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Drawing on the theory of dogmatism and personality traits, this research examines the consumers' shopping behavior and intentions. We propose a model, which incorporates the precepts of stubbornness and retail purchasing conduct. Data were gathered from 446 shoppers in India and analyzed using partial least squares-structural equation modelling (PLS-SEM). The findings indicate that consumers' personality, purchaser conduct, narrowing conduct, and dependability influence their buying behavior. Moreover, consumers’ purchasing goals are influenced by assurance, customization, brand value, and social appeal. The study has practical implications for marketing managers who are focusing on customers with dogmatic behavior.

This study aimed to develop and evaluate the performance of a service system platform based on the Internet of Things (IoT) for monitoring nutritional deficiencies in plants and providing fertilizer recommendations. There are two distinct differences between this work and previous ones; namely, this service system platform has been developed based on IoT using a system engineering approach and its performance has been evaluated using dependability. We have successfully developed and integrated a service system platform and chlorophyll meter that is based on IoT. We have also successfully tested the performance of the service system platform using the JMeter software. The dependability value measured from the five tested variables (reliability, availability, integrity, maintainability, and safety) showed a value of 0.97 which represents a very good level of system confidence in not failing to deliver services to users under normal operational conditions. From a future perspective, this platform can be used as an alternative service to monitor nutrient deficiencies in plants and provide fertilization recommendations to increase yields, reduce fertilizer costs, and prevent the use of excessive fertilizers, which can cause environmental pollution.

Recent research has shown interest in adopting the RISC-V processors for high-reliability electronics, such as aerospace applications. The openness of this architecture enables the implementation and customization of the processor features to increase their reliability. Studies on hardened RISC-V processors facing harsh radiation environments apply fault tolerance techniques in the processor core and peripherals, exploiting system redundancies. In prior work, we present a hardened RISC-V System-on-Chip (SoC), which could detect and correct radiation-induced faults with limited fault awareness. Therefore, in this work, we propose solutions to extend the fault observability of the SoC implementation by providing error detection and monitoring. For this purpose, we introduce observation features in the redundant structures of the system, enabling the report of valuable information that supports enhanced radiation testing and support the application to perform actions to recover from critical failures. Thus, the main contribution of this work is a solution to improve fault awareness and the analysis of the fault models in the system. In order to validate this solution, we performed complementary experiments in two irradiation facilities, comprehending atmospheric neutrons and a mixed-field environment,in which the system proved to be valuable for analyzing the radiation effects on the processor core and its peripherals.In these experiments, we were able to obtain a range of error reports that allowed us to gain a deeper understanding of the faults mechanisms, as well as improve the characterization of the SoC.

The transmission system plays a vital role in the electric power system as it links load centers with power generation and, so, it is mandatory to protect this system from any abnormal conditions. This paper proposes a novel reliable fault detection and location technique based on optimally allocated phasor measurement units. The optimal phasor measurement units allocation guarantees the full observability of the system including all transmission lines, which are impeded in the protection zones. The proposed fault detection and location technique depends on the measured positive sequence components. The proposed technique has essential advantage due to its generalization to be valid for different areas’ sizes and configurations. The detection technique relies on calculated admittance, while the fault location is independent on fault resistance. For validation of the proposed technique, it is applied on the IEEE 14-bus system simulated using Matlab/Simulink® software package. Various faults are simulated considering fault resistance. From the simulated fault cases, the proposed technique proves its security against external faults and the dependability with internal faults.

Virtualization is gaining attraction in the industry as it promises a flexible way to integrate, manage, and re-use heterogeneous software components with mixed-criticality levels, on a shared hardware platform, while obtaining isolation guarantees. This work surveys the state-of-the-practice of real-time virtualization technologies by discussing common issues in the industry. In particular, we analyze how different virtualization approaches and solutions can impact isolation guarantees and testing/certification activities, and how they deal with dependability challenges. The aim is to highlight current industry trends and support industrial practitioners to choose the most suitable solution according to their application domains., Accepted for publication in Elsevier Future Generation Computer Systems

The Emergency Diesel Generator (EDG) is a critical and essential part of the Nuclear Power Plant (NPP). Due to past catastrophic disasters, critical systems of NPP like EDG are designed to meet high dependability requirements. Therefore, we propose a framework for the dynamic reliability assessment using the Fault Tree and the Dynamic Bayesian Network. In this framework, the information of the component's failure probability is updated based on observed data. The framework is powerful to perform qualitative as well as quantitative analysis of the system. The validity of the framework is done by applying it on several NPP systems.

Autonomy of systems has been gaining increasing attention from scientists and engineers in various disciplines such as robotics, artificial intelligence, embedded systems, and control. However, there are serious challenges on the way of designing and adopting such systems, which haven’t, in our perspective, received sufficient attention yet. In this position paper, we review some of those challenges and present potential approaches of coping with them. Moreover, we highlight topics that require immediate attention and research efforts of the community. In particular, we propose three approaches: (i) More dependable autonomy using deterministic methods that can provide similar controllability, dependability, and traceability as that of traditional systems. Among such solutions is providing guarantee bands as opposed to guaranteed narrow operation points. (ii) Orthogonal autonomy adds autonomy in the extra-functional plane of the system. (iii) Expressive system design allows autonomous systems to trace and explain their decisions and reactions even though they may be using less deterministic tools.

Sixth-generation communication networks must be highly dependable due to the foreseen connectivity of critical infrastructures through them. Dependability is a compound metric of four well-known concepts—reliability, availability, safety, and security. Each of these concepts have unique consequences for the success of 6G technologies and applications. Using these concepts, we explore the dependability of 6G networks in this article. Due to the vital role of machine learning in 6G, the dependability of federated learning, as a distributed machine learning technique, has been studied. Since mission-critical applications (MCAs) are highly sensitive in nature, needing highly dependable connectivity, the dependability of MCAs in 6G is explored. Henceforth, this article provides important research directions to promote further research in strengthening the dependability of 6G networks.

Sixth-generation communication networks must be highly dependable due to the foreseen connectivity of critical infrastructures through them. Dependability is a compound metric of four well-known concepts—reliability, availability, safety, and security. Each of these concepts have unique consequences for the success of 6G technologies and applications. Using these concepts, we explore the dependability of 6G networks in this article. Due to the vital role of machine learning in 6G, the dependability of federated learning, as a distributed machine learning technique, has been studied. Since mission-critical applications (MCAs) are highly sensitive in nature, needing highly dependable connectivity, the dependability of MCAs in 6G is explored. Henceforth, this article provides important research directions to promote further research in strengthening the dependability of 6G networks.

Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to selfish miners’ computing power, attack triggering, and honest miners’ recovery capability. The conclusion made based on this research may contribute to the design of resilience algorithms to enhance the self-defense and robustness of cryptocurrency systems.

