Search results for: graph storage structure

Authors: Lakshmi E. Jayachandran, Manepally Rajkumar, Pavuluri Srinivasa Rao

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The objective of this research was to study the changes in eating quality of rice during storage under varying temperature and moisture regimes. Paddy (IR-36) with high amylose content (27%) was stored at a temperature range between 10 to 40°C and moisture content from 9 to 18% (d.b.) for 6 months. Drastic changes in color and parameters representing cooking qualities, cooked rice texture, and surface morphology occurred after 4 months of storage, especially at elevated temperature conditions. Head rice yield was stable throughout the storage except at extreme conditions of temperature and moisture content. Yellowing of rice was prominent at combinations of high temperature and moisture content, both of which had a synergistic effect on the b* values of rice. The cooking time, length expansion ratio and volume expansion ratio of all the rice samples increased with prolonged storage. The texture parameter, primarily, the hardness, cohesiveness, and adhesiveness of cooked rice samples were higher following storage at elevated temperature. Surface morphology was also significantly affected in stored rice as compared to fresh rice. Storage of rice at 10°C with a grain moisture content of 10% for 2 months gave cooked rice samples with good palatability and minimal cooking time. The temperature was found to be the most prominent storage parameter for rough rice, followed by moisture content and storage duration, influencing the quality of rice.

Keywords: rice, cooking quality, storage, surface morphology

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Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

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This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

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Authors: Sawsen Khlifa, Chiheb AMeur Abid, Belhassan Zouari

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Modular verification approaches have been widely attempted to cope with the well known state explosion problem. This paper deals with the modular verification of modular Petri nets. We propose a reduced version for the modular state space of a given modular Petri net. The new structure allows the creation of smaller modular graphs. Each one draws the behavior of the corresponding module and outlines some global information. Hence, this version helps to overcome the explosion problem and to use less memory space. In this condensed structure, the verification of some generic properties concerning one module is limited to the exploration of its associated graph.

Keywords: distributed systems, modular verification, petri nets, state space explosition

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Authors: Sujin Hong, Seokyoon Moon, Heejoong Kim, Yunseok Lee, Youngjune Park

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Gas hydrate is an inclusion compound in which a low-molecular-weight gas or organic molecule is trapped inside a three-dimensional lattice structure created by water-molecule via intermolecular hydrogen bonding. It is generally formed at low temperature and high pressure, and exists as crystal structures of cubic systems − structure I, structure II, and hexagonal system − structure H. Many efforts have been made to apply them to various energy and environmental fields such as gas transportation and storage, CO₂ capture and separation, and desalination of seawater. Particularly, studies on the behavior of gas hydrates by new organic materials for CO₂ storage and various applications are underway. In this study, thermodynamic and spectroscopic analyses of the gas hydrate system were performed focusing on cyclopentanol, an organic molecule that forms gas hydrate at relatively low pressure. The thermodynamic equilibria of CH₄ and CO₂ hydrate systems including cyclopentanol were measured and spectroscopic analyses of XRD and Raman were performed. The differences in thermodynamic systems and formation kinetics of CO₂ added cyclopentane, cyclopentanol and cyclopentanone hydrate systems were compared. From the thermodynamic point of view, cyclopentanol was found to be a hydrate promotor. Spectroscopic analyses showed that cyclopentanol formed a hydrate crystal structure of cubic structure II in the presence of CH₄ and CO₂. It was found that the differences in the functional groups among the organic guest molecules significantly affected the rate of hydrate formation and the total amounts of CO₂ stored in the hydrate systems. The total amount of CO₂ stored in the cyclopentanone hydrate was found to be twice that of the amount of CO₂ stored in the cyclopentane and the cyclopentanol hydrates. The findings are expected to open up new opportunity to develop the gas hydrate based wastewater desalination technology.

Keywords: gas hydrate, CO₂, separation, desalination, formation kinetics, thermodynamic equilibria

Procedia PDF Downloads 233

Authors: Alia Al Nuaimi, Ayesha Al Aberi, Faiza Al Marzouqi, Shaikha Salem Ali Al Yahyaee, Ala Hussein

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In this paper, a PV micro-storage system for residential applications is proposed. The term micro refers to the size of the PV storage system, which is in the range of few kilo-watts, compared to the grid size (~GWs). Usually, in a typical load profile of a residential unit, two peak demand periods exist: one at morning and the other at evening time. The morning peak can be partly covered by the PV energy directly, while the evening peak cannot be covered by the PV alone. Therefore, an energy storage system that stores solar energy during daytime and use this stored energy when the sun is absent is a must. A complete design procedure including theoretical analysis followed by simulation verification and economic feasibility evaluation is addressed in this paper.

