Search results for: entrepreneurial capabilities

Authors: Mokgadi Malatji, Tebogo Mothiba, Rambelani Malema

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Absenteeism is a global problem in the working force and this is no exception in the nursing profession. A lot of attention has been drawn to factors that contribute to absenteeism however little attention has been placed on the effects of absenteeism on the remaining workers/nurses being left behind in the workplace by their colleagues. Nurses absent themselves leaving behind their colleagues to do their work. Nurses who are committed to their work often find themselves working under strenuous conditions due to inadequate staff. These may lead to poor patient care provision, nurses feeling overworked and sick due to the increased workload. The purpose of this study was to investigate the effects of absenteeism on nurses that remained at work at Mankweng Hospital in the Capricorn District, Limpopo Province. A descriptive cross-sectional quantitative research design was conducted to determine if there were any effects of absenteeism on nurses remaining at work. Data collection was done using structured questionnaires. The respondents (n=107), consisted of different categories of registered nurses (professional nurses (n=43), auxiliary nurses (n=40) and staff nurses (n=24)) who participated in this study. The findings indicated that most nurses (76, 6%) are demotivated and they struggle with completion of duties when their colleagues are absent. Patient care that nurses provided when their colleagues were absent was of poor quality as set standards and principles were not adhered to. Individualized patient care was not being implemented due to absenteeism. This simply implies that routine work is being done to cover basic duties. Most nurses (74, 8%) believed that favoritism and lack of appreciation of nurse’s skills and capabilities are being displayed by managers and that this contributes to absenteeism. Nurses who are loyal sacrifice their time and work overtime for absent colleagues and this led to fatigue and stress. From the study findings, it is recommended that nurses be trained frequently to upgrade their studies to motivate them to work. The government can provide this training to improve their skills as this will motivate nurses to work harder and be committed to their work. Training can be offered after a stipulated period. For example, after every five years, a nurse can be provided with a new skill. Team building events must be encouraged for the whole hospital to motivate staff. In conclusion, the study revealed that absenteeism poses detrimental effects on nurses, the hospital and patients. More and more nurses end up changing workplace due to these effects.

Keywords: absenteeism, effects, nurses, remaining at work

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Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau

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Background: Preparing in the stress field (SF) is, increasingly, a concern for doctors of different specialties. Aims: The aim was to evaluate the importance of an e-learning program for doctors postgraduate courses, in SF. Methods: Doctors (n= 40 male, 40 female) of different specialties and ages (31-71 years), who attended postgraduate courses in SF, voluntarily responded to a questionnaire that included the following themes: Importance of SF courses for specialty practiced by each respondent doctor (using visual analogue scale, VAS); What SF themes would be indicated as e-learning (EL); Preferred form of SF information assimilation: Classical lectures (CL), EL or a combination of these methods (CL+EL); Which information on the SF course are facilitated by EL model versus CL; In their view which are the first four advantages and the first four disadvantages of EL compared to CL, for SF. Results: To most respondents, the SF courses are important for the specialty they practiced (VAS by an average of 4). The SF themes suggested to be done as EL were: Stress mechanisms; stress factor models for different medical specialties; stress assessment methods; primary stress management methods for different specialties. Preferred form of information assimilation was CL+EL. Aspects of the course facilitated by EL versus CL model: Active reading of theoretical information, with fast access to keywords details; watching documentaries in everyone's favorite order; practice through tests and the rapid control of results. The first four EL advantages, mentioned for SF were: Autonomy in managing the time allocated to the study; saving time for traveling to the venue; the ability to read information in various contexts of time and space; communication with colleagues, in good times for everyone. The first three EL disadvantages, mentioned for SF were: It decreases capabilities for group discussion and mobilization for active participation; EL information accession may depend on electrical source or/and Internet; learning slowdown can appear, by temptation of postponing the implementation. Answering questions was partially influenced by the respondent's age and genre. Conclusions: 1) Post-graduate courses in SF are of interest to doctors of different specialties. 2) The majority of participating doctors preferred EL, but combined with CL (CL+EL). 3) Preference for EL was manifested mainly by young or middle age men doctors. 4) It is important to balance the proper formula for chosen EL, to be the most efficient, interesting, useful and agreeable.

Keywords: stress field, doctors’ postgraduate courses, classical lectures, e-learning lecture

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Authors: Markus Meyer, Bastian Maucher, Rolf Witzmann

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The ever increasing amount of distributed generation in low voltage distribution grids (mainly PV and micro-CHP) can lead to reverse load flows from low to medium/high voltage levels at times of high feed-in. Reverse load flow leads to rising voltages that may even exceed the limits specified in the grid codes. Furthermore, the share of electrical loads connected to low voltage distribution grids via switched power supplies continuously increases. In combination with inverter-based feed-in, this results in high harmonic levels reducing overall power quality. Especially high levels of third-order harmonic currents can lead to neutral conductor overload, which is even more critical if lines with reduced neutral conductor section areas are used. This paper illustrates a possible concept for smart grids in order to increase the feed-in capacity, improve power quality and to ensure safe operation of low voltage distribution grids at all times. The key feature of the concept is a hierarchically structured control strategy that is run on a superordinated controller, which is connected to several distributed grid analyzers and inverters via broad band powerline (BPL). The strategy is devised to ensure both quick response time as well as the technically and economically reasonable use of the available inverters in the grid (PV-inverters, batteries, stepless line voltage regulators). These inverters are provided with standard features for voltage control, e.g. voltage dependent reactive power control. In addition they can receive reactive power set points transmitted by the superordinated controller. To further improve power quality, the inverters are capable of active harmonic filtering, as well as voltage balancing, whereas the latter is primarily done by the stepless line voltage regulators. By additionally connecting the superordinated controller to the control center of the grid operator, supervisory control and data acquisition capabilities for the low voltage distribution grid are enabled, which allows easy monitoring and manual input. Such a low voltage distribution grid can also be used as a virtual power plant.

