Background: Pharmacists must adjust their distance from patients to facilitate communication during interviews and gain their trust. The distance between the patients and the pharmacists varies depending on many facto...Background: Pharmacists must adjust their distance from patients to facilitate communication during interviews and gain their trust. The distance between the patients and the pharmacists varies depending on many factors, such as gender, posture and the patients’ mood. Only a few of these papers have actually measured and validated distance with patients. In this study, we validated our method of assessing mood and measuring distance before beginning a survey with patients. Methods: We measured comfortable interpersonal distance among men and women using an ecological scenario, in which a pharmacist approaches the subject, and the subject is asked to stop the pharmacist at the distance he/she feel comfortable with. Five pharmacists and 33 subjects participated in the study. The Japanese version of the Brief Mood Questionnaire Checklists (BMC-J) was used to quantify the subject’s mood for the day, and then the distance from the pharmacist that the subjects considered comfortable was measured at the bedside. The relationship between the mood and distance obtained was examined. Results: The comfortable distance of subjects was influenced by gender, posture, and mood. The shortest distance was 94.7 ± 11.1 cm (mean ± SD), for the male subjects versus the female pharmacists in the sitting position. The distance of male subjects shorted when they had positive emotions and lengthened when they were worried. Female subjects maintained a long distance from both male and female pharmacists when they had positive emotions and a short distance when they were worried. Conclusion: Findings show that the distance changes depending on the subjects’ mood at the time of measurement. It was found that the present measurement method can be used to determine the psychological state of the patient and measure the comfort distance at that time, and can be used as a simple method to examine these relationships. Therefore, it is also considered a practical method for the next step, which is a clinical study on patients.展开更多
We establish fixed point theorems in complete fuzzy metric space by using notion of altering distance, initiated by Khan et al. [Bull. Austral. Math. Soc. 30 (1984), 1-9]. Also, we find an affirmative answer in fuzzy ...We establish fixed point theorems in complete fuzzy metric space by using notion of altering distance, initiated by Khan et al. [Bull. Austral. Math. Soc. 30 (1984), 1-9]. Also, we find an affirmative answer in fuzzy metric space to the problem of Sastry [TamkangJ. Math., 31(3) (2000), 243-250].展开更多
Some common fixed point results for mappings satisfying a quasi-contractive condition which involves altering distance functions are obtained in partially ordered complete cone metric spaces. A sufficient condition fo...Some common fixed point results for mappings satisfying a quasi-contractive condition which involves altering distance functions are obtained in partially ordered complete cone metric spaces. A sufficient condition for the uniqueness of common fixed point is proved. Also, an example is given to support our results.展开更多
A class of pseudo distances is used to derive test statistics using transformed data or spacings for testing goodness-of-fit for parametric models. These statistics can be considered as density based statistics and ex...A class of pseudo distances is used to derive test statistics using transformed data or spacings for testing goodness-of-fit for parametric models. These statistics can be considered as density based statistics and expressible as simple functions of spacings. It is known that when the null hypothesis is simple, the statistics follow asymptotic normal distributions without unknown parameters. In this paper we emphasize results for the null composite hypothesis: the parameters can be estimated by a generalized spacing method (GSP) first which is equivalent to minimize a pseudo distance from the class which is considered;subsequently the estimated parameters are used to replace the parameters in the pseudo distance used for estimation;goodness-of-fit statistics for the composite hypothesis can be constructed and shown to have again an asymptotic normal distribution without unknown parameters. Since these statistics are related to a discrepancy measure, these tests can be shown to be consistent in general. Furthermore, due to the simplicity of these statistics and they come a no extra cost after fitting the model, they can be considered as alternative statistics to chi-square statistics which require a choice of intervals and statistics based on empirical distribution (EDF) using the original data with a complicated null distribution which might depend on the parametric family being considered and also might depend on the vector of true parameters but EDF tests might be more powerful against some specific models which are specified by the alternative hypothesis.展开更多
Connes' distance formula is applied to endow linear metric to three 1D lattices of different topologies with a generalization of lattice Dirac operator written down by Dimakis et al.to contain a non-unitary link-v...Connes' distance formula is applied to endow linear metric to three 1D lattices of different topologies with a generalization of lattice Dirac operator written down by Dimakis et al.to contain a non-unitary link-variable.Geometric interpretation of this link-variable is lattice spacing and parallel transport.展开更多
In the present paper, we prove some fixed point theorems of Hegedus contraction in some types of distance spaces, dislocated metric space, left dislocated metric space, right dislocated metric space and dislocated qua...In the present paper, we prove some fixed point theorems of Hegedus contraction in some types of distance spaces, dislocated metric space, left dislocated metric space, right dislocated metric space and dislocated quasi-metric metric space which are generalized metrics spaces where self-distances are not necessarily zero.展开更多