Recent technological advances and manufacturing paradigm evolutions in industrial settings will dramatically increase the complexity of automation control systems. Traditional solutions to the software development of low-level control kernels (e.g., numerical control kernel, motion control kernel, and real-time communication tasks) are unable to cope effectively with such complexity due to an inadequate level of abstraction and challenges for dependability. This article presents a formal semantics integrated model-driven design approach as a holistic solution. A domain-specific modeling language (DSML) is specified based on the adaption of IEC 61,499 architecture, along with the extensions of task model, task-to-resource allocation, and nonfunctional specification. Both formal structural and behavioral semantics of the proposed DSML are then explicitly defined. Design-time formal verification is also achieved by automated model transformations. A metaprogrammable environment is adopted to facilitate flexible modeling, verification, and code generation. A case study is demonstrated on implementing a prototype computer numerical control (CNC) system using the proposed solution.

In order to provide performance increases despite the end of Moore's law and Dennard scaling, architectures aggressively exploit data- and thread-level parallelism using billions of transistors on a single chip, enabled by extreme geometry miniaturization. A resulting challenge is the control, optimization, and reliable operation of such complex multiprocessing architectures. Modern and future systems will be required to operate under multi-dimensional variability: from varying workload, quality-of-service (QoS) goals, and non-functional requirements to varying environmental and operating conditions. A trend has recently emerged to abstract such complex multiprocessing architectures as self-aware factories whose resources are monitored, configured and their use is planned during runtime. In this paper, we present the Information Processing Factory (IPF) paradigm for mixed-criticality. We introduce its 5-layer hierarchical organization and a system configuration framework that ensures that the strict requirements of the safety-critical functions are always met while dynamically managing and optimizing the mixed-critical system at runtime. We illustrate the application of (IPF) in heterogeneous domains with two representative use-cases (healthcare and automotive), investigate the use of (IPF) to achieve long-term dependability, and highlight the open challenges. Experimental results report the reliability levels achievable with the proposed paradigm.

Recommendation systems are gaining popularity with the proliferation of the Internet of People (IoP). The popularity and use of online social networks facilitate integrating these social relationships with recommender systems under a single framework of IoP. This article proposes a new approach for item recommendation based on the diffusion method that combines user relationships in social networks with user-item relationships derived from the IoP. Especially, a resource redistribution process is explored in the user-object network that gives mass diffusion a higher recommendation accuracy and heat conduct a greater diversity by considering the social degree of users whilst calculating the user degree in the network. A tuning parameter is introduced to adjust the weight of resources that the objects finally receives from users based on their social relationships. Finally, extensive experiments conducted on the real-world datasets which contain friendship relationships, demonstrate the efficiencies of our proposed method in achieving notable performance improvements in terms of the recommendation accuracy, service diversity, and practical dependability.

Wireless sensor networks face numerous limitations. Security and Privacy are the two most essential parameters that require consideration in wireless sensor networks for conveying responsive information amid basic applications. High density and limited communication range of sensor nodes, forwarding packets in sensor networks have caused the performance of during multi-hop data transmission. Hence communication with different devices these days are not secure, due to the absence of centralized monitoring and overprotective requirements. This paper is related to speak about Distributed Denial of Service which debilitates the ability of the network and the data being transmitted. The earlier system guarantees the WSN through a self arranged and confined procedure between the nodes in the sensor environment. Here, the authors present the Centralized Detect Eliminate and Control algorithm for authorization and centralized monitoring component to discover the node that has turned into a victim node and to get rid of the information communicated to the fatality node from the neighbour nodes. Overprotective of the communication between the nodes leads to dependability. The simulation results improve the malicious node detection rate and increase the various parameters like throughput and reduce the average delay. This leads to, the overall detection rate built, eventually enhancing the parameters of the network environment.

He Chen,1 Ming Han,2 Hui Jing,1 Zhao Liu,1 Haitao Shang,1 Qiucheng Wang,1 Wen Cheng1 1Department of Ultrasound, Harbin Medical University Cancer Hospital, Harbin City, Heilongjiang Province, People’s Republic of China; 2Department of General Surgery, Heji Hospital of Changzhi Medical College, Changzhi City, Shanxi Province, People’s Republic of ChinaCorrespondence: Wen Cheng; Qiucheng WangDepartment of Ultrasound, Harbin Medical University Cancer Hospital, No. 150, Haping Road, Nangang District, Harbin City, 150081, Heilongjiang Province, People’s Republic of ChinaTel +86 13313677182; +86 13836134350Fax +86 45185718392Email hrbchengwen@163.com; haerbincss@126.comPurpose: This study aimed to evaluate the dependability of automated breast ultrasound (ABUS) compared with handheld ultrasound (HHUS) and mammography (MG) on the Breast Imaging Reporting and Data System (BI-RADS) category and size assessment of malignant breast lesions.Patients and Methods: A total of 344 confirmed malignant lesions were recruited. All participants underwent MG, HHUS, and ABUS examinations. Agreements on the BI-RADS category were evaluated. Lesion size assessed using the three methods was compared with the size of the pathological result as the control. Regarding the four major molecular subtypes, correlation coefficients between size on imaging and pathology were also evaluated.Results: The agreement between ABUS and HHUS on the BI-RADS category was 86.63% (kappa = 0.77), whereas it was 32.22% (kappa = 0.10) between ABUS and MG. Imaging lesion size compared to pathologic lesion size was assessed correctly in 36.92%/52.91% (ABUS), 33.14%/48.84% (HHUS) and 33.44%/43.87% (MG), with the threshold of 3 mm/5 mm, respectively. The correlation coefficient of size of ABUS-Pathology (0.75, Spearman) was statistically higher than that of the MG-Pathology (0.58, Spearman) with P < 0.01, but not different from that of the HHUS-Pathology (0.74, Spearman) with P > 0.05. The correlation coefficient of ABUS-Pathology was statistically higher than that of MG-Pathology in the triple-negative subtype, luminal B subtype, and luminal A subtype (P< 0.01).Conclusion: The agreement between ABUS and HHUS in the BI-RADS category was good, whereas that between ABUS and MG was poor. ABUS and HHUS allowed a more accurate assessment of malignant tumor size compared to MG.Keywords: automated breast ultrasound, hand-held ultrasound, mammography, breast imaging reporting and data system category, size assessment

This research is motivated by efforts to improve effective educational services so that they are able to face developments and competition that is so tight and become an institution that is able to survive, and play a good role, even more advanced. The curriculum can be said to be the heart of education because of its central position in all school activities. The Islamic education curriculum is very interesting to study because ideally, it should contain material that provides coverage for life in this world and in the hereafter. This study aims to analyze and find the concept of curriculum design in realizing an effective school. This study uses a qualitative approach, the type of case study with a multi-case design. Data collection techniques used in-depth interviews, participant observation, and documentation. Data analysis uses the Miles Huberman model of data reduction, data presentation, verification, and drawing conclusions. Data were analyzed from single and cross-case data. Data validity techniques through credibility, transferability, dependability, and confirmability. The results showed that the curriculum design in schools was prepared based on the school's vision, mission, and goals, which were discussed in teacher and education staff working meetings involving committees and foundations. The results of the curriculum design are subject-centered design for intracurricular activities, and with the type of learner-centered design for extracurricular activities. Then, the contents of the curriculum consist of the National Curriculum, local content, and an adequate internal (typical) Islamic curriculum.

