Interdependent Components Research Articles

Modelling and Analysing Replica- and Fault-aware Management of Horizontally Scalable Applications

Modern enterprise applications integrate multiple interdependent software components, whose management must be suitably coordinated. This must be done by taking into account all inter-component dependencies, the faults potentially affecting them, and the fact that each component can be horizontally scaled, i.e., that multiple instances of each component can be spawned or destroyed, depending on application needs. In this article, we introduce a novel solution for suitably modelling and analysing the replica- and fault-aware management of multi-component applications, based on topology graphs and management protocols. More precisely, we first introduce a compositional model of the management behaviour of the (possibly multiple) instances of the components forming an application, faults included. We then show how this model enables automating various useful analyses, from checking the validity of management plans to automatically determining management plans allowing the instance of an application to reach and maintain a desired target configuration.

Review of Seismic Fragility and Loss Quantification of Building-Like Industrial Facilities

Abstract Industrial facilities play a significant role in economic growth now and for the foreseeable future. However, past earthquake reconnaissance surveys have revealed that the seismic vulnerability of these facilities has resulted in huge economic losses mainly due to operational failures. As per ASCE 7, industrial facilities could be classified as building-like and nonbuilding-like types. In this paper, the fragility of building-like industrial facilities is focused. First, relevant design code requirements and provisions were summarized for further discussion on possible improvements. This is followed by a review of the latest techniques, challenges, and knowledge gaps related to the fragility development of building-like industrial facilities. The review indicates gaps in fragility development specific to seismic loss quantification. The need for updated design guidelines, component interdependencies, robust seismic modeling, and analysis techniques for improved decision-making are hence recommended.

The Empirical Reality of IT Project Cost Overruns: Discovering A Power-Law Distribution

ABSTRACT If managers assume a normal or near-normal distribution of Information Technology (IT) project cost overruns, as is common, and cost overruns can be shown to follow a power-law distribution, managers may be unwittingly exposing their organizations to extreme risk by severely underestimating the probability of large cost overruns. In this research, we collect and analyze a large sample comprised of 5,392 IT projects to empirically examine the probability distribution of IT project cost overruns. Further, we propose and examine a mechanism that can explain such a distribution. Our results reveal that IT projects are far riskier in terms of cost than normally assumed by decision makers and scholars. Specifically, we found that IT project cost overruns follow a power-law distribution in which there are a large number of projects with relatively small overruns and a fat tail that includes a smaller number of projects with extreme overruns. A possible generative mechanism for the identified power-law distribution is found in interdependencies among technological components in IT systems. We propose and demonstrate, through computer simulation, that a problem in a single technological component can lead to chain reactions in which other interdependent components are affected, causing substantial overruns. What the power law tells us is that extreme IT project cost overruns will occur and that the prevalence of these will be grossly underestimated if managers assume that overruns follow a normal or near-normal distribution. This underscores the importance of realistically assessing and mitigating the cost risk of new IT projects up front.

Cinematography and Modern Media

The purpose of the study is to analyze modern and traditional media; identify problems and prospects, compare modern media with its traditional analogues; describe the role of main professions associated with film and television; to reveal the problems of modern media. The research methodology consists in applying the following methods: theoretical – analysis of television programs, films, information sources, generalization of the influence of media on world transformations and determination of the interdependence of the structural components that form the whole television space. Scientific novelty. For the first time the components of modern media are deeply analyzed, a detailed analysis of the interdependence of the structural components that form the television space is carried out, using a theoretical analysis of television programs, the factors affecting the quality of the television product are determined. Conclusions. In the course of the article, we analyzed modern and traditional media. With the help of the ongoing analysis, we have established the differences between modern media and traditional ones, problems were identified and possible ways of solving them were analyzed. The components that form modern media were considered in detail and the role of the main film and television professions was determined. The factors, which are influencing the quality of television content were summarized by the author as well.

Experimental evolution of a pheromone signal.

