Search results for: global solar radiation prediction

Authors: Sunday Ofum Ogon

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The 1648 Westphalia Conference in Europe ushered in the state as the only legal entity with powers to engage in interstate relations on matters that bothers on the development need of her citizens. This epochal entry of the state reshaped global relations with the curtailment of the powers of individual and groups in external relations as the state became the only entity that acted on behalf of any individual or non-state actors like NGOs residing within the parameters of such a country. Thus, the paper interrogated the extent at which the state determines her Politico-Economic relations with regards to development and growth within the state. To achieve these objectives, the paper relied on documentary evidences wherein the qualitative descriptive method was used for data collection and analysis. The paper exploited the facilities of the Rentier State theory as a guide to the study. It was revealed at the end of the study that the 21st century global economic relations is largely determine by international organizations as exemplified by the World Bank and the International Monitory Fund (IMF) where their activities in the continent has undermined state sovereignty. Hence the paper recommended amongst others that states should look inward for development strategies rather than relying on handout from supra-national organizations which has infringe on their sovereignty.

Keywords: State , Global , Rentier state, Twenty-First Century

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Authors: Mitrajit Biswas

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This paper is trying to understand the issues related to maintaining a fan base over a period of time. The paper would be trying to look into how the fan base can be actually engaged. That is what are the attributes of keeping a fan base interested and not feeling fatigued or tired. It would also try to understand that what are the key elements required for a franchise to be active and keep the fans engaged. The paper would look to understand the primary elements of a franchise like Marvel to keep the fans engaged for such a long period of time. This will help to improve the scope of literature on consumer engagement and consumption behaviour in modern times of unpredictability. It will also help to understand how the consumers take in a longer period of engagement. This would help to understand that despite huge success and investment in fan engagement and what could be the possible reasons for disengagement? This would include in-depth interviews with a global sample of around 50 people, which would be connected through purposive, convenient, and snowball sampling. It will help to understand whether the customer lifetime value as a theory can be sustained based on customer relationship management. If yes, how can products from certain companies predict and keep up the strategy for the prediction of the consumer engagement process?

Keywords: consumption, fatigue, brand loyalty, sustainable consumption

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Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

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Authors: Eid Alharbi, Yaser Miaji

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The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

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Authors: Eid Alharbi, Yaser Miaji

Abstract:

The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

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Authors: Jaden Lu, Olivia Lu

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Despite the remarkable advancement of solar cell technology, the challenge of optimizing total solar energy harvest efficiency persists, primarily due to significant heat loss. This excess heat not only diminishes solar panel output efficiency but also curtails its operational lifespan. A promising approach to address this issue is the conversion of surplus heat into electricity. In recent years, there is growing interest in the use of thermoelectric generators (TEG) as a potential solution. The integration of efficient TEG devices holds the promise of augmenting overall energy harvest efficiency while prolonging the longevity of solar panels. While certain research groups have proposed the integration of solar cells and TEG devices, a substantial gap between conceptualization and practical implementation remains, largely attributed to low thermal energy conversion efficiency of TEG devices. To bridge this gap and meet the requisites of practical application, a feasible strategy involves the incorporation of a substantial number of p-n junctions within a confined unit volume. However, the manufacturing of high-density TEG p-n junctions presents a formidable challenge. The prevalent solution often leads to large device sizes to accommodate enough p-n junctions, consequently complicating integration with solar cells. Recently, the adoption of 3D printing technology has emerged as a promising solution to address this challenge by fabricating high-density p-n arrays. Despite this, further developmental efforts are necessary. Presently, the primary focus is on the 3D printing of vertically layered TEG devices, wherein p-n junction density remains constrained by spatial limitations and the constraints of 3D printing techniques. This study proposes a novel device configuration featuring horizontally arrayed p-n junctions of Bi2Te3. The structural design of the device is subjected to simulation through the Finite Element Method (FEM) within COMSOL Multiphysics software. Various device configurations are simulated to identify optimal device structure. Based on the simulation results, a new TEG device is fabricated utilizing 3D Selective laser melting (SLM) printing technology. Fusion 360 facilitates the translation of the COMSOL device structure into a 3D print file. The horizontal design offers a unique advantage, enabling the fabrication of densely packed, three-dimensional p-n junction arrays. The fabrication process entails printing a singular row of horizontal p-n junctions using the 3D SLM printing technique in a single layer. Subsequently, successive rows of p-n junction arrays are printed within the same layer, interconnected by thermally conductive copper. This sequence is replicated across multiple layers, separated by thermal insulating glass. This integration created in a highly compact three-dimensional TEG device with high density p-n junctions. The fabricated TEG device is then attached to the bottom of the solar cell using thermal glue. The whole device is characterized, with output data closely matching with COMSOL simulation results. Future research endeavors will encompass the refinement of thermoelectric materials. This includes the advancement of high-resolution 3D printing techniques tailored to diverse thermoelectric materials, along with the optimization of material microstructures such as porosity and doping. The objective is to achieve an optimal and highly integrated PV-TEG device that can substantially increase the solar energy harvest efficiency.

