Search results for: performance parameter

Authors: T. Mohanarajah, J. Rizk, M. Nagrial, A. Hellany

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This paper analyses numerous features of the synchronous Reluctance Motor (Syn-RM) and propose a rotor for high electrical torque, power factor & efficiency using Finite Element Method (FEM). A comprehensive analysis completed on solid rotor structure while the total thickness of the flux guide kept constant. A number of tests carried out for nine different studies to find out optimum location of the flux guide, the optimum location of multiple flux guides & optimum wall thickness between flux guides for high-performance reluctance machines. The results are concluded with the aid of FEM simulation results, the saliency ratio and machine characteristics (location, a number of barriers & wall width) analysed.

Keywords: electrical machines, finite element method, synchronous reluctance machines, variable reluctance machines

Procedia PDF Downloads 465

Authors: Quoc Van Nguyen, Behzad Fatahi, Aslan S. Hokmabadi

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Performance based seismic design is a modern approach to earthquake-resistant design shifting emphasis from “strength” to “performance”. Soil-Structure Interaction (SSI) can influence the performance level of structures significantly. In this paper, a fifteen storey moment resisting frame sitting on a shallow foundation (footing) with different sizes is simulated numerically using ABAQUS software. The developed three dimensional numerical simulation accounts for nonlinear behaviour of the soil medium by considering the variation of soil stiffness and damping as a function of developed shear strain in the soil elements during earthquake. Elastic-perfectly plastic model is adopted to simulate piles and structural elements. Quiet boundary conditions are assigned to the numerical model and appropriate interface elements, capable of modelling sliding and separation between the foundation and soil elements, are considered. Numerical results in terms of base shear, lateral deformations, and inter-storey drifts of the structure are compared for the cases of soil-structure interaction system with different foundation sizes as well as fixed base condition (excluding SSI). It can be concluded that conventional design procedures excluding SSI may result in aggressive design. Moreover, the size of the foundation can influence the dynamic characteristics and seismic response of the building due to SSI and should therefore be given careful consideration in order to ensure a safe and cost effective seismic design.

Keywords: soil-structure-interaction, seismic response, shallow foundation, abaqus, rayleigh damping

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Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

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In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

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Authors: Rani Danavath, V. B. Narsimha

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Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

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Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Liang Zhao, Chongquan Zhong

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Introduction: According to statistics, people spend 80% to 90% of time indoor, so indoor air quality, either at home or in the office, greatly impacts the quality of life, health and work efficiency. Therefore, indoor air quality is very important to human activities. With the acceleration of urbanization, people are spending more time in indoor activity. The time in indoor environment, the living space, and the frequency interior decoration are all increasingly increased. However, housing decoration materials contain formaldehyde and other harmful substances, causing environmental and air quality problems, which have brought serious damage to countless families and attracted growing attention. According to World Health Organization statistics, the indoor environments in more than 30% of buildings in China are polluted by poisonous and harmful gases. Indoor pollution has caused various health problems, and these widespread public health problems can lead to respiratory diseases. Long-term inhalation of low-concentration formaldehyde would cause persistent headache, insomnia, weakness, palpitation, weight loss and vomiting, which are serious impacts on human health and safety. On the other hand, as for offices, some surveys show that good indoor air quality helps to enthuse the staff and improve the work efficiency by 2%-16%. Therefore, people need to further understand the living and working environments. There is a need for easy-to-use indoor environment monitoring instruments, with which users only have to power up and monitor the environmental parameters. The corresponding real-time data can be displayed on the screen for analysis. Environment monitoring should have the sensitive signal alarm function and send alarm when harmful gases such as formaldehyde, CO, SO2, are excessive to human body. System design: According to the monitoring requirements of various gases, temperature and humidity, we designed a portable, light, real-time and accurate monitor for various environmental parameters, including temperature, humidity, formaldehyde, methane, and CO. This monitor will generate an alarm signal when a target is beyond the standard. It can conveniently measure a variety of harmful gases and provide the alarm function. It also has the advantages of small volume, convenience to carry and use. It has a real-time display function, outputting the parameters on the LCD screen, and a real-time alarm function. Conclusions: This study is focused on the research and development of a portable parameter monitoring instrument for indoor environment. On the platform of an STM32 development board, the monitored data are collected through an external sensor. The STM32 platform is for data acquisition and processing procedures, and successfully monitors the real-time temperature, humidity, formaldehyde, CO, methane and other environmental parameters. Real-time data are displayed on the LCD screen. The system is stable and can be used in different indoor places such as family, hospital, and office. Meanwhile, the system adopts the idea of modular design and is superior in transplanting. The scheme is slightly modified and can be used similarly as the function of a monitoring system. This monitor has very high research and application values.

