Search results for: Sequential Linear Programming (SLP)

Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

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The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

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Authors: Joel Ballesteros, Harriet Jane Caleja, Florian Del Mundo, Cherrie Pascual

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Diffraction-based sensing was utilized in the quantification of human ferritin in blood serum to provide an alternative to label-based immunoassays currently used in clinical diagnostics and researches. The diffraction intensity was measured by the diffractive optics technology or dotLab™ system. Two methods were evaluated in this study: direct immunoassay and direct sandwich immunoassay. In the direct immunoassay, human ferritin was captured by human ferritin antibodies immobilized on an avidin-coated sensor while the direct sandwich immunoassay had an additional step for the binding of a detector human ferritin antibody on the analyte complex. Both methods were repeatable with coefficient of variation values below 15%. The direct sandwich immunoassay had a linear response from 10 to 500 ng/mL which is wider than the 100-500 ng/mL of the direct immunoassay. The direct sandwich immunoassay also has a higher calibration sensitivity with value 0.002 Diffractive Intensity (ng mL-1)-1) compared to the 0.004 Diffractive Intensity (ng mL-1)-1 of the direct immunoassay. The limit of detection and limit of quantification values of the direct immunoassay were found to be 29 ng/mL and 98 ng/mL, respectively, while the direct sandwich immunoassay has a limit of detection (LOD) of 2.5 ng/mL and a limit of quantification (LOQ) of 8.2 ng/mL. In terms of accuracy, the direct immunoassay had a percent recovery of 88.8-93.0% in PBS while the direct sandwich immunoassay had 94.1 to 97.2%. Based on the results, the direct sandwich immunoassay is a better diffraction-based immunoassay in terms of accuracy, LOD, LOQ, linear range, and sensitivity. The direct sandwich immunoassay was utilized in the determination of human ferritin in blood serum and the results are validated by Chemiluminescent Magnetic Immunoassay (CMIA). The calculated Pearson correlation coefficient was 0.995 and the p-values of the paired-sample t-test were less than 0.5 which show that the results of the direct sandwich immunoassay was comparable to that of CMIA and could be utilized as an alternative analytical method.

Keywords: biosensor, diffraction, ferritin, immunoassay

Procedia PDF Downloads 351

Authors: Elena M. Capitanul, Carlos A. Nunes Cosenza, Walid El Moudani, Felix Mora Camino

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The construction of a new airport or the extension of an existing one requires massive investments and many times public private partnerships were considered in order to make feasible such projects. One characteristic of these projects is uncertainty with respect to financial and environmental impacts on the medium to long term. Another one is the multistage nature of these types of projects. While many airport development projects have been a success, some others have turned into a nightmare for their promoters. This communication puts forward a new approach for airport investment risk assessment. The approach takes explicitly into account the degree of uncertainty in activity levels prediction and proposes milestones for the different stages of the project for minimizing risk. Uncertainty is represented through fuzzy dual theory and risk management is performed using dynamic programming. An illustration of the proposed approach is provided.

Keywords: airports, fuzzy logic, risk, uncertainty

Procedia PDF Downloads 407

Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

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Authors: N. P. G. N. Chandrasekara, R. M. Pashley

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Ion exchange (IEX) resins are commonly available as cationic or anionic resins but not as polyampholytic resins. This is probably because sequential acid and base washing cannot produce complete regeneration of polyampholytic resins with chemically attached anionic and cationic groups in close proximity. The ‘Sirotherm’ process, developed by the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Melbourne, Australia was originally based on the use of a physical mixture of weakly basic (WB) and weakly acidic (WA) ion-exchange resin beads. These resins were regenerated thermally and they were capable of removing salts from an aqueous solution at higher temperatures compared to the salt sorbed at ambient temperatures with a significant reduction of the sorption capacity with increasing temperature. A new process for the efficient regeneration of mixed bead resins using ammonium bicarbonate with heat was studied recently and this chemical/thermal regeneration technique has the capability for completely regenerating polyampholytic resins. Even so, the low IEX capacities of polyampholytic resins restrict their commercial applications. Recently, we have established another novel process for increasing the IEX capacity of a typical polyampholytic resin. In this paper we will discuss the chemical/thermal regeneration of a polyampholytic (WA/WB) resin and a novel process for enhancing its ion exchange capacity, by increasing its internal pore area. We also show how effective this method is for completely recycled regeneration, with the potential of substantially reducing chemical waste.

