Search results for: modeling of PV panel

Authors: S. M. Mahbobur Rahman

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Whole building energy simulation models are widely used for predicting future energy consumption, performance diagnosis and optimum control.  Black box building energy modeling approach has been heavily studied in the past decade. The thermal response of a building can also be modeled using a network of interconnected resistors (R) and capacitors (C) at each node called R-C network. In this study, a model building, Case 600, as described in the “Standard Method of Test for the Evaluation of Building Energy Analysis Computer Program”, ASHRAE standard 140, is studied along with a 3R2C thermal network model and the ASHRAE clear sky solar radiation model. Although building an energy model involves two important parts of building component i.e., the envelope and internal mass, the effect of building internal mass is not considered in this study. All the characteristic parameters of the building envelope are evaluated as on Case 600. Finally, monthly building energy consumption from the thermal network model is compared with a simple-box energy model within reasonable accuracy. From the results, 0.6-9.4% variation of monthly energy consumption is observed because of the south-facing windows.

Keywords: ASHRAE case study, clear sky solar radiation model, energy modeling, thermal network model

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Authors: Muhammad Naveed Babur, Maria Liaqat

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Background & Objective: People with disabilities especially neurological disabilities have many unmet health and rehabilitation needs, face barriers in accessing mainstream health-care services, and consequently have poor health. There are not sufficient epidemiological studies from Pakistan which assess barriers to neurorehabilitation and ways to counter it. Objectives: The objective of the study was to determine the challenges and to evaluate the barriers for neuro-rehabilitation services in developing countries. Methods: This is Exploratory sequential qualitative study based on the Panel discussion forum in International rehabilitation sciences congress and national rehabilitation conference 2017. Panel group discussion has been conducted in February 2017 with a sample size of eight professionals including Rehabilitation medicine Physician, Physical Therapist, Speech Language therapist, Occupational Therapist, Clinical Psychologist and rehabilitation nurse working in multidisciplinary/Interdisciplinary team. A comprehensive audio-videography have been developed, recorded, transcripted and documented. Data was transcribed and thematic analysis along with characteristics was drawn manually. Data verification was done with the help of two separate coders. Results: After extraction of two separate coders following results are emerged. General category themes are disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. Barriers identified at the level are high cost, stigma, lengthy course of recovery. Hospital related barriers are lack of social support and individually tailored goal setting processes. Organizational barriers identified are lack of basic diagnostic facilities, lack of funding and human resources. Recommendations given by panelists were investment in education, capacity building, infrastructure, governance support, strategies to promote communication and realistic goals. Conclusion: It is concluded that neurorehabilitation in developing countries need attention in following categories i.e. disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. This study also revealed barriers at the level of patient, hospital, organization. Recommendations were also given by panelists.

Keywords: disability, neurorehabilitation, telerehabilitation, disability

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Authors: Lorenzo Petrucci

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This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

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Authors: Faranak Beigmohammadi, Seyed Hadi Peighambardoust, Seyed Jamaledin Peighambardoust

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This study undertakes to investigate the ability of different kinds of nanocomposite films made of cloisite-30B with different percentages of silver and copper oxide nanoparticles incorporated into a low-density polyethylene (LDPE) polymeric matrix by a melt mixing method in order to inhibit the growth of microorganism in soy burger. The number of surviving cell of the total count was decreased by 3.61 log and mold and yeast diminished by 2.01 log after 8 weeks storage at 18 ± 0.5°C below zero, whilst pure LDPE did not has any antimicrobial effect. A composition of 1.3 % cloisite 30B-Ag and 2.7 % cloisite 30B-CuO for total count and 0 % cloisite 30B-Ag and 4 % cloisite 30B-CuO for yeast & mold gave optimum points in combined design test in Design Expert 7.1.5. Suitable microbial models were suggested for retarding above microorganisms growth in soy burger. To validation of optimum point, the difference between the optimum point of nanocomposite film and its repeat was not significant (p<0.05) by one-way ANOVA analysis using SPSS 17.0 software, while the difference was significant for pure film. Migration of metallic nanoparticles into a food stimulant was within the accepted safe level.

