Search results for: bus generalized cost

Authors: Rolando B. Llave Jr.

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In many countries, wheat flour is used an essential component in production/preparation of bread and other baked products considered to have a significant role in man’s diet. Partial replacement of wheat flour with other flours (composite flour) in preparation of the said products is seen as a solution to the scarcity of wheat flour (in non-wheat producing countries), and improved nourishment. In composite flour, other flours may come from cereals, legumes, root crops, and those that are rich in starch. Many countries utilize whatever is locally available. “Adlai” or Job’s tears is a tall cereal plant that belongs to the same family of grass as wheat, rice, and corn. In some countries, it is used as an ingredient in producing many dishes and alcoholic and non-alcoholic beverages. As part of the Food Staple Self-Sufficiency Program (FSSP) of the Department of Agriculture (DA) in the Philippines, “adlai” is being promoted as alternative food source for the Filipinos. In this study, the grits coming from the seeds of “adlai” were turned into flour. The resulting flour was then used as partial replacement for wheat flour in selected baked products namely “pan de sal” (salt bread), cupcakes and cookies. The supplementation of “adlai” flour ranged 20%-45% with 20%-35% for “pan de sal”; 30%-45% for cupcakes; and 25% - 40% for cookies. The study was composed of four (4) phases. Phase I was product formulation studies. Phase II included the acceptability test/sensory evaluation of the baked products where the statistical analysis of the data gathered followed. Phase III was the computation of the theoretical protein content of the most acceptable “pan de sal”, cupcake and cookie, and lastly, in Phase IV, cost benefit was analyzed, specifically in terms of the direct material cost.

Keywords: “adlai”, composite flour, supplementation, sensory evaluation

Procedia PDF Downloads 869

Authors: T. M. Tawfik, M. A. Badr, E. Y. El-Kady, O. E. Abdellatif

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Electric power shortage is a serious problem in remote rural communities in Egypt. Over the past few years, electrification of remote communities including efficient on-site energy resources utilization has achieved high progress. Remote communities usually fed from diesel generator (DG) networks because they need reliable energy and cheap fresh water. The main objective of this paper is to design an optimal economic power supply from hybrid standalone energy system (HSES) as alternative energy source. It covers energy requirements for reverse osmosis desalination unit (DU) located in National Research Centre farm in Noubarya, Egypt. The proposed system consists of PV panels, Wind Turbines (WT), Batteries, and DG as a backup for supplying DU load of 105.6 KWh/day rated power with 6.6 kW peak load operating 16 hours a day. Optimization of HSES objective is selecting the suitable size of each of the system components and control strategy that provide reliable, efficient, and cost-effective system using net present cost (NPC) as a criterion. The harmonization of different energy sources, energy storage, and load requirements are a difficult and challenging task. Thus, the performance of various available configurations is investigated economically and technically using iHOGA software that is based on genetic algorithm (GA). The achieved optimum configuration is further modified through optimizing the energy extracted from renewable sources. Effective minimization of energy charging the battery ensures that most of the generated energy directly supplies the demand, increasing the utilization of the generated energy.

Keywords: energy management, hybrid system, renewable energy, remote area, optimization

Procedia PDF Downloads 199

Authors: Desta Brhanu Gebrehiwot

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The study aims to investigate the impact of land tenure arrangements on fertilizer use per hectare in Northern Ethiopia. Household and Plot level data are used for analysis. Land tenure contracts such as sharecropping and fixed rent arrangements have endogeneity. Different unobservable characteristics may affect renting-out decisions. Thus, the appropriate method of analysis was the instrumental variable estimation technic. Therefore, the family of instrumental variable estimation methods two-stage least-squares regression (2SLS, the generalized method of moments (GMM), Limited information maximum likelihood (LIML), and instrumental variable Tobit (IV-Tobit) was used. Besides, a method to handle a binary endogenous variable is applied, which uses a two-step estimation. In the first step probit model includes instruments, and in the second step, maximum likelihood estimation (MLE) (“etregress” command in Stata 14) was used. There was lower fertilizer use per hectare on sharecropped and fixed rented plots relative to owner-operated. The result supports the Marshallian inefficiency principle in sharecropping. The difference in fertilizer use per hectare could be explained by a lack of incentivized detailed contract forms, such as giving more proportion of the output to the tenant under sharecropping contracts, which motivates to use of more fertilizer in rented plots to maximize the production because most sharecropping arrangements share output equally between tenants and landlords.