Advances in microelectronics have enabled smaller technical nodes, lower threshold voltages, and greater working frequencies. Even though VLSI circuit performance and power consumption have improved as a result, the reliability of the designs has suffered. A fall in noise resistance and an increase in uncertainty from multiple sources of variability make circuits more vulnerable as technology scales down. Fault tolerant techniques are commonly used in safety-critical applications. Three-dimensional electrical devices like double gate, tri-gate, and nanowire field-effect transistors (FETs) give an alternative approach since they regulate the device channel better electrostatically. In this paper, a new form of FinFET with asymmetric gate and source/drain connections is developed, and its simulation results are shown. Asymmetric FinFETs exhibit better short-channel behavior when the current density is increased, according to the results of the benchmarking. High aspect ratio FinFETs give greater current per area while demanding significantly fewer horizontal geometry constraints, making them ideal for situations where conventional scaling has hit its physical limits. The suggested multigate FinFET provides improved performance in low-power and high-frequency applications, according to the experimental results. The work report also includes an evaluation of the proposed multigate FinFET’s dependability.

This study aims to describe the Management of Education Quality Improvement at the Islamic Junior High School Terpadu Daar Al Uluum Asahan. This research uses a qualitative research type, with a phenomenological approach. The research data collection is obtained by using observation, interview and documentation techniques. To check the validity of the data using triangulation techniques, namely credibility, transferability, dependability, and confirmability. Steps to analyze data using data analysis model Milles and Hubberman, namely reducing data, presenting data and then concluding. The results of the research are (1) Planning for improving the quality of education is carried out through meetings involving school principals, assistant principals 1 and 2, along with teachers. (2) The organization of improving the quality of education is carried out by establishing a school organizational structure and making clear job details or division of labor, then carrying out clear and directed work coordination and monitoring. (3) The implementation of improving the quality of education is carried out after the planning and organizing process. Principals, assistant principals, administrative staff and teachers have realized and implemented various planned programs, in order to achieve good, superior and quality education. (4) Supervision of improving the quality of education is carried out as an effort to observe, examine and monitor the quality of education so that efforts to improve the quality of education are being carried out in accordance with the predetermined plan, in order to achieve good, superior and quality education.Keyword: Management, Improvement, Quality of Education

With the present study I investigated the sources of score variance and dependability in a local oral English proficiency test for potential international teaching assistants (ITAs) across four first language (L1) groups, and suggested alternative test designs. Using generalizability theory, I examined the relative importance of L1s (i.e., Indian, Korean, Mandarin, and Spanish), examinees, tasks, and ratings to score variability, and estimated dependability across the L1s. The analyses identified examinees as the largest contributor, which is important for high dependability and validity arguments for test scores. Effects of ratings and tasks were small, but L1 effects on score variance were considerable, with the Indian group’s dependability lowest. Unlike previous generalizability theory studies on L1 effects, however, further analyses revealed that the L1 effects highly likely reflect proficiency differences rather than strong bias when comparing the percent agreement of the ratings, external criteria of examinee English proficiency, and underlying score distributions. I discuss the proficiency differences related to varied socio-linguistic contexts of using and learning English. Lastly, I suggest an alternative design with fewer items and one additional rating for improved dependability. Considering multiple test purposes specific to ITA testing (i.e., efficiency, construct representation, formative advantages), I propose a flexible approach.

Instrumentation and Control systems (I&C) play a significant role in nuclear power plants (NPP) and other safety critical systems (SCS). We have conducted a rigorous study and discussions with experienced practitioners worldwide the strategy for the development of I&C systems to investigate the several aspects related to their dependability. We discussed with experienced practitioners that work on nuclear domain with the intention of knowing their approach, they use day-to-day for the development of such systems. The aim of this research is to obtain to provide guidance to those building I&C systems of NPP and have implications on state engineering licensure boards, in the determination of legal liability, and in risk assessment for policymakers, corporate governors, and insurance executives.

Many data-driven software systems present dependability challenges caused by the distribution and dynamicity of their application environments. We investigate machine learning-driven construction techniques combined with pattern-based architecture, showing that system dependability is linked to data and function quality.

Today’s scientific data analysis very often requires complex Data Analysis Workflows (DAWs) executed over distributed computational infrastructures, e.g., clusters. Much research effort is devoted to the tuning and performance optimization of specific workflows for specific clusters. However, an arguably even more important problem for accelerating research is the reduction of development, adaptation, and maintenance times of DAWs. We describe the design and setup of the Collaborative Research Center (CRC) 1404 “FONDA -– Foundations of Workflows for Large-Scale Scientific Data Analysis”, in which roughly 50 researchers jointly investigate new technologies, algorithms, and models to increase the portability, adaptability, and dependability of DAWs executed over distributed infrastructures. We describe the motivation behind our project, explain its underlying core concepts, introduce FONDA’s internal structure, and sketch our vision for the future of workflow-based scientific data analysis. We also describe some lessons learned during the “making of” a CRC in Computer Science with strong interdisciplinary components, with the aim to foster similar endeavors.

Rising aggressive virus pandemics urge to conduct studies on dependability and security of modern computing systems to secure autonomous and continuous operations of healthcare systems. In that regard, we propose to quantify dependability and security measures of an Internet-of-Medical Things (IoMT) infrastructure relied on an integrated physical architecture of cloud/fog/edge (CFE) computing paradigms in this article. We propose a reliability/availability quantification methodology for the IoMT infrastructure using a hierarchical model of three levels: 1) fault tree (FT) of overall IoMT infrastructure consisting of CFE member systems; 2) FT of subsystems within CFE member systems; and 3) continuous-time Markov chain (CTMC) models of components/devices in the subsystems. We incorporate a number of failure modes for the underlying subsystems, including Mandel-bug related failures and non-Mandel bugs related failure, as well as failures due to cyber-security attacks on software subsystems. Five case-studies of configuration alternation and four operational scenarios of the IoMT infrastructure are considered to comprehend the dependability characteristics of the IoMT physical infrastructure. The metrics of interest include reliability over time, steady state availability (SSA), sensitivity of SSA wrt. selected mean time to failure—equivalent (MTTFeq) and mean time to recovery—equivalent (MTTReq), and sensitivity of SSA wrt. frequencies of cyber-security attacks on software subsystems. The analysis results help comprehend operational behaviors and properties of a typical IoMT infrastructure. The findings of this study can improve the design and implementation of real-world IoMT infrastructures consisting of cloud, fog, and edge computing paradigms.