Keywords: capacity, ion exchange, polyampholytic resin, regeneration

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Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

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Authors: Vinayambika S. Bhat, S. Shanmuga Priya, I. Thirunavukkarasu, Shreeranga Bhat

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An attempt has been made to design a decoupling controller for systems with more inputs more outputs with dead time in it. The de-coupler is designed for the chemical process industry 3×3 plant transfer function with dead time. The Quantitative Feedback Theory (QFT) based controller has also been designed here for the 2×2 distillation column transfer function. The developed control techniques were simulated using the MATLAB/Simulink. Also, the stability of the process was analyzed, together with the presence of various perturbations in it. Time domain specifications like setting time along with overshoot and oscillations were analyzed to prove the efficiency of the de-coupler method. The load disturbance rejection was tested along with its performance. The QFT control technique was synthesized based on the stability and performance specifications in the presence of uncertainty in time constant of the plant transfer function through sequential loop shaping technique. Further, the energy efficiency of the distillation column was improved by proper tuning of the controller. A distillation column consumes 3% of the total energy consumption of the world. A suitable control technique is very important from an economic point of view. The real time implementation of the process is under process in our laboratory.

Keywords: distillation, energy, MIMO process, time delay, robust stability

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Authors: M. H. M. Rashid

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Given H a Hilbert space and B(H) the algebra of bounded linear operator in H, let δAB denote the generalized derivation defined by A and B. The main objective of this article is to study Weyl type theorems for generalized derivation for (A,B) satisfying a couple of Fuglede.

Keywords: Fuglede Property, Weyl’s theorem, generalized derivation, Aluthge transform

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Authors: Hale Kirer Silva Lecuna, Beyza Aydin

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Health is one of the main components of human capital and sustainable development, and it is very important for economic growth. Health economics, which is an indisputable part of the science of economics, has five stages in general. These are health and development, financing of health services, economic regulation in the health, allocation of resources and efficiency of health services. A well-developed and efficient health sector plays a major role by increasing the level of development of countries. The most crucial pillars of the health sector are the hospitals that are divided into public and private. The main purpose of the hospitals is to provide more efficient services. Therefore the aim is to meet patients’ satisfaction by increasing the service quality. Health-related studies in Turkey date back to the Ottoman and Seljuk Empires. In the near past, Turkey applied 'Health Sector Transformation Programs' under different titles between 2003 and 2010. Our aim in this paper is to measure how effective these transformation programs are for the health sector, to see how much they can increase the efficiency of hospitals over the years, to see the return of investments, to make comments and suggestions on the results, and to provide a new reference for the literature. Within this framework, the public and private hospitals in Balıkesir, Bilecik, Bursa, Çanakkale, Edirne, Istanbul, Kirklareli, Kocaeli, Sakarya, Tekirdağ, Yalova will be examined by using Data Envelopment Analysis (DEA) for the years between 2000 and 2019. DEA is a linear programming-based technique, which gives relatively good results in multivariate studies. DEA basically estimates an efficiency frontier and make a comparison. Constant returns to scale and variable returns to scale are two most commonly used DEA methods. Both models are divided into two as input and output-oriented. To analyze the data, the number of personnel, number of specialist physicians, number of practitioners, number of beds, number of examinations will be used as input variables; and the number of surgeries, in-patient ratio, and crude mortality rate as output variables. 11 hospitals belonging to the Marmara region were included in the study. It is seen that these hospitals worked effectively only in 7 provinces (Balıkesir, Bilecik, Bursa, Edirne, İstanbul, Kırklareli, Yalova) for the year 2001 when no transformation program was implemented. After the transformation program was implemented, for example, in 2014 and 2016, 10 hospitals (Balıkesir, Bilecik, Bursa, Çanakkale, Edirne, İstanbul, Kocaeli, Kırklareli, Tekirdağ, Yalova) were found to be effective. In 2015, ineffective results were observed for Sakarya, Tekirdağ and Yalova. However, since these values are closer to 1 after the transformation program, we can say that the transformation program has positive effects. For Sakarya alone, no effective results have been achieved in any year. When we look at the results in general, it shows that the transformation program has a positive effect on the effectiveness of hospitals.

