Search results for: graph spectra

Authors: M. M. M. Jaradat

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For a given graph G, the set Ԑ of all subsets of E(G) forms an |E(G)| dimensional vector space over Z2 with vector addition X⊕Y = (X\Y ) [ (Y \X) and scalar multiplication 1.X = X and 0.X = Ø for all X, Yϵ Ԑ. The cycle space, C(G), of a graph G is the vector subspace of (E; ⊕; .) spanned by the cycles of G. Traditionally there have been two notions of minimality among bases of C(G). First, a basis B of G is called a d-fold if each edge of G occurs in at most d cycles of the basis B. The basis number, b(G), of G is the least non-negative integer d such that C(G) has a d-fold basis; a required basis of C(G) is a basis for which each edge of G belongs to at most b(G) elements of B. Second, a basis B is called a minimum cycle basis (MCB) if its total length Σ BϵB |B| is minimum among all bases of C(G). The lexicographic product GρH has the vertex set V (GρH) = V (G) x V (H) and the edge set E(GρH) = {(u1, v1)(u2, v2)|u1 = u2 and v1 v2 ϵ E(H); or u1u2 ϵ E(G) and there is α ϵ Aut(H) such that α (v1) = v2}. In this work, a construction of a minimum cycle basis for the wreath product of wheels with paths is presented. Also, the length of the longest cycle of a minimum cycle basis is determined. Moreover, the basis number for the wreath product of the same is investigated.

Keywords: cycle space, minimum cycle basis, basis number, wreath product

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Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

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Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

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Authors: Jose M. Gallardo, Nieves Jimenez, Andres Jimenez-Losada, Esperanza Lebron

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A game with a priori incompatibilities is a triple (N,v,g) where (N,v) is a cooperative game, and (N,g) is a graph which establishes initial incompatibilities between some players. In these games, the negotiation has two stages. In the first stage, players can only negotiate with others with whom they are compatible. In the second stage, the grand coalition will be formed. We introduce a value for these games. Given a game with a priori incompatibility (N,v,g), we consider the family of coalitions without incompatibility relations among their players. This family is a normal set system or coalition configuration Ig. Therefore, we can assign to each game with a priori incompatibilities (N,v,g) a game with coalition configuration (N,v, Ig). Now, in order to obtain a payoff vector for (N,v,g), it suffices to calculate a payoff vector for (N,v, Ig). To this end, we apply a value for games with coalition configuration. In our case, we will use the dual configuration value, which has been studied in the literature. With this method, we obtain a value for games with a priori incompatibilities, which is called the Owen value for a priori incompatibilities. We provide a characterization of this value.

Keywords: cooperative game, game with coalition configuration, graph, independent set, Owen value, Shapley value

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Authors: Chetneti Srisa-an

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In Knowledge and Data Engineering field, relational database is the best repository to store data in a real world. It has been using around the world more than eight decades. Normalization is the most important process for the analysis and design of relational databases. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. Normalization is a major task in the design of relational databases. Despite its importance, very few algorithms have been developed to be used in the design of commercial automatic normalization tools. It is also rare technique to do it automatically rather manually. Moreover, for a large and complex database as of now, it make even harder to do it manually. This paper presents a new complete automated relational database normalization method. It produces the directed graph and spanning tree, first. It then proceeds with generating the 2NF, 3NF and also BCNF normal forms. The benefit of this new algorithm is that it can cope with a large set of complex function dependencies.

Keywords: relational database, functional dependency, automatic normalization, primary key, spanning tree

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Authors: Cao Xiaopeng, Shi Linkai

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The practical Byzantine fault-tolerant algorithm does not add nodes dynamically. It is limited in practical application. In order to add nodes dynamically, Dynamic Practical Byzantine Fault Tolerance Algorithm (DPBFT) was proposed. Firstly, a new node sends request information to other nodes in the network. The nodes in the network decide their identities and requests. Then the nodes in the network reverse connect to the new node and send block information of the current network. The new node updates information. Finally, the new node participates in the next round of consensus, changes the view and selects the master node. This paper abstracts the decision of nodes into the undirected connected graph. The final consistency of the graph is used to prove that the proposed algorithm can adapt to the network dynamically. Compared with the PBFT algorithm, DPBFT has better fault tolerance and lower network bandwidth.