Keywords: tenure-contracts, endogeneity, plot-level data, Ethiopia, fertilizer

Procedia PDF Downloads 86

Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Luis F. Caballero-castro, Dirsa Feliciano, Daniela Novoa, Orlando Arroyo, Jesús D. Villalba-morales

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Colombia faces a critical challenge in seismic resilience due to the prevalence of informal housing, which constitutes approximately 70% of residential structures. More than 10 million Colombians (20% of the population), live in homes susceptible to collapse in the event of an earthquake. This, combined with the fact that 83% of the population is in intermediate and high seismic hazard areas, has brought serious consequences to the country. These consequences became evident during the 1999 Armenia earthquake, which affected nearly 100,000 properties and represented economic losses equivalent to 1.88% of that year's Gross Domestic Product (GDP). Despite previous efforts to reinforce informal housing through methods like externally reinforced masonry walls, alternatives related to seismic protection systems (SPDs), such as Buckling-Restrained Braces (BRB), have not yet been explored in the country. BRBs are reinforcement elements capable of withstanding both compression and tension, making them effective in enhancing the lateral stiffness of structures. In this study, the use of low-cost and easily installable BRBs for the retrofit of informal housing in Colombia was evaluated, considering the economic limitations of the communities. For this purpose, a case study was selected involving an informally constructed dwelling in the country, from which field information on its structural characteristics and construction materials was collected. Based on the gathered information, nonlinear models with and without BRBs were created, and their seismic performance was analyzed and compared through incremental static (pushover) and nonlinear dynamic analyses. In the first analysis, the capacity curve was identified, showcasing the sequence of failure events occurring from initial yielding to structural collapse. In the second case, the model underwent nonlinear dynamic analyses using a set of seismic records consistent with the country's seismic hazard. Based on the results, fragility curves were calculated to evaluate the probability of failure of the informal housings before and after the intervention with BRBs, providing essential information about their effectiveness in reducing seismic vulnerability. The results indicate that low-cost BRBs can significantly increase the capacity of informal housing to withstand earthquakes. The dynamic analysis revealed that retrofit structures experienced lower displacements and deformations, enhancing the safety of residents and the seismic performance of informally constructed houses. In other words, the use of low-cost BRBs in the retrofit of informal housing in Colombia is a promising strategy for improving structural safety in seismic-prone areas. This study emphasizes the importance of seeking affordable and practical solutions to address seismic risk in vulnerable communities in earthquake-prone regions in Colombia and serves as a model for addressing similar challenges of informal housing worldwide.

Keywords: buckling-restrained braces, fragility curves, informal housing, incremental dynamic analysis, seismic retrofit

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Authors: Gen Sakoda, Hideki Takayasu, Misako Takayasu

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Waste reduction is a fundamental problem for sustainability. Methods for waste reduction with point-of-sales (POS) data are proposed, utilizing the knowledge of a recent econophysics study on a statistical property of POS data. Concretely, the non-stationary time series analysis method based on the Particle Filter is developed, which considers abnormal fluctuation scaling known as Taylor's law. This method is extended for handling incomplete sales data because of stock-outs by introducing maximum likelihood estimation for censored data. The way for optimal stock determination with pricing the cost of waste reduction is also proposed. This study focuses on the examination of the methods for large sales numbers where Taylor's law is obvious. Numerical analysis using aggregated POS data shows the effectiveness of the methods to reduce food waste maintaining a high profit for large sales numbers. Moreover, the way of pricing the cost of waste reduction reveals that a small profit loss realizes substantial waste reduction, especially in the case that the proportionality constant  of Taylor’s law is small. Specifically, around 1% profit loss realizes half disposal at =0.12, which is the actual  value of processed food items used in this research. The methods provide practical and effective solutions for waste reduction keeping a high profit, especially with large sales numbers.

Keywords: food waste reduction, particle filter, point-of-sales, sustainable development goals, Taylor's law, time series analysis

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Authors: Yassir Abdelrazig, Ren Moses

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Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: gemoetric design, optimization, planning, roadway planning, roadway design

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Dinesh Kumar Sharma, Sanjay Sharma

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Textile manufacturing industry uses a substantial amount of chemicals not only in the production processes but also in manufacturing the raw materials. Dyes are the most significant raw material which provides colour to the fabric and yarn. Dyes are produced by using a large amount of chemicals both organic and inorganic in nature. Dyes are further classified as Reactive or Vat Dyes which are mostly used in cotton textiles. In the process of application of dyes to the cotton fiber, yarn or fabric, several auxiliary chemicals are also used in the solution called dyebath to improve the absorption of dyes. There is a very little absorption of dyes and auxiliary chemicals and a residual amount of all these substances is released as the spent dye bath effluent. Because of the wide variety of chemicals used in cotton textile dyes, there is always a risk of harmful effects which may not be apparent immediately but may have an irreversible impact in the long term. Colour imparted by the dyes to the water also has an adverse effect on its public acceptability and the potability. This study has been conducted with an objective to assess the feasibility of reuse of the spent dye bath. Studies have been conducted in two independent industries manufacturing dyed cotton yarn and dyed cotton fabric respectively. These have been referred as Unit-I and Unit-II. The studies included assessment of reduction in pollution levels and the economic benefits of such reuse. The study conclusively establishes that the reuse of spent dyebath results in prevention of pollution, reduction in pollution loads and cost of effluent treatment & production. This pollution prevention technique presents a good preposition for pollution prevention in cotton textile industry.