Sexual signals are important in speciation, but understanding their evolution is complex as these signals are often composed of multiple, genetically interdependent components. To understand how signals evolve, we thus need to consider selection responses in multiple components and account for the genetic correlations among components. One intriguing possibility is that selection changes the genetic covariance structure of a multicomponent signal in a way that facilitates a response to selection. However, this hypothesis remains largely untested empirically. In this study, we investigate the evolutionary response of the multicomponent female sex pheromone blend of the moth Heliothis subflexa to 10 generations of artificial selection. We observed a selection response of about three‐quarters of a phenotypic standard deviation in the components under selection. Interestingly, other pheromone components that are biochemically and genetically linked to the components under selection did not change. We also found that after the onset of selection, the genetic covariance structure diverged, resulting in the disassociation of components under selection and components not under selection across the first two genetic principle components. Our findings provide rare empirical support for an intriguing mechanism by which a sexual signal can respond to selection without possible constraints from indirect selection responses.

Exploring the possible linkage between the precipitation and temperature over Iran and their association with the large-scale circulations: Cumulative spectral power and wavelet coherence approaches

The current study aims at improving our common knowledge of precipitation and surface temperature variabilities in Iran across different time scales (from intra-annual to decadal) by using two methods (the cumulative spectral power and wavelet coherence analyses) and linking the variabilities to several teleconnection indices, namely Mediterranean Oscillation (MO), Quasi-biennial Oscillation (QBO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), and solar activity (~ Sunspot Number (SN)). Furthermore, the interdependence of the spectral components of indices is also explored. We divided the country to eleven climatic zones and performed the analysis for individual zones as well as for the total area by constructing the precipitation and temperature signals for the study period of 1979–2021 based on the gridded data. Based on the wavelet coherence analysis, the surface temperature and precipitation variations are strongly linked together, in particular at annual cycle and the phase status is predominantly anti-phase for all zones as well as for the all temporal scales. In addition, the MO can be regarded as a predictor of the annual variation of both variables over Iran as our results indicate a significant co-variability in the annual band between MO signal and these variables. Furthermore, a similar semi-annual component is detected in both MO and temperature signals with an anti-phase status, but the same component was not found in the precipitation. Other indices have also substantial influences on both temperature and precipitation, mostly at inter-annual and decadal periods. Based on the wavelet coherence and lagged correlation analyses, evidences of common periodicity, namely 11-year solar cycle, between SN and SOI signals is clearly revealed. Moreover, our results show that if the SN signal is considered as the cause and the SOI signal as the effect, the minimum value of the 11-year component of SOI occurs approximately 2.5 to 3 years after the maximum of the same component in the SN signal. By employing the cumulative spectral power analysis, the main quasi-periodic components of the climatic signals, the surface temperature, and precipitation with their power distribution are presented and compared in different frequency bands. The application of both methods on different zones over Iran is also addressed in addition to the whole area. The results show that although some indices have minor impact on the variabilities of the precipitation and temperature for the whole area in some frequency bands, but the large impact is found in a number of individual zones.

Towards a recipe for language decomposition: quality assessment of language product lines

Programming languages are complex systems that are usually implemented as monolithic interpreters and compilers. In recent years, researchers and practitioners gained interest in product line engineering to improve the reusability of language assets and the management of variability-rich systems, introducing the notions of language workbenches and language product lines (LPLs). Nonetheless, language development remains a complex activity and design or implementation flaws can easily waste the efforts of decomposing a language specification into language features. Poorly designed language decompositions result in high inter-dependent components, reducing the variability space of the LPL system and its maintainability. One should detect and fix the design flaws posthaste to prevent these risks while minimizing the development overhead. Therefore, various aspects of the quality of a language decomposition should be quantitatively measurable through adequate metrics. The evaluation, analysis and feedback of these measures should be a primary part of the engineering process of a LPL. In this paper, we present an exploratory study trying to capture these aspects by introducing a design methodology for LPLs; we define the properties of a good language decomposition and adapt a set of metrics from the literature to the framework of language workbenches. Moreover, we leverage the AiDE 2 LPL engineering environment to perform an empirical evaluation of 26 Neverlang-based LPLs based on this design methodology. Our contributions form the foundations of a design methodology for Neverlang-based LPLs. This methodology is comprised of four different elements: i) an engineering process that defines the order in which decisions are made, ii) an integrated development environment for LPL designers and iii) some best practices in the design of well-structured language decomposition when using Neverlang, supported by iv) a variety of LPL metrics that can be used to detect errors in design decisions.