Keywords: practical byzantine, fault tolerance, blockchain, consensus algorithm, consistency analysis

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Ozlem Temiz Arpaci, Meryem Tasci, Hakan Goker

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Benzimidazole, a structural isostere of indol and purine nuclei that can interact with biopolymers, can be identified as master key. So that benzimidazole compounds are important fragments in medicinal chemistry because of their wide range of biological activities including antimicrobial activity. We planned to synthesize some benzimidazole compounds for developing new antimicrobial drug candidates. In this study, we put some heterocyclic rings on second position and an amidine group on the fifth position of benzimidazole ring and synthesized them using a multiple step procedure. For the synthesis of the compounds, as the first step, 4-chloro-3-nitrobenzonitrile was reacted with cyclohexylamine in dimethyl formamide. Imidate esters (compound 2) were then prepared with absolute ethanol saturated with dry HCl gas. These imidate esters which were not too stable were converted to compound 3 by passing ammonia gas through ethanol. At the Pd / C catalyst, the nitro group is reduced to the amine group (compound 4). Finally, various aldehyde derivatives were reacted with sodium metabisulfite addition products to give compound 5-20. Melting points were determined on a Buchi B-540 melting point apparatus in open capillary tubes and are uncorrected. Elemental analyses were done a Leco CHNS 932 elemental analyzer. 1H-NMR and 13C-NMR spectra were recorded on a Varian Mercury 400 MHz spectrometer using DMSO-d6. Mass spectra were acquired on a Waters Micromass ZQ using the ESI(+) method. The structures of them were supported by spectral data. The 1H-NMR, 13C NMR and mass spectra and elemental analysis results agree with those of the proposed structures. Antimicrobial activity studies of the synthesized compounds are under the investigation.

Keywords: benzimidazoles, synthesis, structure elucidation, antimicrobial

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Authors: Surjyakanta Rana, Sreekantha B. Jonnalagadda

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Synthesis of well distributed Pd nanoparticles (3 – 7 nm) on organo amine-functionalized graphene is reported, which demonstrated excellent catalytic activity towards Suzuki coupling reaction. The active material was characterized by X-ray diffraction (XRD), BET surface area, X-ray photoelectron spectra (XPS), Fourier-transfer infrared spectroscopy (FTIR), Raman spectra, Scanning electron microscope (SEM), Transmittance electron microscopy (TEM) analysis and HRTEM. FT-IR revealed that the organic amine functional group was successfully grafted onto the graphene oxide surface. The formation of palladium nanoparticles was confirmed by XPS, TEM and HRTEM techniques. The catalytic activity in the coupling reaction was superb with 100% conversion and 98 % yield and also activity remained almost unaltered up to six cycles. Typically, an extremely high turnover frequency of 185,078 h-1 is observed in the C-C Suzuki coupling reaction using organo di-amine functionalized graphene as catalyst.

Keywords: Di-amine, graphene, Pd nanoparticle, suzuki coupling

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Authors: Hycham Aboutaleb, Bruno Monsuez

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Current systems' complexity has reached a degree that requires addressing conception and design issues while taking into account environmental, operational, social, legal, and financial aspects. Therefore, one of the main challenges is the way complex systems are specified and designed. The exponentially growing effort, cost, and time investment of complex systems in modeling phase emphasize the need for a paradigm, a framework, and an environment to handle the system model complexity. For that, it is necessary to understand the expectations of the human user of the model and his limits. This paper presents a generic framework for designing complex systems, highlights the requirements a system model needs to fulfill to meet human user expectations, and suggests a graph-based formalism for modeling complex systems. Finally, a set of transformations are defined to handle the model complexity.

Keywords: higraph-based, formalism, system engineering paradigm, modeling requirements, graph-based transformations

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Authors: Allam Srinivasa Rao, Ch. Annapurna Devi, G. Vijaya Prakash

