Search results for: coefficient of performance

Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Lawrence Koech, Ray Everson, Hein Neomagus, Hilary Rutto

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Wet Flue gas desulphurization (FGD) systems are commonly used to remove sulphur dioxide from flue gas by contacting it with limestone in aqueous phase which is obtained by dissolution. Dissolution is important as it affects the overall performance of a wet FGD system. In the present study, effects of pH, stirring speed, solid to liquid ratio and acid concentration on the dissolution of limestone using an organic acid (adipic acid) were investigated. This was investigated using the pH stat apparatus. Calcium ions were analyzed at the end of each experiment using Atomic Absorption (AAS) machine.

Keywords: desulphurization, limestone, dissolution, pH stat apparatus

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Hsin-Chieh Lee, Fen-Ling Kuo, Jui-Chi Lin

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Background: Upper extremity functional impairment that occurs after stroke includes hemiplegia, synergy movement, muscle hypertonicity, and somatosensory impairment, which result in inefficient and inaccurate movement. Robot-assisted rehabilitation is an intensive training approach that is effective in sensorimotor and hand function recovery. However, these systems mostly focused on the proximal part of the upper limb rather than the distal part. The device used in our study was Gloreha Sinfonia, which focuses on the distal part of the upper limb and uses a dynamic support system to facilitate the whole limb function. The objective of this study was to investigate the effects of robot-assisted therapy (RT) with Gloreha device on sensorimotor, and ADLs in patients with stroke. Method: Patients with stroke (N=25) participated AB or BA (A = 12 RT sessions and B = 12 conventional therapy (CT) sessions) for 6 weeks (60 min at each session, twice a week), with 1-month break for washout period. The performance of the patients was assessed by a blinded assessor at 4 time points (pretest 1, posttest 1, pretest 2, posttest 2) which including the Fugl–Meyer Assessment-upper extremity (FMA-UE), box and block test, electromyography of the extensor digitorum communis (EDC) and brachioradialis, a grip dynamometer for motor evaluation; Semmes–Weinstein hand monofilament and Revision of the Nottingham Sensory Assessment for sensory evaluation; and the Modified Barthel Index (MBI) for assessing the ADL ability. Result: RT group significantly improved FMA-UE proximal scores (p = 0.038), FMA-UE total scores (p = 0.046), and MBI (p = 0.030). The EDC exhibited higher efficiency during the small block grasping task in the RT group than in the CT group (p = 0.050). Conclusions: RT with the Gloreha device might lead to beneficial effects on arm motor function, ADL ability, and EDC muscle recruitment efficacy in patients with subacute to chronic stroke.

Keywords: activities of daily living, hand function, robotic rehabilitation, stroke

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Authors: Hugo Rodríguez

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Migrations of researchers, scientists, and inventors are a widespread phenomenon in modern times. In some cases, migrants stay linked to research groups in their countries of origin, either out of their own conviction or because of government policies. We examine different linear models of technological development (using the Ordinary Least Squares (OLS) technique) in eight selected countries and find that the collaborations between resident and nonresident patent applicants correlate with different levels of performance of the technological policies in three different scenarios. Therefore, the reinforcement of that link must be considered a powerful tool for technological development.

Keywords: development, collaboration, patents, technology

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Ana María Rojas Chaparro, Cristian Camilo Sarmiento Chaves

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Given the growing importance of logistics as a discipline for efficient management of materials flow and information, the adoption of tools that permit to create facilities in making decisions based on a global perspective of the system studied has been essential. The article shows how from a concepts-based model is possible to organize and represent in appropriate way the reality, showing accurate and timely information, features that make this kind of models an ideal component to support an information system, recognizing that information as relevant to establish particularities that allow get a better performance about the evaluated sector.

Keywords: system, information, conceptual model, logistics

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Authors: Shiv Kumar

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In the shifting scenario of postmodern age that foregrounds the multiplicity of meanings and discourses, the present research article seeks to investigate various paradigm shift of contemporary performances concerning Haryanvi Saangs, so-called folk plays, which are being performed widely in the regional territory of Haryana, a northern state of India. Folk arts cannot be studied efficiently by using the tools of literary criticism because it differs from the literature in many aspects. One of the most essential differences is that literary works invariably have an author. Folk works, on the contrary, never have an author. The situation is quite clear: either we acknowledge the presence of folk art as a phenomenon in the social and cultural history of people, or we do not acknowledge it and argue it is a poetical or art of fiction. This paper is an effort to understand the performative tradition of Saang which is traditionally known as Saang, Swang or Svang became a popular source for instruction and entertainment in the region and neighbouring states. Scholars and critics have long been debating about the origin of the word swang/svang/saang and their relationship to the Sanskrit word –Sangit, which means singing and music. But in the cultural context of Haryana, the word Saang means ‘to impersonate’ or ‘to imitate’ or ‘to copy someone or something’. The stories they portray are derived for the most part from the same myths, tales, epics and from the lives of Indian religious and folk heroes. Literally, the use of poetic sense, the implication of prose style and elaborate figurative technique are worthwhile to compile the productivity of a performance. All use music and song as an integral part of the performance so that it is also appropriate to call them folk opera. These folk plays are performed strictly by aboriginal people in the state. These people, sometimes denominated as Saangi, possess a culture distinct from the rest of Indian folk performances. The concerned form is also known with various other names like Manch, Khayal, Opera, Nautanki. The group of such folk plays can be seen as a dynamic activity and performed in the open space of the theatre. Nowadays, producers contributed greatly in order to create a rapidly growing musical outlet for budding new style of folk presentation and give rise to the electronic focus genre utilizing many musicians and performers who had to become precursors of the folk tradition in the region. Moreover, the paper proposes to examine available sources relative to this article, and it is believed to draw some different conclusions. For instance, to be a spectator of ongoing performances will contribute to providing enough guidance to move forward on this root. In this connection, the paper focuses critically upon the major performative aspects of Haryanvi Saang in relation to several inquiries such as the study of these plays in the context of Indian literary scenario, gender visualization and their dramatic representation, a song-music tradition in folk creativity and development of Haryanvi dramatic art in the contemporary socio-political background.