Multi-granularity Decomposition of Componentized Network Applications Based on Weighted Graph Clustering

With the development of mobile communication and network technology, smart network applications are experiencing explosive growth. These applications may consume different types of resources extensively, thus calling for the resource contribution from multiple nodes available in probably different network domains to meet the service quality requirements. Task decomposition is to set the functional components in an application in several groups to form subtasks, which can then be processed in different nodes. This paper focuses on the models and methods that decompose network applications composed of interdependent components into subtasks in different granularity. The proposed model characterizes factors that have important effects on the decomposition, such as dependency level, expected traffic, bandwidth, transmission delay between components, as well as node resources required by the components, and a density peak clustering (DPC) -based decomposition algorithm is proposed to achieve the multi-granularity decomposition. Simulation results validate the effect of the proposed approach on reducing the expected execution delay and balancing the computing resource demands of subtasks.

Quantifying disaster resilience of a community with interdependent civil infrastructure systems

Disaster resilient civil infrastructure systems are essential for disaster resilient communities. Measuring the resilience of these systems is the first step towards their improvement. This, however, is not easy: civil infrastructure systems are highly complex, operate in different ways, and are affected differently in different disasters. Adding to the complexity are the dynamic interdependencies among components of such systems, that change as the community is recovering. The Re-CoDeS framework for quantifying disaster resilience measures the lack of resilience of a system (e.g., a community) as the amount of the system’s unmet demand for a considered resource or service over the resilience assessment interval. This paper presents a novel demand/supply-based method to consider dynamic component interdependencies by extending the Re-CoDeS framework: whenever the demand of a component is not met by the currently available supply capacity of the system, that component ceases to operate and its supply capacity decreases. The proposed iRe-CoDeS framework is demonstrated on a virtual community served by three interdependent civil infrastructure systems producing five types of resources and services. Step-by-step instructions for defining a community model within the iRe-CoDeS framework are presented to facilitate the use of the proposed framework.

Graphics Out Loud: Perceptions and Strategic Actions of Students With Visual Impairments When Engaging With Graphics

Introduction: Facility in graphics use is critical to accessing data visualizations in science, technology, engineering, the arts, and mathematics (STEAM) content areas. Efforts to understand the cognitive processes underlying strategic action by students with visual impairments must consider both metacognition and self-regulated learning. Methods: Think-aloud transcripts were analyzed using a priori level one coding based on the Model of Graphic Interpretation (MoGI) followed by second-level coding to analyze nuanced commonalities and differences based on performance, medium, and level. Results: Differences in each component of the MoGI were found for print graphic and tactile graphic users, particularly based on performance and level. Higher performers were better able to articulate strategy use and reasons for selecting strategies. Discussion: Findings coincide with quantitative findings of the participants (see Zebehazy & Wilton, 2021 ). Transcripts provided additional confirming evidence of the interdependence of MoGI components. Implications for Practitioners: Use of think aloud can support assessment and instruction of students with visual impairments to build strategic action and metacognition when engaging with graphics.

Reuse and maintenance practices among divergent forks in three software ecosystems

With the rise of social coding platforms that rely on distributed version control systems, software reuse is also on the rise. Many software developers leverage this reuse by creating variants through forking, to account for different customer needs, markets, or environments. Forked variants then form a so-called software family; they share a common code base and are maintained in parallel by same or different developers. As such, software families can easily arise within software ecosystems, which are large collections of interdependent software components maintained by communities of collaborating contributors. However, little is known about the existence and characteristics of such families within ecosystems, especially about their maintenance practices. Improving our empirical understanding of such families will help build better tools for maintaining and evolving such families. We empirically explore maintenance practices in such fork-based software families within ecosystems of open-source software. Our focus is on three of the largest software ecosystems existence today: Android, .NET, and JavaScript. We identify and analyze software families that are maintained together and that exist both on the official distribution platform (Google play, nuget, and npm) as well as on GitHub , allowing us to analyze reuse practices in depth. We mine and identify 38 software families, 526 software families, and 8,837 software families from the ecosystems of Android, .NET, and JavaScript, to study their characteristics and code-propagation practices. We provide scripts for analyzing code integration within our families. Interestingly, our results show that there is little code integration across the studied software families from the three ecosystems. Our studied families also show that techniques of direct integration using git outside of GitHub is more commonly used than GitHub pull requests. Overall, we hope to raise awareness about the existence of software families within larger ecosystems of software, calling for further research and better tools support to effectively maintain and evolve them.