Keywords: distributed generation, distribution grid, power quality, smart grid, virtual power plant, voltage control

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Authors: Carin Lindskog

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Introduction: Long-term success requires an organizational balance between continuity (exploitation) and change (exploration). The problem of balancing exploitation and exploration is a common issue in studies of organizational learning. In order to better face the tough competition in the face of changes, organizations need to exploit their current business and explore new business fields by developing new capabilities. The purpose of this work in progress is to develop a conceptual framework to shed light on the relevance of 'learning activities', i.e., exploitation and exploration, on different levels. The research questions that will be addressed are as follows: What sort of learning activities are found in the Business Process Management (BPM) field? How can these activities be linked to the individual level, group, level, and organizational level? In the work, a literature review will first be conducted. This review will explore the status of learning activities in the BPM field. An outcome from the literature review will be a conceptual framework of learning activities based on the included publications. The learning activities will be categorized to focus on the categories exploitation, exploration or both and into the levels of individual, group, and organization. The proposed conceptual framework will be a valuable tool for analyzing the research field as well as identification of future research directions. Related Work: BPM has increased in popularity as a way of working to strengthen the quality of the work and meet the demands of efficiency. Due to the increase in BPM popularity, more and more organizations reporting on BPM failure. One reason for this is the lack of knowledge about the extended scope of BPM to other business contexts that include, for example, more creative business fields. Yet another reason for the failures are the fact of the employees’ are resistant to changes. The learning process in an organization is an ongoing cycle of reflection and action and is a process that can be initiated, developed and practiced. Furthermore, organizational learning is multilevel; therefore the theory of organizational learning needs to consider the individual, the group, and the organization level. Learning happens over time and across levels, but it also creates a tension between incorporating new learning (feed-forward) and exploiting or using what has already been learned (feedback). Through feed-forward processes, new ideas and actions move from the individual to the group to the organization level. At the same time, what has already been learned feeds back from the organization to a group to an individual and has an impact on how people act and think.

Keywords: business process management, exploitation, exploration, learning activities

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Authors: Sebastian Töpfer, Marta Gilaberte Basset, Jorge Fuenzalida, Fabian Steinlechner, Juan P. Torres, Markus Gräfe

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This work introduces a combination of digital phase-shifting holography with a non-linear interferometer using undetected photons. Non-linear interferometers can be used in combination with a measurement scheme called quantum imaging with undetected photons, which allows for the separation of the wavelengths used for sampling an object and detecting it in the imaging sensor. This method recently faced increasing attention, as it allows to use of exotic wavelengths (e.g., mid-infrared, ultraviolet) for object interaction while at the same time keeping the detection in spectral areas with highly developed, comparable low-cost imaging sensors. The object information, including its transmission and phase influence, is recorded in the form of an interferometric pattern. To collect these, this work combines the method of quantum imaging with undetected photons with digital phase-shifting holography with a minimal sampling of the interference. With this, the quantum imaging scheme gets extended in its measurement capabilities and brings it one step closer to application. Quantum imaging with undetected photons uses correlated photons generated by spontaneous parametric down-conversion in a non-linear interferometer to create indistinguishable photon pairs, which leads to an effect called induced coherence without induced emission. Placing an object inside changes the interferometric pattern depending on the object’s properties. Digital phase-shifting holography records multiple images of the interference with determined phase shifts to reconstruct the complete interference shape, which can afterward be used to analyze the changes introduced by the object and conclude its properties. An extensive characterization of this method was done using a proof-of-principle setup. The measured spatial resolution, phase accuracy, and transmission accuracy are compared for different combinations of camera exposure times and the number of interference sampling steps. The current limits of this method are shown to allow further improvements. To summarize, this work presents an alternative holographic measurement method using non-linear interferometers in combination with quantum imaging to enable new ways of measuring and motivating continuing research.

Keywords: digital holography, quantum imaging, quantum holography, quantum metrology

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Authors: Mohd Javaid, Shahbaz Khan, Abid Haleem

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Purpose: Large numbers of 3D printing technologies are now available for sophisticated applications in different fields. Additive manufacturing has established its dominance in design, development, and customisation of the product. In the era of developing technologies, there is a need to identify the appropriate technology for different application. In order to fulfil this need, two widely used printing technologies such as Fused Deposition Modeling (FDM), and Binding-Jet 3D Printing are compared for effective utilisation in the current scenario for different applications. Methodology: Systematic literature review conducted for both technologies with applications and associated factors enabling for the same. Appropriate MCDM tool is used to compare critical factors for both the technologies. Findings: Both technologies have their potential and capabilities to provide better direction to the industry. Additionally, this paper is helpful to develop a decision support system for the proper selection of technologies according to their continuum of applications and associated research and development capability. The vital issue is raw materials, and research-based material development is key to the sustainability of the developed technologies. FDM is a low-cost technology which provides high strength product as compared to binding jet technology. Researcher and companies can take benefits of this study to achieve the required applications in lesser resources. Limitations: Study has undertaken the comparison with the opinion of experts, which may not always be free from bias, and some own limitations of each technology. Originality: Comparison between these technologies will help to identify best-suited technology as per the customer requirements. It also provides development in this different field as per their extensive capability where these technologies can be successfully adopted. Conclusion: FDM and binding jet technology play an active role in industrial development. These help to assist the customisation and production of personalised parts cost-effectively. So, there is a need to understand how these technologies can provide these developments rapidly. These technologies help in easy changes or in making revised versions of the product, which is not easily possible in the conventional manufacturing system. High machine cost, the requirement of skilled human resources, low surface finish, and mechanical strength of product and material changing option is the main limitation of this technology. However, these limitations vary from technology to technology. In the future, these technologies are to be commercially viable for efficient usage in direct manufacturing of varied parts.