The problem of regression model building of equipment failure rate using datasets containing information on number of failures of recoverable systems and measurements of technological and operational factors affecting the reliability of production system is considered. This problem is important for choosing optimal strategy for preventive maintenance and restoration of elements of process equipment, which, in turn, significantly affects the efficiency of production management system. From a practical point of view, of greatest interest is the development of methods for regression models building to assess the impact of various technological and operational factors controlled during system operation on failure rate. The usual approach to regression models construction involves preselecting the model structure in the form of a parameterized functional relationship between failure rate and affecting technological variables followed by statistical estimation of unknown model parameters or training the model on datasets of measured covariates and failures.The main problem lies precisely in the choice of model structure, the complexity of which should correspond to amount of data available for training model, which in the problem of failure rate modeling is greatly complicated by lack of a priori information about its dependence on affecting variables. In this work, such a problem is solved using machine learning methods, namely, kernel ridge regression, which makes it possible to effectively approximate complex nonlinear dependences of equipment failure rate on technological factors, while there is no need to pre-select the model structure. Preliminary aggregation of data by combination of factor and cluster analysis can significantly simplify model structure. The proposed technique is illustrated by solving a practical problem of failure rate model building for semiconductor production equipment based on real data., Розглянуто задачу побудови регресійної моделі інтенсивності відмов обладнання з використанням наборів даних, що містять інформацію про кількість відмов відновлюваних систем та вимірювання технологічних і експлуатаційних факторів, що впливають на надійність виробничої системи. Ця проблема є важливою для вибору оптимальної стратегії профілактичного ремонту та відновлення елементів технологічного обладнання, що, у свою чергу, суттєво впливає на ефективність системи управління виробництвом. З практичної точки зору найбільший інтерес представляє розробка методів побудови регресійних моделей для оцінки впливу на інтенсивність відмов різноманітних технологічних та експлуатаційних факторів, контрольованих під час роботи системи. Звичайний підхід до побудови регресійних моделей передбачає попередній вибір структури моделі у формі параметризованого функціонального зв’язку між інтенсивністю відмов і технологічними змінними з наступною статистичною оцінкою невідомих параметрів моделі або навчанням моделі на наборах даних виміряних коваріат і відмов. Основна проблема полягає саме у виборі структури моделі, складність якої повинна відповідати кількості даних, доступних для навчання моделі, що в задачі моделювання інтенсивності відмов значно ускладнюється відсутністю апріорної інформації про її залежність від впливаючих змінних. У даній роботі така задача вирішується за допомогою методів машинного навчання, а саме ядерної гребневої регресії, що дає змогу ефективно апроксимувати складні нелінійні залежності інтенсивності відмов обладнання від технологічних факторів, при цьому немає необхідності попереднього вибору структури моделі. Попереднє агрегування даних шляхом поєднання факторного та кластерного аналізу може значно спростити структуру моделі. Пропонована методика проілюстрована розв’язанням практичної задачі побудови моделі інтенсивності відмов обладнання для виробництва напівпровідників на основі реальних даних.

Perception, localization, planning, and control, high-level functions often organized in a so-called pipeline, are amongst the core building blocks of modern autonomous (ground, air, and underwater) vehicle architectures. These functions are increasingly being implemented using learning-enabled components (LECs), i.e., (software) components leveraging knowledge acquisition and learning processes such as deep learning. Providing quantified component-level assurance as part of a wider (dynamic) assurance case can be useful in supporting both pre-operational approval of LECs (e.g., by regulators), and runtime hazard mitigation, e.g., using assurance-based failover configurations. This paper develops a notion of assurance for LECs based on i) identifying the relevant dependability attributes, and ii) quantifying those attributes and the associated uncertainty, using probabilistic techniques. We give a practical grounding for our work using an example from the aviation domain: an autonomous taxiing capability for an unmanned aircraft system (UAS), focusing on the application of LECs as sensors in the perception function. We identify the applicable quantitative measures of assurance, and characterize the associated uncertainty using a non-parametric Bayesian approach, namely Gaussian process regression. We additionally discuss the relevance and contribution of LEC assurance to system-level assurance, the generalizability of our approach, and the associated challenges., Comment: 8 pp, 4 figures, Appears in the proceedings of EDCC 2019

The study aimed to identify and analyse methods for establishing external communication between humans and autonomous/teleoperated machines/vehicles using various Human-Machine Interfaces (HMIs). The study was divided into three phases. The purpose of the first phase was to identify and highlight previously tested/researched methods for establishing external communication by conducting a literature review. The findings from the literature review were categorised into six points of interest: machine indications, test delivery methods, HMI technologies/types, symbols, textual/numerical messages, and colours associated with different indications. Based on these findings, four HMIs (projection, display, LED-strip, and auditory) were selected for evaluation in a virtual reality environment for the second phase of the study, which has the purpose of identifying which of the human-machine interfaces can effectively communicate the intentions of autonomous/teleoperated machines to humans. The results of phase two indicate that the participants preferred projection as the most effective individual HMI, and when given the option to combine two HMIs, projection combined with auditory was the most preferred combination. The participants were also asked to pick three HMIs of their choosing, resulting in the projection, display and audible HMI combination being the preferred option. The evaluation of HMIs in a virtual reality environment contributes to improving dependability and identifying usability issues. The objective of the third and final phase was to gather all the findings from the previous phases and subsequently refine the report until it was considered finalised. Future work includes enhancing the realism of the VR environment, refining machine behaviour and scenarios, enabling multiple participants to simultaneously interact with the environment, and exploring alternative evaluation methods. Addressing these areas will lead to more realistic evaluations and advancements in human-machine interaction research.

This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing dependability based on architectural models of software-intensive systems early in development, (ii) decomposition and composition of modelling languages and analysis techniques to enable more flexibility in evolution, and (iii) bridging the divergent levels of abstraction between data of the operation phase, architectural models and source code of the development phase.