Keywords: folk play, indigenous, performance, Saang, tradition

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Authors: Thummalapalli CSM Gupta, Banti Sidhiwala

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Mineral oils of naphthenic and paraffinic type have been traditionally been used as insulating liquids in the transformer applications to protect the solid insulation from moisture and ensures effective heat transfer/cooling. The performance of these type of oils have been proven in the field over many decades and the condition monitoring and diagnosis of transformer performance have been successfully monitored through oil properties and dissolved gas analysis methods successfully. Different type of gases representing various types of faults due to components or operating conditions effectively. While large amount of data base has been generated in the industry on dissolved gas analysis for mineral oil based transformer oils and various models for predicting the fault and analysis, oil specifications and standards have also been modified to include stray gassing limits which cover the low temperature faults and becomes an effective preventative maintenance tool that can benefit greatly to know the reasons for the breakdown of electrical insulating materials and related components. Natural esters have seen a rise in popularity in recent years due to their "green" credentials. Some of its benefits include biodegradability, a higher fire point, improvement in load capability of transformer and improved solid insulation life than mineral oils. However, the Stray gases evolution like hydrogen and hydrocarbons like methane (CH4) and ethane (C2H6) show very high values which are much higher than the limits of mineral oil standards. Though the standards for these type esters are yet to be evolved, the higher values of hydrocarbon gases that are available in the market is of concern which might be interpreted as a fault in transformer operation. The current paper focuses on developing a natural ester based transformer oil which shows very levels of stray gassing by standard test methods show much lower values compared to the products available currently and experimental results on various test conditions and the underlying mechanism explained.

Keywords: biodegadability, fire point, dissolved gassing analysis, stray gassing

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Authors: Anteneh Wodaje Bayeh, Daniel Manaye Kabtamu, Chen-Hao Wang

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As one of the most promising electrochemical energy storage systems, vanadium redox flow batteries (VRFBs) have received increasing attention owing to their attractive features for largescale storage applications. However, their high production cost and relatively low energy efficiency still limit their feasibility. For practical implementation, it is of great interest to improve their efficiency and reduce their cost. One of the key components of VRFBs that can greatly influence the efficiency and final cost is the electrode, which provide the reactions sites for redox couples (VO²⁺/VO₂ + and V²⁺/V³⁺). Carbon-based materials are considered to be the most feasible electrode materials in the VRFB because of their excellent potential in terms of operation range, good permeability, large surface area, and reasonable cost. However, owing to limited electrochemical activity and reversibility and poor wettability due to its hydrophobic properties, the performance of the cell employing carbon-based electrodes remained limited. To address the challenges, we synthesized heteroatom-doped bimetallic oxide grown on the surface of carbon through the one-step approach. When applied to VRFBs, the prepared electrode exhibits significant electrocatalytic effect toward the VO²⁺/VO₂ + and V³⁺/V²⁺ redox reaction compared with that of pristine carbon. It is found that the presence of heteroatom on metal oxide promotes the absorption of vanadium ions. The controlled morphology of bimetallic metal oxide also exposes more active sites for the redox reaction of vanadium ions. Hence, the prepared electrode displays the best electrochemical performance with energy and voltage efficiencies of 74.8% and 78.9%, respectively, which is much higher than those of 59.8% and 63.2% obtained from the pristine carbon at high current density. Moreover, the electrode exhibit durability and stability in an acidic electrolyte during long-term operation for 1000 cycles at the higher current density.

Keywords: VRFB, VO²⁺/VO₂ + and V³⁺/V²⁺ redox couples, graphite felt, heteroatom-doping

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Authors: Said Algarni

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The purpose of this study was to investigate selected numerical methods that demonstrate good performance in solving PDEs. We adapted alternative method that involve rational polynomials. Padé time stepping (PTS) method, which is highly stable for the purposes of the present application and is associated with lower computational costs, was applied. Furthermore, PTS was modified for our study which focused on diffusion equations. Numerical runs were conducted to obtain the optimal local error control threshold.

