Architectural Decisions Research Articles

An Overview of Decision-Making in Autonomous Vehicles

In this review we have surveyed the literature on the autonomous vehicle focusing on the decision-making architecture. The main contribution of this paper is to provide an up-to-date reference that tries to cover as much as possible this broad topic rapidly. Therefore, after analyzing the body of literature, we were able to present a detailed overview of the usual anatomy of the decision-making system, review the coverage of public reviews and surveys available around the topic, present the environment and vehicle representation, and showcase the literature through: trajectory planning, risk-uncertainty assessment, and mimicking human behaviour mainly using perception-based methods. We also classified the literature according to scenarios covered, action-space used, and whether or not they emphasize the time horizon or frequency or time-step.

Enabling Business Analytics in SMEs: The Trivi Open-source System

The purpose of this project is to propose an open-source system, called the Trivi system, for enabling business analytics in small and medium-sized enterprises (SMEs). The paper presents the key activities of the project development, including problem identification and motivation, objective definition, design and development, demonstration, and evaluation. The project’s main outcomes are a knowledge development process, a set of use cases related to business analytics techniques in SMEs, and a general architecture for business analytics systems. Moreover, a four-level service architecture (data, information, analytics, and decision services) of the Trivi system is proposed, and a case study about the first validation for the cultural sector is presented.

FIRMWARE AND HARDWARE DEVELOPMENT OF AN Educational PROGRAMMABLE LOGIC CONTROLLER

This paper describes a novel PLC system that integrates cutting-edge hardware and software components, offering an immersive and interactive educational experience. The design, features, and benefits of the newly developed PLC are detailed, highlighting its potential to empower learners in various educational settings. Moreover, the cost-effectiveness of architectural decisions is also highlighted, with the end goal being to create e PLC that is both relevant to industry standards and affordable for universities and higher education schools.

Challenges In Optimizing Migration Costs From On-Premises To Microsoft Azure

The current paper analyzes the feasibility of a modular web application's migration procedure from on-premises to the cloud. Our focus is on identifying cost savings and options for hosting the application in the cloud. The research specifically examines the impact of architectural decisions records (ADR) on a modular monolith use case, utilizing .NET Core for the backend and Angular for the front end, with Clean Architecture as the design pattern.We investigate different cloud models (IaaS, PaaS, Serverless) considering project management's triple constraints (time, cost, performance). The study demonstrates that a modular monolith can be migrated with varying effort and costs depending on the chosen cloud model and technology stack. We explore optimizations such as resource utilization, licensing fees, and cost reduction through infrastructure reservations. Our findings show that the migration cost can range from a 20% increase with IaaS to approximately 70% cost reduction with the Serverless strategy compared to the on-premises environment, using equivalent resources.We also explore methods to lower expenses for each model, including resource modifications, Linux operating systems, and longer resource reservations. Considering limitations, we propose a two-stage migration strategy: initially lifting and shifting the application to IaaS with cost optimization, and subsequently migrating to PaaS for scalability and simplified resource management in the long term.

Advancing Communication for the Deaf: A Convolutional Model for Arabic Sign Language Recognition

For the deaf population that speaks Arabic, Arabic Sign Language (ArSL) is an essential means of communication. This research presents a convolutional model for recognizing Arabic sign language because of the importance of clear communication. We hope to improve the deaf community's access to communication and broaden its sense of belonging by harnessing deep learning's power and fine-tuning the model to ArSL's particularities. To represent the complex hand movements and visual patterns that are characteristic of ArSL, the proposed model makes use of a variety of carefully made architectural decisions, such as the number of layers, the size of the kernels, the activation functions, and the pooling approaches. Our model outperforms state-of-the-art machine learning techniques, as shown by experimental findings on a large dataset. These results not only lay the groundwork for future developments in sign language recognition, but also demonstrate the promise of our technique in improving communication for the Arabic-speaking deaf community.

