Adaptive Software Research Articles

Cartography and Topographic Mapping: The Historical Basis for the Standardization of Anatomical Analysis and Surgical Mark-Making to Improve Outcomes in Body Contouring.

Maps have been used for thousands of years to guide and advance mankind's interests. Recently, cartography has grown exponentially into standardized, densely layered systems, facilitating countless functions that use complex algorithms and multifactorial data. Surgeons have successfully addressed bodily concerns for centuries, aided by consistency of human anatomy, physiologic responses to disease, and patterns of disease. However, body contouring techniques alter the much more inconsistent surface anatomy of stretched or aged skin and highly variable subcutaneous fullness. To date, no consistent strategy has been proposed to analyze, map, and alter human shape in a standardized fashion; however, well-established cartographic methods for topographic mapping can be logically adapted to meet surgical needs. Quantification of results, valid and meaningful comparison of techniques, and anatomical discovery could all be achieved by adopting cartographic methods. As anatomists and scientists, surgeons constantly seek logical and reproducible methods to improve patient outcomes. In this article, the authors present a technique derived from topographic mapping, applied directly to the surface of the human body, reflecting the actual underlying anatomy, to guide both elective and reconstructive procedures. The method provides logical and quantifiable methods for (1) the analysis of anatomy, (2) data-driven planning of surgical care, and (3) a consistent operative implementation-so that each patient can receive individualized, anatomically based procedures. Use of well-established mapping strategies would also promote interdisciplinary collaboration, permit adaptation of software to analyze volume and shape, and improve patient outcomes through quantification of change and meaningful comparisons of procedural options.

An Adaptive System for a Real-Time Matching Application

In order to enhance the customer experience, it is important not only to provide functions, but also to respond to changes in environments and requirements. It is a difficult task to evaluate and manage which function with different locations and contents is most valuable to the user's experience without using computationally time-consuming optimization calculations. To address this, this paper is focusing on self-adaptive software technology. The authors built a software adaptation mechanism that can be immediately calculated online using a performance characteristic map and threshold judgment with a learning function and sequential updates. The results confirmed the effectiveness of the mechanism in an application that supports personnel exchange events.

Apriori Algorithm Based Component Classifications and Adaptation for Software Reuses

With the growth in software development, the software user expects high-quality software services with lesser time complexity. Therefore, the demand for software component based development is also increasing. In the recent past, a good number of research attempts have tried to build an automated framework for generating the recommendations for component equivalence. In software engineering and program building, reusability is the utilization of existing resources in some structure inside the product items. Adaptive software reuse products improve the life cycle of software and enhance the planning, coding, and documentation in different approaches of reusability. On the other hand, reusability can be used to meet with new software demands. Thus, the proposed novel approach to Apriori based component classifications and adaptation is used to software component reusability based on the recommendation of rule-based analysis.

Low cost 3D printing of metals using filled polymer pellets

Nowadays, additive manufacturing of metallic materials is most often carried out using expensive and complex tools that leave the user with limited control and no possibility of modification. In order to make the printing of metal parts more accessible to small structures but also better suited for academic research, the use of a mixture of thermoplastic polymer and metal powder is a good solution as many granular feedstocks already exist for Metal Injection Molding applications. To perform the shaping process, the Fused Granular Fabrication 3D printing technology is set up by diverting the use of a feedstock in the form of pellets that are directly inserted into the print head. This solution, which is less costly, is implemented here by modifying a mid-range printer, the Tool Changer from E3D, and by making the hardware and software adaptations to mount a compact granulates extruder on it, which is also available on the market. The polymer portion present in the green part can then be removed in order to perform the heat treatments that will densify the powder by sintering and give a fully metallic dense object.

Adaptation of FEM-based open-source software for ship structural analysis

ABSTRACT This paper investigates the challenges and opportunities emerging from the application of finite element method-based open-source software in ship structural analysis. Application of general procedure for development and assessment of FEA software used for ship structures is presented and demonstrated on the new upgrade of open-source FEA software OOFEM (Object-Oriented Finite Element Method). Properties of new quadrilateral shell FEs implemented in OOFEM are presented. The new FEs comply with relevant class requirements and are suitable for the usage in the analysis of real-world ship structures. The implemented software upgrade is validated on a series of test problems ranging from simple engineering structures to a real-world model of one part of megayacht’s superstructure. The benefits of validation tests and challenges encountered in the process of selecting the tests and interpreting their results are also discussed.

