Search results for: transportation networks

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Syed Irfan Raza Naqvi, Zheng Jiangbin, Ahmad Moshin, Pervez Akhter

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Currently, the IoT system depends on a centralized client-servant architecture that causes various scalability and privacy vulnerabilities. Distributed ledger technology (DLT) introduces a set of opportunities for the IoT, which leads to practical ideas for existing components at all levels of existing architectures. Blockchain Technology (BCT) appears to be one approach to solving several IoT problems, like Bitcoin (BTC) and Ethereum, which offer multiple possibilities. Besides, IoTs are resource-constrained devices with insufficient capacity and computational overhead to process blockchain consensus mechanisms; the traditional BCT existing challenge for IoTs is poor scalability, energy efficiency, and transaction fees. IOTA is a distributed ledger based on Direct Acyclic Graph (DAG) that ensures M2M micro-transactions are free of charge. IOTA has the potential to address existing IoT-related difficulties such as infrastructure scalability, privacy and access control mechanisms. We proposed an architecture, SLDBI: A Scalable, lightweight DAG-based Blockchain Design for Intelligent IoT Systems, which adapts the DAG base Tangle and implements a lightweight message data model to address the IoT limitations. It enables the smooth integration of new IoT devices into a variety of apps. SLDBI enables comprehensive access control, energy efficiency, and scalability in IoT ecosystems by utilizing the Masked Authentication Message (MAM) protocol and the IOTA Smart Contract Protocol (ISCP). Furthermore, we suggest proof-of-work (PoW) computation on the full node in an energy-efficient way. Experiments have been carried out to show the capability of a tangle to achieve better scalability while maintaining energy efficiency. The findings show user access control management at granularity levels and ensure scale up to massive networks with thousands of IoT nodes, such as Smart Connected Buildings (SCBDs).

Keywords: blockchain, IOT, direct acyclic graphy, scalability, access control, architecture, smart contract, smart connected buildings

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Authors: Hana Drštičková

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The paper describes the findings of a qualitative, engaged research focused on the intersection between transgender and autistic identity in a politically engaged setting of activist (trans, queer, crip, disability justice or any combination thereof) groups. It explores the relationship that autistic and trans people have towards activism and how do they feel their identity(ies) impact the kind of political action they take. Geographically, the research terrain is located mainly in Czechia; however, there are important overlaps with other Eastern European countries. The basis of the research’s approach is built on the interconnected principles of the feminist theory of intersectionality, queer/trans studies, disability studies and the concept of the Neurodiversity Paradigm. This paper argues that the social phenomenon of autism and transness is formed differently in Czechia/Eastern Europe and, therefore, deserves additional attention. Nevertheless, it points out that, even though the socio-political context is different, the fact that these identities have a radical political potential to disrupt normative structures in society remains the same. The measure of oppression these structures generate, and the near absence of any public discourse beyond the pathological paradigm in the chosen terrain contributes to the emergence of mainly queer and trans-activist, and to a lesser extent crip, disability justice or mad activist groups, that attract trans and autistic membership. The subsections of the research focus on the topics of the mutual influence of both identities in flux within individual participants, the perceived (dis)connection of networks of oppression or, conversely, support and identification with the community or communities, and the question of how the trans* and autistic members feel their presence affects the activity, internal dynamics, thematic scope and general values of the activist groups they participate in. The research methodology includes participant observation and active participation in groups where the researcher acts as a partial insider, semi-structured in-depth interviews and a critical participatory methodology. Also included is the reflection of not only the combination of researcher and insider roles but also the combination of research and activist intent.

Keywords: activism, autism, queer, neurodiversity, neuroqueer, transgender

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Authors: Dejenie Birile Gemeda, Wilhelm Stork

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The power system is one of the most important systems in modern society. The existing power system is approaching the critical operating limits as views of several power system operators. With the increase of load demand, high capacity and long transmission networks are widely used to meet the requirement. With the integration of renewable energies such as wind and solar, the uncertainty, intermittence bring bigger challenges to the operation of power systems. These dynamic uncertainties in the power system lead to power disturbances. The disturbances in a heavily stressed power system cause distance relays to mal-operation or false alarms during post fault power oscillations. This unintended operation of these relays may propagate and trigger cascaded trappings leading to total power system blackout. This is due to relays inability to take an appropriate tripping decision based on ensuing power swing. According to the N-1 criterion, electric power systems are generally designed to withstand a single failure without causing the violation of any operating limit. As a result, some overloaded components such as overhead transmission lines can still work for several hours under overload conditions. However, when a large power swing happens in the power system, the settings of the distance relay of zone 3 may trip the transmission line with a short time delay, and they will be acting so quickly that the system operator has no time to respond and stop the cascading. Misfiring of relays in absence of fault due to power swing may have a significant loss in economic performance, thus a loss in revenue for power companies. This research paper proposes a method to distinguish stable power swing from unstable using dynamic line rating (DLR) in response to power swing or disturbances. As opposed to static line rating (SLR), dynamic line rating support effective mitigation actions against propagating cascading outages in a power grid. Effective utilization of existing transmission lines capacity using machine learning DLR predictions will improve the operating point of distance relay protection, thus reducing unintended power outages due to power swing.

Keywords: blackout, cascading outages, dynamic line rating, power swing, overhead transmission lines

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Authors: Kadri-Ann Kertsmik, Martin Talvik, Kimmo Lylykangas, Simo Ilomets, Targo Kalamees

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This study compares the building carbon footprint (CF) values for a case study of a private house located in a cold climate, using the Level(s) methodology. It provides a framework for measuring the environmental performance of buildings throughout their life cycle, taking into account various factors. The study presents the results of the three scenarios, comparing their carbon emissions and highlighting the benefits of circular material usage. The construction process was thoroughly documented, and all materials and components (including minuscule mechanical fasteners, each meter of cable, a kilogram of mortar, and the component of HVAC systems, among other things) delivered to the construction site were noted. Transportation distances of each delivery, the fuel consumption of construction machines, and electricity consumption for temporary heating and electrical tools were also monitored. Using the detailed data on material and energy resources, the CF was calculated for two scenarios: one where circular material usage was applied and another where virgin materials were used instead of reused ones. The results were compared with the CF calculated based on the building permit design model using the Level(s) methodology. To study the range of possible results in the early stage of CF assessment, the same building permit design was given to several experts. Results showed that embodied carbon values for a built scenario were significantly lower than the values predicted by the building permit stage as a result of more precise material quantities, as the calculation methodology is designed to overestimate the CF. Moreover, designers made an effort to reduce the building's CF by reusing certain materials such as ceramic tiles, lightweight concrete blocks, and timber during the construction process. However, in a cold climate context where operational energy (B6) continues to dominate, the total building CF value changes between the three scenarios were less significant. The calculation for the building permit project was performed by several experts, and CF results were in the same range. It alludes that, for the first estimation of preliminary building CF, using average values proves to be an appropriate method for the Estonian national carbon footprint estimation phase during building permit application. The study also identified several opportunities for reducing the carbon footprint of the building, such as reusing materials from other construction sites, preferring local material producers, and reducing wastage on site. The findings suggest that using circular materials can significantly reduce the carbon footprint of buildings. Overall, the study highlights the importance of using a comprehensive approach to measure the environmental performance of buildings, taking into account both the project and the actually built house. It also emphasises the need for ongoing monitoring for designing the building and construction site waste. The study also gives some examples of how to enable future circularity of building components and materials, e.g., building in layers, using wood as untreated, etc.