Keywords: thermoelectric, finite element method, 3d print, energy conversion

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Authors: Mohammed T. Hayajneh

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Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Smita Singh

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The paper develops a critical framework to the hegemonic discourses resorted to by the dominant powers in the global security architecture. Within this framework, security is viewed as a discourse through which identities and threats are represented and produced to legitimize the security concerns of few at the cost of others. International security have long been driven and dominated by power relations. Since the end of the Cold War, the global transformations have triggered contestations to the idea of security at both theoretical and practical level. These widening and deepening of the concept of security have challenged the existing power hierarchies at the theoretical level but not altered the substance and actors defining it. When discourses are introduced into security studies, several critical questions erupt: how has power shaped security policies of the globe through language? How does one understand the meanings and impact of those discourses? Who decides the agenda, rules, players and outliers of the security? Language as a symbolic system and form of power is fluid and not fixed. Over the years the dominant Western powers, led by the United States of America have employed various discursive practices such as humanitarian intervention, responsibility to protect, non proliferation, human rights, war on terror and so on to reorient the constitution of identities and interests and hence the policies that need to be adopted for its actualization. These power relations are illustrated in this paper through the narratives used in the nonproliferation regime. The hierarchical security dynamics is a manifestation of the global power relations driven by many factors including discourses.

Keywords: hegemonic discourse, global security, non-proliferation regime, power politics

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Authors: May Khei Hu, Kevin Leong, Fu Siong Ng, Nicholas Peter

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Introduction: Sympathetic stimulation has been recognised as a potent stimulus of arrhythmogenesis in various cardiac pathologies, possibly by augmenting dispersion of repolarisation. The effects of sympathetic stimulation in healthy subjects however remain unclear. It is, therefore, crucial to first establish the effects of physiological stress on dispersion of repolarisation in healthy subjects before understanding these effects in pathological cardiac conditions. We hypothesised that activation-recovery interval (ARI; which is a surrogate of action potential duration) and dispersion of repolarisation decrease on sympathetic stimulation. Methods: Eight patients aged 18-55 years with structurally normal hearts underwent head-up tilt test (HUTT) and exercise tolerance test (ETT) while wearing the electrocardiographic imaging (ECGi) vest. Patients later underwent CT scan and the epicardial potentials are reconstructed using the ECGi software. Activation and recovery times were determined from the acquired electrograms. ARI was calculated and later corrected using Bazett’s formula. Global and regional dispersion of repolarisation were determined from standard deviation of the corrected ARI (ARIc). One-way analysis of variance (ANOVA) and Wilcoxon test were used to evaluate statistical significance. Results: Global ARIc increased significantly [p<0.01] when patients were tilted upwards but decreased significantly after five minutes [p<0.01]. A subsequent post- hoc analysis revealed that the decrease in R-R was more substantial compared to the change in ARI, resulting in the observed increase in ARIc. Global ARIc decreased on peak exercise [p<0.01] but increased on recovery [p<0.01]. Global dispersion increased significantly on peak exercise [p<0.05] although there were no significant changes in regional dispersion. There were no significant changes in both global and regional dispersion during tilt. Conclusion: ARIc decreases upon sympathetic stimulation in healthy subjects. Global dispersion of repolarisation increases upon exercise although there were no changes in global or regional dispersion during orthostatic stress.

Keywords: dispersion of repolarisation, sympathetic stimulation, Head-up tilt test (HUTT), Exercise tolerance test (ETT), Electrocardiographic imaging (ECGi)

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Authors: R. Burahee, B. Chassinat, T. de Laclos, A. Dépée, A. Sastim

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The purpose of this paper is to propose a solution to detect, predict and reconstitute rain drops in real time – during the night – using an embedded material with an infrared camera. To prevent the system from needing too high hardware resources, simple models are considered in a powerful image treatment algorithm reducing considerably calculation time in OpenCV software. Using a smart model – drops will be matched thanks to a process running through two consecutive pictures for implementing a sophisticated tracking system. With this system drops computed trajectory gives information for predicting their future location. Thanks to this technique, treatment part can be reduced. The hardware system composed by a Raspberry Pi is optimized to host efficiently this code for real time execution.