Keywords: 3D printing, comparison, fused deposition modeling, FDM, binding jet technology

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Authors: Monika Ksiezopolska-Gocalska, Pawel Albrycht, Robert Holyst

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Surface Enhanced Raman Spectroscopy (SERS) is a technique used to analyze very low concentrations of substances in solutions, even in aqueous solutions - which is its advantage over IR. This technique can be used in the pharmacy (to check the purity of products); forensics (whether at a crime scene there were any illegal substances); or medicine (serving as a medical test) and lots more. Due to the high potential of this technique, its increasing popularity in analytical laboratories, and simultaneously - the absence of appropriate platforms enhancing the SERS signal (crucial to observe the Raman effect at low analyte concentration in solutions (1 ppm)), we decided to invent our own SERS platforms. As an enhancing layer, we have chosen gold and silver nanoparticles, because these two have the best SERS properties, and each has an affinity for the other kind of particles, which increases the range of research capabilities. The next step was to commercialize them, which resulted in the creation of the company ‘SERSitive.eu’ focusing on production of highly sensitive (Ef = 10⁵ – 10⁶), homogeneous and reproducible (70 - 80%) substrates. SERStive SERS substrates are made using the electrodeposition of silver or silver-gold nanoparticles technique. Thanks to a very detailed analysis of data based on studies optimizing such parameters as deposition time, temperature of the reaction solution, applied potential, used reducer, or reagent concentrations using a standardized compound - p-mercaptobenzoic acid (PMBA) at a concentration of 10⁻⁶ M, we have developed a high-performance process for depositing precious metal nanoparticles on the surface of ITO glass. In order to check a quality of the SERSitive platforms, we examined the wide range of the chemical compounds and the biological substances. Apart from analytes that have great affinity to the metal surfaces (e.g. PMBA) we obtained very good results for those fitting less the SERS measurements. Successfully we received intensive, and what’s more important - very repetitive spectra for; amino acids (phenyloalanine, 10⁻³ M), drugs (amphetamine, 10⁻⁴ M), designer drugs (cathinone derivatives, 10⁻³ M), medicines and ending with bacteria (Listeria, Salmonella, Escherichia coli) and fungi.

Keywords: nanoparticles, Raman spectroscopy, SERS, SERS applications, SERS substrates, SERSitive

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Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

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In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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Authors: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

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Authors: Francisco Julio Batle Lorente

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The present paper aims at presenting a new category of role for academia: proactive creator/promoter of communities of practice in emerging areas of innovation. It is based in research among practitioners in three different areas: social entrepreneurship, alumni engaged in entrepreneurship and innovation, and digital nomads. The concept of CoP is related to an intentionally created space to share experiences and collectively reflect on the cases arising from practice. Such an endeavour is not contemplated in the literature on academic roles in an explicit way. The goal of the paper is providing a framework for this function and throw some light on the perception and priorities of members of emerging communities (78 alumni, 154 social entrepreneurs, and 231 digital nomads) regarding community, learning, engagement, and networking, areas in which the university can help and, by doing so, contributing to signal the emerging area and creating new opportunities for the academia. The research methodology was based in Survey research. It is a specific type of field study that involves the collection of data from a sample of elements drawn from a well-defined population through the use of a questionnaire. It was considered that survey research might be valuable to the present project and help outline the utility of various study designs and future projects with the emerging communities that are the object of the investigation. Open questions were used for different topics, as well as critical incident technique. It was used a standard technique for survey sampling and questionnaire design. Finally, it was defined a procedure for pretesting questionnaires and for data collection. The questionnaire was channelled by means of google forms. The results indicate that the members of emerging, innovative CoPs and learning such the ones that were selected for this investigation lack cohesion, inspiration, networking, opportunities for creation of social capital, opportunities for collaboration beyond their existing and close network. The opportunity that arises for the academia from proactively helping articulate CoP (and Communities of learning) are related to key elements of any CoP/ CoL: community construction approaches, technological infrastructure, benefits, participation issues and urgent challenges, trust, networking, technical ability/training/development and collaboration. Beyond training, other three areas (networking, collaboration and urgent challenges) were the ones in which the contribution of universities to the communities were considered more interesting and workable to practitioners. The analysis of the responses for the open questions related to perception of the universities offer options for terra incognita to be explored for universities (signalling new areas, establishing broader collaborations with research, government, media and corporations, attracting investment). Based on the findings from this research, there is some evidence that CoPs can offer a formal and informal method of professional and interprofessional development for member of any emerging and innovative community and can decrease social and professional isolation. The opportunity that it offers to academia can increase the entrepreneurial and engaged university identity. It also moves to academia into a realm of civic confrontation of present and future challenges in a more proactive way.