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A new-fangled series of white light emitting 1 mol% of Dy3+ ions doped Single-Alklai and Mixed-Alkai fluoro tungstunate tellurite glasses have been prepared using melt quenching technique and their spectroscopic behaviour was investigated by studying XRD, optical absorption, photoluminescence and lifetime measurements. The bonding parameter studies reveal the ionic nature of the Dy-O bond in the present glasses. From the absorption spectra, the Judd–Ofelt (J-O) intensity parameters have been determined which are used to explore the nature of bonding and symmetry orientation of the Dy–ligand field environment. The evaluated J-O parameters (Ω_4>Ω_2>Ω_6) for all the glasses are following the same trend. The photoluminescence spectra of all the glasses exhibit two intensified peaks in blue and Yellow regions corresponding to the transitions 4F9/2→6H15/2 (483 nm) and 4F9/2→6H13/2 (575 nm) respectively. From the photoluminescence spectra, it is observed that the luminescence intensity is maximum for Dy3+ ion doped potassium combination of fluoro tungstunate tellurite glass (TeWK: 1Dy). The J-O intensity parameters have been used to determine the various radiative properties for the different emission transitions from the 4F9/2 fluorescent level. The highest emission cross-section and branching ratio values observed for the 4F9/2→6H15/2 and 4F9/2→6H13/2 transitions suggest the possible laser action in the visible region from these glasses. By using the experimental lifetimes (τ_exp) measured from the decay spectral features and radiative lifetimes (τ_R), the quantum efficiencies (η) for all the glasses have been evaluated. Among all the glasses, the potassium combined fluoro tungstunate tellurite (TeWK:1Dy) glass has the highest quantum efficiency (94.6%). The CIE colour chromaticity coordinates (x, y), (u, v), colour correlated temperature (CCT) and Y/B ratio were also estimated from the photoluminescence spectra for different compositions of glasses. The (x, y) and (u, v) chromaticity colour coordinates fall within the white light region and the white light can be tuned by varying the composition of the glass. From all these studies, we are suggesting that the 1 mol% of Dy3+ ions doped TeWK glass is more suitable for lasing and White-LED applications.

Keywords: dysprosium, Judd-Ofelt parameters, photo luminescence, tellurite glasses

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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Authors: Sungyani Tripathy, Atul Desai

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Turbo machinery Frame Foundation is very important for power generation, gas, steam, hydro, geothermal and nuclear power plants. The Turbo machinery Foundation system was simulated in SAP: 2000 software and dynamic response of foundation was analysed. In this paper, the detailed study of turbo machinery foundation with different running speed has considered. The different revolution per minute considered in this study is 4000 rpm, 6000 rpm, 8000 rpm, 1000 rpm and 12000 rpm. The above analysis has been carried out considering Winkler spring soil model, solid finite element modelling and dynamic analysis of Turbo machinery foundations. The comparison of frequency and time periods at various mode shapes are addressed in this study. Current work investigates the effect of damping on the response spectra curve at the foundation top deck, considering the dynamic machine load. It has been found that turbo generator foundation with haunches remains more elastic during seismic action for different running speeds.

Keywords: turbo machinery, SAP: 2000, response spectra, running speeds

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Authors: Wei Quan, Liu Chao, Mohammed N. Afsar

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The dielectric properties and ionic conductivity of novel "ceramic state" polymer electrolytes for high capacity lithium battery are characterized by radio-frequency and Microwave methods in two broad frequency ranges from 50 Hz to 20 KHz and 4 GHz to 40 GHz. This innovative solid polymer electrolyte which is highly ionic conductive (10-3 S/cm at room temperature) from -40 oC to +150 oC and can be used in any battery application. Such polymer exhibits properties more like a ceramic rather than polymer. The various applied measurement methods produced accurate dielectric results for comprehensive analysis of electrochemical properties and ion transportation mechanism of this newly invented polymer electrolyte. Two techniques and instruments employing air gap measurement by capacitance bridge and inwave guide measurement by vector network analyzer are applied to measure the complex dielectric spectra. The complex dielectric spectra are used to determine the complex alternating current electrical conductivity and thus the ionic conductivity.

Keywords: polymer electrolyte, dielectric permittivity, lithium battery, ionic relaxation, microwave measurement

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Authors: Ninel Kokanyan, Edvard Kokanyan, Anush Movsesyan, Marc D. Fontana

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Lithium Niobate (LN) is one of the widely used ferroelectrics having a wide number of applications such as phase-conjugation, holographic storage, frequency doubling, SAW sensors. Furthermore, the possibility of doping with rare-earth ions leads to new laser applications. Ho and Tm dopants seem interesting due to laser emission obtained at around 2 µm. Raman spectroscopy is a powerful spectroscopic technique providing a possibility to obtain a number of information about physicochemical and also optical properties of a given material. Polarized Raman measurements were carried out on Ho and Tm doped LN crystals with excitation wavelengths of 532nm and 785nm. In obtained Raman anti-Stokes spectra, we detect expected modes according to Raman selection rules. In contrast, Raman Stokes spectra are significantly different compared to what is expected by selection rules. Additional forbidden lines are detected. These lines have quite high intensity and are well defined. Moreover, the intensity of mentioned additional lines increases with an increase of Ho or Tm concentrations in the crystal. These additional lines are attributed to emission lines reflecting the photoluminescence spectra of these crystals. It means that in our case we were able to detect, within a very good resolution, in the same Stokes spectrum, the transitions between the electronic states, and the vibrational states as well. The analysis of these data is reported as a function of Ho and Tm content, for different polarizations and wavelengths, of the incident laser beam. Results also highlight additional information about π and σ polarizations of crystals under study.

