Non-parametric Statistical Hypothesis Test Research Articles

Enhancement of photovoltaic array characteristics and global maximum power using Padovan transform‐based image encryption strategy

SummaryDuring shading, the mismatch between the panels in the photovoltaic (PV) array mitigates the global maximum power (GMP). Besides, the mismatch in the irradiation levels of distinct rows of the PV array instigates multiple power peaks (MPPs) in the array characteristics. Distinguishing the local and global peaks among MPPs for tracking the GMP is highly challenging for maximum power point tracking (MPPT) controllers. So, to mitigate the MPPs and enhance the GMP, array reconfiguration is preferred. Nevertheless, most existing reconfiguration techniques exhibit poor shade dispersal, distorted electrical characteristics, multiple MPPs, increased mismatch, scalability issues, etc. To overcome these challenges, this paper proposes a new Padovan transform‐based encryption strategy for array reconfiguration. The proposed method was evaluated for both symmetric and unsymmetrically sized arrays. Its performance has also been compared to that of 23 other strategies. The proposed reconfiguration strategy integrated with MPPT is validated experimentally using a prototype model. A nonparametric statistical hypothesis test with a p‐value of 0.05 has been used for a pairwise fair comparison study among the examined approaches. The proposed approach constantly outperforms the current methods because of its unique shade dispersion generated through intelligent reconfiguration offering the GMP improvement of 34.429%, 12.51%, 5.05%, and 37.40%, 22.93%, 16.51% for 9 × 9 and 4 × 8 PV arrays, respectively.

Effects of Content and Language Integrated Learning (CLIL) Training Program on Thai Pre-Service Teachers’ Knowledge of CLIL Approach, CLIL Material Design, and CLIL Teaching

The purpose of this study is to explore the effects of the Content and Language Integrated Learning (CLIL) training program on Thai pre-service teachers’ knowledge of CLIL approach, CLIL material design and CLIL teaching and their opinions toward the training program. A mix-method with a quasi-experimental study was employed in this research. The sample consisted of 14 pre-service Social Studies teachers from a university in Bangkok, Thailand. Data collection tools of the research included an achievement test, a questionnaire and an interview. A non-parametric statistical hypothesis test was used to assess quantitative data. Results revealed that the pre-service teachers’ knowledge of CLIL approach, CLIL material design and CLIL teaching improved with a statistically significant difference. The results also revealed that the pre-service teachers had favorable opinions toward the training program when it comes to training program, learning experiences, CLIL material design, and CLIL teaching. It was concluded that the CLIL training program could have a favorable effect on pre-service teachers. As a result, it was recommended that more CLIL programs be developed and provided to pre-service teachers.

Behavioral inference from non-stationary policies: Theory and application to ridehailing drivers during COVID-19 lockdowns

In the aftermath of a disruptive event like the onset of the COVID-19 pandemic, it is important for policymakers to quickly understand how people are changing their behavior and their goals in response to the event. Choice modeling is often applied to infer the relationship between preference and behavior, but it assumes that the underlying relationship is stationary: that decisions are drawn from the same model over time. However, when observed decisions outcomes are non-stationary in time because, for example, the agent is changing their behavioral policy over time, existing methods fail to recognize the intent behind these changes. To this end, we introduce a non-parametric sequentially-valid online statistical hypothesis test to identify entities in the urban environment that ride-sourcing drivers increasingly sought out or avoided over the initial months of the COVID-19 pandemic. We recover concrete and intuitive behavioral patterns across drivers to demonstrate that this procedure can be used to detect behavioral trends as they are emerging.

An effective optimization method for solving the relay coordination problem of the microgrids

In this work, an opposition-based learning-aggrandized class topper optimization (OBL-ACTO) algorithm is proposed to optimize the operating time of directional overcurrent relays (DOCRs) for an integrated microgrid power distribution network. The proposed OBL-ACTO algorithm is a hybridized method. In this method, an opposition-based learning (OBL) strategy is employed to tackle the local sticking problem of the traditional ACTO method and ameliorate its exploration and exploitation capability. The effectiveness of OBL-ACTO in solving the optimum coordination problem of (DOCRs) is tested on the IEC microgrid system and the 33kv distribution part of a standard IEEE 30-bus system. The proposed method along with the system is executed on the LabVIEW©2015 platform. The effectiveness of the developed method is shown based on the acquired optimal solution by comparing it with recently developed optimization methods for DOCRs problem. The proposed approach reduces the total operating time by 22.827 to 73.819 % to the compared methods. In addition, a non-parametric statistical hypothesis test is performed to show the proposed method’s significance based on the obtained simulation results.

