Hierarchical Theory Research Articles

Pengaruh Implementasi Teori Motivasi Hierarki Abraham Maslow Dalam Peningkatan Semangat Kerja Karyawan PT. Nutrihub

This study aims to examine the implementation of Abraham Maslow's Hierarchical Motivation Theory in increasing employee morale at PT. Nutrihub. The independent variables used in this study are self-actualization needs, esteem needs, social needs, safety needs, and physiological needs. The dependent variable is employee morale. The population in this study are employees of PT. Nutrihub. The sampling technique used was a saturated sample technique with a total sample of 76 employees. For data analysis carried out with validity and reliability tests, descriptive statistical tests, classical assumption tests, multiple regression analysis tests, tests determination, f test and t test. The results showed that the variables of self-actualization needs, esteem needs, social needs, safety needs, and physiological needs partially had a positive and significant effect on the morale of Nutrihub employees. The implications of this research are the basis for companies to see the effect of self-actualization, appreciation, social, security, physiology and employee morale and contribute to improving learning in students of the Faculty of Economics.
 Keywords: Self-Actualization Needs, Appreciation Needs, Social Needs, Security Needs, Physiological Needs, Employee Morale

Assessment of Land Desertification and Its Drivers in Semi-Arid Alpine Mountains: A Case Study of the Qilian Mountains Region, Northwest China

Land desertification associated with climate change and human activities significantly impacts ecosystem functioning in semi-arid alpine mountains. However, accurately revealing the state of desertification risk and the drivers of its evolution is frequently difficult, especially in the semi-arid alpine mountains. A new theoretical framework that combined qualitative and quantitative concepts has been developed to enhance ecological risk assessment in semi-arid alpine mountains and reveal the causes of desertification. The PSR model, multi-layer hierarchical theory, hierarchical analysis, inverse cloud generating principles, field surveys, structured questionnaires, and remote sensing techniques are all combined in this method. Our results showed that the risk of desertification in the study area exhibited a fluctuating trend between 2000 and 2020, with a period of decrease, followed by an increase, and then a subsequent decrease. However, the risk status remained overall stable, remaining at a light desertification level during the entire period. Desertification risk is driven primarily by climate warming and humidification, which can cause the melting of ice/snow. Additionally, increased rainfall and freeze–thaw cycles can enhance soil erosion, further exacerbating the risk. Conversely, the implementation of environmental protection projects, such as the establishment of protected areas, efforts to restore forests and grasslands, and initiatives to conserve soil and water, has been effective in limiting the increase in desertification risk. These efforts serve as a counterforce to the negative impacts of climate change and human activity, highlighting the beneficial effects of human intervention in preventing desertification. High-altitude, high-topographic relief places have considerable desertification risk, mainly in the alpine desert. Due to geography, grazing, rodent and pest infestation, and wildlife, there is still a risk of desertification expanding in low elevation areas. There will be a greater urgency in the future to enhance the management of anthropogenic activities in the local environment in order to handle the growing threat of desertification caused by climate change. This study combined the interactions of the natural environment and human activities, filled a research gap in assessing desertification risk, and revealed its driving mechanisms, as well as provided a theoretical foundation for improving the integrity and sustainability of ecosystems in semi-arid alpine regions and elsewhere.

On novel distributed fixed-time formation tracking of multiple hypersonic flight vehicles with collision avoidance

This paper aims to achieve collision-free formation tracking for multiple hypersonic flight vehicles without introducing conventional approximators such as fuzzy logic systems and neural networks. By relying on the hierarchical control theory, a globally fixed-time distributed formation control protocol with guaranteed tracking behaviors is proposed. Firstly, for the purpose of deriving the virtual control commands in the three-dimensional translational dynamics, a fixed-time consensus control input is presented. Then, by designing a comprehensive performance-preserving feedback control law, the actual control commands are derived, so that the virtual control inputs can be tracked timely and accurately. Meanwhile, with resort to a novel exponential-type artificial potential function, a collision-free control input is proposed to avoid close proximity between adjacent hypersonic flight vehicles. Summarily, the outstanding advantage of the proposed protocol is that it simultaneously realize the collision-free formation tracking, fixed-time stability and performance-preserving control for multiple hypersonic flight vehicles with uncertain dynamics. Lyapunov stability criterion verifies the closed-loop stability, showing that the error signals can attenuate to a tiny region around the origin within a user-specified time. Finally, comparative numerical simulations are performed to further demonstrate the theoretical results.