Keywords: data envelopment analysis, efficiency, health sector, Marmara region

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Authors: Chandan Hegde, K. Ashwini

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Commonsense reasoning is the simulation of human ability to make decisions during the situations that we encounter every day. It has been several decades since the introduction of this subfield of artificial intelligence, but it has barely made some significant progress. The modern computing aids also have remained impotent in this regard due to the absence of a strong methodology towards commonsense reasoning development. Among several accountable reasons for the lack of progress, drawing inference out of commonsense knowledge-base stands out. This review paper emphasizes on a detailed analysis of representation of reasoning uncertainties and feasible prospects of programming aids for drawing inferences. Also, the difficulties in deducing and systematizing commonsense reasoning and the substantial progress made in reasoning that influences the study have been discussed. Additionally, the paper discusses the possible impacts of an effective inference technique in commonsense reasoning.

Keywords: artificial intelligence, commonsense reasoning, knowledge base, uncertainty in reasoning

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Authors: Aleksandr I. Korobov, Natalia V. Shirgina, Aleksey I. Kokshaiskiy, Vyacheslav M. Prokhorov

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The paper presents the results of an experimental study of the effect of reverse mechanical load-unloading on the mechanical, linear, and nonlinear elastic properties of n-AMg6/C60 nanocomposite. Samples for experimental studies of n-AMg6/C60 nanocomposite were obtained by grinding AMg6 polycrystalline alloy in a planetary mill with 0.3 wt % of C60 fullerite in an argon atmosphere. The resulting product consisted of 200-500-micron agglomerates of nanoparticles. X-ray coherent scattering (CSL) method has shown that the average nanoparticle size is 40-60 nm. The resulting preform was extruded at high temperature. Modifications of C60 fullerite interferes the process of recrystallization at grain boundaries. In the samples of n-AMg6/C60 nanocomposite, the load curve is measured: the dependence of the mechanical stress σ on the strain of the sample ε under its multi-cycle load-unloading process till its destruction. The hysteresis dependence σ = σ(ε) was observed, and insignificant residual strain ε < 0.005 were recorded. At σ≈500 MPa and ε≈0.025, the sample was destroyed. The destruction of the sample was fragile. Microhardness was measured before and after destruction of the sample. It was found that the loading-unloading process led to an increase in its microhardness. The effect of the reversible mechanical stress on the linear and nonlinear elastic properties of the n-AMg6/C60 nanocomposite was studied experimentally by ultrasonic method on the automated complex Ritec RAM-5000 SNAP SYSTEM. In the n-AMg6/C60 nanocomposite, the velocities of the longitudinal and shear bulk waves were measured with the pulse method, and all the second-order elasticity coefficients and their dependence on the magnitude of the reversible mechanical stress applied to the sample were calculated. Studies of nonlinear elastic properties of the n-AMg6/C60 nanocomposite at reversible load-unloading of the sample were carried out with the spectral method. At arbitrary values of the strain of the sample (up to its breakage), the dependence of the amplitude of the second longitudinal acoustic harmonic at a frequency of 2f = 10MHz on the amplitude of the first harmonic at a frequency f = 5MHz of the acoustic wave is measured. Based on the results of these measurements, the values of the nonlinear acoustic parameter in the n-AMg6/C60 nanocomposite sample at different mechanical stress were determined. The obtained results can be used in solid-state physics, materials science, for development of new techniques for nondestructive testing of structural materials using methods of nonlinear acoustic diagnostics. This study was supported by the Russian Science Foundation (project №14-22-00042).

