A MATHEMATICAL MODEL OF DEMAND MANAGEMENT FOR CARSHARING

A significant increase of carsharing service in Russia and worldwide has led to need a formal description of the process orders fulfilling on the service. The paper presents a mathematical model for computation the distance between customers and free car, which is built on the basis of the “nearest neighbor”method. A model of demand generation is proposed. The demand depends on the potential number of customers and the probability of finding a car in the area of walking distance. The number of free cars is described as stochastic process, which is based on a birth and death process. The death intensity in the process depends on the probability of finding a car. The estimation of the average number of free cars, their average load and the probability of finding a free car in the walking distance are obtained. The combination of the presented models allows to assess the impact of the number of carsharing vehicles on demand. In particular, a numerical example shows that an increase in the carsheribg fleet can lead to increaseasing in the cars average load. Thus, we can conclude that a larger car-sharing project can be cost-effective only if the carsharing service consists of a large fleet of vehicles, i.e. the service contains a high density of free cars.

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Modelling the number of customers as a birth and death process

European Journal of Finance ◽

10.1080/13518470802042021 ◽

2009 ◽

Vol 15 (2) ◽

pp. 105-118 ◽

Cited By ~ 3

Author(s):

Helena Pinto ◽

Sydney Howell ◽

Dean Paxson

Keyword(s):

Death Process ◽

Birth And Death Process ◽

Number Of Customers

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Telecommunication Traffic Unit and Traffic Mathematical Model

10.31227/osf.io/jf5ry ◽

2018 ◽

Author(s):

Sigit Haryadi

Keyword(s):

Mathematical Model ◽

Theoretical Model ◽

Poisson Process ◽

Point Process ◽

Point Processes ◽

Death Process ◽

Birth And Death Process

Here is described mathematical model of telecommunication traffic, that are about Traffic Unit, Theoretical Model of Telecommunication Traffic, Traffic Process, Traffic at Packet Level, Description of Point Processes, Characteristics of Point Process, Poisson Process, The concept of the Birth and Death Process, and Creating Mathematical Model of the Telecommunication Traffic.

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Modeling and analyzing users’ behavioral strategies with co-evolutionary process

Computational Social Networks ◽

10.1186/s40649-021-00092-1 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Yutaro Miura ◽

Fujio Toriumi ◽

Toshiharu Sugawara

Keyword(s):

Social Relationships ◽

Nearest Neighbor ◽

Evolutionary Process ◽

Cost Effective ◽

Experimental Simulation ◽

Behavioral Strategies ◽

Ego Networks ◽

The Individual ◽

Individual Strategies ◽

The Impact

AbstractSocial networking services (SNSs) are constantly used by a large number of people with various motivations and intentions depending on their social relationships and purposes, and thus, resulting in diverse strategies of posting/consuming content on SNSs. Therefore, it is important to understand the differences of the individual strategies depending on their network locations and surroundings. For this purpose, by using a game-theoretical model of users called agents and proposing a co-evolutionary algorithm called multiple-world genetic algorithm to evolve diverse strategy for each user, we investigated the differences in individual strategies and compared the results in artificial networks and those of the Facebook ego network. From our experiments, we found that agents did not select the free rider strategy, which means that just reading the articles and comments posted by other users, in the Facebook network, although this strategy is usually cost-effective and usually appeared in the artificial networks. We also found that the agents who mainly comment on posted articles/comments and rarely post their own articles appear in the Facebook network but do not appear in the connecting nearest-neighbor networks, although we think that this kind of user actually exists in real-world SNSs. Our experimental simulation also revealed that the number of friends was a crucial factor to identify users’ strategies on SNSs through the analysis of the impact of the differences in the reward for a comment on various ego networks.