Exploring Constraints to Well-Being for Older Adults in Transition Into an Assisted Living Home: A Qualitative Study.

Transitions into an assisted living home (ALH) are difficult and may impact the well-being of older adults. A thematic analysis guided by grounded theory was employed to better understand how a transition into an ALH influenced older adults' overall well-being. Individual, face-to-face interviews were conducted with a convenience sample of 14 participants at an ALH in the rural, southeastern U.S. Two central findings that influenced well-being during the transition process were revealed: loss of independence (sub-themes include loss of physical and mental health and loss of driving) and downsizing in space and possessions. The themes support and broaden the Hierarchical Leisure Constraints Theory, a Modified Constraints to Wellbeing model is proposed, and implications for older adult health care practitioners in ALHs are recommended. Further research is needed on the Modified Constraints to Wellbeing model and how to better describe these constraints to older adults' well-being when relocating into ALHs.

From partners to populations: A hierarchical Bayesian account of coordination and convention.

Languages are powerful solutions to coordination problems: They provide stable, shared expectations about how the words we say correspond to the beliefs and intentions in our heads. Yet, language use in a variable and nonstationary social environment requires linguistic representations to be flexible: Old words acquire new ad hoc or partner-specific meanings on the fly. In this article, we introduce continual hierarchical adaptation through inference (CHAI), a hierarchical Bayesian theory of coordination and convention formation that aims to reconcile the long-standing tension between these two basic observations. We argue that the central computational problem of communication is not simply transmission, as in classical formulations, but continual learning and adaptation over multiple timescales. Partner-specific common ground quickly emerges from social inferences within dyadic interactions, while community-wide social conventions are stable priors that have been abstracted away from interactions with multiple partners. We present new empirical data alongside simulations showing how our model provides a computational foundation for several phenomena that have posed a challenge for previous accounts: (a) the convergence to more efficient referring expressions across repeated interaction with the same partner, (b) the gradual transfer of partner-specific common ground to strangers, and (c) the influence of communicative context on which conventions eventually form. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The effect of embedded structures on cognitive load for novice learners during block-based code comprehension

BackgroundCoding has become an integral part of STEM education. However, novice learners face difficulties in processing codes within embedded structures (also termed nested structures). This study aimed to investigate the cognitive mechanism underlying the processing of embedded coding structures based on hierarchical complexity theory, which suggests that more complex hierarchies are involved in embedded versus sequential coding structures. Hierarchical processing is expected to place a great load on the working memory system to maintain, update, and manipulate information. We therefore examined the difference in cognitive load induced by embedded versus sequential structures, and the relations between the difference in cognitive load and working memory capacity.ResultsThe results of Experiment 1 did not fully support our hypotheses, possibly due to the unexpected use of cognitive strategies and the way stimuli were presented. With these factors well controlled, a new paradigm was designed in Experiment 2. Results indicate that the cognitive load, as measured by the accuracy and response times of a code comprehension task, was greater in embedded versus sequential conditions. Additionally, the extra cognitive load induced by embedded coding structures was significantly related to working memory capacity.ConclusionsThe findings of these analyses suggest that processing embedded coding structures exerts great demands on the working memory system to maintain and manipulate hierarchical information. It is therefore important to provide scaffolding strategies to help novice learners process codes across different hierarchical levels within embedded coding structures.

When English complement clauses meet evidential adverbs

There is much literature about the licensing of complement clauses by complement-taking predicates. However, less has been written about the licensing of adverbs in a complement clause. This article addresses the licensing of English evidential adverbs in complement clauses extracted from the NOW corpus. The article discusses three factors that determine the distribution of evidential adverbs in complement clauses. These are the nature of the evidential adverbs, the constraints of the complement clause and the anchor of the evidential adverb. To explore the role of these three factors, I adopt the hierarchical scopal theory of Functional Discourse Grammar (FDG). If a complement clause licenses the inclusion of the evidential adverb, then there is a match. Should there be no alignment between the complement clause and the adverb, there will be a mismatch. The results of the analysis of the data show that there are mostly matches, which occur with either a current speaker anchor or an actor anchor. Secondly, it appears that in cases of mismatches, there is always a current speaker. It thus appears that a current speaker anchor can override the constraints of the complement clause.