Voting is prominently an important part of democratic societies, and its outcome may have a dramatic and broad impact on societal progress. Therefore, it is paramount that such a society has extensive trust in the electoral process, such that the system’s functioning is reliable and stable with respect to the expectations within society. Yet, with or without the use of modern technology, voting is full of algorithmic and security challenges, and the failure to address these challenges in a controlled manner may produce fundamental flaws in the voting system and potentially undermine critical societal aspects. In this thesis, we argue for a development process of voting systems that is rooted in and assisted by formal methods that produce transparently checkable evidence for the guarantees that the final system should provide so that it can be deemed trustworthy. The goal of this thesis is to advance the state of the art in formal methods that allow to systematically develop trustworthy voting systems that can be provenly verified. In the literature, voting systems are modeled in the following four comparatively separable and distinguishable layers: (1) the physical layer, (2) the computational layer, (3) the election layer, and (4) the human layer. Current research usually either mostly stays within one of those layers or lacks machine-checkable evidence, and consequently, trusted and understandable criteria often lack formally proven and checkable guarantees on software-level and vice versa. The contributions in this work are formal methods that fill in the trust gap between the principal election layer and the computational layer by a reliable translation of trusted and understandable criteria into trustworthy software. Thereby, we enable that executable procedures can be formally traced back and understood by election experts without the need for inspection on code level, and trust can be preserved to the trustworthy system. The works in this thesis all contribute to this end and consist in five distinct contributions, which are the following: (I) a method for the generation of secure card-based communication schemes, (II) a method for the synthesis of reliable tallying procedures, (III) a method for the efficient verification of reliable tallying procedures, (IV) a method for the computation of dependable election margins for reliable audits, (V) a case study about the security verification of the GI voter-anonymization software. These contributions span formal methods on illustrative examples for each of the three principal components, (1) voter-ballot box communication, (2) election method, and (3) election management, between the election layer and the computational layer. Within the first component, the voter-ballot box communication channel, we build a bridge from the communication channel to the cryptography scheme by automatically generating secure card-based schemes from a small formal model with a parameterization of the desired security requirements. For the second component, the election method, we build a bridge from the election method to the tallying procedure by (1) automatically synthesizing a runnable tallying procedure from the desired requirements given as properties that capture the desired intuitions or regulations of fairness considerations, (2) automatically generating either comprehensible arguments or bounded proofs to compare tallying procedures based on user-definable fairness properties, and (3) automatically computing concrete election margins for a given tallying procedure, the collected ballots, and the computed election result, that enable efficient election audits. Finally, for the third and final component, the election management system, we perform a case study and apply state-of-the-art verification technology to a real-world e-voting system that has been used for the annual elections of the German Informatics Society (GI – “Gesellschaft für Informatik”) in 2019. The case study consists in the formal implementation-level security verification that the voter identities are securely anonymized and the voters’ passwords cannot be leaked. The presented methods assist the systematic development and verification of provenly trustworthy voting systems across traditional layers, i.e., from the election layer to the computational layer. They all pursue the goal of making voting systems trustworthy by reliable and explainable formal requirements. We evaluate the devised methods on minimal card-based protocols that compute a secure AND function for two different decks of cards, a classical knock-out tournament and several Condorcet rules, various plurality, scoring, and Condorcet rules from the literature, the Danish national parliamentary elections in 2015, and a state-of-the-art electronic voting system that is used for the German Informatics Society’s annual elections in 2019 and following.

Supervisor:神田 陽治, 先端科学技術研究科, 博士

To improve the operating dependability of a generalized power active distribution network, a multiobjective optimal scheduling approach based on game theory is proposed. The active distribution network's multistakeholder coordinated and optimal dispatching mode is then established, and the game interaction between various stakeholders in the generalized power active distribution network is evaluated. Using the multistakeholder game coordinated and optimal dispatching strategy, manage and regulate the distribution firms, distributed generation operators, and users engaging in demand response in the active distribution network, to guarantee that the distribution system runs smoothly and fairly. The rate of renewable energy usage, network loss, and user satisfaction are all factored into the multiobjective optimum scheduling objective function of a generalized power active distribution network. Using the multistakeholder game coordinated and optimal dispatching strategy, manage and regulate the distribution firms, distributed generation operators, and demand response participants in the active distribution network, to make sure the distribution system runs smoothly and equitably. Taking into account the rate of renewable energy usage, network loss, and user satisfaction, a multiobjective optimum scheduling objective function for a generalized power active distribution network is thus created.

PurposeThe study aims to examine a discrepant industrial case that demonstrates how to achieve economies of scale with additive manufacturing (AM), thereby expanding the scope of AM beyond high-variety, customised production contexts.Design/methodology/approachAbductive reasoning is applied to analyse a case of using AM to compete with conventional production, winning a contract to supply 7,700,000 products. Comparing this case to existing theories and contemporary practices reveals new research directions and practical insights.FindingsEconomies of scale were realised through a combination of technological innovation and the adoption of operations management practices atypical of AM shops (e.g. design for volume, low-cost resource deployment and material flow optimisation). The former improved AM process parameters in terms of time, cost and dependability; the latter improved the entire manufacturing system, including non-AM operations/resources. This system-wide improvement has been largely overlooked in the literature, where AM is typically viewed as a disruptive technology that simplifies manufacturing processes and shortens supply chains.Originality/valueIt is empirically shown that an AM shop can achieve economies of scale and compete with conventional manufacturing in high-volume, standardised production contexts.

The primary goal of any prediction model is an accurate estimation. Software reliability is one of the software organization's major research priorities. One of the quantitative indicators of software quality is software reliability. The Software Reliability Model is used to assess the reliability at various stages of testing. The purpose of this work is to investigate the software's dependability using time-series modeling, which is the most efficient tool for evaluating its predictive power. A fault prediction model based on categorizing faults for measuring software reliability known as Seasonal-ARIMA (S-ARIMA) is proposed in this work. The significant attribute for complex software applications is to ensure software reliability and fault tolerance. However, these attributes would inculcate additional overheads such as added costs, implementation delay, and the representation of software solution providers. Therefore, the corporation needs to ensure the reliability of the software before delivering it to the clients. Finding the mistake with a decent degree of precision at the right time aims to limit the consequences. We have analyzed and evaluated three real-time data sets to measure software reliability by the proposed prediction model for software reliability. Based on the results of these datasets, the proposed S-ARIMA model has achieved high reliability and improved accuracy when compared with the ARIMA model in terms of different parameters like mean square error ( $$MSE$$ ), Relative Prediction Accuracy Improvement $$\left( { RPAI_{MSE} } \right)$$ , and Akanke's Information Criteria ( $$AIC$$ ).

The evolution of cyber–physical system (CPS) benefits from substantial supports of many cutting-edge technologies. However, as a significant medium to bridge virtual and reality parts, the dependability of various network components is facing unprecedented challenges and threats. In this article, we propose a smart collaborative balancing (SCB) scheme to dynamically adjust the orchestration of network functions and efficiently optimize the workflow patterns. First, mathematical models of bandwidth allocation for multiuser with appropriate probability distribution are established. Matrix operations are utilized to solve the relevant issues based on individual congestion windows. Invasion defense mechanisms are also provided and discussed. Second, specific procedures of collaboration among different network components are presented. The capabilities of CPS, in terms of bandwidth allocation and invasion defense, are guaranteed via novel queueing policies and access control mechanisms. Third, we build a comprehensive prototype including multiple domains and users for validations. Experimental results in two scenarios illustrate that SCB not only supports service reliability of end hosts with different priorities, but also resists malicious attacks which are targeting the corresponding terminals inside domains. Compared to the benchmarks in software defined networks and traditional Internet, our scheme performs better in both available resource management and abnormal flow recognition aspects.