Toward an Adaptive Software Architecture for Archetype-Based Health-Care Applications

Self-adaptation gives software systems the ability to adjust their behavior or structure in changing environments such as the health software domain. However, adaptability significantly complicates software implementation and brings great challenges to software engineering.

An Open-Source, Fully Customizable 5-Choice Serial Reaction Time Task Toolbox for Automated Behavioral Training of Rodents

The 5-choice serial reaction time task (5-CSRTT) is a behavioral test often used to study visuospatial attention and impulsiveness in rodents. The task requires animals to allocate attention to a horizontal array of five small apertures equipped with light sources and, within a limited time window, nose-poke one illuminated target aperture to get a food reward at the food magazine located in the opposite wall of the chamber. The task considers behavioral control measures such as response accuracy and reaction times and allows to infer selective attention and impulsivity. Task difficulty can be controlled by modifying the stimulus duration and task design in general. Commercially available apparatus usually consists of an experimental chamber and particular software to specify task parameters, but due to fixed hard- and software, they pose many limitations on changes in the general experimental design and specific task requirements and the related data output. This article explains a fully customizable alternative based on an easy-to-use single-board microcontroller and standard electrotechnical components, an open-access Arduino script, and a Matlab-toolbox for hardware control and behavioral task specifications, respectively. The toolbox includes an optional staircase procedure, enabling automated behavioral training. The complete hardware setup, which can be installed in customized chambers, and the freely adaptable software encourage non-standardized task and chamber design. The design of the system and the open-source code for hardware control and experimental setup are described.

An Open-Source, Fully Customizable 5-Choice Serial Reaction Time Task Toolbox for Automated Behavioral Training of Rodents.

The 5-choice serial reaction time task (5-CSRTT) is a behavioral test often used to study visuospatial attention and impulsiveness in rodents. The task requires animals to allocate attention to a horizontal array of five small apertures equipped with light sources and, within a limited time window, nose-poke one illuminated target aperture to get a food reward at the food magazine located in the opposite wall of the chamber. The task considers behavioral control measures such as response accuracy and reaction times and allows to infer selective attention and impulsivity. Task difficulty can be controlled by modifying the stimulus duration and task design in general. Commercially available apparatus usually consists of an experimental chamber and particular software to specify task parameters, but due to fixed hard- and software, they pose many limitations on changes in the general experimental design and specific task requirements and the related data output. This article explains a fully customizable alternative based on an easy-to-use single-board microcontroller and standard electrotechnical components, an open-access Arduino script, and a Matlab-toolbox for hardware control and behavioral task specifications, respectively. The toolbox includes an optional staircase procedure, enabling automated behavioral training. The complete hardware setup, which can be installed in customized chambers, and the freely adaptable software encourage non-standardized task and chamber design. The design of the system and the open-source code for hardware control and experimental setup are described.

BIM for Landscape Design Improving Climate Adaptation Planning: The Evaluation of Software Tools Based on the ISO 25010 Standard

This paper investigates the capabilities and limitations of different software tools simulating landscape design adaptability. The evaluation of tools is based on the ISO 25010 framework, which investigates software functionality, reliability, performance efficiency, usability, compatibility, and information quality. These quality characteristics of software are analysed during objective experiments where five software tools are used for a case study project at the conceptual design phase. These experiments reveal that the existing software tools for climate adaptation planning are focused on different aspects of climate adaptability, generating different types of information. Moreover, all tools deal with some limitations in terms of compatibility, performance efficiency, and functional operations. The ISO 25010 quality model provides a comprehensive framework to compare the capabilities of different software tools for climate adaptation planning. This paper is part of a wider study including an analysis of the needs of project stakeholders regarding climate adaptation software tools. However, this article focuses on technical capabilities of current climate adaptation software tools.