Keywords: indoor air quality, gas concentration detection, embedded system, sensor

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Authors: Masato Saeki

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Presented herein is a novel algorithms for calculating the damping performance of particle dampers. The particle damper is a passive vibration control technique and has many practical applications due to simple design. It consists of granular materials constrained to move between two ends in the cavity of a primary vibrating system. The damping effect results from the exchange of momentum during the impact of granular materials against the wall of the cavity. This damping has the advantage of being independent of the environment. Therefore, particle damping can be applied in extreme temperature environments, where most conventional dampers would fail. It was shown experimentally in many papers that the efficiency of the particle dampers is high in the case of resonant vibration. In order to use the particle dampers effectively, it is necessary to solve the equations of motion for each particle, considering the granularity. The discrete element method (DEM) has been found to be effective for revealing the dynamics of particle damping. In this method, individual particles are assumed as rigid body and interparticle collisions are modeled by mechanical elements as springs and dashpots. However, the computational cost is significant since the equation of motion for each particle must be solved at each time step. In order to improve the computational efficiency of the DEM, the new algorithms are needed. In this study, new algorithms are proposed for implementing the high performance DEM. On the assumption that behaviors of the granular particles in the each divided area of the damper container are the same, the contact force of the primary system with all particles can be considered to be equal to the product of the divided number of the damper area and the contact force of the primary system with granular materials per divided area. This convenience makes it possible to considerably reduce the calculation time. The validity of this calculation method was investigated and the calculated results were compared with the experimental ones. This paper also presents the results of experimental studies of the performance of particle dampers. It is shown that the particle radius affect the noise level. It is also shown that the particle size and the particle material influence the damper performance.

Keywords: particle damping, discrete element method (DEM), granular materials, numerical analysis, equivalent noise level

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Authors: Mohamed Sanad, Noha Hassan

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A broadband resonant terminal antenna has been developed. It can be used in different MIMO arrangements such as 2x2, 4x4, 8x8, or even 12x12 MIMO configurations. The antenna covers the whole LTE and WiFi bands besides the existing 2G/3G bands (700-5800 MHz), without using any matching/tuning circuits. Matching circuits significantly reduce the efficiency of any antenna and reduce the battery life. They also reduce the bandwidth because they are frequency dependent. The antenna can be implemented in smartphone handsets, tablets, laptops, notebooks or any other terminal. It is also suitable for different IoT and vehicle applications. The antenna is manufactured from a flexible material and can be bent or folded and shaped in any form to fit any available space in any terminal. It is self-contained and does not need to use the ground plane, the chassis or any other component of the terminal. Hence, it can be mounted on any terminal at different positions and configurations. Its performance does not get affected by the terminal, regardless of its type, shape or size. Moreover, its performance does not get affected by the human body of the terminal’s users. Because of all these unique features of the antenna, multiples of them can be simultaneously used for MIMO diversity coverage in any terminal device with a high isolation and a low correlation factor between them.

Keywords: IOT, LTE, MIMO, terminal antenna, WiFi

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Authors: Adrian Kong, William Chang, Rolando Valdes, Alec Rodriguez, Roberto Miki

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The Pneumask consists of a custom snorkel-specific adapter that attaches a snorkel-port of the mask to a 3D-printed filter. This full-face snorkel mask was designed for use as personal protective equipment (PPE) during the COVID-19 pandemic when there was a widespread shortage of PPE for medical personnel. Various clinical validation tests have been conducted, including the sealing capability of the mask, filter performance, CO2 buildup, and clinical usability. However, data regarding the filter efficiencies of Pneumask and multiple filter types have not been determined. Using an experimental system, we evaluated the filtration efficiency across various masks and filters during inhalation. Eighteen combinations of respirator models (5 P100 FFRs, 4 Dolfino Masks) and filters (2091, 7093, 7093CN, BB50T) were evaluated for their exposure to airborne particles sized 0.3 - 10.0 microns using an electronic airborne particle counter. All respirator model combinations provided similar performance levels for 1.0-micron, 3.0-micron, 5.0-micron, 10.0-microns, with the greatest differences in the 0.3-micron and 0.5-micron range. All models provided expected performances against all particle sizes, with Class P100 respirators providing the highest performance levels across all particle size ranges. In conclusion, the modified snorkel mask has the potential to protect providers who care for patients with COVID-19 from increased airborne particle exposure.

