Search results for: demand model

Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

Procedia PDF Downloads 183

Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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In today’s business, it is well-recognized that risk is an important factor that needs to be taken into consideration before a decision is made. Studies indicate that both the number of risks faced by organizations and their potential consequences are growing. Supply chain risk management has become one of the major concerns for practitioners and researchers. Supply chain leaders and scholars are now focusing on the importance of managing supply chain risk. In order to meet the challenge of managing and mitigating supply chain risk (SCR), we must first identify the different dimensions of SCR and assess its relevant probability and severity. SCR has been classified in many different ways, and there are no consistently accepted dimensions of SCRs and several different classifications are reported in the literature. Basically, supply chain risks can be classified into two dimensions namely disruption risk and operational risk. Disruption risks are those caused by events such as bankruptcy, natural disasters and terrorist attack. Operational risks are related to supply and demand coordination and uncertainty, such as uncertain demand and uncertain supply. Disruption risks are rare but severe and hard to manage, while operational risk can be reduced through effective SCM activities. Other SCRs include supply risk, process risk, demand risk and technology risk. In fact, the disorganized classification of SCR has created confusion for SCR scholars. Moreover, practitioners need to identify and assess SCR. As such, it is important to have an overarching framework tying all these SCR dimensions together for two reasons. First, it helps researchers use these terms for communication of ideas based on the same concept. Second, a shared understanding of the SCR dimensions will support the researchers to focus on the more important research objective: operationalization of SCR, which is very important for assessing SCR. In general, fresh food supply chain is subject to certain level of risks, such as supply risk (low quality, delivery failure, hot weather etc.) and demand risk (season food imbalance, new competitors). Effective strategies to mitigate fresh food supply chain risk are required to enhance operations. Before implementing effective mitigation strategies, we need to identify the risk sources and evaluate the risk level. However, assessing the supply chain risk is not an easy matter, and existing research mainly use qualitative method, such as risk assessment matrix. To address the relevant issues, this paper aims to analyze the risk factor of the fresh food supply chain using an approach comprising both fuzzy logic and hierarchical holographic modeling techniques. This novel approach is able to take advantage the benefits of both of these well-known techniques and at the same time offset their drawbacks in certain aspects. In order to develop this integrated approach, substantial research work is needed to effectively combine these two techniques in a seamless way, To validate the proposed integrated approach, a case study in a fresh food supply chain company was conducted to verify the feasibility of its functionality in a real environment.

Keywords: fresh food supply chain, fuzzy logic, hierarchical holographic modelling, operationalization, supply chain risk

Procedia PDF Downloads 242

Authors: M. C. Venter, G. Hitge, S. C. Krygsman, J. Thiart

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For decades, South Africa has been planning transportation systems from a supply, rather than a demand side, perspective. In terms of parking, this relates to requiring the minimum parking provision that is enforced by city officials. Newer insight is starting to indicate that South Africa needs to re-think this philosophy in light of a new policy environment that desires a different outcome. Urban policies have shifted from reliance on the private car for access, to employing a wide range of alternative modes. Car dominated travel is influenced by various parameters, of which the availability and location of parking plays a significant role. The question is therefore, what is the right strategy to achieve the desired transport outcomes for SA. The focus of this paper is used to assess this issue with regard to parking provision, and specifically at a tertiary institution. A parking audit was conducted at the Stellenbosch campus of Stellenbosch University, monitoring occupancy at all 60 parking areas, every hour during business hours over a five-day period. The data from this survey was compared with the prescribed number of parking bays according to the Stellenbosch Municipality zoning scheme (requiring a minimum of 0.4 bays per student). The analysis shows that by providing 0.09 bays per student, the maximum total daily occupation of all the parking areas did not exceed an 80% occupation rate. It is concluded that the prevailing parking standards are not supportive of the new urban and transport policy environment, but that it is extremely conservative from a practical demand point of view.