Keywords: modeling, nanocomposite film, packaging, soy burger

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Authors: Abiodun Olayinka, Daniel Dzidzienyo, Pangirayi Tongoona, Samuel Offei, Edwige Gaby Nkouaya Mbanjo, Chiedozie Egesi, Ismail Yusuf Rabbi

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Cassava (Manihot esculenta Crantz) is a major source of starch for various industrial applications. However, the traditional cultivation and harvesting methods of cassava are labour-intensive and inefficient, limiting the supply of fresh cassava roots for industrial starch production. To achieve improved productivity and quality of fresh cassava roots through mechanized cultivation, cassava cultivars with compact plant architecture and moderate plant height are needed. Plant architecture-related traits, such as plant height, harvest index, stem diameter, branching angle, and lodging tolerance, are critical for crop productivity and suitability for mechanized cultivation. However, the genetics of cassava plant architecture remain poorly understood. This study aimed to identify the genetic bases of the relationships between plant architecture traits and productivity-related traits, particularly starch content. A panel of 453 clones developed at the International Institute of Tropical Agriculture, Nigeria, was genotyped and phenotyped for 18 plant architecture and productivity-related traits at four locations in Nigeria. A genome-wide association study (GWAS) was conducted using the phenotypic data from a panel of 453 clones and 61,238 high-quality Diversity Arrays Technology sequencing (DArTseq) derived Single Nucleotide Polymorphism (SNP) markers that are evenly distributed across the cassava genome. Five significant associations between ten SNPs and three plant architecture component traits were identified through GWAS. We found five SNPs on chromosomes 6 and 16 that were significantly associated with shoot weight, harvest index, and total yield through genome-wide association mapping. We also discovered an essential candidate gene that is co-located with peak SNPs linked to these traits in M. esculenta. A review of the cassava reference genome v7.1 revealed that the SNP on chromosome 6 is in proximity to Manes.06G101600.1, a gene that regulates endodermal differentiation and root development in plants. The findings of this study provide insights into the genetic basis of plant architecture and yield in cassava. Cassava breeders could leverage this knowledge to optimize plant architecture and yield in cassava through marker-assisted selection and targeted manipulation of the candidate gene.

Keywords: manihot esculenta crantz, plant architecture, dartseq, snp markers, genome-wide association study

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Authors: Nadia Allouache

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The use of solar energy in cooling systems is an interesting alternative to the increasing demand of energy in the world and more specifically in southern countries where the needs of refrigeration and air conditioning are tremendous. This technique is even more attractive with regards to environmental issues. This study focuses on performances analysis and optimization of solar reactor of an adsorption cooling machine working with activated carbon-methanol pair. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular adsorber that is the most important component of the machine. The results show the poor heat conduction inside the porous medium and the resistance between the metallic wall and the bed engender the important temperature gradient and a great difference between the metallic wall and the bed temperature; this is considered as the essential causes decreasing the performances of the machine. For fixed conditions of functioning, the total desorbed mass presents a maximum for an optimal value of the height of the adsorber; this implies the existence of an optimal dimensioning of the adsorber.

Keywords: solar cooling system, performances Analysis, optimization, heat and mass transfer, activated carbon-methanol pair, numerical modeling

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Authors: Julia Zimmerman, Gaurav Savant