The internet of things allows having the comfort of these users. However, the number of connected objects is increasing exponentially. There is therefore a risk of degrading the quality of comfort by the phenomena of the non-availability of communication services. These days, with digital networking and agility in the words, autonomous vehicles, are a particular case of the Internet of Things, represent the vehicles of tomorrow, to increase a penetration rate into the market and make marketed (level 5) in EV (Electric vehicle). We must think to study its reliability and availability. Autonomous vehicles that have a level 5 autonomous drive system, must exhibit a high degree of reliability. In this paper, we propose a new architecture based on redundancy, to increase the dependability and minimize the risk of having a breakdown. We also propose a communication strategy allowing the minimization of the message rate abandoned by sharing messages on a different network and switching between DSRC and C-V2X.

Aim. To consider matters of dependability of highly critical non-recoverable space products with short operation life, whose failures are primarily caused by design and process engineering errors, manufacturing defects in the course of single-unit or small-scale production, as well as to define the methodological approach to ensuring the required reliability.Methods. Options were analysed for improving the dependability of entities with short operation life using the case study of single-use mechanical devices and the statistical approaches of the modern dependability theory, special methods of dependability of actuated mechanical assemblies, FMEA, Stage-Gate and ground experiments on single workout equivalents for each type of effect. Results. It was concluded that additional procedures need to be conducted for the purpose of predicting, mitigation and (or) eliminating possible failures as part of the design process using exactly the same approaches that cause failures, i.e., those of design and process engineering. The engineering approaches to dependability are based on early identification of possible causes of failures, which requires a qualified and systemic analysis aimed at identifying the functionality, performance and dependability of an entity, taking into account critical output parameters and probabilistic indicators that affect the performance of the required functions with the allowable probability of failure. The solution is found using a generalized parametric model of operation and design engineering analysis of dependability.Conclusion. For highly critical non-recoverable space entities with short operation life, the reliability requirements should be considered primarily in terms financial, economic, safetyrelated and reputational risks associated with the loss of spacecraft. From a design engineer’s standpoint, the number of nines after the decimal point (rounded to a smaller number of nines for increased confidence) should be seen as the indicator for the application of the appropriate approaches to ensuring the required reliability at the stage of product design. In case of two nines after the decimal point it is quite acceptable to use analytical and experimental verification techniques common to the aerospace industry, i.e., dependability calculations using the statistical methods of the modern dependability theory and performance indicators, FMEA and Stage-Gate, ground experiments on single workout equivalents for each type of effect. As the required number of nines grows, it is advisable to also use early failure prevention methods, one of which is the design engineering analysis of dependability that enables designers to adopt substantiated design solutions on the basis of engineering disciplines and design and process engineering methods of ensuring quality and dependability. The choice of either of the above dependability strategies is determined solely by the developer’s awareness and understanding of potential hazards, which allows managing the risk of potential rare failures or reasonably refusing to do so.

Aim. The paper primarily aims to simulate the operation of railway transportation systems using the queueing theory with the case study of marshalling yards. The goals also include the development of the methods and tools of mathematical simulation and queueing theory. Methods. One of the pressing matters of modern science is the development of methods of mathematical simulation of transportation systems for the purpose of analyzing the efficiency, stability and dependability of their operation while taking into account random factors. Research has shown that the use of the most mature class of such models, the singlephase Markovian queueing systems, does not enable an adequate description of transportation facilities and systems, particularly in railway transportation. For that reason, this paper suggests more complex mathematical models in the form of queueing networks, i.e., multiple interconnected queueing systems, where arrivals are serviced. The graph of a queueing network does not have to be connected and circuit-free (a tree), which allows simulating transportation systems with random structures that are specified in table form as a so-called “routing matrix”. We suggest using the BMAP model for the purpose of describing incoming traffic flows. The Branch Markovian Arrival Process is a Poisson process with batch arrivals. It allows combining several different arrivals into a single structure, which, in turn, significantly increases the simulation adequacy. The complex structure of the designed model does not allow studying it analytically. Therefore, based on the mathematical description, a simulation model was developed and implemented in the form of software. Results. The developed models and algorithms were evaluated using the case study of the largest Russian marshalling yard. A computational experiment was performed and produced substantial recommendations. Another important result of the research is that significant progress was made in the development of a single method of mathematical and computer simulation of transportation hubs based on the queueing theory. That is the strategic goal of the conducted research that aims to improve the accuracy and adequacy of simulation compared to the known methods, as well as should allow extending the capabilities and applicability of the model-based approach. Conclusions. The proposed model-based approach proved to be a rather efficient tool that allows studying the operation of railway marshalling yards under various parameters of arrivals and different capacity of the yards. It is unlikely to completely replace the conventional methods of researching the operation of railway stations based on detailed descriptions. However, the study shows that it is quite usable as a primary analysis tool that does not require significant efforts and detailed statistics.

An estimation of the failure flows is a prerequisite for the operation of industrial products. It is based on statistical data about failures that occur within technical items in the process of their operation. In the technical product documentation, this indicator shall be featured in the “Dependability parameter estimation” section. The dependability analysis of rolling stock is still affected by the difficulty of defining the methodology for evaluating this parameter at various system levels. For the purpose of analysing a multicomponent system, a reliability block diagram should be developed, and the possible replacement (redundant) elements should be taken into consideration. Multicomponent systems are often represented through various block diagrams, where, among others, the “m-out-of-n” structure may be used referring to a system with a parallel arrangement of elements that is operable when at least m elements operate. An example of such system is a set of passenger car doors. The manufacturers and customers may have different approaches to calculating technical system dependability. First, the required dependability indicator for the entire train is defined that, in turn, defines the dependability requirements for a car. At the same time, the dependability indicator for a car is determined by the respective values of its components (subsystems, units and parts). However, the nature of the relationship between a car and its components is not always taken into account. At the same time, car manufacturers can and should define in the regulatory documentation (and later supervise in operation) the dependability indicators for a set of doors (components of a car in our case) as a single system. However, the failure criteria of a set of doors are not always defined. This paper examines the method of calculating the failure flow for a set of passenger car doors based on operational data and the failure flow of a single door. Aim. To propose a method for calculating the failure flow of a set of 6 car doors by analysing the possible reliability block diagrams with subsequent transition to transition and state graphs.Conclusions. A number of block diagrams were developed for the purpose of dependability calculation of sets of passenger car doors based on the system failure criterion. The failure flow of a set of car doors was calculated according to the developed block diagrams. It is concluded that the Markovian method of calculating the failure flow is of higher priority than the logic-and-probability approach, since it takes into account the recovery factor. A Markovian method was proposed for calculating the failure flow and recovery time of a set of car doors for the “3-out-of-4” reliability block diagram.