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The extinction time of a general birth and death process with catastrophes

Journal of Applied Probability ◽

10.1017/s0021900200116031 ◽

1986 ◽

Vol 23 (04) ◽

pp. 851-858 ◽

Cited By ~ 1

Author(s):

P. J. Brockwell

Keyword(s):

Laplace Transform ◽

Size Distribution ◽

Sufficient Conditions ◽

Necessary And Sufficient Conditions ◽

Death Process ◽

Extinction Time ◽

Birth And Death Process ◽

Different Types ◽

The Laplace Transform ◽

Necessary And Sufficient

The Laplace transform of the extinction time is determined for a general birth and death process with arbitrary catastrophe rate and catastrophe size distribution. It is assumed only that the birth rates satisfyλ0= 0,λj> 0 for eachj> 0, and. Necessary and sufficient conditions for certain extinction of the population are derived. The results are applied to the linear birth and death process (λj=jλ, µj=jμ) with catastrophes of several different types.

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Regulatory and sustainability initiatives lead to improved polyaminopolyamide epichlorohydrin (PAE) wet-strength resins and paper products

TAPPI Journal ◽

10.32964/tj17.09.519 ◽

2018 ◽

Vol 17 (09) ◽

pp. 519-532 ◽

Cited By ~ 1

Author(s):

Mark Crisp ◽

Richard Riehle

Keyword(s):

Health And Safety ◽

Cost Effective ◽

Worker Safety ◽

Regulatory Requirements ◽

Wet Strength ◽

The Past ◽

Consumer Safety ◽

Federal Institute ◽

Sustainability Initiatives ◽

The Impact

Polyaminopolyamide-epichlorohydrin (PAE) resins are the predominant commercial products used to manufacture wet-strengthened paper products for grades requiring wet-strength permanence. Since their development in the late 1950s, the first generation (G1) resins have proven to be one of the most cost-effective technologies available to provide wet strength to paper. Throughout the past three decades, regulatory directives and sustainability initiatives from various organizations have driven the development of cleaner and safer PAE resins and paper products. Early efforts in this area focused on improving worker safety and reducing the impact of PAE resins on the environment. These efforts led to the development of resins containing significantly reduced levels of 1,3-dichloro-2-propanol (1,3-DCP) and 3-monochloropropane-1,2-diol (3-MCPD), potentially carcinogenic byproducts formed during the manufacturing process of PAE resins. As the levels of these byproducts decreased, the environmental, health, and safety (EH&S) profile of PAE resins and paper products improved. Recent initiatives from major retailers are focusing on product ingredient transparency and quality, thus encouraging the development of safer product formulations while maintaining performance. PAE resin research over the past 20 years has been directed toward regulatory requirements to improve consumer safety and minimize exposure to potentially carcinogenic materials found in various paper products. One of the best known regulatory requirements is the recommendations of the German Federal Institute for Risk Assessment (BfR), which defines the levels of 1,3-DCP and 3-MCPD that can be extracted by water from various food contact grades of paper. These criteria led to the development of third generation (G3) products that contain very low levels of 1,3-DCP (typically <10 parts per million in the as-received/delivered resin). This paper outlines the PAE resin chemical contributors to adsorbable organic halogens and 3-MCPD in paper and provides recommendations for the use of each PAE resin product generation (G1, G1.5, G2, G2.5, and G3).

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The Impact of Light Polarisation on Light Field of Scenes with Multiple Reflections

Light & Engineering ◽

10.33383/2019-023 ◽

2020 ◽

pp. 108-115 ◽

Cited By ~ 1

Author(s):

Vladimir P. Budak ◽

Anton V. Grimaylo

Keyword(s):

Mathematical Model ◽

Light Field ◽

Global Illumination ◽

Multiple Reflections ◽

Software Environment ◽

The Monte Carlo Method ◽

Mueller Matrices ◽

Volume Integration ◽

The Impact

The article describes the role of polarisation in calculation of multiple reflections. A mathematical model of multiple reflections based on the Stokes vector for beam description and Mueller matrices for description of surface properties is presented. On the basis of this model, the global illumination equation is generalised for the polarisation case and is resolved into volume integration. This allows us to obtain an expression for the Monte Carlo method local estimates and to use them for evaluation of light distribution in the scene with consideration of polarisation. The obtained mathematical model was implemented in the software environment using the example of a scene with its surfaces having both diffuse and regular components of reflection. The results presented in the article show that the calculation difference may reach 30 % when polarisation is taken into consideration as compared to standard modelling.