Keywords: parking provision, parking requirements, travel behaviour, travel demand management

Procedia PDF Downloads 180

Authors: Peter Shi

Abstract:

Algorithmic trading is a rapidly expanding domain within quantitative finance, constituting a substantial portion of trading volumes in the US financial market. The demand for rigorous and robust mathematical theories underpinning these trading algorithms is ever-growing. In this study, the author establishes a new stock market model that integrates the Efficient Market Hypothesis and the statistical arbitrage. The model, for the first time, finds probabilistic relations between the rational price and the market price in terms of the conditional expectation. The theory consequently leads to a mathematical justification of the old market adage: buy-low and sell-high. The thresholds for “low” and “high” are precisely derived using a max-min operation on Bayes’s error. This explicit connection harmonizes the Efficient Market Hypothesis and Statistical Arbitrage, demonstrating their compatibility in explaining market dynamics. The amalgamation represents a pioneering contribution to quantitative finance. The study culminates in comprehensive numerical tests using historical market data, affirming that the “buy-low” and “sell-high” algorithm derived from this theory significantly outperforms the general market over the long term in four out of six distinct market environments.

Keywords: efficient market hypothesis, behavioral finance, Bayes' decision, algorithmic trading, risk control, stock market

Procedia PDF Downloads 72

Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

Procedia PDF Downloads 429

Authors: Addisu H. Addis, Hugh T. Blair, Paul R. Kenyon, Stephen T. Morris, Nicola M. Schreurs, Dorian J. Garrick

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Agent-based modeling (ABM) enables an in silico representation of complex systems and cap-tures agent behavior resulting from interaction with other agents and their environment. This study developed an ABM to represent a pasture-based beef cattle finishing systems in New Zea-land (NZ) using attributes of the rearer, finisher, and processor, as well as specific attributes of dairy-origin beef cattle. The model was parameterized using values representing 1% of NZ dairy-origin cattle, and 10% of rearers and finishers in NZ. The cattle agent consisted of 32% Holstein-Friesian, 50% Holstein-Friesian–Jersey crossbred, and 8% Jersey, with the remainder being other breeds. Rearers and finishers repetitively and simultaneously interacted to determine the type and number of cattle populating the finishing system. Rearers brought in four-day-old spring-born calves and reared them until 60 calves (representing a full truck load) on average had a live weight of 100 kg before selling them on to finishers. Finishers mainly attained weaners from rearers, or directly from dairy farmers when weaner demand was higher than the supply from rearers. Fast-growing cattle were sent for slaughter before the second winter, and the re-mainder were sent before their third winter. The model finished a higher number of bulls than heifers and steers, although it was 4% lower than the industry reported value. Holstein-Friesian and Holstein-Friesian–Jersey-crossbred cattle dominated the dairy-origin beef finishing system. Jersey cattle account for less than 5% of total processed beef cattle. Further studies to include re-tailer and consumer perspectives and other decision alternatives for finishing farms would im-prove the applicability of the model for decision-making processes.

Keywords: agent-based modelling, dairy cattle, beef finishing, rearers, finishers

Procedia PDF Downloads 99

Authors: G. E. Kiral, O. Elma, A. T. Ince, B. Vural, U. S. Selamogullari, M. Uzunoglu

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Energy is an indispensable resource to meet the needs of people. Depending on the needs of people, the correct and efficient use of electrical energy has became important nowadays. Besides the need for the electrical energy is also increasing with the rapidly developing technology and continuously changing living standards. Due to the depletion of energy sources and increased demand for electricity, efficient energy use is an important research topic. Recently, ideas like smart cities, smart buildings and smart homes have been widely used under smart grid concept. With smart grid infrastructure, it will be possible to monitor electrical demand of a residential customer and control each electricity generation center for more efficient energy flow. The smallest component of the smart grid can be considered as smart homes. Better utilization of the electrical grid can be achieved through the communication of the smart home with both other customers in the grid and appliances in the house itself since generation can effectively be scheduled by having more precise demand data. Smart Plugs are used for the communication with the household appliances in the house. Smart Plug is an intermediate control element, which can be mounted on the existing outlet, and thus can be used to monitor the energy consumption of the plugged device and also can provide on/off control energy remotely. This study proposes a Smart Plug for energy monitoring and energy management. Proposed design is composed of five subsystems: micro controller embedded system with communication system, metering circuitry, power supply and switching circuitry. The developed smart plug offers efficient use of electrical energy.