Keywords: dyes, dyebath, reuse, toxic, pollution, costs

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Authors: Tochukwu Timothy Okoli, Devi Datt Tewari

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The high rate of Fintech adoption has not transmitted to greater financial inclusion and development in Africa. This problem is attributed to poor Fintech diversification and usefulness in the continent. This concept is referred to as the Fintech depth of penetration in this study. The study, therefore, assessed its determinants and growth process in a panel of three emergings, twenty-four frontiers and five fragile African economies disaggregated with dummies over the period 2004-2018 to allow for heterogeneity between groups. The System Generalized Method of Moments (GMM) technique reveals that the average depth of Mobile banking and automated teller machine (ATM) is a dynamic heterogeneity process. Moreover, users' previous experiences/compatibility, trial-ability/income, and financial development were the major factors that raise its usefulness, whereas perceived risk, financial openness, and inflation rate significantly limit its usefulness. The growth rate of Mobile banking, ATM, and Internet banking in 2018 is, on average 41.82, 0.4, and 20.8 per cent respectively greater than its average rates in 2004. These greater averages after the 2009 financial crisis suggest that countries resort to Fintech as a risk-mitigating tool. This study, therefore, recommends greater Fintech diversification through improved literacy, institutional development, financial liberalization, and continuous innovation.

Keywords: depth of fintech, emerging Africa, financial technology, internet banking, mobile banking

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Authors: Mubarek Alpkiray, Tan Nguyen, Arild Saasen

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Geothermal drilling operations contain numerous challenges that are encountered to increase the well cost and nonproductive time. Fluid loss is one of the most undesirable troublesome that can cause well abandonment in geothermal drilling. Lost circulation can be seen due to natural fractures, high mud weight, and extremely high formation temperatures. This challenge may cause wellbore stability problems and lead to expensive drilling operations. Wellbore stability is the main domain that should be considered to mitigate or prevent fluid loss into the formation. This paper describes the causes of fluid loss in the Pamukoren geothermal field in Turkey. A geomechanics approach integration and assessment is applied to help the understanding of fluid loss problems. In geothermal drillings, geomechanics is primarily based on rock properties, in-situ stress characterization, the temperature of the rock, determination of stresses around the wellbore, and rock failure criteria. Since a high-temperature difference between the wellbore wall and drilling fluid is presented, temperature distribution through the wellbore is estimated and implemented to the wellbore stability approach. This study reviewed geothermal drilling data to analyze temperature estimation along the wellbore, the cause of fluid loss and stored electric capacity of the reservoir. Our observation demonstrates the geomechanical approach's significant role in understanding safe drilling operations on high-temperature wells. Fluid loss is encountered due to thermal stress effects around the borehole. This paper provides a wellbore stability analysis for a geothermal drilling operation to discuss the causes of lost circulation resulting in nonproductive time and cost.

Keywords: geothermal wells, drilling, wellbore stresses, drilling fluid loss, thermal stress

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Authors: Rene Hellmuth

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Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring of the factory building is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A building information model (BIM) is the planning basis for rebuilding measures and becomes an indispensable data repository to be able to react quickly to changes. Use as a planning basis for restructuring measures in factories only succeeds if the BIM model has adequate data quality. Under this aspect and the industrial requirement, three data quality factors are particularly important for this paper regarding the BIM model: up-to-dateness, completeness, and correctness. The research question is: how can a BIM model be kept up to date with required data quality and which visualization techniques can be applied in a short period of time on the construction site during conversion measures? An as-is analysis is made of how BIM models and digital factory models (including laser scans) are currently being kept up to date. Industrial companies are interviewed, and expert interviews are conducted. Subsequently, the results are evaluated, and a procedure conceived how cost-effective and timesaving updating processes can be carried out. The availability of low-cost hardware and the simplicity of the process are of importance to enable service personnel from facility mnagement to keep digital factory models (BIM models and laser scans) up to date. The approach includes the detection of changes to the building, the recording of the changing area, and the insertion into the overall digital twin. Finally, an overview of the possibilities for visualizations suitable for construction sites is compiled. An augmented reality application is created based on an updated BIM model of a factory and installed on a tablet. Conversion scenarios with costs and time expenditure are displayed. A user interface is designed in such a way that all relevant conversion information is available at a glance for the respective conversion scenario. A total of three essential research results are achieved: As-is analysis of current update processes for BIM models and laser scans, development of a time-saving and cost-effective update process and the conception and implementation of an augmented reality solution for BIM models suitable for construction sites.

