In-house Development Research Articles

Revolutionizing Banking: The Path to an AI-driven Future with a Special Reference to Union Bank

Banking stands at a transformative crossroads, propelled by technological disruption, shifting consumer dynamics, and the catalytic impact of the COVID-19 pandemic. This research charts the course for a new era in banking business models, introducing a paradigm shift known as 'the AI bank of the future.' Grounded in the advancement of artificial intelligence (AI) technologies, this model offers traditional banks the potential to elevate revenue while reducing costs, ushering in innovative customer engagement approaches. In response to multifaceted challenges, including market valuations, competitive threats from neobanks, and changing customer expectations, traditional banks are urged to become 'AI-first' in strategy and operations. This involves leveraging economies of scale through efficient AI deployment to enhance customer engagement with distinctive experiences and superior value propositions. The research meticulously explores the building blocks of an AI bank, delving into four critical layers: engagement, AI-powered decision-making, core technology, and data infrastructure, and a platform-based operating model. Through a series of articles, the study examines trends, challenges, and requirements for each layer, offering an end-to-end view of the capabilities essential for the AI bank of the future. The articles cover topics ranging from the challenges leading banks to adopt an AI-first approach, a day in the life of a consumer transacting with an AI bank, reimagining customer engagement, to AI-powered decision-making and the modernization of core technology. The final piece discusses the necessity of a platform operating model, emphasizing the deployment of AI and analytics capabilities at scale through cross-functional business-technology platforms. To embark on this transformative journey, bank leaders are advised to formulate strategic goals for the AI-enabled digital age, establish an AI-first vision, and strategically modernize enterprise technology. The research underscores the importance of assessing emerging technologies, prioritizing initiatives aligned with customer needs, and considering partnerships for non-differentiating capabilities while focusing on in-house development for distinct competitive advantages. In conclusion, building the AI bank of the future is envisioned as a pathway to innovation, competitive prowess against digital natives, and sustainable increases in profits and valuations. The research serves as a guiding compass, assisting banks in establishing their vision and crafting a strategic roadmap for this transformative journey into the AI-driven future of banking.

The Use of VSR as an In-house Professional Development Tool for Joint Reflection in a Primary School in the Western-Cape, South Africa

Joint reflection amongst teachers is a valuable way to learn from colleagues. The study explored the joint reflection by a primary school mathematics subject team where video-stimulated recall was used as a reflective tool. The research question that guided the study was: what is the influence of joint reflection on the professional development of a mathematics subject team, using video-stimulated recall as a reflective tool? The study leaned on teacher collaboration as a learning context for teachers and used the community of practice as a theoretical framework. The qualitative study used joint video-reflective sessions as data collection instruments where a mathematics subject team of six primary school teachers participated. Lessons of two teachers were video-recorded and played to the subject team and they then jointly reflected on the lessons. The themes that emerged from the data included initial discomfort to share their views about another colleagues’ lesson; learner involvement in lessons; strengthening mathematics concepts; and learning from each other. The study found that colleagues learned from each other, that better ways of doing were suggested and that the analysis of the video was like a two-edged sword where those who presented the lesson learned as well as those who watched the lessons.

Risk avoidance in strategic technology adoption

Purpose Organizational technologies can be classified according to the roles they play as either commodity or strategic. Commodity technologies support common operations, while strategic technologies address perceived threats to competitiveness, often identified by strategic foresight. These must go through an adoption process before playing an effective role in strategy execution. The adoption process includes known activities, ranging from sourcing (itself from in-house development to turn-key acquisition) to operational integration. This paper aims to reveal strategic technology adoption risks that arise during strategy execution. Design/methodology/approach A gradually developed causal loop diagram model, supported by general literature, introduces three general classes of technology adoption risks: mismatched requirements, supplier dependence and unmanaged life cycles. Findings Rather than managed, these risks are incurred or avoided depending on decisions made during the adoption process. Research limitations/implications Despite the scarce literature coverage for the approach, examples revealing the presence of adoption risks are nevertheless available in the well-documented history of enterprise resource planning (ERP). Practical implications Although ERP is presented as a general-purpose strategic technology, the unique business features of maritime container terminals pose serious challenges to its adoption, which provides additional support to the discussion and reinforces the conclusions. Originality/value The approach to identifying risks in strategic technology adoption departs from the current risk paradigm in two significant ways. First, it emphasizes policy decision-making rather than external events. Second, it views risks as systemic rather than occurring independently.

