Typical Squares Research Articles

Exploring the restorative benefits of work in smart working structures on vacations in small villages.

Processes of redefinition of work, already in place in the pre-pandemic era, with the advent of COVID-19, have become widely required. A "model of work" that uses new technologies and the development of existing ones to improve workers' performance and satisfaction has emerged. Smart working has changed how people work and, as a result, spaces must also change to support them. The use of prefabricated movable buildings (PMB) could represent an opportunity to create smart (and co-) working spaces in a regenerative contest. Small villages with historical, architectural, and naturalistic elements and slow-life features are potential platforms where vacation and work could merge easily. This paper aims to establish if working in movable offices, like the PMBs, which provide a high level of visual and acoustics interaction with the surroundings, and which is positioned in small villages' squares, can affect workers' sense of restoration and working performance. In a laboratory setting, in the SENS i-Lab, a videowall and a 3D spatial audio system were used to compare, in terms of restorativeness and self-reported cognitive performance, the effects of a high-rise building context of a City Business District (CBD), i.e. the control scenario, and of two typical squares of small Italian villages with historic buildings, without (HIS) and with water elements (HIS-W). The findings of the experimental sessions showed that when working in close contact (visual and auditory) with historical or water elements, where life flows slowly, workers perceived a higher sense of restoration while job performance was unchanged. Implementing smart working policies in small villages that encourage the use of energy-efficient prefabricated movable buildings and that offer a high level of visual and acoustic interaction with the surrounding environment may represent a promising strategy to foster the development of the local economy and contrast the depopulation of small villages, improving the worker well-being and the reducing the impact of their activities of the environment.

Summer outdoor thermal comfort assessment in city squares—A case study of cold dry winter, hot summer climate zone

Human thermal perception varies with climate. The Dwa climate zone covers vast areas. Conducting outdoor thermal comfort (OTC) studies here would benefit energy efficiency and the economy. However, since OTC research methods are not standardized, different research methods hamper comparing studies in the Dwa climate. This paper aims to determine the summer OTC of typical Dalian squares in the Dwa climate. Dalian is located in the cold A zone (2A) of the China Building Climate Division. The thermal environment of three typical squares was field measured, and a questionnaire survey of the residents was conducted. 33.2 % of Dalian residents evaluated the thermal environment as neutral, and 39.3 % considered it comfortable. And psychological perception and physical perception were not the same. Multiple methods were used to calculate outdoor thermal benchmarks and calibrate thermal stress for three thermal indexes, SET*, PET, and UTCI. Furthermore, PET, with a prediction accuracy of 25.3 %, was determined to be the best indicator applicable to Dalian in the summer. Finally, a comparison of studies under the Dwa climate zone, including Tianjin and Harbin, reconfirmed the mobility of the human thermal zone. These findings are precious and can contribute significantly to ensuring the sustainability of the outdoor environment.

A Spatial Analysis Methodology for the examination of Solar, Wind and Sky View Conditions in Traditional Squares of the Eastern Mediterranean Region

The study of microclimatic conditions, their ability to form determinant parameters of urban morphologies and their impact on the choices for the social interaction of dwellers, has been of increased interest to researchers over the last decades. In this context, spatial analysis methods for assessing the microclimate in public spaces, which can be exploited as means for improving the quality of life in the built environment, are increasingly used. In the framework of this study a spatial analysis methodology of solar, wind and sky view considerations was followed involving public open spaces, i.e., squares, in traditional settlements of Cyprus. Based on this investigation, the study presented herein focused on the spatial examination of the solar, wind and sky view conditions in three typical traditional case-study squares in different climatic regions of Cyprus, pertaining to the Mediterranean climate. The purpose of the study is to discern the potentials and limitations of various traditional built form structured outlines with respect to climate-conscious design, but more importantly to present qualitative comfort assessment tools which allow a spatial – visual perception of the parameters affecting thermal comfort. The assessment methodology which has been applied is based on seasonal image processing techniques of solar, wind and sky view factor parameters. The resulting thermal comfort maps open the road for a major advance in assessing outdoor open spaces through bioclimatic principles and can be used as tool by architects and planners to identify outdoor public spaces that require design interventions or as an initial design step in implementing new climate-based outdoor public spaces.

