Search results for: augmented reality digital technologies

Authors: Amor Jnifene, Cedric Cocaud

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One of the most constraining problems facing the development of autonomous vehicles is the limitations of current technologies. Guidance and navigation controllers need to be faster and more robust. Communication data links need to be more reliable and secure. For an Unmanned Aerial Vehicles (UAV) to be useful, and fully autonomous, one important feature that needs to be an integral part of the navigation system is autonomous trajectory planning. The work discussed in this paper presents a method for on-line trajectory planning for UAV’s. This method takes into account various constraints of different types including specific vectors of approach close to target points, multiple objectives, and other constraints related to speed, altitude, and obstacle avoidance. The trajectory produced by the proposed method ensures a smooth transition between different segments, satisfies the minimum curvature imposed by the dynamics of the UAV, and finds the optimum velocity based on available atmospheric conditions. Given a set of objective points and waypoints a skeleton of the trajectory is constructed first by linking all waypoints with straight segments based on the order in which they are encountered in the path. Secondly, vectors of approach (VoA) are assigned to objective waypoints and their preceding transitional waypoint if any. Thirdly, the straight segments are replaced by 3D curvilinear trajectories taking into account the aircraft dynamics. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircrafts, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircraft, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers.

Keywords: trajectory planning, unmanned autonomous air vehicle, vector of approach, waypoints

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Authors: Ismene Ithai Bras-Ruiz

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Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

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Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand

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Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.

Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing

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Authors: Dalal Albudaiwi, Mike Allen, Talal Alhaji, Shahnaz Khadimehzadah

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As a pandemic, COVID-19 has impacted the whole world since November 2019. In other words, every organization, industry, and institution has been negatively affected by the Coronavirus. The uncertainty of how long the pandemic will last caused chaos at all levels. As with any other institution, public libraries were affected and transmitted into online services and resources. As internationally, have been witnessed that some public libraries were well-prepared for such disasters as the pandemic, and therefore, collections, users, services, technologies, staff, and budgets were all influenced. Public libraries’ policies did not mention any plan regarding such a pandemic. Instead, there are several rules in the guidelines about disasters in general, such as natural disasters. In this pandemic situation, libraries have been involved in different uneasy circumstances. However, it has always been apparent to public libraries the role they play in serving their communities in excellent and critical times. It dwells into the traditional role public libraries play in providing information services and sources to satisfy their information-based community needs. Remarkably increasing people’s awareness of the importance of informational enrichment and enhancing society’s skills in dealing with information and information sources. Under critical circumstances, libraries play a different role. It goes beyond the traditional part of information providers to the untraditional role of being a social institution that serves the community with whatever capabilities they have. This study takes two significant directions. The first focuses on investigating how libraries have responded to COVID-19 and how they manage disasters within their organization. The second direction focuses on how libraries help their communities to act during disasters and how to recover from the consequences. The current study examines how libraries prepare for disasters and the role of public libraries during disasters. We will also propose “measures” to be a model that libraries can use to evaluate the effectiveness of their response to disasters. We intend to focus on how libraries responded to this new disaster. Therefore, this study aims to develop a comprehensive policy that includes responding to a crisis such as Covid-19. An analytical lens inside the libraries as an organization and outside the organization walls will be documented based on analyzing disaster-related literature published in the LIS publication. The study employs content analysis (CA) methodology. CA is widely used in the library and information science. The critical contribution of this work is to propose solutions it provides to libraries and planers to prepare crisis management plans/ policies, specifically to face a new global disaster such as the COVID-19 pandemic. Moreover, the study will help library directors to evaluate their strategies and to improve them properly. The significance of this study lies in guiding libraries’ directors to enhance the goals of the libraries to guarantee crucial issues such as: saving time, avoiding loss, saving budget, acting quickly during a crisis, maintaining libraries’ role during pandemics, finding out the best response to disasters, and creating plan/policy as a sample for all libraries.

Keywords: Covid-19, policy, preparedness, public libraries

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Authors: Navah Z. Ratzon, Rachel Shichrur

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Background: Many studies have assessed and identified the risk factors of safe driving, but there is relatively little research-based evidence concerning the ability to improve the driving skills of drivers in general and in particular of bus drivers, who are defined as a population at risk. Accidents involving bus drivers can endanger dozens of passengers and cause high direct and indirect damages. Objective: To examine the effectiveness of a metacognitive-functional intervention program for the reduction of risk factors among professional drivers relative to a control group. Methods: The study examined 77 bus drivers working for a large public company in the center of the country, aged 27-69. Twenty-one drivers continued to the intervention stage; four of them dropped out before the end of the intervention. The intervention program we developed was based on previous driving models and the guiding occupational therapy practice framework model in Israel, while adjusting the model to the professional driving in public transportation and its particular risk factors. Treatment focused on raising awareness to safe driving risk factors identified at prescreening (ergonomic, perceptual-cognitive and on-road driving data), with reference to the difficulties that the driver raises and providing coping strategies. The intervention has been customized for each driver and included three sessions of two hours. The effectiveness of the intervention was tested using objective measures: In-Vehicle Data Recorders (IVDR) for monitoring natural driving data, traffic accident data before and after the intervention, and subjective measures (occupational performance questionnaire for bus drivers). Results: Statistical analysis found a significant difference between the degree of change in the rate of IVDR perilous events (t(17)=2.14, p=0.046), before and after the intervention. There was significant difference in the number of accidents per year before and after the intervention in the intervention group (t(17)=2.11, p=0.05), but no significant change in the control group. Subjective ratings of the level of performance and of satisfaction with performance improved in all areas tested following the intervention. The change in the ‘human factors/person’ field, was significant (performance : t=- 2.30, p=0.04; satisfaction with performance : t=-3.18, p=0.009). The change in the ‘driving occupation/tasks’ field, was not significant but showed a tendency toward significance (t=-1.94, p=0.07,). No significant differences were found in driving environment-related variables. Conclusions: The metacognitive-functional intervention significantly improved the objective and subjective measures of safety of bus drivers’ driving. These novel results highlight the potential contribution of occupational therapists, using metacognitive functional treatment, to preventing car accidents among the healthy drivers population and improving the well-being of these drivers. This study also enables familiarity with advanced technologies of IVDR systems and enriches the knowledge of occupational therapists in regards to using a wide variety of driving assessment tools and making the best practice decisions.

