Search results for: Electrostatic interaction energy

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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As we enter the new era of Artificial Intelligence (AI) and cloud computing, we mostly rely on the machine and natural language processing capabilities of AI, and energy efficient hardware and software devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and to sustain the depletion of natural resources. The core pillars of sustainability are Economic, Environmental, and Social, which are also informally referred to as 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core sustainability model in the enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand there is also a growing concern in many industries on how to reduce carbon emission and conserve natural resources while adopting sustainability in the corporate business models and policies. In our paper, we would like to discuss the driving forces such as climate changes, natural disasters, pandemic, disruptive technologies, corporate policies, scaled business models and emerging social media and AI platforms that influence the 3 main pillars of sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increase recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (shared IT services, cloud computing and application modernization) with the vision for a sustainable environment.

Keywords: AI, cloud computing, machine learning, social media platform.

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Authors: R. K. Apalowo, D. Chronopoulos, V. Thierry

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There exist a wide range of failure modes in composite structures due to the increased usage of the structures especially in aerospace industry. Moreover, temperature dependent wave response of composite and layered structures have been continuously studied, though still limited, in the last decade mainly due to the broad operating temperature range of aerospace structures. A wave finite element (WFE) and finite element (FE) based computational method is presented by which the temperature dependent wave dispersion characteristics and interaction phenomenon in composite structures can be predicted. Initially, the temperature dependent mechanical properties of the panel in the range of -100 ◦C to 150 ◦C are measured experimentally using the Thermal Mechanical Analysis (TMA). Temperature dependent wave dispersion characteristics of each waveguide of the structural system, which is discretized as a system of a number of waveguides coupled by a coupling element, is calculated using the WFE approach. The wave scattering properties, as a function of temperature, is determined by coupling the WFE wave characteristics models of the waveguides with the full FE modelling of the coupling element on which defect is included. Numerical case studies are exhibited for two waveguides coupled through a coupling element.

Keywords: Temperature dependent mechanical characteristics, wave propagation properties, damage detection, wave finite element, composite structure.

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Authors: Tsung-Hsien Yu, Ya-Hsuan Chou, Ming-Wei Chen, Chi-Ming Chen, Yi-Hsuan Li

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Observations and long-term trends indicate that climate change impacts would be significant and affects Taiwan directly and severely. Taiwan engages not only in mitigation, but also in adaptation. However, there are cognitive gaps on adaptation between government and populace. Besides, a vision of zero-carbon and renewable energy 100% will be adopted in future. Therefore, the objectives of this article are to 1) hold a National Forum for knowing differences between the strategies of zero-carbon and renewable energy 100% and cognitions of general populace, and 2) plan a clear roadmap for the vision, strategy, and measures. In this forum, we set 5 group topics, 5 presumed themes, and issues mentioned review for concluding the critical issues. Finally, there are 4 strategies and 14 critical issues which correlate with the vision and strategy of government and the cognition of the general populace.

Keywords: Cognitive gap, world café, renewable energy, zero-carbon.

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Authors: Kwok Tak Kit

Abstract:

Under the Paris Agreement 2015, the countries committed to address and combat the climate change and its negative impacts and agree to the target of reducing the global greenhouse gas (GHG) emission substantially by limiting the global temperature to 2 0C above the pre-industrial level in this century. An international submit named “26th United Nations Climate Conference” (COP26) was held in Glasgow in 2021 with all committed countries agreed to finalize the outstanding element in Paris Agreement and Glasgow Climate Pact to keep 1.5 0C. In this paper, we will focus on the basic approach of waste strategy, recycling policy, circular economy strategy, net-zero strategy and sustainability strategy and the importance of the elements which affect the carbon emission, waste generation and energy conservation will be further reviewed with recommendation for future study.

Keywords: Net-zero carbon, climate change, carbon emission, energy consumption.