Keywords: lithium niobate, Raman spectroscopy, luminescence, rare-earth ions doped lithium niobate

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Authors: M. Fares, S. Mameri, I. Abdlani, K. Negara

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Neutron detectors in general, proportional counters gas filling based isotope 3He in particular are going to be essential for monitoring and control of certain nuclear facilities, monitoring of experimentation around neutron beams and channels nuclear research reactors, radiation protection instruments and other tools multifaceted exploration and testing of materials, etc. This work consists of a measurement campaign features two Proportional Counters 3He (3He: LND252/USA CP, CP prototype: 3He LND/DDM). This is to make a comparison study of a CP 3He LND252/USA reference one hand, and in the context of routine periodic monitoring of the characteristics of the detectors for controlling the operation especially for laboratory prototypes. In this paper, we have described the different characteristics of the detectors and the experimental protocols used. Tables of measures have been developed and the different curves were plotted. The experimental campaign at stake: 2 PC 3He were thus characterized: Their characteristics (sensitivity, energy pulse height distribution spectra, gas amplification etc.) Were identified: 01 PC 3He 1'' Type: prototype DEDIN/DDM, 01 PC 3He 1'' Type: LND252/USA.

Keywords: PC 3He, sensitivity, pulse height distribution spectra, gas amplification

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Authors: P. C. Okafor, A. J. Ekpunobi

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Mn doped copper sulphide (CuS:Mn) nano-films were deposited on indiums coated tin oxide (ITO) glass substrates using electrodeposition method. Electrodeposition was carried out using bath of PH = 3 at room temperature. Other depositions parameters such as deposition time (DT) are kept constant while Mn doping was varied from 3% to 23%. Absorption spectra of CuS:Mn films was obtained by using JENWAY 6405 UV-VIS -spectrophotometer. Optical band gap (E_g ), optical conductivity (σo) and electrical conductivity (σe) of CuS:Mn films were determined using absorption spectra and appropriate formula. The effect of Mn doping % on these properties were investigated. Results show that film thickness (t) for the 13.27 nm to 18.49 nm; absorption coefficient (α) from 0.90 x 1011 to 1.50 x 1011 optical band gap from 2.29eV to 2.35 eV; optical conductivity from 1.70 x 1013 and electrical conductivity from 160 millions to 154 millions. Possible applications of such films for solar cells fabrication and optoelectronic devices applications were also discussed.

Keywords: copper sulphide (CuS), Manganese (Mn) doping, electrodeposition, optical band gap, optical conductivity, electrical conductivity

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Authors: Nivedha Rajaram

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Hybrid Quantum solvers have been given prime focus in recent days by computation problem-solving domain industrial applications. D’Wave Quantum Computers are one such paragon of systems built using quantum annealing mechanism. Discrete Quadratic Models is a hybrid quantum computing model class supplied by D’Wave Ocean SDK - a real-time software platform for hybrid quantum solvers. These hybrid quantum computing modellers can be employed to solve classic problems. One such problem that we consider in this paper is finding a network connectivity knowledge hub in a huge network of systems. Using this quantum solver, we try to find out the prime system hub, which acts as a supreme connection point for the set of connected computers in a large network. This paper establishes an innovative problem approach to generate a connectivity system hub plot for a set of systems using DWave ocean SDK hybrid quantum solvers.

Keywords: quantum computing, hybrid quantum solver, DWave annealing, network knowledge graph

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Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

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Authors: Muhammad Danladi, Muhammad Bura Garba, Muhammad Yahaya, Dahiru Muhammad

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Biomass is one of the primary sources of energy supply, which contributes to about 78% of Nigeria. In this work, a comparative analysis of the heating values of sawdust and rice husks in the thermal generation of electricity was carried out. In the study, different masses of biomass were used and the corresponding electromotive force in millivolts was obtained. A graph of e.m.f was plotted against the mass of each biomass and a gradient was obtained. Bar graphs were plotted to represent the values of e.m.f and masses of the biomass. Also, a graph of e.m.f against eating values of sawdust and rice husks was plotted, and in each case, as the e.m.f increases also, the heating values increases. The result shows that saw dust with 0.033Mv/g gradient and 3.5 points of intercept had the highest gradient, followed by rice husks with 0.026Mv/g gradient and 2.6 points of intercept. It is, therefore, concluded that sawdust is the most efficient of the two types of biomass in the thermal generation of electricity.

