Hierarchy Framework Research Articles

Maintenance 4.0: implementation challenges and its analysis

PurposeThe purpose of this paper is to identify and analyze the challenges associated with the implementation of the concept of Maintenance 4.0 in industries.Design/methodology/approachThe challenges in the implementation of Maintenance 4.0 are identified through a literature survey and interaction with professionals from the industry and academia. A structural hierarchy framework that integrates the methodologies of ISM and MICMAC is used for the analysis of Maintenance 4.0 implementation challenges. The framework establishes the interrelationship among challenges and segregates them into driving, linkage, dependent and autonomous groups.FindingsA novel concept of Maintenance 4.0 under the aegis of Industry 4.0 is gaining appreciation worldwide. However, there are challenges in the adaptation of Maintenance 4.0 concepts among industries. The various challenges as well as their impact on the objective of implementation of Maintenance 4.0 are identified.Practical implicationsThe practicing engineers, academicians, researchers and the concerned industries can infer from the results to improve upon the causes of such challenges and promote the implementation of Maintenance 4.0 most efficiently and effectively.Originality/valueThis paper is a novel, unique and first of its kind that addresses the most contemporary challenges in the implementation of Maintenance 4.0 concepts in industries.

Implementation of AHP to evaluate variables of prognosis agent technology managing manufacturing organizations

This research aims to use AHP model to evaluate variables of PAT managing manufacturing organizations. Using AHP approach, an evaluation model can be constructed, capable to measure the weight and ranking of variables. Literature helps to identify twenty six variables of PAT. These variables are arranged on the basis of expert’s opinion and construct a conceptual domain in which variable are divided as five major and twenty one sub variables. This domain is used to draw hierarchy framework of AHP model. Thereafter, pair wise comparison is performed on the expert’s responses to measure weight of PAT variables, the responses and matrices, validated by computing consistency ratio. Finally, weight and ranking of entire variables are evaluated in AHP methodology section and concluded in last section which gives interesting suggestions to the manufacturing organizations so as to manage their manufacturing system.

Nonlinear dynamics of a liquid film flow over a solid substrate in the presence of external shear stress and electric field

Using approximation techniques, long-wave length framework and boundary-layer, the effects of electrostatic force and induced shear stress on the flow behavior down an inclined solid substrate are investigated. In general case, the considered model accounts in the presence of inertia regime and streamwise viscous diffusion with the influence of normal electric field and an imposed shear stress. Using the Galerkin weighted residual, two coupled evolution equations for the flow rate and film thickness are extracted. In the appropriate limit cases, the evolution equations obtained by previous authors are recovered. The primary instability has been analyzed using the Whitham wave hierarchy framework. In the nonlinear regime, the behavior of solitary waves arose on the surface of liquid film due to the effects of electrostatic force and imposed shear stress throughout three-dimensional dynamical systems. Some bifurcation points are reported. In both extremely viscous and electrogravity regimes, the Benney-like equation is extracted in a new form. By excluding contribution of external shear stress and viscous dispersion parameter, the interesting results of previous authors are recovered. In both weakly nonlinear and inertialess regimes, the bifurcation points of the three dynamical systems are discussed within the Kuramoto–Sivashinsky type equation.

Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach

The planning and operation of distribution systems have significantly changed due to the extensive osmosis of ICT (information and communication technologies) into power systems. Load growth, together with increased power quality expectations by the customers, has transformed the conventional distribution network to active distribution network (ADN), with penetration of distributed energy resources (DERs). This has imposed the necessity to analyze resilient performance of ADN subjected to the boon of ICT for enhanced situational awareness (SA). This paper focuses on a detailed multi-level hierarchy framework using linguistic scale based multi-criteria decision-making (MCDM) approach for SA oriented resilience level estimation of ADN, considering different high impact low frequency (HILF) events. The rapidly changing environmental conditions and ambiguity in interaction of network parameters lead to non-deterministic resilience (NDR), thus, affecting the operational resilience of ADN on a daily basis. To analyze the uncertain ADN availability due to NDR, hybrid MCDM-dynamic Bayesian network (DBN) approach is used. For better decision-making, the operational performance of ADN, to withstand critical loads due to NDR is analyzed in terms of load not served (LNS) index. The proposed framework is tested on IEEE 33-bus distribution network.