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This study aims to evaluate the efficacy of the U.S. Army Corp of Engineers’ River Analysis System (HEC-RAS) application to modeling the hydraulics of estuaries. HEC-RAS has been broadly used for a variety of riverine applications. However, it has not been widely applied to the study of circulation in estuaries. This report details the model development and validation of a combined 1D/2D unsteady flow hydraulic model using HEC-RAS for estuaries and they are associated with tidally influenced rivers. Two estuaries, Galveston Bay and Delaware Bay, were used as case studies. Galveston Bay, a bar-built, vertically mixed estuary, was modeled for the 2005 calendar year. Delaware Bay, a drowned river valley estuary, was modeled from October 22, 2019, to November 5, 2019. Water surface elevation was used to validate both models by comparing simulation results to NOAA’s Center for Operational Oceanographic Products and Services (CO-OPS) gauge data. Simulations were run using the Diffusion Wave Equations (DW), the Shallow Water Equations, Eulerian-Lagrangian Method (SWE-ELM), and the Shallow Water Equations Eulerian Method (SWE-EM) and compared for both accuracy and computational resources required. In general, the Diffusion Wave Equations results were found to be comparable to the two Shallow Water equations sets while requiring less computational power. The 1D/2D combined approach was valid for study areas within the 2D flow area, with the 1D flow serving mainly as an inflow boundary condition. Within the Delaware Bay estuary, the HEC-RAS DW model ran in 22 minutes and had an average R² value of 0.94 within the 2-D mesh. The Galveston Bay HEC-RAS DW ran in 6 hours and 47 minutes and had an average R² value of 0.83 within the 2-D mesh. The longer run time and lower R² for Galveston Bay can be attributed to the increased length of the time frame modeled and the greater complexity of the estuarine system. The models did not accurately capture tidal effects within the 1D flow area.

Keywords: Delaware bay, estuarine hydraulics, Galveston bay, HEC-RAS, one-dimensional modeling, two-dimensional modeling

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Authors: Paul Campbell, Nicholas Biddle

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There is a complex, endogenous relationship between individual circumstances, attitudes, and behaviour. This study uses longitudinal panel data to assess changes in social and political attitudes over a 7-year period. Attitudes are captured with the question 'what is the most important issue facing Australia today', collected at multiple time points in a longitudinal survey of 2200 Australians. Consistency of attitudes, and factors predicting change over time, are assessed. The consistency of responses has methodological implications for data collection, specifically how often such questions ought to be asked of a population. When change in attitude is observed, this study assesses the extent to which individual demographic characteristics, personality traits, and broader societal events predict change.

Keywords: attitudes, longitudinal survey analysis, personality, social values

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Authors: Amira Abdelrasoul, Huu Doan, Ali Lohi

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An efficient and well-planned ultrafiltration process is becoming a necessity for monetary returns in the industrial settings. The aim of the present study was to develop a mathematical model for an accurate prediction of ultrafiltration membrane fouling of latex effluent applied to homogeneous and heterogeneous membranes with uniform and non-uniform pore sizes, respectively. The models were also developed for an accurate prediction of power consumption that can handle the large-scale purposes. The model incorporated the fouling attachments as well as chemical and physical factors in membrane fouling for accurate prediction and scale-up application. Both Polycarbonate and Polysulfone flat membranes, with pore sizes of 0.05 µm and a molecular weight cut-off of 60,000, respectively, were used under a constant feed flow rate and a cross-flow mode in ultrafiltration of the simulated paint effluent. Furthermore, hydrophilic ultrafilic and hydrophobic PVDF membranes with MWCO of 100,000 were used to test the reliability of the models. Monodisperse particles of 50 nm and 100 nm in diameter, and a latex effluent with a wide range of particle size distributions were utilized to validate the models. The aggregation and the sphericity of the particles indicated a significant effect on membrane fouling.

Keywords: membrane fouling, mathematical modeling, power consumption, attachments, ultrafiltration

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Authors: A. Mansouri, F. Krim

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This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

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Authors: Septiany Trisnaningtyas

