Search results for: thermal error

Authors: Pakinee Pooprasert, Wanxin Wang, Tina Parmar, Dana Ahnood, Tafadzwa Young-Zvandasara, James Morgan

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Homelessness has been shown to be correlated to poor health outcomes, including increased visual health morbidity. Despite this, there are relatively few studies regarding visual health in the homeless population, especially in the UK. This research aims to investigate visual disability and access barriers prevalent in the homeless population in Cardiff, South Wales. Data was collected from 100 homeless participants in three different shelters. Visual outcomes included near and distance visual acuity as well as non-cycloplegic refraction. Qualitative data was collected via a questionnaire and included socio-demographic profile, ocular history, subjective visual acuity and level of access to healthcare facilities. Based on the participants’ presenting visual acuity, the total prevalence of myopia and hyperopia was 17.0% and 19.0% respectively based on spherical equivalent from the eye with the greatest absolute value. The prevalence of astigmatism was 8.0%. The mean absolute spherical equivalent was 0.841D and 0.853D for right and left eye respectively. The number of participants with sight loss (as defined by VA= 6/12-6/60 in the better-seeing eye) was 27.0% in comparison to 0.89% and 1.1% in the general Cardiff and Wales population respectively (p-value is < 0.05). Additionally, 1.0% of the homeless subjects were registered blind (VA less than 3/60), in comparison to 0.17% for the national consensus after age standardization. Most participants had good knowledge regarding access to prescription glasses and eye examination services. Despite this, 85.0% never had their eyes examined by a doctor and 73.0% had their last optometrist appointment in more than 5 years. These findings suggested that there was a significant disparity in ocular health, including visual acuity and refractive error amongst the homeless in comparison to the general population. Further, the homeless were less likely to receive the same level of support and continued care in the community due to access barriers. These included a number of socio-economic factors such as travel expenses and regional availability of services, as well as administrative shortcomings. In conclusion, this research demonstrated unmet visual health needs within the homeless, and that inclusive policy changes may need to be implemented for better healthcare outcomes within this marginalized community.

Keywords: homelessness, refractive error, visual disability, Wales

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Authors: Georgi Bebrov, Rozalina Dimova

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In the field of quantum secure communication, there is no evaluation that characterizes quantum secure communication (QSC) protocols in a complete, general manner. The current paper addresses the problem concerning the lack of such an evaluation for QSC protocols by introducing an optimality evaluation, which is expressed as the average over the three main parameters of QSC protocols: efficiency, security, and practicality. For the efficiency evaluation, the common expression of this parameter is used, which incorporates all the classical and quantum resources (bits and qubits) utilized for transferring a certain amount of information (bits) in a secure manner. By using criteria approach whether or not certain criteria are met, an expression for the practicality evaluation is presented, which accounts for the complexity of the QSC practical realization. Based on the error rates that the common quantum attacks (Measurement and resend, Intercept and resend, probe attack, and entanglement swapping attack) induce, the security evaluation for a QSC protocol is proposed as the minimum function taken over the error rates of the mentioned quantum attacks. For the sake of clarity, an example is presented in order to show how the optimality is calculated.

Keywords: quantum cryptography, quantum secure communcation, quantum secure direct communcation security, quantum secure direct communcation efficiency, quantum secure direct communcation practicality

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Authors: M. Haghnegahdar, G. Naderi, M. H. R. Ghoreishy

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Polypropylene(PP)/Ethylene Propylene Diene Monomer (EPDM) samples (80/20) containing 0, 0.5, 1, 1.5, 2, 2.5, and 3 (expressed in mass fraction) graphene were prepared using melt compounding method to investigate microstructure, mechanical properties, and thermal stability as well as electrical resistance of samples. X-Ray diffraction data confirmed that graphene platelets are well dispersed in PP/EPDM. Mechanical properties such as tensile strength, impact strength and hardness demonstrated increasing trend by graphene loading which exemplifies substantial reinforcing nature of this kind of nano filler and it's good interaction with polymer chains. At the same time it is found that thermo-oxidative degradation of PP/EPDM nanocomposites is noticeably retarded with the increasing of graphene content. Electrical surface resistivity of the nanocomposite was dramatically changed by forming electrical percolation threshold and leads to change electrical behavior from insulator to semiconductor. Furthermore, these results were confirmed by scanning electron microscopy(SEM), dynamic mechanical thermal analysis (DMTA), and transmission electron microscopy (TEM).