Keywords: bus drivers, IVDR, human risk factors, metacognitive-functional intervention

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Leonardo Coloma

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The world changes constantly, every second its properties vary due either natural factors or human intervention. As the most intelligent creatures on the planet, human beings have transformed the environment and paradoxically –have allowed ‘mother nature’ to lose species, accelerate the processes of climate change, the deterioration of the ozone layer, among others. The rapid population growth, the procurement, administration and distribution of resources, waste management, and technological advances are some of the factors that boost urban sprawl whose gray stain extends over the territory, facing challenges such as pollution, overpopulation and scarcity of resources. In Ecuador, these problems are added to the social, cultural, economic and political anomalies that have historically affected it. This fact can represent a greater delay when trying to solve global problems, without having paid attention to local inconveniences –smaller ones, but ones that could be the key to project smart solutions on bigger ones. This research aims to highlight the main characteristics of the development models adopted by two Amazonian cities, and analyze the impact of such urban growth on society; to finally define the parameters that would allow the development of an intelligent city in Ecuador, prepared for the challenges of the XXI Century. Contrasts in the climate, temperature, and landscape of Ecuadorian cities are fused with the cultural diversity of its people, generating a multiplicity of nuances of an indecipherable wealth. However, we strive to apply development models that do not recognize that wealth, not understanding them and ignoring that their proposals will vary according to where they are applied. Urban plans seem to take a bit of each of the new theories and proposals of development, which, in the encounter with the informal growth of cities, with those excluded and ‘isolated’ societies, generate absurd morphologies - where the uncertain becomes tangible. The desire to project smart cities is ever growing, but it is important to consider that this concept does not only have to do with the use of information and communication technologies. Its success is achieved when advances in science and technology allow the establishment of a better relationship between people and their context (natural and built). As a research methodology, urban analysis through mappings, diagrams and geographical studies, as well as the identification of sensorial elements when living the city, will make evident the shortcomings of the urban models adopted by certain populations of the Ecuadorian Amazon. Following the vision of previous investigations started since 2014 as part of ‘Centro de Acciones Urbanas,’ the results of this study will encourage the dialogue between the city (as a physical fact) and those who ‘make the city’ (people as its main actors). This research will allow the development of workshops and meetings with different professionals, organizations and individuals in general.

Keywords: Latin American cities, smart cities, urban development, urban morphology, urban sprawl

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Authors: A. V. Samokhin, A. A. Fadeev, M. A. Sinaiskii, N. V. Alekseev, A. V. Kolesnikov

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Composite materials where metal matrix is reinforced by ceramic or metal particles are of great interest for use in the manufacturing of electrical contacts. Significant improvement of the composite physical and mechanical properties as well as increase of the performance parameters of composite-based products can be achieved if the nanoscale structure in the composite materials is obtained by using nanosized powders as starting components. The results of nanosized composite powders synthesis (Ag-SnO2, W-Cu and Cu-C) in the DC thermal plasma flows are presented in this paper. The investigations included the following processes: - Recondensation of micron powder mixture Ag + SnO2 in a nitrogen plasma; - The reduction of the oxide powders mixture (WO3 + CuO) in a hydrogen-nitrogen plasma; - Decomposition of the copper formate and copper acetate powders in nitrogen plasma. The calculations of equilibrium compositions of multicomponent systems Ag-Sn-O-N, W-Cu-O-H-N and Cu-O-C-H-N in the temperature range of 400-5000 K were carried to estimate basic process characteristics. Experimental studies of the processes were performed using a plasma reactor with a confined jet flow. The plasma jet net power was in the range of 2 - 13 kW, and the feedstock flow rate was up to 0.35 kg/h. The obtained powders were characterized by TEM, HR-TEM, SEM, EDS, ED-XRF, XRD, BET and QEA methods. Nanocomposite Ag-SnO2 (12 wt. %). Processing of the initial powder mixture (Ag-SnO2) in nitrogen thermal plasma stream allowed to produce nanopowders with a specific surface area up to 24 m2/g, consisting predominantly of particles with size less than 100 nm. According to XRD results, tin was present in the obtained products as SnO2 phase, and also as intermetallic phases AgxSn. Nanocomposite W-Cu (20 wt .%). Reduction of (WO3+CuO) mixture in the hydrogen-nitrogen plasma provides W-Cu nanopowder with particle sizes in the range of 10-150 nm. The particles have mainly spherical shape and structure tungsten core - copper shell. The thickness of the shell is about several nanometers, the shell is composed of copper and its oxides (Cu2O, CuO). The nanopowders had 1.5 wt. % oxygen impurity. Heat treatment in a hydrogen atmosphere allows to reduce the oxygen content to less than 0.1 wt. %. Nanocomposite Cu-C. Copper nanopowders were found as products of the starting copper compounds decomposition. The nanopowders primarily had a spherical shape with a particle size of less than 100 nm. The main phase was copper, with small amount of Cu2O and CuO oxides. Copper formate decomposition products had a specific surface area 2.5-7 m2/g and contained 0.15 - 4 wt. % carbon; and copper acetate decomposition products had the specific surface area 5-35 m2/g, and carbon content of 0.3 - 5 wt. %. Compacting of nanocomposites (sintering in hydrogen for Ag-SnO2 and electric spark sintering (SPS) for W-Cu) showed that the samples having a relative density of 97-98 % can be obtained with a submicron structure. The studies indicate the possibility of using high-intensity plasma processes to create new technologies to produce nanocomposite materials for electric contacts.

Keywords: electrical contact, material, nanocomposite, plasma, synthesis

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Authors: Itzel Amaro-Estrada, Eduardo Vergara-Rivera, Virginia Juarez-Flores, Mayra Cobaxin-Cardenas, Rosa Estela Quiroz, Jesus F. Preciado, Sergio Rodriguez-Camarillo

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Bovine anaplasmosis is an infectious, tick-borne disease caused mainly by Anaplasma marginale; typical signs include anemia, fever, abortion, weight loss, decreased milk production, jaundice, and potentially death. Sick bovine can recover when antibiotics are administered; however, it usually remains as carrier for life, being a risk of infection for susceptible cattle. Anaplasma marginale is an obligate intracellular Gram-negative bacterium with genetic composition highly diverse among geographical isolates. There are currently no vaccines fully effective against bovine anaplasmosis; therefore, the economic losses due to disease are present. Vaccine formulation became a hard task for several pathogens as Anaplasma marginale, but peptide-based vaccines are an interesting proposal way to induce specific responses. Phage-displayed peptide libraries have been proved one of the most powerful technologies for identifying specific ligands. Screening of these peptides libraries is also a tool for studying interactions between proteins or peptides. Thus, it has allowed the identification of ligands recognized by polyclonal antiserums, and it has been successful for the identification of relevant epitopes in chronic diseases and toxicological conditions. Protective immune response to bovine anaplasmosis includes high levels of immunoglobulins subclass G2 (IgG2) but not subclass IgG1. Therefore, IgG2 from the serum of protected bovine can be useful to identify ligands, which can be part of an immunogen for cattle. In this work, phage display random peptide library Ph.D. ™ -12 was incubating with IgG2 or blood sera of immunized bovines against A. marginale as targets. After three rounds of biopanning, several candidates were selected for additional analysis. Subsequently, their reactivity with sera immunized against A. marginale, as well as with positive and negative sera to A. marginale was evaluated by immunoassays. A collection of recognized peptides tested by ELISA was generated. More than three hundred phage-peptides were separately evaluated against molecules which were used during panning. At least ten different peptides sequences were determined from their nucleotide composition. In this approach, three phage-peptides were selected by their binding and affinity properties. In the case of the development of vaccines or diagnostic reagents, it is important to evaluate the immunogenic and antigenic properties of the peptides. Immunogenic in vitro and in vivo behavior of peptides will be assayed as synthetic and as phage-peptide for to determinate their vaccine potential. Acknowledgment: This work was supported by grant SEP-CONACYT 252577 given to I. Amaro-Estrada.