Keywords: battery, energy storage, photovoltaic, peak shaving, smart grid

Procedia PDF Downloads 283

Authors: Prat Yotyawilai, Taratip Suwannasart

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Business Process Model and Notation (BPMN) is more important in the business process and creating functional models, and is a standard for OMG, which becomes popular in various organizations and in education. Researches related to software testing based on models are prominent. Although most researches use the UML model in software testing, not many researches use the BPMN Model in creating test cases. Therefore, this research proposes a design of a tool for generating test cases from the BPMN. The model is analyzed and the details of the various components are extracted before creating a flow graph. Both details of components and the flow graph are used in generating test cases.

Keywords: software testing, test case, BPMN, flow graph

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Authors: Marjan Javanmard

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The rheological properties of dairy products critically depend on the underlying organisation of proteins at multiple length scales. When heated and acidified, milk proteins form particle gel that is viscoelastic, solvent rich, ‘soft’ material. In this work recent developments on the rheology of soft particles suspensions were used to interpret and potentially define the properties of dairy gel structures. It is discovered that at volume fractions below random close packing (RCP), the Maron-Pierce-Quemada (MPQ) model accurately predicts the viscosity of the dairy gel suspensions without fitting parameters; the MPQ model has been shown previously to provide reasonable predictions of the viscosity of hard sphere suspensions from the volume fraction, solvent viscosity and RCP. This surprising finding demonstrates that up to RCP, the dairy gel system behaves as a hard sphere suspension and that the structural aggregates behave as discrete particulates akin to what is observed for microgel suspensions. At effective phase volumes well above RCP, the system is a soft solid. In this region, it is discovered that the storage modulus of the sheared AMG scales with the storage modulus of the set gel. The storage modulus in this regime is reasonably well described as a function of effective phase volume by the Evans and Lips model. Findings of this work has potential to aid in rational design and control of dairy food structure-properties.

Keywords: dairy suspensions, rheology-structure, Maron-Pierce-Quemada Model, Evans and Lips Model

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Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Annie B. V., Anu A. G., Harikumar R.

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Microgrid (MG) is a self-governing miniature section of the power system. Nowadays the majority of loads and energy storage devices are inherently in DC form. This necessitates a greater scope of research in the various types of energy storage devices in DC microgrids. In a modern power system, DC microgrid is a manageable electric power system usually integrated with renewable energy sources (RESs) and DC loads with the help of power electronic converters. The stability of the DC microgrid mainly depends on the power imbalance. Power imbalance due to the presence of intermittent renewable energy resources (RERs) is supplied by energy storage devices. Battery, supercapacitor, flywheel, etc. are some of the commonly used energy storage devices. Owing to the high energy density provided by the batteries, this type of energy storage system is mainly utilized in all sorts of hybrid energy storage systems. To minimize the stability issues, a Supercapacitor (SC) is usually interfaced with the help of a bidirectional DC/DC converter. SC can exchange power during transient conditions due to its high power density. This paper analyses the stability issues of DC microgrids with hybrid energy storage systems (HESSs) arises from a reduction in SC operating voltage due to self-discharge. The stability of DC microgrid and power management is analyzed with different control strategies.

Keywords: DC microgrid, hybrid energy storage system (HESS), power management, small signal modeling, supercapacitor

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Authors: S. Khardazi, H. Zaitouni, A. Neqali, S. Lyubchyk, D. Mezzane, M. Amjoud, E. Choukri, S. Lyubchyk, Z. Kutnjak

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In the present paper, structural, dielectric, ferroelectric, and energy storage properties of pure perovskite lead-free BCZT, BTSn, and BTSn-BCZT ferroelectric ceramics have been investigated. Rietveld refinement of XRD data confirms the coexistence of the rhombohedral and orthorhombic phases at room temperature in the composite BCZT–BTSn ceramic. Remarkably, an improved recoverable energy density of 137.86 mJ/cm³ and a high energy storage efficiency of 86.19 % at 80°C under a moderate applied electric field of 30 kV/cm were achieved in the designed BCZT–BTSn ceramic. Besides, the sample exhibits excellent thermal stability of the energy storage efficiency (less than 3%) in the temperature range of 70 to 130 °C under 30 kV/cm. Such results make the pb-free BCZT–BTSn ferroelectric ceramic a very promising potential matrix for energy storage capacitor applications.