Keywords: nanocomposite, graphene, microstructure, mechanical properties

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Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.

Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: wavelet transform, computational error, computational duration, strong ground motion data

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Authors: Saca Nastasia, Radu Lidia, Dobre Daniela, Calotă Razvan

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In order to achieve the European Union's sustainable and circular economy goals, strategies for reducing raw material consumption, reusing waste, and lowering CO₂ emissions have been developed. In this study, expanded perlite mortars with recycled cement (RC) were obtained and characterized. The recycled cement was obtained from demolition concrete waste. The concrete waste was crushed in a jaw and grinded in a horizontal ball mill to reduce the material's average grain size. Finally, the fine particles were sieved through a 125 µm sieve. The recycled cement was prepared by heating demolition concrete waste at 550°C for 3 hours. At this temperature, the decarbonization does not occur. The utilization of recycled cement can minimize the negative environmental effects of demolished concrete landfills as well as the demand for natural resources used in cement manufacturing. Commercial cement CEM II/A-LL 42.5R was substituted by 10%, 20%, and 30% recycled cement. By substituting reference cement (CEM II/A-LL 42.5R) by RC, a decrease in cement aqueous suspension pH, electrical conductivity, and Ca²⁺ concentration was observed for all measurements (2 hours, 6 hours, 24 hours, 4 days, and 7 days). After 2 hours, pH value was 12.42 for reference and conductivity of 2220 µS/cm and decreased to 12.27, respectively 1570 µS/cm for 30% RC. The concentration of Ca²⁺ estimated by complexometric titration was 20% lower in suspension with 30% RC in comparison to reference for 2 hours. The difference significantly diminishes over time. The mortars have cement: expanded perlite volume ratio of 1:3 and consistency between 140 mm and 200 mm. The density of fresh mortar was about 1400 kg/m3. The density, flexural and compressive strengths, water absorption, and thermal conductivity of hardened mortars were tested. Due to its properties, expanded perlite mortar is a good thermal insulation material.

Keywords: concrete waste, expanded perlite, mortar, recycled cement, thermal conductivity, mechanical strength

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Authors: Sara Sallam, Mohamed Taqi, Naoual Belouaggadia

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Solar thermal power plants using parabolic trough collectors (PTC) are currently a powerful technology for generating electricity. Most of these solar power plants use thermal oils as heat transfer fluid. The latter is heated in the solar field and transfers the heat absorbed in an oil-water heat exchanger for the production of steam driving the turbines of the power plant. Currently, we are seeking to develop PTCs with direct steam generation (DSG). This process consists of circulating water under pressure in the receiver tube to generate steam directly into the solar loop. This makes it possible to reduce the investment and maintenance costs of the PTCs (the oil-water exchangers are removed) and to avoid the environmental risks associated with the use of thermal oils. The pressure drops in these systems are an important parameter to ensure their proper operation. The determination of these losses is complex because of the presence of the two phases, and most often we limit ourselves to describing them by models using empirical correlations. A comparison of these models with experimental data was performed. Our calculations focused on the evolution of the pressure of the liquid-vapor mixture along the receiver tube of a PTC-DSG for pressure values and inlet flow rates ranging respectively from 3 to 10 MPa, and from 0.4 to 0.6 kg/s. The comparison of the numerical results with experience allows us to demonstrate the validity of some models according to the pressures and the flow rates of entry in the PTC-DSG receiver tube. The analysis of these two parameters’ effects on the evolution of the pressure along the receiving tub, shows that the increase of the inlet pressure and the decrease of the flow rate lead to minimal pressure losses.