Logistics Cluster as a Way of Implementing a Multisourcing Model to Ensure the Livelihood of the Local Community

In recent years, the living conditions of territorial communities in Ukraine promote the integration of organizations and enterprises in various fields. The cluster is a group of localized interdependent companies, equipment suppliers, components, specialized services, infrastructure, research institutes, universities and other organizations that complement and enhance each other's competitive advantages. Current common problems that hinder the normal functioning of local communities are: utilities and energy efficiency, investment climate and investment, public safety, problems of access to administrative services, communication problems between the leadership of the local community and local population, environmental issues. Based on the results of the study of the internal environment of the united territorial community, the benefits of cluster approach and the benefits that can provide a multisourcing model, it is determined that the main problems that hinder the normal functioning of modern communities can be solved by forming a logistics cluster. The logistics cluster will allow to fully implement the multisourcing model of ensuring the livelihood of the local community. Such model of decision-making on the rational choice of source of supply from several alternatives will: improve the quality of supply management of goods / services; reduce the logistics cycle; reduce supply costs; increase the reliability of supplies, etc. Thus, the formation of a logistics cluster at the level of ensuring the livelihood of the territorial community helps to strengthen the competitiveness of each of the participants. The main participants of the cluster are: production and logistics companies located in the most important centers of intersection and origin of goods and goods, directly involved in the process of providing services.

Governance using the water-food-energy nexus and human-factor measures.

Household water food and energy (WFE) expenditures, reflect respective survival needs for which their resources and social welfare are inter-related. We developed a policy driven quantitative decision-making strategy (DMS) to address the domain geospatial entities’ (nodes or administrative districts) of the WFE nexus, assumed to be information linked across the domain nodal-network. As investment in one of the inter-dependent nexus components may cause unexpected shock to the others, we refer to the WFE normalized expenditures product (Volume) as representing the nexus holistic measure. Volume rate conforms to Boltzman entropy suggesting directed information from high to low Volume nodes. Our hypothesis of causality-driven directional information is exemplified by a sharp price increase in wheat and rice, for U.S. and Thailand respectively, that manifests its impact on the temporal trend of Israel’s administrative districts of the WFE expenditures. Welfare mass (WM) represents the node’s Volume combined with its income and population density. Formulation is suggested for the nodal-network WM temporal balance where each node is scaled by a human-factor (HF) for subjective attitude and a superimposed nodal source/sink term manifesting policy decision. Our management tool is based on two sequential governance processes: one starting with historical data mapping the mean temporal nodal Volumes to single out extremes, and the second is followed by WM balance simulation predicting nodal-network outcome of policy driven targeting. In view of the proof of concept by model simulations in in our previous research, here HF extends the model and attention is devoted to emphasize how the current developed decision-making approach categorically differs from existing nexus related methods. The first governance process is exemplified demonstrating illustrations for Israel’s districts. Findings show higher expenditures for water and lower for energy, and maps pointing to extremes in districts’ mean temporal Volume. Illustrations of domain surfaces for that period enable assessment of relative inclination trends of the normalized Water, Food and Energy directions continuum assembled from time stations, and evolution trends for each of the WFE components.

ДИНАМИЧЕСКАЯ НЕВРОПАТИЯ НАДЛОПАТОЧНОГО НЕРВА – «БОЛЬ В ЛОПАТКЕ И ПЛЕЧЕ». МАНУАЛЬНАЯ ДИАГНОСТИКА И ЛЕЧЕНИЕ

Dynamic suprascapular nerve neuropathy is a cause of shoulder pain and weakness that is often overlooked. The difficulty in diagnosing the nerve dynamic damages is conditioned by the fact that the symptoms are provoked by physical exertion(s) or a certain position of the limb due to compression and(or) overstretching as well as violations of the longitudinal and transverse sliding of the nerve. These symptoms subside when the provoking factor ceases to act and return when movements repeat. Neurologic examinations and nerve conduction studies performed at rest usually show no change. The suprascapular nerve dysfunction is closely related to rotator cuff pathology. The nerve damage is often caused by a dynamic microtrauma during repetitive arm movements over the head with maximum deflection and external rotation of the arm. Suprascapular neuropathy can be caused by the nerve compression or traction in the suprascapular notch or spinoglenoid region. The nerve damage in the suprascapular notch causes weakness in both the supraspinatus and infraspinatus muscles, while damage under the spinoglenoid ligament affects only the infraspinatus muscle. Diagnostics should include manual testing of the supraspinatus and infraspinatus muscles with a neutral position of the arm and neck of the patient being examined and during provocative neurodynamic tests of stretching the suprascapular nerve. Therapeutic measures should be directed to all interdependent components of the peripheral nervous system in the following sequence: osteopathic treatment of the nerve trunk interface (tissues surrounding the nerve trunk); osteopathic treatment of the innervated tissue; osteopathic treatment of the connective tissue of the suprascapular nerve.