Keywords: Padé time stepping, finite difference, reaction diffusion equation, PDEs

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Authors: Jin Liang, James H. Liu, Ti-Jun Xiao

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It is known that there exist many physical phenomena where abrupt or impulsive changes occur either in the system dynamics, for example, ad-hoc network, or in the input forces containing impacts, for example, the bombardment of space antenna by micrometeorites. There are many other examples such as ultra high-speed optical signals over communication networks, the collision of particles, inventory control, government decisions, interest changes, changes in stock price, etc. These are impulsive phenomena. Hence, as a combination of the traditional initial value problems and the short-term perturbations whose duration can be negligible in comparison with the duration of the process, the systems with impulsive conditions (i.e., impulsive systems) are more realistic models for describing the impulsive phenomenon. Such a situation is also suitable for the delay systems, which include some of the past states of the system. So far, there have been a lot of research results in the study of impulsive systems with delay both in finite and infinite dimensional spaces. In this paper, we investigate the periodicity of solutions to the nonautonomous impulsive evolution equations with infinite delay in Banach spaces, where the coefficient operators (possibly unbounded) in the linear part depend on the time, which are impulsive systems in infinite dimensional spaces and come from the optimal control theory. It was indicated that the study of periodic solutions for these impulsive evolution equations with infinite delay was challenging because the fixed point theorems requiring some compactness conditions are not applicable to them due to the impulsive condition and the infinite delay. We are happy to report that after detailed analysis, we are able to combine the techniques developed in our previous papers, and some new ideas in this paper, to attack these impulsive evolution equations and derive periodic solutions. More specifically, by virtue of the related transition operator family (evolution family), we present a Poincaré operator given by the nonautonomous impulsive evolution system with infinite delay, and then show that the operator is a condensing operator with respect to Kuratowski's measure of non-compactness in a phase space by using an Amann's lemma. Finally, we derive periodic solutions from bounded solutions in view of the Sadovskii fixed point theorem. We also present a relationship between the boundedness and the periodicity of the solutions of the nonautonomous impulsive evolution system. The new results obtained here extend some earlier results in this area for evolution equations without impulsive conditions or without infinite delay.

Keywords: impulsive, nonautonomous evolution equation, optimal control, periodic solution

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Authors: Sami Khan, Kripa Varanasi

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Corrosion is a widespread problem in several industries and developing surfaces that resist corrosion has been an area of interest since the last several decades. Superhydrophobic surfaces that combine hydrophobic coatings along with surface texture have been shown to improve corrosion resistance by creating voids filled with air that minimize the contact area between the corrosive liquid and the solid surface. However, these air voids can incorporate corrosive liquids over time, and any mechanical faults such as cracks can compromise the coating and provide pathways for corrosion. As such, there is a need for self-healing corrosion-resistance surfaces. In this work, the anti-corrosion properties of textured surfaces impregnated with a lubricant have been systematically studied. Since corrosion resistance depends on the area and physico-chemical properties of the material exposed to the corrosive medium, lubricant-impregnated surfaces (LIS) have been designed based on the surface tension, viscosity and chemistry of the lubricant and its spreading coefficient on the solid. All corrosion experiments were performed in a standard three-electrode cell using iron, which readily corrodes in a 3.5% sodium chloride solution. In order to obtain textured iron surfaces, thin films (~500 nm) of iron were sputter-coated on silicon wafers textured using photolithography, and subsequently impregnated with lubricants. Results show that the corrosion rate on LIS is greatly reduced, and offers an over hundred-fold improvement in corrosion protection. Furthermore, it is found that the spreading characteristics of the lubricant are significant in ensuring corrosion protection: a spreading lubricant (e.g., Krytox 1506) that covers both inside the texture, as well as the top of the texture, provides a two-fold improvement in corrosion protection as compared to a non-spreading lubricant (e.g., Silicone oil) that does not cover texture tops. To enhance corrosion protection of surfaces coated with a non-spreading lubricant, pyramid-shaped textures have been developed that minimize exposure to the corrosive solution, and a consequent twenty-fold increased in corrosion protection is observed. An increase in viscosity of the lubricant scales with greater corrosion protection. Finally, an equivalent cell-circuit model is developed for the lubricant-impregnated systems using electrochemical impedance spectroscopy. Lubricant-impregnated surfaces find attractive applications in harsh corrosive environments, especially where the ability to self-heal is advantageous.

Keywords: lubricant-impregnated surfaces, self-healing surfaces, wettability, nano-engineered surfaces

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Authors: Marianna Maiaru, Gregory M. Odegard, Josh Kemppainen, Ivan Gallegos, Michael Olaya

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Ceramic matrix composites (CMCs) are typically used in applications that require long-term mechanical integrity at elevated temperatures. CMCs are usually fabricated using a polymer precursor that is initially polymerized in situ with fiber reinforcement, followed by a series of cycles of pyrolysis to transform the polymer matrix into a rigid glass or ceramic. The pyrolysis step typically generates volatile gasses, which creates porosity within the polymer matrix phase of the composite. Subsequent cycles of monomer infusion, polymerization, and pyrolysis are often used to reduce the porosity and thus increase the durability of the composite. Because of the significant expense of such iterative processing cycles, new generations of CMCs with improved durability and manufacturability are difficult and expensive to develop using standard Edisonian approaches. The goal of this research is to develop a computational process-modeling-based approach that can be used to design the next generation of CMC materials with optimized material and processing parameters for maximum strength and efficient manufacturing. The process modeling incorporates computational modeling tools, including molecular dynamics (MD), to simulate the material at multiple length scales. Results from MD simulation are used to inform the continuum-level models to link molecular-level characteristics (material structure, temperature) to bulk-level performance (strength, residual stresses). Processing parameters are optimized such that process-induced residual stresses are minimized and laminate strength is maximized. The multiscale process modeling method developed with this research can play a key role in the development of future CMCs for high-temperature and high-strength applications. By combining multiscale computational tools and process modeling, new manufacturing parameters can be established for optimal fabrication and performance of CMCs for a wide range of applications.