Keywords: direct steam generation, parabolic trough collectors, Ppressure drop, empirical models

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Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: Mina Rouhollahi, J. Boland

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Changes in cities’ heat balance due to rapid urbanization and the urban heat island (UHI) have increased energy demands for space cooling and have resulted in uncomfortable living conditions for urban residents. Climate resilience and comfortable living spaces can be addressed through well-designed urban development. The sustainable housing can be more effective in controlling high levels of urban heat. In Australia, to mitigate the effects of UHIs and summer heat waves, one solution to sustainable housing has been the trend to compact housing design and the construction of energy efficient dwellings. This paper analyses whether current housing configurations and orientations are effective in avoiding increased demands for air conditioning and having an energy efficient residential neighborhood. A significant amount of energy is consumed to ensure thermal comfort in houses. This paper reports on the modelling of heat transfer within the homes using the measurements of radiation, convection and conduction between exterior/interior wall surfaces and outdoor/indoor environment respectively. The simulation was tested on selected 7.5-star energy efficient houses constructed of typical material elements and insulation in Adelaide, Australia. The chosen design dwellings were analyzed in extremely hot weather through one year. The data were obtained via a thermal circuit to accurately model the fundamental heat transfer mechanisms on both boundaries of the house and through the multi-layered wall configurations. The formulation of the Lumped capacitance model was considered in discrete time steps by adopting a non-linear model method. The simulation results focused on the effects of orientation of the solar radiation on the dynamic thermal characteristics of the houses orientations. A high star rating did not necessarily coincide with a decrease in peak demands for cooling. A more effective approach to avoid increasing the demands for air conditioning and energy may be to integrate solar–climatic data to evaluate the performance of energy efficient houses.

Keywords: energy-efficient residential building, heat transfer, neighborhood orientation, solar–climatic data

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Authors: Burak Kaplan, Ünver Kaynak

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Gas turbine engines, crucial for modern aviation and power generation, rely on the efficient operation of turbine blades. However, extreme temperatures and pressures can lead to material degradation and failure. Film cooling, a widely employed technique, injects a coolant onto the blade surface to mitigate the effects of hot gas exposure. This research investigates the impact of film cooling on gas turbine engine performance, focusing on its influence on efficiency, longevity, and overall engine performance. Through a comprehensive literature review, computational fluid dynamics simulations, and thermal performance analysis, this study aims to provide insights into optimizing film cooling configurations for enhanced engine performance. The research explores the thermal performance characteristics of turbine blades with and without film cooling, the influence of various film cooling techniques on engine efficiency, and the design factors that optimize film cooling effectiveness. The findings of this study have the potential to contribute to the development of more efficient and reliable gas turbine engines, ultimately advancing the field of gas turbine technology.

Keywords: gas turbine, engine, cooling, blade, optimization

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Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

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Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

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Authors: Budihardjo Sarwo Sastrosudiro, Arnas Lubis, Muhammad Idrus Alhamid, Nasruddin Jusuf

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Solar thermal cooling system was installed on Mechanical Research Center (MRC) Building that is located in Universitas Indonesia, Depok, Indonesia. It is the first cooling system in Indonesia that utilizes solar energy as energy input combined with natural gas; therefore, the control system must be appropriated with the climates. In order to stabilize the cooling capacity and also to maximize the use of solar energy, the system applies some controllers. Constant flow rate and on/off controller are applied for the hot water, chilled water and cooling water pumps. The hot water circulated by pump when the solar radiation is over than 400W/m², and the chilled water is continually circulated by pump and its temperature is kept constant 7 °C by absorption chiller. The cooling water is also continually circulated until the outlet temperature of cooling tower below than 27 ^oC. Furthermore, the three-way valve is used to control the hot water for generate vapor on absorption chiller. The system performance using that control system is shown in this study results.