Self-learning, adaptive software: an example from aerospace engineering

Self-learning, adaptive software: an example from aerospace engineering

АРХІТЕКТУРА ТА РЕАЛІЗАЦІЯ БАЗОВИХ КОМПОНЕНТІВ СИСТЕМИ НЕЙРОМЕРЕЖЕВОГО ЗАХИСТУ І КОДУВАННЯ ПЕРЕДАЧІ ДАНИХ

The development of basic components of the neural network protection system, data transmission coding based on an integrated approach, which includes an improved method of neural network encryption (decryption) and the method of adaptive barker-like coding (decoding) of data, which focuses on modern element base. The principles of specialization and adaptation of hardware and software to the structure of algorithms for neuro-like encryption (decryption) of data, neural network architecture, and barker-like code are used to develop the system. The architecture of the system is proposed, which takes into account the variable composition of the equipment and modularity. The method of neural network encryption (decryption) of data has been improved. The time of neural network encryption and decryption of data depends on the size of the tables of macroparticle products. The size of the tables of pre-calculated macroparticle products is based on the provision of encryption and decryption of data in real-time. A method of adaptive barker-like encoding (decoding) has been developed, which, due to the signal-to-noise ratio, provides high noise immunity and reduces data transmission time. The hardware of the system, which was created using the developed basic components of neural network protection and barker-like data encoding, is described. When creating hardware, ready-made components and modules of industrial production are used as much as possible, and the availability of appropriate means of software code development is taken into account. Means of neural network cryptographic encryption (decryption) of data of the mobile part of the system are implemented using a microcomputer-based on SoC. Not the most powerful microcomputer of the NanoPi Duo type from FriendlyElec has been especially used to test the means of neural network cryptographic encryption (decryption) of data. Using the created system, it is determined that the performance of neural network cryptographic encryption (decryption) of data blocks based on a microcomputer is carried out in close to real-time. The time of formation and training of the neural network is about 200 ms, and the implementation of encryption and decryption procedures is about 35 ms and 30 ms, respectively, and does not depend significantly on the chosen configuration of the neural network.

Creating a Modeling Language Based on a New Metamodel for Adaptive Normative Software Agents

The demand for creating increasingly dynamic, autonomous and proactive software systems is challenging for the traditional Multi-agent Systems (MASs) approaches. Such requirement has given rise to adaptive software agents approaches. At the same time, norm is an essential and challenging feature that still tends to be addressed in adaptive MAS. In fact, norms to regulate agent behavior is still a vague concept that has not been properly investigated in terms of modeling and implementation. Even though many researchers have proposed modeling languages to deal with different abstractions, these languages fail to support the modeling of abstractions, such as adaptation and norms. Even more severe is the fact that little has been done to support the systematic design of Adaptive Normative Multi-Agent Systems (ANMASs). To facilitate the design and development of ANMASs, this paper presents a new metamodel, as well as language support, as means to provide tools to enable software developers. The proposed metamodel fosters a better understanding of the way agents are able to change their behaviors to deal with norms and captures interactions between agent’s norms and adaptation. To this end, our research is organized into five steps: (i) a literature review to identify the limitations of existing approaches related to ANMAS modeling; (ii) propose a new metamodel to support adaptative and normative concepts; (iii) propose a new language for modeling ANMASs; (iv) perform a qualitative and quantitative evaluation of the proposed language using a real case scenario, and (v) an empirical evaluation. The proposed metamodel and its associated modeling language advances the state of the art in modeling MASs and the approach is assessed in terms of correctness, time and difficulty. Our initial results revealed that our approach can be feasibly applied in a real world application, and is less difficult to apply and requires less time in comparison with a traditional approach. As software applications become more dynamic and adaptive, we believe it is essential to support developers to model MASs with abstractions such as adaptive agents, norms and their relationships. Such information can be foundational to steer future research on modeling adaptive agents capable of understanding and dealing with norms and adaptation.

360° Virtual Reality Video Tours Generation Model for Hostelry and Tourism based on the Analysis of User Profiles and Case-Based Reasoning

This paper proposes an adaptive software archi-tecture focused on hotel marketing based on immersive virtual reality (VRI) with 360° videos, which includes a component based on Case-Based Reasoning (CBR) to provide experiences that correspond to the analysis of user profiles. For the validation of the system, considering that the use of VR can trigger experi-ences in several dimensions, affective, attitudinal and behavioral responses, as well as the cognitive load were evaluated using visu-alizations of 2D photographs contained in hotel websites , which were compared with 360° videos in a VRI environment. To test the hypotheses, a quasi-experimental study was conducted with an independent sample group, in which subjects were randomly assigned to the two types of visualizations. The contribution of the article lies in the incorporation of marketing concepts and approaches in VRI experiences with 360° videos through virtual objects that are used by the software architecture, as well as in the proposed validation of the effectiveness of the proposal.