Keywords: carbon footprint, circular economy, sustainable construction, level(s) methodology

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Authors: Prince Suka Neekia Momta, Rita Iheoma Achonyeulo

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Ant Tracking seismic attribute applied over 4-seconds seismic volume revealed structural features triggered by clay diapirism, growth fault development, rapid deltaic sedimentation and intense drilling. The attribute was extracted on vertical seismic sections and time slices. Mega tectonic structures such as growth faults and clay diapirs are visible on vertical sections with obscured minor lineaments or fractures. Fractures are distinctively visible on time slices yielding recognizable patterns corroborating established geologic models. This model seismic attribute enabled the understanding of fluid flow characteristics and production responses. Three structural patterns recognized in the field include: major growth faults, minor faults or lineaments and network of fractures. Three growth faults mapped on seismic section form major deformation bands delimiting the area into three blocks or depocenters. The growth faults trend E-W, dip down-to-south in the basin direction, and cut across the study area. The faults initiating from about 2000ms extended up to 500ms, and tend to progress parallel and opposite to the growth direction of an upsurging diapiric structure. The diapiric structures form the major deformational bands originating from great depths (below 2000ms) and rising to about 1200ms where series of sedimentary layers onlapped and pinchout stratigraphically against the diapir. Several other secondary faults or lineaments that form parallel streaks to one another also accompanied the growth faults. The fracture networks have no particular trend but form a network surrounding the well area. Faults identified in the study area have potentials for structural hydrocarbon traps whereas the presence of fractures created a fractured-reservoir condition that enhanced rapid fluid flow especially water. High aquifer flow potential aided by possible fracture permeability resulted in rapid decline in oil rate. Through the application of Ant Tracking attribute, it is possible to obtain detailed interpretation of structures that can have direct influence on oil and gas production.

Keywords: seismic, attributes, production, structural

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Authors: Ayesha Waqar Khan, Mariam Altaf, Jamil Ahmad, Shaheen Shahzad

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Kidney fibrosis is an anticipated outcome of possibly all types of progressive chronic kidney disease (CKD). Epithelial-mesenchymal transition (EMT) signaling pathway is responsible for production of matrix-producing fibroblasts and myofibroblasts in diseased kidney. In this study, a discrete model of TGF-beta (transforming growth factor) and CTGF (connective tissue growth factor) was constructed using Rene Thomas formalism to investigate renal fibrosis turn over. The kinetic logic proposed by Rene Thomas is a renowned approach for modeling of Biological Regulatory Networks (BRNs). This modeling approach uses a set of constraints which represents the dynamics of the BRN thus analyzing the pathway and predicting critical trajectories that lead to a normal or diseased state. The molecular connection between TGF-beta, Smad 2/3 (transcription factor) phosphorylation and CTGF is modeled using GenoTech. The order of BRN is CTGF, TGF-B, and SMAD3 respectively. The predicted cycle depicts activation of TGF-B (TGF-β) via cleavage of its own pro-domain (0,1,0) and presentation to TGFR-II receptor phosphorylating SMAD3 (Smad2/3) in the state (0,1,1). Later TGF-B is turned off (0,0,1) thereby activating SMAD3 that further stimulates the expression of CTGF in the state (1,0,1) and itself turns off in (1,0,0). Elevated CTGF expression reactivates TGF-B (1,1,0) and the cycle continues. The predicted model has generated one cycle and two steady states. Cyclic behavior in this study represents the diseased state in which all three proteins contribute to renal fibrosis. The proposed model is in accordance with the experimental findings of the existing diseased state. Extended cycle results in enhanced CTGF expression through Smad2/3 and Smad4 translocation in the nucleus. The results suggest that the system converges towards organ fibrogenesis if CTGF remains constructively active along with Smad2/3 and Smad 4 that plays an important role in kidney fibrosis. Therefore, modeling regulatory pathways of kidney fibrosis will escort to the progress of therapeutic tools and real-world useful applications such as predictive and preventive medicine.

Keywords: CTGF, renal fibrosis signaling pathway, system biology, qualitative modeling

Procedia PDF Downloads 168

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Iris Vural Gursel, Andrea Ramirez

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Effective utilization of lignin is an important mean for developing economically profitable biorefineries. Current literature suggests that large amounts of lignin will become available in second generation biorefineries. New conversion technologies will, therefore, be needed to carry lignin transformation well beyond combustion to produce energy, but towards high-value products such as chemicals and transportation fuels. In recent years, significant progress on catalysis has been made to improve transformation of lignin, and new catalytic processes are emerging. In this work, a techno-economic assessment of two of these novel conversion routes and comparison with more established lignin pyrolysis route were made. The aim is to provide insights into the potential performance and potential hotspots in order to guide the experimental research and ease the commercialization by early identifying cost drivers, strengths, and challenges. The lignin conversion routes selected for detailed assessment were: (non-catalytic) lignin pyrolysis as the benchmark, direct hydrodeoxygenation (HDO) of lignin and hydrothermal lignin depolymerisation. Products generated were mixed oxygenated aromatic monomers (MOAMON), light organics, heavy organics, and char. For the technical assessment, a basis design followed by process modelling in Aspen was done using experimental yields. A design capacity of 200 kt/year lignin feed was chosen that is equivalent to a 1 Mt/y scale lignocellulosic biorefinery. The downstream equipment was modelled to achieve the separation of the product streams defined. For determining external utility requirement, heat integration was considered and when possible gasses were combusted to cover heating demand. The models made were used in generating necessary data on material and energy flows. Next, an economic assessment was carried out by estimating operating and capital costs. Return on investment (ROI) and payback period (PBP) were used as indicators. The results of the process modelling indicate that series of separation steps are required. The downstream processing was found especially demanding in the hydrothermal upgrading process due to the presence of significant amount of unconverted lignin (34%) and water. Also, external utility requirements were found to be high. Due to the complex separations, hydrothermal upgrading process showed the highest capital cost (50 M€ more than benchmark). Whereas operating costs were found the highest for the direct HDO process (20 M€/year more than benchmark) due to the use of hydrogen. Because of high yields to valuable heavy organics (32%) and MOAMON (24%), direct HDO process showed the highest ROI (12%) and the shortest PBP (5 years). This process is found feasible with a positive net present value. However, it is very sensitive to the prices used in the calculation. The assessments at this stage are associated with large uncertainties. Nevertheless, they are useful for comparing alternatives and identifying whether a certain process should be given further consideration. Among the three processes investigated here, the direct HDO process was seen to be the most promising.