Keywords: building information modeling, digital factory model, factory planning, restructuring

Procedia PDF Downloads 114

Authors: D. Mowla, N. Rasti, P. Keshavarz

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Reduction of fossil fuels sources, increasing of pollution gases emission, and global warming effects increase the demand of renewable fuels. One of the main candidates of alternative fuels is biodiesel. Biodiesel limits greenhouse gas effects due to the closed CO₂ cycle. Biodiesel has more biodegradability, lower combustion emissions such as CO, SO_x, HC, PM and lower toxicity than petro diesel. However, biodiesel has high production cost due to high price of plant oils as raw material. So, the utilization of waste cooking oils (WCOs) as feedstock, due to their low price and disposal problems reduce biodiesel production cost. In this study, production of biodiesel by transesterification of methanol and WCO using modified sodic potassic (SP) clinoptilolite zeolite and sodic potassic calcic (SPC) clinoptilolite zeolite as heterogeneous catalysts have been investigated. These natural clinoptilolite zeolites were modified by KOH solution to increase the site activity. The optimum biodiesel yields for SP clinoptilolite and SPC clinoptilolite were 95.8% and 94.8%, respectively. Produced biodiesel were analyzed and compared with petro diesel and ASTM limits. The properties of produced biodiesel confirm well with ASTM limits. The density, kinematic viscosity, cetane index, flash point, cloud point, and pour point of produced biodiesel were all higher than petro diesel but its acid value was lower than petro diesel. Finally, the reusability and regeneration of catalysts were investigated. The results indicated that the spent zeolites cannot be reused directly for the transesterification, but they can be regenerated easily and can obtain high activity.

Keywords: biodiesel, renewable fuel, transesterification, waste cooking oil

Procedia PDF Downloads 238

Authors: Vedansh More, Lalatendu Bal, Ronak Panchal, Atharva Kulkarni

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The project aims at developing a cost-effective test bench capable of testing and validating the complete powertrain package of an electric vehicle. Emrax 228 high voltage synchronous motor was selected as the prime mover for study. A tandem type dynamometer comprising of two loading methods; inertial, using standard inertia rollers and absorptive, using a separately excited DC generator with resistive coils was developed. The absorptive loading of the prime mover was achieved by implementing a converter circuit through which duty of the input field voltage level was controlled. This control was efficacious in changing the magnetic flux and hence the generated voltage which was ultimately dropped across resistive coils assembled in a load bank with all parallel configuration. The prime mover and loading elements were connected via a chain drive with a 2:1 reduction ratio which allows flexibility in placement of components and a relaxed rating of the DC generator. The development will aid in determination of essential characteristics like torque-RPM, power-RPM, torque factor, RPM factor, heat loads of devices and battery pack state of charge efficiency but also provides a significant financial advantage over existing versions of dynamometers with its cost-effective solution.

Keywords: absorptive load, chain drive, chordal action, DC generator, dynamometer, electric vehicle, inertia rollers, load bank, powertrain, pulse width modulation, reduction ratio, road load, testbench

Procedia PDF Downloads 232

Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras

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Cooperative intelligent transport systems (C-ITS) can greatly improve safety and efficiency in road transport by enabling communication, not only between vehicles themselves but also between vehicles and infrastructure. For that reason, traffic surveillance systems on the road are of great importance. This paper focuses on the development of an on-road unit comprising several magnetic sensors for real-time vehicle detection, movement direction, and speed measurement calculations. Magnetic sensors can feel and measure changes in the earth’s magnetic field. Vehicles are composed of many parts with ferromagnetic properties. Depending on sensors’ sensitivity, changes in the earth’s magnetic field caused by passing vehicles can be detected and analyzed in order to extract information on the properties of moving vehicles. In this paper, we present a prototype algorithm for real-time, high-accuracy, vehicle detection, and speed measurement, which can be implemented as a portable, low-cost, and non-invasive to existing infrastructure solution with the potential to replace existing high-cost implementations. The paper describes the algorithm and presents results from its preliminary lab testing in a close to real condition environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).