The impact of the COVID-19 pandemic on patients with Behçet's syndrome within the framework of Maslow's hierarchy of needs: implications for patient empowerment in national or global emergencies.

The aim of this online survey was to assess the impact of the COVID-19 pandemic on patients with Behçet's syndrome (BS) using Maslow's hierarchy of needs. Sixty-eight BS patients from the UK completed an online questionnaire that covered three components of Maslow's hierarchy of needs regarding Physiological needs (sleep, food, mobility), Safety needs (employment, health), Social needs (relationships), personal precautions and main concerns regarding COVID-19. The patients received a letter from the NHS (66.2%) advising shielding. Health concerns were addressed using Tele-medicine by telephone consultations and e-mails to access BS specialists during lockdown (44.1%; 27.9%). In addition, patients also obtained information through official government and Behçet corporate health web pages related to Behçet's disease for self-empowerment. During lockdown, their weekly working hours were reduced (26.65±13.86 vs. 20.79±17.94) (p=0.017) and the employment rate was decreased (32.6% vs. 26.7%) in comparison to pre-lockdown. Moreover, the reduction in frequency of exercise per week (4.39±1.94 vs. 3.71±2.26) and healthy food consumption (73.5 % vs. 47.1%) per week were also reported (p=0.007; p=0.001, respectively). Furthermore, patients experienced sleeping less (54.4%) and feeling lonely (66.1%). Using Maslow's hierarchy of needs provided a framework for reviewing the quality of basic needs in patients' life during lockdown. These needs are required for healthy social lives and the deprivation should be considered while considering healthcare planning. Since lockdown appeared to have a negative influence on patients' lives and disease management in the framework of patient-centred, the empowerment of patients gained importance at this point.

Cracking "Rational Ignorance" With Institutional Arrangement: A Study on the Reasons and Countermeasures for the Lack of Willingness to Express Community Public Service Needs of Urban Residents —— A Survey Based on Dalian City Community

In order to further optimize the supply of community public services and meet the needs of residents for a better life in the community, this paper takes the behavioral hypothesis of "rational ignorance" as the framework for analysis and explores the root causes of the lack of willingness of urban residents to express their needs for community public services. The low civic awareness, high costs and low returns are the essential reasons for the lack of willingness of urban residents to express their needs, and they are also the endogenous factors influencing the low participation of urban residents in community governance and the poor performance of community public service provision. With the help of Williamson's institutional hierarchy framework, this paper proposes countermeasures for the lack of willingness of urban residents to express their needs for community public services from different levels of institutional arrangements in order to create a sound and complete environment for residents to express their needs, thereby alleviating the contradiction between supply and demand of urban community public services and building a new pattern of community governance that is jointly negotiated, built, and shared.

Influences of Mahathirism in Utusan Malaysia editorials on Mahathir’s policies during his premiership from 1981-2003

This study examined editorials in one of Malaysia's Malay newspapers, the Utusan Malaysia, from 1981 to 1987, during Mahathir's premiership. The study specifically examined the influence of Mahathirism on Utusan Malaysia's editorials on government policies. The theoretical framework of Reese's hierarchy of influences served as the foundation for this study. This qualitative study utilised retrospective in-depth interviews with key personnel of Utusan Malaysia as its methodology to answer the research questions. This study found no compelling evidence of direct or overt influence of Mahathirism on the editorials. What the study discovered was the chief editor, Zainuddin Maidin (ZAM)'s enthusiasm for Mahathir's thinking and his conviction that this Prime Minister possessed the courage to carry out his promises of a modernised and prosperous Malaysia and a greater share of the economy for Malays. The editorials demonstrate that he shared Mahathir's concerns about how Malaysia should be developed and how the Malay agenda and increased economic representation for the Malay community should be accomplished. We find in the editorials, not verbatim echoes of Mahathir’s thoughts and ideas, but ZAM’s original thinking about Malaysian nationalism, the Malay agenda and the assertion of Malaysian sovereignty in the face of Western dominance. Many of these ideas are reflected in what is conveniently called Mahathirism. By personal choice ZAM became UMNO's (United Malays National Organization) official spokesman and the journalist, who through his own thinking and unique perspectives on government policies, emphasised Mahathir's political and economic objectives for Malaysia, as well as Mahathir's emphasis on the Malay agenda, as the intellectual basis for his pro-Mahathir editorials. Utusan editorials are primarily influenced by ZAM's thinking and his commitment to Mahathirism or aspects of it.

