Obtaining the effective gripper dimensions for a kiwifruit harvesting robot using kinematic calibration procedures

Purpose A harvesting robot is developed as part of kiwifruit industry automation in New Zealand. This kiwifruit harvester is currently not economically viable, as it drops and damages too many kiwifruit in the harvesting task due to the positional inaccuracy of the gripper. This is due to the difficulties in measuring the exact effective dimensions of the gripper from the manipulator. The purpose of this study is to obtain the effective gripper dimensions using kinematic calibration procedures. Design/methodology/approach A setup of a constraint plate with a dial gauge is proposed to acquire the calibration data. The constraint plate is positioned above the robot. The data is obtained by using a dial gauge and a permanent marker. The effective dimensions of the gripper are used as error parameters in the calibration process. Calibration is exercised by minimizing the difference between target positions and measured positions iteratively. Findings The robot with the obtained effective dimensions is tested in the field. It is found that the fruit drops due to positional inaccuracy of the gripper are greatly reduced after calibration. Practical implications The kiwifruit industry in New Zealand is growing rapidly and announced plans in 2017 to double global sales by 2025. This growth will put extra pressure on the labour supply for harvesting. Furthermore, the Covid pandemic and resulting border restrictions have dramatically reduced seasonal imported labour availability. A robotic system is a potential solution to address the labour shortages for harvesting kiwifruit. Originality/value For kiwifruit harvesting, the picking envelope is well above the robot; the experimental data points obtained by placing a constraint plate above the robot are at similar positions to the target positions of kiwifruit. Using this set of data points for calibration yields a good effect of obtaining the effective dimension of the gripper, which reduces the positional inaccuracy as shown in the field test results.

The blessing of dimensionality for the analysis of climate data

We give a simple description of the blessing of dimensionality with the main focus on the concentration phenomena. These phenomena imply that in high dimensions the lengths of independent random vectors from the same distribution have almost the same length and that independent vectors are almost orthogonal. In the climate and atmospheric sciences we rely increasingly on ensemble modelling and face the challenge of analysing large samples of long time series and spatially extended fields. We show how the properties of high dimensions allow us to obtain analytical results for e.g. correlations between sample members and the behaviour of the sample mean when the size of the sample grows. We find that the properties of high dimensionality with reasonable success can be applied to climate data. This is the case although most climate data show strong anisotropy and both spatial and temporal dependence, resulting in effective dimensions around 25–100.

Dimension Reduction Big Data Using Recognition of Data Features Based on Copula Function and Principal Component Analysis

Nowadays, data are generated in the world with high speed; therefore, recognizing features and dimensions reduction of data without losing useful information is of high importance. There are many ways to dimension reduction, including principal component analysis (PCA) method, which is by identifying effective dimensions in an acceptable level, reducing dimension of data. In the usual method of principal component analysis, data are usually normal, or we normalize data; then, the principal component analysis method is used. Many studies have been done on the principal component analysis method as a step of data preparation. In this paper, we propose a method that improves the principal component analysis method and makes data analysis easier and more efficient. Also, we first identify the relationships between the data by fitting the multivariate copula function to data and simulate new data using the estimated parameters; then, we reduce the dimensions of new data by principal component analysis method; the aim is to improve the performance of the principal component analysis method to find effective dimensions.

A scoping review of public hospitals autonomy in Iran: from budgetary hospitals to corporate hospitals

Background Organizational reforms of hospitals in Iran are mainly aimed at improving efficiency, reducing government spending on health care, and improving the quality of services. These reforms began with hospital autonomization and have continued with other initiatives such as formation of board of trustees, independent and corporatized hospitals. Objective The purpose of this scoping review was to summarize and compare the results of studies conducted on organizational reform of hospitals in Iran to paint a more clear picture of the status quo by identifying knowledge gaps, inform policymakers, and guide future studies and policies. Method This review’s methodology was inspired by Arksey and O’Malley’s methodological framework to examine the extent, range, and nature of research activity about organizational hospital reforms in Iran. A literature search was performed using PubMed, Scopus, Web of Science, and Google Scholar for English papers as well as SID, IranDoc, Magiran, and the Social Security Research Institute Database for Persian papers from 1991 to April 2020. Results Twenty studies were included in the review. Studies were grouped by the types of organizational reform, study’s objective, setting, methodology, data collection and analysis techniques, and key findings. Thematic construction was used based on the types of organizational reform to present a narrative account of existing literature. Conclusions The autonomy granted to the hospitals was unbalanced and paradoxical in terms of key effective dimensions. Poor governance and regulatory arrangements, low commitment to corporate governance, Inappropriate board composition, weak internal controls, unsustainable financing and inefficient payment mechanisms, poor interaction with stakeholders and ignoring contextual factors have been cited as the main reasons for the failure of organizational reforms in Iran. The limited use of evidence and research was obvious at different stages of policymaking, especially in the policy formulation phase and evaluation of its results.