Keywords: social innovation, new roles of academia, community of learning, community of practice

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Authors: Aliyu J. Abubakar, Mazlan Hashim, Amin B. Pour

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Exploiting geothermal resources for either power, home heating, Spa, greenhouses, industrial or tourism requires an initial identification of suitable areas. This can be done cost-effectively using remote sensing satellite imagery which has synoptic capabilities of covering large areas in real time and by identifying possible areas of hydrothermal alteration and minerals related to Geothermal systems. Earth features and minerals are known to have unique diagnostic spectral reflectance characteristics that can be used to discriminate them. The focus of this paper is to investigate the applicability of mapping hydrothermal alteration in relation to geothermal systems (thermal springs) at Yankari Park Northeastern Nigeria, using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data for resource exploration. The ASTER Short Wave Infrared (SWIR) bands are used to highlight and discriminate alteration areas by employing sophisticated digital image processing techniques including image transformations and spectral mapping methods. Field verifications are conducted at the Yankari Park using hand held Global Positioning System (GPS) monterra to identify locations of hydrothermal alteration and rock samples obtained at the vicinity and surrounding areas of the ‘Mawulgo’ and ‘Wikki’ thermal springs. X-Ray Diffraction (XRD) results of rock samples obtained from the field validated hydrothermal alteration by the presence of indicator minerals including; Dickite, Kaolinite, Hematite and Quart. The study indicated the applicability of mapping geothermal anomalies for resource exploration in unmapped sparsely vegetated savanna environment characterized by subtle surface manifestations such as thermal springs. The results could have implication for geothermal resource exploration especially at the prefeasibility stages by narrowing targets for comprehensive surveys and in unexplored savanna regions where expensive airborne surveys are unaffordable.

Keywords: geothermal exploration, image enhancement, minerals, spectral mapping

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Authors: Katielly Vianna Polkowski, Rodrigo Denizarte de Oliveira Polkowski, Cristiano Grings Herbert

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The use of nanomaterials in the formulation of polymeric materials modifies their molecular structure, offering an infinite range of possibilities for the development of smart products, being of great importance for science and contemporary industry. Shape memory polymers are generally lightweight, have high shape recovery capabilities, they are easy to process and have properties that can be adapted for a variety of applications. Shape memory materials are active materials that have attracted attention due to their superior damping properties when compared to conventional structural materials. The development of methodologies capable of preparing new materials, which use graphene in their structure, represents technological innovation that transforms low-cost products into advanced materials with high added value. To obtain an improvement in the shape memory effect (SME) of polymeric materials, it is possible to use graphene in its composition containing low concentration by mass of graphene nanoplatelets (GNP), graphene oxide (GO) or other functionalized graphene, via different mixture process. As a result, there was an improvement in the SME, regarding the increase in the values of maximum strain. In addition, the use of graphene contributes to obtaining nanocomposites with superior electrical properties, greater crystallinity, as well as resistance to material degradation. The methodology used in the research is Systematic Review, scientific investigation, gathering relevant studies on influence of nanomaterials on the properties of shape memory polymeric, using the literature database as a source and study methods. In the present study, a systematic reviewwas performed of all papers published from 2014 to 2022 regarding graphene and shape memory polymeric througha search of three databases. This study allows for easy identification of themost relevant fields of study with respect to graphene and shape memory polymeric, as well as the main gaps to beexplored in the literature. The addition of graphene showed improvements in obtaining higher values of maximum deformation of the material, attributed to a possible slip between stacked or agglomerated nanostructures, as well as an increase in stiffness due to the increase in the degree of phase separation that results in a greater amount physical cross-links, referring to the formation of shortrange rigid domains.

Keywords: graphene, shape memory, smart materials, polymers, nanomaterials

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Authors: Madalena Corte-real, João Pedro Nunes, Bernardo Fernandes, Ana Jorge Correira

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This presentation looks, from a sociological perspective, at neighboring practices in the inner city of Lisbon. The capital of Portugal, with half a million inhabitants, inserted in a metropolitan area with almost 2,9 million people, has been in the international spotlight seen as an interesting city to live in and to invest in, especially in the real estate market. This promotion emerged in the context of the financial crisis, where local authorities aimed to make Lisbon a more competitive city, calling for visitors and financial and human capital. Especially in the last decade, Portugal’s capital has been experiencing a significant increase in terms of migration from creative and entrepreneurial exiles to economic and political expats. In this context, the territory under analysis, in particular, is a mixed-used area undergoing rapid transformations in recent years marked by the presence of newcomers and non-nationals as well as social and cultural heterogeneity. It is next to one of the main arteries, considered the most multicultural part of the city, and presented in the press as one of the coolest neighborhoods in Europe. In view of these aspects, this research aims to address key-topics in current urban research: anonymity often related to big cities, socio-spatial attachment to the neighborhood, and the effects of diversity in the everyday relations of residents and shopkeepers. This case-study intends to look at particularities in local regimes differently affected by growing mobility. Against a backdrop of unidimensional generalizations and a tendency to refer to central countries and global cities, it aims to discuss national and local specificities. In methodological terms, the project comprises essentially a qualitative approach that consists of direct observation techniques and ethnographic methods as well semi-structured interviews to residents and local stakeholders whose narratives are subject to content analysis. The paper starts with a characterization of the broader context of the city of Lisbon, followed by territorial specificities regarding socio-spatial development, namely the city’s and the inner-areas morphology as well as the population’s socioeconomic profile. Following the residents and stakeholders’ narratives and practices it will assess the perception and behaviors regarding the representation of the area, relationships and experiences, routines, and sociability. Results point to a significant presence of neighborhood relations and different forms of support, in particular, among the different groups – e.g., old long-time residents, middle-class families, global creative class, and communities of economic migrants. Fieldwork reveals low levels of place-attachment although some residents refer, presently, high levels of satisfaction. Engagement with living space, this case-study suggests, reveals the social construction and lived the experience of neighboring by different groups, but also the way different and contrasting visions and desires are articulated to the profound urban, cultural and political changes that permeate the area.