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Authors: Zelmina Lubovac, Björn Olsson, Jonas Gamalielsson

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This paper describes a novel approach for deriving modules from protein-protein interaction networks, which combines functional information with topological properties of the network. This approach is based on weighted clustering coefficient, which uses weights representing the functional similarities between the proteins. These weights are calculated according to the semantic similarity between the proteins, which is based on their Gene Ontology terms. We recently proposed an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The rational underlying this approach is that each module can be reduced to a set of triangles (protein triplets connected to each other). Here, we propose considering semantic similarity weights of all triangle-forming edges between proteins. We also apply varying semantic similarity thresholds between neighbours of each node that are not neighbours to each other (and hereby do not form a triangle), to derive new potential triangles to include in module-defining procedure. The results show an improvement of pure topological approach, in terms of number of predicted modules that match known complexes.

Keywords: Modules, systems biology, protein interactionnetworks, yeast.

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Authors: Randy Gomez, Keisuke Nakamura, Kazuhiro Nakadai

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Distant-talking voice-based HCI system suffers from performance degradation due to mismatch between the acoustic speech (runtime) and the acoustic model (training). Mismatch is caused by the change in the power of the speech signal as observed at the microphones. This change is greatly influenced by the change in distance, affecting speech dynamics inside the room before reaching the microphones. Moreover, as the speech signal is reflected, its acoustical characteristic is also altered by the room properties. In general, power mismatch due to distance is a complex problem. This paper presents a novel approach in dealing with distance-induced mismatch by intelligently sensing instantaneous voice power variation and compensating model parameters. First, the distant-talking speech signal is processed through microphone array processing, and the corresponding distance information is extracted. Distance-sensitive Gaussian Mixture Models (GMMs), pre-trained to capture both speech power and room property are used to predict the optimal distance of the speech source. Consequently, pre-computed statistic priors corresponding to the optimal distance is selected to correct the statistics of the generic model which was frozen during training. Thus, model combinatorics are post-conditioned to match the power of instantaneous speech acoustics at runtime. This results to an improved likelihood in predicting the correct speech command at farther distances. We experiment using real data recorded inside two rooms. Experimental evaluation shows voice recognition performance using our method is more robust to the change in distance compared to the conventional approach. In our experiment, under the most acoustically challenging environment (i.e., Room 2: 2.5 meters), our method achieved 24.2% improvement in recognition performance against the best-performing conventional method.

Keywords: Human Machine Interaction, Human Computer Interaction, Voice Recognition, Acoustic Model Compensation, Acoustic Speech Enhancement.

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Authors: F. O. Aron, T. O. Olwal, A. Kurien, M. O. Odhiambo

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A considerable amount of energy is consumed during transmission and reception of messages in a wireless mesh network (WMN). Reducing per-node transmission power would greatly increase the network lifetime via power conservation in addition to increasing the network capacity via better spatial bandwidth reuse. In this work, the problem of topology control in a hybrid WMN of heterogeneous wireless devices with varying maximum transmission ranges is considered. A localized distributed topology control algorithm is presented which calculates the optimal transmission power so that (1) network connectivity is maintained (2) node transmission power is reduced to cover only the nearest neighbours (3) networks lifetime is extended. Simulations and analysis of results are carried out in the NS-2 environment to demonstrate the correctness and effectiveness of the proposed algorithm.

Keywords: Topology Control, Wireless Mesh Networks, Backbone, Energy Efficiency, Localized Algorithm.

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Authors: Hanan Alenezi

Abstract:

Membrane performance depends on the kind of solvent used in preparation. A membrane made by Polyetherimide (PEI) was evaluated for gas separation using X-Ray Diffraction (XRD), Scanning electron microscope (SEM), and Energy Dispersive X-Ray Spectroscopy (EDS). The purity and the thickness are detected to evaluate the membrane in order to optimize PEI membrane preparation.

Keywords: Energy Dispersive X-Ray Spectroscopy, EDS, membrane, Polyetherimide, PEI, Scanning electron microscope, SEM, Solvent, X-Ray Diffraction, XRD.