The Temporal Challenge of Hope

Abstract Hope informs and inspires our actions. We look to succeed at achieving what we hope for, and this orients our hope towards the future in which time is conceived linearly. The connection between hope as success and linear time creates several difficulties when we seek to defend our hope. This is especially the case regarding past hopes and the dead, who can no longer hope for themselves. J. T. Fraser’s hierarchical theory of time’s conflicts is a complex theory of time that makes possible thinking through hope more critically.

Solar energy in Jordan: Investigating challenges and opportunities of using domestic solar energy systems

With the recent global increase in fossil energy prices post Covid-19 and the drive to enhance sustainability towards NetZero, renewable energy is becoming one of the key global technologies to power societies at an affordable cost. This paper presents a novel study in relation to solar energy use in residential dwellings in Jordan, to discuss the benefits and challenges of using domestic solar energy systems within the current context of increasing energy prices. The Self-Determination Theory and Maslow's Hierarchical Theory are discussed in-line with the findings. This study, in addition to literature review, has utilised qualitative and quantitative data collected from an on-line survey with 366 participants to investigate Jordanian consumers' energy consumption behaviour, perception of renewables, and major factors influencing solar energy adoption. The novelty of this study that it provides a bench mark of affordability for future initiatives. The Jordan Renewable Energy & Energy Efficiency Fund is currently creating several initiatives to drive the society to adopt renewable energy. The results of this study will help to identify the crucial factors that could be hindering the adoption and expansion of renewables, particularly solar energy. This work has investigated awareness, motivation, difficulties, affordability and level of satisfaction in relation to solar energy in domestic dwellings. The results of this study have shown that Jordanians believe that financial affordability and awareness are both crucial for utilising renewables. For current users of solar systems, there is an increased satisfaction in their performance levels. However, energy storage is critical for enhancing the implementation of solar energy due to the complexity of grid-connected systems and the need for off-grid installations. Therefore, if renewable energy providers and governmental bodies aim to expand the implementation of solar energy technology and enhance public engagement, then it can be suggested that they should expand the promotion process of solar energy through platforms and further initiatives that engage with the public and subsidise the cost to provide more affordable solar energy systems for residential dwellings. The aim is to decrease carbon emission, reduce energy cost and enhance sustainability towards Net Zero Carbon emission.

Multifield intermittency of dust storm turbulence in the atmospheric surface layer

Dust storms are typical dispersed two-phase atmospheric turbulence involving electrified charged dust particles. Previous observations have demonstrated that clean-air atmospheric turbulence is strongly intermittent. However, the intermittency of the wind velocity, concentration of dust particles with a diameter smaller than $10\ \mathrm {\mu }{\rm m}$ (PM10) and electric fields, known as multifield intermittency, has not been reported or characterized yet. Here, we quantify the small-scale multifield intermittency of dust storms using datasets obtained from the Qingtu Lake Observation Array and a wavelet-based data analysis technique. The results indicate that the probability density functions of the multifield increments are scale dependent, and the scaling exponents of the multifield structure functions exhibit anomalous scaling, suggesting that the multiple fields in dust storms are also highly intermittent. Specifically, the wind velocity during dust storms appears to be more intermittent as compared with clean-air conditions. Among the multiple fields, the small-scale intermittency is strongest for PM10 dust concentration, moderate for electric fields and weakest for wind velocity. Furthermore, the anomalous scaling of multiple fields is well described by the hierarchical structure theory of turbulence. It is theoretically predicted that the wind velocity displays a one-dimensional filamentary structure, while the PM10 dust concentration and electric fields display two-dimensional sheet-like structures. Finally, after removing the coherent components of the observed time series by the proposed wavelet conditioning statistics, Kolmogorov linear scaling is recovered for the multiple fields, suggesting that small-scale multifield intermittency is caused by the presence of small-scale coherent structures.