Multi-Granularity Collaborative Decision With Cognitive Networking in Intelligent Transportation Systems

Cognitive networking is a valuable enabler to improve the capability of intelligent transportation system (ITS) by analyzing and utilizing the heterogeneous traffic information. However, the significant increase in the amount of decision-making tasks makes it difficult to guarantee real-time performance of decision response. This paper focuses on the problem of the quality and real-time assurance of collaborative decision-making response in large-scale ITS during multi-task parallelism execution. First, a collaborative decision architecture with cognitive networking is developed, which introduces the advanced 6G communication technology to enhance information interaction capability of vehicle-road-cloud collaboration, and lays the foundation for multi-task real-time decision-making with inevitable fuzzy information in the perception process. Then, a multi-task parallel multi-granularity collaborative decision model (MPMCD) is designed to improve knowledge discovery ability for decision-making process by building multi-granularity information structures. An AI-driven cognitive networking collaborative decision-making (ACNCD) algorithm is further proposed based on MPMCD model to support multi-task parallel vehicle-road-cloud collaborative real-time decision. Extensive simulation experiments are carried out to evaluate ACNCD algorithm in terms of several performance criteria including decision response time, accuracy, and accident rate. The obtained results show that the comprehensive decision-making performance of ACNCD outperforms other relevant existing algorithms.

Neuro - Perspectives in Farmers Decision Architecture

Neuro - Perspectives in Farmers Decision Architecture

Using Deep Reinforcement Learning with Hierarchical Risk Parity for Portfolio Optimization

We devise a hierarchical decision-making architecture for portfolio optimization on multiple markets. At the highest level a Deep Reinforcement Learning (DRL) agent selects among a number of discrete actions, representing low-level agents. For the low-level agents, we use a set of Hierarchical Risk Parity (HRP) and Hierarchical Equal Risk Contribution (HERC) models with different hyperparameters, which all run in parallel, off-market (in a simulation). The information on which the DRL agent decides which of the low-level agents should act next is constituted by the stacking of the recent performances of all agents. Thus, the modelling resembles a statefull, non-stationary, multi-arm bandit, where the performance of the individual arms changes with time and is assumed to be dependent on the recent history. We perform experiments on the cryptocurrency market (117 assets), on the stock market (46 assets) and on the foreign exchange market (28 pairs) showing the excellent robustness and performance of the overall system. Moreover, we eliminate the need for retraining and are able to deal with large testing sets successfully.

Simulations of non-image-forming effects of light in building design: A literature review

Light affects many aspects of human physiology, through the non-image-forming (NIF) pathway. To account for this pathway, lighting design simulation tools need to combine several luminous and temporal factors to predict how architectural and lighting design decisions affect eye-level light exposure. Based on a systematic literature review, containing 55 journal and conference papers, the state-of-the-art towards implementing lighting beyond vision in computer simulation workflows for building design is presented. The review shows that, while interest in simulating the NIF effects of light on people is increasing, there is not a common method to perform these simulations. Gaps were identified in the currently available simulation workflows in relation to metrics, software and approaches for predicting NIF effects of light in the context of the building design.

Developing a Design Framework to Methodize the Architecture Thesis Projects with Emphasis on Programming and Conceptualization Processes

The research develops a design framework as an applied tool to structure the necessary stages throughout architectural design programs, in particular thesis projects. The architecture thesis students apply programming and conceptualization in several different ways, and a significant proportion of them prefers to use precedents instead. Architecture thesis projects tend to focus mainly on the studies, methods, and analysis, however, the relationship between the programming-conceptualization and the rest of the thesis project seems to have attracted less attention. To cover this gap, a design framework was developed to link the architecture findings to the design objective and strategies. The research employed qualitative methods, including structured observation, and content and graphical analysis. The data were also derived from thesis students’ drawings offered in the final exam. The findings revealed the potential capacity of the design framework to connect the analytical outputs with the architectural design decisions through a specific concentration on the processes of programming and conceptualization. In conclusion, the design framework could enable architecture thesis students to create a range of alternatives with regard to programming and concepts, whereas these options are still well-connected to design decisions. This will undoubtedly help students and lecturers with the creation of a systematic process of inputs, activities, outputs, and possible impacts.