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Authors: H. Masaeli, R. Ziaei, F. Khoshnoudian

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Shock response analysis of the soil–structure systems induced by near–fault pulses is investigated. Vibration transmissibility of the soil–structure systems is evaluated by shock response spectra (SRS). Medium–to–high rise buildings with different aspect ratios located on different soil types as well as different foundations with respect to vertical load bearing safety factors are studied. Two types of mathematical near–fault pulses, i.e. forward directivity and fling step, with different pulse periods as well as pulse amplitudes are selected as incident ground shock. Linear versus nonlinear soil–structure interaction (SSI) condition are considered alternatively and the corresponding results are compared. The results show that nonlinear SSI is likely to amplify the acceleration responses when subjected to long–period incident pulses with normalized period exceeding a threshold. It is also shown that this threshold correlates with soil type, so that increased shear–wave velocity of the underlying soil makes the threshold period decrease.

Keywords: Nonlinear soil–structure interaction, shock response spectrum, near–fault ground shock, rocking isolation.

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Authors: Sue-Yi Chen, Wei-Chun Hsu, Jon-Yiew Gan

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Si-based double-junction tandem solar cells have become a popular research topic because of the advantages of low manufacturing cost and high energy conversion efficiency. However, there is no set of calculations to select the appropriate top cell materials. Therefore, this paper will propose a simple but practical selection method. First of all, we calculate the S-Q limit and explain the reasons for developing tandem solar cells. Secondly, we calculate the theoretical energy conversion efficiency of the double-junction tandem solar cells while combining the commercial monocrystalline Si and materials' practical efficiency to consider the actual situation. Finally, we conservatively conclude that if considering 75% performance of the theoretical energy conversion efficiency of the top cell, the suitable bandgap energy range will fall between 1.38 eV to 2.5 eV. Besides, we also briefly describe some improvements of several proper materials, CZTS, CdSe, Cu2O, ZnTe, and CdS, hoping that future research can select and manufacture high-efficiency Si-based tandem solar cells based on this paper successfully. Most importantly, our calculation method is not limited to silicon solely. If other materials’ performances match or surpass silicon's ability in the future, researchers can also apply this set of deduction processes.

Keywords: High-efficiency solar cells, material selection, Si-based double-junction solar cells, tandem solar cells, photovoltaics.

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Authors: H. Golchoobian, M. H. Taheri, S. Saedodin, A. Sarafraz

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This paper investigates the possibility of using three systems of organic Rankine auxiliary power generation, ejector refrigeration and absorption to recover energy from a diesel car. The analysis is done for both urban and suburban driving modes that vary from 60 to 120 km/h. Various refrigerants have also been used for organic Rankine and Ejector refrigeration cycles. The capacity was evaluated by Organic Rankine Cycle (ORC) system in both urban and suburban conditions for cyclopentane and ammonia as refrigerants. Also, for these two driving plans, produced cooling by absorption refrigeration system under variable ambient temperature conditions and in ejector refrigeration system for R123, R134a and R141b refrigerants were investigated.

Keywords: Absorption system, diesel engine, ejector refrigeration, energy recovery, organic Rankine cycle.

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Authors: Aditi Shukla, Ambarish S. Vidyarthi, Subir Samanta

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The worldwide prevalence of H3N2 influenza virus and its increasing resistance to the existing drugs necessitates for the development of an improved/better targeting anti-influenza drug. H3N2 influenza neuraminidase is one of the two membrane-bound proteins belonging to group-2 neuraminidases. It acts as key player involved in viral pathogenicity and hence, is an important target of anti-influenza drugs. Oseltamivir is one of the potent drugs targeting this neuraminidase. In the present work, we have taken subtype N2 neuraminidase as the receptor and probable analogs of oseltamivir as drug molecules to study the protein-drug interaction in anticipation of finding efficient modified candidate compound. Oseltamivir analogs were made by modifying the functional groups using Marvin Sketch software and were docked using Schrodinger-s Glide. Oseltamivir analog 10 was detected to have significant energy value (16% less compared to Oseltamivir) and could be the probable lead molecule. It infers that some of the modified compounds can interact in a novel manner with increased hydrogen bonding at the active site of neuraminidase and it might be better than the original drug. Further work can be carried out such as enzymatic inhibition studies; synthesis and crystallizing the drug-target complex to analyze the interactions biologically.