Keywords: diversity, lisbon, neighboring and neighborhood, place-attachment

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Authors: Milena Nanova, Radul Shishkov, Damyan Damov, Martin Georgiev

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This research paper presents an in-depth exploration of the use of generative design in urban residential architecture, with a dual focus on aligning aesthetic values with legal and environmental constraints. The study aims to demonstrate how generative design methodologies can innovate residential building designs that are not only legally compliant and environmentally conscious but also aesthetically compelling. At the core of our research is a specially developed generative design framework tailored for urban residential settings. This framework employs computational algorithms to produce diverse design solutions, meticulously balancing aesthetic appeal with practical considerations. By integrating site-specific features, urban legal restrictions, and environmental factors, our approach generates designs that resonate with the unique character of urban landscapes while adhering to regulatory frameworks. The paper places emphasis on algorithmic implementation of the logical constraint and intricacies in residential architecture by exploring the potential of generative design to create visually engaging and contextually harmonious structures. This exploration also contains an analysis of how these designs align with legal building parameters, showcasing the potential for creative solutions within the confines of urban building regulations. Concurrently, our methodology integrates functional, economic, and environmental factors. We investigate how generative design can be utilized to optimize buildings' performance, considering them, aiming to achieve a symbiotic relationship between the built environment and its natural surroundings. Through a blend of theoretical research and practical case studies, this research highlights the multifaceted capabilities of generative design and demonstrates practical applications of our framework. Our findings illustrate the rich possibilities that arise from an algorithmic design approach in the context of a vibrant urban landscape. This study contributes an alternative perspective to residential architecture, suggesting that the future of urban development lies in embracing the complex interplay between computational design innovation, regulatory adherence, and environmental responsibility.

Keywords: generative design, computational design, parametric design, algorithmic modeling

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Yasser Sanad, Thu Trang Dao

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Introduction: Implementing the One Health (OH) approach requires an integrated, interdisciplinary, and cross-sectoral methodology. OH is a key tool for developing and implementing programs and projects and includes developing ambitious policies that consider the common needs and benefits of human, animal, plant, and ecosystem health. OH helps humanity readjust its path to environmentally friendly and impartial sustainability. As co-leader of the Global Health Security Agenda’s Zoonotic Disease Action Package, Vietnam pioneered a strong OH approach to effectively address early waves of the COVID-19 outbreak in-country. Context and Aim: The repeated surges in COVID-19 in Vietnam challenged the capabilities of the national system and disclosed the gaps in multi-sectoral coordination and resilience. To address this, FHI 360 advocated for the standardization of the OH platform by government actors to increase the resiliency of the system during and post COVID-19. Methods: FHI 360 coordinated technical resources to develop and implement evidence-based OH policies, promoting high-level policy dialogue between the Ministries of Health, Agriculture, and the Environment, and policy research to inform developed policies and frameworks. Through discussions, an OH-building Partnership (OHP) was formed, linking climate change, the environment, and human and animal health. Findings: The OHP Framework created a favorable policy environment within and between sectors, as well as between governments and international health security partners. It also promoted strategic dialogue, resource mobilization, policy advocacy, and integration of international systems with National Steering Committees to ensure accountability and emphasize national ownership. Innovative contribution to policy, practice and/or research: OHP was an effective evidence-based research-to-policy platform linking to the National One Health Strategic Plan (2021-2025). Collectively they serve as a national framework for the implementation and monitoring of OH activities. Through the adoption of policies and plans, the risk of zoonotic pathogens, environmental agent spillover, and antimicrobial resistance can be minimized through strengthening multi-sectoral OH collaboration for health security.

Keywords: one health, national policies, health security, COVID-19, Vietnam

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Authors: Emanuela Chiarella, Clelia Nisticò, Nicola Lombardo, Giovanna Lucia Piazzetta, Nadia Lobello, Maria Mesuraca

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Killian’s Antrochoanal Polyp is a benign lesion of the maxillary sinus characterized by unilateral nasal obstruction, pus discharge, and headache. It affects, more commonly children and young adults. Although its etiology still remains unclear, chronic inflammation, autoreactivity, allergies, and viral infections are strongly associated with its formation and development, resulting in nasal tissue remodeling. We aimed to investigate the stem cells components which reside in this pathological tissue. In particular, we adopted a protocol for the isolation and culturing of mesenchymal stem cells from surgical biopsies of three Killian nasal polyp patients (KNP-MSCs) as well as from their healthy nasal tissue (HNT-MSCs) that were used as controls. The immunophenotype profile of HNT-MSCs and KNP-MSCs was more similar, with a marked positivity for CD73, CD90, and CD105 expression, while being negative for CD34 and CD14 haematopoietic genes. Cell proliferation assay showed that KNP-MSCs had a replicative disadvantage compared to HNT-MSCs, as evidenced by the significantly lower number of cells in the S-phase of the cell cycle. KNP-MSCs also took longer to close a wound than HNT-MSCs, indicating a partial epithelial phenotype in which low levels of ICAM-1 mRNA and a significant increase in E-CAD transcript were detectable. Subsequently, the differentiation potential of both MSCs populations was analyzed by inducing osteoblastic or adipocyte differentiation for up to 20 days. KNP-MSCs showed the ability to differentiate into osteoblasts, although ALP activity as well as the number and size of calcium deposits were lower than osteogenic induced-HNT-MSCs. Also, mRNA levels of osteoblastic marker genes (OCN, OPN, OSX, RUNX2) resulted lower compared to control cell population. Instead, the analysis of the adipogenic differentiation potential showed a similar behavior between KNP-MSCs and HNT-MSCs considering that the amount of lipid droplets, the expression of adipocyte-specific genes (FABP4, AdipoQ, PPARγ2, LPL) and the content of triacylglycerols were almost overlapping. Taken together, these results first demonstrated that Killian's nasal polyp is a source of mesenchymal stem cells with self-renewal and multi-differentiative capabilities.