Keywords: COVID-19, PPE, mask, filtration, efficiency

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Authors: Kati Skarp, Keijo Varis, Juha Kettunen

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The purpose of this paper is to examine and evaluate the top-down and bottom-up leadership development programs focused on human capital that improve the performance of a company. This study reports on the external top-down leadership development program supported by a consulting company and the internal participatory action research of the bottom-up program. The sickness rate and the lost time incident failure rate decreased and the ideas produced for cost savings improved, leading to increased earnings during the top-down program. The estimated cost savings potential of the bottom-up program was 3.8 million euro based on the cost savings of meeting habits, maintenance practices and the way of working in production. The results of this study are useful for those who plan and evaluate leadership development and human capital productivity consultation programs to improve the performance of a company.

Keywords: leadership, development, human resources, company, indicators, evaluation

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Authors: Liyew Yizengaw Yitayih

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This nanotechnology study focuses on how potassium ions (K+) affect lithium-ion (Li-ion) battery performance. By adding potassium ions (K+) to the lithium tin oxide (LiSnO) anode and employing styrene-butadiene rubber (SBR) as a binder, the doping of K+ was specifically studied. The methods employed in this study include computer modeling and simulation, material fabrication, and electrochemical characterization. The potassium ions (Li+) were successfully doped into the LiSnO lattice during charge/discharge cycles, which increased the lithium-ion diffusivity and electrical conductivity within the anode. However, it was found that internal doping of potassium ions (K+) into the LiSnO lattice occurred at high potassium ion concentrations (>16.6%), which hampered lithium ion transfer because of repulsion and physical blockage. The electrochemical efficiency of lithium-ion batteries was improved by this comprehensive study's presentation of potassium ions' (K+) potential advantages when present in the appropriate concentrations in electrode materials.

Keywords: lithium-ion battery, LiSnO anode, potassium doping, lithium-ion diffusivity, electronic conductivity

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Authors: Ghassan Al-Dulaimi

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This paper studied the biochemical parameter (BOD5) and (DO) for the Thames River (Canada-Ontario). Water samples have been collected from Thames River along different points between Chatham to Woodstock and were analysed for various water quality parameters during the low flow season (April). The study involves the application of the stream water quality model QUAL2K model to simulate and predict the dissolved oxygen (DO) and biochemical oxygen demand (BOD5) profiles for Thames River in a stretch of 251 kilometers. The model output showed that DO in the entire river was within the limit of not less than 4 mg/L. For Carbonaceous Biochemical Oxygen Demand CBOD, the entire river may be divided into two main reaches; the first one is extended from Chatham City (0 km) to London (150 km) and has a CBOD concentration of 2 mg/L, and the second reach has CBOD range (2–4) mg/L in which begins from London city and extend to near Woodstock city (73km).

Keywords: biochemical oxygen demand, dissolved oxygen, Thames river, QUAL2K model

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Authors: Alena Kulikova, Leonid Parmaksiz, Ekaterina Orel