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Urban pollution control strategy: SBR technology to treat agricultural waste from pig farm in Indonesia

Sains & Teknologi ◽

10.24123/jst.v2i2.2250 ◽

2019 ◽

Vol 2 (2) ◽

pp. 21

Author(s):

Lindawati Lindawati

Keyword(s):

Cost Estimation ◽

Batch Reactor ◽

Agricultural Waste ◽

Cost Effective ◽

Land Application ◽

Pig Manure ◽

Small Scale ◽

Piggery Wastewater ◽

Pig Farm ◽

Number Of Customers

Reduction of food rations and shortages is one of the impacts of the increasing human population. Food sector industries then try to cope with the fast growing number of customers. Agribusiness sector gains its popularity in these recent years, including pig farm. The increase trend of animal farming industry is likely to bring increasing pollution problem unless effective treatment methods are used. The main problems related to the pig farm include odor nuisance and pig manure disposal. The existing land application of piggery wastewater is the traditional way to discharge the wastewater. This may yield in land and water contamination, due to the accumulation of unused nutrients by crop plant. A case study of a large commercial pig farm from Australia is proposed to apply in smaller scale in Indonesia. Operational strategies for the small-scale SBR (Sequencing Batch Reactor) treating piggery effluent were developed based on lab-scale experiments. Due to SBR characteristics, which are money-saving and space-saving, it is very suitable to be applied in urban area. An economic evaluation was made of various process options. The cost estimation showed that SBR is a cost effective process, allowing operational batches to be adjusted to reduce unnecessary aeration cost. A reduction in the aeration cost was achieved by shortening the batch time from 24-h to 8-h. A comparison of three different SBR options showed that smaller size reactors could be more flexible and cost effective when compared with the larger ones.

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Exploring the Benefits of Early Contractor Involvement (ECI) and the Mechanism for Automated 5D BIM Quantification Process in Offsite Modular Construction

Modular and Offsite Construction (MOC) Summit Proceedings ◽

10.29173/mocs6 ◽

2016 ◽

Author(s):

Tochukwu Moses ◽

David Heesom ◽

David Oloke ◽

Martin Crouch

Keyword(s):

Effective Means ◽

Cost Effective ◽

Modular Construction ◽

Automated Quantification ◽

Building Information ◽

Project Risks ◽

Value Add ◽

The Uk ◽

The Impact ◽

Level 2

The UK Construction Industry through its Government Construction Strategy has recently been mandated to implement Level 2 Building Information Modelling (BIM) on public sector projects. This move, along with other initiatives is key to driving a requirement for 25% cost reduction (establishing the most cost-effective means) on. Other key deliverables within the strategy include reduction in overall project time, early contractor involvement, improved sustainability and enhanced product quality. Collaboration and integrated project delivery is central to the level 2 implementation strategy yet the key protocols or standards relative to cost within BIM processes is not well defined. As offsite construction becomes more prolific within the UK construction sector, this construction approach coupled with BIM, particularly 5D automated quantification process, and early contractor involvement provides significant opportunities for the sector to meet government targets. Early contractor involvement is supported by both the industry and the successive Governments as a credible means to avoid and manage project risks, encourage innovation and value add, making cost and project time predictable, and improving outcomes. The contractor is seen as an expert in construction and could be counter intuitive to exclude such valuable expertise from the pre-construction phase especially with the BIM intent of äóÖbuild it twiceäó», once virtually and once physically. In particular when offsite construction is used, the contractoräó»s construction expertise should be leveraged for the virtual build in BIM-designed projects to ensure a fully streamlined process. Building in a layer of automated costing through 5D BIM will bring about a more robust method of quantification and can help to deliver the 25% reduction in overall cost of a project. Using a literature review and a case study, this paper will look into the benefits of Early Contractor Involvement (ECI) and the impact of 5D BIM on the offsite construction process.