A cellular hierarchy framework for understanding heterogeneity and predicting drug response in acute myeloid leukemia.

The treatment landscape of acute myeloid leukemia (AML) is evolving, with promising therapies entering clinical translation, yet patient responses remain heterogeneous, and biomarkers for tailoring treatment are lacking. To understand how disease heterogeneity links with therapy response, we determined the leukemia cell hierarchy makeup from bulk transcriptomes of more than 1,000 patients through deconvolution using single-cell reference profiles of leukemia stem, progenitor and mature cell types. Leukemia hierarchy composition was associated with functional, genomic and clinical properties and converged into four overall classes, spanning Primitive, Mature, GMP and Intermediate. Critically, variation in hierarchy composition along the Primitive versus GMP or Primitive versus Mature axes were associated with response to chemotherapy or drug sensitivity profiles of targeted therapies, respectively. A seven-gene biomarker derived from the Primitive versus Mature axis was associated with response to 105 investigational drugs. Cellular hierarchy composition constitutes a novel framework for understanding disease biology and advancing precision medicine in AML.

Critical food guidance for tackling food waste in Canada

Food waste is a complex problem with far reaching negative environmental, social, and economic impacts. To identify appropriate solutions to address food waste, the food recovery hierarchy developed by the Environmental Protection Agency is currently the most popular guiding framework in food waste prevention and reduction. However, this paper found that the application and the interpretation of the guide is quite problematic due to its lack of consideration of scale in efforts to prevent and reduce food loss and waste. Furthermore, the food recovery hierarchy is premised on a linear food supply chain instead of a circular approach. Although the hierarchy recommends prevention as the most preferred approach, it still provides the option (albeit less preferred) to landfill food waste. Based on values and worldviews that potentially serve as better tools for food waste prevention and reduction, this paper explores the tensions within the food recovery hierarchy framework and identifies alternative critical food guidance developed in a Canadian social innovation lab.

A Lightweight Authentication Framework for Wireless Sensor Networks

Wireless Sensor Network (WSN) is emerging as a dominant technology with its applications in areas like agriculture, communication, environment monitoring, and surveillance. The inherited vulnerability and resource-constrained nature of sensor nodes led researchers to propose many lightweight cryptographic protocols for WSN. These sensors are low-cost, low energy, have low processing capability and have low storage restrictions. WSN suffers from many risks because of these unique constraints. This paper proposes a new lightweight security framework for WSNs and covers different lightweight cryptographic schemes for WSN applications. The aim is to provide cryptographic primitives for integrity, confidentiality, and protection from the man-in-the-middle and reply attacks. The work is based solely on symmetric cryptography and it has four phases; Network Initialization, Node Initialization, Nodes Communication, and Node Authentication. This work adopts the Low-Energy Adaptive Clustering Hierarchy (LEACH) framework, which deploys random rotation to distribute the energy among a group of nodes. The probability of attacking in LEACH is higher at cluster head and member nodes. Therefore, data transmission among communicated nodes is encrypted over multiple levels of protection by dynamic session keys to provide a high level of security. In addition, an authentication ticket is provided by a cluster head for each authenticated node to identify another node. The session keys are dynamically generated and updated during the communication to prevent compromising or capturing the keys. Through simulation and evaluation of the system, the results showed less energy consumption and efficient cryptographic primitive were compared with existing schemes

Ecological equivalence assessment: The potential of genetic tools, remote sensing and metapopulation models to better apply the mitigation hierarchy