A canopy shading-based approach to heat exposure risk mitigation in small squares

The impact of climate change in recent years on public health risks continues to intensify, and rational arrangement of trees can effectively reduce urban heat islands. As a gathering place for residents' outdoor activities, the small squares widespread in a city have a high risk of daytime heat exposure during summer due to their lack of shelter. How to maintain a balance between openness and shading has become a challenge for urban design. The tree canopy plan that forms a continuous shaded area during the hottest hours of a typical summer day is provided based on the principles of planting economy, activity space adequacy, and heat stress relief effectiveness. Taking 5 typical squares in Dalian, China as an example, we calculated the spatio-temporal distribution of the mean radiant temperature (Tmrt) before and after tree canopy planning using the validated SOLWEIG model, and quantified the corresponding changes in risk levels. This study aims to provide climate change adaptation strategies for small squares to deal with health risks through implementing tree canopies. The results showed that the average Tmrt decreased by 3.5 °C -7.7 °C during the hottest period of the day (11:00–15:00, August 14, 2020). The high-risk areas were reduced by 27%–50.4%. The improvement rate of canopy planning is 53%–94% in the high-risk area, but only 36% in the medium-risk area. We concluded that square height-to-width ratios are associated with the degree of heat exposure risk, and squares with high levels of heat exposure risk have greater overall cooling potential after tree canopy planning. Implementing tree canopy planning can create continuous low-risk paths, while keeping the square open and protecting those who need to pass during the hottest hours. Compared with the medium-risk areas planted in squares, the planning benefits of high-risk areas are better.

The Influence of Big Data Management on Organizational Performance in Organizations: The Role of Electronic Records Management System Potentiality

Aim/Purpose: The use of digital technology, such as an electronic records management system (ERMS), has prompted widespread changes across organizations. The organization needs to support its operations with an automation system to improve production performance. This study investigates ERMS’s potentiality to enhance organizational performance in the oil and gas industry. Background: Oil and gas organizations generate enormous electronic records that lead to difficulties in managing them without any system or digitalization procedure. The need to use a system to manage big data and records affects information security and creates several problems. This study supports decision-makers in oil and gas organizations to use ERMS to enhance organizational performance. Methodology: We used a quantitative method by integrating the typical partial least squares (SEM-PLS) approach, including measurement items, respondents’ demographics, sampling and collection of data, and data analysis. The SEM-PLS approach uses a measurement and structural model assessment to analyze data. Contribution: This study contributes significantly to theory and practice by providing advancements in identity theory in the context of big data management and electronic records management. This study is a foundation for further research on the role of ERMS in operations performance and Big Data Management (BDM). This research makes a theoretical contribution by studying a theory-driven framework that may serve as an essential lens to evaluate the role of ERMS in performance and increase its potentiality in the future. This research also evaluated the combined impacts of general technology acceptance theory elements and identity theory in the context of ERMS to support data management. Findings: This study provides an empirically tested model that helps organizations to adopt ERMS based on the influence of big data management. The current study’s findings looked at the concerns of oil and gas organizations about integrating new technologies to support organizational performance. The results demonstrated that individual characteristics of users in oil and gas organizations, in conjunction with administrative features, are robust predictors of ERMS. The results show that ERMS potentiality significantly influences the organizational performance of oil and gas organizations. The research results fit the big ideas about how big data management and ERMS affect respondents to adopt new technologies. Recommendations for Practitioners: This study contributes significantly to the theory and practice of ERMS potentiality and BDM by developing and validating a new framework for adopting ERMS to support the performance and production of oil and gas organizations. The current study adds a new framework to identity theory in the context of ERMS and BDM. It increases the perceived benefits of using ERMS in protecting the credibility and authenticity of electronic records in oil and gas organizations. Recommendation for Researchers: This study serves as a foundation for future research into the function and influence of big data management on ERMS that support the organizational performance. Researchers can examine the framework of this study in other nations in the future, and they will be able to analyze this research framework to compare various results in other countries and expand ERMS generalizability and efficacy. Impact on Society: ERMS and its impact on BDM is still a developing field, and readers of this article can assist in gaining a better understanding of the literature’s dissemination of ERMS adoption in the oil and gas industry. This study presents an experimentally validated model of ERMS adoption with the effect of BDM in the oil and gas industry. Future Research: In the future, researchers may be able to examine the impact of BDM and user technology fit as critical factors in adopting ERMS by using different theories or locations. Furthermore, researchers may include the moderating impact of demographical parameters such as age, gender, wealth, and experience into this study model to make it even more robust and comprehensive. In addition, future research may examine the significant direct correlations between human traits, organizational features, and individual perceptions of BDM that are directly related to ERMS potentiality and operational performance in the future.