Keywords: biorefinery, economic assessment, lignin conversion, process design

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Authors: Ugur Fidan, Naim Karasekreter

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Healthy and clean water should not contain disease-causing micro-organisms and toxic chemicals and must contain the necessary minerals in a balanced manner. Today, water resources have a limited and strategic importance, necessitating the management of water reserves. Water tanks meet the water needs of people and should be regularly chlorinated to prevent waterborne diseases. For this purpose, automatic chlorination systems placed in water tanks for killing bacteria. However, the regular operation of automatic chlorination systems depends on refilling the chlorine tank when it is empty. For this reason, there is a need for a stock control system, in which chlorine levels are regularly monitored and supplied. It has become imperative to take urgent measures against epidemics caused by the fact that most of our country is not aware of the end of chlorine. The aim of this work is to rehabilitate existing water tanks and to provide a method for a modern water storage system in which chlorination is digitally monitored by turning the newly established water tanks into a closed system. A sensor network structure using GSM/GPRS communication infrastructure has been developed in the study. The system consists of two basic units: hardware and software. The hardware includes a chlorine level sensor, an RFID interlock system for authorized personnel entry into water tank, a motion sensor for animals and other elements, and a camera system to ensure process safety. It transmits the data from the hardware sensors to the host server software via the TCP/IP protocol. The main server software processes the incoming data through the security algorithm and informs the relevant unit responsible (Security forces, Chlorine supply unit, Public health, Local Administrator) by e-mail and SMS. Since the software is developed base on the web, authorized personnel are also able to monitor drinking water tank and report data on the internet. When the findings and user feedback obtained as a result of the study are evaluated, it is shown that closed drinking water tanks are built with GRP type material, and continuous monitoring in digital environment is vital for sustainable health water supply for people.

Keywords: wireless sensor networks (WSN), monitoring, chlorine, water tank, security

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Authors: Emre Basturk, Memet Vezir Kahraman

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In many developing countries, with the rapid economic improvements, energy shortage and environmental issues have become a serious problem. Therefore, it has become a very critical issue to improve energy usage efficiency and also protect the environment. Thermal energy storage system is an essential approach to match the thermal energy claim and supply. Thermal energy can be stored by heating, cooling or melting a material with the energy and then enhancing accessible when the procedure is reversed. The overall thermal energy storage techniques are sorted as; latent heat or sensible heat thermal energy storage technology segments. Among these methods, latent heat storage is the most effective method of collecting thermal energy. Latent heat thermal energy storage depend on the storage material, emitting or discharging heat as it undergoes a solid to liquid, solid to solid or liquid to gas phase change or vice versa. Phase change materials (PCMs) are promising materials for latent heat storage applications due to their capacities to accumulate high latent heat storage per unit volume by phase change at an almost constant temperature. Phase change materials (PCMs) are being utilized to absorb, collect and discharge thermal energy during the cycle of melting and freezing, converting from one phase to another. Phase Change Materials (PCMs) can generally be arranged into three classes: organic materials, salt hydrates and eutectics. Many kinds of organic and inorganic PCMs and their blends have been examined as latent heat storage materials. Organic PCMs are rather expensive and they have average latent heat storage per unit volume and also have low density. Most organic PCMs are combustible in nature and also have a wide range of melting point. Organic PCMs can be categorized into two major categories: non-paraffinic and paraffin materials. Paraffin materials have been extensively used, due to their high latent heat and right thermal characteristics, such as minimal super cooling, varying phase change temperature, low vapor pressure while melting, good chemical and thermal stability, and self-nucleating behavior. Ultraviolet (UV)-curing technology has been generally used because it has many advantages, such as low energy consumption , high speed, high chemical stability, room-temperature operation, low processing costs and environmental friendly. For many years, PCMs have been used for heating and cooling industrial applications including textiles, refrigerators, construction, transportation packaging for temperature-sensitive products, a few solar energy based systems, biomedical and electronic materials. In this study, UV-curable, fatty alcohol containing soybean oil based phase change materials (PCMs) were obtained and characterized. The phase transition behaviors and thermal stability of the prepared UV-cured biobased PCMs were analyzed by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The heating process phase change enthalpy is measured between 30 and 68 J/g, and the freezing process phase change enthalpy is found between 18 and 70 J/g. The decomposition of UVcured PCMs started at 260 ºC and reached a maximum of 430 ºC.

Keywords: fatty alcohol, phase change material, thermal energy storage, UV curing

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Authors: John K. Avor, Choong-Koo Chang

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The transfer of electrical loads at power generation stations from Standby Auxiliary Transformer (SAT) to Unit Auxiliary Transformer (UAT) and vice versa is through a fast bus transfer scheme. Fast bus transfer is a time-critical application where the transfer process depends on various parameters, thus transfer schemes apply advance algorithms to ensure power supply reliability and continuity. In a nuclear power generation station, supply continuity is essential, especially for critical class 1E electrical loads. Bus transfers must, therefore, be executed accurately within 4 to 10 cycles in order to achieve safety system requirements. However, the main problem is that there are instances where transfer schemes scrambled due to inaccurate interpretation of key parameters; and consequently, have failed to transfer several critical loads from UAT to the SAT during main generator trip event. Although several techniques have been adopted to develop robust transfer schemes, a combination of Artificial Neural Network and Fuzzy Systems (Neuro-Fuzzy) has not been extensively used. In this paper, we apply the concept of Neuro-Fuzzy to determine plant operating mode and dynamic prediction of the appropriate bus transfer algorithm to be selected based on the first cycle of voltage information. The performance of Sequential Fast Transfer and Residual Bus Transfer schemes was evaluated through simulation and integration of the Neuro-Fuzzy system. The objective for adopting Neuro-Fuzzy approach in the bus transfer scheme is to utilize the signal validation capabilities of artificial neural network, specifically the back-propagation algorithm which is very accurate in learning completely new systems. This research presents a combined effect of artificial neural network and fuzzy systems to accurately interpret key bus transfer parameters such as magnitude of the residual voltage, decay time, and the associated phase angle of the residual voltage in order to determine the possibility of high speed bus transfer for a particular bus and the corresponding transfer algorithm. This demonstrates potential for general applicability to improve reliability of the auxiliary power distribution system. The performance of the scheme is implemented on APR1400 nuclear power plant auxiliary system.