Preservice Teachers’ Knowledge and Attitudes toward Digital-Game-Based Language Learning

There is a good body of literature about digital-game-based language learning (DGBL), but research has mainly focused on students as game players rather than as future educators. This paper reports on a research conducted among 154 teacher candidates at a higher-education institution in Spain regarding the adoption of digital games in education. It analyzes the participants’ knowledge of and attitudes toward digital games in foreign language learning. Quantitative and qualitative data were gathered through a pre/post-test, digital game presentations, and student blog posts. The research comprised five stages associated with critical thinking skills (definition, selection, demonstration, discussion, and reflection), including a game learning module. In the first two stages, preservice teachers completed the module activities and selected different games aimed at teaching English to children in preschool and elementary education. In the last two, they illustrated, discussed, and evaluated the digital games in class following a rubric and reflected on their perception in blog posts. In this four-week research based on a mixed method and convenience sampling, quantitative and qualitative data were gathered through a pre- and post-test survey about student perceptions toward the use of video game in the classroom, class discussion, and blog posts. Statistical data analysis unveiled gender-based differences related to gameplay frequency and genre preferences. The Wilcoxon signed-rank test was used as a nonparametric statistical hypothesis test to compare the two sets of scores resulting from the same participants, and it showed a significant difference (p ≤ 0.05) after the treatment in two of the five dimensions in the survey about teacher candidates’ attitudes toward game usage in education, namely, usefulness (U) and preference for video games (PVG). Research findings revealed preservice teachers’ positive attitudes but lack of practical knowledge about the use of digital games in foreign-language learning.

Optimal coordination of over-current relay in a power distribution network using opposition based learning fractional order class topper optimization (OBL-FOCTO) algorithm

For the appropriate service of the power system network, the protection system which is equipped with relays and circuit breakers must operate in proper and efficient manner. In the power protection system, relays act as the brain of the circuit breaker which sense the fault situation and send the command to trip the circuit breaker to isolate the faulty part for reliable operation of rest part of the power system network. The relay performance may be affected by the Plug Setting (PS) and Time Dial Setting (TDS) due to the complex distribution network. The performance of the relay operation can be improved by proper tuning of TDS and PS. Therefore, to optimize the PS and TDS and to improve the performance of relay operating time, an opposition based learning fractional order class topper optimization algorithm called (OBL-FOCTO) is presented. The proposed method is a modified version of classical Class Topper Optimization (CTO, in which an Opposition Based Learning (OBL) concept as well as Fractional Order (FO) updating concept is introduced to improve the explorative and exploitive properties. The exploitation, exploration and convergence behavior of OBL-FOCTO is validated using CEC-2020 benchmark functions. The performance of the proposed method is evaluated using six test systems like IEEE 3 Bus, IEEE 4 Bus and IEEE 30 Bus system respectively. The superiority of the proposed method is shown by comparing the obtained results with some other existing results obtained using some existing methods. The results of the presented method for the relay coordination problem shows that the total operating time of the relays is minimized ( taking 0.037 to 10.432 percent less operating time to perform the relay operation for different cases) while compared to existing results for all six test systems with maintaining coordinations between each relays and also fulfill other constraints. Further, a non-parametric statistical hypothesis test has been applied to all test systems of the simulation results to show their significance.

Influences of local hydroclimatology and teleconnections on Florida's precipitation and temperature variability