Keywords: reconstitution, prediction, detection, rain drop, real time, raspberry, infrared

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Authors: Okuyade Ighoroje Wilson Ata

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Magneto-hydrodynamic mixed convective chemically reacting fluid flow through two parallel vertical plates channel with Hall, radiation, and chemical reaction effects are examined. The fluid is assumed to be chemically reactive, electrically conducting, magnetically susceptible, viscous, incompressible, and Newtonian; the plates are porous, electrically conductive, and heated to a high-temperature regime to generate thermal rays. The flow system is highly interactive, such that cross/double diffusion is present. The governing equations are partial differential equations transformed into ordinary differential equations using similarity transformation and solved by the method of Homotopy Perturbation. Expressions for the concentration, temperature, velocity, Nusselt number, Sherwood number, and Wall shear stress are obtained, computed, and presented graphically and tabularly. The analysis of results shows, amongst others, that an increase in the Raleigh number increases the main velocity and temperature but decreases the concentration. More so, an increase in chemical reaction rate increases the main velocity, temperature, rate of heat transfer from the terminal plate, the rate of mass transfer from the induced plate, and Wall shear stress on both the induced and terminal plates, decreasing the concentration, and the mass transfer rate from the terminal plate. Some of the obtained results are benchmarked with those of existing literature and are in consonance.

Keywords: chemical reaction, hall effect, magneto-hydrodynamic, radiation, vertical plates channel

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Authors: S. V. Akulinichev, S. A. Chaushansky, V. I. Derzhiev

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High dose rate (HDR) brachytherapy is a method of contact radiotherapy, when a single sealed source with an activity of about 10 Ci is temporarily inserted in the tumor area. The isotopes Ir-192 and (much less) Co-60 are used as active material for such sources. The other type of brachytherapy, the low dose rate (LDR) brachytherapy, implies the insertion of many permanent sources (up to 200) of lower activity. The pulse dose rate (PDR) brachytherapy can be considered as a modification of HDR brachytherapy, when the single source is repeatedly introduced in the tumor region in a pulse regime during several hours. The PDR source activity is of the order of one Ci and the isotope Ir-192 is currently used for these sources. The PDR brachytherapy is well recommended for the treatment of several tumors since, according to oncologists, it combines the medical benefits of both HDR and LDR types of brachytherapy. One of the main problems for the PDR brachytherapy progress is the shielding of the treatment area since the longer stay of patients in a shielded canyon is not enough comfortable for them. The use of Yb-169 as an active source material is the way to resolve the shielding problem for PDR, as well as for HRD brachytherapy. The isotope Yb-169 has the average photon emission energy of 93 KeV and the half-life of 32 days. Compared to iridium and cobalt, this isotope has a significantly lower emission energy and therefore requires a much lighter shielding. Moreover, the absorption cross section of different materials has a strong Z-dependence in that photon energy range. For example, the dose distributions of iridium and ytterbium have a quite similar behavior in the water or in the body. But the heavier material as lead absorbs the ytterbium radiation much stronger than the iridium or cobalt radiation. For example, only 2 mm of lead layer is enough to reduce the ytterbium radiation by a couple of orders of magnitude but is not enough to protect from iridium radiation. We have created an original facility to produce the start stable isotope Yb-168 using the laser technology AVLIS. This facility allows to raise the Yb-168 concentration up to 50 % and consumes much less of electrical power than the alternative electromagnetic enrichment facilities. We also developed, in cooperation with the Institute of high pressure physics of RAS, a new technology for manufacturing high-density ceramic cores of ytterbium oxide. Ceramics density reaches the limit of the theoretical values: 9.1 g/cm3 for the cubic phase of ytterbium oxide and 10 g/cm3 for the monoclinic phase. Source cores from this ceramics have high mechanical characteristics and a glassy surface. The use of ceramics allows to increase the source activity with fixed external dimensions of sources.