Keywords: digital engineering, finite elements, manufacturing, molecular dynamics

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Authors: Anand R. Nair, Markus Trenker

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Lifting body concepts were conceived as early as 1917 and patented by Roy Scroggs. It was an idea of using the fuselage as a lift producing body with no or small wings. Many of these designs were developed and even flight tested between 1920’s to 1970’s, but it was not pursued further for commercial flight as at lower airspeeds, such a configuration was incapable to produce sufficient lift for the entire aircraft. The concept presented in this contribution is combining the lifting body design along with a fixed wing to maximise the lift produced by the aircraft. Conventional aircraft fuselages are designed to be aerodynamically efficient, which is to minimise the drag; however, these fuselages produce very minimal or negligible lift. For the design of an unmanned fixed wing transport aircraft, many of the restrictions which are present for commercial aircraft in terms of fuselage design can be excluded, such as windows for the passengers/pilots, cabin-environment systems, emergency exits, and pressurization systems. This gives new flexibility to design fuselages which are unconventionally shaped to contribute to the lift of the aircraft. The two lifting body concepts presented in this contribution are targeting different applications: For a fast cargo delivery drone, the fuselage is based on a scaled airfoil shape with a cargo capacity of 500 kg for euro pallets. The aircraft has a span of 14 m and reaches 1500 km at a cruising speed of 90 m/s. The aircraft could also easily be adapted to accommodate pilot and passengers with modifications to the internal structures, but pressurization is not included as the service ceiling envisioned for this type of aircraft is limited to 10,000 ft. The next concept to be investigated is called a multi-purpose drone, which incorporates a different type of lifting body and is a much more versatile aircraft as it will have a VTOL capability. The aircraft will have a wingspan of approximately 6 m and flight speeds of 60 m/s within the same service ceiling as the fast cargo delivery drone. The multi-purpose drone can be easily adapted for various applications such as firefighting, agricultural purposes, surveillance, and even passenger transport. Lifting body designs are not a new concept, but their effectiveness in terms of cargo transportation has not been widely investigated. Due to their enhanced lift producing capability, lifting body designs enable the reduction of the wing area and the overall weight of the aircraft. This will, in turn, reduce the thrust requirement and ultimately the fuel consumption. The various designs proposed in this contribution will be based on the general aviation category of aircrafts and will be focussed on unmanned methods of operation. These unmanned fixed-wing transport drones will feature appropriate cargo loading/unloading concepts which can accommodate large size cargo for efficient time management and ease of operation. The various designs will be compared in performance to their conventional counterpart to understand their benefits/shortcomings in terms of design, performance, complexity, and ease of operation. The majority of the performance analysis will be carried out using industry relevant standards in computational fluid dynamics software packages.

Keywords: lifting body concept, computational fluid dynamics, unmanned fixed-wing aircraft, cargo drone

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Authors: Stephen Anim, Emmanuel O. Sarpong, Daniel Apaak

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This study investigates the relationship between morphological predictors and running ability, emphasizing gender-specific variations among male and female athletes in Cape Coast Metropolis (CCM), Ghana. The dynamic interplay between an athlete's physique and their performance capabilities holds particular relevance in the realm of sports science, influencing training methodologies and talent identification processes. The research aims to contribute comprehensive insights into the morphological determinants of running proficiency, with a specific focus on the local athletic community in Cape Coast Metropolis. Utilizing a correlational research design, a thorough analysis of morphological features, encompassing 22 morphological features including body weight, 6 measurements related to body length, 7 body girth, and knee diameter, and 7 skinfold measurements against 50m dash, among male and female athletes, was conducted. The study involved 420 athletes both male (N=210) and female (N=210) aged 16-22 from 10 Senior High Schools (SHS) in the Cape Coast Metropolis, providing a representative sample of the local athletic community. The collected data were statistically analysed using means and standard deviation, and stepwise multiple regression to determine how morphological variables contribute to and predict running proficiency outcomes. The investigation revealed that athletes from Senior High Schools (SHS) in Cape Coast Metropolis (CCM) exhibit well-developed physiques and sufficient fitness levels suitable for overall athletic performance, taking into account gender differences. Moreover, the findings suggested that approximately 77% of running ability could be attributed to morphological factors, leading to diverse predictive models for male and female athletes within SHS in CCM, Ghana. Consequently, these formulated equations hold promise for predicting running ability among young athletes, particularly in the context of SHS environments.

