scholarly journals Development Cycle Modeling: Transdisciplinary Implications

2021 ◽  
Vol 12 ◽  
Author(s):  
Samuel Denard
Keyword(s):  
New Product ◽  
Holistic View ◽  
Agent Based ◽  
Development Path ◽  
Development Cycle ◽  
Proposed Model ◽  
Quantitative Development ◽  
Development Phases ◽  
Product Creation ◽  
Form Development

This paper argues that development (product, system, software, etc.) is an inherently transdisciplinary activity. Development is defined as the conversion of ideas into their manifestations. This conversion is often characterized by development phases, e.g., concept, requirements, design, implementation, and evaluation/testing (CRDIE). Iterative sequences of these phases form development cycles. Development cycles drive new product creation as well as product quality and cost and utility. Consequently, understanding development cycles is important. Models can provide insight; however, end-to-end quantitative development cycle models are, at best, rare. This paper outlines such a model, the Statistical Agent-based Model of Development and Evaluation (SAbMDE). For purposes of this paper, transdisciplinarity is defined as a developer’s holistic view of reality as filtered by that developer’s sensory input and perception of that reality. The model builds its mathematical and logical structures on a foundational concept that includes and describes this sensory and perceptual integration. Because the proposed model has this transdisciplinary characteristic, the model's use and results will have transdisciplinary implications. One implication: Ideas are discovered, not created. Another: A developer must first adjust their perception to see the development path that leads to a desired end product before they can traverse that path. A third: The ordering of information in a development space must be maintained.. This paper defines a minimal SAbMDE model that logically and mathematically reveals these and other SAbMDE transdisciplinarity implications.

scholarly journals A Novel Crowdsourcing Model for Micro-Mobility Ride-Sharing Systems

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4636
Author(s):  
Mohammed Elhenawy ◽  
Mostafizur R. Komol ◽  
Mahmoud Masoud ◽  
Shiqiang Liu ◽  
Huthaifa I. Ashqar ◽  
...  
Keyword(s):  
User Needs ◽  
Computational Results ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Ride Sharing ◽  
Proposed Model ◽  
Micro Mobility

Substantial research is required to ensure that micro-mobility ride sharing provides a better fulfilment of user needs. This study proposes a novel crowdsourcing model for the ride-sharing system where light vehicles such as scooters and bikes are crowdsourced. The proposed model is expected to solve the problem of charging and maintaining a large number of light vehicles where these efforts will be the responsibility of the crowd of suppliers. The proposed model consists of three entities: suppliers, customers, and a management party responsible for receiving, renting, booking, and demand matching with offered resources. It can allow suppliers to define the location of their private e-scooters/e-bikes and the period of time they are available for rent. Using a dataset of over 9 million e-scooter trips in Austin, Texas, we ran an agent-based simulation six times using three maximum battery ranges (i.e., 35, 45, and 60 km) and different numbers of e-scooters (e.g., 50 and 100) at each origin. Computational results show that the proposed model is promising and might be advantageous to shift the charging and maintenance efforts to a crowd of suppliers.

scholarly journals A strategy learning model for autonomous agents based on classification

2015 ◽  
Vol 25 (3) ◽  
pp. 471-482 ◽  
Author(s):  
Bartłomiej Śnieżyński
Keyword(s):  
Reinforcement Learning ◽  
Supervised Learning ◽  
Learning Process ◽  
Autonomous Agents ◽  
Good Alternative ◽  
Learning Model ◽  
Learning Method ◽  
Complex Environments ◽  
Agent Based ◽  
Proposed Model

AbstractIn this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

scholarly journals Agent Based Load Balancing in Grid Computing

2020 ◽  
Author(s):  
Wided Ali ◽  
Fatima Bouakkaz
Keyword(s):  
Load Balancing ◽  
Heterogeneous Systems ◽  
Agent Based ◽  
Selection Policy ◽  
Development Framework ◽  
Policy Selection ◽  
Proposed Model ◽  
Multi Agent ◽  
Location Policy ◽  
System Characteristics

