Search results for: offline programming

Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

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We consider a linear programming model to help farmers to decide if it is convinient to choose among three kinds of export fruits for their future investment. We consider area, investment, water, productivitiy minimal unit, and harvest restrictions and a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability and initia investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market.

Keywords: mixed integer problem, fruit production, support decision model, fruit tree farms

Procedia PDF Downloads 457

Authors: Ovanes Chakoyan

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MOH (mineral oil hydrocarbons), which consist of mineral oil saturated hydrocarbons(MOSH) and mineral oil aromatic hydrocarbons(MOAH), are present in various products such as vegetable oils, animal feed, foods, and infant formula. Contamination of foods with mineral oil hydrocarbons, particularly mineral oil aromatic hydrocarbons(MOAH), exhibiting carcinogenic, mutagenic, and hormone-disruptive effects. Identifying toxic substances among the many thousands comprising mineral oils in food samples is a difficult analytical challenge. A method based on an offline-solid phase extraction approach coupled with gas chromatography-triple quadrupole(GC-MS/MS) was developed for the determination of MOSH/MOAH in various products such as vegetable oils, animal feed, foods, and infant formula. A glass solid phase extraction cartridge loaded with 7 g of activated silica gel impregnated with 10 % silver nitrate for removal of olefins and lipids. The MOSH/MOAH fractions were eluated with hexane and hexane: dichloromethane : toluene, respectively. Each eluate was concentrated to 50 µl in toluene and injected on splitless mode into GC-MS/MS. Accuracy of the method was estimated as measurement of recovery of spiked oil samples at 2.0, 15.0, and 30.0 mg kg -1, and recoveries varied from 85 to 105 %. The method was applied to the different types of samples (sunflower meal, chocolate ships, santa milk chocolate, biscuits, infant milk, cornflakes, refined sunflower oil, crude sunflower oil), detecting MOSH up to 56 mg/kg and MOAH up to 5 mg/kg. The limit of quantification(LOQ) of the proposed method was estimated at 0.5 mg/kg and 0.3 mg/kg for MOSH and MOAH, respectively.

Keywords: MOSH, MOAH, GC-MS/MS, foods, solid phase extraction

Procedia PDF Downloads 88

Authors: J. Fernandez de Canete, P. Del Saz Orozco, I. Garcia-Moral, A. Akhrymenka

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Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Keywords: object-oriented programming, activated sludge process, OpenModelica, feedback control

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Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

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Authors: A. S. Walkey, N. P. Patidar

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It is not always economical to provide reactive power using synchronous alternators. The cost of reactive power can be minimized by optimal placing of FACTS devices in power systems. In this paper a Particle Swarm Optimization- Sequential Quadratic Programming (PSO-SQP) algorithm is applied to minimize the cost of reactive power generation along with real power generation to alleviate the bus voltage violations. The effectiveness of proposed approach tested on IEEE-14 bus systems. In this paper in addition to synchronous generators, an opportunity of FACTS devices are also proposed to procure the reactive power demands in the power system.

Keywords: reactive power, reactive power cost, voltage security margins, capability curve, FACTS devices

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Authors: Ferenc Kovács, Gábor Hosszú

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The paper presents an advanced control system for tennis ball throwing machines to improve their accuracy according to the ball impact points. A further advantage of the system is the much easier calibration process involving the intelligent solution of the automatic adjustment of the stroking parameters according to the ball elasticity, the self-calibration, the use of the safety margin at very flat strokes and the possibility to placing the machine to any position of the half court. The system applies mathematical methods to determine the exact ball trajectories and special approximating processes to access all points on the aimed half court.

Keywords: control system, robot programming, robot control, sports equipment, throwing machine

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Authors: Khosrow Maleknejad, Asyieh Ebrahimzadeh

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In this paper, the numerical solution of optimal control problem (OCP) for systems governed by Volterra integro-differential (VID) equation is considered. The method is developed by means of the Legendre wavelet approximation and collocation method. The properties of Legendre wavelet accompany with Gaussian integration method are utilized to reduce the problem to the solution of nonlinear programming one. Some numerical examples are given to confirm the accuracy and ease of implementation of the method.