The Ethical Foundations of Buddhist Cognitive Models

While issues related to greed and fear are ubiquitous in everyday life, they become particularly evident in crises such as the current COVID-19 pandemic, when societal responses are frequently based on either fear of the disease or craving for the reestablishment of pre-pandemic “normal” life. In this context, a question can be posed whether it is possible to approach and understand these phenomena in other ways, and consequently respond in a different manner. In search for alternative approaches to the problem of human greed and fear, this article investigates their conceptualisations from the perspective of the Theravāda Abhidhamma, an important formulation of ancient Indian Buddhist philosophy. The Abhidhamma analyses and expounds the processes of cognition, using a multivalent and complex structure, comprised of interrelated and interdependent components (dhamma), which are involved in the ever-changing flow of mental and physical phenomena. This article proposes that the entirety of the structural cognitive model of the Abhidhamma is founded on, and permeated by ethics. The components involved in cognitive processes are classified in three ways, as ethical, unethical, or indeterminate; greed and fear are presented as components of unethical mental states, which in turn may lead to actions that are harmful to oneself and society. This Abhidhammic analysis of cognition provides a model, in which a different conceptualisation of greed and fear is presented; it identifies those components and conditions for cognition which allow for an ethical (kusala) stance and consequently ethical actions. The article thus propounds that the knowledge of cognitive models of ancient India can be relevant to the search for new approaches to contemporary ethical challenges, and may contribute to a different understanding of, and responses to, greed and fear.

СУЩНОСТЬ И СТРУКТУРА ЕСТЕСТВЕННО-НАУЧНОЙ КОМПЕТЕНТНОСТИ БУДУЩИХ СПЕЦИАЛИСТОВ В СФЕРЕ КЛИНИЧЕСКОЙ МЕДИЦИНЫ

The problem of ensuring the practice-oriented nature of the natural science training of future specialists in the field of clinical medicine is actualized. The relevance of the formation of natural science competence in future specialists in the field of clinical medicine is substantiated. The author’s understanding of the essence of natural science competence is given. The structure of the natural science competence of future specialists in the field of clinical medicine is determined as a system of interrelated and interdependent components, to which the author refers the motivational-value, cognitive, praxeological and personal-behavioral components.

Identifying the Key Components in ResNet-50 for Diabetic Retinopathy Grading from Fundus Images: A Systematic Investigation

Although deep learning based diabetic retinopathy (DR) classification methods typically benefit from well-designed architectures of convolutional neural networks, the training setting also has a non-negligible impact on the prediction performance. The training setting includes various interdependent components, such as objective function, data sampling strategy and data augmentation approach. To identify the key components in a standard deep learning framework (ResNet-50) for DR grading, we systematically analyze the impact of several major components. Extensive experiments are conducted on a publicly-available dataset EyePACS. We demonstrate that (1) the ResNet-50 framework for DR grading is sensitive to input resolution, objective function, and composition of data augmentation, (2) using mean square error as the loss function can effectively improve the performance with respect to a task-specific evaluation metric, namely the quadratically-weighted Kappa, (3) utilizing eye pairs boosts the performance of DR grading and (4) using data resampling to address the problem of imbalanced data distribution in EyePACS hurts the performance. Based on these observations and an optimal combination of the investigated components, our framework, without any specialized network design, achieves the state-of-the-art result (0.8631 for Kappa) on the EyePACS test set (a total of 42670 fundus images) with only image-level labels. Our codes and pre-trained model are available at https://github.com/YijinHuang/pytorch-classification