Keywords: magnetic sensors, vehicle detection, speed measurement, traffic surveillance system

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Authors: Yoshifumi Hino

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An infinitely repeated prisoner’s dilemma is a typical model that represents teamwork situation. If both players choose costly actions and contribute to the team, then both players are better off. However, each player has an incentive to choose a selfish action. We analyze the game under costly observation. Each player can observe the action of the opponent only when he pays an observation cost in that period. In reality, teamwork situations are often costly observation. Members of some teams sometimes work in distinct rooms, areas, or countries. In those cases, they have to spend their time and money to see other team members if they want to observe it. The costly observation assumption makes the cooperation difficult substantially because the equilibrium must satisfy the incentives not only on the action but also on the observational decision. Especially, it is the most difficult to cooperate each other when the stage-game is prisoner's dilemma because players have to communicate through only two actions. We examine whether or not players can cooperate each other in prisoner’s dilemma under costly observation. Specifically, we check whether symmetric Pareto efficient payoff vectors in repeated prisoner’s dilemma can be approximated by sequential equilibria or not (efficiency result). We show the efficiency result without any randomization device under certain circumstances. It means that players can cooperate with each other without any randomization device even if the observation is costly. Next, we assume that public randomization device is available, and then we show that any feasible and individual rational payoffs in prisoner’s dilemma can be approximated by sequential equilibria under a specific situation (folk theorem). It implies that players can achieve asymmetric teamwork like leadership situation when public randomization device is available.

Keywords: cost observation, efficiency, folk theorem, prisoner's dilemma, private monitoring, repeated games.

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

Procedia PDF Downloads 336

Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Wieland Hoppe, Nadine Wachter, Stefan Bringezu

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Carbon dioxide (CO2) utilization might be a promising way to substitute fossil raw materials like coal, oil or natural gas as carbon source of chemical production. While first life cycle assessments indicate a positive environmental performance of CO2-based process routes, a commercialization of CO2 is limited by several economic obstacles up to now. We, therefore, analyzed the economic performance of the three CO2-based chemicals methane and methanol as basic chemicals and polyoxymethylene as polymer on a cradle-to-gate basis. Our approach is oriented towards life cycle costing. The focus lies on the cost drivers of CO2-based technologies and options to stimulate a CO2-based economy by changing regulative factors. In this way, we analyze various modes of operation and give an outlook for the potentially cost-effective development in the next decades. Biogas, waste gases of a cement plant, and flue gases of a waste incineration plant are considered as CO2-sources. The energy needed to convert CO2 into hydrocarbons via electrolysis is assumed to be supplied by wind power, which is increasingly available in Germany. Economic data originates from both industrial processes and process simulations. The results indicate that CO2-based production technologies are not competitive with conventional production methods under present conditions. This is mainly due to high electricity generation costs and regulative factors like the German Renewable Energy Act (EEG). While the decrease in production costs of CO2-based chemicals might be limited in the next decades, a modification of relevant regulative factors could potentially promote an earlier commercialization.

Keywords: carbon capture and utilization (CCU), economic assessment, life cycle costing (LCC), power-to-X

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Authors: Kurniawan D. Irianto, Demetres D. Kouvatsos

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The growth of wireless devices affects the availability of limited frequencies or spectrum bands as it has been known that spectrum bands are a natural resource that cannot be added. Many studies about available spectrum have been done and it shows that licensed frequencies are idle most of the time. Cognitive radio is one of the solutions to solve those problems. Cognitive radio is a promising technology that allows the unlicensed users known as secondary users (SUs) to access licensed bands without making interference to licensed users or primary users (PUs). As cloud computing has become popular in recent years, cognitive radio networks (CRNs) can be integrated with cloud platform. One of the important issues in CRNs is security. It becomes a problem since CRNs use radio frequencies as a medium for transmitting and CRNs share the same issues with wireless communication systems. Another critical issue in CRNs is performance. Security has adverse effect to performance and there are trade-offs between them. The goal of this paper is to investigate the performance related to security trade-off in CRNs with supporting cloud platforms. Furthermore, Queuing Network Models with preemptive resume and preemptive repeat identical priority are applied in this project to measure the impact of security to performance in CRNs with or without cloud platform. The generalized exponential (GE) type distribution is used to reflect the bursty inter-arrival and service times at the servers. The results show that the best performance is obtained when security is disable and cloud platform is enable.