Reasons for the Failure of Most In-House Software Development in Tanzania: A Case Study of Selected Higher Learning Institutions (HLIs)

Since it has evolved into an essential part of today’s world, 90% of Tanzanian businesses have attempted to develop in-house software for their operations. However, a substantial fraction of these projects haven’t quite achieved what they set out to. The bulk of in-house software development projects in Tanzania have been unsuccessful. This article presents ideas for improving the success rate of in-house software development initiatives and explains why this is the case. As part of the qualitative research methodology, software developers, project managers, and other stakeholders took part in focus groups and interviews. The results show that there are several factors, such as a lack of qualified staff, an inadequate budget allocation, poor project management, a lack of precise project requirements, improper communication, an inadequate amount of resources, and a lack of user involvement, that significantly contribute to the failure of in-house software development projects in Tanzania. The study makes numerous recommendations for enhancing the success rate of in-house software development initiatives in Tanzania. Involving end users throughout the project life cycle, implementing strong project management practices, allocating enough time and resources for software testing, hiring experts to establish and gather precise project requirements, allocating adequate budgets, and setting up efficient communication channels are a few examples of these. Additionally, in-house software development must adhere to the SDLC’s standards by enhancing the model of the SDLC that best suits the nature of the development process.

14C MEASUREMENT OF SAMPLES FOR ENVIRONMENTAL SCIENCE APPLICATIONS AT THE NATIONAL ENVIRONMENTAL ISOTOPE FACILITY (NEIF) RADIOCARBON LABORATORY, SUERC, UK

ABSTRACT The National Environmental Isotope Facility (NEIF) Radiocarbon Laboratory at the Scottish Universities Environmental Research Centre (SUERC) performs radiocarbon measurement of a wide range of sample matrices for applications in environmental research. Radiocarbon is applied to palaeoenvironmental, palaeoceanographic, and palaeoclimatic investigations, as well as work to understand the source, fate, turnover, and age of carbon in the modern carbon cycle. The NEIF Radiocarbon Laboratory supports users in the development and deployment of novel sampling techniques and laboratory approaches. Here, we give an overview of methods and procedures used by the laboratory to support the field collection, laboratory processing, and measurement of samples. This includes in-house development of novel and/or specialized methods and approaches, such as field collection of CO2 and CH4, hydropyrolysis, and ramped oxidation. The sample types covered include organic remains (e.g., plant material, peat, wood, charcoal, proteins), carbonates (e.g., speleothems, foraminifera, mollusc shell, travertine), waters (dissolved organic and inorganic carbon), gases (CO2 and CH4), soils and sediments (including sub-fractions).

Machine learning based software effort estimation using development-centric features for crowdsourcing platform

Crowd-Sourced software development (CSSD) is getting a good deal of attention from the software and research community in recent times. One of the key challenges faced by CSSD platforms is the task selection mechanism which in practice, contains no intelligent scheme. Rather, rule-of-thumb or intuition strategies are employed, leading to biasness and subjectivity. Effort considerations on crowdsourced tasks can offer good foundation for task selection criteria but are not much investigated. Software development effort estimation (SDEE) is quite prevalent domain in software engineering but only investigated for in-house development. For open-sourced or crowdsourced platforms, it is rarely explored. Moreover, Machine learning (ML) techniques are overpowering SDEE with a claim to provide more accurate estimation results. This work aims to conjoin ML-based SDEE to analyze development effort measures on CSSD platform. The purpose is to discover development-oriented features for crowdsourced tasks and analyze performance of ML techniques to find best estimation model on CSSD dataset. TopCoder is selected as target CSSD platform for the study. TopCoder’s development tasks data with development-centric features are extracted, leading to statistical, regression and correlation analysis to justify features’ significance. For effort estimation, 10 ML families with 2 respective techniques are applied to get broader aspect of estimation. Five performance metrices (MSE, RMSE, MMRE, MdMRE, Pred (25) and Welch’s statistical test are incorporated to judge the worth of effort estimation model’s performance. Data analysis results show that selected features of TopCoder pertain reasonable model significance, regression, and correlation measures. Findings of ML effort estimation depicted that best results for TopCoder dataset can be acquired by linear, non-linear regression and SVM family models. To conclude, the study identified the most relevant development features for CSSD platform, confirmed by in-depth data analysis. This reflects careful selection of effort estimation features to offer good basis of accurate ML estimate.