Peliatan Style in Legong Keraton Lasem Performance

The Legong Keraton Lasem dance is one of the classical Balinese dances featuring Panji's story about the love story of King Lasem and Diah Rangke Sari. This classical dance first appeared and developed in the palace environment of Bali. There have been many research results on the Legong Keraton Dance. However, there has not been any research that reveals the Legong Keraton Lasem and Peliatan Style. The problems are: 1) How did the Peliatan Style in Legong Lasem Performance Originate?; 2) What is the form of the Peliatan Style in Legong Keraton Lasem dance?. The purpose of this research was to reveal the existence of the Peliatan Style in Legong Keraton Lasem Performance, which has catapulted Bali's name into the eyes of the world. This research was conducted using qualitative methods. The source of the data for this study was the Legong performance, the dancers, musicians, artists, cultural observers, and related communities who were selected based on purposive sampling and snowball techniques. All data that has been collected through observation, interviews, and literature studies will be analysed using aesthetic theory, hierarchical theory, and practical theory. The results showed that the Peliatan Style in Legong Keraton has a distinctive characteristic in the volume of dance movements performed, which tends to be large with the maximum tilt of the dancer's body. It is different from how to dance the Legong Keraton in general. The Legong Keraton Lasem with Peliatan Style emerged due to two factors, namely internal and external factors. Internal factors include the talent possessed by the Legong dancers themselves. They dance with the aim of satisfying their material and spiritual needs. Meanwhile, encouragement from outside came from the environment of Peliatan Village, which is indeed famous for its artistic activities; its people are very passionate about art every day.

Identification of adequate sample size for conflict-based crash risk evaluation: An investigation using Bayesian hierarchical extreme value theory models

The use of traffic conflict-based models to estimate crash risk and evaluate the safety of road locations is a popular direction for road safety analysis. However, a challenging issue of traffic conflict-based crash risk modeling is the selection of an appropriate sample size. Reliable conflict-based crash risk models typically require a large sample size which is always very difficult to collect. Further, when choosing a sample size, the bias-variance trade-off of model estimation is a constant concern. This study proposes an approach for identifying an adequate sample size for conflict-based crash risk estimation models. The appropriate sample size is determined by checking the model convergence and its goodness-of-fit. A quantitative approach for objectively testing the model goodness-of-fit is developed. Both the trace plots and the variation tendencies of Brooks-Gelman-Rubin statistics of parameter simulation chains are examined to inspect the model convergence. A graphical method is also used to check the model goodness of fit. If the model has not converged or fits poorly, then additional samples are required. The proposed method was applied to identify the adequate sample size for a Bayesian hierarchical extreme value theory (EVT) block maxima (BM) model using traffic conflict data from four signalized intersections in the city of Surrey, British Columbia. The indicator, modified time to collision (MTTC), was used to delineate traffic conflicts. A series of stationary and non-stationary Bayesian hierarchical BM models were developed using the cycle-level maximums of negated MTTC. The adequate sample sizes of stationary and non-stationary Bayesian hierarchical BM models were determined separately. Further, two methods of increasing the sample size (i.e., extending the observation period and combining data from different sites) were compared in terms of goodness-of-fit as well as crash estimate accuracy and precision. The results show that for both stationary and non-stationary models, the sample size used is adequate for model convergence and goodness-of-fit. Moreover, adding covariates to the stationary Bayesian hierarchical BM model does not affect the size of the required sample. Extending the observation period outperforms combining data from different sites in terms of goodness-of-fit as well as crash estimation accuracy and precision of non-stationary models. This is likely related to the existence of unmeasured factors that could impair model estimation and inference when merging data from several sites to augment the number of samples. Overall, the findings of this study can be applied to examine whether available data is adequate and the amount of additional data required for producing reliable statistical inference.

Evaluating competing models of distress tolerance via structural equation modeling