Safety of transportation buildings against vehicle bomb attacks with multi-criteria decision-making

PurposeThis study aims to focus on security measures for protecting transportation buildings from vehicle bomb attacks. It discusses ways to mitigate the effects of vehicle bomb terrorist attacks through architectural design decisions on transportation buildings.Design/methodology/approachThe main research topic is the evaluation of architectural design decisions for vehicle bomb attacks at transportation buildings with the multi-criteria decision-making method. First, it was investigated which characteristics the impact of the explosion on the structures depended on. The measures for vehicle bomb attacks regarding the relationship between the urban scale and the building were determined by four main criteria and 17 sub-criteria. Due to the complex and ambiguous nature of architectural design, these criteria were evaluated by the analytic hierarchy processes. After the criteria weights were obtained, the alternative sample buildings, including the train stations and airports, were evaluated with the Technique for Order Preference by Similarity to an Ideal Solution method.FindingsThe site security design was determined as the most effective component for vehicle bomb attacks among the main criteria. The most important sub-criterion was the perimeter firewall. In the evaluations of the alternatives, it was determined that airports performed better against vehicle bomb attacks in terms of architectural design requirements than train stations.Originality/valueThis research contributes to the literature for the countries where explosions occur intensively by determining the importance of architectural design parameters for the transportation buildings and surroundings against vehicle bomb attacks. This study provides an evaluation model based on transportation buildings considering the relationship between the urban scale and the building itself.

How design rules emerge and evolve: a coevolutionary architectural perspective on firm and industry organization

AbstractThis paper elaborates on how design rules emerge and evolve as firms’ micro-level choices of product and organization architectures coevolve with changes in product markets and an industry’s competitive and cooperative dynamics. We suggest that the design rules a firm adopts will vary according to firms’ strategic choices of product and organization architectures that they believe are or may become feasible in a given industry. Building on the mirroring hypothesis that product designs a firm adopts will influence the organization designs it uses, we develop a model that identifies key relationships that influence firms’ strategic choices of product and organization architectures and associated design rules. We then elaborate on key interactions between firm-level architectural choices and the architecture-enabled competitive and cooperative dynamics that obtain in an industry. Our model identifies strategically important aspects of open- and closed-system architectures and modular and nonmodular architectures that impact industry structures, interfirm interactions, and resulting industry dynamics. Drawing on these analyses, we suggest how firms’ strategic choices of architectures are influenced by their assessments of (i) the potential for capturing value through both gains from specialization and gains from trade that firms believe will be enabled by their architectural choices and (ii) both ex ante and ex post transaction costs implied by their architecture decisions. We conclude by suggesting how the perspective on firm’s strategic architectural decisions we develop here enables new approaches to understanding evolutions of both product markets and industry structures for serving product markets.

Exploring Architectural Design Factors Affecting Building Maintainability and Strategies to Overcome Current Shortcomings

The design phase is when most critical decisions are made in terms of building maintainability. However, process-oriented empirical studies that identify problem factors and develop strategies remain lacking. Based on this gap in the literature, this research proposes a framework for enhancing architectural design decisions and practices through identifying and exploring problem factors affecting building maintainability. In addition, this research developed strategies to overcome the shortcomings of current practices in the Turkish building sector. Architectural design factors that influence building maintainability and relevant problems were evaluated through a web-based questionnaire survey conducted with facility managers. The findings indicate that improper selection of building materials and inadequate provisions for waterproofing, indoor ventilation, and service areas appear to be prominent areas of concern. Moreover, it was observed that the facility management profession has not gained a well-deserved place in the industry. The strategies proposed to overcome the shortcomings of current practices could be assumed to be supportive actions both for creating awareness in the industry and for making appropriate architectural design decisions about building maintainability.