A practitioner's commentary on C. Chan (2009): “Forging a link between research and pedagogy: A holistic framework for evaluating business English materials”

In this commentary, I discuss the value of Chan's (2009) research-informed checklists for evaluating business English materials by providing a practitioner's approach to using the checklists. I adapted the checklists for three different uses. The first was to evaluate the teaching methodology followed in a business English textbook from an ESP series. The second use was as a guide and evaluation tool for my in-house business English material development. The final use was also to support the design and then evaluation of custom-made banking English course materials. In conclusion, I found that adapting these research-informed checklists, based on local needs, creates opportunities for professional development, tailored courses, and transferability to other ESP genres.

Adaptive Security Activities Selection Model Using Multi-Criteria Decision-Making Methods

Adaptive security activities are a list of recommended security activities to be integrated smoothly with the software development life cycle (SDLC) to produce a secure application software. Adaptive security activities are needed due to the emergence of factors and constraints which have been determined as one of the reasons for the underutilisation of security activities implementation, especially in the earlier phase of software development process. Security activities selection models were proposed to select and recommend security activities but the models were focused on certain factors or as a solution for specific constraints, and thus the recommended security activities were not adaptive. Consequently, an adaptive security activities selection (ASAS) model was proposed by combining the factors and constraints faced by the development team in selecting security activities. The model consisted of two integrated multi-criteria decisionmaking (MCDM) methods, namely Analytic Network Process (ANP) and Reference Ideal Method (RIM). ANP was used to prioritise and weight the criteria while RIM was used to measure and evaluate the security activities with the value of constraints in regard to each criterion. To validate the model a case study was performed on four inhouse web application development teams in the Malaysian public sector. The proposed model was able to recommend security activities in the requirement and design phase based on different constraints faced by each of the development teams. The model was adaptive due to its flexibility and ability to change and suit different evolved conditions when recommending the security activities.

EXPLORING EFFICIENCY GROWTH OF ADVANCED TECHNOLOGY-GENERATING SECTORS IN THE EUROPEAN UNION: A STOCHASTIC FRONTIER ANALYSIS

This study investigates the efficiency growth of advanced technology-generating sectors within the European Union (EU). Using a stochastic frontier analysis of annual sector-level panel data from 2000 to 2019, we examine sectoral (NACE two-digit level) and territorial implications. Our findings indicate that technological change was more intense in advanced technology-generating sectors than in other economic sectors, primarily driven by fixed capital investments. However, the impact of in-house research and development varied. Economic sectors such as pharmaceuticals and motor vehicles struggled to improve their production efficiency due to high competition and market specificity. A comparative analysis of EU economies showed a lower level of production efficiency in catching-up economies. Nevertheless, these economies contributed to the shift of the production possibility frontier in certain sectors on the EU level. Therefore, this study contributes to the ongoing scientific discussion on technological innovations in diverse territories, suggesting that less-developed economies could generate technological advancements in specific areas. We also discuss the implications for innovation and industrial policy actions.