Keywords: sol-gel, ferroelectrics, lead-free, perovskites, energy storage

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Authors: Yuchao Hua, Lingai Luo

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Thermal energy storage is of critical importance for the highly-efficient utilization of renewable energy sources. Over the past decades, single-tank thermocline technology has attracted much attention owing to its high cost-effectiveness. In the present work, we investigate the influence of the filler porosity’s non-uniform distribution on the thermal performance of the packed-bed sensible heat thermocline storage tanks on the basis of the analytical model obtained by the Laplace transform. It is found that when the total amount of filler materials (i.e., the integration of porosity) is fixed, the different porosity distributions can result in the significantly-different behaviors of outlet temperature and thus the varied charging and discharging efficiencies. Our results indicate that a non-uniform distribution of the fillers with the proper design can improve the heat storage performance without changing the total amount of the filling materials.

Keywords: energy storage, heat thermocline storage tank, packed bed, transient thermal analysis

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Authors: Mahdi Jalili

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Functional connectivity in the human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks – whose nodes are brain regions and edges correspond to functional links between them – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using correlation analysis and were further binarized to obtain binary functional networks. Global and local efficiency measures – as graph theory metrics– were computed for the extracted networks. We found that male brains have a significantly greater global efficiency (i.e., global communicability of the network) across all frequency bands for a wide range of cost values in both hemispheres. Furthermore, for a range of cost values, female brains showed significantly greater right-hemispheric local efficiency (i.e., local connectivity) than male brains.

Keywords: EEG, brain, functional networks, network science, graph theory

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Authors: A. Kellou, L. Rouaiguia, L. Rabahi

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In the present work, the atomic hydrogen absorption trend in the GdNi5 and GdNi4Cu rare earth compounds within the hexagonal CaCu5 type of crystal structure (space group P6/mmm) is investigated. The density functional theory (DFT) combined with the generalized gradient approximation (GGA) is used to study the site preference of atomic hydrogen at 0K. The octahedral and tetrahedral interstitial sites are considered. The formation energies and structural properties are determined in order to evaluate hydrogen effects on the stability of the studied compounds. The energetic diagram of hydrogen storage is established and compared in GdNi5 and GdNi4Cu. The magnetic properties of the selected compounds are determined using spin polarized calculations. The obtained results are discussed with and without hydrogen addition taking into account available theoretical and experimental results.

Keywords: density functional theory, hydrogen storage, rare earth compounds, structural and magnetic properties

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

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Authors: Hae-Yeoun Lee

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Quantification of cardiac function is performed by calculating blood volume and ejection fraction in routine clinical practice. However, these works have been performed by manual contouring,which requires computational costs and varies on the observer. In this paper, an automatic left ventricle segmentation algorithm on cardiac magnetic resonance images (MRI) is presented. Using knowledge on cardiac MRI, a K-mean clustering technique is applied to segment blood region on a coil-sensitivity corrected image. Then, a graph searching technique is used to correct segmentation errors from coil distortion and noises. Finally, blood volume and ejection fraction are calculated. Using cardiac MRI from 15 subjects, the presented algorithm is tested and compared with manual contouring by experts to show outstanding performance.

Keywords: cardiac MRI, graph searching, left ventricle segmentation, K-means clustering

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Authors: Subhash Chandra Sharma, Mohammad Soleimani

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Selection of the correct lubricant for the top of rail application is a complex process. In this paper, the selection of the proper lubricant for a Top-Of-Rail (TOR) lubrication system based on graph theory and matrix approach has been developed. Attributes influencing the selection process and their influence on each other has been represented through a digraph and an equivalent matrix. A matrix function which is called the Permanent Function is derived. By substituting the level of inherent contribution of the influencing parameters and their influence on each other qualitatively, a criterion called Suitability Index is derived. Based on these indices, lubricants can be ranked for their suitability. The proposed model can be useful for maintenance engineers in selecting the best lubricant for a TOR application. The proposed methodology is illustrated step–by-step through an example.