Keywords: bovine anaplasmosis, peptides, phage display, veterinary vaccines

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Authors: Vladimir Messerle, Alexandr Ustimenko, Oleg Lavrichshev

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This work presents plasma technology for solid fuel ignition and combustion. Plasma activation promotes more effective and environmentally friendly low-rank coal ignition and combustion. To realise this technology at coal fired power plants plasma-fuel systems (PFS) were developed. PFS improve efficiency of power coals combustion and decrease harmful emission. PFS is pulverized coal burner equipped with arc plasma torch. Plasma torch is the main element of the PFS. Plasma forming gas is air. It is blown through the electrodes forming plasma flame. Temperature of this flame is varied from 5000 to 6000 K. Plasma torch power is varied from 100 to 350 kW and geometrical sizes are the following: the height is 0.4-0.5 m and diameter is 0.2-0.25 m. The base of the PFS technology is plasma thermochemical preparation of coal for burning. It consists of heating of the pulverized coal and air mixture by arc plasma up to temperature of coal volatiles release and char carbon partial gasification. In the PFS coal-air mixture is deficient in oxygen and carbon is oxidised mainly to carbon monoxide. As a result, at the PFS exit a highly reactive mixture is formed of combustible gases and partially burned char particles, together with products of combustion, while the temperature of the gaseous mixture is around 1300 K. Further mixing with the air promotes intensive ignition and complete combustion of the prepared fuel. PFS have been tested for boilers start up and pulverized coal flame stabilization in different countries at power boilers of 75 to 950 t/h steam productivity. They were equipped with different types of pulverized coal burners (direct flow, muffle and swirl burners). At PFS testing power coals of all ranks (lignite, bituminous, anthracite and their mixtures) were incinerated. Volatile content of them was from 4 to 50%, ash varied from 15 to 48% and heat of combustion was from 1600 to 6000 kcal/kg. To show the advantages of the plasma technology before conventional technologies of coal combustion numerical investigation of plasma ignition, gasification and thermochemical preparation of a pulverized coal for incineration in an experimental furnace with heat capacity of 3 MW was fulfilled. Two computer-codes were used for the research. The computer simulation experiments were conducted for low-rank bituminous coal of 44% ash content. The boiler operation has been studied at the conventional mode of combustion and with arc plasma activation of coal combustion. The experiments and computer simulation showed ecological efficiency of the plasma technology. When a plasma torch operates in the regime of plasma stabilization of pulverized coal flame, NOX emission is reduced twice and amount of unburned carbon is reduced four times. Acknowledgement: This work was supported by Ministry of Education and Science of the Republic of Kazakhstan and Ministry of Education and Science of the Russian Federation (Agreement on grant No. 14.613.21.0005, project RFMEFI61314X0005).

Keywords: coal, ignition, plasma-fuel system, plasma torch, thermal power plant

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Authors: Małgorzata Golonka, Jadwiga Laska

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Among self-healing materials, the most unexplored group are thermoplastic polymers. These polymers are used not only to produce packaging with a relatively short life but also to obtain coatings, insulation, casings, or parts of machines and devices. Due to its exceptional resistance to weather conditions, hydrophobicity, sufficient mechanical strength, and ease of extrusion, polyethylene is used in the production of polymer pipelines and as an insulating layer for steel pipelines. Polyethylene or PE coated steel pipelines can be used in difficult conditions such as underground or underwater installations. Both installation and use under such conditions are associated with high stresses and consequently the formation of microdamages in the structure of the material, loss of its integrity and final applicability. The ideal solution would be to include a self-healing system in the polymer material. In the presented study the behavior of resin-coated microcapsules in the extrusion process of low-density polyethylene was examined. Microcapsules are a convenient element of the repair system because they can be filled with appropriate reactive substances to ensure the repair process, but the main problem is their durability under processing conditions. Rapeseed oil, which has a relatively high boiling point of 240⁰C and low volatility, was used as the core material that simulates the reactive agents. The capsule shell, which is a key element responsible for its mechanical strength, was obtained by in situ polymerising urea-formaldehyde, melamine-urea-formaldehyde or melamine-formaldehyde resin on the surface of oil droplets dispersed in water. The strength of the capsules was compared based on the shell material, and in addition, microcapsules with single- and multilayer shells were obtained using different combinations of the chemical composition of the resins. For example, the first layer of appropriate tightness and stiffness was made of melamine-urea-formaldehyde resin, and the second layer was a melamine-formaldehyde reinforcing layer. The size, shape, distribution of capsule diameters and shell thickness were determined using digital optical microscopy and electron microscopy. The efficiency of encapsulation (i.e., the presence of rapeseed oil as the core) and the tightness of the shell were determined by FTIR spectroscopic examination. The mechanical strength and distribution of microcapsules in polyethylene were tested by extruding samples of crushed low-density polyethylene mixed with microcapsules in a ratio of 1 and 2.5% by weight. The extrusion process was carried out in a mini extruder at a temperature of 150⁰C. The capsules obtained had a diameter range of 70-200 µm. FTIR analysis confirmed the presence of rapeseed oil in both single- and multilayer shell microcapsules. Microscopic observations of cross sections of the extrudates confirmed the presence of both intact and cracked microcapsules. However, the melamine-formaldehyde resin shells showed higher processing strength compared to that of the melamine-urea-formaldehyde coating and the urea-formaldehyde coating. Capsules with a urea-formaldehyde shell work very well in resin coating systems and cement composites, i.e., in pressureless processing and moulding conditions. The addition of another layer of melamine-formaldehyde coating to both the melamine-urea-formaldehyde and melamine-formaldehyde resin layers significantly increased the number of microcapsules undamaged during the extrusion process. The properties of multilayer coatings were also determined and compared with each other using computer modelling.