Keywords: performance vs. security, cognitive radio networks, cloud platforms, GE-type distribution

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Authors: Youssef El Makhrout, Aude Pommeret, Tunç Durmaz

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This paper analyses the consequences of a heat pump on the optimal behavior of a prosumer. A theoretical microeconomic model is developed for household heating and electricity consumption to analyze the profitability of installing a solar PV system with a heat pump, battery storage, and grid use. The aim is to present the optimal scenario of investment in renewable energy equipment to cover domestic and heating needs. Simulation data of a French house of 170m² in Chambery are used in this paper. The house is divided into 5 zones with 3 heated zones of 89.4 m² occupied by two people. The analysis is based on hourly data for one year, from 00:00 01/01/2021 to 23:00 31/12/2021. Results indicate that without taking the cost of materials and no financial aid, the most profitable scenario for a household is when he owns solar panels, a heat pump, and battery storage. However, with the costs and financial aid of the French government for energy renovation, the net economic surplus change and the profitability during 20 years are important when the household decides to add a heat pump to existing solar panels. In this scenario, the household can realize 35.84% as a surplus change improvement, but this cannot cover all installation costs. The household can get benefits and cover all installation costs after exploiting financial support in the case of adopting a heat pump. The investment in a battery is still not profitable because of its high cost and the lack of financial aid. Some public policy recommendations are proposed, especially for solar panels and battery storage.

Keywords: household’s heating, prosumer, electricity consumption, renewable energy, welfare gain, comfort, solar PV, heat pumps, storage

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Authors: Qijiao He

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MicroElectrical-Mechanical System (MEMS) is one of the most rapidly developing frontier research field both in theory study and applied technology. Micro-channel is a very important link component of MEMS. With the research and development of MEMS, the size of the micro-devices and the micro-channels becomes further smaller. Compared with the macroscale flow, the flow characteristics of gas in the micro-channel have changed, and the rarefaction effect appears obviously. However, for the rarefied gas and microscale flow, Navier-Stokes-Fourier (NSF) equations are no longer appropriate due to the breakup of the continuum hypothesis. A Nonlinear Coupled Constitutive Model (NCCM) has been derived from the Boltzmann equation to describe the characteristics of both continuum and rarefied gas flows. We apply the present scheme to simulate continuum and rarefied gas flows in a micro-channel structure. And for comparison, we apply other widely used methods which based on particle simulation or direct solution of distribution function, such as Direct simulation of Monte Carlo (DSMC), Unified Gas-Kinetic Scheme (UGKS) and Lattice Boltzmann Method (LBM), to simulate the flows. The results show that the present solution is in better agreement with the experimental data and the DSMC, UGKS and LBM results than the NSF results in rarefied cases but is in good agreement with the NSF results in continuum cases. And some characteristics of both continuum and rarefied gas flows are observed and analyzed.

Keywords: continuum and rarefied gas flows, discontinuous Galerkin method, generalized hydrodynamic equations, numerical simulation

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Authors: Clara Stella Anugerah

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This study actually is a reflection of the general election in 2014. The researcher was interested in this case as the assessment of several phenomenons that happened recently. One of them is the use of social media for the campaign. By this modern era, social media becomes closer with society. It gains the communication process, and by the time being communicating others also becomes easier than before. Furthermore, social media can minimize the cost of communication with many people as a far distance that often comes to be an obstacle of communication does not become a big problem anymore. In Indonesia, the advantages of social media were used by a political party, Gerindra, to face the election that was held on 2014. Actually Gerindra is a newly formed political party that was established in 2008. In spite of Gerindra is the new comer in the election, according to the General Election Committee’s data in Indonesia, Gerindra has the biggest budget than others to cost campaign in social media. Because of that, this research wants to look “how is the pattern of Gerindra party’s campaign to face the general election in 2014? To ask that question, the theory used for this research is campaign method based on ICT (Information Communication Technology) by Rummele. According to the rummele, Gerindra was a party that used a product of social media massively, mainly facebook and twitter. According to that observation, this research focus on campaign that had been done by Gerindra in both of those social media by the time window given by KPU (General Election Committee) on Maret 16th until April 5th, 2014. The conclusion was derived by content analysis method that was used in the methodology. In this context, that method was used while interpreting the content uploaded by Gerindra to facebook or twitter, such as picture and writing. Finally, by that method and reflecting the rummele theory, this research inferred that the patern used for Gerindra’s campaign in social media tends to be top-down. It means: Gerindra showed uncommunicative tendency in social media and only want to catch much mass without mentioned a mission and vision clearly.