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Purpose: This research aims to examine the factors affecting the profitability of pharmaceutical company during the Covid-19 Pandemic in Indonesia. A sharp decline in the number of patients coming to the hospital for treatment during the pandemic has an impact on the growth of the pharmaceutical sector and brought major changes in financial position and business performance. Pharmaceutical companies that provide products related to the Covid-19 pandemic can survive and continue to grow. This study investigates the factors affecting the profitability of pharmaceutical company during the Covid-19 Pandemic in Indonesia associated with the number of Covid-19 cases. Design/methodology/approach: This study uses panel-data regression models to evaluate the influence of the number of Covid-19 confirmed cases on profitability of ninelisted pharmaceuticalcompanies in Indonesia. This research is based on four independent variables that were empirically examined for their relationship with profitability. These variables are liquidity (current ratio), growth rate (sales growth), firm size (total sales), and market power (the Lerner index). Covid-19 case is used as moderating variable. Data of nine pharmaceutical companies listed on the Indonesia Stock Exchange covering the period of 2018–2021 were extracted from companies’ quarterly annual reports. Findings: In the period during Covid-19, company growth (sales growth) and market power (lerner index) have a positive and significant relationship to ROA and ROE. Total of confirmed Covid-19 cases has a positive and significant relationship to ROA and is proven to have a moderating effect between company’s growth (sales growth) to ROA and ROE and market power (Lerner index) to ROA. Research limitations/implications: Due to data availability, this study only includes data from nine listed pharmaceutical companies in Indonesian Stock exchange and quarterly annual reportscovering the period of 2018-2021. Originality/value: This study focuses onpharmaceutical companies in Indonesia during Covid-19 pandemic. Previous study analyzes the data from pharmaceutical companies’ annual reports since 2014 and focus on universal health coverage (national health insurance) implementation from the Indonesian government. This study analyzes the data using fixed effect panel-data regression models to evaluate the influence of Covid-19 confirmed cases on profitability. Pooled ordinary least squares regression and fixed effects were used to analyze the data in previous study. This study also investigate the moderating effect of Covid-19 confirmed cases to profitability in relevant with the pandemic situation.

Keywords: profitability, indonesia, pharmaceutical, Covid-19

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Authors: Farhan Beg, Raymond Moberly

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The Indian subcontinent is facing a massive challenge with regards to energy security in member countries, to provide reliable electricity to facilitate development across various sectors of the economy and consequently achieve the developmental targets. The instability of the current precarious situation is observable in the frequent system failures and blackouts. The deployment of interconnected electricity ‘Supergrid’ designed to carry huge quanta of power across the Indian sub-continent is proposed in this paper. Besides enabling energy security in the subcontinent, it will also provide a platform for Renewable Energy Sources (RES) integration. This paper assesses the need and conditions for a Supergrid deployment and consequently proposes a meshed topology based on Voltage Source High Voltage Direct Current (VSC-HVDC) converters for the Supergrid modeling. Various control schemes for the control of voltage and power are utilized for the regulation of the network parameters. A 3 terminal Multi Terminal Direct Current (MTDC) network is used for the simulations.

Keywords: super grid, wind and solar energy, high voltage direct current, electricity management, load flow analysis

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Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

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The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

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Authors: Viriyavudh Sim, WooYoung Jung

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Damage due to high wind is not limited to load resistance components such as beam and column. The majority of damage is due to breach in the building envelope such as broken roof, window, and door. In this paper, wind fragility of window glass in residential apartment was determined to compare the difference between two window configuration models. Monte Carlo Simulation method had been used to derive damage data and analytical fragilities were constructed. Fragility of window system showed that window located in leeward wall had higher probability of failure, especially those close to the edge of structure. Between the two window models, Model 2 had higher probability of failure, this was due to the number of panel in this configuration.

Keywords: wind fragility, glass window, high rise building, wind disaster

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Authors: Abdulfetah Shobole, Arif Karakas, Ugur Savas Selamogullari, Mustafa Baysal

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The concern of reducing emissions of Co2 from the fossil fuel generating units and using renewable energy sources increased in our world. Due this fact the integration ratio of wind farms to grid reached 20-30% in some part of our world. With increased integration of large MW scaled wind farms to the electric grid, the stability of the electrical system is a great concern. Thus, operators of power systems usually deman the wind turbine generators to obey the same rules as other traditional kinds of generation, such as thermal and hydro, i.e. not affect the grid stability. FACTS devices such as SVC or STATCOM are mostly installed close to the connection point of the wind farm to the grid in order to increase the stability especially during faulty conditions. In this paper wind farm with DFIG turbine type and STATCOM are dynamically modeled and simulated under three phase short circuit fault condition. The dynamic modeling is done by DigSILENT PowerFactory for the wind farm, STATCOM and the network. The simulation results show improvement of system stability near to the connection point of the STATCOM.