Keywords: Mesenchymal stem cells, adipogenic differentiation, osteogenic differentiation, EMT

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Authors: Daniel John Avutia

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Solar Photovoltaic (PV) development is reliant on the sunlight hours available in a particular region to generate electricity. A potential area is assessed through its inherent solar radiation intensity measured in watts per square meter. Solar energy development involves the feasibility, design, construction, operation and maintenance of the relevant infrastructure, but this paper will focus on the design and construction aspects. Africa and Australasia have the longest sunlight hours per day and the highest solar radiation per square meter, 7 sunlight hours/day and 5 kWh/day respectively. Solar PV support configurations consist of fixed-tilt support and tracker system structures, the differentiation being that the latter was introduced to improve the power generation efficiency of the former due to the sun tracking movement capabilities. The installation of Solar PV foundations involves rammed piles, drilling/grout piles and shallow raft reinforced concrete structures. This paper presents a case study of 2 solar PV projects in Africa and Australia, discussing the foundation design consideration and associated construction cost implications of the selected foundations systems. Solar PV foundations represent up to one fifth of the civil works costs in a project. Therefore, the selection of the most structurally sound and feasible foundation for the prevailing ground conditions is critical towards solar PV development. The design wind speed measured by anemometers govern the pile embedment depth for rammed and drill/grout foundation systems. The lateral pile deflection and vertical pull out resistance of piles increase proportionally with the embedment depth for uniform pile geometry and geology. The pile driving rate may also be used to anticipate the lateral resistance and skin friction restraining the pile. Rammed pile foundations are the most structurally suitable due to the pile skin friction and ease of installation in various geological conditions. The competitiveness of solar PV projects within the renewable energy mix is governed by lowering capital expenditure, improving power generation efficiency and power storage technological advances. The power generation reliability and efficiency are areas for further research within the renewable energy niche.

Keywords: design, foundations, piles, solar

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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

Procedia PDF Downloads 151

Authors: David Krejci, Tony Schönherr, Quirin Koch, Valentin Hugonnaud, Lou Grimaud, Alexander Reissner, Bernhard Seifert

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In 2018 the NANO thruster became the first Field Emission Electric Propulsion (FEEP) system ever to be verified in space in an In-Orbit Demonstration mission conducted together with Fotec. Since then, 160 additional ENPULSION NANO propulsion systems have been deployed in orbit on 73 different spacecraft across multiple customers and missions. These missions included a variety of different satellite bus sizes ranging from 3U Cubesats to >100kg buses, and different orbits in Low Earth Orbit and Geostationary Earth orbit, providing an abundance of on orbit data for statistical analysis. This large-scale industrialization and flight heritage allows for a holistic way of gathering data from testing, integration and operational phases, deriving lessons learnt over a variety of different mission types, operator approaches, use cases and environments. Based on these lessons learnt a new generation of propulsion systems is developed, addressing key findings from the large NANO heritage and adding new capabilities, including increased resilience, thrust vector steering and increased power and thrust level. Some of these successor products have already been validated in orbit, including the MICRO R3 and the NANO AR3. While the MICRO R3 features increased power and thrust level, the NANO AR3 is a successor of the heritage NANO thruster with added thrust vectoring capability. 5 NANO AR3 have been launched to date on two different spacecraft. This work presents flight telemetry data of ENPULSION NANO systems and onorbit statistical data of the ENPULSION NANO as well as lessons learnt during onorbit operations, customer assembly, integration and testing support and ground test campaigns conducted at different facilities. We discuss how transfer of lessons learnt and operational improvement across independent missions across customers has been accomplished. Building on these learnings and exhaustive heritage, we present the design of the new generation of propulsion systems that increase the power and thrust level of FEEP systems to address larger spacecraft buses.

Keywords: FEEP, field emission electric propulsion, electric propulsion, flight heritage

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

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Authors: Masome Moeni, Roya Abedizadeh, Elham Aram, Hamid Sadeghi-Abandansari, Davood Sabour, Robert Menzel, Ali Hassanpour