Keywords: Gerindra party, political party, social media, campaign, general election on 2014

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Authors: Chengbin Wang, Li Lu, Luodan Suo, Qinghai Wang, Fan Yang, Xu Wang, Mona Marin

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Background: Two-dose varicella vaccination has been recommended in Beijing since November 2012. We investigated a varicella outbreak in a highly vaccinated elementary school population to examine transmission patterns and risk factors for vaccine failure. Methods: A varicella case was defined as an acute generalized maculopapulovesicular rash without other apparent cause in a student attending the school from March 28 to May 17, 2015. Breakthrough varicella was defined as varicella >42 days after last vaccine dose. Vaccination information was collected from immunization records. Information on prior disease and clinical presentation was collected via survey of students’ parents. Results: Of the 1056 school students, 1028 (97.3%) reported no varicella history, of whom 364 (35.4%) had received 1-dose and 650 (63.2%) had received 2-dose varicella vaccine, for 98.6% school-wide vaccination coverage with ≥ 1 dose before the outbreak. A total of 20 cases were identified for an overall attack rate of 1.9%. The index case was in a 2-dose vaccinated student who was not isolated. The majority of cases were breakthrough (19/20, 95%) with attack rates of 7.1% (1/14), 1.6% (6/364) and 2.0% (13/650) among unvaccinated, 1-dose, and 2-dose students, respectively. Most cases had < 50 lesions (18/20, 90%). No difference was found between 1-dose and 2-dose breakthrough cases in disease severity or sociodemographic factors. Conclusion: Moderate 2-dose varicella vaccine coverage was insufficient to prevent a varicella outbreak. Two-dose breakthrough varicella is still contagious. High 2-dose varicella vaccine coverage and timely isolation of ill persons might be needed for varicella outbreak control in the 2-dose era.

Keywords: varicella, outbreak, breakthrough varicella, vaccination

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Authors: Ana Lambelho

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In an economic crisis such as the one that shook (and still shake) Europe, one does not question the importance of the measures that encourage the hiring and integration of young people into the labour market. In the mentioned context, enterprises tend to reduce the cost of labour and to seek flexible contracting instruments. The professional internships allow innovation and creativity at low cost, because, as they are not labour contracts, the enterprises do not have to respect the minimum standards related to wages, working time duration and so on. In Portugal, we observe a widespread existence of training contracts in which the trainee worked several hours without salary or was paid below the legally prescribed for the function and the work period. For this reason, under the tripartite agreement for a new system of regulation of labour relations, employment policies and social protection, between the Government and the social partners, in June 2008, foresaw a prohibition of professional internships unpaid and the legal regulation of the mandatory internships for access to an activity. The first Act about private internship contracts, i.e., internships without public funding was embodied in the Decree-Law N. 66/2011, of 1^st June. This work is dedicated to the study of the legal regime of the internship contract in Portugal, by analysing the problems brought by the new set of rules and especially those which remains unresolved. In fact, we can conclude that the number of situations covered by the Act is much lower than what was expected, because of the exclusion of the mandatory internship for access to a profession when the activity is developed autonomously. Since the majority of the activities can be developed both autonomously or subordinated, it is quite easy to out of the Act requirements and, so, out of the protection that it confers to the intern. In order to complete this study, we considered not only the mentioned legal Act, but also the few doctrine and jurisprudence about the theme.

Keywords: intern, internship contact, labour law, Portugal

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Authors: Mohammadreza Vafaei, Amirali Moradi, Sophia C. Alih

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The method selected for the design of structures not only can affect their seismic vulnerability but also can affect their construction cost. For the design of steel structures, two distinct methods have been introduced by existing codes, namely allowable stress design (ASD) and load resistant factor design (LRFD). This study investigates the effect of using the aforementioned design methods on the seismic vulnerability and construction cost of steel structures. Specifically, a 20-story building equipped with special moment resisting frame and an eccentrically braced system was selected for this study. The building was designed for three different intensities of peak ground acceleration including 0.2 g, 0.25 g, and 0.3 g using the ASD and LRFD methods. The required sizes of beams, columns, and braces were obtained using response spectrum analysis. Then, the designed frames were subjected to nine natural earthquake records which were scaled to the designed response spectrum. For each frame, the base shear, story shears, and inter-story drifts were calculated and then were compared. Results indicated that the LRFD method led to a more economical design for the frames. In addition, the LRFD method resulted in lower base shears and larger inter-story drifts when compared with the ASD method. It was concluded that the application of the LRFD method not only reduced the weights of structural elements but also provided a higher safety margin against seismic actions when compared with the ASD method.