Keywords: self-healing polymers, polyethylene, microcapsules, extrusion

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Authors: Zi Y. Kang, Tracy D. Cassidy, Tom Cassidy

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3D apparel CAD is one of the remarkable products in advanced technology which enables intuitive design, visualisation and evaluation of garments through stereoscopic drape simulation. The progressive improvements of 3D apparel CAD have led to the creation of more realistic clothing simulation which is used not only in design development but also in presentation, promotion and communication for fashion as well as other industries such as film, game and social network services. As a result, 3D clothing technology is becoming more ubiquitous in human culture and lives today. This study considers that such phenomenon implies that the technology has reached maturity and it is time to inspect the status of current technology and to explore its potential uses in ways to create cultural values to further move forward. For this reason, this study aims to generate virtual costumes as culturally significant objects using 3D apparel CAD and to assess its capability, applicability and attitudes of the audience towards clothing simulation through comparison with physical counterparts. Since the access to costume collection is often limited due to the conservative issues, the technology may make valuable contribution by democratization of culture and knowledge for museums and its audience. This study is expected to provide foundation knowledge for development of clothing technology and for expanding its boundary of practical uses. To prevent any potential damage, two replicas of the costumes in the 1860s and 1920s at the Museum of London were chosen as samples. Their structural, visual and physical characteristics were measured and collected using patterns, scanned images of fabrics and objective fabric measurements with scale, KES-F (Kawabata Evaluation System of Fabrics) and Titan. Commercial software, DC Suite 5.0 was utilised to create virtual costumes applying collected data and the following outcomes were produced for the evaluation: Images of virtual costumes and video clips showing static and dynamic simulation. Focus groups were arranged with fashion design students and the public for evaluation which exposed the outcomes together with physical samples, fabrics swatches and photographs. The similarities, application and acceptance of virtual costumes were estimated through discussion and a questionnaire. The findings show that the technology has the capability to produce realistic or plausible simulation but expression of some factors such as details and capability of light material requires improvements. While the use of virtual costumes was viewed as more interesting and futuristic replacements to physical objects by the public group, the fashion student group noted more differences in detail and preferred physical garments highlighting the absence of tangibility. However, the advantages and potential of virtual costumes as effective and useful visual references for educational and exhibitory purposes were underlined by both groups. Although 3D apparel CAD has sufficient capacity to assist garment design process, it has limits in identical replication and more study on accurate reproduction of details and drape is needed for its technical improvements. Nevertheless, the virtual costumes in this study demonstrated the possibility of the technology to contribute to cultural and knowledgeable value creation through its applicability and as an interesting way to offer 3D visual information.

Keywords: digital clothing technology, garment simulation, 3D Apparel CAD, virtual costume

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Authors: Bhojan Dhakal, Naba Raj Devkota, Chet Raj Upreti, Maheshwar Sapkota

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A study was conducted to find out the production potential, nutrient composition, and the variability of the most commonly available fodder trees along with the varying altitude to help optimize the dry matter requirement during winter lean period. The study was carried out from March to June, 2012 in Lho and Prok Village Development Committee of Manaslu Conservation Area (MCA), located in Gorkha district of Nepal. The other objective of the research was to learn the impact of climate change on livestock production linking it with feed availability. The study was conducted in two parts: social and biological. Accordingly, a households (HHs) survey was conducted to collect primary data from 70 HHs, focusing on the perception of respondents on impacts of climatic variability on the feeding management. The next part consisted of understanding yield potential and nutrient composition of the four most commonly available fodder trees (M. azedirach, M. alba, F. roxburghii, F. nemoralis), within two altitudes range: (1500-2000 masl and 2000-2500 masl) by using a RCB design in 2*4 factorial combination of treatments, each replicated four times. Results revealed that majority of the farmers perceived the change in climatic phenomenon more severely within the past five years. Farmers were using different adaptation technologies such as collection of forage from jungle, reducing unproductive animals, fodder trees utilization, and crop by product feeding at feed scarcity period. Ranking of the different fodder trees on the basis of indigenous knowledge and experiences revealed that F. roxburghii was the best-preferred fodder tree species (index value 0.72) in terms overall preferability whereas M. azedirach had highest growth and productivity (index value 0.77), F. roxburghii had highest adoptability (index value 0.69) and palatability (index value 0.69) as well. Similarly, fresh yield and dry matter yield of the each fodder trees was significant (P < 0.01) between the altitude and within species. Fodder trees yield analysis revealed that the highest dry matter (DM) yield (28 kg/tree) was obtained for F. roxburghii but that remained statistically similar (P > 0.05) to the other treatment. On the other hand, most of the parameters: ether extract (EE), acid detergent lignin (ADL), acid detergent fibre (ADF), cell wall digestibility (CWD), relative digestibility (RD), digestible nutrient (TDN), and Calcium (Ca) among the treatments were highly significant (P < 0.01). This indicates the scope of introducing productive and nutritive fodder trees species even at the high altitude to help reduce fodder scarcity problem during winter. The finding also revealed the scope of promoting all available local fodder trees species as crude protein content of these species were similar.

Keywords: fodder trees, yield potential, climate change, nutrient composition

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Authors: Ramanamurthi Botlagunta

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Return migrate on is a process; it’s not a new phenomenal. People are migrating since civilization started. In the case of Indian Diaspora, peoples migrated before the Independence of India. Even after the independence. There are various reasons for the migration. According to the characteristics of the migrants, geographical, political, and economic factors there are many changes occur in the mode of migration. In India currently almost 25 million peoples are outside of the country. But all of them not able to get the immigrants status in their respective host society due to the nature of individual perception and the immigration policies of the host countries. They came back to homeland after spending days/months/years. They are known as the return migrants. Returning migrants are 'persons returning to their country of citizenship after having been international migrants, whether short term or long-term'. Increasingly, migration is seen very differently from what was once believed to be a one-way phenomenon. The renewed interest of return migration can be seen through two aspects one is that growing importance of temporary migration programmers in other countries and other one is that potential role of migrants in developing their home countries. Conceptualized return migration in several ways: occasional return, seasonal return, temporary return, permanent return, and circular return. The reasons for the return migration are retirement, failure to assimilate in the host country, problems with acculturation in the destination country, being unsuccessful in the emigrating country, acquiring the desired wealth, innovate and to serve as change agents in the birth country. With the advent of globalization and the rapid development of transportation systems and communication technologies, this is a process by which immigrants forge and sustain simultaneous multi-stranded social relations that link together their societies of origin and settlement. We can find that Current theories of transnational migration are greatly focused on the economic impacts on the home countries, while social, cultural and political impacts have recently started gaining momentum. This, however, has been changing as globalization is radically transforming the way people move around the world. One of the reasons for the return migration is that lack of proportionate representation of Asian immigrants in positions of authority and decision-making can be a result of challenges confronted in cultural and structural assimilation. The present study mainly focuses socioeconomic and demographic profile of return migration of Indians from other countries in general and particularly on Andhra Pradesh the people who are returning from other countries. Migration is that lack of proportionate representation of Asian immigrants in positions of authority and decision-making can be a result of challenges confronted in cultural and structural assimilation. The present study mainly focuses socioeconomic and demographic profile of return migration of Indians from other countries in general and particularly on Andhra Pradesh the people who are returning from other countries.