Keywords: H3N2 Influenza, Neuraminidase, Oseltamiviranalogs, structure based drug designing

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Authors: Mehdi Nafar, Mohammad Reza Mansouri

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The present research presents a direct active and reactive power control (DPC) of a wind energy conversion system (WECS) for the maximum power point tracking (MPPT) based on a doubly fed induction generator (DFIG) connected to electric power grid. The control strategy of the Rotor Side Converter (RSC) is targeted in extracting a maximum of power under fluctuating wind speed. A fuzzy logic speed controller (FLC) has been used to ensure the MPPT. The Grid Side Converter is directed in a way to ensure sinusoidal current in the grid side and a smooth DC voltage. To reduce fluctuations, rotor torque and voltage use of multilevel inverters is a good way to remove the rotor harmony.

Keywords: DFIG, power quality improvement, wind energy conversion system, WECS, fuzzy logic, RSC, GSC, inverter.

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Authors: J. Radojicic, D. Surdilovic, G. Schreck

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The paper considers a novel modular and intrinsically safe redundant robotic system with biologically inspired actuators (pneumatic artificial muscles and rubber bellows actuators). Similarly to the biological systems, the stiffness of the internal parallel modules, representing 2 DOF joints in the serial robotic chains, is controlled by co-activation of opposing redundant actuator groups in the null-space of the module Jacobian, without influencing the actual robot position. The decoupled position/stiffness control allows the realization of variable joint stiffness according to different force-displacement relationships. The variable joint stiffness, as well as limited pneumatic muscle/bellows force ability, ensures internal system safety that is crucial for development of human-friendly robots intended for human-robot collaboration. The initial experiments with the system prototype demonstrate the capabilities of independently, simultaneously controlling both joint (Cartesian) motion and joint stiffness. The paper also presents the possible industrial applications of snake-like robots built using the new modules.

Keywords: bellows actuator, human-robot interaction, hyper redundant robot, pneumatic muscle.

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Authors: Zhou Yingkun, Xu Guorui, Wei Siming, Huang Yongzhang

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With the increasing of the penetration of renewable energy in power system, the whole inertia of the power system is declining, which will endanger the frequency stability of the power system. In order to enhance the inertia, virtual synchronous generator (VSG) has been proposed. In addition, the motor-generator pair (MGP) system is proposed to enhance grid inertia. Both of them need additional equipment to provide instantaneous energy, so the economic problem should be considered. In this paper, the basic working principle of MGP system and VSG are introduced firstly. Then, the technical characteristics and economic investment of MGP/VSG are compared by calculation and simulation. The results show that the MGP system can provide same inertia with less cost than VSG.

Keywords: High renewable energy penetration, inertia of power system, virtual synchronous generator, motor-generator pair system, techno-economic analysis.

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Authors: A. Bayoumi, M. Abdallah, F. Hage Chehade

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Structures on the ground surface bear impact from the tunneling-induced settlement, especially when twin tunnels are constructed. The tunneling influence on the structure is considered as a critical issue based on the construction procedure and relative position of tunnels. Lebanon is suffering from a traffic phenomenon caused by the lack of transportation systems. After several traffic counts and geotechnical investigations in Beirut city, efforts aim for the construction of tunneling systems. In this paper, we present a non-linear numerical modeling of the effect of the twin tunnels constructions on the structures located at soil surface for a particular site in Beirut. A parametric study, which concerns the geometric configuration of tunnels, the distance between their centers, the construction order, and the position of the structure, is performed. The tunnel-soil-structure interaction is analyzed by using the non-linear finite element modeling software PLAXIS 2D. The results of the surface settlement and the bending moment of the structure reveal significant influence when the structure is moved away, especially in vertical aligned tunnels.

Keywords: Bending moment, construction procedure, elastic modulus, relative position, soil, structure location, surface settlement, twin tunnels.

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Authors: Fiona Browne, Huiru Zheng, Haiying Wang, Francisco Azuaje

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Recent years have seen a growing trend towards the integration of multiple information sources to support large-scale prediction of protein-protein interaction (PPI) networks in model organisms. Despite advances in computational approaches, the combination of multiple “omic" datasets representing the same type of data, e.g. different gene expression datasets, has not been rigorously studied. Furthermore, there is a need to further investigate the inference capability of powerful approaches, such as fullyconnected Bayesian networks, in the context of the prediction of PPI networks. This paper addresses these limitations by proposing a Bayesian approach to integrate multiple datasets, some of which encode the same type of “omic" data to support the identification of PPI networks. The case study reported involved the combination of three gene expression datasets relevant to human heart failure (HF). In comparison with two traditional methods, Naive Bayesian and maximum likelihood ratio approaches, the proposed technique can accurately identify known PPI and can be applied to infer potentially novel interactions.