Optimization of 16-QAM and 32-QAM Constellations for Mitigating Impairments of Phase Noise in Millimeter-Wave Receivers

In this paper, two optimized circular quadrature amplitude modulations (C-16QAM and C-32QAM) are proposed to mitigate phase noise in millimeter-wave receivers. A six-port direct conversion receiver in a short range wireless link test bench is used to validate the concept. Those modulation techniques are performed through the optimization of both, Euclidean distance between symbols and the gap between the concentric rings of the symbol constellation. The numerical simulations and experimental results show that the proposed constellation schemes can achieve lower bit error rate (BER) compared to the typical squares 16-QAM and 32-QAM, and other C-16QAM and C-32QAM modulations, reported in the literature.

Investigation and Research on Student Satisfaction Evaluation of Campus Node Square—Taking Southwest University of Science and Technology as an Example

With the development and maturity of higher education in China, the construction of university campus is also facing many problems, among which the research and design of campus node square cannot be ignored. Aiming at investigating students’ satisfaction, this paper establishes a satisfaction evaluation index system. Relevant data of each evaluation index were obtained by questionnaire survey. By means of the fuzzy comprehensive evaluation method, this paper studies the relationship between the perceptual characteristics of four typical campus node squares in Qingyi Campus of Southwest University of Science and Technology and students’ satisfaction, which provides a reference for the humanized design of campus node space. The research shows that the four indexes of humanistic atmosphere, interest, ground pavement and atmosphere are the key points in the design and construction of campus node square. The four squares have different shapes. Except for the Light of Science and Technology Square, the satisfaction rate is 67%, and the other three squares are not satisfied by the majority of students. Finally, aiming at the problems of four squares, we put forward to optimize the layout, and improve the infrastructure and functional configuration, etc .

Cross-National Comparison of Soundscape in Urban Public Open Spaces between China and Croatia

There are similarities and differences between open public space soundscape evaluation in different countries, mainly due to the influence of cultural background. This paper systematically compares the effect of social-cultural context on soundscape of urban public open spaces in China and Croatia. Eleven well-known and typical squares were selected. A series of questionnaire surveys within the soundscape framework were carried out during the summer season, and gathered data were analyzed. Principal component analysis (PCA) resulted in two principal components, eventfulness and pleasantness, as notable soundscape factors. However, eventfulness is the major factor in China, and pleasantness is the major factor in Croatia. In terms of environmental satisfaction, natural condition is the major factor based on PCA. Urban condition is the second factor in China, however, it is the third factor in Croatia. It is interesting to note that the physical environment is the most important factor in Croatian inland and coastal places, which is different compared to Chinese places. Visit purpose is the dominant factor associated with sound and environmental satisfaction. Natural sound and children have mainly positive correlations to sound and environmental satisfaction in China, whereas sounds of human activities have mainly negative correlations to sound and environmental satisfaction in Croatia.

Local Preferences for Shea Nut and Butter Production in Northern Benin: Preliminary Results

Shea products in Benin (West Africa) are produced in a low-developed agroindustry, but they are estimated to be the country’s third largest export. The nut harvesting and quality guaranteeing in the butter process can only be achieved through improvements in the value chain, thus making it more attractive for stakeholders. The aim of this paper is to provide keys to a better product valorization, obtain a significant increase in household incomes based on shea butter marketing opportunities, and offer competitive products at the local and regional markets. Different markets were designed to catch processors and consumers’ preferences for two improved shea products: butter and nuts in Northern Benin. An open-ended contingent valuation (CV) was applied, and the willingness to pay (WTP) and willingness to accept (WTA) were estimated by using a typical ordinary least squares (OLS) modelling approach. On local markets in Benin, the color, length, and weight of the nuts, as well as the color, smell, and texture of shea butter significantly influence, respectively, the processors’ willingness to accept and the consumers’ willingness to pay for a specific quality level. An increase in price would ensure the quality of the shea butter and would be covered by the premium to be paid by consumers. Certification design and the development of shea resources management and conservation programs should include ethnic preferences and consider gender, to avoid reducing women’s profits in the shea butter local market.