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Social and emotional skills are considered by modern researchers as predictors of a person's success both in specific areas of activity and in the life of a person as a whole. The popularity of this scientific direction ensures the emergence of a large number of practices aimed at developing and evaluating socio-emotional skills. Assessment of social and emotional development is carried out at the national level, as well as at the level of individual regions and institutions. Despite the fact that many of the already existing social and emotional skills assessment tools are quite convenient and reliable, there are now more and more new technologies and task formats which improve the basic characteristics of the tools. Thus, the goal of the current study is to develop a tool for assessing social and emotional skills such as emotion recognition, emotion regulation, empathy and a culture of self-care. To develop a tool assessing social and emotional skills, Rasch-Gutman scenario-based approach was used. This approach has shown its reliability and merit for measuring various complex constructs: parental involvement; teacher practices that support cultural diversity and equity; willingness to participate in the life of the community after psychiatric rehabilitation; educational motivation and others. To assess emotion recognition, we used a situational judgment task based on OCC (Ortony, Clore, and Collins) emotions theory. The main advantage of these two approaches compare to classical Likert scales is that it reduces social desirability in answers. A field test to check the psychometric properties of the developed instrument was conducted. The instrument was developed for the presidential autonomous non-profit organization “Russia - Land of Opportunity” for nationwide soft skills assessment among higher education students. The sample for the field test consisted of 500 people, students aged from 18 to 25 (mean = 20; standard deviation 1.8), 71% female. 67% of students are only studying and are not currently working and 500 employed adults aged from 26 to 65 (mean = 42.5; SD 9), 57% female. Analysis of the psychometric characteristics of the scales was carried out using the methods of IRT (Item Response Theory). A one-parameter rating scale model RSM (Rating scale model) and Graded Response model (GRM) of the modern testing theory were applied. GRM is a polyatomic extension of the dichotomous two-parameter model of modern testing theory (2PL) based on the cumulative logit function for modeling the probability of a correct answer. The validity of the developed scales was assessed using correlation analysis and MTMM (multitrait-multimethod matrix). The developed instrument showed good psychometric quality and can be used by HR specialists or educational management. The detailed results of a psychometric study of the quality of the instrument, including the functioning of the tasks of each scale, will be presented. Also, the results of the validity study by MTMM analysis will be discussed.

Keywords: social and emotional skills, psychometrics, MTMM, IRT

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Authors: M. Manjunath, R. Rakesh, Y. T. Krishne Gowda, G. Panduranga Murthy

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The availability of energy resources plays a vital role in the progress of a country. Over the last decades, there is an increase in the consumption of energy worldwide resulting in the depletion of fossil fuels. This necessitates dependency on other countries for energy resources. Therefore, a renewable eco-friendly alternate fuel is replaced in place of fossil fuel which can be vegetable oils as a substitute fuel for diesel. Since oils are more viscous it cannot be used directly in CI engines without any engine modification. Thus, a conversion of vegetable oils to biodiesel is done by a Transesterification process. The present paper is restricted to Biofuel substitute for diesel and which can be obtained from a number of edible and non-edible oil resources. The oil from these resources can be Transesterified by a suitable method depending on its FFA content for the production of biodiesel and that can be used to operate CI engine. In this work, an attempt is made to test the performance of CI engine using Transesterified peanut and sunflower oil methyl esters blends with diesel.

Keywords: SOME, POME, BMEP, BSFC, BTE

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

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Authors: Khosru M. Salim, Md. Jasim Uddin, Mohammad Rejwan Uddin

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Developing countries like Bangladesh has huge population lives in the rural areas out of electricity. They are using manually operated tube well for collecting underground water to meet their daily demand. A human labour is required to lift water from tube well. Sometimes, it is impossible for a elementary school going child to operate a tube well in the school. Solar powered water pump could be a sustainable water pumping solution in the rural area of Bangladesh. To minimize the cost, a 0.5 horse power solar water pump is designed considering the requirement of water for a typical house hold in this research. A prototype of the 0.5 hp capacity system is implemented and tested in the rooftop of the university lab to validate the performances. Based on the experimental data, the performance of the system is analyzed and presented in this paper.

Keywords: water pump, solar photovoltaic module, performance analysis, feasibility study

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: Mohammad Shams Esfand Abadi, Mohammad Ranjbar, Reza Ebrahimpour

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This work presents the distributed processing solution problem in a diffusion network based on the adapt then combine (ATC) and combine then adapt (CTA)selective partial update normalized least mean squares (SPU-NLMS) algorithms. Also, we extend this approach to dynamic selection affine projection algorithm (DS-APA) and ATC-DS-APA and CTA-DS-APA are established. The purpose of ATC-SPU-NLMS and CTA-SPU-NLMS algorithm is to reduce the computational complexity by updating the selected blocks of weight coefficients at every iteration. In CTA-DS-APA and ATC-DS-APA, the number of the input vectors is selected dynamically. Diffusion cooperation strategies have been shown to provide good performance based on these algorithms. The good performance of introduced algorithm is illustrated with various experimental results.