Keywords: migration, return migration, globalization, development, socio- economic, Asian immigrants, UN, Andhra Pradesh

Procedia PDF Downloads 371

Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

Procedia PDF Downloads 267

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

Procedia PDF Downloads 100

Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

Procedia PDF Downloads 79

Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

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Authors: Ashir Ahmed

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Peacekeeping is a collective responsibility of governments, law enforcement agencies, communities, families, and individuals. Moreover, the complex nature of peacekeeping activities requires a holistic and collaborative approach where various community sectors work together to form collective strategies that are likely to be more effective than strategies designed and delivered in isolation. Similarly, it is important to learn from past programs to evaluate the initiatives that have worked well and the areas that need further improvement. Review of recent peacekeeping initiatives suggests that there have been tremendous efforts and resources put in place to deal with the emerging threat of terrorism, radicalization and violent extremism through number of de-radicalization programs. Despite various attempts in designing and delivering successful programs for deradicalization, the threat of people being radicalized is growing more than ever before. This research reviews the prominent de-radicalization programs to draw an understanding of their strengths and weaknesses. Some of the weaknesses in the existing programs include. Inaccessibility: Limited resources, geographical location of potential participants (for offline programs), inaccessibility or inability to use various technologies (for online programs) makes it difficult for people to participate in de-radicalization programs. Timeliness: People might need to wait for a program on a set date/time to get the required information and to get their questions answered. This is particularly true for offline programs. Lack of trust: The privacy issues and lack of trust between participants and program organizers are another hurdle in the success of de-radicalization programs. The fear of sharing participants information with organizations (such as law enforcement agencies) without their consent led them not to participate in these programs. Generalizability: Majority of these programs are very generic in nature and do not cater the specific needs of an individual. Participants in these programs may feel that the contents are irrelevant to their individual situations and hence feel disconnected with purpose of the programs. To address the above-mentioned weaknesses, this research developed a framework that recommends some improvements in de-radicalization programs. One of the recommendations is to offer 24/7, secure, private and online hotline (also referred as helpline) for the people who have any question, concern or situation to discuss with someone who is qualified (a counsellor) to deal with people who are vulnerable to be radicalized. To make these hotline services viable and sustainable, the existing organizations offering support for depression, anxiety or suicidal ideation could additionally host these services. These helplines should be available via phone, the internet, social media and in-person. Since these services will be embedded within existing and well-known services, they would likely to get more visibility and promotion. The anonymous and secure conversation between a person and a counsellor would ensure that a person can discuss the issues without being afraid of information sharing with any third party – without his/her consent. The next stage of this project would include the operationalization of the framework by collaborating with other organizations to host de-radicalization hotlines and would assess the effectiveness of such initiatives.

Keywords: de-radicalization, framework, hotlines, peacekeeping

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Authors: Bijit Kalita, K. V. N. Surendra

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The pulley works under both compressive loading due to contacting belt in tension and central torque due to cause rotation. In a power transmission system, the belt pulley assemblies offer a contact problem in the form of two mating cylindrical parts. In this work, we modeled a pulley as a heavy two-dimensional circular disk. Stress analysis due to contact loading in the pulley mechanism is performed. Finite element analysis (FEA) is conducted for a pulley to investigate the stresses experienced on its inner and outer periphery. In most of the heavy-duty applications, most frequently used mechanisms to transmit power in applications such as automotive engines, industrial machines, etc. is Belt Drive. Usually, very heavy circular disks are used as pulleys. A pulley could be entitled as a drum and may have a groove between two flanges around the circumference. A rope, belt, cable or chain can be the driving element of a pulley system that runs over the pulley inside the groove. A pulley is experienced by normal and shear tractions on its contact region in the process of motion transmission. The region may be belt-pulley contact surface or pulley-shaft contact surface. In 1895, Hertz solved the elastic contact problem for point contact and line contact of an ideal smooth object. Afterward, this hypothesis is generally utilized for computing the actual contact zone. Detailed stress analysis in such contact region of such pulleys is quite necessary to prevent early failure. In this paper, the results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. Based on the literature on contact stress problem induced in the wide field of applications, generated stress distribution on the shaft-pulley and belt-pulley interfaces due to the application of high-tension and torque was evaluated in this study using FEA concepts. Finally, the results obtained from ANSYS (APDL) were compared with the Hertzian contact theory. The study is mainly focused on the fatigue life estimation of a rotating part as a component of an engine assembly using the most famous Paris equation. Digital Image Correlation (DIC) analyses have been performed using the open-source software. From the displacement computed using the images acquired at a minimum and maximum force, displacement field amplitude is computed. From these fields, the crack path is defined and stress intensity factors and crack tip position are extracted. A non-linear least-squares projection is used for the purpose of the estimation of fatigue crack growth. Further study will be extended for the various application of rotating machinery such as rotating flywheel disk, jet engine, compressor disk, roller disk cutter etc., where Stress Intensity Factor (SIF) calculation plays a significant role on the accuracy and reliability of a safe design. Additionally, this study will be progressed to predict crack propagation in the pulley using maximum tangential stress (MTS) criteria for mixed mode fracture.

Keywords: crack-tip deformations, contact stress, stress concentration, stress intensity factor

Procedia PDF Downloads 124

Authors: Tracey Woods

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In the ever-evolving landscape of academia, the traditional role of the librarian has undergone a remarkable transformation. Once considered as custodians of books and gatekeepers of information, librarians have the potential to take on the vital role of facilitators of cross and inter-disciplinary projects. This shift is driven by the growing recognition of the value of interdisciplinary collaboration in addressing complex research questions in pursuit of novel solutions to real-world problems. This paper shall explore the potential of the academic librarian’s role in facilitating innovative, multi-disciplinary projects, both recognising and validating the vital role that the librarian plays in a somewhat underplayed profession. Academic libraries support teaching, the strengthening of knowledge discourse, and, potentially, the development of innovative practices. As the role of the library gradually morphs from a quiet repository of books to a community-based information hub, a potential opportunity arises. The academic librarian’s role is to build knowledge across a wide span of topics, from the advancement of AI to subject-specific information, and, whilst librarians are generally not offered the research opportunities and funding that the traditional academic disciplines enjoy, they are often invited to help build research in support of the academic. This identifies that one of the primary skills of any 21st-century librarian must be the ability to collaborate and facilitate multi-disciplinary projects. In universities seeking to develop research diversity and academic performance, there is an increasing awareness of the need for collaboration between faculties to enable novel directions and advancements. This idea has been documented and discussed by several researchers; however, there is not a great deal of literature available from recent studies. Having a team based in the library that is adept at creating effective collaborative partnerships is valuable for any academic institution. This paper outlines the development of such a project, initiated within and around an identified library-specific need: the replication of fragile special collections for object-based learning. The research was developed as a multi-disciplinary project involving the faculties of engineering (digital twins lab), architecture, design, and education. Centred around methods for developing a fragile archive into a series of tactile objects furthers knowledge and understanding in both the role of the library as a facilitator of projects, chairing and supporting, alongside contributing to the research process and innovating ideas through the bank of knowledge found amongst the staff and their liaising capabilities. This paper shall present the method of project development from the initiation of ideas to the development of prototypes and dissemination of the objects to teaching departments for analysis. The exact replication of artefacts is also balanced with the adaptation and evolutionary speculations initiated by the design team when adapted as a teaching studio method. The dynamic response required from the library to generate and facilitate these multi-disciplinary projects highlights the information expertise and liaison skills that the librarian possesses. As academia embraces this evolution, the potential for groundbreaking discoveries and innovative solutions across disciplines becomes increasingly attainable.