Keywords: auxiliary power system, bus transfer scheme, fuzzy logic, neural networks, reliability

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Authors: Federico Capra, Emanuele Martelli, Matteo Gazzani, Marco Mazzotti, Maurizio Notaro

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Natural gas is a major energy source in the current global economy, contributing to roughly 21% of the total primary energy consumption. Production of natural gas starting from renewable energy sources is key to limit the related CO2 emissions, especially for those sectors that heavily rely on natural gas use. In this context, biomethane produced via biogas upgrading represents a good candidate for partial substitution of fossil natural gas. The upgrading process of biogas to biomethane consists in (i) the removal of pollutants and impurities (e.g. H2S, siloxanes, ammonia, water), and (ii) the separation of carbon dioxide from methane. Focusing on the CO2 removal process, several technologies can be considered: chemical or physical absorption with solvents (e.g. water, amines), membranes, adsorption-based systems (PSA). However, none emerged as the leading technology, because of (i) the heterogeneity in plant size, ii) the heterogeneity in biogas composition, which is strongly related to the feedstock type (animal manure, sewage treatment, landfill products), (iii) the case-sensitive optimal tradeoff between purity and recovery of biomethane, and iv) the destination of the produced biomethane (grid injection, CHP applications, transportation sector). With this contribution, we explore the use of a technology for biogas upgrading and we compare the resulting performance with benchmark technologies. The proposed technology makes use of a chemical sorbent, which is engineered by RSE and consists of Di-Ethanol-Amine deposited on a solid support made of γ-Alumina, to chemically adsorb the CO2 contained in the gas. The material is packed into fixed beds that cyclically undergo adsorption and regeneration steps. CO2 is adsorbed at low temperature and ambient pressure (or slightly above) while the regeneration is carried out by pulling vacuum and increasing the temperature of the bed (vacuum-temperature swing adsorption - VTSA). Dynamic adsorption tests were performed by RSE and were used to tune the mathematical model of the process, including material and transport parameters (i.e. Langmuir isotherms data and heat and mass transport). Based on this set of data, an optimal VTSA cycle was designed. The results enabled a better understanding of the interplay between material and cycle tuning. As exemplary application, the upgrading of biogas for grid injection, produced by an anaerobic digester (60-70% CO2, 30-40% CH4), for an equivalent size of 1 MWel was selected. A plant configuration is proposed to maximize heat recovery and minimize the energy consumption of the process. The resulting performances are very promising compared to benchmark solutions, which make the VTSA configuration a valuable alternative for biomethane production starting from biogas.

Keywords: biogas upgrading, biogas upgrading energetic cost, CO2 adsorption, VTSA process modelling

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Authors: Beatriz Botella-Gil, Patricio Martínez-Barco, Lea Canales

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The Internet and ICT are an integral element of and omnipresent in our daily lives. Technologies have changed the way we see the world and relate to it. The number of companies in the ICT sector is increasing every year, and there has also been an increase in the work that occurs online, from sending e-mails to the way companies promote themselves. In social life, ICT’s have gained momentum. Social networks are useful for keeping in contact with family or friends that live far away. This change in how we manage our relationships using electronic devices and social media has been experienced differently depending on the age of the person. According to currently available data, people are increasingly connected to social media and other forms of online communication. Therefore, it is no surprise that violent content has also made its way to digital media. One of the important reasons for this is the anonymity provided by social media, which causes a sense of impunity in the victim. Moreover, it is not uncommon to find derogatory comments, attacking a person’s physical appearance, hobbies, or beliefs. This is why it is necessary to develop artificial intelligence tools that allow us to keep track of violent comments that relate to violent events so that this type of violent online behavior can be deterred. The objective of our research is to create a guide for detecting and recording violent messages. Our annotation guide begins with a study on the problem of violent messages. First, we consider the characteristics that a message should contain for it to be categorized as violent. Second, the possibility of establishing different levels of aggressiveness. To download the corpus, we chose the social network Twitter for its ease of obtaining free messages. We chose two recent, highly visible violent cases that occurred in Spain. Both of them experienced a high degree of social media coverage and user comments. Our corpus has a total of 633 messages, manually tagged, according to the characteristics we considered important, such as, for example, the verbs used, the presence of exclamations or insults, and the presence of negations. We consider it necessary to create wordlists that are present in violent messages as indicators of violence, such as lists of negative verbs, insults, negative phrases. As a final step, we will use automatic learning systems to check the data obtained and the effectiveness of our guide.

Keywords: human language technologies, language modelling, offensive language detection, violent online content

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Authors: Mohamad Mahdi Namdari

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In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

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Authors: Muzaffar Shaikh, Shoaib Shaikh, Mark Moyou, Gaby Hawat

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This paper presents the use of Analytic Hierarchy Process (AHP) in evaluating the site selection of a new plant by a corporation. Due to intense competition at a global level, multinational corporations are continuously striving to minimize production and shipping costs of their products. One key factor that plays significant role in cost minimization is where the production plant is located. In the U.S. for example, labor and land costs continue to be very high while they are much cheaper in countries such as India, China, Indonesia, etc. This is why many multinational U.S. corporations (e.g. General Electric, Caterpillar Inc., Ford, General Motors, etc.), have shifted their manufacturing plants outside. The continued expansion of the Internet and its availability along with technological advances in computer hardware and software all around the globe have facilitated U.S. corporations to expand abroad as they seek to reduce production cost. In particular, management of multinational corporations is constantly engaged in concentrating on countries at a broad level, or cities within specific countries where certain or all parts of their end products or the end products themselves can be manufactured cheaper than in the U.S. AHP is based on preference ratings of a specific decision maker who can be the Chief Operating Officer of a company or his/her designated data analytics engineer. It serves as a tool to first evaluate the plant site selection criteria and second, alternate plant sites themselves against these criteria in a systematic manner. Examples of site selection criteria are: Transportation Modes, Taxes, Energy Modes, Labor Force Availability, Labor Rates, Raw Material Availability, Political Stability, Land Costs, etc. As a necessary first step under AHP, evaluation criteria and alternate plant site countries are identified. Depending upon the fidelity of analysis, specific cities within a country can also be chosen as alternative facility locations. AHP experience in this type of analysis indicates that the initial analysis can be performed at the Country-level. Once a specific country is chosen via AHP, secondary analyses can be performed by selecting specific cities or counties within a country. AHP analysis is usually based on preferred ratings of a decision-maker (e.g., 1 to 5, 1 to 7, or 1 to 9, etc., where 1 means least preferred and a 5 means most preferred). The decision-maker assigns preferred ratings first, criterion vs. criterion and creates a Criteria Matrix. Next, he/she assigns preference ratings by alternative vs. alternative against each criterion. Once this data is collected, AHP is applied to first get the rank-ordering of criteria. Next, rank-ordering of alternatives is done against each criterion resulting in an Alternative Matrix. Finally, overall rank ordering of alternative facility locations is obtained by matrix multiplication of Alternative Matrix and Criteria Matrix. The most practical aspect of AHP is the ‘what if’ analysis that the decision-maker can conduct after the initial results to provide valuable sensitivity information of specific criteria to other criteria and alternatives.