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Significant number of studies and preclinical research in formulation of cancer nano-pharmaceutics have led to an improvement in cancer care. Nonetheless, the antineoplastic agents have ‘failed to live up to its promise’ since their clinical performance is moderately low. For almost ninety years, iron oxide nanoparticles (IONPS) have managed to keep its reputation in clinical application due to their low toxicity, versatility and multi-modal capabilities. Drug Administration approved utilization of IONPs for diagnosis of cancer as contrast media in magnetic resonance imaging, as heat mediator in magnetic hyperthermia and for the treatment of iron deficiency. Furthermore, IONPs have high drug-loading capacity, which makes them good candidates as therapeutic agent transporters. There are yet challenges to overcome for successful clinical application of IONPs, including stability of drug and poor delivery, which might lead to (i) drug resistance, (ii) shorter blood circulation time, and (iii) rapid elimination and adverse side effects from the system. In this study, highly stable and super paramagnetic IONPs were prepared for efficient and targeted drug delivery in cancer treatment. The synthesis procedure was briefly involved the production of IONPs via co-precipitation followed by coating with tetraethyl orthosilicate and 3-aminopropylethoxysilane and grafting with folic acid for stability targeted purposes and controlled drug release. Physiochemical and morphological properties of modified IONPs were characterised using different analytical techniques. The resultant IONPs exhibited clusters of 10 nm spherical shape crystals with less than 100 nm size suitable for drug delivery. The functionalized IONP showed mesoporous features, high stability, dispersibility and crystallinity. Subsequently, the functionalized IONPs were successfully loaded with oxaliplatin, a chemotherapeutic agent, for a controlled drug release in an actively targeting cancer cells. FT-IR observations confirmed presence of oxaliplatin functional groups, while ICP-MS results verified the drug loading was ~ 1.3%.

Keywords: cancer treatment, chemotherapeutic agent, drug delivery, iron oxide, multi-functional nanoparticle

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Authors: Panwad Wongthong, Thanan Apivantanaporn, Sutthiwan Amattayakul

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Nature-based tourism is one of the fastest growing industries that can bring in economic benefits, improve quality of life and promote conservation of biodiversity and habitats. As tourism develops, substantial socio-economic and environmental costs become more explicit. Particularly in island destinations, the dynamic system and geographical limitations makes the intensity of tourism development and severity of the negative environmental impacts greater. The current contribution of the tourism sector to global climate change is established at approximately 5% of global anthropogenic CO2 emissions. In all scenarios, tourism is anticipated to grow substantially and to account for an increasingly large share of global greenhouse gas emissions. This has prompted an urgent call for more sustainable alternatives. This study selected a small island of Koh Mak in Thailand as a case study because of its reputation of being laid back, family oriented and rich in biodiversity. Importantly, it is a test platform for low carbon tourism development project supported by the Designated Areas for Sustainable Tourism Administration (DASTA) in collaboration with the Institute for Small and Medium Enterprises Development (ISMED). The study explores strategies for low carbon tourism management and assesses challenges and opportunities for Koh Mak to become a low carbon tourism destination. The goal is to identify suitable management approaches applicable for Koh Mak which may then be adapted to other small islands in Thailand and the region. Interventions/initiatives to increase energy efficiency in hotels and resorts; cut carbon emissions; reduce impacts on the environment; and promote conservation will be analyzed. Ways toward long-term sustainability of climate-friendly tourism will be recommended. Recognizing the importance of multi-stakeholder involvement in the tourism sector, findings from this study can reward Koh Mak tourism industry with a triple-win: cost savings and compliance with higher standards/markets; less waste, air emissions and effluents; and better capabilities of change, motivation of business owners, staff, tourists as well as residents. The consideration of climate change issues in the planning and implementation of tourism development is of great significance to protect the tourism sector from negative impacts.

Keywords: climate change, CO2 emissions, low carbon tourism, sustainable tourism management

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Authors: Przemysław Tomczyk, Dagmara Plata-Alf, Piotr Kwiatek

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Literature review is indispensable in research. One of the key techniques used in it is bibliometric analysis, where one of the methods is science mapping. The classic approach that dominates today in this area consists of mapping areas, keywords, terms, authors, or citations. This approach is also used in relation to the review of literature in the field of marketing. The development of technology has resulted in the fact that researchers and practitioners use the capabilities of software available on the market for this purpose. The use of science mapping software tools (e.g., VOSviewer, SciMAT, Pajek) in recent publications involves the implementation of a literature review, and it is useful in areas with a relatively high number of publications. Despite this well-grounded science mapping approach having been applied in the literature reviews, performing them is a painstaking task, especially if authors would like to draw precise conclusions about the studied literature and uncover potential research gaps. The aim of this article is to identify to what extent a new approach to science mapping, variable mapping, takes advantage of the classic science mapping approach in terms of research problem formulation and content/thematic analysis for literature reviews. To perform the analysis, a set of 5 articles on customer ideation was chosen. Next, the analysis of key words mapping results in VOSviewer science mapping software was performed and compared with the variable map prepared manually on the same articles. Seven independent expert judges (management scientists on different levels of expertise) assessed the usability of both the stage of formulating, the research problem, and content/thematic analysis. The results show the advantage of variable mapping in the formulation of the research problem and thematic/content analysis. First, the ability to identify a research gap is clearly visible due to the transparent and comprehensive analysis of the relationships between the variables, not only keywords. Second, the analysis of relationships between variables enables the creation of a story with an indication of the directions of relationships between variables. Demonstrating the advantage of the new approach over the classic one may be a significant step towards developing a new approach to the synthesis of literature and its reviews. Variable mapping seems to allow scientists to build clear and effective models presenting the scientific achievements of a chosen research area in one simple map. Additionally, the development of the software enabling the automation of the variable mapping process on large data sets may be a breakthrough change in the field of conducting literature research.

