The Zulliger Test (or Z-Test) is a projective technique elaborated by Hans Zulliger (1893-1965), both in the individual form and in the collective form. It is a psychodiagnostic instrument that, as ...the most famous Rorschach Test, is based on the ink spots method (or “ink-blot”), and that invites the subject to interpret symmetrical and little structured spots. Initially, it was created in the slides version for the selection of soldiers of Swiss army and successively proposed as planks for the individual administration. The following article proposes to evidence the usefulness of individual form of Z-Test in the appraisal of psychical operation, both normal and pathological. A review of the literature is lead carrying out searches of articles and witnesses through search engines PubMed, ResearchGate, Google Scholar, APA following PsycNET® by the keywords: “Zulliger test”, “Hans Zulliger”, “projective test”. Found the usefullness of Z-Test in individual form for the appraisal of psychical operation, the necessity of a study is evidenced for the definition of the normative champion of the Italian adult normal population.
Summary
Wireless sensor networks (WSNs) are one of the nonnegligible ingredients in any Internet of Things (IoT)‐based system. Fault tolerance in the IoT‐enabled WSNs is an essential part of avoiding ...harmful actions. Many approaches are reported in the literature on fault detection and fault tolerance for WSNs. However, they either consume additional energy to identify and tolerate failures or use extra hardware and software resources. This paper proposes an intelligent fault tolerance routing scheme for IoT‐enabled WSNs that significantly improves the QoS of the IoT‐enabled WSNs. We propose a novel two‐population z‐test‐based fault detection mechanism to detect faulty nodes in the networks. Furthermore, an intelligent routing scheme is proposed that reuses different partially faulty nodes to tolerate faults within the network. An extensive experiment on the proposed intelligent fault tolerance routing scheme is performed to demonstrate the efficiency of the proposed scheme. Experiment results are compared with the state‐of‐the‐art algorithms to show the effectiveness of the proposed scheme in terms of false‐positive rate, false alarm rate, fault detection accuracy, energy consumption, fault detection accuracy, and network lifetime.
This paper proposes an intelligent fault tolerance routing scheme for IoT‐enabled WSNs that significantly improves the QoS of the IoT‐enabled WSNs. Furthermore, an intelligent routing scheme is proposed that reuses different partially faulty nodes to tolerate faults within the network. Experiment results are compared with the state‐of‐the‐art algorithms to show the effectiveness of the proposed scheme in terms of false‐positive rate, false alarm rate, fault detection accuracy, energy consumption, fault detection accuracy, and network lifetime.
Positive and negative signatures of the ionospheric storms caused by the penetration electric field, disturbance dynamo, neutral wind, neutral composition, etc., have been reported. In this paper, ...the ionospheric total electron content (TEC) derived from the records of a network of ground‐based GPS receivers in Taiwan is used to statistically study the characteristics such as local time of appearance and duration of the storm signatures of various casuals in the equatorial ionization anomaly (EIA) region during 1994–2003. A bias‐corrected accelerated bootstrap method and a z test are employed for the first time to detect each event, and the overall storm signatures and characteristics, respectively. It is found that the positive signatures that appeared minutes to hours after the geomagnetic storm onset are pronounced on the storm day and the next day, while the negative signatures that started hours after the geomagnetic storm onset can last for as long as the next 4 days. The positive signature is statistically significant and most pronounced, when the intense geomagnetic storm onset occurs during local afternoon, which suggests that the signature may result from a combination of the prompt penetration electric field effect and mechanical effects of equatorward neutral wind. Additionally, the negative signature that is statistically significant and most pronounced in the local afternoon of the storm‐onset day and/or the next day may be produced by the disturbance dynamo or overshielding effects. The long‐lasting negative signature occurred in local midnight‐noon period on days 2–4 after the storm onset may result from the neutral composition disturbances.
Key Points
Statistical studies of the duration of ionospheric storms
Discriminate ionospheric storm effects
A bias‐corrected accelerated bootstrap method and a z test analyses
Recently, vehicle-to-vehicle (V2V) based localization has attracted much attention due to its potential to achieve high accuracy. However, the error caused by non-line-of-sight (NLOS) propagation ...significantly affects the localization performance. In this paper, a novel method combining V2V communication and NLOS identification is proposed to improve accuracy of vehicle localization in NLOS scenarios. First, the algorithm identifies NLOS links with statistical methods. In this step, identification is conducted by decision theory or z-test, which depends on whether priori NLOS information is known or not. After that, NLOS links are discarded. Using the information including length of remaining links and GPS positions of surrounding vehicles, the estimated positions of target vehicles can be obtained by multilateration. It is shown by simulations that the proposed algorithm outperforms several classical methods in accuracy. Specifically, when priori NLOS information is available, 80% of vehicles have a localization error less than 5 m. For the case where NLOS information cannot be obtained, the algorithm still have good performance, and the ratio of vehicles having error within 5 m reaches 70%.
Through simulation, Whitlock showed that when all the alternatives have the same effect size, the weighted z-test is superior to both unweighted z-test and Fisher's method when combining P-values ...from independent studies. In this paper, we show that under the same situation, the generalized Fisher method due to Lancaster outperforms the weighted z-test.