Features of the construction tecniques of Ani masters. Walls and point supports

Introduction. The construction technique of the master-builders is a little-studied aspect of the architectural heritage of the medieval Armenian capital of Ani (961–945). The author of the article proposes to answer a number of questions related to changes in masonry of the walls, pylons and pillars and the device of the columns, with the advent of new forms of socles on the monuments of the metropolitan school of architecture in the Bagratid era.
 
 Materials and methods. The information from publications and from own observations allows for the testing between changes in building technique and architectural decisions. The limitation of the material to the structures of walls and supports does not exclude references to the relationship of these elements with coverings, which peculiarities will be disclosed in subsequent publications.
 
 Results. Ani masters have developed a traditional masonry with inextricably connected three leyers: outside stone and internal rubble concrete. The main Ani architect Trdat used the combination of the wall structure with the frame system, while the internal design of the concrete core has been preserved around the entire perimeter of the building, with enlargements in places of еру weighting’s concentration. Stone blocks by the end of the 10th century became narrower, up to 0.3 m deep, but the rows of laying walls and pillars alternated, up to 1.5–2 m, which led to the use of vertically oriented blocks. In line with the development of the blind arcade order, facades of the churches of the 1020–1030s were laid out on this kind of slabs. Depending on the architect of each building, the achievements in the number of laying rows for the height of the order pilaster was introduced. A sharp rise in the round columns in the church of St. Gregory Gagkashen in comparison with its prototype, the VII century church of Zvartnots, the nature of the wall socles and other features of the Ani monuments were not covered with the help of useful economic or technical problems.
 
 Conclusions. Most of the changes of features of the masonry of the walls and pillars, as well as of the columns in Ani of the Bagratid era correspond to their direct dependence on the architectural design and lead to the achievement of a certain architectural image.

Distilling Reference Architectures in the High‐tech Equipment Industry

ABSTRACTCompanies in the high‐tech equipment industry are continuously looking for ways to optimize their business. A notoriously difficult part of optimizing is the R&D activities, as risks and uncertainties are inherent. In our experience, creating and using a reference architecture for a product or portfolio to guide future developments is a good way to improve R&D effectiveness and efficiency. But developing a reference architecture by capturing the relevant information and establishing the structure, the models and their interrelations, the tools, and secondly, getting clarity on how to use such reference is not easy. In this article, we describe a method to ‘distill’ a reference architecture using the knowledge built‐up in years of developing products and using the customer and business values to capture the key architectural decisions for future products. We explain the purpose and usage of a reference architecture and how to organize it. The experiences obtained in Thermo Fisher Scientific have proven the importance and practicality of this approach.

GP-NFSP: Decentralized task offloading for mobile edge computing with independent reinforcement learning

In Mobile Edge Computing (MEC), offloading tasks from mobile devices to edge servers may accelerate the processing speed and save the energy of the devices, hence improving device users’ quality of experience. Recently, reinforcement learning (RL) is increasingly used for offload decision making. RL seeks long-term cumulative benefits and is proved useful for a sequence of decisions, thus is well suited for the work. Due to privacy and security concerns, mobile devices may be unwilling to expose their local information, leading to a fully decentralized MEC environment. Independent RL (IRL) emerges as a promising solution for this scenario. However, IRL solutions are faced with the non-stationarity issue, which arises when the components are changing their policies. In this paper, we proposing adopting the Neural Fictitious Self-Play (NFSP) architecture for offload decision making. NFSP explicitly tackles the non-stationarity issue with the built-in self-play mechanism, and uses a mixed strategy consisting of deep RL and the past average strategy, which is approximated by supervised deep learning. Furthermore, we use the Proximal Policy Optimization (PPO) algorithm as the RL component and exploit the Gated Recurrent Unit (GRU) to deal with the partial-observability issue in fully decentralized MEC. We conduct extensive simulation experiment, the result of which shows that our method outperforms the raw IRL approaches, validating the effectiveness of our proposed method.