Keywords: analytic hierarchy process, multinational corporations, plant site selection, preference ratings

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Authors: Sabyasachi Behera, Shiv Kumar, Pramod Gautam, Anisur Rahman, Pawan Pathak, Rahul Bhadouria

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Background: The increasing proportion of population especially urban poor and vulnerable groups or groups with specific needs, with health indicators worse than their rural counterparts in India face various issues related with availability and quality of health care. The reasons are myriad, starting from information and awareness of the community, especially, in a scenario wherein the needs and challenges of floating and migrant urban populations remain poorly understood. Weak linkages between health care facilities and slum dwellers and vulnerable populations hinder the improvement of health services for urban poor. Method: To address this issue, TCIHC program is helping health department of Indore city of Madhya Pradesh to establish a referral mechanism with a dual approach: at both community and facility level. The former is based on the premise of ‘building social capital’, i.e. norms and networks within a community facilitating collective action, helps improve the demand and supply of health services at appropriate levels of care (Minus 2: Accredited Social Health Activist and Community Health Groups; Minus 1: Urban Health Nutrition Days; Zero: Urban Primary Health Center; Plus 1: secondary facility with BEmONC services; Plus 2: secondary facilities with CEmONC services; Plus 3: tertiary level facility) for the urban poor. The latter focuses on encouraging the provision of all services at various levels of service delivery points and stakeholders to function in a coordinated manner to ensure better health service availability and coverage in underserved slum areas. Results: This initiative has enhanced the utilization of community based, primary and secondary level services through defined referral pathways that are clearly known to a community dweller. Conclusion: An ideal referral mechanism should begin with referral at the community level wherein services of a frontline health care provider are accessed by them at their door-step, causing no delay in both understanding and decision on the health issues faced by them.

Keywords: levels of care, linkages, referral mechanism, service delivery

Procedia PDF Downloads 132

Authors: Serdar Yaman, Hanzade Haykiri-Acma

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Biomass is a CO₂-neutral fuel that is renewable and sustainable along with having very huge global potential. Efficient use of biomass in power generation and production of biomass-based biofuels can mitigate the greenhouse gasses (GHG) and reduce dependency on fossil fuels. There are also other beneficial effects of biomass energy use such as employment creation and pollutant reduction. However, most of the biomass materials are not capable of competing with fossil fuels in terms of energy content. High moisture content and high volatile matter yields of biomass make it low calorific fuel, and it is very significant concern over fossil fuels. Besides, the density of biomass is generally low, and it brings difficulty in transportation and storage. These negative aspects of biomass can be overcome by thermal pretreatments that upgrade the fuel property of biomass. That is, torrefaction is such a thermal process in which biomass is heated up to 300ºC under non-oxidizing conditions to avoid burning of the material. The treated biomass is called as biochar that has considerably lower contents of moisture, volatile matter, and oxygen compared to the parent biomass. Accordingly, carbon content and the calorific value of biochar increase to the level which is comparable with that of coal. Moreover, hydrophilic nature of untreated biomass that leads decay in the structure is mostly eliminated, and the surface properties of biochar turn into hydrophobic character upon torrefaction. In order to investigate the effectiveness of torrefaction process on biomass properties, several biomass species such as olive milling residue (OMR), Rhododendron (small shrubby tree with bell-shaped flowers), and ash tree (timber tree) were chosen. The fuel properties of these biomasses were analyzed through proximate and ultimate analyses as well as higher heating value (HHV) determination. For this, samples were first chopped and ground to a particle size lower than 250 µm. Then, samples were subjected to torrefaction in a horizontal tube furnace by heating from ambient up to temperatures of 200, 250, and 300ºC at a heating rate of 10ºC/min. The biochars obtained from this process were also tested by the methods applied to the parent biomass species. Improvement in the fuel properties was interpreted. That is, increasing torrefaction temperature led to regular increases in the HHV in OMR, and the highest HHV (6065 kcal/kg) was gained at 300ºC. Whereas, torrefaction at 250ºC was seen optimum for Rhododendron and ash tree since torrefaction at 300ºC had a detrimental effect on HHV. On the other hand, the increase in carbon contents and reduction in oxygen contents were determined. Burning characteristics of the biochars were also studied using thermal analysis technique. For this purpose, TA Instruments SDT Q600 model thermal analyzer was used and the thermogravimetric analysis (TGA), derivative thermogravimetry (DTG), differential scanning calorimetry (DSC), and differential thermal analysis (DTA) curves were compared and interpreted. It was concluded that torrefaction is an efficient method to upgrade the fuel properties of biomass and the biochars from which have superior characteristics compared to the parent biomasses.

Keywords: biochar, biomass, fuel upgrade, torrefaction

Procedia PDF Downloads 362

Authors: Zahra Hamidi

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Promoting cycling, as an affordable environmentally friendly mode of transport to replace private car use has been central to sustainable transport policies. Cycling is faster than walking and combined with public transport has the potential to extend the opportunities that people can access. In other words, cycling, besides direct positive health impacts, can improve people mobility and ultimately their quality of life. Transport literature well supports the close relationship between mobility, quality of life, and, well being. At the same time inequity in the distribution of access and mobility has been associated with the key aspects of injustice and social exclusion. The pattern of social exclusion and inequality in access are also often related to population characteristics such as age, gender, income, health, and ethnic background. Therefore, while investing in transport infrastructure it is important to consider the equity of provided access for different population groups. This paper proposes a method to evaluate the equity of cycling in a city from Rawls egalitarian perspective. Since this perspective is concerned with the difference between individuals and social groups, this method combines accessibility measures and Theil index of inequality that allows capturing the inequalities ‘within’ and ‘between’ groups. The paper specifically focuses on two population characteristics as gender and ethnic background. Following Rawls equity principles, this paper measures accessibility by bikes to a selection of urban activities that can be linked to the concept of the social primary goods. Moreover, as growing number of cities around the world have launched bike-sharing systems (BSS) this paper incorporates both private and public bikes networks in the estimation of accessibility levels. Additionally, the typology of bike lanes (separated from or shared with roads), the presence of a bike sharing system in the network, as well as bike facilities (e.g. parking racks) have been included in the developed accessibility measures. Application of this proposed method to a real case study, the city of Malmö, Sweden, shows its effectiveness and efficiency. Although the accessibility levels were estimated only based on gender and ethnic background characteristics of the population, the author suggests that the analysis can be applied to other contexts and further developed using other properties, such as age, income, or health.