Assured Mission Adaptation of UAVs

The design of systems that can change their behaviour to account for scenarios that were not foreseen at design time remains an open challenge. In this article, we propose an approach for adaptation of mobile robot missions that is not constrained to a predefined set of mission evolutions. We implement an adaptive software architecture and show how controller synthesis can be used both to guarantee correct transitioning from the old to the new mission goals with runtime architectural reconfiguration to include new software actuators and sensors if necessary. The architecture brings together architectural concepts that are commonplace in robotics such as temporal planning, discrete, hybrid and continuous control layers together with architectural concepts from adaptive systems such as runtime models and runtime synthesis. We validate the architecture flying several missions taken from the robotic literature for different real and simulated UAVs.

STRUMM: An Intelligent, Adaptive Software Package for Older Adults With a Cognitive Impairment

Many older adults have a cognitive impairment (CI), which negatively impacts on their quality of life and threatens their independence. In this presentation, we provide an overview of the conceptual framework, structure, and processes of our multi-site Center, ENHANCE, which is focused on developing technology support for aging adults with a CI. ENHANCE has two cross-site research projects, two cross-site development projects, training, and dissemination components. A core battery of measures is collected across all projects. We also discuss the Supportive Technology Resources through Usability & Machine-learning Methods (STRUMM) research project, which focuses on an innovative intelligent adaptive software package aimed at providing cognitive and social support, and support for resource access to aging adults with a CI. STRUMM is designed to meet the user’s varying cognitive needs. Finally, we present preliminary data regarding the perceived usability and value of STRUMM from our clinical partners and potential user groups.

ENHANCE: The Center for Enhancing Neurocognitive Health, Abilities, Networks, & Community Engagement

Approximately 9 % of those aged 65 and over have a cognitive impairment due to a variety of causes including Alzheimer’s disease and other forms of dementia, Mild Cognitive Impairment (MCI), Parkinson’s disease, traumatic brain injury (TBI), and stroke. Few technology solutions have been directed towards supporting older adults with cognitive impairments and the literature regarding the efficacy of these solutions is sparse. In this symposium, we describe our new Center called ENHANCE (Enhancing Neurocognitive Health, Abilities, Networks, and Community Engagement), which is focused on developing technology support for aging adults with a cognitive impairment due to MCI, TBI, and Stroke. Sara Czaja will provide an overview of the conceptual framework, goals, and structure of ENHANCE, and describe the STRUMM project, that focuses on the design and evaluation of an innovative intelligent adaptive software package aimed at providing cognitive and social support to aging adults with cognitive impairments. Wendy Rogers will discuss the ENACT project, a longitudinal needs assessment focusing on understanding the needs, challenges, and support preferences of our target population and informal caregivers. Neil Charness will describe the AUGMENT development project, which is concerned with developing an instructional support tool for mobility activities, such as wayfinding, locating, and using transportation services. Finally, Walter Boot will discuss the DREAM development project, which is focused on developing a technology-based cognitive aid to support prospective memory activities. Michelle Bourgeois will serve as the discussant for the symposium and highlight the unique opportunities and challenges associated with ENHANCE.

Effectiveness of a numeracy intelligent tutoring system in kindergarten: A conceptual replication

Intelligent Tutoring Systems are a genre of highly adaptive software providing individualized instruction. The current study was a conceptual replication of a previous randomized control trial that incorporated the intelligent tutoring system Native Numbers, a program designed for early numeracy instruction. As a conceptual replication, we kept the method of instruction, the demographics, the number of kindergarten classrooms (n = 3), and the same numeracy and intrinsic motivation screeners as the original study. We changed the time of year of instruction, changed the control group to a wait-control group, added a maintenance assessment for the first group of participants, and included a mathematical language assessment. Analysis of within- and between-group differences using repeated measures ANOVA indicated gains of numeracy were significant only after using Native Numbers (Partial Eta Square = 0.147). Results of intrinsic motivation and mathematical language were not significant. The effect size of numeracy achievement did not reach that of the original study (Partial Eta Square = 0.622). Here, we compared the two studies, discussed plausible reasons for differences in the magnitude of effect sizes, and provided suggestions for future research.