Within the framework of the mitigation hierarchy, biodiversity offsetting is the main tool promoted to reach No Net Loss. One of the determining factors of offsetting success is the evaluation of ecological equivalence. Various equivalence assessment methods (EAMs) have been developed to provide a framework to evaluate the balance between expected biodiversity losses and gains. In the context of achieving No Net Loss, EAMs must address challenges of Operationality, Currency, Uncertainty, Spatial scale and Time frame. In this study, we investigated the way the most widely used EAMs address these challenges, positing that certain tools from ecological science could limit the trade-offs between these challenges and improve the ecological assessment process. To this end, we analysed the risks and benefits associated with the inclusion of genetic tools (landscape genetics and eDNA), remote sensing and metapopulation models in selected EAMs.Our results revealed trade-offs between these five challenges, in particular between Operationality and Currency. The EAMs varied strongly in these two aspects, depending on the general assessment approach and the biodiversity component they focus on. To a lesser degree, Time frame and Spatial scale also differed between the methods. We identified that the integration of the different tools differs among them, being easier for remote sensing and metapopulation models than for the genetic tools. Nevertheless, the integration resulted in benefits compared to the current use of the methods – benefits that included improving the objectivation of the assessment and the automatization potential. The tools also show potential for automatization, which could have major benefits for operationality. In terms of risks, the integration of these tools increases the technical complexity of the methods, requiring new skills, and would change the overall approach of the ecological assessment.

A new hierarchy framework for feature engineering through multi‐objective evolutionary algorithm in text classification

SummarySentiment classification is a field of sentiment analysis concerned with analyzing opinions, emotions, evaluations, and attitudes regarding a special topic like a product, an organization, a person, or an incident. With the growth of user‐generated content on the Web, this field gained great importance in online reviews. With a wide range of reviews, customers cannot read all reviews. Considering the increasing rate of electronic documents and the urgent need manually mine for keywords that are hard and time‐consuming, doing the same automatically is of high demand. A new framework proposed here to mine and classify users' comments based on mining keywords by applying the sequence pattern mining through the Separation‐Power concept, a multi‐objective evolutionary algorithm based on decomposition with four objectives, and a neural network as the final classifier. Some modifications are made on multi‐objective evolutionary algorithm based on decomposition and Apriori algorithms to improve the text classification efficiency. To evaluate the proposed framework, three datasets applied; which compared with the two methods to measure accuracy, precision, recall, and error‐index. The results indicate that this framework provides a better outcome than its counterparts with 99.45 precision, 99.34 accuracy, 99.48 recall, and 99.28% f‐measure.

Representing Route Familiarity Using the Abstraction Hierarchy Framework.

Familiarity with a route is influenced by levels of dynamic and static knowledge about the route and the route network such as type of roads, infrastructure, traffic conditions, purpose of travel, weather, departure time, etc. To better understand and develop route choice models that can incorporate more meaningful representations of route familiarity, OBDII devices were installed in the vehicles of 32 drivers, 65 years and older, for a period of three months. Personalized web-based trip diaries were used to provide older drivers with post-trip feedback reports about their risky driving behaviors, and collect feedback about their route familiarity, preferences, and reasons for choosing the route driven vs. an alternate low-risk route. Feedback responses were analyzed and mapped onto an abstraction hierarchy framework, which showed that among older drivers, route familiarity depends not only on higher abstraction levels such as trip goals, purpose, and driving strategies, but also on the lower levels of demand on driving skills, and characteristics of road type. Additionally, gender differences were identified at the lower levels of the familiarity abstraction model, especially for driving challenges and the driving environment. Results from the analyses helped highlight the multi-faceted nature of route familiarity, which can be used to build the necessary levels of granularity for modelling and interpretation of spatial and contextual route choice recommendation systems for specific population groups such as older drivers.

An Analytical Framework of Tonal and Rhythmic Hierarchy in Natural Music Using the Multivariate Temporal Response Function.

Even without formal training, humans experience a wide range of emotions in response to changes in musical features, such as tonality and rhythm, during music listening. While many studies have investigated how isolated elements of tonal and rhythmic properties are processed in the human brain, it remains unclear whether these findings with such controlled stimuli are generalizable to complex stimuli in the real world. In the current study, we present an analytical framework of a linearized encoding analysis based on a set of music information retrieval features to investigate the rapid cortical encoding of tonal and rhythmic hierarchies in natural music. We applied this framework to a public domain EEG dataset (OpenMIIR) to deconvolve overlapping EEG responses to various musical features in continuous music. In particular, the proposed framework investigated the EEG encoding of the following features: tonal stability, key clarity, beat, and meter. This analysis revealed a differential spatiotemporal neural encoding of beat and meter, but not of tonal stability and key clarity. The results demonstrate that this framework can uncover associations of ongoing brain activity with relevant musical features, which could be further extended to other relevant measures such as time-resolved emotional responses in future studies.