Keywords: Bayesian network, Classification, Data integration, Protein interaction networks.

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Authors: Farhan Beg

Abstract:

The Indian subcontinent is facing a massive challenge with regards to the energy security in member countries, i.e. providing a reliable source of electricity to facilitate development across various sectors of the economy and thereby achieve the developmental targets it has set for itself. A highly precarious situation exists in the subcontinent which is observed in the series of system failures which most of the times leads to system collapses-blackouts. To mitigate the issues related with energy security as well as keep in check the increasing supply demand gap, a possible solution that stands in front of the subcontinent is the deployment of an interconnected electricity ‘Supergrid’ designed to carry huge quanta of power across the sub continent as well as provide the infra structure for RES integration. This paper assesses the need and conditions for a Supergrid deployment and consequently proposes a meshed topology based on VSC HVDC converters for the Supergrid modeling.

Keywords: Super grid, Wind and Solar Energy, HVDC, Electricity management, Load Flow Analysis.

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Authors: Nahid-Al-Masood, Rifat Mirza, Jubaer Ahmed, Amina Hasan Abedin, S.R. Deeba, Faeza Hafiz, Mahmuda Begum, A. Hasib Chowdhury

Abstract:

Bangladesh is a developing country with large population. Demand of electrical energy is increasing day by day because of increasing population and industrialization. But due to limited resources, people here are suffering from power crisis problem which is considered as a major obstacle to the economic development. In most of the cases, it is extremely difficult to extend high tension transmission lines to some of the places that are separated from the mainland. Renewable energy is considered to be the right choice for providing clean energy to these remote settlements. This paper proposes a cost effective design of off-grid wind-diesel hybrid power system using combined heat and power (CHP) technology in a grid isolated island, Sandwip, Bangladesh. Design and simulation of the wind-diesel hybrid power system is performed considering different factors for the island Sandwip. Detailed economic analysis and comparison with solar PV system clearly reveals that wind-diesel hybrid power system can be a cost effective solution for the isolated island like Sandwip.

Keywords: renewable energy, off-grid, wind-diesel hybrid system, CHP technology, economic analysis

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Authors: Ahmed Shinkafi, Craig Lawson

Abstract:

There is a great advancement towards the All-Electric Aircraft (AEA) technology. The AEA concept assumes that all aircraft systems will be integrated into one electrical power source in the future. The principle of the electro-thermal system is to transfer the energy required for anti/de-icing to the protected areas in electrical form. However, powering a large aircraft anti-icing system electrically could be quite excessive in cost and system weight. Hence, maximising the anti/de-icing efficiency of the electro-thermal system in order to minimise its power demand has become crucial to electro-thermal de-icing system sizing. In this work, an enhanced methodology has been developed for conceptual sizing of aircraft electro-thermal de-icing System. The work factored those critical terms overlooked in previous studies which were critical to de-icing energy consumption. A case study of a typical large aircraft wing de-icing was used to test and validate the model. The model was used to optimise the system performance by a trade-off between the de-icing peak power and system energy consumption. The optimum melting surface temperatures and energy flux predicted enabled the reduction in the power required for de-icing. The weight penalty associated with electro-thermal anti-icing/de-icing method could be eliminated using this method without under estimating the de-icing power requirement.

Keywords: Aircraft de-icing system, electro-thermal, in-flight icing.

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Authors: I. Omerhodzic, S. Avdakovic, A. Nuhanovic, K. Dizdarevic

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In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.

Keywords: Epilepsy, EEG, Wavelet transform, Energydistribution, Neural Network, Classification.

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Authors: W. Kultangwattana, K. Somkantha, P. Phuangsuwan

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This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.

Keywords: Adbominal Aorta Aneurysm, Bayesian Classifier, Snakes Model, Texture Feature.