Базова архітектура мобільної робототехнічної платформи з інтелектуальною системою управління рухом і захистом передачі даних

The requirements for a mobile robotic platform (MRP) with an intelligent traffic control system and data transmission protection are determined. Main requirements are the reduction of dimensions, energy consumption, and cost; remote and intelligent autonomous traffic control; real-time cryptographic data protection; preservation of working capacity in the conditions of action of external factors; adaptation to customer requirements; ability to perform tasks independently in conditions of uncertainty of the external environment. It is proposed to develop a mobile robotic platform based on an integrated approach including: navigation methods, methods of pre-processing and image recognition; modern methods and algorithms of intelligent control, artificial neural networks, and fuzzy logic; neuro-like methods of cryptographic data transmission protection; modern components and modern element base; methods of intellectual processing and evaluation of data from sensors in the conditions of interference and incomplete information; methods and means of automated design of MRP hardware and software. The following principles were chosen for the development of a mobile robotic platform with an intelligent control system and cryptographic protection of data transmission: hierarchical construction of an intelligent control system; systematicity; variable composition of equipment; modularity; software openness; compatibility; specialization and adaptation of hardware and software to the structure of algorithms for data processing and protection; use of a set of basic design solutions. The basic architecture of a mobile robotic platform with an intelligent traffic control system and data transmission protection has been developed, which is the basis for the construction of mobile robotic platforms with specified technical and operational parameters. To implement neuro-like tools, the method of tabular-algorithmic calculation of the scalar product was improved, which due to the simultaneous formation of k macroparticle products provides k times reduction of the time of the scalar product calculation. Keywords: mobile robotic platform; intelligent processing; architecture; neural network; autonomous control; sensors; data protection.

Assessing the Usability of a Tumor Dashboard for Multidisciplinary Care Teams for First Time Users; First Exploration of a Comparative Participatory Cognitive Walkthrough to Show Mismatches in Cognitive Models.

Due to the COVID-19 pandemic, multidisciplinary team (MDT) meetings have to switch from physical to digital meetings. However, the technology they currently use to facilitate these meetings can sometimes be lacking, therefore many software companies have developed new software to ease our new digital workspace. In this study, we propose a new method, a comparative participatory cognitive walkthrough, which can show mismatches in cognitive models. To test our method, we tested the compatibility of EPIC EMR (EPIC Care) and the NAVIFY Tumor Board for preparing MDT meetings. The identified mismatches are categorized in the HOT-fit model by Yusof et al, a common way to evaluate if a healthcare information system fits with the healthcare professionals and the organization. In total, 16 mismatches were identified. These mismatches were discussed in a feedback session with an implementation manager of the NAVIFY Tumor Board. The proposed method seems to be a fast and cheap method to gain useful insights in how well new software matches with the software currently in use, by comparing the cognitive models in place when performing tasks involved with specific scenarios. The identified aspects can be of use for the development and adaptation of the new software, as well as provide guidelines on which aspects to focus on when training healthcare professionals to use the new software to have a smooth transition of software.

Adaptive learning: Helpful to the flipped classroom in the online environment of COVID?

Flipped instruction in an undergraduate numerical methods course in the online, remote environment during the COVID‐19 pandemic was conducted with and without the use of adaptive‐learning lessons for pre‐class preparation. This comparison was made to explore potential differences with and without adaptive software relative to exam and concept inventory performance and student perceptions of the classroom environment, learning and motivation, and benefits and drawbacks. Student perceptions were gathered via the College and University Classroom Environment Inventory (CUCEI) and a survey designed to capture feedback specific to flipped instruction. The analysis was made possible by a current NSF grant to study adaptive learning in the flipped classroom at three universities and extensive prior research with the flipped classroom and adaptive learning by the authors. Results gathered in the online flipped classroom with adaptive learning suggested positive changes in the following: classroom environmental perceptions, preference for flipped instruction, perceived responsibility imposed, motivation for independent learning, and perceived learning. Furthermore, based on an open‐ended question, there was a significant decrease in the proportion of students who experienced load, burden, or stressors in the online flipped classroom when adaptive learning was available versus not. Multiple‐choice exam and concept‐inventory results were slightly higher with adaptive lessons (although not significantly so), with the most promising results occurring for Pell grant recipients. The emerging medical education literature has suggested that adaptive learning and flipped instruction will be key to post‐pandemic education. The present article begins advocacy for adaptive learning with flipped instruction in engineering education.