AbstractUnderstanding the influences of local hydroclimatology and two large‐scale oceanic‐atmospheric oscillations (i.e., Atlantic Multidecadal Oscillation (AMO) and El Niño‐Southern Oscillation (ENSO)) on seasonal precipitation (P) and temperature (T) relationships for a tropical region (i.e., Florida) is the focus of this study. The warm and cool phases of AMO and ENSO are initially identified using sea surface temperatures (SSTs). The associations of SSTs and regional minimum, maximum and average surface air temperatures (SATs) with precipitation are then evaluated. The seasonal variations in P‐SATs and P‐SSTs associations considering AMO and ENSO phases for sites in (1) two soil temperature regimes (i.e., thermic and hyperthermic); (2) urban and non‐urban regions; and (3) regions with and without water bodies, are analysed using two monthly datasets. The analyses are carried out using trend tests, two association measures, nonparametric and parametric statistical hypothesis tests and kernel density estimates. Decreasing (increasing) trend in precipitation (SATs) is noted in the recent multi‐decadal period (1985–2019) compared to the previous one (1950–1984) indicating a progression towards warmer and drier climatic conditions across Florida. Spatially and temporally non‐uniform variations in the associations of precipitation with SATs and SSTs are noted. Strong positive (weak negative) P–T associations are noted during the wet (dry) season for both AMO phases and El Niño, while significant (positive) P–T associations are observed across southern Florida during La Niña in the dry season. The seasonal influences are predominant in governing the P–T relationship over the regions with and without water bodies; however, considerable variations between El Niño and La Niña are noted during the dry season. The climate variability influences on P–T correlations for hyperthermic and thermic soil zones are found to be insignificant (significant) during the wet (dry) season. Nonparametric clustering is performed to identify the spatial clusters exhibiting homogeneous P–T relationships considering seasonal and climate variability influences.

Understanding Sleep in Pediatric Patients with Sickle Cell Disease Admitted for Vaso-Occlusive Pain Crisis through Objective Data

▪Introduction: Sickle cell disease (SCD) is an inherited red cell disorder that leads to sickling of red blood cells, anemia and vaso-occlusion. The most common reason for hospitalization and morbidity in children is pain due to vaso-occlusive crisis (VOC). Importantly, poor sleep quality can lead to increased pain the subsequent day and nocturnal pain leads to reduced deep sleep, both which can then modify pain sensitivity. Studies using sleep diaries have shown this cyclical relationship between sleep and pain. Frequent occurrences of restless sleep are therefore believed to contribute to an increased severity and intensity of pain episodes.There is very little data, however, looking at objective data such as vital signs to define sleep in patients with SCD admitted for VOC. We aimed to make comparisons between sleep hours and daytime hours for pain scores, patient controlled analgesia (PCA) usage and vital sign data in effort to better define and understand sleep in SCD.Methods: We performed a retrospective chart review for patients with SCD between January 1, 2014 and January 31, 2017. We included all patients admitted to the pediatric service, admitted for >48 hours for simple VOC, and placed on a PCA during admission. Patients with complications of acute chest syndrome, stroke or surgery were excluded. The primary aim was to describe sleep using objective data during sleep hours for patients with SCD admitted with pain. In this study, sleep was simply defined by time (12am-6am). Objective data included: PCA usage and nursing documentation such as vitals. Secondary aim was to examine potential differences during sleep to other 6-hour intervals of time for objective data. Differences within each patient were analyzed using Wilcoxon signed-rank test, a non-parametric statistical hypothesis test used for repeated measurements on the same sample to compare their population means.Results: We analyzed 50 patients that met criteria (46% female and 78% with HbSS). The median age was 14 (range 2-19) and median days of admission was 6 (range 4-11). Average length of stay was 6.3 days.We found each patient analyzed had extremely different patterns of pain scores, vitals, and PCA usage patterns at day and night during hospitalization for VOC. Mean and median values at night as compared to daytime hours for vitals (HR, systolic blood pressure - SBP, and diastolic blood pressure - DBP), PCA usage, and pain scores did not differ across all patients. In contrast, we did find most individual patient data revealed an increasing HR and blood pressure following admission, which then decreased prior to discharge.Interestingly, within patient analysis found significant differences between night hours and day hours. The number of PCA doses attempted and delivered were both significantly lower in sleep hours (z=-2.7, p=0.007 and z=-3.2, p=0.002). Vital signs indicated that SBP, DBP, and respiratory rate were all also significantly lower during sleep hours (see Table 1). We did not find differences between sleep and daytime hours for pain, HR and temperature.Conclusion: As expected, we found a large amount of variation across all patients for PCA usage and objective measures. Using a simple time definition of sleep, we also found no differences between night hours and daytime hours across all patients. However, while there were no statistically significant differences in vitals across the 50 patients between day and night, we found that the pain levels during their hospitalization to be highly individualized in nature.We found significant differences (at significance level of 0.05) between night hours and daytime hours within each patient. These included PCA usage, SBP, DBP, oxygen saturation, and respiratory rate. Although no differences were found in pain and HR, we did notice interesting trends during hospitalizations, including a gradual increase and eventual decrease in HR and blood pressure for many of the patients. This further highlights the need for clinical decisions and treatments to be tailored to individual patients based on their vitals and medication usage. We are optimistic to find significant differences in objective measures during sleep hours and aim to expand our analysis to determine potential prediction of sleep to subsequent day outcomes (pain and discharge) and definition of ‘good sleep’ by objective measures (such as low HR) using individual patient models. [Display omitted] DisclosuresJonassaint:Sicklesoft: Other: Owner. Shah:Novartis: Other: Speaker; Alexion: Other: Speaker.