Keywords: nanocomposite, generation of acoustic harmonics, nonlinear acoustic parameter, hysteresis

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Authors: Ahmed Elreedy, Ahmed Tawfik

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This investigation aims to assess the effect of inoculum to substrate ratio (ISR) and nitrogen to phosphorous balance on simultaneous biohydrogen and methane production from anaerobic decomposition of mono-ethylene glycol (MEG). Different ISRs were applied in the range between 2.65 and 13.23 gVSS/gCOD, whereas the tested N/P ratios were changed from 4.6 to 8.5; both under thermophilic conditions (55°C). The maximum obtained methane and hydrogen yields (MY and HY) of 151.86±10.8 and 22.27±1.1 mL/gCODinitial were recorded at ISRs of 5.29 and 3.78 gVSS/gCOD, respectively. Unlikely, the ammonification process, in terms of net ammonia produced, was found to be ISR and COD/N ratio dependent, reaching its peak value of 515.5±31.05 mgNH4-N/L at ISR and COD/N ratio of 13.23 gVSS/gCOD and 11.56. The optimum HY was enhanced by more than 1.45-fold with declining N/P ratio from 8.5 to 4.6; whereas, the MY was improved (1.6-fold), while increasing N/P ratio from 4.6 to 5.5 with no significant impact at N/P ratio of 8.5. The results obtained revealed that the methane production was strongly influenced by initial ammonia, compared to initial phosphate. Likewise, the generation of ammonia was markedly deteriorated from 535.25±41.5 to 238.33±17.6 mgNH4-N/L with increasing N/P ratio from 4.6 to 8.5. The kinetic study using Modified Gompertz equation was successfully fitted to the experimental outputs (R2 > 0.9761).

Keywords: mono-ethylene glycol, biohydrogen and methane, inoculum to substrate ratio, nitrogen to phosphorous balance, ammonification

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Authors: Trevor C. Brown, David J. Miron

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Gas-solid physical adsorption methods are central to the characterization and optimization of the effective surface area, pore size and porosity for applications such as heterogeneous catalysis, and gas separation and storage. Properties such as adsorption uptake, capacity, equilibrium constants and Gibbs free energy are dependent on the composition and structure of both the gas and the adsorbent. However, challenges remain, in accurately calculating these properties from experimental data. Gas adsorption experiments involve measuring the amounts of gas adsorbed over a range of pressures under isothermal conditions. Various constant-parameter models, such as Langmuir and Brunauer-Emmett-Teller (BET) theories are used to provide information on adsorbate and adsorbent properties from the isotherm data. These models typically do not provide accurate interpretations across the full range of pressures and temperatures. The Langmuir adsorption isotherm is a simple approximation for modelling equilibrium adsorption data and has been effective in estimating surface areas and catalytic rate laws, particularly for high surface area solids. The Langmuir isotherm assumes the systematic filling of identical adsorption sites to a monolayer coverage. The BET model is based on the Langmuir isotherm and allows for the formation of multiple layers. These additional layers do not interact with the first layer and the energetics are equal to the adsorbate as a bulk liquid. This BET method is widely used to measure the specific surface area of materials. Both Langmuir and BET models assume that the affinity of the gas for all adsorption sites are identical and so the calculated adsorbent uptake at the monolayer and equilibrium constant are independent of coverage and pressure. Accurate representations of adsorption data have been achieved by extending the Langmuir and BET models to include pressure-varying uptake capacities and equilibrium constants. These parameters are determined using a novel regression technique called flexible least squares for time-varying linear regression. For isothermal adsorption the adsorption parameters are assumed to vary slowly and smoothly with increasing pressure. The flexible least squares for pressure-varying linear regression (FLS-PVLR) approach assumes two distinct types of discrepancy terms, dynamic and measurement for all parameters in the linear equation used to simulate the data. Dynamic terms account for pressure variation in successive parameter vectors, and measurement terms account for differences between observed and theoretically predicted outcomes via linear regression. The resultant pressure-varying parameters are optimized by minimizing both dynamic and measurement residual squared errors. Validation of this methodology has been achieved by simulating adsorption data for n-butane and isobutane on activated carbon at 298 K, 323 K and 348 K and for nitrogen on mesoporous alumina at 77 K with pressure-varying Langmuir and BET adsorption parameters (equilibrium constants and uptake capacities). This modeling provides information on the adsorbent (accessible surface area and micropore volume), adsorbate (molecular areas and volumes) and thermodynamic (Gibbs free energies) variations of the adsorption sites.