Bankfull Shields number versus slope and grain size

ABSTRACTMany characteristics of alluvial rivers, including hydraulic geometry and sediment transport during periods of morphological activity, can be related to the bankfull Shields number. Recent papers have used regression analysis on large datasets of bankfull hydraulic geometry to formulate a predictive relation for bankfull Shields number as a function of reach-averaged channel slope and characteristic bed grain size. These results show different regression fits; the relationship for bankfull Shields stress is therefore still ambiguous. We propose a new relation via multivariate major axis regression, a symmetric, error-in-variables regression scheme, which improves on previous attempts by introducing error in both the dependent variable and independent variables. We discuss the use of typical ordinary least squares, Bayesian, and error-in-variables regressions to inform the use of regression statistical methods to quantify hydraulic geometry. The results reported here back previous claims that bankfull shear velocity is rather invariant to median bed material.

In any way, shape, or form? Toddlers’ understanding of shapes

Using the intermodal preferential looking paradigm, two-year-old children’s ability to discriminate valid (typical and atypical) squares, rectangles, triangles, and circles from invalid distractors was examined. The cognitive and environmental factors that might predict this ability were also investigated. Two-year-old children (N=33) were able to discriminate squares, triangles, and circles, but not rectangles. No significant cognitive or environmental predictors of this ability were found. The results suggest that the ability to shape discriminate at age two is under considerable development and that other factors may be responsible for children’s ability to discriminate shapes.

The Economics of Foreign Aid: Time Series Evidence from a Less Developed Country (LDC)

Empirical literature on aid-growth nexus mostly centered within cross-country framework exploiting typical ordinary least squares (OLS) estimation. As a result, scarcity prevails studies empirically examine country-specific causes of aid-growth nexus exercising distinct methods. This study aims to fill this gap, taking the case of Bangladesh- a leading aid recipient country. Empirical findings based on vector error correction modeling and Granger causality test unearth absence of long-run and short-run causality of aid on GDP growth. Therefore, this study argues that although aid remains a major component of LDCs macroeconomic framework; however, it is yet to emerge as a significant player in their economic growth.

Assessment of internal flesh browning in intact apple using visible-short wave near infrared spectroscopy

Certain cultivars of apple are prone to an internal flesh browning defect following extended controlled atmosphere storage. A number of (destructive) reference methods were assessed for scoring the severity of this defect in a fruit, including visual assessment, image analysis (% cross section area affected), International Commission on Illumination (CIE) chromameter Lab values of a cut surface and juice Abs420, of which visual scoring on a 5 point scale and a colour index based on CIE Lab were recommended. Non-invasive detection of this disorder using three instruments operating in the visible-shortwave near infrared (NIR) but varying in optical geometry (interactance, partial transmission and full transmission) was attempted. Quantitative prediction of defect level was best assessed using visible-shortwave NIRS in a transmission optical geometry, with a typical partial least squares (PLS) regression model with correlation coefficient of determination, R2p=0.83 and root mean square of errors of prediction=0.63 (5 point defect score scale). The binary classification approaches of linear discriminant analysis, PLS discriminant analysis, support vector machine approach and logistic regression were trialled for separation of acceptable fruit, with the best result achieved using the PLS discriminant analysis method, followed by linear discriminant analysis and support vector machine classification. Classification accuracy [(True Positive+True Negative)/(Positive+Negative)] on an independent validation population of >95% and a false discovery rate [False Positive/(True Positive+False Positive)]of <2% was achieved.