Keywords: Liaison librarian, multi-disciplinary collaborations, library innovations, librarian stakeholders

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Authors: Teimuraz Manjapharashvili, Ketevani Manjaparashvili

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Fuzzy logic is a modeling method for complex or ill-defined systems and is a relatively new mathematical approach. Its basis is to consider overlapping cases of parameter values and define operations to manipulate these cases. Fuzzy logic can successfully create operative automatic management or appropriate advisory systems. Fuzzy logic techniques in various operational control technologies have grown rapidly in the last few years. Fuzzy logic is used in many areas of human technological activity. In recent years, fuzzy logic has proven its great potential, especially in the automation of industrial process control, where it allows to form of a control design based on the experience of experts and the results of experiments. The engineering of chemical technological processes uses fuzzy logic in optimal management, and it is also used in process control, including the operational control of continuous cycle chemical industrial, technological processes, where special features appear due to the continuous cycle and correct management acquires special importance. This paper discusses how intelligent systems can be developed, in particular, how fuzzy logic can be used to build knowledge-based expert systems in chemical process engineering. The implemented projects reveal that the use of fuzzy logic in technological process control has already given us better solutions than standard control techniques. Fuzzy logic makes it possible to develop an advisory system for decision-making based on the historical experience of the managing operator and experienced experts. The present paper deals with operational control and management systems of continuous cycle chemical technological processes, including advisory systems. Because of the continuous cycle, many features are introduced in them compared to the operational control of other chemical technological processes. Among them, there is a greater risk of transitioning to emergency mode; the return from emergency mode to normal mode must be done very quickly due to the impossibility of stopping the technological process due to the release of defective products during this period (i.e., receiving a loss), accordingly, due to the need for high qualification of the operator managing the process, etc. For these reasons, operational control systems of continuous cycle chemical technological processes have been specifically discussed, as they are different systems. Special features of such systems in control and management were brought out, which determine the characteristics of the construction of control and management systems. To verify the findings, the development of an advisory decision-making information system for operational control of a lime kiln using fuzzy logic, based on the creation of a relevant expert-targeted knowledge base, was discussed. The control system has been implemented in a real lime production plant with a lime burn kiln, which has shown that suitable and intelligent automation improves operational management, reduces the risks of releasing defective products, and, therefore, reduces costs. The special advisory system was successfully used in the said plant both for the improvement of operational management and, if necessary, for the training of new operators due to the lack of an appropriate training institution.

Keywords: chemical process control systems, continuous cycle industrial technological processes, fuzzy logic, lime kiln

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Authors: Biswaranjan D. Mohapatra, Ipsha Hota, Swarna P. Mantry, Nibedita Behera, Kumar S. K. Varadwaj

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Designing highly active and low-cost oxygen evolution (2H₂O → 4H⁺ + 4e⁻ + O₂) electrocatalyst is one of the most active areas of advanced energy research. Some precious metal-based electrocatalysts, such as IrO₂ and RuO₂, have shown excellent performance for oxygen evolution reaction (OER); however, they suffer from high-cost and low abundance which limits their applications. Recently, layered double hydroxides (LDHs), composed of layers of divalent and trivalent transition metal cations coordinated to hydroxide anions, have gathered attention as an alternative OER catalyst. However, LDHs are insulators and coupled with carbon materials for the electrocatalytic applications. Graphene covalently doped with nitrogen has been demonstrated to be an excellent electrocatalyst for energy conversion technologies such as; oxygen reduction reaction (ORR), oxygen evolution reaction (OER) & hydrogen evolution reaction (HER). However, they operate at high overpotentials, significantly above the thermodynamic standard potentials. Recently, we reported remarkably enhanced catalytic activity of benzoate or 1-pyrenebutyrate functionalized N-doped graphene towards the ORR in alkaline medium. The molecular and heteroatom co-doping on graphene is expected to tune the electronic structure of graphene. Therefore, an innovative catalyst architecture, in which LDHs are anchored on aromatic acid functionalized ‘N’ doped graphene may presumably boost the OER activity to a new benchmark. Herein, we report fabrication of Co₂Fe-LDH on aromatic acid (AA) functionalized ‘N’ doped reduced graphene oxide (NG) and studied their OER activities in alkaline medium. In the first step, a novel polyol method is applied for synthesis of AA functionalized NG, which is well dispersed in aqueous medium. In the second step, Co₂Fe LDH were grown on AA functionalized NG by co-precipitation method. The hybrid samples are abbreviated as Co₂Fe LDH/AA-NG, where AA is either Benzoic acid or 1, 3-Benzene dicarboxylic acid (BDA) or 1, 3, 5 Benzene tricarboxylic acid (BTA). The crystal structure and morphology of the samples were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). These studies confirmed the growth of layered single phase LDH. The electrocatalytic OER activity of these hybrid materials was investigated by rotating disc electrode (RDE) technique on a glassy carbon electrode. The linear sweep voltammetry (LSV) on these catalyst samples were taken at 1600rpm. We observed significant OER performance enhancement in terms of onset potential and current density on Co₂Fe LDH/BTA-NG hybrid, indicating the synergic effect. This exploration of molecular functionalization effect in doped graphene and LDH system may provide an excellent platform for innovative design of OER catalysts.

Keywords: π-π functionalization, layered double hydroxide, oxygen evolution reaction, reduced graphene oxide

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Authors: Anthony Nyamekeh-Armah Adjei, Toshiaki Aoki

