Search results for: optimization analysis

Authors: Sara Muhammad Elqudah, Vigh László Gergely

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Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.

Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: A. Arshad, M. Lehtonen. M. Humayun

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With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

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Authors: Angela Meyer

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The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

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Authors: F. J. Ma, A. K. H. Kwan

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Crack caused by shrinkage movement of concrete is a serious problem especially when restraint is provided. It may cause severe serviceability and durability problems. The existing prediction methods for crack width of concrete due to shrinkage movement are mainly numerical methods under simplified circumstances, which do not agree with each other. To get a more unified prediction method applicable to more sophisticated circumstances, finite element crack width analysis for shrinkage effect should be developed. However, no existing finite element analysis can be carried out to predict the crack width of concrete due to shrinkage movement because of unsolved reasons of conventional finite element analysis. In this paper, crack width analysis implemented by finite element analysis is presented with pseudo-discrete crack model, which combines traditional smeared crack model and newly proposed crack queuing algorithm. The proposed pseudo-discrete crack model is capable of simulating separate and single crack without adopting discrete crack element. And the improved finite element analysis can successfully simulate the stress redistribution when concrete is cracked, which is crucial for predicting crack width, crack spacing and crack number.

Keywords: crack queuing algorithm, crack width analysis, finite element analysis, shrinkage effect

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Authors: Jeffrey A. Lavarias, Jessie C. Elauria, Arnold R. Elepano, Engelbert K. Peralta, Delfin C. Suministrado

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Shelling process is one of the primary processes and critical steps in the processing of chocolate or any product that is derived from cocoa beans. It affects the quality of the cocoa nibs in terms of flavor and purity. In the Philippines, small-scale food processor cannot really compete with large scale confectionery manufacturers because of lack of available postharvest facilities that are appropriate to their level of operation. The impact of this study is to provide the needed intervention that will pave the way for cacao farmers of engaging on the advantage of value-adding as way to maximize the economic potential of cacao. Thus, provision and availability of needed postharvest machines like mechanical cacao sheller will revolutionize the current state of cacao industry in the Philippines. A mechanical cacao sheller was developed, fabricated, and evaluated to establish optimum shelling conditions such as moisture content of cocoa beans, clearance where of cocoa beans passes through the breaker section and speed of the breaking mechanism on shelling recovery, shelling efficiency, shelling rate, energy utilization and large nib recovery; To establish the optimum level of shelling parameters of the mechanical sheller. These factors were statistically analyzed using design of experiment by Box and Behnken and Response Surface Methodology (RSM). By maximizing shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization, the optimum shelling conditions were established at moisture content, clearance and breaker speed of 6.5%, 3 millimeters and 1300 rpm, respectively. The optimum values for shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization were recorded at 86.51%, 99.19%, 21.85kg/hr, 89.75%, and 542.84W, respectively. Experimental values obtained using the optimum conditions were compared with predicted values using predictive models and were found in good agreement.

Keywords: cocoa beans, optimization, RSM, shelling parameters

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Authors: Afnan Ahmad, Shahid Ali, Mujahid Khan

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This research presents the parametric study of an existing earth fill dam located at Latamber, Karak city, Pakistan. The study consists of carrying out seepage analysis, slope stability analysis, and Earthquake analysis of the dam for the existing dam geometry and do the same for modified geometry. Dams are massive as well as expensive hydraulic structure, therefore it needs proper attention. Additionally, this dam falls under zone 2B region of Pakistan, which is an earthquake-prone area and where ground accelerations range from 0.16g to 0.24g peak. So it should be deal with great care, as the failure of any dam can cause irreparable losses. Similarly, seepage as well as slope failure can also cause damages which can lead to failure of the dam. Therefore, keeping in view of the importance of dam construction and associated costs, our main focus is to carry out parametric study of newly constructed dam. GeoStudio software is used for this analysis in the study in which Seep/W is used for seepage analysis, Slope/w is used for Slope stability analysis and Quake/w is used for earthquake analysis. Based on the geometrical, hydrological and geotechnical data, Seepage and slope stability analysis of different proposed geometries of the dam are carried out along with the Seismic analysis. A rigorous analysis was carried out in 2-D limit equilibrium using finite element analysis. The seismic study began with the static analysis, continuing by the dynamic response analysis. The seismic analyses permitted evaluation of the overall patterns of the Latamber dam behavior in terms of displacements, stress, strain, and acceleration fields. Similarly, the seepage analysis allows evaluation of seepage through the foundation and embankment of the dam, while slope stability analysis estimates the factor of safety of the upstream and downstream of the dam. The results of the analysis demonstrate that among multiple geometries, Latamber dam is secure against seepage piping failure and slope stability (upstream and downstream) failure. Moreover, the dam is safe against any dynamic loading and no liquefaction has been observed while changing its geometry in permissible limits.