Keywords: DFIG wind turbine, statcom, dynamic modeling, digsilent

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Authors: Wided Bakari, Patrice Bellot, Omar Trigui, Mahmoud Neji

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This article constitutes an opening to think of the modeling and analysis of Arabic texts in the context of a question-answer system. It is a question of exceeding the traditional approaches focused on morphosyntactic approaches. Furthermore, we present a new approach that analyze a text in order to extract correct answers then transform it to logical predicates. In addition, we would like to represent different levels of information within a text to answer a question and choose an answer among several proposed. To do so, we transform both the question and the text into logical forms. Then, we try to recognize all entailment between them. The results of recognizing the entailment are a set of text sentences that can implicate the user’s question. Our work is now concentrated on an implementation step in order to develop a system of question-answering in Arabic using techniques to recognize textual implications. In this context, the extraction of text features (keywords, named entities, and relationships that link them) is actually considered the first step in our process of text modeling. The second one is the use of techniques of textual implication that relies on the notion of inference and logic representation to extract candidate answers. The last step is the extraction and selection of the desired answer.

Keywords: NLP, Arabic language, question-answering, recognition text entailment, logic forms

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Authors: H. Vahdani

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By the adsorption of polar compounds and/or the deposition of organic material, the wettability of originally water-wet reservoir rock can be altered. The degree of alteration is determined by the interaction of the oil constituents, the mineral surface, and the brine chemistry. Recently improving oil recovery by tuning wettability alteration is believed as a new recovery method. Various researchers have demonstrated that low salt water injection has a significant impact on oil recovery. It has been shown, for instance, that additional oil can be produced from reservoir rock by managing the injection water. Large wettability sensitivity has been observed, indicating that the oil/water capillary pressure profiles play a major role during low saline water injection simulation. Although the exact physics on how this alteration occurs is still a research topic; however, it has been reported that some of its effect can be captured by a relative permeability shift from an oil-wet system to a water-wet system. Modeling of low salt water injection mainly is based on the theory of wettability alteration and is hence strongly dependent on the wettability of the reservoir. In this article, combination of different wettabilities has been simulated and it is observed that the highest recoveries were from the cases were the reservoir initially was water-wet, and the lowest recoveries was from the cases were the reservoir initially was considered oil-wet. However for the cases where the reservoir initially was oil-wet, the effect of low-salinity waterflooding was the largest.

Keywords: low salt water injection, wettability alteration, modelling, relative permeability

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Authors: Ravinder Singh, Ankita Gurao, Saroj Bandhan, Sudhir Kumar Kashyap

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The Bos taurus Beta defensin 3 is a defensin peptide secreted by neutrophils and epithelial that exhibits anti-microbial activity. It is one of the crucial components forming an innate defense against intra mammary infections in livestock. The beta defensin 3 by virtue of its anti-microbial activity inhibits major mastitis pathogens including Staphylococcus aureus and Pseudomonas aeruginosa etc, which are also responsible for biofilm formation leading to antibiotic resistance phenomenon. Therefore, the defensin may prove as a non-conventional option to treat mastitis. In this study, computational analysis has been performed including sequence comparison among species and homology modeling of Bos taurus beta defensin 3 protein. The assessments of protein structure were done using the protein structure and model assessment tools integrated in Swiss Model server, which employs various local and global quality evaluation parameters. Further, molecular docking was also carried out between the defensin peptide and the components of biofilm to gain insight into various interactions and structural differences crucial for functionality of this protein.