Keywords: bibliometrics, literature review, science mapping, variable mapping

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Authors: Amal G. Kurian

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The use of mathematical modeling has seen a considerable boost in recent times with the development of many advanced algorithms and mathematical modeling capabilities. The advantages this method has over other methods are that they are much closer to standard physics theories and thus represent a better theoretical model. They take lesser solving time and have the ability to change various parameters for optimization, which is a big advantage, especially in automotive industry. This thesis work focuses on a thorough investigation of the effects of vehicle speed and road roughness on a heavy commercial vehicle ride and structural dynamic responses. Since commercial vehicles are kept in operation continuously for longer periods of time, it is important to study effects of various physical conditions on the vehicle and its user. For this purpose, various experimental as well as simulation methodologies, are adopted ranging from experimental transfer path analysis to various road scenario simulations. To effectively investigate and eliminate several causes of unwanted responses, an efficient and robust technique is needed. Carrying forward this motivation, the present work focuses on the development of a mathematical model of a 4-axle configuration heavy commercial vehicle (HCV) capable of calculating responses of the vehicle on different road PSD inputs and vehicle speeds. Outputs from the model will include response transfer functions and PSDs and wheel forces experienced. A MATLAB code will be developed to implement the objectives in a robust and flexible manner which can be exploited further in a study of responses due to various suspension parameters, loading conditions as well as vehicle dimensions. The thesis work resulted in quantifying the effect of various physical conditions on ride comfort of the vehicle. An increase in discomfort is seen with velocity increase; also the effect of road profiles has a considerable effect on comfort of the driver. Details of dominant modes at each frequency are analysed and mentioned in work. The reduction in ride height or deflection of tire and suspension with loading along with load on each axle is analysed and it is seen that the front axle supports a greater portion of vehicle weight while more of payload weight comes on fourth and third axles. The deflection of the vehicle is seen to be well inside acceptable limits.

Keywords: mathematical modeling, HCV, suspension, ride analysis

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Authors: Chloe Richards, Adrian Delgado Ollero, Yan Delaure, Fiona Regan

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Growing concern about the natural environment has accelerated the search for non-toxic, but at the same time, economically reasonable, antifouling materials. Bioinspired surfaces, due to their nano and micro topographical antifouling capabilities, provide a hopeful approach to the design of novel antifouling surfaces. Biological organisms are known to have highly evolved and complex topographies, demonstrating antifouling potential, i.e. shark skin. Previous studies have examined the antifouling ability of topographic patterns, textures and roughness scales found on natural organisms. One of the mechanisms used to explain the adhesion of cells to a substrate is called attachment point theory. Here, the fouling organism experiences increased attachment where there are multiple attachment points and reduced attachment, where the number of attachment points are decreased. In this study, an attempt to characterize the microtopography of the common brill fish, Scophthalmus rhombus, was undertaken. Scophthalmus rhombus is a small flatfish of the family Scophthalmidae, inhabiting regions from Norway to the Mediterranean and the Black Sea. They reside in shallow sandy and muddy coastal areas at depths of around 70 – 80 meters. Six engineered surfaces (inspired by the Brill fish scale) produced by a 2-photon polymerization (2PP) process were evaluated for their potential as an antifouling solution for incorporation onto tidal energy blades. The micro-textures were analyzed for their AF potential under both static and dynamic laboratory conditions using two laboratory grown diatom species, Amphora coffeaeformis and Nitzschia ovalis. The incorporation of a surface topography was observed to cause a disruption in the growth of A. coffeaeformis and N. ovalis cells on the surface in comparison to control surfaces. This work has demonstrated the importance of understanding cell-surface interaction, in particular, topography for the design of novel antifouling technology. The study concluded that biofouling can be controlled by physical modification, and has contributed significant knowledge to the use of a successful novel bioinspired AF technology, based on Brill, for the first time.

Keywords: attachment point theory, biofouling, Scophthalmus rhombus, topography

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

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Authors: Nur Farah Ain Zainee, Ahmad Ismail, Nazlina Ibrahim, Asmida Ismail

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Seaweeds are economically important as they have the potential of being utilized, the capabilities and opportunities for further expansion as well as the availability of other species for future development. Hence, research on the diversity and distribution of seaweeds have to be expanded whilst the seaweeds are one of the Malaysian marine valuable heritage. The study on the distribution of seaweeds at Pengerang, Johor was carried out between February and November 2015 at Kampung Jawa Darat and Kampung Sungai Buntu. The study sites are located at the south-southeast of Peninsular Malaysia where the Petronas Refinery and Petrochemicals Integrated Project Development (RAPID) are in progress. In future, the richness of seaweeds in Pengerang will vanish soon due to the loss of habitat prior to RAPID project. The research was completed to study the diversity of seaweed and to determine the present of fungal endophyte isolated from the seaweed. The sample was calculated by using quadrat with 25-meter line transect by 3 replication for each site. The specimen were preserved, identified, processed in the laboratory and kept as herbarium specimen in Algae Herbarium, Universiti Kebangsaan Malaysia. The complete thallus specimens for fungal endophyte screening were chosen meticulously, transferred into sterile zip-lock plastic bag and kept in the freezer for further process. A total of 29 species has been identified including 12 species of Chlorophyta, 2 species of Phaeophyta and 14 species of Rhodophyta. From February to November 2015, the number of species highly varied and there was a significant change in community structure of seaweeds. Kampung Sungai Buntu shows the highest diversity throughout the study compared to Kampung Jawa Darat. This evidence can be related to the high habitat preference such as types of shores which is rocky, sandy and having lagoon and bay. These can enhance the existence of the seaweeds community due to variations of the habitat. Eighteen seaweed species were selected and screened for the capability presence of fungal endophyte; Sargassum polycystum marked having the highest number of fungal endophyte compared to the other species. These evidence has proved the seaweed have capable of accommodating a lot of species of fungal endophytes. Thus, these evidence leads to positive consequences where further research should be employed.

Keywords: diversity, fungal endophyte, macroalgae, screening, seaweed

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Authors: Ali Hamza

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Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

Procedia PDF Downloads 54