Various index structures have recently been proposed to facilitate high-dimensional KNN queries, among which the techniques of approximate vector presentation and one-dimensional (1D) transformation can break the curs...Various index structures have recently been proposed to facilitate high-dimensional KNN queries, among which the techniques of approximate vector presentation and one-dimensional (1D) transformation can break the curse of dimensionality. Based on the two techniques above, a novel high-dimensional index is proposed, called Bit-code and Distance based index (BD). BD is based on a special partitioning strategy which is optimized for high-dimensional data. By the definitions of bit code and transformation function, a high-dimensional vector can be first approximately represented and then transformed into a 1D vector, the key managed by a B+-tree. A new KNN search algorithm is also proposed that exploits the bit code and distance to prune the search space more effectively. Results of extensive experiments using both synthetic and real data demonstrated that BD out- performs the existing index structures for KNN search in high-dimensional spaces.展开更多
文摘Background: Pharmacists must adjust their distance from patients to facilitate communication during interviews and gain their trust. The distance between the patients and the pharmacists varies depending on many factors, such as gender, posture and the patients’ mood. Only a few of these papers have actually measured and validated distance with patients. In this study, we validated our method of assessing mood and measuring distance before beginning a survey with patients. Methods: We measured comfortable interpersonal distance among men and women using an ecological scenario, in which a pharmacist approaches the subject, and the subject is asked to stop the pharmacist at the distance he/she feel comfortable with. Five pharmacists and 33 subjects participated in the study. The Japanese version of the Brief Mood Questionnaire Checklists (BMC-J) was used to quantify the subject’s mood for the day, and then the distance from the pharmacist that the subjects considered comfortable was measured at the bedside. The relationship between the mood and distance obtained was examined. Results: The comfortable distance of subjects was influenced by gender, posture, and mood. The shortest distance was 94.7 ± 11.1 cm (mean ± SD), for the male subjects versus the female pharmacists in the sitting position. The distance of male subjects shorted when they had positive emotions and lengthened when they were worried. Female subjects maintained a long distance from both male and female pharmacists when they had positive emotions and a short distance when they were worried. Conclusion: Findings show that the distance changes depending on the subjects’ mood at the time of measurement. It was found that the present measurement method can be used to determine the psychological state of the patient and measure the comfort distance at that time, and can be used as a simple method to examine these relationships. Therefore, it is also considered a practical method for the next step, which is a clinical study on patients.
文摘We establish fixed point theorems in complete fuzzy metric space by using notion of altering distance, initiated by Khan et al. [Bull. Austral. Math. Soc. 30 (1984), 1-9]. Also, we find an affirmative answer in fuzzy metric space to the problem of Sastry [TamkangJ. Math., 31(3) (2000), 243-250].
基金Supported by the National Natural Science Foundation of China（11271293）
文摘Some common fixed point results for mappings satisfying a quasi-contractive condition which involves altering distance functions are obtained in partially ordered complete cone metric spaces. A sufficient condition for the uniqueness of common fixed point is proved. Also, an example is given to support our results.
文摘A class of pseudo distances is used to derive test statistics using transformed data or spacings for testing goodness-of-fit for parametric models. These statistics can be considered as density based statistics and expressible as simple functions of spacings. It is known that when the null hypothesis is simple, the statistics follow asymptotic normal distributions without unknown parameters. In this paper we emphasize results for the null composite hypothesis: the parameters can be estimated by a generalized spacing method (GSP) first which is equivalent to minimize a pseudo distance from the class which is considered;subsequently the estimated parameters are used to replace the parameters in the pseudo distance used for estimation;goodness-of-fit statistics for the composite hypothesis can be constructed and shown to have again an asymptotic normal distribution without unknown parameters. Since these statistics are related to a discrepancy measure, these tests can be shown to be consistent in general. Furthermore, due to the simplicity of these statistics and they come a no extra cost after fitting the model, they can be considered as alternative statistics to chi-square statistics which require a choice of intervals and statistics based on empirical distribution (EDF) using the original data with a complicated null distribution which might depend on the parametric family being considered and also might depend on the vector of true parameters but EDF tests might be more powerful against some specific models which are specified by the alternative hypothesis.
文摘Connes' distance formula is applied to endow linear metric to three 1D lattices of different topologies with a generalization of lattice Dirac operator written down by Dimakis et al.to contain a non-unitary link-variable.Geometric interpretation of this link-variable is lattice spacing and parallel transport.
文摘In the present paper, we prove some fixed point theorems of Hegedus contraction in some types of distance spaces, dislocated metric space, left dislocated metric space, right dislocated metric space and dislocated quasi-metric metric space which are generalized metrics spaces where self-distances are not necessarily zero.
基金Project (No. [2005]555) supported by the Hi-Tech Research and De-velopment Program (863) of China
文摘Various index structures have recently been proposed to facilitate high-dimensional KNN queries, among which the techniques of approximate vector presentation and one-dimensional (1D) transformation can break the curse of dimensionality. Based on the two techniques above, a novel high-dimensional index is proposed, called Bit-code and Distance based index (BD). BD is based on a special partitioning strategy which is optimized for high-dimensional data. By the definitions of bit code and transformation function, a high-dimensional vector can be first approximately represented and then transformed into a 1D vector, the key managed by a B+-tree. A new KNN search algorithm is also proposed that exploits the bit code and distance to prune the search space more effectively. Results of extensive experiments using both synthetic and real data demonstrated that BD out- performs the existing index structures for KNN search in high-dimensional spaces.