Keywords: lubricant selection, top of rail lubrication, graph-theory, Ranking of lubricants

Procedia PDF Downloads 266

Authors: E. R. Swart, S. J. Gismondi, N. R. Swart, C. E. Bell

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We present an heuristic algorithm that decides graph non-Hamiltonicity. All graphs are directed, each undirected edge regarded as a pair of counter directed arcs. Each of the n! Hamilton cycles in a complete graph on n+1 vertices is mapped to an n-permutation matrix P where p(u,i)=1 if and only if the ith arc in a cycle enters vertex u, starting and ending at vertex n+1. We first create exclusion set E by noting all arcs (u, v) not in G, sufficient to code precisely all cycles excluded from G i.e. cycles not in G use at least one arc not in G. Members are pairs of components of P, {p(u,i),p(v,i+1)}, i=1, n-1. A doubly stochastic-like relaxed LP formulation of the Hamilton cycle decision problem is constructed. Each {p(u,i),p(v,i+1)} in E is coded as variable q(u,i,v,i+1)=0 i.e. shrinks the feasible region. We then implement the Weak Closure Algorithm (WCA) that tests necessary conditions of a matching, together with Boolean closure to decide 0/1 variable assignments. Each {p(u,i),p(v,j)} not in E is tested for membership in E, and if possible, added to E (q(u,i,v,j)=0) to iteratively maximize |E|. If the WCA constructs E to be maximal, the set of all {p(u,i),p(v,j)}, then G is decided non-Hamiltonian. Only non-Hamiltonian G share this maximal property. Ten non-Hamiltonian graphs (10 through 104 vertices) and 2000 randomized 31 vertex non-Hamiltonian graphs are tested and correctly decided non-Hamiltonian. For Hamiltonian G, the complement of E covers a matching, perhaps useful in searching for cycles. We also present an example where the WCA fails.

Keywords: Hamilton cycle decision problem, computational complexity theory, graph theory, theoretical computer science

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Authors: Antonin Jolly, Bertrand Aubry, Corentin Michel, Rebecca Freva

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Wind energy depends on wind strength and varies largely in time. When it is above the demand, it generates a loss while in the opposite case; energy needs are not fully satisfied. To overcome this problem specific to irregular energies, the process of pumped-storage hydroelectricity (PSH) is studied in present paper. A combination of wind turbine and pumped storage system is more predictable and is more compliant to provide electricity supply according to daily demand. PSH system is already used in several countries to accumulate electricity by pumping water during off-peak times into a storage reservoir, and to use it during peak times to produce energy. Present work discusses a feasibility study on size and financial productivity of PSH system actuated with wind turbines specific power.

Keywords: wind turbine, hydroelectricity, energy storage, pumped-storage hydroelectricity

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Authors: Ayşe Dilek Maden

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For a given a simple connected graph, we present some new bounds via a new approach for a special topological index given by the sum of the real number power of the non-zero normalized Laplacian eigenvalues. To use this approach presents an advantage not only to derive old and new bounds on this topic but also gives an idea how some previous results in similar area can be developed.

Keywords: degree Kirchhoff index, normalized Laplacian eigenvalue, spanning tree, simple connected graph

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Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

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Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

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Authors: Umar Hayatu Sidik

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The natural gas vehicle represents a cost-competitive, lower-emission alternative to the gasoline-fuelled vehicle. The immediate challenge that confronts natural gas is increasing its energy density. This paper addresses the question of energy density by reviewing the storage technologies for natural gas with improved adsorbent. Technical comparisons are made between storage systems containing adsorbent and conventional compressed natural gas based on the associated amount of moles contained with Compressed Natural Gas (CNG) and Adsorbed Natural Gas (ANG). We also compare gas storage in different cylinder types (1, 2, 3 and 4) based on weight factor and storage capacity. For the storage tank system, we discussed the concept of carbon adsorbents, when used in CNG tanks, offer a means of increasing onboard fuel storage and, thereby, increase the driving range of the vehicle. It confirms that the density of the stored gas in ANG is higher than that of compressed natural gas (CNG) operated at the same pressure. The obtained experimental data were correlated using linear regression analysis with common adsorption kinetic (Pseudo-first order and Pseudo-second order) and isotherm models (Sip and Toth). The pseudo-second-order kinetics describe the best fitness with a correlation coefficient of 9945 at 35 bar. For adsorption isotherms, the Sip model shows better fitness with the regression coefficient (R2) of 0.9982 and with the lowest RSMD value of 0.0148. The findings revealed the potential of adsorbent in natural gas storage applications.