Keywords: Langmuir adsorption isotherm, BET adsorption isotherm, pressure-varying adsorption parameters, adsorbate and adsorbent properties and energetics

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Matthew Holland, Jason Everett, Martin Cox, Iain Suthers

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High spatial-resolution distribution of planktivorous reef fish can reveal behavioural adaptations to optimise the balance between feeding success and predator avoidance. We used a multi-beam echosounder to record bathymetry and the three-dimensional distribution of fish schools associated with natural and artificial reefs. We utilised generalised linear models to assess the distribution, orientation, and aggregation of fish schools relative to the structure, vertical relief, and currents. At artificial reefs, fish schooled more closely to the structure and demonstrated a preference for the windward side, particularly when exposed to strong currents. Similarly, at natural reefs fish demonstrated a preference for windward aspects of bathymetry, particularly when associated with high vertical relief. Our findings suggest that under conditions with stronger current velocity, fish can exercise their preference to remain close to structure for predator avoidance, while still receiving an adequate supply of zooplankton delivered by the current. Similarly, when current velocity is low, fish tend to disperse for better access to zooplankton. As artificial reefs are generally deployed with the goal of creating productivity rather than simply attracting fish from elsewhere, we advise that future artificial reefs be designed as semi-linear arrays perpendicular to the prevailing current, with multiple tall towers. This will facilitate the conversion of dispersed zooplankton into energy for higher trophic levels, enhancing reef productivity and fisheries.

Keywords: artificial reef, current, forage fish, multi-beam, planktivorous fish, reef fish, schooling

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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: Ferhat Erdal, Osman Tunca, Serkan Tas, Serdar Carbas

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Web-expanded steel beams provide an easy and economical solution for the systems having longer structural members. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. Until recently, there were two common types of open web-expanded beams: with hexagonal openings, also called castellated beams, and beams with circular openings referred to as cellular beams, until the generation of sinusoidal web-expanded beams. In the present research, the optimum design of a new generation beams, namely sinusoidal web-expanded beams, will be carried out and the design results will be compared with castellated and cellular beam solutions. Thanks to a reduced fabrication process and substantial material savings, the web-expanded beam with sinusoidal holes (Angelina™ Beam) meets the economic requirements of steel design problems while ensuring optimum safety. The objective of this research is to carry out non-linear finite element analysis (FEA) of the web-expanded beam with sinusoidal holes. The FE method has been used to predict their entire response to increasing values of external loading until they lose their load carrying capacity. FE model of each specimen that is utilized in the experimental studies is carried out. These models are used to simulate the experimental work to verify of test results and to investigate the non-linear behavior of failure modes such as web-post buckling, shear buckling and vierendeel bending of beams.

Keywords: steel structures, web-expanded beams, angelina beam, optimum design, failure modes, finite element analysis

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Authors: Naser Shagerdi Esmaeli, Mohsen Hamidpour, Parisa Hasankhani Tehrani

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Background: The TP53 mutation is frequently detected in acute myeloid leukemia (AML) patients with complex karyotype (CK), but the stability of this mutation during the clinical course remains unclear. Material and Methods: In this study, TP53 mutations were identified in 7% of 500 patients with de novo AML and 58.8% of patients with CK in Tabriz, Iran. TP53 mutations were closely associated with older age, lower white blood cell (WBC) and platelet counts, FAB M6 subtype, unfavorable-risk cytogenetics, and CK, but negatively associated with NPM1 mutation, FLT3/ITD and DNMT3A mutation. Result: Multivariate analysis demonstrated that TP53 mutation was an independent poor prognostic factor for overall survival and disease-free survival among the total cohort and the subgroup of patients with CK. A scoring system incorporating TP53 mutation and nine other prognostic factors, including age, WBC counts, cytogenetics, and gene mutations, into survival analysis proved to be very useful to stratify AML patients. Sequential study of 420 samples showed that TP53 mutations were stable during AML evolution, whereas the mutation was acquired only in 1 of the 126 TP53 wild-type patients when therapy-related AML originated from different clone emerged. Conclusion: In conclusion, TP53 mutations are associated with distinct clinic-biological features and poor prognosis in de novo AML patients and are rather stable during disease progression.