Keywords: accessibility, cycling, equity, gender

Procedia PDF Downloads 391

Authors: Kanchan Mondal, Adam Sims, Madhav Soti, Jitendra Gautam, David Carron

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Fischer-Tropsch (FT) synthesis is a complex series of heterogeneous reactions between CO and H2 molecules (present in the syngas) on the surface of an active catalyst (Co, Fe, Ru, Ni, etc.) to produce gaseous, liquid, and waxy hydrocarbons. This product is composed of paraffins, olefins, and oxygenated compounds. The key challenge in applying the Fischer-Tropsch process to produce transportation fuels is to make the capital and production costs economically feasible relative to the comparative cost of existing petroleum resources. To meet this challenge, it is imperative to enhance the CO conversion while maximizing carbon selectivity towards the desired liquid hydrocarbon ranges (i.e. reduction in CH4 and CO2 selectivities) at high throughputs. At the same time, it is equally essential to increase the catalyst robustness and longevity without sacrificing catalyst activity. This paper focuses on process development to achieve the above. The paper describes the influence of operating parameters on Fischer Tropsch synthesis (FTS) from coal derived syngas in supercritical carbon dioxide (ScCO2). In addition, the unreacted gas and solvent recycle was incorporated and the effect of unreacted feed recycle was evaluated. It was expected that with the recycle, the feed rate can be increased. The increase in conversion and liquid selectivity accompanied by the production of narrower carbon number distribution in the product suggest that higher flow rates can and should be used when incorporating exit gas recycle. It was observed that this process was capable of enhancing the hydrocarbon selectivity (nearly 98 % CO conversion), reducing improving the carbon efficiency from 17 % to 51 % in a once through process and further converting 16 % CO2 to liquid with integrated recycle of the product gas stream and increasing the life of the catalyst. Catalyst robustness enhancement has been attributed to the absorption of heat of reaction by the compressed CO2 which reduced the formation of hotspots and the dissolution of waxes by the CO2 solvent which reduced the blinding of active sites. In addition, the recycling the product gas stream reduced the reactor footprint to one-fourth of the once through size and product fractionation utilizing the solvent effects of supercritical CO2 were realized. In addition to the negative CO2 selectivities, methane production was also inhibited and was limited to less than 1.5%. The effect of the process conditions on the life of the catalysts will also be presented. Fe based catalysts are known to have a high proclivity for producing CO2 during FTS. The data of the product spectrum and selectivity on Co and Fe-Co based catalysts as well as those obtained from commercial sources will also be presented. The measurable decision criteria were the increase in CO conversion at H2:CO ratio of 1:1 (as commonly found in coal gasification product stream) in supercritical phase as compared to gas phase reaction, decrease in CO2 and CH4 selectivity, overall liquid product distribution, and finally an increase in the life of the catalysts.

Keywords: carbon efficiency, Fischer Tropsch synthesis, low GHG, pressure tunable fractionation

Procedia PDF Downloads 232

Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

Procedia PDF Downloads 54

Authors: Kalep Filli, Sophia Wassén, Annika Krona, Mats Stading

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Food security challenge and the growing population in Sub-Saharan Africa centers on its agricultural transformation, where about 70% of its population is directly involved in farming. Research input can create economic opportunities, reduce malnutrition and poverty, and generate faster, fairer growth. Africa is discarding $4 billion worth of grain annually due to pre and post-harvest losses. Grains and tubers play a central role in food supply in the region but their production has generally lagged behind because no robust scientific input to meet up with the challenge. The African grains are still chronically underutilized to the detriment of the well-being of the people of Africa and elsewhere. The major reason for their underutilization is because they are under-researched. Any commitment by scientific community to intervene needs creative solutions focused on innovative approaches that will meet the economic growth. In order to mitigate this hurdle, co-creation activities and initiatives are necessary.An example of such initiatives has been initiated through Modibbo Adama University of Technology Yola, Nigeria and RISE (The Research Institutes of Sweden) Gothenburg, Sweden. Exchange of expertise in research activities as a possibility to create channel for value addition to agricultural commodities in the region under the ´Traditional Grain Network programme´ is in place. Process technologies, such as extrusion offers the possibility of creating products in the food and feed sectors, with better storage stability, added value, lower transportation cost and new markets. The Swedish–Nigerian initiative has focused on the development of high protein pasta. Dry microscopy of pasta sample result shows a continuous structural framework of proteins and starch matrix. The water absorption index (WAI) results showed that water was absorbed steadily and followed the master curve pattern. The WAI values ranged between 250 – 300%. In all aspect, the water absorption history was within a narrow range for all the eight samples. The total cooking time for all the eight samples in our study ranged between 5 – 6 minutes with their respective dry sample diameter ranging between 1.26 – 1.35 mm. The percentage water solubility index (WSI) ranged from 6.03 – 6.50% which was within a narrow range and the cooking loss which is a measure of WSI is considered as one of the main parameters taken into consideration during the assessment of pasta quality. The protein contents of the samples ranged between 17.33 – 18.60 %. The value of the cooked pasta firmness ranged from 0.28 - 0.86 N. The result shows that increase in ratio of cowpea flour and level of pregelatinized cowpea tends to increase the firmness of the pasta. The breaking strength represent index of toughness of the dry pasta ranged and it ranged from 12.9 - 16.5 MPa.

Keywords: cowpea, extrusion, gluten free, high protein, pasta, sorghum

Procedia PDF Downloads 176

Authors: Charbel Aoun, Loic Lagadec

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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

Procedia PDF Downloads 162

Authors: Pankaj Kumar Jha, Mahendra Singh Hada, Brijendra Singh, Sandeep Yadav

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Protective relays are commonly connected to the secondary windings of instrument transformers, i.e., current transformers (CTs) and/or capacitive voltage transformers (CVTs). The purpose of CT and CVT is to provide galvanic isolation from high voltages and reduce primary currents and voltages to a nominal quantity recognized by the protective relays. Selecting the correct instrument transformers for an application is imperative: failing to do so may compromise the relay’s performance, as the output of the instrument transformer may no longer be an accurately scaled representation of the primary quantity. Having an accurately rated instrument transformer is of no use if these devices are not properly connected. The performance of the protective relay is reliant on its programmed settings and on the current and voltage inputs from the instrument transformers secondary. This paper will help in understanding the fundamental concepts of the connections of Instrument Transformers to the protection relays and the effect of incorrect connection on the performance of protective relays. Multiple case studies of protection system mal-operations due to incorrect connections of instrument transformers will be discussed in detail in this paper. Apart from the connection issue of instrument transformers to protective relays, this paper will also discuss the effect of multiple earthing of CTs and CVTs secondary on the performance of the protection system. Case studies presented in this paper will help the readers to analyse the problem through real-world challenges in complex power system networks. This paper will also help the protection engineer in better analysis of disturbance records. CT and CVT connection errors can lead to undesired operations of protection systems. However, many of these operations can be avoided by adhering to industry standards and implementing tried-and-true field testing and commissioning practices. Understanding the effect of missing neutral of CVT, multiple earthing of CVT secondary, and multiple grounding of CT star points on the performance of the protection system through real-world case studies will help the protection engineer in better commissioning the protection system and maintenance of the protection system.