Distance Learning in Greece during Covid-19 Pandemic

The purpose of this study is to investigate the reaction of Greeks to this new educational reality due to the Covid-19 outbreak. Since the first restrictive measures were implemented in March 2020in Greece, distance learning has become a dynamic part of people’s daily lives with the prospect of remain in gas such in the future. A total of N=170 students, parents, teachers, civil servants, private sector employees who were involved in the distance learning process either as instructors or as students in the period of Covid-19 pandemic in Greece, were selected with the use of snowball sampling. A questionnaire using demographic and satisfaction related variables was completed by the respondents, namely citizens across Greece, based on a Likert scale questionnaire which is a useful and multidimensional instrument, to assess satisfaction within the time frame from July 7, 2020 to October 20, 2020; the period when there occurred a loosening in the restrictive measures between the two lockdowns in Greece. It was investigated how the demographic factors, specifically gender, age, occupation, and place of residence, influence the attitude of the respondents towards synchronous and asynchronous distance learning as well as their intention to continue using online education services in the future after the lifting of the restrictive measures. Additionally, the customers’ preferences concerning the most enjoyable distance learning experience were examined, so that they will be available to the distance learning program designers. Descriptive statistical analysis and non-parametric statistical hypothesis tests were conducted in SPSS and R. Most of the respondents had not participated in online courses before the Covid-19 outbreak, 46 % did participate in e-learning courses before the Covid-19 lockdown while 54 % did not and 34.1% respondents prefer face-to-face learning, while 15.9% prefer e-learning. Also, 50% respondents prefer a combination of face-to-face learning and e-learning. Hypothesis tests showed that there are statistically significant differences between users’ preferences as well as regarding their demographic characteristics. Undergraduate and postgraduate university students continue to participate in online learning courses and are willing to invest financial resources and time in this new educational process (?2(4)=10.440, p=0.034), unlike high school students who prefer face-to-face learning (p=0.042). The present study will lead to practical implications, such as the formation of e-learning programs which aim for the best user experience and the best learning outcomes. Also, private educational organizations can include the results in the key elements to implementing a strategic marketing mix.

The Effectiveness of Science, Technology, Engineering, and Mathematics-Inquiry Learning for 15-16 Years Old Students Based on K-13 Indonesian Curriculum: The Impact on the Critical Thinking Skills

<p style="text-align:justify">Industrial revolution 4.0 is currently present in various countries, including Indonesia. Indonesia responded quickly through technological developments, especially education. The actions of the Indonesian government to deal with industrial 4.0 are contained in the 4C principle, one of which is Critical Thinking. The Science, Technology, Engineering, and Mathematics (STEM) learning approach has become an alternative in building critical thinking skills, especially in science learning. The purpose of this study is to quantitatively measure the impact of the STEM-inquiry model based on the K-13 Indonesian Curriculum towards critical thinking skills of 15-16 years old students. This study employed quasi-experimental with non-equivalent control group design at SMAN 1 (State Senior High School) Padang Cermin, Lampung, Indonesia. The research subjects consisted of 50 students. The critical thinking skill was measured through 10 items of an essay question on the momentum and impulse material. Based on the results of the non-parametric statistical hypothesis test Mann Whitney, the significance level of 0.004 was obtained (sig <0.05). The results of the hypothetical test showed that the student's critical thinking skills before and after using the STEM-based inquiry model were different. It can be concluded that the application of the STEM-based inquiry model was effective in increasing students' critical thinking skills.</p>

Contamination Assessment of Durum Wheat and Barley Irrigated with Treated Wastewater through Physiological and Biochemical Effects and Statistical Analyses