Keywords: selective partial update, affine projection, dynamic selection, diffusion, adaptive distributed networks

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Authors: Feng-Tsai Weng, Dong- Syuan Cai, Tsochu-Lin

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A vehicle gasoline engine converts gasoline into power so that the car can move, and lubricants are important for engines and also gear boxes. Manufacturers have produced numbers of engine oils, and gear oils for engines and gear boxes to SAE International Standards. Some products not only can improve the lubrication of both the engine and gear box but also can raise power of vehicle this can be easily seen in the advertisement declared by the manufacturers. To observe the lubrication performance, a multi-leveled (heavy duty) gear oil was added to a gasoline engine as the oil in the vehicle. The oil was checked at about every 10,000 kilometers. The engine was detailed disassembled, cleaned, and parts were measured. The wear of components of the engine parts were checked and recorded finally. Based on the experiment results, some gear oil seems possible to be used as engine oil in particular vehicles. Vehicle owners should change oil periodically in about every 6,000 miles (or 10,000 kilometers). Used car owners may change engine oil in even longer distance.

Keywords: multi-level gear oil, engine oil, viscosity, abrasion

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Authors: Brandtner-Hafner Martin

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Adhesives have established themselves as an innovative joining technology in the industry. Their strengths lie in joining different materials, avoiding structural weakening as in welding or screwing, and enabling lightweight construction methods. Now there are a variety of ways to improve the efficiency and effectiveness of bonded joints. One way is to add fiber fillers. This leads to an improvement in adhesion and cohesion (structural integrity). In this study, the effectiveness of fiber-modified adhesives for bonding different construction materials is reviewed. A series of experimental tests were performed using the fracture analytical GF principle to study the adhesive bonding safety and performance of the joint. Three different structural adhesive systems based on epoxy, CA/A hybrid, and PUR were modified with different fiber materials on different substrates. The results show that significant performance improvements can be achieved and that bonding reliability can be sustainably increased.

Keywords: fiber-modified adhesives, bonding safety, GF-principle, fracture analysis

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Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

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The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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Authors: Mohammad Hadi Khorashadi Zadeh

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Many new applications and internet services have been emerged since the innovation of mobile networks and devices. However, these applications have problems of security, management, and performance in business environments. Cloud systems provide information transfer, management facilities, and security for virtual environments. Therefore, an innovative internet service and a business model are proposed in the present study for creating a secure and consolidated environment for managing the mobile information of organizations based on cloud virtual phones (CVP) infrastructures. Using this method, users can run Android and web applications in the cloud which enhance performance by connecting to other CVP users and increases privacy. It is possible to combine the CVP with distributed protocols and central control which mimics the behavior of human societies. This mix helps in dealing with sensitive data in mobile devices and facilitates data management with less application overhead.

Keywords: BYOD, mobile cloud computing, mobile security, information management

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Authors: Awni H. Alkhazaleh, Baljinder K. Kandola

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In this study, a form-stable composite Paraffin/Nanoclay (PA-NC) has been prepared by absorbing PA into porous particles of NC to be used for low-temperature latent heat thermal energy storage. The leakage test shows that the maximum mass fraction of PA that can be incorporated in NC without leakage is 60 wt.%. Differential scanning calorimetry (DSC) has been used to measure the thermal properties of the PA and PA-NC both before and after incorporation in plasterboard (PL). The mechanical performance of the samples has been evaluated in flexural mode. The thermal energy storage performance has been studied using a small test chamber (100 mm × 100 mm × 100 mm) made from 10 mm thick PL and measuring the temperatures using thermocouples. The flammability of the PL+PL-NC has been discussed using a cone calorimeter. The results indicate that the form composite PA has good potential for use as thermal energy storage materials in building applications.

Keywords: building materials, flammability, phase change materials, thermal energy storage

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Authors: Shieh Shiow-fang

Abstract:

Superstitious thoughts or actions often occur during athletic competitions. Often "superstitious rituals" have a positive impact on the performance of competitive athletes. Athletes affirm the many psychological benefits of religious beliefs mostly in a positive way. Method: By snowball sampling, we recruited 10 experienced competitive athletes as participants. We used in-person and online one-to-one in-depth interview to collect their experiences about sport superstition. The total interview time was 795 minutes. We analyzed the raw data with the grounded theory processes suggested by Strauss and Corbin (1990). Results: The factors affecting athlete performance are ritual beliefs, taboo awareness, learning norms, and spontaneous attribution behaviors. Conclusion: We concluded that sports superstition reflects several psychological implications. The analysis results of this paper can provide another research perspective for the future study of sports superstition behavior.