Keywords: collocation method, Legendre wavelet, optimal control, Volterra integro-differential equation

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Authors: S. S. Sathiesh

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The aim of this project is to study the radiation mechanism synchrotron and Inverse Compton scattering. Theoretically, we discussed spectral energy distribution for both. Programming is done for plotting the graph of Power-law spectrum for synchrotron Radiation using fortran90. The importance of power law spectrum was discussed and studied to infer its physical parameters from the model fitting. We also discussed how to infer the physical parameters from the theoretically drawn graph, we have seen how one can infer B (magnetic field of the source), γ min, γ max, spectral indices (p1, p2) while fitting the curve to the observed data.

Keywords: blazars/quasars, beaming, synchrotron radiation, Synchrotron Self Compton, inverse Compton scattering, mrk421

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Authors: M. Omer, D. Wilson

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Creating a database scheme is essentially a manual process. From a requirement specification, the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time-consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that the first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore, this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: information extraction, natural language processing, relation extraction

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of project scheduling and material ordering can provide more flexibility to the project scheduling problem, as the project execution costs can be enhanced. Hence, the issue has been taken into account in this paper. To do so, a mixed-integer mathematical model is developed which considers the aforementioned flexibility, in addition to the materials quantity discount and space availability restrictions. Moreover, the activities duration has been treated as decision variables. Finally, the efficiency of the proposed model is tested by different instances. Additionally, the influence of the aforementioned parameters is investigated on the model performance.

Keywords: material ordering, project scheduling, quantity discount, space availability

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Authors: Jagoda Bruni, Jan Müller-Lucanus, Gernot Stöger-Knes

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The purpose of this article is to demonstrate modern project management approaches in the SAP S/R Hana surrounding a programming environment composed of multiple focus-diversified projects. We would like to propose innovative and goal-oriented management standards based on the specificity of the SAP transformations and customer-driven expectations. Due to the regular sprint-based controlling and management tools' application, it has been data-proven that extensive analysis of productive hours of the employees as much as a thorough review of the project progress (per GAP, per business process, and per Lot) within the whole program, can have a positive impact on customer satisfaction and improvement for projects' budget. This has been a collaborative study based on real-life experience and measurements in collaboration with our customers.

Keywords: project management, program management, SAP, controlling

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Authors: Sana Ansari, Sirus Mohammadi

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In distribution systems, shunt capacitors are used to reduce power losses, to improve voltage profile, and to increase the maximum flow through cables and transformers. This paper presents a new method to determine the optimal locations and economical sizing of fixed and/or switched shunt capacitors with a view to power losses reduction and voltage stability enhancement. General Algebraic Modeling System (GAMS) has been used to solve the maximization modules using the MINOS optimization software with Linear Programming (LP). The proposed method is tested on 33 node distribution system and the results show that the algorithm suitable for practical implementation on real systems with any size.

Keywords: power losses, voltage stability, radial distribution systems, capacitor

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Authors: Nikita Rajendra Sharma, Jai Prakash Kushvah, Gerhard Rinkenauer

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Driving a car is a discrete aiming movement in which drivers aim at successful extraction of relevant information and elimination of potentially distracting one. It is the motor preparation which enables one to react to certain stimuli onsite by allowing perceptual process for optimal adjustment. Drivers prepare their responses according to the available resources of advanced and ongoing information to drive efficiently. It requires constant programming and reprogramming of the motor system. The reaction time (RT) is shorter when a response signal is preceded by a warning signal. The reason behind this reduced time in responding to targets is that the warning signal causes the participant to prepare for the upcoming response by updating the motor program before the execution. While performing the primary task of changing lanes while driving, the simultaneous occurrence of additional information during the presentation of cues (congruent or incongruent with respect to target cue) might impact the motor preparation and execution. The presence of additional information (other than warning or response signal) between warning signal and imperative stimulus influences human motor preparation to a reasonable extent. The present study was aimed to assess the impact of congruent and incongruent additional information (with respect to imperative stimulus) on driving performance (reaction time, steering wheel amplitude, and steering wheel duration) during a lane change task. implementing movement pre-cueing paradigm. 22 young valid car-drivers (Mage = 24.1+/- 3.21 years, M = 10, F = 12, age-range 21-33 years) participated in the study. The study revealed that additional information influenced the overall driving performance as potential distractors and relevant information. Findings suggest that the events of additional information relatively influenced the reaction time and steering wheel angle as potential distractor or irrelevant information. Participants took longer to respond, and higher steering wheel angles were reported for targets coupled with additional information in comparison with warning signs preceded by potential distractors and the participants' response time was more for a higher number of lanes (2 Lanes > 1 Lane). The same additional information appearing interchangeably at warning signals and targets worked as relevant information facilitating the motor programming in the trails where they were congruent with the direction of lane change direction.