Keywords: beta defensin 3, bos taurus, docking, homology modeling

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Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Nauman Idrees

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Modeling and simulation during the conceptual design phase are the most effective means of system testing resulting in time and cost savings as compared to the testing of hardware prototypes, which are mostly not available during the conceptual design phase. This paper uses the model-based design (MBD) method in designing the fly-by-wire flight controls system of a fighter aircraft using Simulink. The process begins with system definition and layout where modeling requirements and system components were identified, followed by hierarchical system layout to identify the sequence of operation and interfaces of system with external environment as well as the internal interface between the components. In the second step, each component within the system architecture was modeled along with its physical and functional behavior. Finally, all modeled components were combined to form the fly-by-wire flight controls system of a fighter aircraft as per system architecture developed. The system model developed using this method can be simulated using any simulation software to ensure that desired requirements are met even without the development of a physical prototype resulting in time and cost savings.

Keywords: fly-by-wire, flight controls system, model based design, Simulink

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Authors: Xiuzhan Guo, Arthur Berrill, Ajinkya Kulkarni, Kostya Belezko, Min Luo

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Ontology operations, e.g., aligning and merging, were studied and implemented extensively in different settings, such as categorical operations, relation algebras, and typed graph grammars, with different concerns. However, aligning and merging operations in the settings share some generic properties, e.g., idempotence, commutativity, associativity, and representativity, labeled by (I), (C), (A), and (R), respectively, which are defined on an ontology merging system (D~M), where D is a non-empty set of the ontologies concerned, ~ is a binary relation on D modeling ontology aligning and M is a partial binary operation on D modeling ontology merging. Given an ontology repository, a finite set O ⊆ D, its merging closure Ô is the smallest set of ontologies, which contains the repository and is closed with respect to merging. If (I), (C), (A), and (R) are satisfied, then both D and Ô are partially ordered naturally by merging, Ô is finite and can be computed, compared, and sorted efficiently, including sorting, selecting, and querying some specific elements, e.g., maximal ontologies and minimal ontologies. We also show that the ontology merging system, given by ontology V -alignment pairs and pushouts, satisfies the properties: (I), (C), (A), and (R) so that the merging system is partially ordered and the merging closure of a given repository with respect to pushouts can be computed efficiently.

Keywords: ontology aligning, ontology merging, merging system, poset, merging closure, ontology V-alignment pair, ontology homomorphism, ontology V-alignment pair homomorphism, pushout

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Authors: Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Lidija Jevrić, Evgenija Djurendić, Jovana Ajduković

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In the present study, the molecular modeling of a series of 24 17-picolyl and 17-picolinylidene androstane derivatives whit significant anticancer activity was carried out. Modelling of studied compounds was performed by CS ChemBioDraw Ultra v12.0 program for drawing 2D molecular structures and CS ChemBio3D Ultra v12.0 for 3D molecular modelling. The obtained 3D structures were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. Full geometry optimization was done by the Austin Model 1 (AM1) until the root mean square (RMS) gradient reached a value smaller than 0.0001 kcal/Åmol using Molecular Orbital Package (MOPAC) program. The obtained physicochemical, lipophilicity and topological descriptors were used for analysis of molecular similarities and dissimilarities applying suitable chemometric methods (principal component analysis and cluster analysis). These results are the part of the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina and CMST COST Action CM1306.

Keywords: androstane derivatives, anticancer activity, chemometrics, molecular descriptors

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Authors: Azlina Binti Abu Bakar, Fahmi Zaidi Bin Abdul Razak, Wan Salihin Wong Abdullah

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Psychographic is a psychological study of values, attitudes, interests and it is used mostly in prediction, opinion research and social research. This study predicts the influence of performance expectancy, effort expectancy, social influence and facilitating condition on e-government acceptance among Malaysian citizens. The survey responses of 543 e-government users have been validated and analyzed by means of covariance-based Structural Equation Modeling. The findings indicate that e-government acceptance among Malaysian citizens are mainly influenced by performance expectancy (β = 0.66, t = 11.53, p < 0.01) and social influence (β = 0.20, t = 4.23, p < 0.01). Surprisingly, there is no significant effect of facilitating condition and effort expectancy on e-government continuance intention (β = 0.01, t = 0.27, p > 0.05; β = -0.01, t = -0.40, p > 0.05). This study offers government and vendors a frame of reference to analyze citizen’s situation before initiating new innovations. In case of Malaysian e-government technology, adoption strategies should be built around fostering level of citizens’ technological expectation and social influence on e-government usage.