Keywords: body fat, body girth, body length, morphological features, running ability, senior high school

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Authors: B. Sudhakara Reddy

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This study provides a snapshot of the sustainability of selected Indian cities by employing 70 indicators in four dimensions to develop an overall city sustainability index. In recent years, the concept of ‘urban sustainability’ has become prominent due to its complexity. Urban areas propel growth and at the same time poses a lot of ecological, social and infrastructural problems and risks. In case of developing countries, the high population density of and the continuous in-migration run the highest risk in natural and man-made disasters. These issues combined with the inability of policy makers in providing basic services makes the cities unsustainable. To assess whether any given policy is moving towards or against urban sustainability it is necessary to consider the relationships among its various dimensions. Hence, in recent years, while preparing the sustainability index, an integral approach involving indicators of different dimensions such as ‘economic’, ‘environmental’ and 'social' is being used. It is also important for urban planners, social analysts and other related institutions to identify and understand the relationships in this complex system. The objective of the paper is to develop a city performance index (CPI) to measure and evaluate the urban regions in terms of sustainable performances. The objectives include: i) Objective assessment of a city’s performance, ii) setting achievable goals iii) prioritise relevant indicators for improvement, iv) learning from leaders, iv) assessment of the effectiveness of programmes that results in achieving high indicator values, v) Strengthening of stakeholder participation. Using the benchmark approach, a conceptual framework is developed for evaluating 25 Indian cities. We develop City Sustainability index (CSI) in order to rank cities according to their level of sustainability. The CSI is composed of four dimensions: Economic, Environment, Social, and Institutional. Each dimension is further composed of multiple indicators: (1) Economic that considers growth, access to electricity, and telephone availability; (2) environmental that includes waste water treatment, carbon emissions, (3) social that includes, equity, infant mortality, and 4) institutional that includes, voting share of population, urban regeneration policies. The CSI, consisting of four dimensions disaggregate into 12 categories and ultimately into 70 indicators. The data are obtained from public and non-governmental organizations, and also from city officials and experts. By ranking a sample of diverse cities on a set of specific dimensions the study can serve as a baseline of current conditions and a marker for referencing future results. The benchmarks and indices presented in the study provide a unique resource for the government and the city authorities to learn about the positive and negative attributes of a city and prepare plans for a sustainable urban development. As a result of our conceptual framework, the set of criteria we suggest is somewhat different to any already in the literature. The scope of our analysis is intended to be broad. Although illustrated with specific examples, it should be apparent that the principles identified are relevant to any monitoring that is used to inform decisions involving decision variables. These indicators are policy-relevant and, hence they are useful tool for decision-makers and researchers.

Keywords: benchmark, city, indicator, performance, sustainability

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Authors: Khalil Ullah Khan

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Linguistic abilities in students with hearing impairment yet remain a concern for educationists. The emerging technological support and provisions in the recent era vow to have addressed the situation and claim significant contributions in terms of linguistic repertoire. Being a descriptive and quantitative paradigm of study, the purpose of this research set forth was to assess the linguistic competencies of students with hearing impairment in the English language. The goals were further broken down to identify the level of reading abilities in the subject population. The population involved students with HI studying at a higher secondary level in Lahore. A simple random sampling technique was used to choose a sample of fifty students. A purposive curriculum-based assessment was designed in line with the accelerated learning program by the Punjab Government to assess Linguistic competence among the sample. Further to it, an Informal Reading Inventory (IRI) corresponding to reading levels was also developed by researchers duly validated and piloted before the final use. Descriptive and inferential statistics were utilized to reach the findings. Spearman’s correlation was used to find out the relationship between the degree of hearing loss, grade level, gender and type of amplification device. An Independent sample t-test was used to compare means among groups. Major findings of the study revealed that students with hearing impairment exhibit significant deviation from the mean scores when compared in terms of grades, severity and amplification device. The study divulged that respective students with HI have yet failed to qualify for an independent level of reading according to their grades, as the majority fall at the frustration level of word recognition and passage comprehension. The poorer performance can be attributed to lower linguistic competence, as it is shown in the frustration levels of reading, writing and comprehension. The correlation analysis did reflect an improved performance grade. Wise. However, scores could only correspond to frustration level, and independent levels were never achieved. Reported achievements at the instructional level of the subject population may further to linguistic skills if practiced purposively.

Keywords: linguistic competence, hearing impairment, reading levels, educationist

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Authors: G. Vici, L. Cesanelli, L. Belli, R. Ceci, V. Polzonetti

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Several factors contribute to success in sport and diet is one of them. Evidence-based sport nutrition guidelines underline the importance of macro- and micro-nutrients’ balance and timing in order to improve athlete’s physical status and performance. Nevertheless, a high content of proteins is commonly found in resistance training athletes’ diet with carbohydrate intake that is not enough or not well planned. The aim of the study was to evaluate the impact of different protein and carbohydrate diet contents on body composition and sport performance on a group of resistance training athletes. Subjects were divided as study group (n=16) and control group (n=14). For a period of 4 months, both groups were subjected to the same resistance training fitness program with study group following a specific diet and control group following an ab libitum diet. Body compositions were evaluated trough anthropometric measurement (weight, height, body circumferences and skinfolds) and Bioimpedence Analysis. Physical strength and training status of individuals were evaluated through the One Repetition Maximum test (RM1). Protein intake in studied group was found to be lower than in control group. There was a statistically significant increase of body weight, free fat mass and body mass cell of studied group respect to the control group. Fat mass remains almost constant. Statistically significant changes were observed in quadriceps and biceps circumferences, with an increase in studied group. The MR1 test showed improvement in study group’s strength but no changes in control group. Usually people consume hyper-proteic diet to achieve muscle mass development. Through this study, it was possible to show that protein intake fixed at 1,7 g/kg/d can meet the individual's needs. In parallel, the increased intake of carbohydrates, focusing on quality and timing of assumption, has enabled the obtainment of desired results with a training protocol supporting a hypertrophic strategy. Therefore, the key point seems related to the planning of a structured program both from a nutritional and training point of view.