Keywords: biomass, electricity, thermal, generation

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Authors: Mostafa Ghasemi, Andrew Urquhart

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In this study, fluorescent carbon dots (CDs) were synthesized in a green way using a one-step hydrothermal method. Carbon dots are carbon-based nanomaterials with a size of less than 10 nm, unique structure, and excellent properties such as low toxicity, good biocompatibility, tunable fluorescence, excellent photostability, and easy functionalization. These properties make them a good candidate to use in different fields such as biological sensing, photocatalysis, photodynamic, and drug delivery. Fourier transformed infrared (FTIR) spectra approved OH/NH groups on the surface of the as-synthesized CDs, and UV-vis spectra showed excellent fluorescence quenching effect of Fe (III) ion on the as-synthesized CDs with high selectivity detection compared with other metal ions. The probe showed a linear response concentration range (0–2.0 mM) to Fe (III) ion, and the limit of detection was calculated to be about 0.50 μM. In addition, CDs also showed good sensitivity to the pH value in the range from 2 to 14, indicating great potential as a pH sensor.

Keywords: carbon dots, fluorescence, pH sensing, metal ions sensor

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Authors: Moustapha Bande, Hakima Ould-Slimane, Hanifa Boucheneb

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Software development for complex systems requires efficient and automatic tools that can be used to verify the satisfiability of some critical properties such as security ones. With the emergence of Aspect-Oriented Programming (AOP), considerable work has been done in order to better modularize the separation of concerns in the software design and implementation. The goal is to prevent the cross-cutting concerns to be scattered across the multiple modules of the program and tangled with other modules. One of the key challenges in the aspect-oriented programs is to be sure that all the pieces put together at the weaving time ensure the satisfiability of the overall system requirements. Our paper focuses on this problem and proposes a formal property verification approach for a given property from the woven program. The approach is based on the control flow graph (CFG) of the woven program, and the use of a satisfiability modulo theories (SMT) solver to check whether each property (represented par one aspect) is satisfied or not once the weaving is done.

Keywords: aspect-oriented programming, control flow graph, property verification, satisfiability modulo theories

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Authors: Juni C. Kim, Anna R. Robuck, Douglas I. Walker

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The human exposome, which includes chemical exposures over the lifetime and their effects, is now recognized as an important measure for understanding human health; however, the complexity of the data makes the identification of environmental chemicals challenging. The goal of our project was to establish a computational workflow for the improved identification of environmental pollutants containing chlorine or bromine. Using the “pattern. search” function available in the R package NonTarget, we wrote a multifunctional script that searches mass spectral clusters from untargeted gas-chromatography high-resolution mass spectrometry (GC-HRMS) for the presence of spectra consistent with chlorine and bromine-containing organic compounds. The “pattern. search” function was incorporated into a different function that allows the evaluation of clusters containing multiple analyte fragments, has multi-core support, and provides a simplified output identifying listing compounds containing chlorine and/or bromine. The new function was able to process 46,000 spectral clusters in under 8 seconds and identified over 150 potential halogenated spectra. We next applied our function to a deidentified dataset from patients diagnosed with primary biliary cholangitis (PBC), primary sclerosing cholangitis (PSC), and healthy controls. Twenty-two spectra corresponded to potential halogenated compounds in the PSC and PBC dataset, including six significantly different in PBC patients, while four differed in PSC patients. We have developed an improved algorithm for detecting halogenated compounds in GC-HRMS data, providing a strategy for prioritizing exposures in the study of human disease.

