An algorithm for pulsed activation of solenoid valves for variable rate application of agricultural chemicals

An alternative algorithm to Pulse Width Modulation (PWM) for pulsed activation of solenoid valves for applying chemicals through agricultural sprayer nozzles is presented. Solenoid valves attached to individual spray nozzles on a modified EMDEK tractor-mounted sprayer system are activated by electronic pulsation to vary the application rate of agricultural chemicals, varying the output by location according to Geographical Information System (GIS) data and a GPS system. A potential advantage of this alternative algorithm over pulse width modulation based systems is the use of lower-cost industrial solenoid valves with slower opening and closing times instead of the more expensive high speed valves normally used in PWM systems

Modification of a commercial PWM sprayer control system for precision farming application

The control system of a commercial sprayer was modified for variable–rate control of 12 individual solenoid shut off valves spaced 0.5 m apart on a sprayer boom. The variable-rate control system consisted of pulse width modulation (PWM) solenoids, a by pass control valve, and nozzle control system interfaced to a computer. An algorithm was developed to vary application rate across the booms with computing the best possible combinations of pulse width at the optimal boom through the computer control program for nozzles. This algorithm compensates inaccuracy of applying desired application rate due to pressure fluctuations across the booms

TraVaS: Differentially Private Trace Variant Selection for Process Mining

In the area of industrial process mining, privacy-preserving event data publication is becoming increasingly relevant. Consequently, the trade-off between high data utility and quantifiable privacy poses new challenges. State-of-the-art research mainly focuses on differentially private trace variant construction based on prefix expansion methods. However, these algorithms face several practical limitations such as high computational complexity, introducing fake variants, removing frequent variants, and a bounded variant length. In this paper, we introduce a new approach for direct differentially private trace variant release which uses anonymized \textit{partition selection} strategies to overcome the aforementioned restraints. Experimental results on real-life event data show that our algorithm outperforms state-of-the-art methods in terms of both plain data utility and result utility preservation

The relationship between body mass index and preeclampsia: A systematic review and meta-analysis

Background: One of the causes of maternal and fetal mortality and morbidity is pregnancy-induced hypertension, the most common form of which is preeclampsia that causes many complications for mother and fetus. Objective: The aim of this systematic review and meta-analysis was to determine the relationship between body mass index (BMI) and preeclampsia in Iran. Materials and Methods: Using valid keywords in the SID database, PubMed, Scopus, data obtained from all the articles, which were reviewed in Iran between 2000 and 2016, were combined using the meta-analysis method (random-effects model) and analyzed using STATA version 11.1. Results: A total number of 5,946 samples were enrolled in 16 studies with the mean BMI values of 25.13, 27.42, and 26.33 kg /m2 in the healthy, mild, and severe preeclamptic groups, respectively. Conclusion: The results of this study revealed that there is a significant relationship between BMI and the risk of preeclampsia, so it can be said that BMI may be one of the ways to diagnose preeclampsia

Interactive Process Identification and Selection from SAP ERP

SAP ERP is one of the most popular information systems supporting various organizational processes, e.g., O2C and P2P. However, the amount of processes and data contained in SAP ERP is enormous. Thus, the identification of the processes that are contained in a specific SAP instance, and the creation of a list of related tables is a significant challenge. Eventually, one needs to extract an event log for process mining purposes from SAP ERP. This demo paper shows the tool Interactive SAP Explorer that tackles the process identification and selection problem by encoding the relational structure of SAP ERP in a labeled property graph. Our approach allows asking complex process-related queries along with advanced representations of the relational structure

TraVaG: Differentially Private Trace Variant Generation Using GANs

Process mining is rapidly growing in the industry. Consequently, privacy concerns regarding sensitive and private information included in event data, used by process mining algorithms, are becoming increasingly relevant. State-of-the-art research mainly focuses on providing privacy guarantees, e.g., differential privacy, for trace variants that are used by the main process mining techniques, e.g., process discovery. However, privacy preservation techniques for releasing trace variants still do not fulfill all the requirements of industry-scale usage. Moreover, providing privacy guarantees when there exists a high rate of infrequent trace variants is still a challenge. In this paper, we introduce TraVaG as a new approach for releasing differentially private trace variants based on \text{Generative Adversarial Networks} (GANs) that provides industry-scale benefits and enhances the level of privacy guarantees when there exists a high ratio of infrequent variants. Moreover, TraVaG overcomes shortcomings of conventional privacy preservation techniques such as bounding the length of variants and introducing fake variants. Experimental results on real-life event data show that our approach outperforms state-of-the-art techniques in terms of privacy guarantees, plain data utility preservation, and result utility preservation

Prevalence of Anaerobic Bacteria (P.gingivalis) as Major Microbial Agent in the Incidence Periodontal Diseases by Meta-analysis

Statement of the Problem: Periodontal diseases are complex oral diseases characterized by bacterial-induced inflammatory destruction of tooth-supporting tissues. Porphyromonas gingivalis (P. gingivalis) is a common gram-negative anaerobic oral bacteria strongly associated with periodontal disease. Purpose: The present study was conducted to estimate prevalence of P. gingivalis in patients with periodontal diseases by using meta-analysis method. Martials and Method: Different databases including PubMed, EmBase, Scopus, the Institute for Scientific Information (ISI) Web of Science, and the Cochrane Library were searched to identify original English-language studies addressing prevalence of P. gingivalis in periodontal diseases up to December 2014. The random effects model was applied in the meta-analysis and the heterogeneity between studies was assessed using a Cochran test and the I2 index. Funnel plots and Egger test were used to examine publication bias. Statistical analyses were performed using STATA version 12. Results: Forty-two eligible studies published during 1993- 2016 were selected for meta-analysis. Considering all the included studies, the total sample size was 5,884 individuals containing 2,576 healthy people with a mean age of 37.21±7.45 years and 3,308 periodontal patients with a mean age of 44.16±8.35 years. Overall, the prevalence of P. gingivalis was 78% [95% CI: 74-81] in periodontal diseases group and 34% [95% CI: 26-41] in healthy individuals. There was a significantly higher prevalence of P.gingivalis in individuals with periodontal diseases compared to healthy subjects [78% versus 34%, respectively]. Conclusion: This study indicates that P. gingivalis is highly present in subjects with periodontal diseases and it also appears in periodontally healthy people, although to a lesser extent. Thus, the presence of P. gingivalis increases the chance of periodontal disease and it can be considered as a main potential risk factor