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The unreliable and poor efficiency of electricity distribution leading to frequent power outages and high losses are the major challenge facing the power distribution sector in Ghana. Distribution system routes electricity from the power generating station at a higher voltage through the transmission grid and steps it down through the low voltage lines to end users. Approximately all electricity problems and disturbances that have increased the call for renewable and sustainable energy in recent years have their roots in the distribution system. Therefore, sustaining electricity distribution efficiency can potentially contribute to the reserve of natural energy resources use in power generation, reducing greenhouse gas emission (GHG), decreasing tariffs for consumers and effective human security. Human Security is a people-centered approach where individual human being is the principal object of concern, focuses on protecting the vital core of all human lives in ways for meeting basic needs that enhance the safety and protection of individuals and communities. The vulnerability is the diminished capacity of an individual or group to anticipate, resist and recover from the effect of natural, human-induced disaster. The research objectives are to explore the causes of frequent power outages to consumers, high losses in the distribution network and the effect of poor electricity distribution efficiency on the vulnerable (poor and ordinary) people that mostly depend on electricity for their daily activities or life to survive. The importance of the study is that in a developing country like Ghana where raising a capital for new infrastructure project is difficult, it would be beneficial to enhance the efficiency that will significantly minimize the high energy losses, reduce power outage, to ensure safe and reliable delivery of electric power to consumers to secure the security of people’s livelihood. The methodology used in this study is both interview and questionnaire survey to analyze the response from the respondents on causes of power outages and high losses facing the electricity company of Ghana (ECG) and its effect on the livelihood on the vulnerable people. Among the outcome of both administered questionnaire and the interview survey from the field were; poor maintenance of existing sub-stations, use of aging equipment, use of poor distribution infrastructure and poor metering and billing system. The main observation of this paper is that the poor network efficiency (high losses and power outages) affects the livelihood of the vulnerable people. Therefore, the paper recommends that policymakers should insist on all regulation guiding electricity distribution to improve system efficiency. In conclusion, there should be decentralization of off-grid solar PV technologies to provide a sustainable and cost-effective, which can increase daily productivity and improve the quality of life of the vulnerable people in the rural communities.

Keywords: electricity efficiency, high losses, human security, power outage

Procedia PDF Downloads 286

Authors: Fabrizio Ascione, Martina Borrelli, Rosa Francesca De Masi, Silvia Ruggiero, Giuseppe Peter Vanoli

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The Directive 2010/31/EC 'Directive of the European Parliament and of the Council of 19 may 2010 on the energy performance of buildings' moved the targets of the previous version toward more ambitious targets, for instance by establishing that, by 31 December 2020, all new buildings should demand nearly zero-energy. Moreover, the demonstrative role of public buildings is strongly affirmed so that also the target nearly zero-energy buildings is anticipated, in January 2019. On the other hand, given the very low turn-over rate of buildings (in Europe, it ranges between 1-3%/yearly), each policy that does not consider the renovation of the existing building stock cannot be effective in the short and medium periods. According to this proposal, the study provides a novel, holistic approach to design the refurbishment of educational buildings in colder cities of Mediterranean regions enabling stakeholders to understand the uncertainty to use numerical modelling and the real environmental and economic impacts of adopting some energy efficiency technologies. The case study is a university building of Molise region in the centre of Italy. The proposed approach is based on the application of the cost-optimal methodology as it is shown in the Delegate Regulation 244/2012 and Guidelines of the European Commission, for evaluating the cost-optimal level of energy performance with a macroeconomic approach. This means that the refurbishment scenario should correspond to the configuration that leads to lowest global cost during the estimated economic life-cycle, taking into account not only the investment cost but also the operational costs, linked to energy consumption and polluting emissions. The definition of the reference building has been supported by various in-situ surveys, investigations, evaluations of the indoor comfort. Data collection can be divided into five categories: 1) geometrical features; 2) building envelope audit; 3) technical system and equipment characterization; 4) building use and thermal zones definition; 5) energy building data. For each category, the required measures have been indicated with some suggestions for the identifications of spatial distribution and timing of the measurements. With reference to the case study, the collected data, together with a comparison with energy bills, allowed a proper calibration of a numerical model suitable for the hourly energy simulation by means of EnergyPlus. Around 30 measures/packages of energy, efficiency measure has been taken into account both on the envelope than regarding plant systems. Starting from results, two-point will be examined exhaustively: (i) the importance to use validated models to simulate the present performance of building under investigation; (ii) the environmental benefits and the economic implications of a deep energy refurbishment of the educational building in cold climates.

Keywords: energy simulation, modelling calibration, cost-optimal retrofit, university building

Procedia PDF Downloads 178

Authors: Katarina Revocati Mteule

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The background of this research arises from global demands for fair business opportunities. As one of responses to these demands, nations embarked on reforms in commercial laws. In 1990s Tanzania resorted to economic transformation through liberalization to attract more investments included reform in commercial laws enforcement. This research scrutinizes the effectiveness of reforms in Tanzania in comparison with Canada and Singapore and the role of technology. The methodology to be used is doctrinal legal research mixed with international comparative legal research. It involves comparative analysis of library, online, and internet resources as well as Case Laws and Statutory Laws. Tanzania, Canada and Singapore are sampled comparators basing on their distinct level of economic development. The criteria of analysis includes the nature of reforms, type of technology, technological infrastructure and human resource technical competence in each country. As the world progresses towards reforms in commercial laws, improvements in law, policy, and regulatory frameworks are paramount. Specifically, commercial laws are essential in contract enforcement and dispute resolution and how it copes with modern technologies is a concern. Harnessing the best technology is necessary to cope with the modernity in world businesses. In line with this, Tanzania is improving its business environment, including law enforcement mechanisms that are supportive to investments. Reforms such as specialized commercial law enforcement coupled with alternative dispute resolutions such as arbitration, mediation, and reconciliation are emphasized. Court technology as one of the reform tools given high priority. This research evaluates the progress and the effectiveness of the reforms in Commercial Laws towards friendly business environment in Tanzania in comparison with Canada and Singapore. The experience of Tanzania is compared with Canada and Singapore to see what to improve for each country to enhance quick and fair enforcement of commercial law. The research proposes necessary global standards of procedures and in national laws to offer a business-friendly environment and the use of appropriate technology. Solutions are proposed in tackling the challenges of delays in enforcing Commercial Laws such as case management, funding, legal and procedural hindrances, laxity among staff, and abuse of Court process among litigants, all in line with modern technology. It is the finding of the research that proper use of technology has managed to reduce case backlogs and time taken to resolve a commercial dispute, to increase court integrity by minimizing human contacts in commercial law enforcement which may lead to solicitation of favors and saving of parties’ time due to online service. Among the three countries, each one is facing a distinct challenge due to the level of poverty and remoteness from online service. How solutions are found in one country is a lesson to another. To conclude, this paper is suggesting solutions for improving the commercial law enforcement mechanisms in line with modern technology. The call for technological transformation is essential for the enforcement of commercial laws.