Load-Balancing is an important problem in distributed heterogeneous systems. In this paper, an Agent-based load-balancing model is developed for implementation in a grid environment. Load balancing is realized via migration of worker agents from overloaded resources to underloaded ones. The proposed model purposes to take benefit of the multi-agent system characteristics to create an autonomous system. The Agent-based load balancing model is implemented using JADE (Java Agent Development Framework) and Alea 2 as a grid simulator. The use of MAS is discussed, concerning the solutions adopted for gathering information policy, location policy, selection policy, worker agents migration, and load balancing.

scholarly journals Formal and Informal Communication in New Product Development Teams: The Mediation Effect of Team Trust

2018 ◽  
Vol 6 (2) ◽  
pp. 97-111
Author(s):  
Volkan Polat ◽  
Gary Lynn ◽  
Ali Akgün ◽  
Onur Emre
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Innovation Management ◽  
New Product ◽  
Project Managers ◽  
Mediation Effect ◽  
Informal Communication ◽  
Holistic View ◽  
New Product Development Teams ◽  
Team Trust

New product development (NPD) projects are costly, and fragile against failures as compared to other structures. This study has a holistic view of team factors to examine their relationship with team communication. Communication contributes to technical and practical processes such as learning, new idea development, and creativity. Trust has become prominent by affecting outcomes and processes indirectly, and changing relationships within team. This paper attempted to offer a contribution to the technology and innovation management (TIM) literature by presenting a model for researchers and project managers to understand potential interrelationships among team level factors (team autonomy, stability, member experience, and empowerment), team trust, and team formal and informal communication in NPD teams.

Estimating good design attributes from generalized drivers to provide early assistance to design requirements analysis

2017 ◽  
Vol 15 (03) ◽  
pp. 317-340 ◽  
Author(s):  
Lei Zhao ◽  
Theodor Freiheit
Keyword(s):  
New Product ◽  
Requirements Analysis ◽  
Relative Importance ◽  
Attribute Importance ◽  
Content Type ◽  
Good Design ◽  
Good Product ◽  
Development Cycle ◽  
Design Attributes ◽  
Design Requirements

Purpose This paper aims to examine the perceptions of good design attributes and propose a model to estimate their relative importance through fundamental drivers. Design activities must understand and meet customer and producer expectations and deliver products in a profitable manner. Requirements analysis is conducted to understand customer expectations, but in new product development, this information can be available too late in the development cycle. Moreover, customer needs are often unclear to designers at early stages of design, with customers often unable to articulate their requirements or unaware of how a new product may solve problems or create complications. Evaluating non-product-specific drivers to generalized good product design attributes can help designers estimate important factors in early requirements analysis. Design/methodology/approach Quantification of the weight designers place in their mental models of what makes up a good product is determined from linear regression modeling, providing a more concrete evaluation of inherently subjective perceptions. A survey is deployed using Mechanical TurkTM to collect perceptions of good product attributes and drivers through product case studies. Data are analyzed using a utility theory framework and importance of attributes is estimated from the importance of drivers. Findings A generalized model that estimates good design attributes from drivers is presented. This study also demonstrates that non-product-specific attribute importance can be extracted from specific product cases. An application example demonstrating the relative importance of good design attributes is given for different types of watches. Research limitations/implications The approach is intended to supplement ordinary product design and development processes, and is not intended to replace market research and concept testing activities. Model coefficient weights are dependent on the quality of the data that was collected, which has limitations. While the current study included confounding variables, introducing interactions into the model could make attribute importance prediction more accurate. Practical implications While design requirements analysis is now central to modern design practice, these estimates can be available too late in the development cycle, especially when customers have no experience with the product type. The developed model quantifies design attributes that consumers, manufacturers and society as a whole use to distinguish if a product will be considered well designed. Product designers can better focus their development resources toward good design attributes based on guidance generated from generalized drivers. Originality/value Historically, requirements analysis is undertaken specific to the product being designed. This paper provides a model to give designers early guidance in a non-product-specific framework. The framework also considers good design attributes as holistic, including societal and producer concerns. Although all of the proposed good design attributes can be associated with a well-engineered product, it is unnecessary to design a product that performs exceptionally on every attribute. This model provides identification of the handful of attributes that can make the most significant difference for design success.