Keywords: continuance intention, Malaysian citizen, media psychology, structural equation modeling

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Authors: M. Novak, E. Munoz, A. Jana, M. Nelemans

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Cities and local governments the world over are interested to employ circular strategies as a means to bring about food security, create employment and increase resilience. The selection and implementation of circular strategies is facilitated by modeling the effects of strategies locally and understanding the impacts such strategies have had in other (comparable) cities and how that would translate locally. Urban areas are heterogeneous because of their geographic, economic, social characteristics, governance, and culture. In order to better understand the effect of circular strategies on urban systems, we create a dataset for over 300 cities around the world designed to facilitate circular strategy scenario modeling. This new dataset integrates data from over 20 prominent global national and urban data sources, such as the Global Human Settlements layer and International Labour Organisation, as well as incorporating employment data from over 150 cities collected bottom up from local departments and data providers. The dataset is made to be reproducible. Various clustering techniques are explored in the paper. The result is sets of clusters of cities, which can be used for further research, analysis, and support comparative, regional, and national policy making on circular cities.

Keywords: data integration, urban innovation, cluster analysis, circular economy, city profiles, scenario modelling

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Authors: Pallab Das, Nabam Zomleen

Abstract:

Effective dissipation of lateral loads that are coming due to seismic force determines the strength, durability and safety concern of the structure. Masonry infill has high stiffness and strength capabilities which can be put into an effective utilization for lateral load dissipation by incorporating it into building construction, but masonry behaves in highly nonlinear manner, so it is highly important to find out generalized, yet a rational approach to determine its nonlinear behavior and failure mode and it’s response when it is incorporated into building. But most of the countries do not specify the procedure for design of masonry infill wall. Whereas, there are many analytical modeling method available in literature, e.g. equivalent diagonal strut method, finite element modeling etc. In this paper the masonry infill is modeled and 6-storey bare framed building and building with masonry infill is analyzed using SAP-200014 in order to find out inter-storey drift by time-history analysis and capacity curve by Pushover analysis. The analysis shows that, while, the structure is well within CP performance level for both the case, whereas, there is considerable reduction of inter-storey drift of about 28%, when the building is analyzed with masonry infill wall.

Keywords: capacity curve, masonry infill, nonlinear analysis, time history analysis

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Authors: Adji Achmad Rinaldo Fernandes

Abstract:

SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Hussain Bohra, Pradyuman Sharma

Abstract:

This study highlights the significance of Balance Sheet Indicators on the corporate performance in the case of Indian manufacturing companies. Balance sheet indicators show the actual financial health of the company and it helps to the external investors to choose the right company for their investment and it also help to external financing agency to give easy finance to the manufacturing companies. The period of study is 2000 to 2014 for 813 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test and Hausman test results proof the suitability of the fixed effect model for the estimation. Return on assets (ROA) is used as the proxy to measure corporate performance. ROA is the best proxy to measure corporate performance as it already used by the most of the authors who worked on the corporate performance. ROA shows return on long term investment projects of firms. Different ratios like Current Ratio, Debt-equity ratio, Receivable turnover ratio, solvency ratio have been used as the proxies for the Balance Sheet Indicators. Other firm specific variable like firm size, and sales as the control variables in the model. From the empirical analysis, it was found that all selected financial ratios have significant and positive impact on the corporate performance. Firm sales and firm size also found significant and positive impact on the corporate performance. To check the robustness of results, the sample was divided on the basis of different ratio like firm having high debt equity ratio and low debt equity ratio, firms having high current ratio and low current ratio, firms having high receivable turnover and low receivable ratio and solvency ratio in the form of firms having high solving ratio and low solvency ratio. We find that the results are robust to all types of companies having different form of selected balance sheet indicators ratio. The results for other variables are also in the same line as for the whole sample. These findings confirm that Balance sheet indicators play as significant role on the corporate performance in India. The findings of this study have the implications for the corporate managers to focus different ratio to maintain the minimum expected level of performance. Apart from that, they should also maintain adequate sales and total assets to improve corporate performance.