Keywords: absorption chiller, control system, solar cooling, solar energy

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Authors: Dojoon Jung, Kiwoong Moon, Joong Lee

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The height of criminals is one of the important clues that can determine the scope of the suspect's search or exclude the suspect from the search target. Although measuring the height of criminals by video alone is limited by various reasons, the 3D data of the scene and the Closed Circuit Television (CCTV) footage are matched, the height of the criminal can be measured. However, it is still difficult to measure the height of CCTV footage in the non-contact type measurement method because of variables such as position, posture, and head shape of criminals. In this paper, we propose a method of matching the CCTV footage with the 3D data on the crime scene and measuring the height of the person using the 3D human body model in the matched data. In the proposed method, the height is measured by using 3D human model in various scenes of the person in the CCTV footage, and the measurement value of the target person is corrected by the measurement error of the replay CCTV footage of the reference person. We tested for 20 people's walking CCTV footage captured from an indoor and an outdoor and corrected the measurement values with 5 reference persons. Experimental results show that the measurement error (true value-measured value) average is 0.45 cm, and this method is effective for the measurement of the person's height in CCTV footage.

Keywords: human height, CCTV footage, 2D/3D matching, 3D human body model

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Authors: Milad Yousefi, Moslem Yousefi, Ricarpo Poley, Amer Nordin Darus

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Design optimization of heat exchangers is a very complicated task that has been traditionally carried out based on a trial-and-error procedure. To overcome the difficulties of the conventional design approaches especially when a large number of variables, constraints and objectives are involved, a new method based on a well-stablished evolutionary algorithm, particle swarm optimization (PSO), weighted sum approach and a novel constraint handling strategy is presented in this study. Since, the conventional constraint handling strategies are not effective and easy-to-implement in multi-objective algorithms, a novel feasibility-based ranking strategy is introduced which is both extremely user-friendly and effective. A case study from industry has been investigated to illustrate the performance of the presented approach. The results show that the proposed algorithm can find the near pareto-optimal with higher accuracy when it is compared to conventional non-dominated sorting genetic algorithm II (NSGA-II). Moreover, the difficulties of a trial-and-error process for setting the penalty parameters is solved in this algorithm.

Keywords: Heat exchanger, Multi-objective optimization, Particle swarm optimization, NSGA-II Constraints handling.

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Authors: Jasvinder Singh, Manjinder Singh

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Welding of dissimilar materials is a complicated process due to the difference in melting point of two materials. Thermal conductivity and coefficient of thermal expansion of dissimilar materials also different; therefore, residual stresses produced in the weldment and base metal are the most critical problem associated with the joining of dissimilar materials. Tensile strength and impact toughness also reduced due to the residual stresses. In the present research work, an attempt has been made to weld SS304 and MS1018 dissimilar materials by submerged arc welding (SAW). By conducting trail, runs most effective parameters welding current, Arc voltage, welding speed and nozzle to plate distance were selected to weld these materials. The fractional factorial technique was used to optimize the welding parameters. Effect on tensile strength (TS), fracture toughness (FT) and microhardness of weldment were studied. It was concluded that by optimizing welding current, voltage and welding speed the properties of weldment can be enhanced.

Keywords: SAW, Tensile Strength (TS), fracture toughness, micro hardness

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Authors: German Osma, Gabriel Ordonez

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The production of metal-rubber spares for vehicles is a sequential process that consists in the transformation of raw material through cutting activities and chemical and thermal treatments, which demand electricity and fossil fuels. The energy efficiency analysis for these cases is mostly focused on studying of each machine or production step, but is not common to study of the quality of the production process achieves from aggregated value viewpoint, which can be used as a quality measurement for determining of impact on the environment. In this paper, the theory of exergetic cost is used for determining of aggregated exergy to three metal-rubber spares, from an exergy analysis and thermoeconomic analysis. The manufacturing processing of these spares is based into batch production technique, and therefore is proposed the use of this theory for discontinuous flows from of single models of workstations; subsequently, the complete exergy model of each product is built using flowcharts. These models are a representation of exergy flows between components into the machines according to electrical, mechanical and/or thermal expressions; they determine the demanded exergy to produce the effective transformation in raw materials (aggregated exergy value), the exergy losses caused by equipment and irreversibilities. The energy resources of manufacturing process are electricity and natural gas. The workstations considered are lathes, punching presses, cutters, zinc machine, chemical treatment tanks, hydraulic vulcanizing presses and rubber mixer. The thermoeconomic analysis was done by workstation and by spare; first of them describes the operation of the components of each machine and where the exergy losses are; while the second of them estimates the exergy-aggregated value for finished product and wasted feedstock. Results indicate that exergy efficiency of a mechanical workstation is between 10% and 60% while this value in the thermal workstations is less than 5%; also that each effective exergy-aggregated value is one-thirtieth of total exergy required for operation of manufacturing process, which amounts approximately to 2 MJ. These troubles are caused mainly by technical limitations of machines, oversizing of metal feedstock that demands more mechanical transformation work, and low thermal insulation of chemical treatment tanks and hydraulic vulcanizing presses. From established information, in this case, it is possible to appreciate the usefulness of theory of exergetic cost for analyzing of aggregated value in manufacturing processes.