Inherently Selective Atomic Layer Deposition for Optical and Sensor Applications: Microreactor Direct Atomic Layer Processing (μDALP™)

In parallel to additive manufacturing leading the revolution in traditional manufacturing, the same principles can revolutionize traditional thin film deposition techniques. Where lithography and vapor phase deposition techniques struggle, for example, with rapid iterations for prototyping or incompatibility with the used chemistry, additive manufacturing can shine. Indeed, several approaches are in development for 3D nanopriting1,2,3.Atomic Layer Deposition, and in more general Atomic Layer Processing, offers a unique opportunity for localized 3D processing/printing due to its two-step process. While simple in theory, due to well-developed examples of Spatial Atomic Layer Deposition (SALD), in practice miniturization of SALD requires substantial effort into the creation of suitable micro-nozzles. Uniquely, ATLANT 3D has developed proprietary Spatial ALD micronozzles, naming the process microreactor Direct Atomic Layer Processing - µDALPTM.The µDALPTM process undergoes the same cyclic ALD process but, thanks to the in-house microreactor development, is only done in a localized area. The microreactor or micronozzle confines the flows of gases used for ALD within a µm-scale area on the substrate, wherein the reactive species adsorb on the surface to deposit one monolayer of the desired material. Similarly, to spatial ALD, the creation of this monolayer then hinges on the movement of the substrate.4 Since the µDALPTM process is based on physical separation, it is theoretically compatible with any ALD process. As such, the material capabilities can match traditional ALD and exceed other special or patterning thin film techniques, such as lithography, which can be costly and time-consuming, especially for rapid prototyping required for innovation.Films deposited with ATLANT 3D technology have been shown to produce high-quality, crystalline, atomically precise thin films.1 It has been used to fabricate temperature (Fig.1) and capacitive sensors with sensitivities that meet or exceed those of devices made using conventional vapor phase deposition techniques.5 Low-cost rapid prototyping facilitated by ATLANT 3D technology of such devices enables design innovation and optimization not possible with other thin film deposition techniques.ATLANT 3D platform provides flexibility in deposition geometry (Fig.2) that enables a range of optical applications that require high-precision fabrication techniques. Optically transparent films can be used as localized thin protective layers for device encapsulation, as well as for atomic corrections of defects. Alternating deposition materials enable multilayer mirror fabrication of custom dimensions. Smooth thickness gradients can be used to manufacture ultrathin optical lenses. Overlapping depositions with discrete steps enable the manufacturing of binary lenses and phase masks. Growth rate enhancement in rastered direct processing mode using ATLANT 3D technology can produce periodic grating structures.1 Conformal coatings on complex surfaces can act as functionalization layers or seed layers for further material deposition through e.g. electrochemical processes.[1] Kundrata I. et al., ALD/ALE 2022 [Int. Conf.], 2022 [2] de la Huerta C. A. M. et al., arXiv, 2020, 0523. [3] Winkler, R. et al., J. Appl. Phys., 2019, 125, 210901[4] Paul Poodt., JVSTA., 2012, 30, 010802[5] Kundrata, I. et al., Small Methods., 2022, 6 (5), 2101546 Figure 1

Agile Software Development Assisted Implementation of a Mentoring Solution in a Large Enterprise

Mentoring and coaching have many forms and formats. Choosing the right one is often challenging because of cost, delays on program launch, concerns with adoption, participation and capacity, overall readiness of mentors, prioritization and how it fits the company’s objectives and culture. As part of talent development, organizational solutions, productivity and automations teams, which aim to develop mentor-mentee (coach-coached) matching engine and overall business process automation of a mentorship program, we had to identify the key deliverables, main features, evaluate existing solutions and then design, develop and operate the system. In this paper we present the in-house development process of a mentoring program software solution, its architecture and operations in trivago from 2018 until 2020.

How does age and gender of the employees influence human resource practices–employee competencies relationship?