Modeling of a 1000 MW power plant ultra super-critical boiler system using fuzzy-neural network methods

A thermal power plant is an energy conversion system consisting of boilers, turbines, generators and their auxiliary machines respectively. It is a complex multivariable system associated with severe nonlinearity, uncertainties and multivariable couplings. These characters will be more evident when the system is working at a higher level energy conversion capacity. In many cases, it is almost impossible to build a mathematical model of the system using conventional analytic methods. The paper presents our recent work in modeling of a 1000MW ultra supercritical once-through boiler unit of a power plant. Using on-site measurement data, two different structures of neural networks are employed to model the thermal power plant unit. The method is compared with the typical recursive least squares (RLSs) method, which obviously demonstrated the merit of efficiency of the neural networks in modeling of the 1000MW ultra supercritical unit.

Instrumental Variable Analysis for Estimation of Treatment Effects With Dichotomous Outcomes

Instrumental variable analyses are increasingly used in epidemiologic studies. For dichotomous exposures and outcomes, the typical 2-stage least squares approach produces risk difference estimates rather than relative risk estimates and is criticized for assuming normally distributed errors. Using 2 example drug safety studies evaluated in 3 cohorts from Pennsylvania (1994-2003) and British Columbia, Canada (1996-2004), the authors compared instrumental variable techniques that yield relative risk and risk difference estimates and that are appropriate for dichotomous exposures and outcomes. Methods considered include probit structural equation models, 2-stage logistic models, and generalized method of moments estimators. Employing these methods, in the first study the authors observed relative risks ranging from 0.41 to 0.58 and risk differences ranging from -1.41 per 100 to -1.28 per 100; in the second, they observed relative risks of 1.38-2.07 and risk differences of 7.53-8.94; and in the third, they observed relative risks of 1.45-1.59 and risk differences of 3.88-4.84. The 2-stage logistic models showed standard errors up to 40% larger than those of the instrumental variable probit model. Generalized method of moments estimation produced substantially the same results as the 2-stage logistic method. Few substantive differences among the methods were observed, despite their reliance on distinct assumptions.

Interactive mesh deformation using equality-constrained least squares

Mesh deformation techniques that preserve the differential properties have been intensively studied. In this paper, we propose an equality-constrained least squares approach for stably deforming mesh models while approximately preserving mean curvature normals and strictly satisfying other constraints such as positional constraints. We solve the combination of hard and soft constraints by constructing a typical least squares system using QR decomposition. A well-known problem of hard constraints is over-constraints. We show that the equality-constrained least squares approach is useful for resolving such over-constrained situations. In our framework, the rotations of mean curvature normals are treated using the logarithms of unit quaternions in R^3. During deformation, mean curvature normals can be rotated while preserving their magnitudes. In addition, we introduce a new modeling constraints called rigidity constraints and show that rigidity constraints can effectively preserve the shapes of feature regions during deformation. Our framework achieves good performance for interactive deformation of mesh models.

Pansystems methodology and construction of magic squares

Some patterns of refined epitomes of pansystems methodology were revealed roles and the related of them in problem-solving , modeling, algorithm-generating and theory-constructing were introduced. An important application of pansystems methodology is to give some methods of constructing the typical pansymmetries-magic squares. 1 . a method of recursively constructing magic squares of order n ( n ⩾ 5) ; 2. when magic squares of order m ( m ⩾ 3) and magic squares of order n ( n ⩾ 3) are given a formula of obtaining magic squares of order mn ; 3. when magic squares of order m ( m ⩾ 3) are given, a method of obtaining magic squares of order 2 m .

Stabilized Identification Via GSVD Optimized Based on Bayesian Information Theoretic Criterion and Minimum Mean Squares Error

Identification of an impulse response by using strongly correlated input signals is a typical ill-posed least squares estimation problem. In the present paper, multiple number of regularization parameters are employed to regularize the inversion of a rank-deficient matrix consisting of input signals. We give two approaches for determining these regularization parameters by using only accessible signal data. The first approach is based on minimization of a new Bayesian information theoretic criterion (ABIC) which can be derived on a basis of the Bayesian statistical approach. The second one is based on minimization of an estimated mean squares error (EMSE) of the parameter estimate. An iterative algorithm is given to calculate the optimal regularization parameters and the noise variance estimate simultaneously. By applying the proposed schemes, one can identify oscillatory peaks outside of the frequency range of the input power spectrum, even if the PE condition is not satisfied or even when the number of input-output data is rather less than the length of impulse response to be estimated.