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Authors: M. Zake, I. Barmina, A. Kolmickovs, R. Valdmanis

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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3% and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10% increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10% 

Keywords: Biomass, combustion, electrodynamic control, gasification.

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Authors: Bolanle Deborah Motilewa, E. K. Rowland Worlu, Gbenga Mayowa Agboola, Ayodele Maxwell Olokundun

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Several studies have proposed a one-size fit all approach to Corporate Social Responsibility (CSR) practices, such that CSR as it applies to developed countries is adapted to developing countries, ignoring the differing institutional environments (such as the regulative, economic, social and political environments), which affects the profitability and practices of businesses operating in them. CSR as it applies to filling institutional gaps in developing countries, was categorized into four themes: environmental protection, product and service innovation, social innovation and local cluster development. Based on the four themes, the study employed a qualitative research approach through the use of interviews and review of available publications to study the influence of institutional environments on CSR practices engaged in by three renewable energy firms operating in Nigeria. Over the course of three 60-minutes sessions with the top management and selected workers of the firms, four propositions were made: regulatory environment influences environmental protection practice of Nigerian renewable firms, economic environment influences product and service innovation practice of Nigerian renewable energy firms, the social environment impacts on social innovation in Nigerian renewable energy firms, and political environment affects local cluster development practice of Nigerian renewable energy firms. It was also observed that beyond institutional environments, the international exposure of an organization’s managers reflected in their approach to CSR. This finding on the influence of international exposure on CSR practices creates an area for further study. Insights from this paper are set to help policy makers in developing countries, CSR managers, and future researchers.

Keywords: Corporate social responsibility, institutional environment, renewable energy firms, developing countries, international exposure.

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Authors: Malika Fekih, Mohamed Saighi

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Many methods exist for either measuring or estimating evaporation from free water surfaces. Evaporation pans provide one of the simplest, inexpensive, and most widely used methods of estimating evaporative losses. In this study, the rate of evaporation starting from a water surface was calculated by modeling with application to dams in wet, arid and semi arid areas in Algeria. We calculate the evaporation rate from the pan using the energy budget equation, which offers the advantage of an ease of use, but our results do not agree completely with the measurements taken by the National Agency of areas carried out using dams located in areas of different climates. For that, we develop a mathematical model to simulate evaporation. This simulation uses an energy budget on the level of a vat of measurement and a Computational Fluid Dynamics (Fluent). Our calculation of evaporation rate is compared then by the two methods and with the measures of areas in situ.

Keywords: Evaporation, Energy budget, Surface water temperature, CFD, Dams

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Authors: Tae-Hyub Hong, Choeng-Ryul Choi, Chang-Nyung Kim

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Human heart valves diseased by congenital heart defects, rheumatic fever, bacterial infection, cancer may cause stenosis or insufficiency in the valves. Treatment may be with medication but often involves valve repair or replacement (insertion of an artificial heart valve). Bileaflet mechanical heart valves (BMHVs) are widely implanted to replace the diseased heart valves, but still suffer from complications such as hemolysis, platelet activation, tissue overgrowth and device failure. These complications are closely related to both flow characteristics through the valves and leaflet dynamics. In this study, the physiological flow interacting with the moving leaflets in a bileaflet mechanical heart valve (BMHV) is simulated with a strongly coupled implicit fluid-structure interaction (FSI) method which is newly organized based on the Arbitrary-Lagrangian-Eulerian (ALE) approach and the dynamic mesh method (remeshing) of FLUENT. The simulated results are in good agreement with previous experimental studies. This study shows the applicability of the present FSI model to the complicated physics interacting between fluid flow and moving boundary.

Keywords: Bileaflet Mechanical Heart Valve, Fluid- Structure Interaction.

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Authors: M. Kamal M. Shah, Noorhifiantylaily Ahmad, O. Irma Wani, J. Sahari

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This paper presents the computationally mechanics analysis of energy absorption for cylindrical and square thin wall tubed structure by using ABAQUS/explicit. The crashworthiness behavior of AISI 1020 mild steel thin-walled tube under axial loading has been studied. The influence effects of different model’s cross-section, as well as model length on the crashworthiness behavior of thin-walled tube, are investigated. The model was placed on loading platform under axial loading with impact velocity of 5 m/s to obtain the deformation results of each model under quasi-static loading. The results showed that model undergoes different deformation mode exhibits different energy absorption performance.