Keywords: earth-fill dam, finite element, liquefaction, seepage analysis

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Authors: Young-Kwan Choi, Han-Sang Jeong, Yeon-Ho Ok, Jae-Ho Choi

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The purpose of this study is to verify validity of design by testing output of induction generator through finite element analysis before manufacture of induction generator designed. Characteristics in the operating domain of induction generator can be understood through analysis of magnetic field according to load (rotational speed) of induction generator. Characteristics of induction generator such as induced voltage, current, torque, magnetic flux density (magnetic flux saturation), and loss can be predicted by analysis of magnetic field.

Keywords: electromagnetic analysis, induction generator, small hydro power generator, small francis turbine generator

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Authors: Shivdayal Patel, Suhail Ahmad

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Safety assurance and failure prediction of composite material component of an offshore structure due to low velocity impact is essential for associated risk assessment. It is important to incorporate uncertainties associated with material properties and load due to an impact. Likelihood of this hazard causing a chain of failure events plays an important role in risk assessment. The material properties of composites mostly exhibit a scatter due to their in-homogeneity and anisotropic characteristics, brittleness of the matrix and fiber and manufacturing defects. In fact, the probability of occurrence of such a scenario is due to large uncertainties arising in the system. Probabilistic finite element analysis of composite plates due to low-velocity impact is carried out considering uncertainties of material properties and initial impact velocity. Impact-induced damage of composite plate is a probabilistic phenomenon due to a wide range of uncertainties arising in material and loading behavior. A typical failure crack initiates and propagates further into the interface causing de-lamination between dissimilar plies. Since individual crack in the ply is difficult to track. The progressive damage model is implemented in the FE code by a user-defined material subroutine (VUMAT) to overcome these problems. The limit state function is accordingly established while the stresses in the lamina are such that the limit state function (g(x)>0). The Gaussian process response surface method is presently adopted to determine the probability of failure. A comparative study is also carried out for different combination of impactor masses and velocities. The sensitivity based probabilistic design optimization procedure is investigated to achieve better strength and lighter weight of composite structures. Chain of failure events due to different modes of failure is considered to estimate the consequences of failure scenario. Frequencies of occurrence of specific impact hazards yield the expected risk due to economic loss.

Keywords: composites, damage propagation, low velocity impact, probability of failure, uncertainty modeling

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Authors: Abdelrahman Mohamed

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The ancient Egyptians used canopic vessels in embalming operations in order to preserve the guts of the mummified corpse. Canopic vessels were made of many materials, including pottery and glazed pottery. In this research, we study a pottery canopic vessel and a glazed pottery vessel. An analysis to find out the compounds and elements of the materials from which the container is made and the colors, and also to make some analysis for the organic materials present inside it, such as the Fourier Transform Infrared Spectroscopy analysis and the Gas chromatograph mass spectrometers analysis of the organic residue. Through the study and analysis, it was proved that some of the materials present in the pot were coniferous oil and animal fats. In the other pot, the analysis showed the presence of some plant resins (mastic) inside rolls of linen. Restoration operations were carried out, such as mechanical cleaning, strengthening, and completing the reinforcement of the pots.

Keywords: canopic jar, embalming, FTIR, GCMS, linen.

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Authors: Suresh Vanguri, Suresh Palla, K. V. Kalyani, S. K. Chaturvedi, B. N. Mohapatra