Adaptive Ensemble Multi-Agent Based Intrusion Detection Model

2010 ◽  
pp. 36-48 ◽  
Author(s):  
Tarek Helmy
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Machine Learning Algorithms ◽  
Agent Based ◽  
Detection Model ◽  
Detection Analysis ◽  
Proposed Model ◽  
Multi Agent

The system that monitors the events occurring in a computer system or a network and analyzes the events for sign of intrusions is known as intrusion detection system. The performance of the intrusion detection system can be improved by combing anomaly and misuse analysis. This chapter proposes an ensemble multi-agent-based intrusion detection model. The proposed model combines anomaly, misuse, and host-based detection analysis. The agents in the proposed model use rules to check for intrusions, and adopt machine learning algorithms to recognize unknown actions, to update or create new rules automatically. Each agent in the proposed model encapsulates a specific classification technique, and gives its belief about any packet event in the network. These agents collaborate to determine the decision about any event, have the ability to generalize, and to detect novel attacks. Empirical results indicate that the proposed model is efficient, and outperforms other intrusion detection models.

Simulating E-business Innovation Process Improvement with Virtual Teams Across Europe and Asia

2011 ◽  
pp. 1023-1043
Author(s):  
Kenneth D. Strang ◽  
Cliff E.L. Chan
Keyword(s):  
Virtual Teams ◽  
New Product Development ◽  
Quality Function Deployment ◽  
Phase 1 ◽  
Innovation Process ◽  
New Product ◽  
Geographically Dispersed ◽  
Proposed Model ◽  
The Voice

In this article, E-business new product development innovation processes were studied at four enterprises across Europe and Asia. E-entrepreneurship innovation was improved using a quality of idea priority model. The conventional quality function deployment phase 1 matrix was revised to increase the voice of customers and engineer quality of idea decision-making. The proposed model was simulated with geographically dispersed virtual teams (based on production data). Statistical analyses were applied to test the hypothesis that an improved innovation process could better discriminate between new product return on investment pass or fail probability.

A Proposed Model of an Intelligent Software Agent for Marketing Education (ISAME)

2021 ◽  
pp. 529-537
Author(s):  
Hussein Moselhy Sayed Ahmed
Keyword(s):  
Software Agent ◽  
Interactive Software ◽  
Initial Test ◽  
Training And Education ◽  
Agent Based ◽  
Marketing Education ◽  
Education Resources ◽  
Intelligent Software ◽  
Proposed Model ◽  
Digital Environments

The purpose of this article is to illustrate the advantages of intelligent software agent technologies in order to facilitate the location and customization of appropriate marketing education resources, as well as to foster collaboration between individuals within digital environments. In order to do this, this article discusses how such intelligent and interactive software can translate into a better educational environment for marketing curriculum, particularly e-marketing courses. The authors present a conceptual model for managing marketing training and education using intelligent software agent, based on extant literature. So, this article presents some initial test of the proposed model of ISAME usage in marketing education in e-marketing class.

Simulating E-business Innovation Process Improvement with Virtual Teams Across Europe and Asia

2010 ◽  
Vol 1 (1) ◽  
pp. 22-41 ◽  
Author(s):  
Kenneth D. Strang ◽  
Cliff E.L. Chan
Keyword(s):  
Virtual Teams ◽  
New Product Development ◽  
Quality Function Deployment ◽  
Phase 1 ◽  
Innovation Process ◽  
New Product ◽  
Geographically Dispersed ◽  
Proposed Model ◽  
The Voice

In this article, E-business new product development innovation processes were studied at four enterprises across Europe and Asia. E-entrepreneurship innovation was improved using a quality of idea priority model. The conventional quality function deployment phase 1 matrix was revised to increase the voice of customers and engineer quality of idea decision-making. The proposed model was simulated with geographically dispersed virtual teams (based on production data). Statistical analyses were applied to test the hypothesis that an improved innovation process could better discriminate between new product return on investment pass or fail probability.

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