Keywords: commercial law, enforcement, technology

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Authors: Ashlie Latiolais

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Architecture, as a discipline, is on a trajectory of extension beyond the boundaries of buildings and, more increasingly, is coupled with research that connects to alternative and typically disjointed disciplines. A “both/and” approach and (expanded) definition of architecture, as depicted here, expands the margins that contain the profession. Figuratively, architecture is a series of edges, events, and occurrences that establishes a choreography or stage by which humanity exists. The way in which architecture controls and suggests the movement through these spaces, being within a landscape, city, or building, can be viewed as a datum by which the “dance” of everyday life occurs. This submission views the realm of architecture through the lens of movement and dance as a cross-fertilizer of collaboration, tectonic, and spatial geometry investigations. “Designing on digital programs puts architects at a distance from the spaces they imagine. While this has obvious advantages, it also means that they lose the lived, embodied experience of feeling what is needed in space—meaning that some design ideas that work in theory ultimately fail in practice.” By studying the body in motion through real-time performance, a more holistic understanding of architectural space surfaces and new prospects for theoretical teaching pedagogies emerge. The atypical intersection rethinks how architecture is considered, created, and tested, similar to how “dance artists often do this by thinking through the body, opening pathways and possibilities that might not otherwise be accessible” –this is the essence of this poster submission as explained through unFOLDED, a creative performance work. A new languageismaterialized through unFOLDED, a dynamic occupiable installation by which architecture is investigated through dance, movement, and body analysis. The entry unfolds a collaboration of an architect, dance choreographer, musicians, video artist, and lighting designers to re-create one of the first documented avant-garde performing arts collaborations (Matisse, Satie, Massine, Picasso) from the Ballet Russes in 1917, entitled Parade. Architecturally, this interdisciplinary project orients and suggests motion through structure, tectonic, lightness, darkness, and shadow as it questions the navigation of the dark space (stage) surrounding the installation. Artificial light via theatrical lighting and video graphics brought the blank canvas to life – where the sensitive mix of musicality coordinated with the structure’s movement sequencing was certainly a challenge. The upstage light from the video projections created both flickered contextual imagery and shadowed figures. When the dancers were either upstage or downstage of the structure, both silhouetted figures and revealed bodies are experienced as dancer-controlled installation manipulations occurred throughout the performance. The experimental performance, through structure, prompted moving (dancing) bodies in space, where the architecture served as a key component to the choreography itself. The tectonic of the delicate steel structure allowed for the dancers to interact with the installation, which created a variety of spatial conditions – the contained box of three-dimensional space, to a wall, and various abstracted geometries in between. The development of this research unveils the new role of an Architect as a Choreographer of the built environment.

Keywords: dance, architecture, choreography, installation, architect, choreographer, space

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Authors: Rajkumar Ghosh

Abstract:

Fluoride contamination is a growing concern in various regions across the globe, including North 24 Parganas in West Bengal, India. The presence of excessive fluoride in the environment can have detrimental effects on crops, soil quality, and water resources. This note aims to shed light on the implications of fluoride contamination and its impact on the agricultural sector in North 24 Parganas. The agricultural lands in North 24 Parganas have been significantly affected by fluoride contamination, leading to adverse consequences for crop production. Excessive fluoride uptake by plants can hinder their growth, reduce crop yields, and impact the quality of agricultural produce. Certain crops, such as paddy, vegetables, and fruits, are more susceptible to fluoride toxicity, resulting in stunted growth, leaf discoloration, and reduced nutritional value. Fluoride-contaminated water, often used for irrigation, contributes to the accumulation of fluoride in the soil. Over time, this can lead to soil degradation and reduced fertility. High fluoride levels can alter soil pH, disrupt the availability of essential nutrients, and impair microbial activity critical for nutrient cycling. Consequently, the overall health and productivity of the soil are compromised, making it increasingly challenging for farmers to sustain agricultural practices. Fluoride contamination in North 24 Parganas extends beyond the soil and affects water resources as well. The excess fluoride seeps into groundwater, making it unsafe for consumption. Long-term consumption of fluoride-contaminated water can lead to various health issues, including dental and skeletal fluorosis. These health concerns pose significant risks to the local population, especially those reliant on contaminated water sources for their daily needs. Addressing fluoride contamination requires concerted efforts from various stakeholders, including government authorities, researchers, and farmers. Implementing appropriate water treatment technologies, such as defluoridation units, can help reduce fluoride levels in drinking water sources. Additionally, promoting alternative irrigation methods and crop diversification strategies can aid in mitigating the impact of fluoride on agricultural productivity. Furthermore, creating awareness among farmers about the adverse effects of fluoride contamination and providing access to alternative water sources are crucial steps toward safeguarding the health of the community and sustaining agricultural activities in the region. Fluoride contamination poses significant challenges to crop production, soil health, and water resources in North 24 Parganas, West Bengal. It is imperative to prioritize efforts to address this issue effectively and implement appropriate measures to mitigate fluoride contamination. By adopting sustainable practices and promoting awareness, the community can work towards restoring the agricultural productivity, soil quality and ensuring access to safe drinking water in the region.

Keywords: fluoride contamination, drinking water, toxicity, soil health

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Authors: María Canal-Rodríguez, María Arnaiz, Natalia Rey-Raap, Ana Arenillas, Jon Ajuria

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The constant demand of electrical energy, as well as the increase in environmental concern, lead to the necessity of investing in clean and eco-friendly energy sources that implies the development of enhanced energy storage devices. Li-ion batteries (LIBs) and Electrical double layer capacitors (EDLCs) are the most widespread energy systems. Batteries are able to storage high energy densities contrary to capacitors, which main strength is the high-power density supply and the long cycle life. The combination of both technologies gave rise to Li-ion capacitors (LICs), which offers all these advantages in a single device. This is achieved combining a capacitive, supercapacitor-like positive electrode with a faradaic, battery-like negative electrode. Due to the abundance and affordability, dual carbon-based LICs are nowadays the common technology. Normally, an Active Carbon (AC) is used as the EDLC like electrode, while graphite is the material commonly employed as anode. LICs are potential systems to be used in applications in which high energy and power densities are required, such us kinetic energy recovery systems. Although these devices are already in the market, some drawbacks like the limited power delivered by graphite or the energy limiting nature of AC must be solved to trigger their used. Focusing on the anode, one possibility could be to replace graphite with Hard Carbon (HC). The better rate capability of the latter increases the power performance of the device. Moreover, the disordered carbonaceous structure of HCs enables storage twice the theoretical capacity of graphite. With respect to the cathode, the ACs are characterized for their high volume of micropores, in which the charge is storage. Nevertheless, they normally do not show mesoporous, which are really important mainly at high C-rates as they act as transport channels for the ions to reach the micropores. Usually, the porosity of ACs cannot be tailored, as it strongly depends on the precursor employed to get the final carbon. Moreover, they are not characterized for having a high electrical conductivity, which is an important characteristic to get a good performance in energy storage applications. A possible candidate to substitute ACs are carbon aerogels (CAs). CAs are materials that combine a high porosity with great electrical conductivity, opposite characteristics in carbon materials. Furthermore, its porous properties can be tailored quite accurately according to with the requirements of the application. In the present study, CAs with controlled porosity were obtained from polymerization of resorcinol and formaldehyde by microwave heating. Varying the synthesis conditions, mainly the amount of precursors and pH of the precursor solution, carbons with different textural properties were obtained. The way the porous characteristics affect the performance of the cathode was studied by means of a half-cell configuration. The material with the best performance was evaluated as cathode in a LIC versus a hard carbon as anode. An analogous full LIC made by a high microporous commercial cathode was also assembled for comparison purposes.

Keywords: li-ion capacitors, energy storage, tailored porosity, carbon aerogels

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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