This study compares the unidimensional and multidimensional measures of involvement by examining their predictive validity on satisfaction and loyalty. By adopting the three-step approach comparing ...correlated correlations of non-nested models involving Steiger's Z test, this study found that the multidimensional measure of involvement predicted satisfaction and loyalty better than the unidimensional measure within the same data. Therefore, tourism researchers are suggested to adopt the multidimensional measure of involvement to maximize the predictive power of these two constructs. Attention also needs to be paid to its specific dimension. The dimension of attraction had the highest predictability for both satisfaction and loyalty, followed by social identity for satisfaction and social identity and social for loyalty. Hence, with limited resources, is suggested that these dimensions be used.
Multi-regional clinical trial (MRCT) has become an increasing trend for its supporting simultaneous global drug development. After MRCT, consistency assessment needs to be conducted to evaluate ...regional efficacy. The weighted Z-test approach is a common consistency assessment approach in which the weighting parameter
does not have a good practical significance; the discounting factor approach improved from the weighted Z-test approach by converting the estimation of
in original weighted Z-test approach to the estimation of discounting factor
. However, the discounting factor approach is an approach of frequency statistics, in which
was fixed as a certain value; the variation of
was not considered, which may lead to un-reasonable results. In this paper, we proposed a Bayesian approach based on
to evaluate the treatment effect for the target region in MRCT, in which the variation of
was considered. Specifically, we first took
random instead of fixed as a certain value and specified a beta distribution for it. According to the results of simulation, we further adjusted the Bayesian approach. The application of the proposed approach was illustrated by Markov Chain Monte Carlo simulation.
•Belt use averaged 80% among out-of-state drivers and 74% among in-state drivers.•Out-of-state drivers were 5% more likely than in-state drivers to use seatbelts.•Out-of-state drivers showed higher ...seatbelt compliance rate in primary law states.•Encouraging seatbelt use always could greatly reduce traffic injuries.
Introduction: This study explored the seatbelt use among in-state and out-of-state drivers in relation to their personal (age, gender, license status, etc.) and crash characteristics (time, location, roadway factors, etc.) using crash data over a 10-year period (2010–2019) from the Fatality Analysis Reporting System (FARS). Method: Comparison of seatbelt use between the two groups (in-state vs. out-of-state drivers) were conducted using Z-test statistics. Logistic regression models were developed to examine the probability of seatbelt use among each group. Results: New findings in this study showed that out-of-state drivers were 5% more likely than in-state drivers to use seatbelts. Regardless of the driver’s age, gender, license status, vehicle type, and injury severity, seatbelt use was significantly higher among out-of-state drivers. Moreover, irrespective of the location (rural or urban), the season (time, day, or month), road type (arterial, local streets, etc.), and jurisdictional seatbelt law (primary or secondary), out-of-state drivers were more seatbelt compliant than in-state drivers. Finally, out-of-state drivers traveling from states with secondary/no seatbelt laws exhibited higher seatbelt compliance rate in primary seatbelt law states than in states with less strict laws (i.e., secondary/no law). Practical Applications: The findings in this study are critical to addressing a myriad of policy questions related to seatbelt laws and seatbelt use. Future research should focus on the disparity in seatbelt use between the two groups and determine intervention strategies that are effective at promoting seatbelt use across the United States. Additionally, given the significant differences in driver seatbelt use behavior based on the type of seatbelt law, if states with less strict laws upgrade to primary seatbelt laws, there likely will be increases in seatbelt compliance in those states.
Traditional Z-test methods during noninvasive prenatal screens (NIPS) use the fixed parameter of standard deviation (SD), which ignores the influence of actual sequencing read counts of a sample on ...the results. The aim of this study is to eliminate the influence of the sequencing depth of individual samples on the results and enhance the power of NIPS.
In this study, we propose an improved NIPS method, which calculates the SD in the Z-score process adaptively according to the actual read count of the test sample. Our approach obtained the SD linear fitting function along with the read count with a large number of reference samples, in which SD and read count fit well. The effectiveness of our enhanced NIPS method was evaluated on three common trisomy syndromes and five recurrent CNV syndromes with 3219 and 6592 samples based on whole genome sequencing of maternal peripheral blood.
A total of 3,219 pregnant samples have been used for validating the proposed method on detecting fetal trisomy syndromes (T13, T18, and T21), in which eight false negative (FN) samples have been corrected as true positive (TP) and eight false positive (FP) samples have been fixed as true negative (TN) with our proposed adaptive-SD method. Another 6592 samples were used to compare the two methods on detecting five recurrent fetal copy number variation (CNV) syndromes, in which the FP samples have decreased from 99 to 39.
Our adaptive-SD NIPS method shows more power on detecting both trisomy syndromes and five recurrent CNVs in the pregnant samples with diverse read counts. Besides, our proposed method contributes to lower FP and FN samples than the traditional Z-test method in NIPS. Our results show that our enhanced NIPS methods are effective in detecting both abnormal fetal trisomy syndromes and recurrent CNV syndromes in pregnant women.
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