PurposeApplying resource-based view and the configurational approach theory, this study seeks to understand the moderating role of age and gender between human resource practices and employee competencies relationship.Design/methodology/approach43 food processing firms of India participated in the study. Applying multilevel approach, the responses of 295 human resource managers and 3,557 employees were used for the analysis.FindingsThe human resource practices–employee competencies relationship was stronger in the case of young employees. Furthermore, the relationship was better in case of male employees over female employees. The results urge for greater attention toward age and gender diversity issues while tailoring human resource practices for enhancing employee skills. This article contributes the human resource management literature by exploring the role of age and gender, which has been used as the control variables as the moderating variables for governing the human resource practices–employee competencies relationship.Practical implicationsSpecial focus can be placed on extensive custom in-house training and development activities. Proper division of work can be done for new employees and experienced employees depending upon their learning capabilities. The firms can do so by either implementing formal or informal organizational structures to achieve full gains. Firms should focus largely on narrowing the development practices adopted for diverse age groups of workforce population. The four practices proposed by the Organization for Economic Cooperation and Development (2006) for ensuring effectiveness of development practices and its impact on old age employee effectiveness and attitude should be put in practice.Originality/valueThe originality of this study lies in its exploration of the intricate interplay among age, gender and human resource practices in shaping employee competencies. By understanding how these factors interact within the human resource practices–employee competencies framework, this research offers a unique perspective on the evolving workforce dynamics. It goes beyond the conventional human resource management strategies to uncover nuanced insights, shedding light on tailored approaches that consider the specific needs and aspirations of diverse employees. This innovative perspective contributes to a more inclusive, efficient and adaptable work environment, enriching both the academic understanding of human resources and the practical implementation of strategies for contemporary organizations.

Facilitating In-House Mobile App Development Within Psychiatric Outpatient Services for Patients Diagnosed With Borderline Personality Disorder: Rapid Application Development Approach.

Mobile app development within mental health is often time- and resource-consuming, challenging the development of mobile apps for psychiatry. There is a continuum of software development methods ranging from linear (waterfall model) to continuous adaption (Scrum). Rapid application development (RAD) is a model that so far has not been applied to psychiatric settings and may have some advantages over other models. This study aims to explore the utility of the RAD model in developing a mobile app for patients with borderline personality disorder (BPD) in a psychiatric outpatient setting. The 4 phases of the RAD model: (1) requirements planning, (2) user design, (3) construction, and (4) cutover, were applied to develop a mobile app within psychiatric outpatient services for patients diagnosed with BPD. For the requirements planning phase, a short time frame was selected to minimize the time between product conceptualization and access within a clinical setting. Evidenced-based interactive content already developed was provided by current staff to enhance usability and trustworthiness. For the user design phase, activity with video themes and a discrete number of functions were used to improve the app functionality and graphical user interface. For the construction phase, close collaboration between clinicians, researchers, and software developers yielded a fully functional, in-house-developed app ready to be tested in clinical practice. For the cutover phase, the mobile app was tested successfully with a small number (n=5) of patients with a BPD. The RAD model could be meaningfully applied in a psychiatric setting to develop an app for BPD within a relatively short time period from conceptualization to implementation in the clinic. Short time frames and identifying a limited number of stakeholders with relevant skills in-house facilitated the use of this model. Despite some limitations, RAD could be a useful model in the development of apps for clinical populations to enable development and access to evidence-based technology.

Teachers’ professional development shaped through self-reflection using video-stimulated recall

Background: Self-reflection is seen to be a key factor to individual improvement and development, and thus commendable of investigating. The challenge however is what tools to use to reflect effectively. This study examined the professional development of in-service Mathematics teachers through self-reflection using Video Stimulated Recall (VSR) as a reflective tool.Aim: The aim of the study was to contribute to the body of knowledge of professional development of teachers through VSR.Setting: This article describes an intervention where VSR was incorporated in two primary schools on the Cape Flats, Western Cape.Method: This study implemented the qualitative research paradigm involving four teachers. Data collection consisted of video recordings of lessons and semi-structured interviews after watching the video recording of their own lessons. A minimum of two cycles of observations and interviews were conducted per teacher.Results: After self-reflection, some of the participants altered their classroom practices to enhance the teaching and learning of mathematics while some reflected superficially. The lack of reflecting on their learners’ mathematical thinking and reasoning might have been ascribed to the limitation of viewing only two recorded lessons, the possible inability of the interviewer to probe the participants further or the participants’ inability or unwillingness to reflect deeper.Conclusion: Video-stimulated recall allowed participants to self-reflect. However, this tool should be used over a longer period to significantly influence practice.Contribution: Video-stimulated recall as a reflective tool can be used as an in-house professional development initiative that is customised to the needs and context of the participants.