The present work focused on the impact of crop irrigation by treated wastewater (TWW) on soil fertility, in germination, and growth of two species of cereals (T. turgidum and H. vulgare). This investigation was conducted at the germination stage (controlled condition) and in pots containing a soil irrigated with wastewater in comparison with controlled soil. Germination rate, vigor index, seedling growth, total fresh mass, chlorophyll content, proline, ascorbate peroxidase (APX), guaiacol peroxidase (GPX), and catalase (CAT) activities were measured. Similar effects were shown on both species which emphasize the important role of antioxidant enzymes in the defense against oxidative stress induced by prolonged reuse of TWW. The disturbing effect of the reuse TWW on soil fertility, germination, and development of young plants (T. turgidum and H. vulgare) was linked to the presence of micropollutants in TWW. Data were analyzed by R language using a nonparametric statistical hypothesis test. These have caused the disorganization of many physiological mechanism targets, especially growth disorders observed under different abiotic stress conditions. In conclusion, high salt and heavy metal concentrations contained in the TWW are the major constraints related to the reuse of TWW. Hence, repetitive irrigation with this water can induce, at long term, soil contamination which can limit plant production and crop contamination.

Well-being and disease severity of multiple sclerosis patients following a physical activity program

Abstract Introduction: Multiple sclerosis (MS) is a chronic disease of the central nervous system that mainly affects young adults, promoting a great impact on functionality. Fatigue is a very common symptom, associated with multiple impairments in sensitivity, muscle activity, neuromotor control, balance, cognition and problem-solving ability. MS leads to strong functional restrictions, particularly in the context of daily living activities, as well as in patient participation. Objective: To understand the implications of a self-regulation program in the perception of well-being and mental health in MS patients. Methods: A set of exercises was implemented for use in daily activities, supported by different studies with MS patients. Patients were asked to classify the severity of their disease and to use the Mental Health Inventory (MHI-38), at the beginning (time A) and at the end (time B) of the self-regulation program. We used the Statistical Package for the Social Sciences (SPSS) version 25. A non-parametric statistical hypothesis test (Wilcoxon test) was used to analyze the variables. Results: The mean age was 44 years old, with patients between the ages of 20 and 58. 58.3% were women, 37.5% were currently married, 67% were retired and the mean level of education was 12.5 years. The correlation between the perception of disease severity and psychological well-being before the self-regulation program (r = 0.26, p < 0.05) and after the intervention (r = 0.37, p < 0.01) suggests a low to moderate correlation. Conclusion: The implementation of the self-regulatory model, through the promotion of physical activity in patients with MS, had a positive impact of clinical rehabilitation, well-being, and perception of disease severity of these people.

The effect of a maternal meal on fetal liver blood flow

IntroductionDuring the third trimester of development, the human fetus accumulates fat, an important energy reservoir during the early postnatal period. The fetal liver, perfused by the nutrient-rich and well-oxygenated blood coming directly from the placenta, is assumed to play a central role in these processes. Earlier studies have linked fetal liver blood flow with maternal nutritional status and response to the maternal oral glucose tolerance test. Our aim was to explore the effect of a regular maternal meal on fetal liver blood flow at two timepoints during the third trimester, representing the start and towards the end of the fetal fat accretion period. We also sought to explore the influence of prepregancy body mass index on how the maternal meal affects fetal liver blood flow.MethodsUsing ultrasound Doppler, we examined 108 healthy women with singleton pregnancies in gestational weeks 30 and 36. At each visit, the first examination was performed with the participant in a fasting state at 08.30 a.m., followed by a standard breakfast meal of approximately 400 kcal. The examination was repeated after 105 minutes. Umbilical vein and ductus venosus blood flow was estimated from diameter and blood flow velocity measurements. Fetal liver flow was calculated as umbilical vein flow minus ductus venosus flow, and change in liver blood flow as flow after minus before the meal. The total group was divided into a normal-weight group (prepregancy body mass index 18.5–25.0 kg/m2; n = 83) and an overweight group (prepregancy body mass index >25.0 kg/m2; n = 21). Four women with prepregancy body mass index <18.5 kg/m2 were excluded from these analyses. Non-parametric statistical hypothesis tests were used for group comparisons.ResultsFor the total group, we observed a significant increase in median (10th - 90th percentile) liver flow 28.9 (‒67.9–111.6) ml/min (p = 0.002) following the meal in week 36, but not in week 30, ‒2.63 (‒53.2–65.0) ml/min (p = 0.91). This result in turn yielded a statistically significant increase in delta liver flow from weeks 30 to 36 of 26.0 (‒107.1–146.6) ml/min (p = 0.008). The increase in postprandial liver flow was observed only in the normal-weight group in week 36. Accordingly, the delta liver flow values between the two weight groups were significantly different in week 36 (p = 0.006) but not in week 30 (p = 0.155). Among the normal-weight women, the increase in delta liver blood flow from weeks 30 to 36 was 39.3 (‒83.0–156.1) ml/min (p<0.001); in contrast, we observed no statistically significant change in the overweight group (‒44.5 (‒229.0–123.2) ml/min; p = 0.073). As a substitute for liver size, we divided the delta liver flow values by abdominal circumference and found no changes in the statistical significance results within or between the two weight groups.ConclusionIn our healthy study population, we observed a statistically significant difference in liver blood flow after maternal intake of a regular meal. This effect depended on gestational age and maternal prepregancy body mass index, but apparently was independent of liver size, based on abdominal circumference as a proxy measure.