Keywords: energy efficiency, home energy management, smart home, smart plug

Procedia PDF Downloads 727

Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

Procedia PDF Downloads 157

Authors: Brahmia Nadjet

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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems (such as GIS, RDBMS), so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

Procedia PDF Downloads 502

Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

Procedia PDF Downloads 416

Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

Procedia PDF Downloads 228

Authors: Jolanta Tamošaitienė

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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

Procedia PDF Downloads 255

Authors: Iyagbaye O. Rich, Omoigberale O. Michael, Iyagbaye A. Louis

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The physical, chemical parameters and some trace contents of Ugbogui in Edo State, Nigeria were investigated from August 2015 to April 2016. Four stations were studied from upstream to downstream using standard methods. A total of thirty-three (33) physical and chemical characteristics and trace metal contents were examined; Air and water temperatures, depth, transparency, colour, turbidity, flow velocity, pH, total alkalinity, conductivity and dissolved solids etc. Other includes dissolved oxygen, oxygen saturation, biochemical oxygen demand, chloride, phosphate, sodium, nitrate, sulphate, potassium, calcium, magnesium, iron, lead, copper, zinc, nickel, cadmium, vanadium and chromium. Eleven (11) parameters exhibited clear seasonal variations. However, there were high significant differences (p < 0.01) in the values of depth, colour, total suspended solid, biochemical oxygen demand, chemical oxygen demand, chloride, bicarbonate, phosphate, sulphate, iron, manganese, zinc, copper, chromium and cadmium among the stations. The anthropogenic activities had negatively impacted at station 3 of the river, although most of the recorded values were still within permissible limits.

Keywords: anthropogenic activities, Nigeria, permissible limits, physical and chemical parameters, trace metal, water quality

Procedia PDF Downloads 126

Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: cache system, formal verification, novel model, system on chip (SoC)

Procedia PDF Downloads 496

Authors: Owamah Hilary, O. C. Izinyon

Abstract:

Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

Procedia PDF Downloads 429

Authors: Mawardati Mawardati

Abstract:

This research was carried out on the traditional milkfish and shrimp culture cultivation from March to May 2018 in East Aceh District. This study aims to to analyze the differences between traditional milkfish cultivation and shrimp farming in East Aceh District, Aceh Province. The analytical method used is acquisition analysis and Independent Sample T test analysis. The results showed a significant difference between milkfish farming and shrimp farming in East Aceh District, Aceh Province. Based on the results of the analysis, the average profit from shrimp farming is higher than that of milkfish farming. This demand exceeds market demand for exports. Thus the price of shrimp is still far higher than the price of milk fish.

Keywords: comparative, profit, shrimp, milkfish

Procedia PDF Downloads 153

Authors: Chui Ka Shing

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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

Procedia PDF Downloads 219

Authors: Nadjet Brahmia

Abstract:

The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transportation (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems (such as GIS, RDBMS…), so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

Procedia PDF Downloads 557

Authors: Ian McCulloh, Andrew Placona, Darren Stewart, Daniel Gause, Kevin Kiernan, Morgan Stuart, Christopher Zinner, Laura Cartwright

Abstract:

An estimated 22-25% of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. As many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist.

Keywords: decision science, KDPI, optimism bias, organ transplant

Procedia PDF Downloads 105

Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

Procedia PDF Downloads 575

Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: R. Ramesh, K. K. Shivaraman

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The main aim of this paper is to handle the energy requirement in an efficient manner by merging the advanced digital communication and control technologies for smart grid applications. In order to reduce user home load during peak load hours, utility applies several incentives such as real-time pricing, time of use, demand response for residential customer through smart meter. However, this method provides inconvenience in the sense that user needs to respond manually to prices that vary in real time. To overcome these inconvenience, this paper proposes a convolutional neural network (CNN) with k-means clustering machine learning model which have ability to forecast energy requirement in short term, i.e., hour of the day or day of the week. By integrating our proposed technique with home energy management based on Bluetooth low energy provides predicted value to user for scheduling appliance in advanced. This paper describes detail about CNN configuration and k-means clustering algorithm for short-term energy forecasting.