The paper aims to improve the terminology used in dependability-related state standards. Examples are given of the use of the terms “estimate” and “definition” in the “Risk management” and “Dependability in technics” series of state standards. The meanings of those terms were clarified based on the existing regulatory documents. Requirements for the integrity of the used terms were defined. Wordings were proposed for the term definitions that feature the words “estimate” and “definition”. Aim. To examine and discuss the common, but not sufficiently substantiated terms “estimate” and “definition” used in state standards, i.e., to consider the legitimacy of their application as part of the above series of state standards. Proposals as to the improvement of such terms’ application were also set forth. Methods. Examples are given of the use of the terms “estimate” and “definition” in state standards. Based on the existing state standards, the actual meanings of the considered terms were clarified: “definition” refers to the way a term is defined, while “estimate” and “estimation” are closely associated with mathematical statistics. The requirements for the integrity of the used terminology are defined and come down to it being unambiguous, consistent within itself and across the relevant state standards. In this context, the shortcomings of the examined terms are shown that are associated with the above requirements, i.e., the meaning, content, essence and key features of such terms are clearly defined. Any comments or references to other regulatory documents are missing as well. Results. In most standards, in the “Terms and definitions” section, the concept of “definition” is used correctly, i.e., terms are defined. However, in other cases, the concept of “definition” is used in a different sense, as nothing is actually being defined. Based on the term integrity requirements and in light of the above shortcomings, proposed replacements for the terms in question were defined. In most cases, instead of the terms “estimate” and “definition”, it is proposed to use the terms “calculation” and “computation”, as well as their cognates, “calculate”, “compute”. It should be noted that along the state standards, theseterms are used in technical documentation, science papers, monographs and textbooks. Conclusions. The use of the examined terms in some standards lacks integrity. The requirements of the standardization recommendations are not observed, the terms are not unambiguous and consistent with other standards. Based on these requirements, the paper proposes improved ways of using the terms “estimate” and “definition”. The suggested terms should be considered as a tentative proposal. Final definitions and/or replacements of these terms are to be developed through extensive discussion and compromise.

Internet-of-Things (IoT) ecosystems tend to grow both in scale and complexity as they consist of a variety of heterogeneous devices, which span over multiple architectural IoT layers (e.g., cloud, edge, sensors). Further, IoT systems increasingly demand the resilient operability of services as they become part of critical infrastructures. This leads to a broad variety of research works that aim to increase the resilience of these systems. In this paper, we create a systematization of knowledge about existing scientific efforts of making IoT systems resilient. In particular, we first discuss the taxonomy and classification of resilience and resilience mechanisms and subsequently survey state-of-the-art resilience mechanisms that have been proposed by research work and are applicable to IoT. As part of the survey, we also discuss questions that focus on the practical aspects of resilience, e.g., which constraints resilience mechanisms impose on developers when designing resilient systems by incorporating a specific mechanism into IoT systems., 37 pages. This preprint is an accepted version to be published as an OpenAccess article in an upcoming issue of ACM Computing Surveys (CSUR). The final, published version of this article will be available under DOI http://dx.doi.org/10.1145/3462513. OpenAcess: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license CC-BY-NC

Time sensitive networking (TSN) is an emerging technology for in-vehicle networks, which has strict timing constraints and dependability requirements. The performance and efficiency of TSN depend on a reliable scheduling mechanism for real-time communications. Traditionally, the TSN scheduler is analyzed using simulations and testing, which are error-prone and inaccurate. In this article, we employ a timed model checker UPPAAL to formally model and analyze the TSN scheduler with a consideration of its transmission latency and time utilization. We first use the build-in assertion in UPPAAL to verify the deadlock-free property, safety property, and starvation-free property of our model. Then, we calculate the time utilization and the transmission delay of audio video bridging data frame under two scheduling mechanisms according to the simulation process. Then, we compared the time performance of this two scheduling mechanisms and found that each of them has their own advantages and disadvantages. This article provides a formal analysis framework for investigating scheduling strategies in TSN, which facilitates the designers to have a better understanding and development of TSN schedulers in the future.

Contingencies such as faults, loss of generation or load may produce undesirable relay operations which can lead to cascade tripping causing system catastrophic failure. Thus, security of power system protection is a major concern for utilities. In this article, an approach based on system integrity protection scheme is proposed for enhancing the security of protection functions. Synchronous data measurements from strategic portions in the system are utilized for separating fault from stressed conditions. Determining the vulnerable relays (VR) which may maloperate during a stressed condition and incorporation of remedial strategy are proposed. It includes two algorithms; the first of which computes the relay margin to form a look-up table containing VR at different fault scenario and operating condition, in offline studies. Then, in accordance with the real-time system conditions, the relay characteristics are set for VRs based on the local information to avoid maloperation. The second is activated during critical heavy loading condition that may lead to voltage collapse and determines the load to be shed based upon sensitivity calculations of relay operation margin. The proposed method is tested for an IEEE-39 bus New England system as well as validated on real-time digital simulator (RTDS) platform for various operating scenarios and found to be robust. Thus, improvement in security of protection operation is achieved without compromising the dependability factor.

This research aims to find out the management of public services and how to improve public services in the Regional Library and Archival Office of West Nusa Tenggara Province. This study uses descriptive qualitative methods. In this research, data collection techniques using interviews, observations, and documentation of public services in the Regional Library and Archival Office of West Nusa Tenggara (NTB) Province. Data analysis techniques are performed with data reduction measures, data presentation, and conclusion drawing. In this research, data validity check techniques using credibility, transferability, dependability, and confirmability. The results show that: (1) public service management ranging from planning, organizing, implementation, and evaluation is still fully not running smoothly. Public services provided have been very maximal, although, in its implementation, there are still perceived shortcomings ranging from lack of reading collection materials, inadequate infrastructure, minimal funds, and the need for building procurement to support the implementation of existing services so that services to the community are still felt less; (2) Efforts of NTB Provincial Library and Archival Office to improve and improve public services conducted by always improving human resources and improving infrastructure facilities to support the implementation of public services.

Fuzz testing enables automated remote testing of cyberphysical and Internet of Things systems. The selection of effective test vector sequences is critical and a natural domain for the employment of artificial intelligence and machine learning techniques that incorporate successful selection criteria.