Keywords: natural gas, adsorbent, compressed natural gas, adsorption

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Authors: Boumesbah Asma, Chergui Mohamed El-amine

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Since it has been shown that the multi-objective minimum spanning tree problem (MOST) is NP-hard even with two criteria, we propose in this study a hybrid NSGA-II algorithm with an exact mutation operator, which is only used with low probability, to find an approximation to the Pareto front of the problem. In a connected graph G, a spanning tree T of G being a connected and cycle-free graph, if k edges of G\T are added to T, we obtain a partial graph H of G inducing a reduced size multi-objective spanning tree problem compared to the initial one. With a weak probability for the mutation operator, an exact method for solving the reduced MOST problem considering the graph H is then used to give birth to several mutated solutions from a spanning tree T. Then, the selection operator of NSGA-II is activated to obtain the Pareto front approximation. Finally, an adaptation of the VNS metaheuristic is called for further improvements on this front. It allows finding good individuals to counterbalance the diversification and the intensification during the optimization search process. Experimental comparison studies with an exact method show promising results and indicate that the proposed algorithm is efficient.

Keywords: minimum spanning tree, multiple objective linear optimization, combinatorial optimization, non-sorting genetic algorithm, variable neighborhood search

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Authors: Liu Fangxin, Zhao Jijun

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Nowadays, China and the world are facing the same problems of flooding, city waterlogging and other environment issues. Throughout history, China had many excellent experiences dealing with the flood, and can be used as a significant reference for contemporary urban construction. In view of this, the research used the method of literature analysis to find out the main water storage measures in ancient cities, including reservoir storage and pond water storage. And it used the case study method to introduce the historical evolution, engineering measures and landscape design of 4 typical ancient Chinese cities in details. Then we found the pond and the reservoir were the main infrastructures for the ancient Chinese city to avoid the waterlogging and flood. At last this paper summed up the historical experience of Chinese traditional water storage and made conclusions that the establishment of a reasonable green water storage facilities could be used to solve today's rain and flood problems, and hoped to give some enlightenment of stormwater management to our modern city.

Keywords: ancient Chinese cities, water storage project, Chinese classical gardening, stormwater management, green facilities

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Authors: Itumeleng Phage

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Students’ comprehension of graphs may be affected by the characteristics of the discipline in which the graph is used, the type of the task as well as the background of the students who are the readers or interpreters of the graph. This research study investigated these aspects of the graph comprehension of 152 first-year undergraduate physics students by comparing their responses to corresponding tasks in the mathematics and physics disciplines. The discipline characteristics were analysed for four task-related constructs namely coordinates, representations, area and slope. Students’ responses to corresponding visual decoding and judgement tasks set in mathematics and kinematics contexts were statistically compared. The effects of the participants’ gender, year of school completion and study course were determined as reader characteristics. The results of the empirical study indicated that participants generally transferred their mathematics knowledge on coordinates and representation of straight line graphs to the physics contexts, but not in the cases of parabolic and hyperbolic functions or area under graphs. Insufficient understanding of the slope concept contributed to weak performances on this construct in both mathematics and physics contexts. Discipline characteristics seem to play a vital role in students’ understanding, while reader characteristics had insignificant to medium effects on their responses.

Keywords: kinematics graph, discipline characteristics, constructs, coordinates, representations, area and slope

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Authors: Seshi Reddy Kasu, Florian Misoc

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The use of hydroelectric pump-storage system at large scale, MW-size systems, is already widespread around the world. Designed for large scale applications, pump-storage station can be scaled-down for small, remote residential applications. Given the cost and complexity associated with installing a substation further than 100 miles from the main transmission lines, a remote, independent and self-sufficient system is by far the most feasible solution. This article is aiming at the design of wind and solar power generating system, by means of pumped-storage to replace the wind and/or solar power systems with a battery bank energy storage. Wind and solar pumped-storage power generating system can reduce the cost of power generation system, according to the user's electricity load and resource condition and also can ensure system reliability of power supply. Wind and solar pumped-storage power generation system is well suited for remote residential applications with intermittent wind and/or solar energy. This type of power systems, installed in these locations, could be a very good alternative, with economic benefits and positive social effects. The advantage of pumped storage power system, where wind power regulation is calculated, shows that a significant smoothing of the produced power is obtained, resulting in a power-on-demand system’s capability, concomitant to extra economic benefits.