Keywords: Axial loading, energy absorption performance, computational mechanics, crashworthiness behavior, deformation mode, thin-walled tubes.

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Authors: N. Hadthamard, P. Chaumpluk, M. Buanong, P. Boonyaritthongchai, C. Wongs-Aree

Abstract:

Ripe ‘Nam Dok Mai’ mango (Mangifera indica L.) is an important exported fruit of Thailand, but rapidly declined in the quality attributes mainly by infection of anthracnose and stem end rot diseases. Multilayer coating is considered as a developed technique to maintain the postharvest quality of mangoes. The utilization of alternated coating by matching oppositely electrostatic charges between 0.1% chitosan and 0.1% polystyrene sulfonate (PSS) was studied. A number of the coating layers (layer by layer) were applied on mature green ‘Nam Dok Mai No.4’ mangoes prior to storage at 25 ^oC, 65-70% relative humidity (RH). There were significant differences in some quality attributes of mangoes coated by 3½ layers, 4½ layers and 5½ layers. In comparison to coated mangoes, uncoated fruits were higher in weight loss, total soluble solids, respiration rate, ethylene production and disease incidence except the titratable acidity. Coating fruit at 3½ layers exhibited the ripening delay and reducing disease infection without off flavour. On the other hand, fruit coated with 5½ layers comprised the lowest acceptable score, caused by exhibiting disorders from fermentation at the end of storage. As a result, multilayer coating between chitosan and PSS could effectively maintain the postharvest quality of mango, but number of coating layers should be thoroughly considered.

Keywords: Multilayer, chitosan, polystyrene sulfonate, Nam Dok Mai No.4.

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Authors: N. J. Imu, N. Rabbani, Md E. Hossain

Abstract:

Achieving national climate goals requires transforming the energy system and increasing the use of renewable energy in Bangladesh as renewable energy offers an environmentally friendly energy supply. In view of this, Bangladesh has set a goal of 100% renewable power generation by 2050. Among all the renewable energy, solar is the most effective and popular source of renewable energy in Bangladesh. In order to build up on-grid and off-grid solar systems to increase energy transformation, monocrystalline type (highly efficient) solar module, and the polycrystalline type (low-efficient) solar module are commonly used. Due to their low price and availability, polycrystalline-type solar modules dominated the local market in the past years. However, in recent times the use of monocrystalline types modules has increased considerably owing to the significant decrease in price difference that existed between these two modules. Despite the deployment of both mono- and poly-crystalline modules in the market, the proliferation of low-quality solar panels are dominating the market resulting in reduced generation of solar electricity than expected. This situation is further aggravated by insufficient information regarding the effect of solar irradiation on solar module performance in relation to the quality of the materials used for the production of the module. This research aims to evaluate the efficiency of monocrystalline and polycrystalline solar modules that are available in Bangladesh by considering seasonal variations. Both types of solar modules have been tested for three different capacities 45W, 60W, and 100W in Dhaka regions to evaluate their power generation capability under Standard Test Conditions (STC). Module testing data were recorded twelve months in a full year from January to December. Data for solar irradiation were collected using HT304N while HT I-V400 multifunction instrument was used for testing voltage and current of photovoltaic (PV) systems and complete power quality analyzer. Results obtained in this study indicated differences between the efficiencies of polycrystalline and monocrystalline solar modules under the country’s solar irradiation. The average efficiencies of 45W, 60W, and 100W monocrystalline solar panels were recorded as 11.73%, 13.41%, and 15.37% respectively while for polycrystalline panels were 8.66%, 9.37%, and 12.34%. Monocrystalline solar panels, which offer greater working output than polycrystalline ones, are also represented by the Pearson Correlation value. The output of polycrystalline solar panels fluctuated highly with the changes in irradiation and temperature whereas monocrystalline panels were much stable.

Keywords: Solar energy, solar irradiation, efficiency, polycrystalline solar module, monocrystalline solar module, SPSS analysis.

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Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

Abstract:

Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: Climate, reanalysis, renewable energy, solar radiation.

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