Keywords: exposome, metabolome, computational metabolomics, high-resolution mass spectrometry, exposure, pollutants

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Authors: Abiodun Ayodele Sanyaolu

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The research was carried out to investigate the time series analysis on quarterly production of fruit juice at the National Horticultural Research Institute Ibadan from 2010 to 2018. Documentary method of data collection was used, and the method of least square and moving average were used in the analysis. From the calculation and the graph, it was glaring that there was increase, decrease, and uniform movements in both the graph of the original data and the tabulated quarter values of the original data. Time series analysis was used to detect the trend in the highest number of fruit juice and it appears to be good over a period of time and the methods used to forecast are additive and multiplicative models. Since it was observed that the production of fruit juice is usually high in January of every year, it is strongly advised that National Horticultural Research Institute should make more provision for fruit juice storage outside this period of the year.

Keywords: fruit juice, least square, multiplicative models, time series

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Authors: Kamel Taıbı, Abdelmadjid Rais

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Nickel–Aluminium ferrites with the general formula Ni Alx Fe2-x O4 (0 ≤ x ≤ 1) were studied using X-ray diffraction, Infra Red and Raman spectroscopy. XRD diffraction patterns and their Reitveld refinements show that all samples have a pure single-phase cubic spinel structure. From these patterns, the lattice parameters of these samples have been calculated and compared with those predicted theoretically. Most of the values were found to decrease with increasing Al content. Infra Red spectra showed two significant absorption bands. The high band corresponds to tetrahedral (A) sites and the lower band to octahedral [B] sites, thus confirming the single phase spinel structure. For all compositions, Raman spectra show the five active modes A1g + E1g + 3 T2g of the motion of O2- ions and both the A-site and B-site ions. The Raman frequencies trend with aluminium concentration show a blue shift for all modes consistent with the replacement of Fe3+ by lower mass Al3+. Composition dependence of the Raman frequency modes is discussed in relationship with the cations distribution among the A-sites and B-sites.

Keywords: Ni-Al ferrites, spinel structure, XRD, Raman spectroscopy

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Authors: Tesfaye Fenta Boka, Niu Zhendong

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Recommender systems play a crucial role in connecting individuals with the items they require, as is particularly evident in the rapid growth of online grocery shopping platforms. These systems predominantly rely on user-centered recommendations, where items are suggested based on individual preferences, garnering considerable attention and adoption. However, our focus lies on the item-centered recommendation task within the grocery shopping context. In the reverse next item period recommendation (RNPR) task, we are presented with a specific item and challenged to identify potential users who are likely to consume it in the upcoming period. Despite the ever-expanding inventory of products on online grocery platforms, the cold start item problem persists, posing a substantial hurdle in delivering personalized and accurate recommendations for new or niche grocery items. To address this challenge, we propose a Graph Neural Network (GNN)-based approach. By capitalizing on the inherent relationships among grocery items and leveraging users' historical interactions, our model aims to provide reliable and context-aware recommendations for cold-start items. This integration of GNN technology holds the promise of enhancing recommendation accuracy and catering to users' individual preferences. This research contributes to the advancement of personalized recommendations in the online grocery shopping domain. By harnessing the potential of GNNs and exploring item-centered recommendation strategies, we aim to improve the overall shopping experience and satisfaction of users on these platforms.

Keywords: recommender systems, cold start item recommendations, online grocery shopping platforms, graph neural networks

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Authors: Ouafek Nora, Keghouche Nassira, Dehdouh Heider, Untidt Carlos

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A lot of knowledge has been accumulated on the metal clusters supported on oxide surfaces because of their multiple applications in microelectronics, heterogeneous catalysis, and magnetic devices. In this work, the surface state of Ni / MgO has been studied by XPS (X-ray Photoemission Spectroscopy). The samples were prepared by impregnation with ion exchange Ni²⁺ / MgO, followed by either a thermal treatment in air (T = 100 -350 ° C) or a gamma irradiation (dose 100 kGy, 25 kGy dose rate h -1). The obtained samples are named after impregnation NMI, NMR after irradiation, and finally NMC(T) after calcination at the temperature T (T = 100-600 °C). A structural study by XRD and HRTEM reveals the presence of nanoscaled Ni-Mg intermetallic phases (Mg₂Ni, MgNi₂, and Mg₆Ni) and magnesium hydroxide. Mg(OH)₂ in nanometric range (2- 4 nm). Mg-Ni compounds are of great interest in energy fields (hydrogen storage…). XPS spectra show two Ni2p peaks at energies of about 856.1 and 861.9 eV, indicating that the nickel is primarily in an oxidized state on the surface. The shift of the main peak relative to the pure NiO (856.1 instead of 854.0 eV) suggests that in addition to oxygen, nickel is engaged in another link with magnesium. This is in agreement with the O1s spectra which present an overlap of peaks corresponds to NiO and MgO, at a calcination temperature T ≤ 300 °C.