Keywords: brachytherapy, high, pulse dose rates, radionuclides for therapy, ytterbium sources

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

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Authors: Malik Shahzad Shabbir, Muhammad Saarim Ghazi, Amir Khalil ur Rehman

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This study examines the factors which influence and contribute towards the financial viability of Islamic finance and its impact on global financial stability. However, the purpose of this paper is to differentiate the practical implications of both Islamic and conventional finance on global financial stability. The Islamic finance is asset backed financing which creates wealth through trade, commerce and believes in risk and return sharing. Islamic banking is asset driven as against to conventional banking which is liability driven. In order to introduce new financial products for market, financial innovation in Islamic finance must be within the Shari’ah parameters that are tested against the ‘Maqasid al-Shari’ah’. Interest-based system leads to income and wealth inequalities and mis-allocation of resources. Moreover, this system has absence of just and equitable aspect of distribution that may exploit either the debt holder or the financier. Such implications are reached to a tipping point that leaves only one choice: change or face continued decline and misery.

Keywords: viability, global financial stability, practical implications, asset driven, tipping point

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Authors: Lana Migla

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Phase change materials (PCMs) have an important role in improving the efficiency of thermal heat storage. As these materials are characterized by low thermal conductivity, it is necessary to develop heat transfer techniques to improve their thermophysical properties. This scientific article focuses on the geometrical configurations of encapsulated PCM containers and the impact of designs to improve the performance of the solar thermal cooling system. The literature review showed that in-depth research is being conducted on different methods of improving the efficiency of PCM heat transfer, which is the main design task for the containers. Techniques such as microencapsulated PCMs, adding fins and different combinations of fins and nanoparticles are used. The use of graphite, metal foam and doping of high photothermal materials is also being studied. To determine most efficient container configuration, the article looks at different designs of PCM containers with fins for the storage tank. This paper experimentally investigates the effect of the encapsulation design on the performance of a lab-scale thermal energy storage tank. The development of optimized energy storage with integrated phase change material containers reduces auxiliary heater energy consumption, increases the COP of the solar cooling system, and reduces the environmental impact of the cooling system. The review shows that in the cylindrical construction, the ratio between the radius of shell and tube is significant, which means this ratio is the main issue to enhance transfer efficiency and to increase the value of stored heat. Therefore, three cylindrical tube containers with different radiuses 20mm, 35mm, 50mm filled with commercial phase change material were tested. The results show that using a smaller radius achieved a higher power, leading to a reduction in the charging and discharging time. The three fins were added to the selected cylindrical tube to determine their effects on heat exchanging efficiency. The observed optimized performance given by the fin’s arrangement achieved a 40% reduction of PCM's melting time compared to the heat exchanging without fins. The exact dimensions of the PCM containers and fins placements will be presented on-site.

Keywords: energy performance, PCM containers, solar thermal cooling, storage tank

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Authors: Ying-Ming Su

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Fujian earthen building which was known as a classic for ecological buildings was listed on the world heritage in 2008 (UNESCO) in China. Its design strategy can be applied to modern architecture planning and design. This study chose two different cases (Round Atrium: Er-Yi Building, Double Round Atrium: Zhen-Chen Building) of earthen building in Fu-Jian to compare the ventilation effects of different atrium forms. We adopt field measurements and computational fluid dynamics (CFD) simulation of temperature, humidity, and wind environment to identify the relationship between external environment and atrium about comfort and to confirm the relationship about atrium H/W (height/width). Results indicate that, through the atrium convection effect, it makes the natural wind guides to each space surrounded and keeps indoor comfort. It illustrates that the smaller the ratio of the H/W which is the relationship between the height and the width of an atrium is, the greater the wind speed generated within the street valley. Moreover, the wind speed is very close to the reference wind speed. This field measurement verifies that the value of H/W has great influence of solar radiation heat and sunshine shadows. The ventilation efficiency is: Er-Yi Building (H/W =0.2778) > Zhen-Chen Building (H/W=0.3670). Comparing the cases with the same shape but with different H/W, through the different size patios, airflow revolves in the atriums and can be brought into each interior space. The atrium settings meet the need of building ventilation, and can adjust the humidity and temperature within the buildings. It also creates good ventilation effect.