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Enhancing the fly ash utilization in the manufacture of cement is identified as one of the key areas to mitigate the Green House Gas emissions from the cement industry. Though increasing the fly ash content in cement has economic and environmental benefits, it results in a decrease in the compressive strength values, particularly at early ages. Quality of clinker and fly ash were identified as predominant factors that govern the extent of absorption of fly ash in the manufacturing of cement. This paper presents systematic investigations on the effect of clinker and fly ash quality on the properties of resultant cement. Since mechanical activation alters the physicochemical properties such as particle size distribution, surface area, phase morphology, understanding the variation of these properties with activation is required for its applications. The effect of mechanical activation on fly ash surface area, specific gravity, flow properties, lime reactivity, comparative compressive strength (CCS), reactive silica and mineralogical properties were also studied. The fineness of fly ash was determined by Blaine’s method, specific gravity, lime reactivity, CCS were determined as per the method IS 1727-1967. The phase composition of fly ash was studied using the X-ray Diffraction technique. The changes in the microstructure and morphology with activation were examined using the scanning electron microscope. The studies presented in this paper also include evaluation of Portland Pozzolana Cement (PPC), prepared using high volume fly ash. Studies are being carried out using clinker from cement plants located in different regions/clusters in India. Blends of PPC containing higher contents of activated fly ash have been prepared and investigated for their chemical and physical properties, as per Indian Standard procedures. Changes in the microstructure of fly ash with activation and mechanical properties of resultant cement containing high volumes of fly ash indicated the significance of optimization of the quality of clinker and fly ash fineness for better techno-economical benefits.

Keywords: flow properties, fly ash enhancement, lime reactivity, microstructure, mineralogy

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Authors: Chompunut Jantarasorn, Chutima Prommak

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This paper presents an intensive measurement studying of the network performance analysis when IEEE 802.11g Wireless Local Area Networks (WLAN) coexisting with IEEE 802.15.4 Wireless Personal Area Network (WPAN). The measurement results show that the coexistence between both networks could increase the Frame Error Rate (FER) of the IEEE 802.15.4 networks up to 60% and it could decrease the throughputs of the IEEE 802.11g networks up to 55%.

Keywords: wireless performance analysis, coexistence analysis, IEEE 802.11g, IEEE 802.15.4

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: Yang Chen, Lili Fu

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Promoting urban regeneration in existing areas has been elevated to a national strategy in China. In this context, because of the multidimensional sustainable effect through the intensive use of land, mixed-use development has become an important objective for high-quality urban regeneration in the inner city. However, in the long period of time since China's reform and opening up, the "unbalanced phenomenon" of mixed-use development in China's inner cities has been very serious. On the one hand, the excessive focus on certain individual spaces has led to an increase in the level of mixed-use development in some areas, substantially ahead of others, resulting in a growing gap between different parts of the inner city; On the other hand, the excessive focus on a one-dimensional element of the spatial organization of mixed-use development, such as the enhancement of functional mix or spatial capacity, has led to a lagging phenomenon or neglect in the construction of other dimensional elements, such as pedestrian permeability, green environmental quality, social inclusion, etc. This phenomenon is particularly evident in the central area of the inner city, and it clearly runs counter to the need for sustainable development in China's new era. Therefore, a rational qualitative and quantitative analysis of the "unbalanced phenomenon" will help to identify the problem and provide a basis for the formulation of relevant optimization plans in the future. This paper builds a dynamic evaluation method of mixed-use development based on a meta-dimensional model and then uses spatial evolution analysis and spatial consistency analysis with ArcGIS software to reveal the "unbalanced phenomenon " in over the past 40 years of the central city area in Nanjing, a China’s typical city facing regeneration. This study result finds that, compared to the increase in functional mix and capacity, the dimensions of residential space mix, public service facility mix, pedestrian permeability, and greenness in Nanjing's city central area showed different degrees of lagging improvement, and the unbalanced development problems in each part of the city center are different, so the governance and planning plan for future mixed-use development needs to fully address these problems. The research methodology of this paper provides a tool for comprehensive dynamic identification of mixed-use development level’s change, and the results deepen the knowledge of the evolution of mixed-use development patterns in China’s inner cities and provide a reference basis for future regeneration practices.

Keywords: mixed-use development, unbalanced phenomenon, the meta-dimensional model, over the past 40 years of Nanjing, China

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Authors: Esma Birisci, Ronald McGarvey

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One of the common problems in food service industry is demand uncertainty. This research presents a multi-criteria optimization approach to identify the efficient frontier of points lying between the minimum-waste and minimum-shortfall solutions within uncertain demand environment. It also addresses correlation across demands for items (e.g., hamburgers are often demanded with french fries). Reducing overproduction food waste (and its corresponding environmental impacts) and an aversion to shortfalls (leave some customer hungry) need to consider as two contradictory objectives in an all-you-care-to-eat environment food service operation. We identify optimal production adjustments relative to demand forecasts, demand thresholds for utilization of leftovers, and percentages of demand to be satisfied by leftovers, considering two alternative metrics for overproduction waste: mass; and greenhouse gas emissions. Demand uncertainty and demand correlations are addressed using a kernel density estimation approach. A statistical analysis of the changes in decision variable values across each of the efficient frontiers can then be performed to identify the key variables that could be modified to reduce the amount of wasted food at minimal increase in shortfalls. We illustrate our approach with an application to empirical data from Campus Dining Services operations at the University of Missouri.