Keywords: battery bank, photo-voltaic, pump-storage, wind energy

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Authors: Zhengrong Wu, Haibo Yang

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In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

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Authors: Somyung Oh, Jeonghyeon Ha, Kyungwon Lee, Sejong Oh

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Microarray is a general scheme to find differentially expressed genes for target concept. The output is expressed by heat map, and biologists analyze related terms of gene ontology to find some characteristics of differentially expressed genes. In this paper, we propose integrated visualization tool for heat map and gene ontology graph. Previous two methods are used by static manner and separated way. Proposed visualization tool integrates them and users can interactively manage it. Users may easily find and confirm related terms of gene ontology for given differentially expressed genes. Proposed tool also visualize connections between genes on heat map and gene ontology graph. We expect biologists to find new meaningful topics by proposed tool.

Keywords: heat map, gene ontology, microarray, differentially expressed gene

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Authors: Carlos F. Sanz-Navarro, Sonia Fereres

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Binary and ternary mixtures of molten salts are excellent thermal energy storage systems and have been widely used in commercial tanks both in nuclear and solar thermal applications. However, the energy density of the commercially used mixtures is still insufficient, and therefore, new systems based on latent heat storage (or phase change materials, PCM) are currently being investigated. In order to shed some light on the macroscopic physical properties of the molten salt phases, knowledge of the microscopic structure and dynamics is required. Several molecular dynamics (MD) simulations have been performed to model the thermal behavior of (Li,K)2CO3 mixtures. Up to this date, this particular molten salt mixture has not been extensively studied but it is of fundamental interest for understanding the behavior of other commercial salts. Molten salt diffusivities, the internal electrical ion mobility, and the physical properties of the solid-liquid phase transition have been calculated and compared to available data from literature. The effect of anion polarization and the application of a strong external electric field have also been investigated. The influence of electrical ion mobility on local composition is explained through the Chemla effect, well known in electrochemistry. These results open a new way to design optimal high temperature energy storage materials.

Keywords: atomistic simulations, thermal storage, latent heat, molten salt, ion mobility

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Authors: Jinyong Yao, Hongzhi Li, Chao Du, Jiao Li

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Reliability of long-term storage products is related to the availability of the whole system, and the evaluation of storage life is of great necessity. These products are usually highly reliable and little failure information can be collected. In this paper, an analytical method based on data from accelerated storage life test is proposed to evaluate the reliability index of the long-term storage products. Firstly, singularities are eliminated by data normalization and residual analysis. Secondly, with the pre-processed data, the degradation path model is built to obtain the pseudo life values. Then by life distribution hypothesis, we can get the estimator of parameters in high stress levels and verify failure mechanisms consistency. Finally, the life distribution under the normal stress level is extrapolated via the acceleration model and evaluation of the true average life available. An application example with the camera stabilization device is provided to illustrate the methodology we proposed.

Keywords: accelerated storage life test, failure mechanisms consistency, life distribution, reliability

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Authors: Osama Saber

Abstract:

Cyanate is one such anion which is produced during protein poisoning in the body and has been studied extensively in the field of biochemistry because of its toxicity. The present work aims at confinement and storage of cyanate in the nano scale. It was achieved through the intercalation of cyanate anions into nanolayerd structures of Ni-Al LDH. In addition, the effect of aging time on the intercalation of cyanate was clarified using X-ray diffraction and scanning electron microscopy. Furthermore, the effect of cations on the affinity towards the intercalation of cyanate anions inside LDH structure was studied by replacement of tetra-valent cations Ti4+ instead of the tri-vallent cations Al3+ during the preparation of LDH structure. X-ray diffraction patterns of the Ni-Ti LDH showed that the interlayer spacing was 0.73 nm. This spacing was smaller than that of Ni-Al LDH suggesting that the interlayered anions into Ni-Ti LDH are different from those into Ni-Al LDH. Thermal analyses (TG, DTG, and DTA) and Infra-red spectra revealed the presence of only cyanate anions into Ni-Ti LDH while, in the case of Ni-Al LDH, both cyanate and carbonate anions were observed. SEM images showed plate-like morphology for both Ni-Ti and Ni-Al LDHs although the shapes of their plates are not similar. Our results suggested that the LDH structures containing titanium cations have higher affinity for cyanate anions than those containing aluminum cations. Therefore, this choice for cyanate in the interlayered spacing widens the applicability to study the effect of the confinement on the toxicity of cyanate by bio researchers.

Keywords: nanolayered structures, Ni-Al LDH, Ni-Ti LDH, intercalation of cyanate anions, urea hydrolysis

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