Keywords: exergy-aggregated value, exergy efficiency, thermoeconomics, exergy modeling

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Authors: Sairi Satari

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Introduction: Six-sigma is a metric that quantifies the performance of processes as a rate of Defects-Per-Million Opportunities. Sigma methodology can be applied in chemical pathology laboratory for evaluating process performance with evidence for process improvement in quality assurance program. In the laboratory, these methods have been used to improve the timeliness of troubleshooting, reduce the cost and frequency of quality control and minimize pre and post-analytical errors. Aim: The aim of this study is to evaluate the sigma values of the Cobas 8000 analyzer based on the minimum requirement of the specification. Methodology: Twenty-one analytes were chosen in this study. The analytes were alanine aminotransferase (ALT), albumin, alkaline phosphatase (ALP), Amylase, aspartate transaminase (AST), total bilirubin, calcium, chloride, cholesterol, HDL-cholesterol, creatinine, creatinine kinase, glucose, lactate dehydrogenase (LDH), magnesium, potassium, protein, sodium, triglyceride, uric acid and urea. Total error was obtained from Clinical Laboratory Improvement Amendments (CLIA). The Bias was calculated from end cycle report of Royal College of Pathologists of Australasia (RCPA) cycle from July to December 2016 and coefficient variation (CV) from six-month internal quality control (IQC). The sigma was calculated based on the formula :Sigma = (Total Error - Bias) / CV. The analytical performance was evaluated based on the sigma, sigma > 6 is world class, sigma > 5 is excellent, sigma > 4 is good and sigma < 4 is satisfactory and sigma < 3 is poor performance. Results: Based on the calculation, we found that, 96% are world class (ALT, albumin, ALP, amylase, AST, total bilirubin, cholesterol, HDL-cholesterol, creatinine, creatinine kinase, glucose, LDH, magnesium, potassium, triglyceride and uric acid. 14% are excellent (calcium, protein and urea), and 10% ( chloride and sodium) require more frequent IQC performed per day. Conclusion: Based on this study, we found that IQC should be performed frequently for only Chloride and Sodium to ensure accurate and reliable analysis for patient management.

Keywords: sigma matrics, analytical performance, total error, bias

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Authors: Venkat Kamavaram, Ravi Pare

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Modern warfighters experience extreme environmental conditions in many of their operational and training activities. In temperatures exceeding 95°F, the body’s temperature regulation can no longer cool through convection and radiation. In this case, the only cooling mechanism is evaporation. However, evaporative cooling is often compromised by excessive humidity. Natural cooling mechanisms can be further compromised by clothing and protective gear, which trap hot air and moisture close to the body. Creating an efficient heat extraction apparel system that is also lightweight without hindering dexterity or mobility of personnel working in extreme temperatures is a difficult technical challenge and one that needs to be addressed to increase the probability for the future success of the US military. To address this challenge, Oceanit Laboratories, Inc. has developed and patented a Liquid Cooled Garment (LCG) more effective than any on the market today. Oceanit’s LCG is a form-fitting garment with a network of thermally conductive tubes that extracts body heat and can be worn under all authorized and chemical/biological protective clothing. Oceanit specifically designed and developed ThermoCore®, a thermally conductive polymer, for use in this apparel, optimizing the product for thermal conductivity, mechanical properties, manufacturability, and performance temperatures. Thermal Manikin tests were conducted in accordance with the ASTM test method, ASTM F2371, Standard Test Method for Measuring the Heat Removal Rate of Personal Cooling Systems Using a Sweating Heated Manikin, in an environmental chamber using a 20-zone sweating thermal manikin. Manikin test results have shown that Oceanit’s LCG provides significantly higher heat extraction under the same environmental conditions than the currently fielded Environmental Control Vest (ECV) while at the same time reducing the weight. Oceanit’s LCG vests performed nearly 30% better in extracting body heat while weighing 15% less than the ECV. There are NO cooling garments in the market that provide the same thermal extraction performance, form-factor, and reduced weight as Oceanit’s LCG. The two cooling garments that are commercially available and most commonly used are the Environmental Control Vest (ECV) and the Microclimate Cooling Garment (MCG).