Distress Tolerance (DT) is a transdiagnostic risk and maintenance factor implicated in a wide range of internalizing spectrum (INT) disorders. DT is commonly conceptualized as a higher-order construct, yet its lower-order dimensions are still debated. While the tolerance of negative emotions, frustration, and physical discomfort are widely considered to be central features of DT, the inclusions of intolerance of uncertainty (IU) and anxiety sensitivity (AS) are disputed. This study is the first to compare the two leading hierarchical models of DT directly. We also propose and test a DT model which includes IU and AS as lower-order dimensions. This “combined” model drew from the prior hierarchical theories and subsequent research demonstrating IU and AS to be highly correlated. To evaluate the competing models of DT, structured equation modeling was used to construct latent models representing each leading model and our novel “combined” model. A clinical sample was analyzed (N = 278), with participants having completed self-report scales measuring DT's theorized lower-order dimensions. Of the proposed models, the “combined” model demonstrated the best fit indices in the context of INT. A regression model with our “combined” model indicated that even after its shared variance with the Distress Intolerance Index (DII) was removed, it still had a moderate association with INT (β = 0.805, p < .01). This suggests that the only extant measure of the higher-order DT construct, the DII, fails to capture considerable variance in its latent structure. Future directions are discussed.

Research on Apples Motivational Behavior for Knowledge Workers

With the progress of society, the factors that affect the development and management of enterprises are also more diversified. Among them, the incentive mechanism for employees is a necessary factor to promote the development of enterprises; and knowledge-based employees, as products of the information age, are an important force to promote enterprises. This paper takes Apple as a case study to study the incentive mechanism of knowledge workers. Based on the definitions of motivational behavior and knowledge workers, the article looks for the application of motivational theories in organizational behavior such as Maslows Hierarchical Theory of Needs in Apple. By analyzing the research on the incentive mechanism of knowledge workers, it is found that Apple is more controversial in the two aspects of internal incentives and salary fairness for knowledge workers. Therefore, this article concludes based on the research results: Two-factor theory and fairness theory are what Apple needs to pay special attention to and use when conducting incentive behaviors. The significance of this research is to analyze the motivational behavior of the enterprise, improve it with the theory of organizational behavior, and practice it in the future enterprise management, so that the strengths of knowledge workers can promote the growth of the enterprise.

Formation of a Paradigm for Designing Cyber-Physical Systems: Educational Perspective

The subject of the article is the process of forming a paradigm for designing cyber-physical systems. The object of the work is cyber-physical systems. the purpose of the work is to increase the efficiency of cyber-physical systems in the economy and society. To achieve this goal, the following tasks are solved: the formation of a paradigm for designing cyber-physical systems. descriptions of methodological provisions of the general theory of cyber-physical systems. descriptions of the factors generated by the general theory of cyber-physical systems to increase the effectiveness of such systems. General characteristics of methods of design and research of cyber-physical systems at all stages of their life cycle. description of the content of new academic disciplines in the field of design and research of cyber-physical systems. Methods of the article are philosophy and methodology of science, theory of hierarchical systems, theory modeling, historical and system analysis, and theory of technological structures. The scientific novelty of the article is associated with the formation of the design paradigm of cyber-physical systems and the creation of a general theory of cyber-physical systems.

Research on home care model of intelligent community based on SD model -- Taking Meilin community as an example

The problem of aging has appeared in some countries, and the problem of providing for the aged has become one of the key issues. In recent years, aging has also become a social problem in China, but the current pension model can not meet the diversified and personalized needs of the elderly in China. In this paper, the intelligent community home-based elderly care model has become the forefront of academic research and a new topic of elderly care practice. On this basis, this paper sorts out the research context of the home-based elderly care model in smart communities, and uses Maslow's Hierarchical Needs Theory (MHNT) and Welfare Pluralism Theory (WPT) as research methods to analyze the needs of the elderly and the choice of welfare providers. In addition, this paper uses the method of system dynamics to establish a model to analyze the supply and demand balance of different pension models, and demonstrates the advancement of community home-based pension model. Finally, through the interview and investigation of the staff and managers of the smart community home-based elderly care model in Meilin community, Dongzhi County, Anhui Province, China, this paper summarizes the existing elderly care model in the community, and finds some deficiencies, such as the lack of full-time personnel, the inadequate use of new technologies and the lack of financial support. According to this, the paper puts forward corresponding countermeasures: (1) the problems of personnel can be solved by strengthening the training of service personnel, improving the system of volunteers and community service personnel working together, etc;(2) The problem of technology application can be solved by cooperating with external enterprises or other organizational units in research and development; (3In terms of financial support, it is necessary to broaden the channels of obtaining funds, seek the cooperation of enterprises, and adopt the innovative pension service mode of charging for providing high-end services and using the income for public welfare free basic services to effectively raise funds. Through the above research, the authors can put forward solutions to the pension problems faced by Meilin community, integrate relevant resources, and reduce the social burden.