Keywords: environmental studies, food waste, production planning, uncertain and correlated demand

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Authors: Mauricio Terceros, Jann-Eike Saathoff, Martin Achmus

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In non-cohesive soil, onshore wind turbines are often found on shallow foundations with a circular or octagonal shape. For the current generation of wind turbines, shallow foundations with very large breadths are required. The foundation support costs thus represent a considerable portion of the total construction costs. Therefore, an economic optimization of the type of foundation is highly desirable. A conceivable alternative foundation type would be a pier foundation, which combines the load transfer over the foundation area at the pier base with the transfer of horizontal loads over the shaft surface of the pier. The present study aims to evaluate the load-bearing behavior of a pier foundation based on comprehensive parametric studies. Thereby, three-dimensional numerical simulations of both pier and shallow foundations are developed. The evaluation of the results focuses on the rotational stiffnesses of the proposed soil-foundation systems. In the design, the initial rotational stiffness is decisive for consideration of natural frequencies, whereas the rotational secant stiffness for a maximum load is decisive for serviceability considerations. A systematic analysis of the results at different load levels shows that the application of the typical pier foundation is presumably limited to relatively small onshore wind turbines.

Keywords: onshore wind foundation, pier foundation, rotational stiffness of soil-foundation system, shallow foundation

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Authors: Mohammad Mirzaei

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This article proposes literary criticism as a source of insight into consumer behavior, provides an extensive overview of literary criticism, provides concrete illustrative analysis, and offers suggestions for further research. To do, a literary analysis of advertising copy identifies elements that provide additional information to consumer researchers and discusses the contribution of literary criticism to consumer research. Important post-war critical schools of thought are reviewed, and relevant theoretical concepts are summarized. Ivory Flakes' advertisements are analyzed using a variety of concepts drawn from literary schools, primarily sociocultural and reader responses. Suggestions for further research on content analysis, image analysis, and consumption history are presented.

Keywords: consumer behaviour, consumer research, consumption history, criticism

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: S. Arpit, P. K. Das, S. K. Dash

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In this paper, a comparative study is done between two fuels, naphtha and natural gas (NG), for a gas turbine (GT) plant of 32.5 MW with the same thermodynamic configuration. From the energy analysis, it is confirmed that the turbine inlet temperature (TIT) of the gas turbine in the case of natural gas is higher as compared to naphtha, and hence the isentropic efficiency of the turbine is better. The result from the exergy analysis also confirms that due to high turbine inlet temperature in the case of natural gas, exergy destruction in combustion chamber is less. But comparing two fuels for overall analysis, naphtha has higher energy and exergetic efficiency as compared to natural gas.

Keywords: exergy analysis, gas turbine, naphtha, natural gas

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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Authors: Zhenyu Yang, Qiunan Chen, Xiaocheng Huang

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Reliable prediction of tunnel collapse remains a prominent challenge in the field of civil engineering. In this study, leveraging the nonlinear Hoek-Brown failure criterion and the upper-bound theorem, an analytical solution for the collapse surface of shallowly buried circular tunnels was derived, taking into account the coupled effects of surface loads and pore water pressures. Initially, surface loads and pore water pressures were introduced as external force factors, equating the energy dissipation rate to the external force, yielding our objective function. Subsequently, the variational method was employed for optimization, and the outcomes were juxtaposed with previous research findings. Furthermore, we utilized the deduced equation set to systematically analyze the influence of various rock mass parameters on collapse shape and extent. To validate our analytical solutions, a comparison with prior studies was executed. The corroboration underscored the efficacy of our proposed methodology, offering invaluable insights for collapse risk assessment in practical engineering applications.