Keywords: superstition, taboo awareness, learning norms, competitive athlete

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

Abstract:

Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Naime Boudemagh, Zoheir Hammoudi

Abstract:

The parameters estimation of the K-distribution is an essential part in radar detection. In fact, presence of interfering targets in reference cells causes a decrease in detection performances. In such situation, the estimate of the shape and the scale parameters are far from the actual values. In the order to avoid interfering targets, we propose an Automatic Censoring (AC) algorithm of radar interfering targets in K-distribution. The censoring technique used in this work offers a good discrimination between homogeneous and non-homogeneous environments. The homogeneous population is then used to estimate the unknown parameters by the classical Method of Moment (MOM). The AC algorithm does not need any prior information about the clutter parameters nor does it require both the number and the position of interfering targets. The accuracy of the estimation parameters obtained by this algorithm are validated and compared to various actual values of the shape parameter, using Monte Carlo simulations, this latter show that the probability of censing in multiple target situations are in good agreement.

Keywords: parameters estimation, method of moments, automatic censoring, K distribution

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Authors: Atiqa Marium

Abstract:

In 2015, all 193 UN Member countries adopted the 2030 Agenda for Sustainable Development, which is an ambitious 15- year plan to address some of the most pressing issues the world faces. Goal 4 is about Quality Education which highlights the importance of inclusive and quality education for sustainable development. Sustainable Development Goal 10 focuses on reducing inequalities within and among countries. In June 2019, Federal Government in Canada released “Towards Canada’s 2030 Agenda National Strategy”, which was an important step to move the 2030 Agenda forward. In April 2019, the Ontario government announced the performance-based funding model for publically assisted colleges and universities in Ontario, which is now part of the universities’ budget 2024-2025. The literature review has shown that the funding model has been implemented by different governments to achieve objectives. However, this model has also resulted in conflicting consequences like reducing university autonomy, education quality/ academic standards, and increased equity concerns. The primary focus of this paper will be to analyze the tensions and coherence between the proposed funding model for education for sustainable development goals and targets set by Canada’s 2030 Agenda National Strategy. Considering that the literature review has provided evidence that the performance-based funding model has resulted in reducing quality of education and increased equity issues in other countries, it will be interesting to see how this proposed funding will align with the SDGs of “Quality Education” and “Reduced Inequalities”. This paper will be well-suited for Volume 4, with the theme of re-visioning institutional impact and sustainability. This paper will underscore the importance of policy coherence between federal and provincial policies for higher education institutions in Ontario for better institutional impact and helping universities in the attainment of goals set in 2030 Agenda towards education for sustainable development.

Keywords: performance-based funding model, education for sustainable development, policy coherence, sustainable development gaols

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Authors: Farrukh Javed, Krzysztof Podgórski

Abstract:

We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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Authors: Mohamed H. Gabr, Kiyoshi Uzawa

Abstract:

The current study aims to investigate the effect of fillers with different geometries and sizes on the interfacial shear properties of PA6 composites with de-sized carbon fiber. The fillers which have been investigated are namely; nano-layer silicates (nanoclay), sub-micro aluminum titanium (ALTi) particles, and multiwall carbon nanotube (MWCNT). By means of X-ray photoelectron spectroscopy (XPS), epoxide group which defined as a sizing agent, has been removed. Sizing removal can reduce the acid parameter of carbon fibers surface promoting bonding strength at the fiber/matrix interface which is a desirable property for the carbon fiber composites. Microdroplet test showed that the interfacial shear strength (IFSS) has been enhanced with the addition of 10wt% ALTi by about 23% comparing with neat PA6. However, with including other types of fillers into PA6, the results did not show enhancement of IFSS.

Keywords: sub-micro particles, nano-composites, interfacial shear strength, polyamide 6

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Authors: Y. M. Aiyesimi, G. T. Okedayo, O. W. Lawal

Abstract:

The analysis has been carried out to study unsteady MHD thin film flow of a third grade fluid down an inclined plane with heat transfer when the slippage between the surface of plane and the lower surface of the fluid is valid. The governing nonlinear partial differential equations involved are reduced to linear partial differential equations using regular perturbation method. The resulting equations were solved analytically using method of separation of variable and eigenfunctions expansion. The solutions obtained were examined and discussed graphically. It is interesting to find that the variation of the velocity and temperature profile with the slip and magnetic field parameter depends on time.

Keywords: non-Newtonian fluid, MHD flow, thin film flow, third grade fluid, slip boundary condition, heat transfer, separation of variable, eigenfunction expansion

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