Keywords: body composition, diet, exercise, protein

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Authors: Rafiqul Hasan, A. S. M. Tanim Anwar, Mohammad Azizul Hakim

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Background: Chronic kidney disease (CKD) is a major public health problem that continues to increase in prevalence globally. The prevalence of chronic kidney disease is increasing day by day in low to middle income countries (LMICs). People living in LMICs have the highest need for renal replacement therapy (RRT) despite they have lowest access to various modalities of treatment. As continuous ambulatory peritoneal dialysis (CAPD) does not require advanced technologies, very much infrastructure, dialysis staff support, it should be an ideal form of RRT in LMICs, particularly for those living in remote areas. To authors knowledge there was scarcity of data regarding CAPD performance in remote area of Bangladesh. This study was aimed to report the characteristics and outcomes of CAPD in ESRD patients lived in least developed area of Bangladesh. Methods: This prospective study was conducted in Cox’sbazar Medical College Hospital, Cox’sbazar and Parkview hospital Ltd, Chattogram, Bangladesh. Data were collected by questionnaire from the patients of any age with end-stage renal disease (ESRD) who underwent CAPD in 2018–2021. The baseline characteristics, PD-related complication as well as patient and technique survivals were analyzed. Results: Out of 31 patients who underwent CAPD, 18 (58%) were male on the age range of 15–79 years. The mean follow-up duration was 18 months. Mortality was inversely related with the EF of echocardiography. The peritonitis rate was 0.48 episodes per patient per year. The 1, 3 and 4-year patient survival rates were 64.34% (95% CI = 52.5–81.5), 23.79% (95% CI = 17.9 – 57.4) and 3.22% (95% CI = 31.2–77.5) respectively. Conclusions: In this study, CAPD performance was poorer than usual reference. Cardiac compromised patient and inappropriate dwell might be the main contributing factors behind this scenario. The peritonitis rate was nearly similar to that of developed countries. CAPD was cost effective than HD in remote area. Some accessible measures may be taken to make CAPD a more acceptable RRT modality with improved outcomes in poor socioeconomic backgrounds.

Keywords: dialysis cost, peritoneal dialysis, peritonitis, CAPD, least developed area, remote area, Bangladesh

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Authors: Yan-Shen Yang, Bai-Chen Xie

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Background and significance of the study: Both green power trading schemes and interregional power transmission are effective ways to increase green power absorption and achieve renewable power development goals. China accelerates the construction of interregional power transmission lines and the green power market. A critical issue focusing on the close interaction between these two approaches arises, which can heavily affect the green power quota allocation and renewable power development. Existing studies have not discussed this issue adequately, so it is urgent to figure out their relationship to achieve a suitable power market design and a more reasonable power grid construction.Basic methodologies: We develop an equilibrium model of the power market in China to analyze the coupling effect of these two approaches as well as their influence on power generation and interregional transmission in China. Our model considers both the Tradable green certificate (TGC) and green power market, which consists of producers, consumers in the market, and an independent system operator (ISO) minimizing the total system cost. Our equilibrium model includes the decision optimization process of each participant. To reformulate the models presented as a single-level one, we replace the producer, consumer, ISO, and market equilibrium problems with their Karush-Kuhn-Tucker (KKT) conditions, which is further reformulated as a mixed-integer linear programming (MILP) and solved in Gurobi solver. Major findings: The result shows that: (1) the green power market can significantly promote renewable power absorption while the TGC market provides a more flexible way for green power trading. (2) The phenomena of inefficient occupation and no available transmission lines appear simultaneously. The existing interregional transmission lines cannot fully meet the demand for wind and solar PV power trading in some areas while the situation is vice versa in other areas. (3) Synchronous implementation of green power and TGC trading mechanism can benefit the development of green power as well as interregional power transmission. (4) The green power transaction exacerbates the unfair distribution of carbon emissions. The Carbon Gini Coefficient is up to 0.323 under the green power market which shows a high Carbon inequality. The eastern coastal region will benefit the most due to its huge demand for external power.

