 hours) and Home Refuelling Station (HRS, refuelling time 8-10 minutes). The team is working on HRA and HRS technologies. The article also highlights the impact of alternative fuel use on energy security by reducing reliance on imports of crude oil and petroleum products.

Keywords: alternative fuels, CNG (Compressed Natural Gas), CNG stations, LNG (Liquefied Natural Gas), NGVs (Natural Gas Vehicles), pollutant emissions

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Authors: Muhammad Abdul Basit Memon

Abstract:

The importance of organizational knowledge sharing and knowledge management has been documented in numerous research studies in available literature, since knowledge sharing has been recognized as a founding pillar for superior organizational performance and a source of gaining competitive advantage. Built on this, most of the successful organizations perceive knowledge management and knowledge sharing as a concern of high strategic importance and spend huge amounts on the effective management and sharing of organizational knowledge. However, despite some very serious endeavors, many firms fail to capitalize on the benefits of knowledge sharing because of being unaware of the individual characteristics, interpersonal, organizational and contextual factors that influence knowledge sharing; simply the antecedent to knowledge sharing. The extant literature on antecedents to knowledge sharing, offers a range of antecedents mentioned in a number of research articles and research studies. Some of the previous studies about antecedents to knowledge sharing, studied antecedents to knowledge sharing regarding inter-organizational knowledge transfer; others focused on inter and intra organizational knowledge sharing and still others investigated organizational factors. Some of the organizational antecedents to KS can relate to the characteristics and underlying aspects of knowledge being shared e.g., specificity and complexity of the underlying knowledge to be transferred; others relate to specific organizational characteristics e.g., age and size of the organization, decentralization and absorptive capacity of the firm and still others relate to the social relations and networks of organizations such as social ties, trusting relationships, and value systems. In the same way some researchers have highlighted on only one aspect like organizational commitment, transformational leadership, knowledge-centred culture, learning and performance orientation and social network-based relationships in the organizations. A bulk of the existing research articles on antecedents to knowledge sharing has mainly discussed organizational or environmental factors affecting knowledge sharing. However, the focus, later on, shifted towards the analysis of individuals or personal determinants as antecedents for the individual’s engagement in knowledge sharing activities, like personality traits, attitude and self efficacy etc. For example, employees’ goal orientations (i.e. learning orientation or performance orientation is an important individual antecedent of knowledge sharing behaviour. While being consistent with the existing literature therefore, the antecedents to knowledge sharing can be classified as being individual and organizational. This paper is an endeavor to discuss a conceptual framework of the individual and organizational antecedents to knowledge sharing in the light of the available literature and empirical evidence. This model not only can help in getting familiarity and comprehension on the subject matter by presenting a holistic view of the antecedents to knowledge sharing as discussed in the literature, but can also help the business managers and especially human resource managers to find insights about the salient features of organizational knowledge sharing. Moreover, this paper can help provide a ground for research students and academicians to conduct both qualitative as well and quantitative research and design an instrument for conducting survey on the topic of individual and organizational antecedents to knowledge sharing.

Keywords: antecedents to knowledge sharing, knowledge management, individual and organizational, organizational knowledge sharing

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Authors: Christian T. Lystbaek

Abstract:

Background: The importance of innovation management has traditionally been ascribed to private production companies, however, there is an increasing interest in public services innovation management. One of the major theoretical challenges arising from this situation is to understand public values justifying public services innovation management. However, there is not single and stable definition of public value in the literature. The research question guiding this paper is: What is the supposed added value operating in the public sphere? Methodology: The study takes an action research strategy. This is highly contextualized methodology, which is enacted within a particular set of social relations into which on expects to integrate the results. As such, this research strategy is particularly well suited for its potential to generate results that can be applied by managers. The aim of action research is to produce proposals with a creative dimension capable of compelling actors to act in a new and pertinent way in relation to the situations they encounter. The context of the study is a workshop on public services innovation within elderly care. The workshop brought together different actors, such as managers, personnel and two groups of users-citizens (elderly clients and their relatives). The process was designed as an extension of the co-construction methods inherent in action research. Scenario methods and focus groups were applied to generate dialogue. The main strength of these techniques is to gather and exploit as much data as possible by exposing the discourse of justification used by the actors to explain or justify their points of view when interacting with others on a given subject. The approach does not directly interrogate the actors on their values, but allows their values to emerge through debate and dialogue. Findings: The public values related to public services innovation management in elderly care were identified in two steps. In the first step, identification of values, values were identified in the discussions. Through continuous analysis of the data, a network of interrelated values was developed. In the second step, tracking group consensus, we then ascertained the degree to which the meaning attributed to the value was common to the participants, classifying the degree of consensus as high, intermediate or low. High consensus corresponds to strong convergence in meaning, intermediate to generally shared meanings between participants, and low to divergences regarding the meaning between participants. Only values with high or intermediate degree of consensus were retained in the analysis. Conclusion: The study shows that the fundamental criterion for justifying public services innovation management is the capacity for actors to enact public values in their work. In the workshop, we identified two categories of public values, intrinsic value and behavioural values, and a list of more specific values.

Keywords: public services innovation management, public value, co-creation, action research

Procedia PDF Downloads 260