Comparative study of SPI success factors in global and in-house environment for large-scale software companies

Background Software process improvement (SPI) is an indispensable phenomenon in the evolution of a software development company that adopts global software development (GSD) or in-house development. Several software development companies do not only adhere to in-house development but also go for the GSD paradigm. Both development approaches are of paramount significance because of their respective advantages. Many studies have been conducted to find the SPI success factors in the case of companies that opt for in-house development. Still, less attention has been paid to the SPI success factors in the case of the GSD environment for large-scale software companies. Factors that contribute to the SPI success of small as well as medium-sized companies have been identified, but large-scale companies have still been overlooked. The research aims to identify the success factors of SPI for both development approaches (GSD and in-house) in the case of large-scale software companies. Methods Two systematic literature reviews have been performed. An industrial survey has been conducted to detect additional SPI success factors for both development environments. In the subsequent step, a comparison has been made to find similar SPI success factors in both development environments. Lastly, another industrial survey is conducted to compare the common SPI success factors of GSD and in-house software development, in the case of large-scale companies, to divulge which SPI success factor carries more value in which development environment. For this reason, parametric (Pearson correlation) and non-parametric (Kendall’s Tau correlation and the Spearman correlation) tests have been performed. Results The 17 common SPI factors have been identified. The pinpointed common success factors expedite and contribute to SPI in both environments in the case of large-scale companies.

Bots2ReC – Analysis of Key Findings for the Application Development of Semi-Autonomous Asbestos Removal

The removal of asbestos from existing buildings is a socially important and challenging renovation process due to the handling of hazardous materials. The EU project Robots to ReConstruction (Bots2ReC) has developed a robotic system for semi-autonomous asbestos removal for apartment buildings. The removal of plaster and tiles and the associated tile adhesive is implemented as a semi-autonomous construction task by mobile manipulators and integrated into the existing construction process. The development is based on a test-driven approach in order to obtain information about the achievable performance and the acceptance of the human operators as early as possible. The identification of the control variables for the respective tools and the embedding in the on-site process flow are named as the main reasons for the test-driven approach. The analysis of selected key findings of the project shows for the developed semantic mapping via mobile robot that a minimal, application-specific data format favours an efficient overall process control via task planning up to execution. In the development of mobile bases for the application, it can be shown that a holonomic drive is preferable to a differential drive due to the partly narrow and angled parts of the building. To carry out the intended processes and to guide the automated power tools, the in-house development of serial manipulators is necessary, since the combination of the required working space with the occurring weight and process forces cannot be solved within the requirements by an industrial manipulator. Finally, the main benefit of this papers contribution is seen in the transferable outcomes to other on-site automation projects. 

A Framework for Automated Exploration of Trojan Attack Space in FPGA Netlists

Field Programmable Gate Arrays (FPGAs) provide a flexible compute platform for quick prototyping or hardware acceleration in diverse application domains. However, similar to the global semiconductor life-cycle in the modern supply chain, FPGA-based product development includes processes and interactions with potentially untrusted parties outside the traditional scrutiny of a completely in-house development cycle. An untrusted party or software can maliciously alter a hardware intellectual property (IP) block mapped to an FPGA device during various stages of the FPGA life-cycle. Such malicious alterations, also known as hardware Trojan attacks, have garnered significant research into their detection and prevention in the context of application-specific integrated circuit (ASIC) design flow. However, Trojan attacks in FPGAs have not enjoyed this same attention. Designers often rely on mapping ASIC-specific solutions and evaluation benchmarks to the FPGA domain, which leaves much of the FPGA-specific Trojan space uncovered. We note that the distinctive business model as well as the architectural configurations of FPGAs present unique opportunities for Trojan attacks to an adversary. To this end, we introduce a framework to automatically explore the hardware Trojan attack space in FPGA netlists. It is capable of inserting different types of FPGA-specific Trojans in a netlist enabling rapid exploration of potential Trojan attacks in an FPGA design: soft-template, monolithic, and distributed dark silicon. Soft template Trojans use behavioral templates with random synthesis constraints to increase Trojan structural diversity. Monolithic and distributed dark silicon Trojans use the under-utilized input space (FPGA dark silicon) in FPGA primitives to realize Trojans with effectively zero area and power footprint. Further optimizations are also presented to remove any potential delay impact. We then generate over 1300 Trojan-inserted benchmarks using each of the introduced FPGA Trojan classes, and compare their impact on utilization, delay, and power. Finally, we evaluate our Trojans against a machine learning-based Trojan detection to highlight their evasiveness.