Keywords: bus reactor, current transformer, capacitive voltage transformer, distance protection, differential protection, directional earth fault, disturbance report, instrument transformer, ICT, REF protection, shunt reactor, voltage selection relay, VT fuse failure

Procedia PDF Downloads 68

Authors: Frea Van Steenweghen, Lander Hollevoet, Johan A. Martens

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Compared to other hydrogen (H₂) carriers, ammonia (NH₃) is one of the most promising carriers as it contains 17.6 wt% hydrogen. It is easily liquefied at ≈ 9–10 bar pressure at ambient temperature. More importantly, NH₃ is a carbon-free hydrogen carrier with no CO₂ emission at final decomposition. Ammonia has a well-defined regulatory framework and a good track record regarding safety concerns. Furthermore, the industry already has an existing transport infrastructure consisting of pipelines, tank trucks and shipping technology, as ammonia has been manufactured and distributed around the world for over a century. While NH₃ synthesis and transportation technological solutions are at hand, a missing link in the hydrogen delivery scheme from ammonia is an energy-lean and efficient technology for cracking ammonia into H₂ and N₂. The most explored option for ammonia decomposition is thermo-catalytic cracking which is, by itself, the most energy-efficient approach compared to other technologies, such as plasma and electrolysis, as it is the most energy-lean and robust option. The decomposition reaction is favoured only at high temperatures (> 300°C) and low pressures (1 bar) as the thermocatalytic ammonia cracking process is faced with thermodynamic limitations. At 350°C, the thermodynamic equilibrium at 1 bar pressure limits the conversion to 99%. Gaining additional conversion up to e.g. 99.9% necessitates heating to ca. 530°C. However, reaching thermodynamic equilibrium is infeasible as a sufficient driving force is needed, requiring even higher temperatures. Limiting the conversion below the equilibrium composition is a more economical option. Thermocatalytic ammonia cracking is documented in scientific literature. Among the investigated metal catalysts (Ru, Co, Ni, Fe, …), ruthenium is known to be most active for ammonia decomposition with an onset of cracking activity around 350°C. For establishing > 99% conversion reaction, temperatures close to 600°C are required. Such high temperatures are likely to reduce the round-trip efficiency but also the catalyst lifetime because of the sintering of the supported metal phase. In this research, the first focus was on catalyst bed design, avoiding diffusion limitation. Experiments in our packed bed tubular reactor set-up showed that extragranular diffusion limitations occur at low concentrations of NH₃ when reaching high conversion, a phenomenon often overlooked in experimental work. A second focus was thermocatalyst development for ammonia cracking, avoiding the use of noble metals. To this aim, candidate metals and mixtures were deposited on a range of supports. Sintering resistance at high temperatures and the basicity of the support were found to be crucial catalyst properties. The catalytic activity was promoted by adding alkaline and alkaline earth metals. A third focus was studying the optimum process configuration by process simulations. A trade-off between conversion and favorable operational conditions (i.e. low pressure and high temperature) may lead to different process configurations, each with its own pros and cons. For example, high-pressure cracking would eliminate the need for post-compression but is detrimental for the thermodynamic equilibrium, leading to an optimum in cracking pressure in terms of energy cost.

Keywords: ammonia cracking, catalyst research, kinetics, process simulation, thermodynamic equilibrium

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Authors: Denise Bianco

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Several studies on innovation and creativity in organisations emphasise the need to expand horizons and take on alternative and unexpected views to produce something new. This paper theorises the potential impact artists can have as creative catalysts, working embedded in non-artistic organisations. It begins from an understanding that in today's ever-changing scenario, organisations are increasingly seeking to open up new creative thinking through deviant behaviours to produce innovation and that art residencies need to be critically revised in this specific context in light of their disruptive potential. On the one hand, this paper builds upon recent contributions made on workplace creativity and related concepts of deviance and disruption. Research suggests that creativity is likely to be lower in work contexts where utter conformity is a cardinal value and higher in work contexts that show some tolerance for uncertainty and deviance. On the other hand, this paper draws attention to Artist-in-Residence as a vehicle for epistemic friction between divergent and convergent thinking, which allows the creation of unparalleled ways of knowing in the dailiness of situated and contextualised social processes. In order to do so, this contribution brings together insights from the most relevant theories on organisational creativity and unconventional agile methods such as Art Thinking and direct insights from ethnographic fieldwork in the context of embedded art residencies within work organisations to propose a redefinition of Artist-in-Residence and their potential impact on organisational creativity. The result is a re-definition of embedded Artist-in-Residence in organisational settings from a more comprehensive, multi-disciplinary, and relational perspective that builds on three focal points. First the notion that organisational creativity is a dynamic and synergistic process throughout which an idea is framed by recurrent activities subjected to multiple influences. Second, the definition of embedded Artist-in-Residence as an assemblage of dynamic, productive relations and unexpected possibilities for new networks of relationality that encourage the recombination of knowledge. Third, and most importantly, the acknowledgment that embedded residencies are, at the very essence, bi-cultural knowledge contexts where creativity flourishes as the result of open-to-change processes that are highly relational, constantly negotiated, and contextualised in time and space.

Keywords: artist-in-residence, convergent and divergent thinking, creativity, creative friction, deviance and creativity

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Authors: Obiamaka Nwobu, Samuel Faboyede, O. Oluseyi

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This study investigated the influence of gender on expectations and actual experiences from Industrial Work Experience, which is an aspect of the curriculum of undergraduate accounting students in selected Nigerian Universities. A survey research design was employed. Copies of a research questionnaire were made and administered to eighty (80) accounting students in selected Nigerian Universities who embarked on Students’ Industrial Work Experience Scheme (SIWES). Their expectations were juxtaposed with their actual experiences gleaned from the Industrial Work Experience. The data for the purpose of this study was analyzed using independent sample t-test. A total of fifteen (15) male and forty four (44) female students responded to the survey. This resulted in a response rate of 73.8 per cent. The results of this study indicated that there was no significant difference in the expectation of male and female undergraduate accounting students that the internship experience will be able to prepare them for an accounting career in the future, impart relevant knowledge, relate theories to work environment, enhance knowledge in financial accounting, cost accounting, accounting software, and general practice of accounting; prepare financial statements, interpret financial statements, develop problem solving skills, communication skills, and interpersonal skills; improve personal confidence and self-esteem, increase exposure to latest technology in the workplace, build rapport and networks, provide earnings, job experience, provide information and experience to choose career path. Furthermore, findings from the survey showed that there were differences in the expectations of students and their actual experiences with respect to their ability to relate theories to work environment, enhance knowledge in financial accounting, cost accounting, accounting software and exposure to latest technology in the workplace. The study only examined the perceptions of students from two Universities in South-West Nigeria. The research instrument used in this study can be administered to undergraduate accounting students in other universities in Nigeria. The Industrial Work Experience Scheme for undergraduate accounting students should be highly encouraged by tertiary institutions in Nigeria. This will ultimately make the students well prepared for a career in accounting.