Cellular processing algorithm for the vertex bisection problem: Detailed analysis and new component design

The vertex bisection problem splits a graph G=(V,E) into two sets, L⊆V,|L|=⌊|V|/2⌋ and R=V∖L, such that it minimizes the number of vertices in L connected to R. This problem is a combinatorial NP-hard problem with relevant applications in network communications and, currently, there is only one metaheuristic method that solves it. In this paper, we propose a Cellular Processing Algorithm (CPA) that outperforms the state of the art showing a detailed description of its components and assessing the impact of its main components. Additionally, we include the best-known solutions for the new benchmark of 137 challenging instances. The experimental study, with the new benchmark, shows that the CPA increases the number of best solutions found to 190% and decreases the time to 21% with respect to an efficiency-improved version of the state of the art algorithm. Finally, a non-parametric statistical hypothesis test confirms that the CPA outperforms statistically the efficiency-improved implementation of the state of the art algorithm.

Improved IIR-type fractional order digital integrators using cat swarm optimization

Design of wideband infinite impulse response (IIR) digital fractional order integrators (DFOIs) based on a bio-inspired metaheuristic optimization approach called the cat swarm optimization (CSO) algorithm is presented in this paper. To investigate the efficiency of the proposed approach, the CSO-based DFOIs are evaluated against those of the approximations designed using real-coded genetic algorithm (RGA), standard particle swarm optimization (PSO), and differential evolution (DE) by different magnitude and phase response error metrics. Simulation results reveal the better frequency response of the CSO-based DFOIs in comparison with the competing designs. Both parametric and nonparametric statistical hypothesis tests validate the performance consistency of CSO. Comparisons with the cited literature confirm the efficacy of the proposed models.

Content- and Language-Integrated Learning Based Strategies for the Professional Development of Early Childhood Education Pre-Service Teachers

This research article presents the results of an exploratory study that was conducted with a group of 14 early childhood education pre-service teachers at a private Colombian university. It intended to determine: 1) the amount of metalanguage expressions used for teaching English as a foreign language (EFL) and foreign language (FL) content; 2) the number of concepts related to the teaching of EFL and FL content pre-service teachers were able to learn in a 7-session (14 face-to-face hours) course based on a methodology inspired by the content and language integrated learning (CLIL) approach, using songs, rhymes, and poems in English; 3) the degree of difficulty pre-service teachers perceived about teaching English and English content to young children. This quasi-experimental study was performed with pre- and post-study tests given to one group, analyzing quantitative data through a non-parametric statistical hypothesis test and a non-parametric measure of rank correlation. Pre-service teachers were found to successfully learn vocabulary and concepts, but their perceptions about the degree of difficulty of teaching EFL and FL content remained basically the same as prior to the course. In addition, the correlation between the participants’ level of English and their learning process was analyzed, as well as the correlation between English proficiency level and perception of the degree of difficulty of teaching EFL and FL content. The results show a strong correlation in the first case, but no correlation for the second one.