Feasibility Study of Fluidic Sealing in Turbine Shroud

This paper analyses the methods for manufacturing turbine blades, focusing on the possibility of manufacturing slots in the region of the shroud. The reason for this analysis is the new flow control technique that can be used to limit the shroud leakage flow in a turbine—the air curtain. The air curtain uses a bypass slot to connect the upstream cavern of a shroud seal with the tip of a shroud fin. The bypass slot is an essential part of the solution, while at the same time introducing difficulties in the manufacturing process. Additionally, a parametric study on the bypass slot dimensions is performed using numerical simulations. The features of the numerical model and its validation against experimental data are presented. The parametric study includes the inlet and outlet dimensions, as well as the width of the slot. The most effective dimensions are shown, along with a possible explanation as to why they are the most effective. Interestingly, a slot that does not cover the whole span of the fin is more effective than a slot covering the whole span of the fin. This is caused by additional streamwise vortices that are created in the proximity of the bypass slot.

MODIFIED EFFECTIVE AREA APPROACH TO ESTIMATE MOTORCYCLE EQUIVALENT UNITS IN AHMEDABAD CITY

This paper presents a methodology for estimation of Motorcycle Equivalent Units (MEU) in mixed traffic flow for motorcycle dominated traffic with increased accuracy by considering dynamic characteristics of subject vehicles, like speed and effective area. Besides, this increased accuracy is the result of the inclusion of speed of adjacent motorcycles in the form of speed ratios to estimate the effective area required by the subject vehicle at a particular speed. The effective area for each sample is computed with consideration of the effective dimensions and speed of that subject vehicle and its adjacent motorcycles on both sides in the proposed methodology. Two mid-block sections of urban roads in Ahmedabad city were selected for field data collection by videography method in this case study. The collected field data was analysed through Speed Estimation from Video Data (SEV) software. A table of classified speed ratios is also presented to derive an idea regarding the magnitude of change in lateral clearances of subject vehicles. The MEU values obtained for cars, motorcycles, rickshaws, buses, Light Commercial Vehicles (LCV), and bicycles were 3.02, 1.00, 1.84, 9.82, 6.2, and 1.9 respectively. Further, the proposed model was compared with a previously developed model to justify the increase in accuracy and to observe the variations in MEUs. The values estimated can be used to establish speed-flow relations, measure roadway capacity in urban roads, analyse the level of service in order to plan suitable traffic control and regulatory measures.

The blessing of dimensionality for the analysis of climate data

We give a simple description of the blessing of dimensionality with the main focus on the concentration phenomena. These phenomena imply that in high dimensions the length of independent random vectors from the same distribution have almost the same length and that independent vectors are almost orthogonal. In climate and atmospheric sciences we rely increasingly on ensemble modelling and face the challenge of analysing large samples of long time-series and spatially extended fields. We show how the properties of high dimensions allow us to obtain analytical results for, e.g., correlations between sample members and the behaviour of the sample mean when the size of the sample grows. We find that the properties of high dimensionality with reasonable success can be applied to climate data. This is the case although most climate data show strong anisotropy and both spatial and temporal dependence resulting in effective dimensions around 25–100.

Design of a Model for Management of Referral System in the Iranian Urban Family Physician Program

Background: The purpose of this research was to identify the main dimensions of management of referral systems in family physician program and then introduce them to policymakers of the country primary health care. Methods: This descriptive-correlation study was designed in Mazandaran Province, northern Iran (2017). The participants were employees of health centers of Mazandaran and Fars Provinces, Iran. The dimensions influencing on the referral system were identified systematically in the selected countries by using researcher-made questionnaire according to a statistical method called Factor Analysis. The data sufficiency was evaluated by the Bartlett's and Kaiser-Meyer-Olkin’s tests. Reliability of test was calculated and confirmed according to Cronbach's Alpha and Combined Reliability tests. Validity of the test was calculated and confirmed based on the average variance extracted (AVE). Results: In confirmatory factor analysis, coefficient of effect of Electronic Health Record on referral system (as the most important dimension), coefficient of Family Physician, coefficient of structure of insurance, coefficient of policymaking in health care system, coefficient of proper stewardship of health system, and basic health care services, were 0.887, 0.877, 0.860, 0.804, 0.568, and 0.522, respectively. Conclusion: Six effective dimensions including Electronic Health Record (as the most important dimension), family physician, structure of insurance, policymaking in health care system, proper stewardship of health system, and basic health care services were identified. According to six effective dimensions on management model of the referral system in the Iranian urban family physician program, the health system authorities pay serious attention to the six identified dimensions of the current study to improve the health of the urban community