Measuring accountability in interlocal agreements between Indigenous and local governments

AbstractInterlocal agreements are becoming a popular policy tool for facilitating intergovernmental coordination and cooperation in Canada and the United States. Indigenous and local governments are also turning to these agreements despite long histories of colonialism, exploitation and dispossession by the settler State toward Indigenous communities. To what extent do interlocal agreements between Indigenous and municipal governments require stringent accountability measures to facilitate intergovernmental coordination? Using a hierarchical Bayesian item response theory model, we explore this question by analyzing 317 interlocal agreements between Indigenous and municipal communities in Canada. We find that accountability strength varies significantly across agreements, contrary to our expectation that accountability requirements would be strong across agreements due to the long history of colonialism. We also find that some of the variation may be a function of the policy area addressed by each agreement, although this finding is likely the result of measurement uncertainty in our estimates.

High-Rise Residential Outdoor Space Value System: A Case Study of Yangtze River Delta Area

The outbreak of COVID-19 has drawn wider attention from residents with growing demand for outdoor space in residential areas because of restrictions on residents' mobility, especially in China. However, the high-rise residential complex in China is featured with a high population density along with less outdoor space per household. This means that the current status of outdoor space in residential areas is far from satisfying residents' growing needs. This is consistent with our preliminary survey that highlights general low satisfaction of residents with outdoor space. According to the hierarchical theory of needs, a literature review, and a questionnaire survey, a framework is proposed in this study to examine the universal value system of high-rise residential outdoor space using the Yangtze River Delta Area as a case study. This framework consists of six dimensions, i.e., space physical comfort (physical environment and space size), space function (functional complexity and scale, age-range, and time-range), space safety (daily, social, and hygiene safety), space diversity (spatial layerings, forms, and scales diversity), accessibility (spatial attraction and concentration and path clarity) and sustainability (cultural, social, ecological, and financial sustainability). Consequently, a questionnaire was designed according to the framework and 251 valid questionnaires were received. Then, structural equation modeling (SEM) was undertaken to examine the impact of each dimension on the value of outdoor space and the framework was optimized into four dimensions, i.e., space physical comfort, space function, space safety, and DAT (space diversity, accessibility, and sustainability). Finally, the mechanism of how outdoor space quality influences the high-rise residential complex is analyzed. These findings provide useful input for the future planning and design of high-rise residential areas.

Multivariate functional neuroimaging analyses reveal that strength-dependent face expectations are represented in higher-level face-identity areas

Perception is an active inference in which prior expectations are combined with sensory input. It is still unclear how the strength of prior expectations is represented in the human brain. The strength, or precision, of a prior could be represented with its content, potentially in higher-level sensory areas. We used multivariate analyses of functional resonance imaging data to test whether expectation strength is represented together with the expected face in high-level face-sensitive regions. Participants were trained to associate images of scenes with subsequently presented images of different faces. Each scene predicted three faces, each with either low, intermediate, or high probability. We found that anticipation enhances the similarity of response patterns in the face-sensitive anterior temporal lobe to response patterns specifically associated with the image of the expected face. In contrast, during face presentation, activity increased for unexpected faces in a typical prediction error network, containing areas such as the caudate and the insula. Our findings show that strength-dependent face expectations are represented in higher-level face-identity areas, supporting hierarchical theories of predictive processing according to which higher-level sensory regions represent weighted priors.

Designing Fairness in Autonomous Peer-to-peer Energy Trading

Several autonomous energy management and peer-to-peer trading mechanisms for future energy markets have been recently proposed based on optimization and game theory. In this paper, we study the impact of trading prices on the outcome of these market designs for energy-hub networks. We prove that, for a generic choice of trading prices, autonomous peer-to-peer trading is always network-wide beneficial but not necessarily individually beneficial for each hub. Therefore, we leverage hierarchical game theory to formalize the problem of designing locally-beneficial and network-wide fair peer-to-peer trading prices. Then, we propose a scalable and privacy-preserving price-mediation algorithm that provably converges to a profile of such prices. Numerical simulations on a 3-hub network show that the proposed algorithm can indeed incentivize active participation of energy hubs in autonomous peer-to-peer trading schemes.