Keywords: tunnel roof stability, analytical solution, hoek–brown failure criterion, limit analysis

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Dina Athariah, Desriani Desriani, Bugi Ratno Budiarto, Abinawanto Abinawanto, Dwi Wulandari

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Breast cancer is a regulated by many genes. Defect in PIK3CA gene especially at position of exon 9 (E542K and E545K), called hot spot mutation induce early transformation of breast cells. The early detection of breast cancer based on mutation profile of this hot spot region would be hampered by the existence of pseudogene, marked by its substitution mutation at base 1658 (E545A) and deletion at 1659 that have been previously proven in several cancers. To the best of the authors’ knowledge, until recently no studies have been reported about pseudogene phenomenon in breast cancer. Here, we reported PCR optimization to to obtain true exon 9 of PIK3CA gene from its pseudogene hence increasing the validity of data. Material and methods: two genomic DNA with Dev and En code were used in this experiment. Two pairs of primer were design for Standard PCR method. The size of PCR products for each primer is 200bp and 400bp. While other primer was designed for Nested-PCR followed with DNA sequencing method. For Nested-PCR, we optimized the annealing temperature in first and second run of PCR, and the PCR cycle for first run PCR (15x versus 25x). Result: standard PCR using both primer pairs designed is failed to detect the true PIK3CA gene, appearing a substitution mutation at 1658 and deletion at 1659 of PCR product in sequence chromatogram indicated pseudogene. Meanwhile, Nested-PCR with optimum condition (annealing temperature for the first round at 55oC, annealing temperatung for the second round at 60,7oC with 15x PCR cycles) and could detect the true PIK3CA gene. Dev sample were identified as WT while En sample contain one substitution mutation at position 545 of exon 9, indicating amino acid changing from E to K. For the conclusion, pseudogene also exists in breast cancer and the apllication of optimazed Nested-PCR in this study could detect the true exon 9 of PIK3CA gene.

Keywords: breast cancer, exon 9, hotspot mutation, PIK3CA, pseudogene

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Mohammad Reza Ameri, Ali Massumi, Mohammad Haghbin

Abstract:

Non-linear static analysis, commonly referred to as pushover analysis, is a powerful tool for assessing the seismic response of structures. A suitable lateral load pattern for pushover analysis can bring the results of this simple, quick and low-cost analysis close to the realistic results of nonlinear dynamic analyses. In this research, four samples of 10- and 15 story (two- and four-bay) reinforced concrete frames were studied. The lateral load distribution patterns recommended in FEMA 273/356 guidelines were applied to the sample models in order to perform pushover analyses. The results were then compared to the results obtained from several nonlinear incremental dynamic analyses for a range of earthquakes. Finally, a lateral load distribution pattern was proposed for pushover analysis of medium-rise reinforced concrete buildings based on the results of nonlinear static and dynamic analyses.

Keywords: lateral load pattern, nonlinear static analysis, incremental dynamic analysis, medium-rise reinforced concrete frames, performance based design

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Authors: Adel Assiri, Ahmed Emam, Hmood Al-Dossari

Abstract:

Sentiment analysis (SA) has received growing attention in Arabic language research. However, few studies have yet to directly apply SA to Arabic due to lack of a publicly available dataset for this language. This paper partially bridges this gap due to its focus on one of the Arabic dialects which is the Saudi dialect. This paper presents annotated data set of 4700 for Saudi dialect sentiment analysis with (K= 0.807). Our next work is to extend this corpus and creation a large-scale lexicon for Saudi dialect from the corpus.

Keywords: Arabic, sentiment analysis, Twitter, annotation

Procedia PDF Downloads 611

Authors: Ferdi Sönmez, Nihal Yorulmaz

Abstract:

Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: operator cost, bi-level optimization model, user cost, urban transportation

Procedia PDF Downloads 229

Authors: Konja Knüppel, Gerrit Meyer, Peter Nyhuis

Abstract:

The increasing interconnectedness and complexity of production processes raise the susceptibility of production systems to failure. Therefore, the ability to respond quickly to failures is increasingly becoming a competitive factor. The research project "Sustainable failure management in manufacturing SMEs" is developing a methodology to identify failures in the production and select preventive and reactive measures in order to correct failures and to establish sustainable failure management systems.

Keywords: failure categorization, failure management, logistic performance, production optimization

Procedia PDF Downloads 361

Authors: Sujit K. Basak

Abstract:

This paper presents a comparison of reference management software between RefWorks and Zotero. The results were drawn by comparing two software and the novelty of this paper is the comparative analysis of software and it has shown that ReftWorks can import more information from the Google Scholar for the researchers. This finding could help to know researchers to use the reference management software.

Keywords: analysis, comparative analysis, reference management software, researchers

Procedia PDF Downloads 527

Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

Abstract:

Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

Procedia PDF Downloads 212