Keywords: thermally conductive composite, tubing, garment design, form fitting vest, thermocore

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Authors: Mansa Radhakrishnan, Anwar Ali, Muhammad Rizwan Mughal

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Many universities around the world are working on modular and low budget architecture of small spacecraft to reduce the development cost of the overall system. This paper focuses on the design of a modular solar power harvesting system for a hexagonal-shaped small satellite. The designed solar power harvesting systems are composed of solar panels and power converter subsystems. The solar panel is composed of solar cells mounted on the external face of the printed circuit board (PCB), while the electronic components of power conversion are mounted on the interior side of the same PCB. The solar panel with dimensions 16.5cm × 99cm is composed of 36 solar cells (each solar cell is 4cm × 7cm) divided into four parallel banks where each bank consists of 9 solar cells. The output voltage of a single solar cell is 2.14V, and the combined output voltage of 9 series connected solar cells is around 19.3V. The output voltage of the solar panel is boosted to the satellite power distribution bus voltage level (28V) by a boost converter working on a constant voltage maximum power point tracking (MPPT) technique. The solar panel module is an eight-layer PCB having embedded coil in 4 internal layers. This coil is used to control the attitude of the spacecraft, which consumes power to generate a magnetic field and rotate the spacecraft. As power converter and distribution subsystem components are mounted on the PCB internal layer, therefore it is mandatory to do thermal analysis in order to ensure that the overall module temperature is within thermal safety limits. The main focus of the overall design is on compactness, miniaturization, and efficiency enhancement.

Keywords: small satellites, power subsystem, efficiency, MPPT

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Authors: Feyza Eda Akyurek, Bayram Sahin, Kadir Gelis, Eyuphan Manay, Murat Ceylan

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Turbulent forced convection heat transfer and pressure drop characteristics of Al₂O₃–water nanofluid flowing through a concentric tube heat exchanger with and without coiled wire turbulators were studied experimentally. The experiments were conducted in the Reynolds number ranging from 4000 to 20000, particle volume concentrations of 0.8 vol.% and 1.6 vol.%. Two turbulators with the pitches of 25 mm and 39 mm were used. The results of nanofluids indicated that average Nusselt number increased much more with increasing Reynolds number compared to that of pure water. Thermal conductivity enhancement by the nanofluids resulted in heat transfer enhancement. Once the pressure drop of the alumina/water nanofluid was analyzed, it was nearly equal to that of pure water at the same Reynolds number range. It was concluded that nanofluids with the volume fractions of 0.8 and 1.6 did not have a significant effect on pressure drop change. However, the use of wire coils in heat exchanger enhanced heat transfer as well as the pressure drop.

Keywords: turbulators, heat exchanger, nanofluids, heat transfer enhancement

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Authors: M. J. Uddin, M. M. Rahman

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The unsteady convective heat transfer flow of nanofluids in a half circular-annulus shape enclosure using nonhomogeneous dynamic model has been investigated numerically. The round upper wall of the enclosure is maintained at constant low temperature whereas the bottom wall is heated by three different thermal conditions. The enclosure is permeated by a uniform magnetic field having variable orientation. The Brownian motion and thermophoretic phenomena of the nanoparticles are taken into account in model construction. The governing nonlinear momentum, energy, and concentration equations are solved numerically using Galerkin weighted residual finite element method. To discover the best performer, the average Nusselt number is demonstrated for different types of nanofluids. The heat transfer rate for different flow parameters, positions of the annulus, thicknesses of the half circular-annulus and thermal conditions is also exhibited.