Open-source Python library for modeling coupled thermo-hydro-mechanical (THM) processes

Abstract. The interactions between temperature, fluids, and mechanical properties in a repository system are essentially described scientifically by coupled thermo-hydro-mechanical (THM) processes. THM modeling, i.e., the prediction of the behavior of materials under different conditions, is the fundamental numerical tool here. The confident handling and deep understanding of numerical computation methods is thus the prerequisite for performing and evaluating preliminary safety analyses in the site selection process. At the Federal Office for the Safety of Nuclear Waste Management (BASE), a software library for the simulation of coupled THM processes is currently being developed. The main goal of the in-house development is an open-source toolbox in the scripting language Python and is motivated by several long-term sub-goals: targeted development of expertise within BASE regarding numerical modeling of safety-relevant aspects in the long-term safety analyses; diversification of the testing capabilities regarding the preliminary safety investigations by means of an in-house, independent modeling software; foundation of a library of known benchmarks and evaluation examples for the comparison of different software tools; documentation and processing of basic THM scenarios for internal or, if necessary, public technical training. The focus of this development is on creating a toolbox that is easy to use and at the same time highly flexible. The main methodical aspects are as follows: building a new library based on the pyGIMLi pre- and postprocessing framework (Rücker et al., 2017); creating a finite-element reference implementation in the Python scripting language for maximal transparency; creating an easy-to-use interface to the solution of the weak formulation for the finite-element theory with expressions of a symbolic manner allowing maximal flexibility; defining an interface to allow for the integration of alternative, third-party high-performance libraries; creating a collection of Jupyter notebooks of well-documented test cases and benchmarks. Choosing the open-source approach ensures the best possible transparency and, in the long term, also allows the provision of appropriately quality-assured and documented simulation tools to the public. The presented poster shows the current development status of the software library and the currently implemented quality assurance concepts and gives an outline of the potential applications of the library.

Only the Ugly Face? A Theoretical Model of Brand Dilution

This paper challenges two common views of brand dilution: first, that it is exclusively the unintended consequence of a poorly executed strategy of brand extension and, second, that its likelihood is heightened by brand licensing. Using a new theoretical model, we show that brand dilution can be seen not just as an unfortunate development to be avoided, but as an opportunity to monetize the brand. We further show that, at the relevant margin, switching from in-house development to licensing reduces the risk of brand dilution. The model offers a novel perspective on some important managerial choices and generates a series of empirically testable hypotheses. This paper was accepted by Dmitri Kuksov, marketing. Funding: Financial support from PRIN 20157NHSTP004 is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.00852 .

Feedback error-state Kalman filter with time-delay compensation for hydroacoustic-aided inertial navigation of underwater vehicles

This article is intended as a tutorial to assist engineers who want to develop and implement low-cost underwater vehicle inertial navigation systems (INS) aided by time-delayed hydroacoustic position measurements. A discrete-time unit quaternion error-state Kalman filter (ESKF) is used for sensor fusion. The ESKF is implemented as a feedback algorithm with reset functionality. This is motivated by the need for long-endurance autonomous underwater vehicles (AUVs). Proprietary navigation systems do not allow users to add more measurement equations to the code if additional sensors are available. However, the open-source filter architecture presented in the article provides for this. The article also aims to make in-house development of strapdown INS accessible and affordable for vendors of low-cost AUV systems. Finally, a case study of an AUV with a standard sensor suite is included to demonstrate the performance of the ESKF aided by time-delayed position measurements.