Keywords: convolutional neural network, fuzzy logic, k-means clustering approach, smart home energy management

Procedia PDF Downloads 305

Authors: Dimitra Alexiou

Abstract:

In an urban area the allocation placement of an emergency service mobile units, such as ambulances, police patrol must be designed so as to achieve a prompt response to demand locations. In this paper, a partition of a given urban network into distinct sub-networks is performed such that; the vertices in each component are close and simultaneously the difference of the sums of the corresponding population in the sub-networks is almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in the framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.

Keywords: graph partition, emergency service, distances, location

Procedia PDF Downloads 499

Authors: Claudia Munoz, Henry Laniado

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In this research, the impact of outbound and return flight schedule preferences on airline choice for international trips is quantified. Several studies have used airline choice data to identify preferences and trade-offs of different air carrier service attributes, such as travel time, fare and frequencies. However, estimation of the effect return flight schedules have on airline choice for an international round-trip flight has not yet been studied in detail. The multinomial logit model found shows that airfare, travel time, arrival preference schedule in the outward journey, departure preference in the return journey and the schedule combination of round-trip flights are significantly affecting passenger choice behavior in international round-trip flights. it results indicated that return flight schedule preference plays a substantial role in air carrier choice and has a similar effect to outbound flight schedule preference. Thus, this study provides an analytical tool designed to provide a better understanding of international round-trip flight demand determinants and support carrier decisions.

Keywords: flight schedule, airline choice, return flight, passenger choice behavior

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the newly developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: demand forecasting, machine learning, risk management, supply chain design

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

Procedia PDF Downloads 485

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

Procedia PDF Downloads 88

Authors: T. Sahbani, M. Bouteraa, R. Wamkeue

Abstract:

Wind Turbine are considered to be one of the more efficient system of energy production nowadays, a reason that leads the main industrial companies in wind turbine construction and researchers in over the world to look for better performance and one of the ways for that is the use of the synchronous permanent magnet generator. In this context, this work is about developing an analytical model that could simulate different situation in which the synchronous generator may go through, and of course this model match perfectly with the numerical and experimental model.

Keywords: MATLAB, synchronous permanent magnet generator, wind turbine, analytical model

Procedia PDF Downloads 549

Authors: T. Yuri M. Zagloel, Inaki M. Hakim, Syarafi A. M.

Abstract:

Manufacturing process has been considered as one of the most important activity in business process. It correlates with productivity and quality of the product so industries could fulfill customer’s demand. With the increasing demand from customer, industries must improve their manufacturing ability such as shorten lead time and reduce wastes on their process. Lean manufacturing has been considered as one of the tools to waste elimination in manufacturing or service industri. Workforce development is one practice in lean manufacturing that can reduce waste generated from operator such as waste of unnecessary motion. Anthropometric approach is proposed to determine the recommended measurement in operator’s work area. The method will get some dimensions from Indonesia people that related to piston workstation. The result from this research can be obtained new design for the workarea considering ergonomic aspect.

Keywords: adjustable, anthropometric, ergonomic, waste

Procedia PDF Downloads 400

Authors: Hussain Ali Bekhet, Tuan Ab. Rashid Bin Tuan Abdullah, Tahira Yasmin

Abstract:

The strong relationship between energy consumption and economic growth is widely recognised. Most countries’ energy demand declined during the economic depression known as the Global Financial Crisis (GFC) of 2008–2009. The objective of the current study is to investigate the energy consumption and performance of Malaysia’s manufacturing sectors during the GFC. We applied the output multiplier approach, which is based on the input-output model. Two input-output tables of Malaysia covering 2005 and 2010 were used. The results indicate significant changes in the output multipliers of the manufacturing sectors between 2005 and 2010. Moreover, the energy-to-manufacturing sectors’ output multipliers also decreased during the GFC due to a decline in export-oriented industries during the crisis. The increasing importance of the manufacturing sector to the development of Malaysian trade resulted in a noticeable decrease in the consumption of each energy sector’s output, especially the electricity and gas sector. Based on the research findings, the Malaysian government released several policy implementations in the form of stimulus packages to enhance these sectors’ performance and generally improve the Malaysian economy.

Keywords: global financial crisis, input-output model, manufacturing, output multipliers, energy, Malaysia

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