Keywords: nanofluid, convection, semicircular-annulus, nonhomogeneous dynamic model, finite element method

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Authors: Matteo Gentilucci, Marco Materazzi, Gilberto Pambianchi

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Climate change is an increasingly central issue in the world, because it affects many of human activities. In this context regional studies are of great importance because they sometimes differ from the general trend. This research focuses on a small area of central Italy which overlooks the Adriatic Sea, the province of Macerata. The aim is to analyze space-based climate changes, for precipitation and temperatures, in the last 3 climatological standard normals (1961-1990; 1971-2000; 1981-2010) through GIS software. The data collected from 30 weather stations for temperature and 61 rain gauges for precipitation were subject to quality controls: validation and homogenization. These data were fundamental for the spatialization of the variables (temperature and precipitation) through geostatistical techniques. To assess the best geostatistical technique for interpolation, the results of cross correlation were used. The co-kriging method with altitude as independent variable produced the best cross validation results for all time periods, among the methods analysed, with 'root mean square error standardized' close to 1, 'mean standardized error' close to 0, 'average standard error' and 'root mean square error' with similar values. The maps resulting from the analysis were compared by subtraction between rasters, producing 3 maps of annual variation and three other maps for each month of the year (1961/1990-1971/2000; 1971/2000-1981/2010; 1961/1990-1981/2010). The results show an increase in average annual temperature of about 0.1°C between 1961-1990 and 1971-2000 and 0.6 °C between 1961-1990 and 1981-2010. Instead annual precipitation shows an opposite trend, with an average difference from 1961-1990 to 1971-2000 of about 35 mm and from 1961-1990 to 1981-2010 of about 60 mm. Furthermore, the differences in the areas have been highlighted with area graphs and summarized in several tables as descriptive analysis. In fact for temperature between 1961-1990 and 1971-2000 the most areally represented frequency is 0.08°C (77.04 Km² on a total of about 2800 km²) with a kurtosis of 3.95 and a skewness of 2.19. Instead, the differences for temperatures from 1961-1990 to 1981-2010 show a most areally represented frequency of 0.83 °C, with -0.45 as kurtosis and 0.92 as skewness (36.9 km²). Therefore it can be said that distribution is more pointed for 1961/1990-1971/2000 and smoother but more intense in the growth for 1961/1990-1981/2010. In contrast, precipitation shows a very similar shape of distribution, although with different intensities, for both variations periods (first period 1961/1990-1971/2000 and second one 1961/1990-1981/2010) with similar values of kurtosis (1st = 1.93; 2nd = 1.34), skewness (1st = 1.81; 2nd = 1.62 for the second) and area of the most represented frequency (1st = 60.72 km²; 2nd = 52.80 km²). In conclusion, this methodology of analysis allows the assessment of small scale climate change for each month of the year and could be further investigated in relation to regional atmospheric dynamics.

Keywords: climate change, GIS, interpolation, co-kriging

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Adrian Garrido Sanchis, Richard Pashley

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The MS2 (ATCC15597-B1) virus was used as a surrogate to estimate the inactivation rates for enteric viruses when using a hot air bubble column evaporator (HBCE) system in the treatment of household wastewater. In this study, we have combined MS2 virus surface charging properties with thermal inactivation rates, using an improved double layer plaque assay technique, in order to assess the efficiency of the HBCE process for virus removal in water. When bubbling a continuous flow of dry air, at 200°C, only heats the aqueous solution in the bubble column to about 50°C. Viruses are not inactivated by this solution temperature, as confirmed separately from water bath heating experiments. Hence, the efficiency of the HBCE process for virus removal in water appeared to be caused entirely by collisions between the hot air bubbles and the virus organisms. This new energy efficient treatment for water reuse applications can reduce the thermal energy required to only 25% (about 113.7 kJ/L) of that required for boiling (about 450 kJ/L).