Keywords: acute myloblastic leukemia, TP53, FLT3/ITD, Iran

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Authors: Esther Burkitt, Dawn Watling

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Background: Four types of patterns of simultaneous mixed emotions have been identified in middle childhood, adolescence and adulthood. The present study applied an analogue emotion scale which permits measuring of intensity of opposite valence emotions over time rather than bipolar ratings and used an exhaustive coding scheme to investigate whether children in early childhood experience previously identified and additional types of mixed emotional experiences. Methods: To explore the presence of simultaneous mixed emotion experiences in early childhood, 112 children (59 girls) aged 5 years 1 month - 7 years 2 months (X=6 years 1 month; SD = 10 months) were recruited across the UK. They were allocated on the basis of alternation by gender on class lists to one of two conditions hearing vignettes describing mixed emotion events in an age and gender matched protagonist or themselves (other, n = 57 and self, n = 55). Findings: New types of flexuous, vertical and other experiences were identified alongside sequential, prevalent, highly parallel and inverse types of experiences identified in older populations. Conclusions: The analogue emotion scale uncovered a broader range of simultaneous mixed emotional experiences than previously identified. The value of exploring the utility of the findings in emotion assessments is discussed along with suggestions to explore impacts of educational and cultural influences on children’s mixed emotional experiences.

Keywords: childhood, emotion, graphing, self

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Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

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In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the Spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are Class balancing, Data shuffling, and Standardization were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the Sequential model and Relu activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: neural network, pineapple, soluble solid content, spectroscopy

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Authors: Mihai Caramihai, Dan Vasilescu

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The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

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Authors: Anil Kumar Tripathi, Ratneshwer Gupta

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All the software engineering researches and best industry practices aim at providing software products with high degree of quality and functionality at low cost and less time. These requirements are addressed by the Component Based Software Engineering (CBSE) as well. CBSE, which deals with the software construction by components’ assembly, is a revolutionary extension of Software Engineering. CBSE must define and describe processes to assure timely completion of high quality software systems that are composed of a variety of pre built software components. Though these features provide distinct and visible benefits in software design and programming, they also raise some challenging problems. The aim of this work is to summarize the pertinent issues and considerations in CBSE to make an understanding in forms of concepts and observations that may lead to development of newer ways of dealing with the problems and challenges in CBSE.

Keywords: software component, component based software engineering, software process, testing, maintenance

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Authors: Egor E. Nuzhin, Nikolay V. Brilliantov

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We propose an approach for addressing Reinforcement Learning (RL) problems. It combines the ideas of umbrella sampling, borrowed from Monte Carlo technique of computational physics and chemistry, with optimal control methods, and is realized on the base of neural networks. This results in a powerful algorithm, designed to solve hard RL problems – the problems, with long-time delayed reward, state-traps sticking and a lack of terminal states. It outperforms the prominent algorithms, such as PPO, RND, iLQR and VI, which are among the most efficient for the hard problems. The new algorithm deals with a continuous ensemble of agents and expected return, that includes the ensemble entropy. This results in a quick and efficient search of the optimal policy in terms of ”exploration-exploitation trade-off” in the state-action space.

Keywords: umbrella sampling, reinforcement learning, policy gradient, dynamic programming

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Authors: Der Chyan Lin

Abstract:

Since the early introduction by Ormondroyd and Den Hartog, vibration absorber (VA) has become one of the most commonly used vibration mitigation strategies. The strategy is most effective for a primary plant subjected to a single frequency excitation. For continuous systems, notable advances in vibration absorption in the multi-frequency system were made. However, the efficacy of the VA strategy for systems under multi-frequency excitation is not well understood. For example, for an N degrees-of-freedom (DOF) primary-absorber system, there are N 'peak' frequencies of large amplitude vibration per every new excitation frequency. In general, the usable range for vibration absorption can be greatly reduced as a result. Frequency modulated harmonic excitation is a commonly seen multi-frequency excitation example: f(t) = cos(ϖ(t)t) where ϖ(t)=ω(1+α sin⁡(δt)). It is known that f(t) has a series expansion given by the Bessel function of the first kind, which implies an infinity of forcing frequencies in the frequency modulated harmonic excitation. For an SDOF system of natural frequency ωₙ subjected to f(t), it can be shown that amplitude peaks emerge at ω₍ₚ,ₖ₎=(ωₙ ± 2kδ)/(α ∓ 1),k∈Z; i.e., there is an infinity of resonant frequencies ω₍ₚ,ₖ₎, k∈Z, making the use of VA strategy ineffective. In this work, we propose an absorber frequency placement strategy for SDOF vibration systems subjected to frequency-modulated excitation. An SDOF linear mass-spring system coupled to lateral absorber systems is used to demonstrate the ideas. Although the mechanical components are linear, the governing equations for the coupled system are nonlinear. We show using N identical absorbers, for N ≫ 1, that (a) there is a cluster of N+1 natural frequencies around every natural absorber frequency, and (b) the absorber frequencies can be moved away from the plant's resonance frequency (ω₀) as N increases. Moreover, we also show the bandwidth of the VA performance increases with N. The derivations of the clustering and bandwidth widening effect will be given, and the superiority of the proposed strategy will be demonstrated via numerical experiments.

Keywords: Bessel function, bandwidth, frequency modulated excitation, vibration absorber

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Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

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Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: air pollution, AODV, re-scheduling, WSNs

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Authors: Abdelhak-Djamel Seriai, Selim Kebir, Allaoua Chaoui

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During the last decades, object oriented program- ming has been massively used to build large-scale systems. However, evolution and maintenance of such systems become a laborious task because of the lack of object oriented programming to offer a precise view of the functional building blocks of the system. This lack is caused by the fine granularity of classes and objects. In this paper, we use a post object-oriented technology namely software components, to propose an approach based on the identification of the functional building blocks of an object oriented system by analyzing its source code. These functional blocks are specified as software components and the result is a multi-layer component based software architecture.

Keywords: software comprehension, software component, object oriented, software architecture, reverse engineering

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Authors: M. Moeinaddini, Z. Asadi-Shekari, Z. Sultan, M. Zaly Shah

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Happiness can be related to everything that can provide a feeling of satisfaction or pleasure. This study tries to consider the relationship between land use factors and feeling of happiness at the neighbourhood level. Land use variables (beautiful and attractive neighbourhood design, availability and quality of shopping centres, sufficient recreational spaces and facilities, and sufficient daily service centres) are used as independent variables and the happiness score is used as the dependent variable in this study. In addition to the land use variables, socio-economic factors (gender, race, marital status, employment status, education, and income) are also considered as independent variables. This study uses the Oxford happiness questionnaire to estimate happiness score of more than 300 people living in six neighbourhoods. The neighbourhoods are selected randomly from Skudai neighbourhoods in Johor, Malaysia. The land use data were obtained by adding related questions to the Oxford happiness questionnaire. The strength of the relationship in this study is found using generalised linear modelling (GLM). The findings of this research indicate that increase in happiness feeling is correlated with an increasing income, more beautiful and attractive neighbourhood design, sufficient shopping centres, recreational spaces, and daily service centres. The results show that all land use factors in this study have significant relationship with happiness but only income, among socio-economic factors, can affect happiness significantly. Therefore, land use factors can affect happiness in Skudai more than socio-economic factors.

Keywords: neighbourhood land use, neighbourhood design, happiness, socio-economic factors, generalised linear modelling

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Authors: Kanika S. Raheja, A. Pandey, Shaila Bahl, Pratik Kumar, S. P. Lochab