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Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

Current Drug Targets ◽

10.2174/1389450119666180809122244 ◽

2019 ◽

Vol 20 (5) ◽

pp. 488-500 ◽

Cited By ~ 6

Author(s):

Yan Hu ◽

Yi Lu ◽

Shuo Wang ◽

Mengying Zhang ◽

Xiaosheng Qu ◽

...

Keyword(s):

Machine Learning ◽

Drug Design ◽

Anticancer Drugs ◽

Nearest Neighbor ◽

Cost Effective ◽

Support Vector ◽

Learning Approaches ◽

K Nearest Neighbor ◽

Activity Prediction ◽

Linear Discriminant

Background: Globally the number of cancer patients and deaths are continuing to increase yearly, and cancer has, therefore, become one of the world's highest causes of morbidity and mortality. In recent years, the study of anticancer drugs has become one of the most popular medical topics. Objective: In this review, in order to study the application of machine learning in predicting anticancer drugs activity, some machine learning approaches such as Linear Discriminant Analysis (LDA), Principal components analysis (PCA), Support Vector Machine (SVM), Random forest (RF), k-Nearest Neighbor (kNN), and Naïve Bayes (NB) were selected, and the examples of their applications in anticancer drugs design are listed. Results: Machine learning contributes a lot to anticancer drugs design and helps researchers by saving time and is cost effective. However, it can only be an assisting tool for drug design. Conclusion: This paper introduces the application of machine learning approaches in anticancer drug design. Many examples of success in identification and prediction in the area of anticancer drugs activity prediction are discussed, and the anticancer drugs research is still in active progress. Moreover, the merits of some web servers related to anticancer drugs are mentioned.

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Analyzing the Impact of Healthy Behavior on Weight Change with a Provable Mathematical Model (Preprint)

10.2196/preprints.25201 ◽

2020 ◽

Author(s):

Ayan Chatterjee ◽

Ram Bajpai ◽

Pankaj Khatiwada

Keyword(s):

Physical Activity ◽

Mathematical Model ◽

Health Behavior ◽

Weight Change ◽

Simulated Data ◽

Negative Behavior ◽

Healthy Behavior ◽

Healthy Habits ◽

Lifestyle Diseases ◽

The Impact

BACKGROUND Lifestyle diseases are the primary cause of death worldwide. The gradual growth of negative behavior in humans due to physical inactivity, unhealthy habit, and improper nutrition expedites lifestyle diseases. In this study, we develop a mathematical model to analyze the impact of regular physical activity, healthy habits, and a proper diet on weight change, targeting obesity as a case study. Followed by, we design an algorithm for the verification of the proposed mathematical model with simulated data of artificial participants. OBJECTIVE This study intends to analyze the effect of healthy behavior (physical activity, healthy habits, and proper dietary pattern) on weight change with a proposed mathematical model and its verification with an algorithm where personalized habits are designed to change dynamically based on the rule. METHODS We developed a weight-change mathematical model as a function of activity, habit, and nutrition with the first law of thermodynamics, basal metabolic rate (BMR), total daily energy expenditure (TDEE), and body-mass-index (BMI) to establish a relationship between health behavior and weight change. Followed by, we verified the model with simulated data. RESULTS The proposed provable mathematical model showed a strong relationship between health behavior and weight change. We verified the mathematical model with the proposed algorithm using simulated data following the necessary constraints. The adoption of BMR and TDEE calculation following Harris-Benedict’s equation has increased the model's accuracy under defined settings. CONCLUSIONS This study helped us understand the impact of healthy behavior on obesity and overweight with numeric implications and the importance of adopting a healthy lifestyle abstaining from negative behavior change.

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