Keywords: balance sheet, corporate performance, current ratio, panel data method

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Authors: I. A Tijani, Y. F Wu, C.W. Lim

Abstract:

Concrete Damaged Plasticity Model (CDPM) is capable of modeling the stress-strain behavior of confined concrete. Nevertheless, the accuracy of the model largely depends on its parameters. To date, most research works mainly focus on the identification and modification of the parameters for fiber reinforced polymer (FRP) confined concrete prior to damage. And, it has been established that the FRP-strengthened concrete behaves differently to FRP-repaired concrete. This paper presents a modified plastic damage model within the context of the CDPM in ABAQUS for modelling of a uniformly FRP-confined repaired concrete under monotonic loading. The proposed model includes infliction damage, elastic stiffness, yield criterion and strain hardening rule. The distinct feature of damaged concrete is elastic stiffness reduction; this is included in the model. Meanwhile, the test results were obtained from a physical testing of repaired concrete. The dilation model is expressed as a function of the lateral stiffness of the FRP-jacket. The finite element predictions are shown to be in close agreement with the obtained test results of the repaired concrete. It was observed from the study that with necessary modifications, finite element method is capable of modeling FRP-repaired concrete structures.

Keywords: Concrete, FRP, Damage, Repairing, Plasticity, and Finite element method

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Authors: Ayşin Sev, Meltem Ezel

Abstract:

Sustainability, being the urgent issue of our time, is closely related with the innovations in technology. Nanotechnology (NT), although not a new science, can be regarded relatively a new science for buildings with brand new materials and applications. This paper tends to give a research review of current and near future applications of nanotechnology (NT) for achieving high-performance and healthy buildings for a sustainable future. In the introduction, the driving forces for the sustainability of construction industry are explained. Then, the term NT is defined, and significance of innovations in NT for a sustainable construction industry is revealed. After presenting the application areas of NT and nanomaterials for buildings with a number of cases, challenges in the adoption of this technology are put forward, and finally the impacts of nanoparticles and nanomaterials on human health and environment are discussed.

Keywords: nanomaterial, self-healing concrete, self cleaning sensor, nanosensor, steel, wood, aerogel, flexible solar panel

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Authors: Maha Bakakri, Rachid Tadili, Fatiha Lemmini

Abstract:

Morocco is one of the few countries that have kept their traditional crafts, despite the competition of modern industry and its impact on manual labor. Therefore the optimization of energy consumption becomes an obligation and this is the purpose of this document. In this work we present some characteristics of the furnace studied, its operating principle and the experimental measurements of the evolutions of the temperatures inside and outside the walls of the furnace, values which will be used later in the calculation of its thermal losses. In order to determine the major source of the thermal losses of the furnace we have established the heat balance of the furnace. The energy consumed, the useful energy and the thermal losses through the walls and the chimney of the furnace are calculated thanks to the experimental measurements which we realized for several firings. The results show that the energy consumption of this type of furnace is very high and that the main source of energy loss is mainly due to the heat losses of the combustion gases that escape from the furnace by the chimney while the losses through the walls are relatively small. it have opted for energy recovery as a solution where we can recover some of the heat lost through the use of a heat exchanger system using a double tube introduced into the flue gas exhaust stack compartment. The study on the heat recovery system is presented and the heat balance inside the exchanger is established. In this paper we also present the numerical modeling of heat transfer by conduction through the walls of the furnace. A numerical model has been established based on the finite volume method and the double scan method. It makes it possible to determine the temperature profile of the furnace and thus to calculate the thermal losses of its walls and to deduce the thermal losses due to the combustion gases. Validation of the model is done using the experimental measurements carried out on the furnace. The results obtained in this work, relating to the energy consumed during the operation of the furnace are important and are part of the energy efficiency framework that has become a key element in global energy policies. It is the fastest and cheapest way to solve energy, environmental and economic security problems.

Keywords: energy cunsumption, energy recovery, modeling, energy eficiency

Procedia PDF Downloads 49