Keywords: XPS, XRD, nanoparticules, Ni-MgO

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Authors: Ahmet Battal, Demet Tatar, Bahattin Düzgün

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Various transparent conducting oxides (TCOs) are mostly used much applications due to many properties such as cheap, high transmittance/electrical conductivity etc. One of the clearest among TCOs, indium tin oxide (ITO), is the most widely used in many areas. However, as ITO is expensive and very low regarding reserve, other materials with suitable properties (especially SnO2 thin films) are be using instead of it. In this report, tin oxide thin films doubly doped with antimony and fluorine (AFTO) were deposited by spray at different substrate temperatures on glass substrate. It was investigated their structural, optical, electrical and luminescence properties. The substrate temperature was varied from 320 to 480 ˚C at the interval of 40 (±5) ºC. X-ray results were shown that the films are polycrystalline with tetragonal structure and oriented preferentially along (101), (200) and (210) directions. It was observed that the preferential orientations of crystal growth are not dependent on substrate temperature, but the intensity of preferential orientation was increased with increasing substrate temperature until 400 ºC. After this substrate temperature, they decreased. So, substrate temperature impact structure of these thin films. It was known from SEM analysis, the thin films have rough and homogenous and the surface of the films was affected by the substrate temperature i.e. grain size are increasing with increasing substrate temperature until 400 ºC. Also, SEM and AFM studies revealed the surface of AFTO thin films to be made of nanocrystalline particles. The average transmittance of the films in the visible range is 70-85%. Eg values of the films were investigated using the absorption spectra and found to be in the range 3,20-3,93 eV. The electrical resistivity decreases with increasing substrate temperature, then the electrical resistivity increases. PL spectra were found as a function of substrate temperature. With increasing substrate temperature, emission spectra shift a little bit to a UV region. Finally, tin oxide thin films were successfully prepared by this method and a spectroscopic characterization of the obtained films was performed. It was found that the films have very good physical properties. It was concluded that substrate temperature impacts thin film structure.

Keywords: thin films, spray pyrolysis, SnO2, doubly doped

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Authors: Yong Pan, Li Wang, Xue Qiong Su, Dong Wen Gao

Abstract:

To date, nanomaterials have received extensive attention over the years because of their wide application. Various nanomaterials such as nanoparticles, nanowire, nanoring, nanostars and other nanostructures have begun to be systematically studied. The preparation of these materials by chemical methods is not only costly, but also has a long cycle and high toxicity. At the same time, preparation of nanoparticles of multi-doped composites has been limited due to the special structure of the materials. In order to prepare multi-doped composites with the same structure as macro-materials and simplify the preparation method, the Ga_xCo_1-xZnSe_0.4 (x = 0.1, 0.3, 0.5) nanoparticles are prepared by Pulse Laser Ablation (PLA) method. The particle component and structure are systematically investigated by X-ray diffraction (XRD) and Raman spectra, which show that the success of our preparation and the same concentration between nanoparticles (NPs) and target. Morphology of the NPs characterized by Transmission Electron Microscopy (TEM) indicates the circular-shaped particles in preparation. Fluorescence properties are reflected by PL spectra, which demonstrate the best performance in concentration of Ga_0.3Co_0.3ZnSe_0.4. Therefore, all the results suggest that PLA is promising to prepare the multi-NPs since it can modulate performance of NPs.

Keywords: PLA, physics, nanoparticles, multi-doped

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Authors: Jens Ehm

Abstract:

Manufacturing in supply chains requires an efficient organisation of production and transport processes in order to guarantee the supply of all partners within the chain with the material that is needed for the reliable fulfilment of tasks. If one partner is not able to supply products for a certain period, these products might be missing as the working material for the customer to perform the next manufacturing step, potentially as supply for further manufacturing steps. This way, local disruptions can influence the whole supply chain. In order to avoid material shortages, an efficient scheduling of tasks is necessary. However, the occurrence of unexpected disruptions cannot be eliminated, so that a modification of the schedule should be arranged as fast as possible. This paper discusses the challenges for the implementation of real-time scheduling and control methods and presents a graph-based approach that enables the integrated scheduling of production and transport processes for multiple supply chain partners and offers the potential for quick adaptations to parts of the initial schedule.

Keywords: production, logistics, integrated scheduling, real-time scheduling

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

Abstract:

Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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