Keywords: green power market, tradable green certificate, interregional power transmission, power market equilibrium model

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Authors: Christina Largent, Tazley Hobbs

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Objective: A literature review was performed to examine the existing research on COVID-19 lockdown as it relates to ADHD child/adolescent individuals, media use, and impact on educational performance/learning. It was surmised that with the COVID-19 shut-down and transition to remote learning, a less structured learning environment, increased screen time, in addition to potential difficulty accessing school resources would impair ADHD individuals’ performance and learning. A resulting increase in the number of youths diagnosed and treated for ADHD would be expected. As of yet, there has been little to no published data on the incidence of ADHD as it relates to COVID-19 outside of reports from several nonprofit agencies such as CHADD (Children and Adults with Attention-Deficit/Hyperactivity Disorder ), who reported an increased number of calls to their helpline, The New York based Child Mind Institute, who reported an increased number of appointments to discuss medications, and research released from Athenahealth showing an increase in the number of patients receiving new diagnosis of ADHD and new prescriptions for ADHD medications. Methods: A literature search for articles published between 2020 and 2021 from Pubmed, Google Scholar, PsychInfo, was performed. Search phrases and keywords included “covid, adhd, child, impact, remote learning, media, screen”. Results: Studies primarily utilized parental reports, with very few from the perspective of the ADHD individuals themselves. Most findings thus far show that with the COVID-19 quarantine and transition to online learning, ADHD individuals’ experienced decreased ability to keep focused or adhere to the daily routine, as well as increased inattention-related problems, such as careless mistakes or lack of completion in homework, which in turn translated into overall more difficulty with remote learning. To add further injury, one study showed (just on evaluation of two different sites within the US) that school based services for these individuals decreased with the shift to online-learning. Increased screen time, television, social media, and gaming were noted amongst ADHD individuals. One study further differentiated the degree of digital media, identifying individuals with “problematic “ or “non-problematic” use. ADHD children with problematic digital media use suffered from more severe core symptoms of ADHD, negative emotions, executive function deficits, damage to family environment, pressure from life events, and a lower motivation to learn. Conclusions and Future Considerations: Studies found not only was online learning difficult for ADHD individuals but it, in addition to greater use of digital media, was associated with worsening ADHD symptoms impairing schoolwork, in addition to secondary findings of worsening mood and behavior. Currently, data on the number of new ADHD cases, in addition to data on the prescription and usage of stimulants during COVID-19, has not been well documented or studied; this would be well-warranted out of concern for over diagnosing or over-prescribing our youth. It would also be well-worth studying how reversible or long-lasting these negative impacts may be.

Keywords: COVID-19, remote learning, media use, ADHD, child, adolescent

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Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: Marina Shurupova, Victor Anisimov, Alexander Latanov

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Background: The cerebellar lesions inevitably provoke oculomotor impairments in patients of different age. Symptoms of subtentorial tumors, particularly medulloblastomas, include static and dynamic coordination disorders (ataxia, asynergia, imbalance), hypo-muscle tonus, disruption of the cranial nerves, and within the oculomotor system - nystagmus (fine or gross). Subtentorial tumors can also affect the areas of cerebellum that control the oculomotor system. The noninvasive eye-tracking technology allows obtaining multiple oculomotor characteristics such as the number of fixations and their duration, amplitude, latency and velocity of saccades, trajectory and scan path of gaze during the process of the visual field navigation. Eye tracking could be very useful in clinical studies serving as convenient and effective tool for diagnostics. The aim: We studied the dynamics of oculomotor system functioning in patients undergoing remission from cerebellar tumors removal surgeries and following neurocognitive rehabilitation. Methods: 38 children (23 boys, 15 girls, 9-17 years old) that have recovered from the cerebellar tumor-removal surgeries, radiation therapy and chemotherapy and were undergoing course of neurocognitive rehabilitation participated in the study. Two tests were carried out to evaluate oculomotor performance - gaze stability test and counting test. The monocular eye movements were recorded with eye tracker ArringtonResearch (60 Hz). Two experimental sessions with both tests were conducted before and after rehabilitation courses. Results: Within the final session of both tests we observed remarkable improvement in oculomotor performance: 1) in the gaze stability test the spread of gaze positions significantly declined compared to the first session, and 2) the visual path in counting test significantly shortened both compared to the first session. Thus, neurocognitive rehabilitation improved the functioning of the oculomotor system in patients following the cerebellar tumor removal surgeries and subsequent therapy. Conclusions: The experimental data support the effectiveness of the utilization of the eye tracking technique as diagnostic tool in the field of neurooncology.

Keywords: eye tracking, rehabilitation, cerebellar tumors, oculomotor system

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Authors: Zena F. Mushtaq, Iqbal M. Abbas

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Background: Diabetes mellitus during pregnancy is one of the major medical and social problems with increasing prevalence in last decades and may lead to more vulnerable to dental problems and increased risk for periodontal diseases. Objectives: To assess oral hygiene behaviors among pregnant women with diabetes who attended primary health care centers and find out the relationship between oral hygiene behaviors and studied variables. Methodology: A cross sectional design was conducted from 7 July to 30 September 2014 on non probability (convenient sample) of 150 pregnant women with diabetes was selected from twelve Primary Health Care Centers at Baghdad city. Questionnaire format is tool for data collection which had designed and consisted of three main parts including: socio demographic, reproductive characteristics and items of oral hygiene behaviors among pregnant women with diabetes. Reliability of the questionnaire was determined through internal consistency of correlation coefficient (R= 0.940) and validity of content was determined through reviewing it by (12) experts in different specialties and was determined through pilot study. Descriptive and inferential statistics were used to analyze collected data. Result: Result of study revealed that (35.3%) of study sample was (35-39) years old with mean and SD is (X & SD = 33.57 ± 5.54) years, and (34.7%) of the study sample was graduated from primary school and less, half of the study sample was government employment and self employed, (42.7%) of the study sample had moderate socioeconomic status, the highest percentage (70.0%) of the study sample was nonsmokers, The result indicates that oral hygiene behaviors have moderate mean score in all items. There are no statistical significant association between oral hygiene domain and studied variables. Conclusions: All items related to health behavior concerning oral hygiene is in moderate mean of score, which may expose pregnant women with diabetes to high risk of periodontal diseases. Recommendations: Dental care provider should perform a dental examination at least every three months for each pregnant woman with diabetes, explanation of the effect of DM on periodontal health, oral hygiene instruction, oral prophylaxis, professional cleaning and treatment of periodontal diseases(scaling and root planing) when needed.