Keywords: traditional folk houses, atrium, tulou, ventilation, building microclimate

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Authors: Rui Calejo Rodrigues

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Building Refurbishing and Maintenance is a major area of knowledge ultimately dispensed to user/occupant criteria. The optimization of the service life of a building needs a special background to be assessed as it is one of those concepts that needs proficiency to be implemented. ISO 15686-2 Buildings and constructed assets - Service life planning: Part 2, Service life prediction procedures, states a factorial method based on deterministic data for building components life span. Major consequences result on a deterministic approach because users/occupants are not sensible to understand the end of components life span and so simply act on deterministic periods and so costly and resources consuming solutions do not meet global targets of planet sustainability. The estimation of 2 thousand million conventional buildings in the world, if submitted to a probabilistic method for service life planning rather than a deterministic one provide an immense amount of resources savings. Since 1989 the research team nowadays stating for CEES–Center for Building in Service Studies developed a methodology based on Montecarlo method for probabilistic approach regarding life span of building components, cost and service life care time spans. The research question of this deals with the importance of probabilistic approach of buildings life planning compared with deterministic methods. It is presented the mathematic model developed for buildings probabilistic lifespan approach and experimental data is obtained to be compared with deterministic data. Assuming that buildings lifecycle depends a lot on component replacement this methodology allows to conclude on the global impact of fixed replacements methodologies such as those on result of deterministic models usage. Major conclusions based on conventional buildings estimate are presented and evaluated under a sustainable perspective.

Keywords: building components life cycle, building maintenance, building sustainability, Montecarlo Simulation

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Authors: Sandeep Kumar, Naveen Gupta

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Terahertz (THz) generation has been investigated by beating two cosh-Gaussian laser beams of the same amplitude but different wavenumbers and frequencies through rippled collisionless plasma. The ponderomotive force is operative which is induced due to the intensity gradient of the laser beam over the cross-section area of the wavefront. The electrons evacuate towards a low-intensity regime, which modifies the dielectric function of the medium and results in cross focusing of cosh-Gaussian laser beams. The evolution of spot size of laser beams has been studied by solving nonlinear Schrodinger wave equation (NLSE) with variational technique. The laser beams impart oscillations to electrons which are enhanced with ripple density. The nonlinear oscillatory motion of electrons gives rise to a nonlinear current density driving THz radiation. It has been observed that the periodicity of the ripple density helps to enhance the THz radiation.

Keywords: rippled collisionless plasma, cosh-gaussian laser beam, ponderomotive force, variational technique, nonlinear current density

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Authors: Bala Adamu Malami

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The necessity of low-cost electronic vehicle/car security designed in coordination with other security measures is always there in our society to reduce the risk of vehicle intrusion. Keeping this problem in mind, we are designing an automatic GPS system which is technology to build an integrated and fully customized vehicle to detect the movement of the vehicle and also serve as a security system at a reasonable cost. Users can locate the vehicle's position via GPS by using the Google Maps application to show vehicle coordinates on a smartphone. The tracking system uses a Global System for Mobile Communication (GSM) modem for communication between the mobile station and the microcontroller to send and receive commands. Further design can be improved to capture the vehicle movement range and alert the vehicle owner when the vehicle is out of range.

Keywords: electronic, GPS, GSM modem, communication, vehicle

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Authors: O. Maranci, A. B. Tugrul

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Scintigraphy is an imaging method of nuclear events provoked by collisions or charged current interactions with radiation. It is used for diagnostic test used in nuclear medicine via radiopharmaceuticals emitting radiation which is captured by gamma cameras to form two-dimensional images. Liver scintigraphy is widely used in nuclear medicine.Tc-99m and Cr-51 gamma radioisotopes can be used for this purpose. Cr-51 usage is more important for patients’ organ dose that has higher energy and longer half-life as compared to Tc-99m. In this study, it is aimed to determine the required dose for critical organs of patient through liver scintigraphy via Cr-51 gamma radioisotope. Experimental studies were conducted on patients even though conducting experimental studies on patients is extremely difficult for determination of critical organ doses. Torso phantom was utilized to simulate the liver scintigraphy by using 20 mini packages of Cr-51 that were placed on the organ. The radioisotope was produced by irradiation in central thimble of TRIGA MARK II Reactor at 250 KW power. As the results of the study, critical organ doses were determined and evaluated with different critic organs.