Keywords: MS2 virus inactivation, water reuse, hot bubble column evaporator, water treatment

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Authors: Suresh Prasad Sharma, Som Nath Saha

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This paper deals with the effect of Global Solar Radiation (GSR) on the performance of double flow solar air heater having corrugated plate as an absorber. An analytical model of a double flow solar air heater has been presented, and a computer program in C++ language has been developed to calculate the outlet air temperature, heat gain, pressure drop for estimating the thermal and thermohydraulic efficiencies. The performance of double flow corrugated absorber is compared with double flow flat plate and conventional solar air heaters. It is found that the double flow arrangement effectively increases the air temperature rise and efficiencies in comparison to a conventional collector. However, corrugated absorber is more superior to that of flat plate double flow solar air heater. The results indicate that increasing the solar radiation leads to achieve higher air temperature rise and efficiencies.

Keywords: corrugated absorber, double flow, flat plate, solar air heater

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Authors: S. Ramteke, K. S. Patel

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Aerosols are complex mixture of particulate matters (PM) inclusive of carbons, silica, elements, various salts, etc. Aerosols get deep into the human lungs and cause a broad range of health effects, in particular, respiratory and cardiovascular illnesses. They are one of the major culprits for the climate change. They are emitted by the high thermal processes i.e. vehicles, steel, sponge, cement, thermal power plants, etc. Raipur (22˚33'N to 21˚14'N and 82˚6'E) to 81˚38'E) is a growing industrial city in central India with population of two million. In this work, the distribution of inorganics (i.e. Cl⁻, NO³⁻, SO₄²⁻, NH₄⁺, Na⁺, K⁺, Mg²⁺, Ca²⁺, Al, Cr, Mn, Fe, Ni, Cu, Zn, and Pb) associated to the PM in the ambient air is described. The PM₁₀ in ambient air of Raipur city was collected for duration of one year (December 2014 - December 2015). The PM₁₀ was segregated into nine modes i.e. PM₁₀.₀₋₉.₀, PM₉.₀₋₅.₈, PM₅.₈₋₄.₇, PM₄.₇₋₃.₃, PM₃.₃₋₂.₁, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇, PM₀.₇₋₀.₄ and PM₀.₄ to know their emission sources and health hazards. The analysis of ions and metals was carried out by techniques i.e. ion chromatography and TXRF. The PM₁₀ concentration (n=48) was ranged from 100-450 µg/m³ with mean value of 73.57±20.82 µg/m³. The highest concentration of PM₄.₇₋₃.₃, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇ was observed in the commercial, residential and industrial area, respectively. The effect of meteorology i.e. temperature, humidity, wind speed and wind direction in the PM₁₀ and associated elemental concentration in the air is discussed.

Keywords: ambient aerosol, ions, metals, segregation

Procedia PDF Downloads 200

Authors: Maurice Brogly, Edwige Privas, Rajesh K. Gajendran, Sophie Bistac

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Anti-sticky coatings based on perfluoroalkoxy (PFA) coatings are widely used in food processing industry especially for bread making. Their tribological performance, such as low friction coefficient, low surface energy and high heat resistance, make them an appropriate choice for anti-sticky coating application in moulds for food processing industry. This study is dedicated to evidence the transfer of contaminants from the coating due to wear and thermal ageing of the mould. The risk of contamination is induced by the damage of the coating by bread crust during the demoulding stage. The study focuses on the wear resistance and potential transfer of perfluorinated polymer from the anti-sticky coating. Friction between perfluorinated coating and bread crust is modeled by a tribological pin-on-disc test. The cellular nature of the bread crust is modeled by a polymer foam. FTIR analysis of the polymer foam after friction allow the evaluation of the transfer from the perfluorinated coating to polymer foam. Influence of thermal ageing on the physical, chemical and wear properties of the coating are also investigated. FTIR spectroscopic results show that the increase of PFA transfer onto the foam counterface is associated to the decrease of the friction coefficient. Increasing lubrication by film transfer results in the decrease of the friction coefficient. Moreover increasing the friction test parameters conditions (load, speed and sliding distance) also increase the film transfer onto the counterface. Thermal ageing increases the hydrophobic character of the PFA coating and thus also decreases the friction coefficient.

Keywords: fluorobased polymer coatings, FTIR spectroscopy, non-stick food moulds, wear and friction

Procedia PDF Downloads 331