Keywords: allowable stress design, load resistant factor design, nonlinear time history analysis, seismic vulnerability, steel structures

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Authors: Rawan K. Al-Duaij, Salem A. Al-Salem

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Projects, the unique and temporary process of achieving a set of requirements have always been challenging; Planning the schedule and budget, managing the resources and risks are mostly driven by a similar past experience or the technical consultations of experts in the matter. With that complexity of Projects in Scope, Time, and execution environment, Adjustment Orders are tools to reflect changes to the original project parameters after Contract signature. Adjustment Orders are the official/legal amendments to the terms and conditions of a live Contract. Reasons for issuing Adjustment Orders arise from changes in Contract scope, technical requirement and specification resulting in scope addition, deletion, or alteration. It can be as well a combination of most of these parameters resulting in an increase or decrease in time and/or cost. Most business leaders (handling projects in the interest of the owner) refrain from using Adjustment Orders considering their main objectives of staying within budget and on schedule. Success in managing the changes results in uninterrupted execution and agreed project costs as well as schedule. Nevertheless, this is not always practically achievable. In this paper, a detailed study through utilizing Industrial Engineering & Systems Management tools such as Six Sigma, Data Analysis, and Quality Control were implemented on the organization’s five years records of the issued Adjustment Orders in order to investigate their prevalence, and time and cost impact. The analysis outcome revealed and helped to identify and categorize the predominant causations with the highest impacts, which were considered most in recommending the corrective measures to reach the objective of minimizing the Adjustment Orders impacts. Data analysis demonstrated no specific trend in the AO frequency in past five years; however, time impact is more than the cost impact. Although Adjustment Orders might never be avoidable; this analysis offers’ some insight to the procedural gaps, and where it is highly impacting the organization. Possible solutions are concluded such as improving project handling team’s coordination and communication, utilizing a blanket service contract, and modifying the projects gate system procedures to minimize the possibility of having similar struggles in future. Projects in the Oil and Gas sector are always evolving and demand a certain amount of flexibility to sustain the goals of the field. As it will be demonstrated, the uncertainty of project parameters, in adequate project definition, operational constraints and stringent procedures are main factors resulting in the need for Adjustment Orders and accordingly the recommendation will be to address that challenge.

Keywords: adjustment orders, data analysis, oil and gas sector, systems management

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Authors: Hongbo Zhang, Xinlu Tang, Jiangwei Li, Chi Yan

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Home zone parking pilot (HPP) is a fast-growing segment in low-speed autonomous driving applications. It requires the car automatically cruise around a parking lot and park itself in a range of up to 100 meters inside a recurrent home/office parking lot, which requires precise parking lot mapping and localization solution. Although Lidar is ideal for SLAM, the car OEMs favor a low-cost fish-eye camera based visual SLAM approach. Recent approaches have employed segmentation models to extract semantic features and improve mapping accuracy, but these AI models are memory unfriendly and computationally expensive, making deploying on embedded ADAS systems difficult. To address this issue, we proposed a new method that utilizes object detection models to extract robust and accurate parking lot features. The proposed method could reduce computational costs while maintaining high accuracy. Once combined with vehicles’ wheel-pulse information, the system could construct maps and locate the vehicle in real-time. This article will discuss in detail (1) the fish-eye based Around View Monitoring (AVM) with transparent chassis images as the inputs, (2) an Object Detection (OD) based feature point extraction algorithm to generate point cloud, (3) a low computational parking lot mapping algorithm and (4) the real-time localization algorithm. At last, we will demonstrate the experiment results with an embedded ADAS system installed on a real car in the underground parking lot.

Keywords: ADAS, home zone parking pilot, object detection, visual SLAM

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Andi Fallahi, Bona Ryan Situmeang

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The Construction Industry is notoriously risky. Much of the preparatory paperwork that precedes construction project can be viewed as the formulation of risk allocation between the owner and the Contractor. The Owner is taking the risk that his project will not get built on the schedule that it will not get built for what he has budgeted and that it will not be of the quality he expected. The Contractor Face a multitude of risk. One of them is an unforeseen condition at the construction site. The Owner usually has the upper hand here if the unforeseen condition occurred. Site data contained in Ground Investigation report is often of significant contractual importance in disputes related to the unforeseen ground condition. A ground investigation can never fully disclose all the details of the underground condition (Risk of an unknown ground condition can never be 100% eliminated). Adipala Coal Fired Steam Power Plant (CSFPP) 1 x 660 project is one of the large CSFPP project in Indonesia based on Engineering, Procurement, and Construction (EPC) Contract. Unforeseen Ground Condition it’s responsible by the Contractor has stipulated in the clausal of Contract. In the implementation, there’s indicated unforeseen ground condition at Circulating Water Pump House (CWPH) area which caused the Contractor should be changed the Method of Work that give big impact against Time of Completion and Cost Project. This paper tries to analyze the best way for allocating the risk between The Owner and The Contractor. All parties that allocating of sharing risk fairly can ultimately save time and money for all parties, and get the job done on schedule for the least overall cost.

Keywords: unforeseen ground condition, coal fired steam power plant, circulating water pump house, Indonesia

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