Towards an integration of two aspects of semiosis – A cognitive semiotic perspective

Meaning-making processes, understood hierarchically, in line with the Semiotic Hierarchy framework, change on various timescales. To account for and predict these changes, one can take a cognitive view on semiosis. I adopt an interdisciplinary approach combining semiotic studies and cognitive studies in an attempt to account for meaning-making activity and to predict the course of semiosis. In this context, I consider meaning-making activity as shaped by both “external” (to a semiotic system) as well as “internal” factors. I also show how both the “external” and “internal” sources of the dynamicity of meaning-making should be framed in terms of studies on cognition.
 I start with a non-standard, 4e approach to meaning-making. According to this framework, meaning-making processes are constituted by (and not just dependent on) environmental and bodily factors. The dynamicity of semiosis can be accounted for in terms of an experiencing, embodied subject (agent) enacting her/his/its own domain of meaningful phenomena. As I argue, this perspective on meaning-making is the cognitive foundation of the first two levels of the Semiotic Hierarchy.
 In the following sections I present the Peircean view on signs and semiosis, according to which semiosis is a result of the very nature of a sign and a sign system. In this view, the dynamicity of semiosis has primarily “internal” sources: it stems from the unavoidable fallibility of interpretation and synechism of signs. As I show, this aspect of semiosis can be addressed by means of standard (cognitivist) cognitive science and by means of cognitive modelling.
 Ultimately, I sketch a proposal of an attempt to develop a uniform cognitive framework allowing for integration of the above-mentioned aspects of semiosis – a framework based on Rowlands’ idea of the Amalgamated Mind.

Evolutionary framework of hierarchy of effects models: exploring relevance in the shifting of customer path

Purpose The hierarchies of effects models have been perpetually updated across different time period. Ever since the evolution of the primary customer path indicated through the Attention, Interest, Desire, Action model in the 1900s, the hierarchical frameworks have witnessed a significant transformation in context to the present age of Web connectivity. Therefore, the purpose of this study is to understand the transformation in the hierarchy of effects models in the age of connectivity. Design/methodology/approach This paper is conceptual in nature and an attempt to provide an overall view of the shifting dimension in the customer path as indicated in the various hierarchies of effects models since evolution up to the age of digitalisation. Findings It is observed that in the age of connectivity customer loyalty is expressed in terms of brand advocacy rather than repurchase, and that the customer path has been redefined. This seems pertinent because of the swift exchange of information that occurs among the online customer communities. Originality/value This paper identifies a need to provide a contemporary outlook to the customer path in the age of internet connectivity.

Coordinated management of aggregated electric vehicles and thermostatically controlled loads in hierarchical energy systems

This paper presents an energy management model for electric vehicles (EVs) and thermostatically controlled loads (TCLs) in intelligent energy systems based on the transactive control of aggregators. The management strategy will penetrate through three physical layers of electricity networks: transmission layer, distribution layer, and behind-meter layer. In the proposed framework, the aggregated EVs are modeled as a battery energy storage system (BESS), and the aggregated TCLs are modeled as a virtual energy storage system (VESS) at the behind-meter layer. A deep learning method, namely a hybrid of convolutional neural networks and long short-term memory (CNN-LSTM), is used to forecast the local loads of EVs and TCLs. The aggregators can dispatch these controllable loads directly as demand management to fit the predicted load curve. Peer-to-peer (P2P) trading is realized at the distribution level, and distributed optimization is utilized since the information between each aggregator is opaque. The primal problem is decoupled into subproblems of aggregators. The sub-gradient method is employed to update the multipliers of each decomposed Lagrange function. After the local energy transaction is cleared at the distribution level, wind generators and thermal generators are centrally dispatched at the transmission level based on the conventional optimal power flow model. The proposed hierarchy framework is verified in the IEEE 30-bus system. Simulation results reveal that the scalability issue of single-layer centralized dispatch can be well addressed, and end-users’ information privacy can be protected. The coordinated management of EVs and TCLs also brings in economic and environmental benefits.