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The subject of undertaking for this paper is the study of BaSO4 nanophosphor doped with Europium in which mainly the concentration of the rare earth impurity Eu (0.05, 0.1, 0.2, 0.5, and 1 mol %) has been varied. A comparative study of the thermoluminescence(TL) properties of the given nanophosphor has also been done using a well-known standard dosimetry material i.e. TLD-100.Firstly, a number of samples were prepared successfully by the chemical co-precipitation method. The whole lot was then compared to a well established standard material (TLD-100) for its TL sensitivity property. BaSO4:Eu ( 0.2 mol%) showed the highest sensitivity out of the lot. It was also found that when compared to the standard TLD-100, BaSo4:Eu (0.2mol%) showed surprisingly high sensitivity for a large range of doses. The TL response curve for all prepared samples has also been studied over a wide range of doses i.e 10Gy to 2kGy for gamma radiation. Almost all the samples of BaSO4:Eu showed a remarkable linearity for a broad range of doses, which is a characteristic feature of a fine TL dosimeter. The graph remained linear even beyond 1kGy for gamma radiation. Thus, the given nanophosphor has been successfully optimised for the concentration of the dopant material to achieve its highest TL sensitivity. Further, the comparative study with the standard material revealed that the current optimised sample shows an astonishingly better TL sensitivity and a phenomenal linear response curve for an incredibly wide range of doses for gamma radiation (Co-60) as compared to the standard TLD-100, which makes the current optimised BaSo4:Eu quite promising as an efficient gamma radiation dosimeter. Lastly, the present phosphor has been optimised for its annealing temperature to acquire the best results while also studying its fading and reusability properties.

Keywords: gamma radiation, nanoparticles, radiation dosimetry, thermoluminescence

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Authors: Damian Graham, Ashleigh H. Hall, Damani R. Sulph, Michael A. James, Shawn B. Vassell

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This paper assesses the design and feasibility of a Materials Recovery Facility (MRF) in Jamaica as a possible green industry approach to the nation’s economic and solid waste management problems. Jamaica is a developing nation that is vulnerable to climate change that can affect its blue economy and tourism on which it is heavily reliant. Jamaica’s National Solid Waste Management Authority (NSWMA) collects only a fraction of all the solid waste produced annually which is then transported to dumpsites. The remainder is either burnt by the population or disposed of illegally. These practices negatively impact the environment, threaten the sustainability of economic growth from blue economy and tourism and its waste management system is predominantly a cost centre. The implementation of an MRF could boost the manufacturing sector, contribute to economic growth, and be a catalyst in creating a green industry with multiple downstream value chains with supply chain linkages. Globally, there is a trend to reuse and recycle that created an international market for recycled solid waste. MRFs enable the efficient sorting of solid waste into desired recoverable materials thus providing a gateway for entrance to the international trading of recycled waste. Research into the current state and effort to improve waste management in Jamaica in contrast with the similar and more advanced territories are outlined. The study explores the concept of green industrialization and its applicability to vulnerable small state economies like Jamaica. The study highlights the possible contributions and benefits derived from MRFs as a seeding factory that can anchor the reverse and forward logistics of other green industries as part of a logistic-cantered economy. Further, the study showcases an engineering economic analysis that assesses the viability of the implementation of an MRF in Jamaica. This research outlines the potential cost of constructing and operating an MRF and provides a realistic cash flow estimate to establish a baseline for profitability. The approach considers quantitative and qualitative data, assumptions, and modelling using industrial engineering tools and techniques that are outlined. Techniques of facility planning, system analysis and operations research with a focus on linear programming techniques are expressed. Approaches to overcome some implementation challenges including policy, technology and public education are detailed. The results of this study present a reasonable judgment of the prospects of incorporating an MRF to improve Jamaica’s solid waste management and contribute to socioeconomic and environmental benefits and an alternate pathway for economic sustainability.

Keywords: engineering-economic analysis, facility design, green industry, MRF, manufacturing, plant layout, solid-waste management, sustainability, waste disposal

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Authors: Lisa Tribuzio

Abstract:

This paper explores the complexity of working with Muslim communities in Australia. It will draw upon the notions of belonging, social inclusion and effective community programming to engage Muslim communities in Western environments given the current global political climate. Factors taken into consideration for effective engagement include: family engagement, considering key practices such as Ramadan, fasting and prayer and food requirements, gender relations, core values around faith and spirituality, considering attitudes towards self disclosure in a counseling setting and the notion of Us and Them in the media and systems and its effect on minority communities. It will explore recent research in the field from Australian researchers as well as recommendations from United Nations in working with Muslim communities. It will also explore current practice models applied in Australia in engaging effectively with diverse communities and addressing racism and discrimination in innovative ways.

Keywords: Muslim, cultural diversity, social inclusion, racism

Procedia PDF Downloads 416