Keywords: additional information, lane change task, motor preparation, movement pre-cueing, reaction time, steering wheel amplitude

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Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: Kwan Hee Han, Jun Woo Lee, Sung Moon Bae, Twae Kyung Park

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ECA (Event-Condition-Action) languages are largely adopted for event processing since they are an intuitive and powerful paradigm for programming reactive systems. However, there are some limitations about ECA rules for processing of complex events such as coupling of event producer and consumer. The objective of this paper is to propose an ECA rule pattern to improve the current limitations of ECA rule, and to develop a prototype system. In this paper, conventional ECA rule is separated into 3 parts and each part is extended to meet the requirements of CEP. Finally, event processing logic is established by combining the relevant elements of 3 parts. The usability of proposed extended ECA rule is validated by a test scenario in this study.

Keywords: complex event processing, ECA rule, Event processing system, event-driven architecture, internet of things

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Authors: Jelena Vucicevic

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Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. This paper will try to introduce another way of calculating reliability by using R statistical software. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. The R programming environment is a widely used open source system for statistical analysis and statistical programming. It includes thousands of functions for the implementation of both standard and new statistical methods. R does not limit user only to operation related only to these functions. This program has many benefits over other similar programs: it is free and, as an open source, constantly updated; it has built-in help system; the R language is easy to extend with user-written functions. The significance of the work is calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. Seventy generators were studied. For each one, the number of hours of running time from its first being put into service until fan failure or until the end of the study (whichever came first) was recorded. Dataset consists of two variables: hours and status. Hours show the time of each fan working and status shows the event: 1- failed, 0- censored data. Censored data represent cases when we cannot track the specific case, so it could fail or success. Gaining the result by using R was easy and quick. The program will take into consideration censored data and include this into the results. This is not so easy in hand calculation. For the purpose of the paper results from R program have been compared to hand calculations in two different cases: censored data taken as a failure and censored data taken as a success. In all three cases, results are significantly different. If user decides to use the R for further calculations, it will give more precise results with work on censored data than the hand calculation.

Keywords: censored data, R statistical software, reliability analysis, time to failure

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Authors: I. Khutsishvili, G. Sirbiladze, B. Ghvaberidze

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This work proposes a fuzzy methodology to support the investment decisions. While choosing among competitive investment projects, the methodology makes ranking of projects using the new aggregation OWA operator – AsPOWA, presented in the environment of possibility uncertainty. For numerical evaluation of the weighting vector associated with the AsPOWA operator the mathematical programming problem is constructed. On the basis of the AsPOWA operator the projects’ group ranking maximum criteria is constructed. The methodology also allows making the most profitable investments into several of the project using the method developed by the authors for discrete possibilistic bicriteria problems. The article provides an example of the investment decision-making that explains the work of the proposed methodology.

Keywords: expert evaluations, investment decision making, OWA operator, possibility uncertainty

Procedia PDF Downloads 558

Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB", "ANSYS FLUENT", "XFoil" package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi-objective problems can be helpful for future developments. Also we developed method for Stability Analysis (Lateral-Directional and Longitudinal).

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, longitudinal stability, lateral-directional stability

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Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

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Authors: Noor Hasmini Abdghani, Nik Kamariah Nikmat, Nor Hayati Ahmad

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Rapid growth of the internet technology led to changes in the consumer lifestyles. This involved customer buying behaviour-based internet that create new kind of buying strategy. Hence, it has summoned many of world firms including Malaysia to generate new quality strategy in preparation to face new customer buying lifestyles. Particularly, this study focused on identifying online customer segment of automobile passenger car customers. Secondly, the objective is to understand online customer’s receptiveness towards internet technologies. This study distributed 700 questionnaires whereby 582 were returned representing 83% response rate. The data were analysed using factor and regression analyses. The result from the factor analysis precipitates four online passenger car segmentations in Malaysia, which are: Segment (1)- Automobile Online shopping Preferences, Segment (2)- Automobile Online Brand Comparison, Segment (3)- Automobile Online Information Seeking and Segment (4)- Automobile Offline Shopping Preferences. In understanding the online customer’s receptiveness towards internet, the regression result shows that there is significant relationship between each of four segments of online passenger car customer with attitude towards automobile online shopping. This implies that, for online customers to have receptiveness toward internet technologies, he or she must have preferences toward online shopping or at least prefer to browse any related information online even if the actual purchase is made at the traditional store. With this proposed segmentation strategy, the firms especially the automobile firms will be able to understand their online customer behavior. At least, the proposed segmentation strategy will help the firms to strategize quality management approach for their online customers’ buying decision making.