Research has been carried out on a mobile-based presence system authentication method using MAC addresses, BSSID and IP addresses for (Wi-Fi) networks. This study aims to develop an authentication method on the attendance system that meets two authentication requirements, namely the suitability of employee identity and location suitability, so that the attendance process becomes easy, effective, fast, and can reduce fraud. The employee's identity can be obtained from the MAC address of the smartphone that has been previously registered, while the employee's location during the attendance process can be confirmed to be in the company environment by checking the BSSID data and IP of the Wi-Fi network connected to the smartphone. The data is then compared with MAC address data from all Wi-Fi networks installed in the company area. RAD is used as a development model because it is simple and fast. Overall, employee identification and site checking as authentication of the developed system went well. Other than that, every function on the system works well. Furthermore, the results of the user experience evaluation using the UEQ questionnaire received an average score above 0.8 on 6 scales. This shows that the system has attractiveness, perspicuity, efficiency, dependability, stimulation and novelty. &nbsp, Telah dilakukan penelitian metode autentikasi sistem presensi berbasis mobile dengan pemanfaatan MAC address, Basic Service Set Identifier (BSSID) dan IP address jaringan Wireless-Fidelity (Wi-Fi). Tujuan penelitian ini untuk pengembangan metode autentikasi pada sistem presensi dengan pemenuhan dua syarat autentikasi, yaitu kesesuaian identitas pegawai dan lokasi, agar proses presensi menjadi mudah, efektif, cepat, dan tingkat kecurangan dapat dikurangi. Identitas pegawai dapat diidentifikasi berdasarkan MAC address smartphone yang telah didaftarkan sebelumnya, sedangkan lokasi pegawai pada saat proses presensi dapat dipastikan berada di lingkungan perusahaan dengan pengecekan data BSSID dan IP address jaringan Wi-Fi yang terhubung ke smartphone. Data tersebut dibandingkan terhadap data MAC address dari seluruh instalasi jaringan Wi-Fi yang berada di area perusahaan. Model pengembangan sistem berbasis kepada Rapid Application Development (RAD) dengan pertimbangan, bahwa proses bersifat sederhana dan cepat. Proses pengujian melalui dua cara, yaitu pengujian fungsionalitas dan evaluasi pengalaman pengguna saat penggunaan sistem. Berpedoman kepada hasil pengujian ditunjukkan, bahwa identifikasi identitas pegawai dan pengecekan lokasi sebagai autentikasi pada sistem yang dikembangkan berjalan dengan baik. Hasil pengujian fungsionalitas ditunjukkan, bahwa setiap fungsi pada sistem presensi berjalan baik, berdasarkan hasil yang diharapkan dan dibandingkan terhadap hasil keluaran (output) saat pengujian. Evaluasi terhadap user experience dilakukan dengan penggunaan User Experience Questionnaire (UEQ) dengan nilai rata-rata 0,8 pada skala 6. Berdasarkan penilaian terhadap kuesioner UEQ ditunjukkan, sistem dengan kepemilikan daya tarik, kejelasan, efisien, ketepatan, stimulasi, dan berkebaruan. Dengan demikian, dapat dikatakan bahwa user menerima dengan baik sistem presensi yang dikembangkan.

The paper considers the peculiarities of the SCADA (energy infrastructure management system in the railway infrastructure), as well as issues of the overall dependability in the corporate infrastructure, which is the aim of the study. The study, based on the accepted structure and values of the parameters, examines what depends on and how the readiness factor of a SCADA system changes when the recovery intensity changes and at a fixed failure rate. The results show that with increasing recovery intensity, the readiness factors of the telecommunications network and SCADA system thus defined increase, while reducing the downtime. For a more in-depth study of the overall reliability of the SCADA system, it is necessary to set specific normatively accepted dependability parameters of all connected elements, as well as a real set structure. Based on the fact that with backup resources provided, a defined dependability of the system can be ensured at preset values of the reliability parameters of its components and the backup structure; the opposite problem can also be solved. The proposed approach for studying the reliable behavior of the SCADA system within the corporate infrastructure can be noted as a contribution of the present work and conclusions are made for the practical use of the results.

PurposeThere has been a growing call regarding broad criteria for assessing qualitative methods' reliability and validity in international marketing (IM) research. In response, this study synthesizes the past literature to present an overarching, yet adaptable, trustworthiness verification framework for assessing the rigor of various qualitative methods used in IM.Design/methodology/approachThe paper draws on qualitative research from various disciplines. It uses content analysis to examine how trustworthiness is conceptualized in qualitative studies in International Marketing Review (IMR) from 2005 to 2019.FindingsThe analysis reveals that strategies to ensure rigor and trustworthiness of qualitative research in IMR are partially applied. There remain gaps in implementing quality criteria across the trustworthiness dimensions of credibility, transferability, dependability, conformability and ethics.Research limitations/implicationsThis paper highlights the importance of incorporating strategies for assessing the quality of qualitative research in IM research. Since the analysis only focused on IMR, future research should explore and test the framework in other IM and business journals to reach a broader consensus in assessing qualitative studies' rigor.Originality/valueIM researchers have yet to develop a consensus regarding broad criteria for assessing qualitative methods' reliability and validity. This paper is an attempt to fill this gap.

In the era of technology, compact and low-powered IoT devices have become an integral part of the daily routines of various sectors such as healthcare, education, industries, defense, and agriculture, etc. The IoT has increased the flow of enormous data from one network to another and extended the dependability of the public networks. In health applications, this dependency can cause excessive packets to be lost and prolonged waiting, which can cause sensitive applications to suffer. The authors suggested fog computing as a potential middle layer in the delay-aware computational system in existing works. There are many issues with the cloud-based computation model, such as location awareness, long-distance communication path, and unmanageable network bandwidth. These parameters can be solved using a fog computing model, which helps achieve ultra-low latency and minimum service delivery time. However, task offloading and scheduling are significant open research issues concerning resource management and allocation in a cloud-fog system. This paper presents a delay-aware application offloading focusing on reducing the response time and maximizing the system performance. Our proposed model developed a multiclass open queueing model that maintains the traffic on different queues, aiming to achieve maximum system performance. The simulation results demonstrate that our proposed model DAAO (Delay-aware application offloading) yields a performance improvement of 14.30% service rate and minimized failure rate by 2.0%. The simulation results supported the robustness of the proposed model in terms of minimum response time and maximum success rate. Our proposed model achieves a better tradeoff than existing work in terms of offloading and minimum failure rate.

To prompt the use of driving automation in an appropriate and safe manner, system designers require knowledge about the dynamics of driver trust. To enhance this knowledge, this study manipulated prior information of a partial driving automation into two types (detailed and less) and investigated the effects of the information on the development of trust with respect to three trust attributions proposed by Muir (1994): predictability, dependability, and faith. Furthermore, a driving simulator generated two types of automation failures (limitation and malfunction), and at six instances during the study, 56 drivers completed questionnaires about their levels of trust in the automation. Statistical analysis found that trust ratings of automation steadily increased with the experience of simulation regardless of the drivers’ levels of knowledge. Automation failure led to a temporary decrease in trust ratings; however, the trust was rebuilt by a subsequent experience of flawless automation. Results showed that dependability was the most dominant belief of drivers’ trust throughout the whole experiment, regardless of their knowledge level. Interestingly, detailed analysis indicated that trust can be accounted by different attributions depending on the drivers’ circumstances: the subsequent experience of error-free automation after the exposure to automation failure led predictability to be a secondary predictive attribution of drivers’ trust in the detailed group whilst faith was consistently the secondary contributor to shaping trust in the less group throughout the experiment. These findings have implications for system design regarding transparency and for training methods and instruction aimed at improving driving safety in traffic environments with automated vehicles.