КРИТЕРІЇ ОПТИМІЗАЦІЇ СТРАТЕГІЧНИХ ЦІЛЕЙ ЕКОНОМІЧНОГО РОЗВИТКУ

The article considers the development of the socio-economic system as a qualitative transformation of the system, which leads to a new state, taking into account natural changes and the transition from one state to a more perfect. The strategic goals of economic development in the national macroeconomic environment were defined as the unity of interconnected and interdependent components. The main factors and conditions that determine the sustainable development of the country were listed. The concept of "Sustainability" was defined. Types of resilience were considered. The basic conditions for sustainable economic development were provided. These conditions are the systematization, selection and complexity of the process of resource provision of the economic environment of the national economy. A model for ensuring the sustainable development of the socio-economic system was proposed. The main segment components that determine the structure and state of macroeconomic processes from the standpoint of sustainable development of the socio-economic system were identified. The structure of the socio-economic system was considered as a complex, multifaceted, multicomponent and multilevel economic system. The main conditions for the development of the socio-economic system were listed. These conditions are monitoring and measuring the results of activities in the system. The model of the influence of the structural and functional environment on the effectiveness of the socio-economic system was illustrated. The concept of "Efficiency" was defined as a relative value that characterizes the ratio of the results obtained with the goals of the socio-economic system or the result with the cost of obtaining it. The basic principles and components that allow the modern economy to function were listed. The concept of "Adaptability" as a process of permanent purposeful structural and functional adaptation of the system of strategic economic development goals to certain living conditions was analyzed. Conclusions were made on the strategic goals of economic development of the socio-economic system.

ЭКОЛОГИЧЕСКИЕ ОСНОВЫ МЕЛИОРАЦИИ ЗЕМЕЛЬ

The analysis of the current state of agricultural land reclamation in Russia is carried out. It is noted that over the past 20 years, more than 85% of reclaimed lands are degraded; the intensity of degradation has increased almost 2 times compared to the previous 20 years. This was due to the lack of a systematic analysis of the cause-and-effect relationships of the concept of «LAND» as a natural object and natural resource, which includes a number of interacting and interdependent components, such as atmosphere, biota, soil, surface and groundwater. Ways to improve the efficiency of agricultural land reclamation are proposed and substantiated, based on the rational use of the natural resource potential of the territories and the elimination of contradictions between the agricultural use of the lands and the environment protection. The proposed approaches make it possible to remove the main contradictions between agriculture, land reclamation and environment protection.

ОЦІНЮВАННЯ ВЗАЄМОЗАЛЕЖНОСТІ МІЖ ВТРАТОЮ ДОВІРИ ДО ПУБЛІЧНОЇ ВЛАДИ ТА МАКРОЕКОНОМІЧНОЮ СТАБІЛЬНІСТЮ УКРАЇНИ

In the conditions of changes in social relations, trust becomes a relevant factor in human activity. Ensuring trust in public authorities is an urgent issue today, as a prerequisite for the socio-political and economic growth of the country. Quite often, it depends on the effectiveness of state regulation, namely, the adopted strategy of reform, the definition of strategic targets of state policy regarding the functioning of socio-political and economic institutions at the micro-, meso-, and macro- levels. The purpose of the article was to assess the relationship between the loss of trust in public authorities and the macroeconomic stability of Ukraine. The authors proposed a scientific and methodical approach to assessing the interdependence of relevant components: 1) a research base was formed, which involves collecting and checking determinants for abnormality by the Irwin method; 2) the relevant determinants of the macroeconomic component according to factor loadings are determined (by the stony scree graph); 3) normalization of determinants of macroeconomic development and indicators of distrust in public authorities based on Harrington's approach; 4) formation of integral indicators using the convolution method of calculating the geometric mean value; 5) regressive interdependencies between the loss of trust in public authorities and the macroeconomic stability of Ukraine are constructed. The obtained results made it possible to analyze the consequences of the crisis of confidence on macroeconomic stability. A high level of alienation between society and political institutions inhibits economic development, stable socio-political growth and macroeconomic stability of the country as a whole. The results will be useful for the activities of the Verkhovna Rada of Ukraine, the Office of the President of Ukraine, the Cabinet of Ministers, central bodies of executive and legislative power of Ukraine, the Ministry of Finance of Ukraine, and the Ministry of Social Policy of Ukraine.