Keywords: Automobile, Market Segmentation, Online Shopping Attitude, Quality Management Strategy

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Michaela Kaineder, Beate Bartlmae, Stefan Gaebler, Miriam Gutleder, Marlene Wuerfl

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Digital tools and e-participation processes have seen a steady increase in popularity in recent years. While online trends come with the premise of new opportunities and easier participatory possibilities, there are still manifold challenges that smart city initiators and developers need to face. In this paper, innovative quality criteria of citizen participation processes was suggested by defining meaningful and measurable evaluation categories. Considering various developments, including the global megatrend of connectivity, a need for a fundamental examination of the basic structure of citizen participation processes was identified. To this end, the application of methods and tools through different points in the policy cycle is required. In order to provide an overview of the current challenges and problems in the field of participation, this paper analyzes those issues by carrying out a literature review that also focuses on disparities in the civic sector that might hinder residents in their desire for engagement. Additionally, a case study was chosen to demonstrate the potential that e-participation tools offer to planning experts and public authorities when integrating citizen’s creativity and experience at a large scale. This online co-creation process finally leads to offline events – such as local co-design workshops - with professional planners. The findings of this paper subsequently suggest a combination of e-participation and analogue forms to merge the benefits of both worlds, resulting in a broader audience and higher quality for participation processes.

Keywords: citizen participation, disparities, e-participation, integrated urban development, sustainable development goals, sustainable urban development

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Authors: Pin-Ling Yin, Dung-Ying Lin

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Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

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Authors: Ioana Pisica, Dimitrios Gkritzapis

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The significance of UAS in scientific applications has been amply demonstrated in recent years. The combinations of portability and quasi-static positioning by means of flying in close loop path make them versatile and efficient in the inspection of power systems infrastructure. In this paper, we critically assess several platforms and sensor capabilities to identify their pros and cons in relation to the power systems assets to be monitored. In this respect, it is paramount the flights to be conducted by using UAS which bear certain suitable features, such as responsive and easy control, video capturing in real time, autonomous routing of pre-planned flight programming with differentiating payloads. The outcome of this research is a set of optimal requirements for power system assets monitoring with UAS.

Keywords: platforms, power system, sensors, UAVs

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Authors: Yang-Kuei Lin, Yin-Yi Chou

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In this research, we have considered operating room scheduling problem. The objective is to minimize total operating cost. The total operating cost includes idle cost and overtime cost. We have proposed a dispatching rule that can guarantee to find feasible solutions for the studied problem efficiently. We compared the proposed dispatching rule with the optimal solutions found by solving Inter Programming, and other solutions found by using modified existing dispatching rules. The computational results indicates that the proposed heuristic can find near optimal solutions efficiently.

Keywords: assignment, dispatching rule, operation rooms, scheduling

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Authors: H. R. Kamali, A. Sadegheih, M. A. Vahdat-Zad, H. Khademi-Zare

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In this paper, a single product, multi-echelon, multi-period closed loop supply chain is surveyed, including a variety of costs, time conditions, and capacities, to plan and determine the values and time of the components procurement, production, distribution, recycling and disposal specially for high-tech products that undergo a decreasing production cost and sale price over time. For this purpose, the mathematic model of the problem that is a kind of mixed integer linear programming is presented, and it is finally proved that the problem belongs to the category of NP-hard problems.

Keywords: closed loop supply chain, continuous price decrease, NP-hard, planning

Procedia PDF Downloads 364

Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: capacity-booking, SPA, monthly production planning, linear programming

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Authors: M. Chen, S-Q. Zhang, X. Wang, D. Tate

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This paper presents a numerical solution, namely limit and shakedown analysis, to predict the safety state of smart structures made of heterogeneous materials under unknown cyclic loadings, for instance, the flexure hinge in the micro-positioning stage driven by piezoelectric actuator. In combination of homogenization theory and finite-element method (FEM), the safety evaluation problem is converted to a large-scale nonlinear optimization programming for an acceptable bounded loading as the design reference. Furthermore, a general numerical scheme integrated with the FEM and interior-point-algorithm based optimization tool is developed, which makes the practical application possible.

Keywords: limit state, shakedown analysis, homogenization, heterogeneous structure

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Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

Abstract:

Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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