Keywords: gender, expectations, actual experiences, industrial work experience

Procedia PDF Downloads 243

Authors: Gevorgianiene Violeta, Sumskiene Egle

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Background. Child removal is a profound and life-altering measure that significantly impacts both children and their mothers. Unfortunately, mothers with intellectual disabilities are disproportionately affected by the removal of their children. This action is often taken due to concerns about the mother's perceived inability to care for the child, instances of abuse and neglect, or struggles with addiction. In many cases, the failure to meet society's standards of a "good mother" is seen as a deviation from conventional norms of femininity and motherhood. From an institutional perspective, separating a child from their mother is sometimes viewed as a step toward restoring justice or doing what is considered "right." In another light, this act of child removal can be seen as the removal of a mother from her child, an attempt to shield society from the complexities and fears associated with motherhood for women with disabilities. This separation can be likened to the Greek legend of the Minotaur, a fearsome beast confined within an impenetrable labyrinth. By reimagining this legend, we can see the social fears surrounding 'mothering with intellectual disability' as deeply sealed within an unreachable place. The Aim of this Presentation. Our goal with this presentation is to draw from our research and the metaphors found in the Greek legend to delve into the profound challenges faced by mothers with intellectual disabilities in raising their children. These challenges often become entangled within an insurmountable labyrinth, including navigating complex institutional bureaucracies, enduring persistent doubts cast upon their maternal competencies, battling unfavorable societal narratives, and struggling to retain custody of their children. Coupled with limited social support networks, these challenges frequently lead to situations resulting in maternal failure and, ultimately, child removal. On a broader scale, this separation of a child from their mother symbolizes society’s collective avoidance of confronting the issue of 'mothering with disability,' which can only be effectively addressed through united efforts. Conclusion. Just as in the labyrinth of the Minotaur legend, the struggles faced by mothers with disabilities in their pursuit of retaining their children reveal the need for a metaphorical 'string of Ariadne.' This string symbolizes the support offered by social service providers, communities, and the loved ones these women often dream of but rarely encounter in their lives.

Keywords: motherhood, disability, child removal, support.

Procedia PDF Downloads 45

Authors: Valentina V. Goftman, Vladislav A. Pankratov, Alexey V. Markin, Tangi Aubert, Zeger Hens, Sarah De Saeger, Irina Yu. Goryacheva

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The most important requirements for biochemical applicability of quantum dots (QDs) are: 1) the surface cap should render intact or improved optical properties; 2) mono-dispersion and good stability in aqueous phase in a wide range of pH and ionic strength values; 3) presence of functional groups, available for bioconjugation; 4) minimal impact from the environment on the QDs’ properties and, vice versa, minimal influence of the QDs’ components on the environment; and 5) stability against chemical/biochemical/physical influence. The latter is especially important for in vitro and in vivo applications. For example, some physical intracellular delivery strategies (e.g., electroporation) imply a rapid high-voltage electric field impulse in order to temporarily generate hydrophilic pores in the cell plasma membrane, necessary for the passive transportation of QDs into the cell. In this regard, it is interesting to investigate how different capping layers, which can provide high stability and sufficient fluorescent properties of QDs in a water solution, behave under these abnormal conditions. In this contribution, hydrophobic core-shell CdSe/CdS/CdZnS/ZnS QDs (λem=600 nm), produced by means of the Successive Ion Layer Adsorption and Reaction (SILAR) technique, were transferred to a water solution using two of the most commonly used methods: (i) encapsulation in an amphiphilic brush polymer based on poly(maleic anhydride-alt-1-octadecene) (PMAO) modified with polyethylene glycol (PEG) chains and (ii) silica covering. Polymer encapsulation preserves the initial ligands on the QDs’ surface owing to the hydrophobic attraction between the hydrophobic groups of the amphiphilic molecules and the surface hydrophobic groups of the QDs. This covering process allows maintaining the initial fluorescent properties, but it leads to a considerable increase of the QDs’ size. However, covering with a silica shell, by means of the reverse microemulsion method, allows maintaining both size and fluorescent properties of the initial QDs. The obtained water solutions of polymer covered and silica-coated QDs in three different concentrations were exposed to a low-voltage electric field for a short time and the fluorescent properties were investigated. It is shown that the PMAO-PEG polymer acquires some additional charges in the presence of the electric field, which causes repulsion between the polymer and the QDs’ surface. This process destroys the homogeneity of the whole amphiphilic shell and it dramatically decreases the fluorescent properties (dropping to 10% from its initial value) because of the direct contact of the QDs with the strongly oxidative environment (water). In contrast, a silica shell possesses dielectric properties which allow retaining 90% of its initial fluorescence intensity, even after a longer electric impact. Thus, silica shells are clearly a preferable covering for bio-application of QDs, because – besides the high uniform morphology, controlled size and biocompatibility – it allows protecting QDs from oxidation, even under the influence of an electric field.

Keywords: electric field, polymer coating, quantum dots, silica covering, stability

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Authors: Ntloyalefu Justinah, Fumane Khanare

Abstract:

English learning has been found as one of the prevalent areas of difficulty for Deaf learners. However, studies conducted indicated that this challenge experienced by Deaf learners is an upsetting concern globally as is blamed and hampered by various reasons such as the way English is taught at schools, lack of teachers ' skills and knowledge, therefore, impact negatively on their academic performance. Despite any difficulty in English learning, this language is considered nowadays as the key tool to an educational and occupational career especially in Lesotho. This paper, therefore, intends to contribute to the existing literature by providing the views of Lesotho English teachers, which focuses on how effectively Universal design for learning can be implemented to enhance the academic performance of Deaf learners in context of the English language classroom. The purpose of this study sought to explore the use of universal design for learning (UDL) to support Deaf learners in Lesotho Secondary schools. The present study is informed by interpretative paradigm and situated within a qualitative research approach. Ten participating English teachers from two inclusive schools were purposefully selected and telephonically interviewed to generate data for this study. The data were thematically analysed. The findings indicated that even though UDL is identified as highly proficient and promotes flexibility in teaching methods teachers reflect limited knowledge of the UDL approach. The findings further showed that UDL ensures education for all learners, including marginalised groups, such as learners with disabilities through different teaching strategies. This means that the findings signify the effective use of UDL for the better performance of the English language by Deaf learners (DLs). This aligns with literature that shows mobilizing English teachers as assets help DLs to be engaged and have control in their communities by defining and solving problems using their resources and connections to other networks for asset and exchange. The study, therefore, concludes that teachers acknowledge that even though they assume to be knowledgeable about the definition of UDL, they have a limited practice of the approach, thus they need to be equipped with some techniques and skills to apply for supporting the performance of DLs by using UDL approach in their English teaching. The researchers recommend the awareness of UDL principles by the ministry of Education and Training and teachers training Universities, as well as teachers training colleges, for them to include it in their curricula so that teachers could be properly trained on how to apply it in their teaching effectively

Keywords: deaf learners, Lesotho, support learning, universal design for learning

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