Reducing Computational Cost During Robot Navigation and Human–Robot Interaction with a Human-Inspired Reinforcement Learning Architecture

We present a new neuro-inspired reinforcement learning architecture for robot online learning and decision-making during both social and non-social scenarios. The goal is to take inspiration from the way humans dynamically and autonomously adapt their behavior according to variations in their own performance while minimizing cognitive effort. Following computational neuroscience principles, the architecture combines model-based (MB) and model-free (MF) reinforcement learning (RL). The main novelty here consists in arbitrating with a meta-controller which selects the current learning strategy according to a trade-off between efficiency and computational cost. The MB strategy, which builds a model of the long-term effects of actions and uses this model to decide through dynamic programming, enables flexible adaptation to task changes at the expense of high computation costs. The MF strategy is less flexible but also 1000 times less costly, and learns by observation of MB decisions. We test the architecture in three experiments: a navigation task in a real environment with task changes (wall configuration changes, goal location changes); a simulated object manipulation task under human teaching signals; and a simulated human–robot cooperation task to tidy up objects on a table. We show that our human-inspired strategy coordination method enables the robot to maintain an optimal performance in terms of reward and computational cost compared to an MB expert alone, which achieves the best performance but has the highest computational cost. We also show that the method makes it possible to cope with sudden changes in the environment, goal changes or changes in the behavior of the human partner during interaction tasks. The robots that performed these experiments, whether real or virtual, all used the same set of parameters, thus showing the generality of the method.

Comprehensive analysis and evaluation of ship energy efficiency practices

The IMO is working to reduce emissions from ships. One of its initiatives is the Ship Energy Efficiency Management Program (SEEMP), which is based on the Plan, Do, Check and Act (PDCA) cycle. In order to clearly describe the weight of energy efficiency improvement methods in practice, current energy efficiency practices were summarised systematically from five aspects, including optimising navigational management and operation, improving power system efficiency, reducing ship resistance, improving company management as well as the application of new energy and new technologies. Based on the Fuzzy- Analytic hierarchy process (AHP) method, a multi-level evaluation system was established by considering the importance degree of these practices. Comprehensive evaluation was carried out in accordance with the results obtained from the questionnaire survey of experienced experts in China. The evaluation results show that the management innovation has higher influence than technological alteration in achieving the energy conservation and emissions reduction of ships, and the speed optimisation is recognised as the most effective approach onboard at present. The multi-attribute decision-making architecture and comprehensive evaluation method proposed is much needed by the ship managers and crew members to determine the best practice of energy efficiency.

Generation of Phenomenal Interior Quality from Refurbishment of Commercial Spaces in Residential Areas

Commercial buildings in the residential districts are under rapid redevelopment because retail shopping activities are being replaced by community service, education, eating and dinning and experiential activities in China. This paper revealed three interior refurbishment projects aiming to recreating interior public spaces. Interior fitting has rapidly grown in the building industry. Product suppliers provide strong support for construction quality and intervene in architectural design decisions. Interior design, as independent work, promotes effective dialogue with clients, users and suppliers in the design process. It is a platform for quality by understanding the texture, lighting and atmosphere as the key area of control in design. The interior design of three projects of Baumschlager Eberle Architekten (BEA) Hong Kong Ltd, transforms the common areas of shopping centres in residential areas into interior public spaces. The paper introduces and evaluates the design methods of BEA architects to present and control design quality, especially for interior public spaces. The territory, material, visibility, rhythms and use and overall interior atmosphere are analysed with case studies based on the literature review on outdoor public spaces. The paper concludes that interior refurbishment is an independent level of design in the recreating ―publicness‖ in existing building structure. Only when conceptually free from the constraints of structure and façade can unique atmospheres be achieved through design, opening up further intervention in future.

The Psychology of Architecture Decision Records

Architecture Decision Records (ADRs) have been characterized as a lean documentation technique, but this overlooks their cultural impact: writing ADRs can also help developers evolve into architectural thinkers. ADRs accomplish this by subtly influencing developers to change four key behaviors: improved appreciation of design’s value, increased design participation, better follow through on decisions, and stronger design engagement. These four complementary behaviors nudge developers to see themselves as software architects, which in turn transforms the team’s culture.