Keywords: critical organ doses, liver, scintigraphy, TRIGA Mark-II

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Authors: Venencia Albert, Arulselvi Subramanian, Hara Prasad Pati, Asok K. Mukhophadhyay

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Acute traumatic coagulopathy in an endogenous dysregulation of the intrinsic coagulation system in response to the injury, associated with three-fold risk of poor outcome, and is more amenable to corrective interventions, subsequent to early identification and management. Multiple definitions for stratification of the patients' risk for early acute coagulopathy have been proposed, with considerable variations in the defining criteria, including several trauma-scoring systems based on prehospital data. We aimed to develop a clinically relevant definition for acute coagulopathy of trauma based on conventional coagulation assays and to assess its efficacy in comparison to recently established prehospital prediction models. Methodology: Retrospective data of all trauma patients (n = 490) presented to our level I trauma center, in 2014, was extracted. Receiver operating characteristic curve analysis was done to establish cut-offs for conventional coagulation assays for identification of patients with acute traumatic coagulopathy was done. Prospectively data of (n = 100) adult trauma patients was collected and cohort was stratified by the established definition and classified as "coagulopathic" or "non-coagulopathic" and correlated with the Prediction of acute coagulopathy of trauma score and Trauma-Induced Coagulopathy Clinical Score for identifying trauma coagulopathy and subsequent risk for mortality. Results: Data of 490 trauma patients (average age 31.85±9.04; 86.7% males) was extracted. 53.3% had head injury, 26.6% had fractures, 7.5% had chest and abdominal injury. Acute traumatic coagulopathy was defined as international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s. Of the 100 adult trauma patients (average age 36.5±14.2; 94% males), 63% had early coagulopathy based on our conventional coagulation assay definition. Overall prediction of acute coagulopathy of trauma score was 118.7±58.5 and trauma-induced coagulopathy clinical score was 3(0-8). Both the scores were higher in coagulopathic than non-coagulopathic patients (prediction of acute coagulopathy of trauma score 123.2±8.3 vs. 110.9±6.8, p-value = 0.31; trauma-induced coagulopathy clinical score 4(3-8) vs. 3(0-8), p-value = 0.89), but not statistically significant. Overall mortality was 41%. Mortality rate was significantly higher in coagulopathic than non-coagulopathic patients (75.5% vs. 54.2%, p-value = 0.04). High prediction of acute coagulopathy of trauma score also significantly associated with mortality (134.2±9.95 vs. 107.8±6.82, p-value = 0.02), whereas trauma-induced coagulopathy clinical score did not vary be survivors and non-survivors. Conclusion: Early coagulopathy was seen in 63% of trauma patients, which was significantly associated with mortality. Acute traumatic coagulopathy defined by conventional coagulation assays (international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s) demonstrated good ability to identify coagulopathy and subsequent mortality, in comparison to the prehospital parameter-based scoring systems. Prediction of acute coagulopathy of trauma score may be more suited for predicting mortality rather than early coagulopathy. In emergency trauma situations, where immediate corrective measures need to be taken, complex multivariable scoring algorithms may cause delay, whereas coagulation parameters and conventional coagulation tests will give highly specific results.

Keywords: trauma, coagulopathy, prediction, model

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Promila Dahiya, Kiran Singh

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Indian agriculture has come a long way from being an era of frequent droughts and vulnerability to food shortages to becoming a significant exporter of agricultural commodities. Polyhouses are essentially microcosms aimed at providing physical environment suitable for the survival and growth of plants with high degree of temperature, humidity and carbon dioxide. The present study was conducted in 21 districts of Haryana State to review Polyhouse farming is an alternative farming in Haryana State to fulfil the needs of population byminimum use of land, water and energy. The information regarding number, area and type of polyhouses and subsidy provided by Govt. of India and Haryana on polyhouse farming was collected from respective district horticulture offices of Haryana State. Four different types of polyhouses were studied during work viz., Hitechnology polyhouse (Hi-tech), Anti-Insect Net Shade House (AINSH), Naturally Ventilated Polyhouse (NVPH) and Walk-In-Tunnel (WIT).In study it was found that in walk-in-tunnel (WIT) and natural ventilated polyhouses (NVPH) the temperature was 69.54% and 52.29% higher and the humidity was 96.37% and 85.19 % higher in comparison to open farming in the months of January and May. No significant different was found in temperature, humidity, dust, solar radiation and CO2 level between open and anti insect net shade house (AINH). In Hi-tech polyhouse, the environment was totally controlled by computer and was not found to much strenuous. Health status of workers was checked by doctor, and it was found that in polyhouse farming workers were more prone to problems of allergy and asthma.