Keywords: diabetes, health behavior, pregnant women, oral hygiene

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Andrew Fox, Tao Zhang, Yuanhong Zhao, Qingping Yang

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The furniture manufacturing industry has been slow in general to adopt the latest manufacturing technologies, historically relying heavily upon specialised conventional machinery. This approach not only requires high levels of specialist process knowledge, training, and capital investment but also suffers from significant subtractive manufacturing waste and high logistics costs due to the requirement for centralised manufacturing, with high levels of furniture product not re-cycled or re-used. This paper aims to address the problems by introducing suitable digital manufacturing technologies to create step changes in furniture manufacturing design, as the traditional design practices have been reported as building in 80% of environmental impact. In this paper, a 3D printing robot for furniture manufacturing is reported. The 3D printing robot mainly comprises a KUKA industrial robot, an Arduino microprocessor, and a self-assembled screw fed extruder. Compared to traditional 3D printer, the 3D printing robot has larger motion range and can be easily upgraded to enlarge the maximum size of the printed object. Generative design is also investigated in this paper, aiming to establish a combined design methodology that allows assessment of goals, constraints, materials, and manufacturing processes simultaneously. ‘Matrixing’ for part amalgamation and product performance optimisation is enabled. The generative design goals of integrated waste reduction increased manufacturing efficiency, optimised product performance, and reduced environmental impact institute a truly lean and innovative future design methodology. In addition, there is massive future potential to leverage Single Minute Exchange of Die (SMED) theory through generative design post-processing of geometry for robot manufacture, resulting in ‘mass customised’ furniture with virtually no setup requirements. These generatively designed products can be manufactured using the robot based additive manufacturing. Essentially, the 3D printing robot is already functional; some initial goals have been achieved and are also presented in this paper.

Keywords: additive manufacturing, generative design, robot, sustainability

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Authors: Binbin Chen, Dennis Y. C. Leung

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Aluminium (Al) -air cell holds a high volumetric capacity density of 8.05 Ah cm-3, benefit from the trivalence of Al ions. Additional benefits of Al-air cell are low price and environmental friendliness. Furthermore, the Al energy conversion process is characterized of 100% recyclability in theory. Along with a large base of raw material reserve, Al attracts considerable attentions as a promising material to be integrated within the global energy system. However, despite the early successful applications in military services, several problems exist that prevent the Al-air cells from widely civilian use. The most serious issue is the parasitic corrosion of Al when contacts with electrolyte. To overcome this problem, super-pure Al alloyed with various traces of metal elements are used to increase the corrosion resistance. Nevertheless, high-purity Al alloys are costly and require high energy consumption during production process. An alternative approach is to add inexpensive inhibitors directly into the electrolyte. However, such additives would increase the internal ohmic resistance and hamper the cell performance. So far these methods have not provided satisfactory solutions for the problem within Al-air cells. For the operation of alkaline Al-air cell, there are still other minor problems. One of them is the formation of aluminium hydroxide in the electrolyte. This process decreases ionic conductivity of electrolyte. Another one is the carbonation process within the gas diffusion layer of cathode, blocking the porosity of gas diffusion. Both these would hinder the performance of cells. The present work optimizes the above problems by building an Al-air cell operation system, consisting of four components. A top electrolyte tank containing fresh electrolyte is located at a high level, so that it can drive the electrolyte flow by gravity force. A mechanical rechargeable Al-air cell is fabricated with low-cost materials including low grade Al, carbon paper, and PMMA plates. An electrolyte waste tank with elaborate channel is designed to separate the hydrogen generated from the corrosion, which would be collected by gas collection device. In the first section of the research work, we investigated the performance of the mechanical rechargeable Al-air cell with a constant flow rate of electrolyte, to ensure the repeatability experiments. Then the whole system was assembled together and the feasibility of operating was demonstrated. During experiment, pure hydrogen is collected by collection device, which holds potential for various applications. By collecting this by-product, high utilization efficiency of aluminum is achieved. Considering both electricity and hydrogen generated, an overall utilization efficiency of around 90 % or even higher under different working voltages are achieved. Fluidic electrolyte could remove aluminum hydroxide precipitate and solve the electrolyte deterioration problem. This operation system provides a low-cost strategy for harvesting energy from the abundant secondary Al. The system could also be applied into other metal-air cells and is suitable for emergency power supply, power plant and other applications. The low cost feature implies great potential for commercialization. Further optimization, such as scaling up and optimization of fabrication, will help to refine the technology into practical market offerings.

Keywords: aluminium-air cell, high efficiency, hydrogen, mechanical recharge

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

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A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference to signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: noise signal, pulse interference, signal power, spectrum width, detection

Procedia PDF Downloads 327