A coordinated scheme for transmission and distribution expansion planning: A Tri-level approach

In traditional power system planning problems, transmission and distribution networks are separated, which is not suitable for future power systems due to the rapid development of active distribution networks. This paper presents a hierarchy framework to optimize the transmission and distribution network expansion in a simultaneous manner. The proposed decentralized decision-making architecture forms a Tri-level structure where the first level is the transmission expansion planning (TEP) problem solved by the transmission system operator (TSO) as the leader, while the second level is the distribution expansion planning (DEP) problem solved by the distribution system operators (DSOs) as the second level followers. The third level problem is the optimal economic dispatch problem solved by the independent system operator (ISO) as the third level follower. The economic dispatch problem is replaced by its primal-dual (PD) formulation leading to a bilevel multi-follower mixed-integer linear programming (BMF-MILP) problem. Then, by using multi-parametric programming (MPP) method, the BMF-MILP problem is recast as several single level independent optimization problems. Numerical experiments are shown to corroborate the efficiency and tractability of the presented model. The results show the new coordinated transmission and distribution expansion planning (CTDEP) model provides additional flexibility and reduces the total cost.

Modelling and optimisation of oil palm biomass value chains and the environment–food–energy–water nexus in peninsular Malaysia

This study aims to develop a decision model to optimise the oil palm biomass value chains by minimising the environmental impact whiles generating economy value from their bioproducts. The model considers two major components, namely, a fuzzy analytic hierarchy (FAHP) framework and a multi-objective optimisation model. Both components will be used by integrating the priorities of the environmental and economic impacts obtained from experts' judgement with the multi-objective optimisation model to generate an optimal solution based on expert's judgement. The framework used to study different case study for the oil palm industry in Peninsular Malaysia. Results show that a maximum profit of 267,116,398 USD per year can be achieved. However, to minimise the environmental impact, a 34% cut of the profit is needed to reduce 91% of CO2 emissions generated and 97% of water consumption. Moreover, the model generates optimal pathways by selecting the processing facilities that are needed in the value chain to achieve the objectives. The biomass or bio-product distribution networks around Peninsular Malaysia are also presented in this paper. Several scenarios are discussed to observe the effects on the optimal value chain solutions by manipulating the production level. On the basis of the results, the interactions of the environment–food–energy–water nexus are investigated. Therefore, this study can contribute to the improvement of oil palm industry policies while addressing sustainability issues through the proposed value chain model.

Climate change beliefs and support for development: Testing a cognitive hierarchy of support for natural resource-related economic development in rural Pennsylvania

Economic development in rural areas is commonly tied to the use of natural resources. These uses can be categorized as extractive (e.g. mining, natural gas, and logging) or non-extractive (e.g. real estate, tourism, outdoor recreation , and wind energy). Research has shown local support is crucial for sustainable economic development. Therefore, understanding what drives support can help researchers better understand why some projects succeed where others do not. This becomes increasingly important in the face of global climatic change. Extractive uses of natural resources in rural areas are associated with high volumes of CO2 emissions and will have to be greatly reduced if the United States is to successfully respond to climate change. In their place, non-extractive forms of natural resource development have emerged as possible alternatives in transition. Therefore, understanding the impact of climate change beliefs on support for different forms of natural resource development is beneficial for ensuring equitable plans that reflect the needs and desires of rural residents. Using a cognitive hierarchy framework, we test a model hypothesizing support for extractive or non-extractive development is influenced by climate change beliefs which are influenced by both environmental beliefs and political conservatism . We test our model on a sample of rural Pennsylvanians using structural equation modeling and find mixed support for the model. Notably, anthropocentrism and biocentrism both had positive relationships with both forms of development, refuting hypotheses. Further, belief in anthropogenic climate change had a positive relationship with extractive support, but no relationship with non-extractive support. • Cognitive models of attitudes are insufficient. • Anthropocentrism increased support for all natural resource development. • Beliefs in climate change decreased support for resource extraction. • Beliefs in climate change had no impact on non-extractive natural resource development.