Assessment of the Robustness of a Fixtureless Inspection Method for Nonrigid Parts Based on a Verification and Validation Approach

The increasing practical use of computer-aided inspection (CAI) methods requires assessment of their robustness in different contexts. This can be done by quantitatively comparing estimated CAI results with actual measurements. The objective is comparing the magnitude and dimensions of defects as estimated by CAI with those of the nominal defects. This assessment is referred to as setting up a validation metric. In this work, a new validation metric is proposed in the case of a fixtureless inspection method for nonrigid parts. It is based on using a nonparametric statistical hypothesis test, namely the Kolmogorov–Smirnov (K–S) test. This metric is applied to an automatic fixtureless CAI method for nonrigid parts developed by our team. This fixtureless CAI method is based on calculating and filtering sample points that are used in a finite element nonrigid registration (FENR). Robustness of our CAI method is validated for the assessment of maximum amplitude, area, and distance distribution of defects. Typical parts from the aerospace industry are used for this validation and various levels of synthetic measurement noise are added to the scanned point cloud of these parts to assess the effect of noise on inspection results.

Soil characteristics in the floodplains of Munawar Tawi in Rajouri, Western Himalayas, India

BackgroundIn Himalayas, particularly Jammu and Kashmir, where 85% of people depend on agriculture and allied sectors, 70% of agriculture is rain-fed. While the Himalayas, highly seismic, contribute highest in sediment transported to the world oceans, surface soil is under threat due to erosion, and Rajouri district in western Himalayas is no exception. Various factors, especially land use pattern and climate change, further affect the soil fertility and nutrient contents. However, information on essential nutrients in the soil across the region is meager.MethodsWe examined soil texture, soil type, lime status, pH, EC and select nutrients in January (non-cropping season) and June (cropping season) in paddy/wheat fields in Rajouri town, and its upstream and downstream locations. We also examined area under major crops, yield and fertilizer inputs from 2000 to 2012.ResultsWilcoxon signed-rank test, a non-parametric statistical hypothesis test used when comparing two related samples, showed that pH, EC, K, Zn, Fe and Mn are higher in January than in June while OC, N, P, Na, Mg, Ca and Cu are vice versa. Kruskal–Wallis test, another non-parametric statistical hypothesis test used when comparing more than two related samples, showed nutrients varying significantly from upstream to downstream in both the seasons. Area and yield under rice, wheat and maize cultivation during 2000–2012 did not show any significant change. During the period, while significant increase in N and P input was seen, micronutrients remain neglected. Correlation matrix shows significant relation among the nutrients in January and June. In the case of rice, the yield was significantly positively correlated with area under cultivation, but in the case of wheat, the yield was negatively correlated with the area.ConclusionsThe study presents baseline information on soil characteristics across seasons and locations in Rajouri. It highlights the inadequacy of the official database and need for generating accurate data on crops and yields that are more authentic.

Optimal design of IIR digital FOI using IPSO

ABSTRACTThis paper presents an efficient approach to design digital Fractional-Order Integrators (FOIs) exhibiting an accurate magnitude response by employing a metaheuristic algorithm called Improved Particle Swarm Optimisation (IPSO). The proposed infinite impulse response (IIR) filter type IPSO-based digital FOIs have been judged against the Real-coded Genetic Algorithm, Particle Swarm Optimisation (PSO), and Differential Evolution -based digital FOIs with respect to various performance metrics. The superior performance of the IPSO-based designs is also emphasised using different statistical indices. Parametric and non-parametric statistical hypothesis tests demonstrate the reliable performance of IPSO-based designs. MATLAB simulation results confirm the accurate magnitude response of the proposed digital FOIs as compared with the published literature.

Enhanced colliding bodies optimisation-based optimal design of wideband digital integrators and differentiators

This paper presents an efficient approach to determine the optimal set of coefficients for the design of wideband infinite impulse response (IIR) digital integrators (DIs) and digital differentiators (DDs) of first, second, third, and fourth order, meeting the accurate magnitude response specification, using a recently proposed evolutionary optimisation algorithm called enhanced colliding bodies optimisation (ECBO). To demonstrate the effectiveness of the proposed approach, the results of the ECBO-based designs have been compared with those of eight other nature-inspired metaheuristic optimisation algorithms. Parametric and non-parametric statistical hypothesis tests are conducted to validate the consistency of the performance of the ECBO-based DIs and DDs. Simulation results demonstrate that ECBO-based designs achieve the least absolute magnitude error and demonstrate a competitive group delay response of the designed DIs and DDs of different orders as compared with the designs based on the competing algorithms. The proposed DIs and DDs also outperform those of the design approaches published in literature and achieve the best responses in terms of the maximum absolute magnitude error over a wide frequency range.