Keywords: polyhouse, unfavorable climate, walk-in-tunnel, psychological aspect

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Yilin Liao, Hewen Li, Paula McConvey

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Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

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Authors: D. Amaranatha Reddy

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Highly efficient and stable co-catalysts materials is of great important for boosting photo charge carrier’s separation, transportation efficiency, and accelerating the catalytic reactive sites of semiconductor photocatalysts. As a result, it is of decisive importance to fabricate low price noble metal free co-catalysts with high catalytic reactivity, but it remains very challenging. Considering this challenge here, dual metal organic frame work derived N-Doped Fe3C nanocages have been rationally designed and decorated with ultrathin ZnIn2S4 nanosheets for efficient photocatalytic hydrogen generation. The fabrication strategy precisely integrates co-catalyst nanocages with ultrathin two-dimensional (2D) semiconductor nanosheets by providing tightly interconnected nano-junctions and helps to suppress the charge carrier’s recombination rate. Furthermore, constructed highly porous hybrid structures expose ample active sites for catalytic reduction reactions and harvest visible light more effectively by light scattering. As a result, fabricated nanostructures exhibit superior solar driven hydrogen evolution rate (9600 µmol/g/h) with an apparent quantum efficiency of 3.6 %, which is relatively higher than the Pt noble metal co-catalyst systems and earlier reported ZnIn2S4 based nanohybrids. We believe that the present work promotes the application of sulfide based nanostructures in solar driven hydrogen production.

Keywords: photocatalysis, water splitting, hydrogen fuel production, solar-driven hydrogen

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Authors: Adel A. Ghoneim

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Air conditioning devices are substantially utilized in the summer months, as a result maximum loads in Kuwait take place in these intervals. Peak energy consumption are usually more expensive to satisfy compared to other standard power sources. The primary objective of the current work is to enhance the performance of high concentrated photovoltaic (HCPV) systems in an attempt to minimize peak power usage in Kuwait using HCPV modules. High concentrated PV multi-junction solar cells provide a promising method towards accomplishing lowest pricing per kilowatt-hour. Nevertheless, these cells have various features that should be resolved to be feasible for extensive power production. A single diode equivalent circuit model is formulated to analyze multi-junction solar cells efficiency in Kuwait weather circumstances taking into account the effects of both the temperature and the concentration ratio. The diode shunt resistance that is commonly ignored in the established models is considered in the present numerical model. The current model results are successfully validated versus measurements from published data to within 1.8% accuracy. Present calculations reveal that the single diode model considering the shunt resistance provides accurate and dependable results. The electrical efficiency (η) is observed to increase with concentration to a specific concentration level after which it reduces. Implementing grid systems is noticed to increase with concentration to a certain concentration degree after which it decreases. Employing grid connected HCPV systems results in significant peak load reduction.

Keywords: grid connected, high concentrated photovoltaic systems, peak load, solar cells

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Authors: Davoud Jafari, Paolo Di Marco, Alessandro Franco, Sauro Filippeschi

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This paper summarizes the results of an investigation into the heat pipe heat transfer for solar collector applications. The study aims to show the feasibility of a concentrating solar collector, which is coupled with a heat pipe. Particular emphasis is placed on the capillary and boiling limits in capillary porous structures, with different mesh numbers and wick thicknesses. A mathematical model of a cylindrical heat pipe is applied to study its behaviour when it is exposed to higher heat input at the evaporator. The steady state analytical model includes two-dimensional heat conduction in the HP’s wall, the liquid flow in the wick and vapor hydrodynamics. A sensitivity analysis was conducted by considering different design criteria and working conditions. Different wicks (mesh 50, 100, 150, 200, 250, and, 300), different porosities (0.5, 0.6, 0.7, 0.8, and 0.9) with different wick thicknesses (0.25, 0.5, 1, 1.5, and 2 mm) are analyzed with water as a working fluid. Results show that it is possible to improve heat transfer capability (HTC) of a HP by selecting the appropriate wick thickness, the effective pore radius, and lengths for a given HP configuration, and there exist optimal design criteria (optimal thick, evaporator adiabatic and condenser sections). It is shown that the boiling and wicking limits are connected and occurs in dependence on each other. As different parts of the HP external surface collect different fractions of the total incoming insolation, the analysis of non-uniform heat flux distribution indicates that peak heat flux is not affecting parameter. The parametric investigations are aimed to determine working limits and thermal performance of HP for medium temperature SC application.

Keywords: screened heat pipes, analytical model, boiling and capillary limits, concentrating collector

Procedia PDF Downloads 549